WorldWideScience

Sample records for neuromorphic sensory systems

  1. Neuromorphic sensory systems.

    Science.gov (United States)

    Liu, Shih-Chii; Delbruck, Tobi

    2010-06-01

    Biology provides examples of efficient machines which greatly outperform conventional technology. Designers in neuromorphic engineering aim to construct electronic systems with the same efficient style of computation. This task requires a melding of novel engineering principles with knowledge gleaned from neuroscience. We discuss recent progress in realizing neuromorphic sensory systems which mimic the biological retina and cochlea, and subsequent sensor processing. The main trends are the increasing number of sensors and sensory systems that communicate through asynchronous digital signals analogous to neural spikes; the improved performance and usability of these sensors; and novel sensory processing methods which capitalize on the timing of spikes from these sensors. Experiments using these sensors can impact how we think the brain processes sensory information. 2010 Elsevier Ltd. All rights reserved.

  2. Towards a neuromorphic vestibular system.

    Science.gov (United States)

    Corradi, Federico; Zambrano, Davide; Raglianti, Marco; Passetti, Giovanni; Laschi, Cecilia; Indiveri, Giacomo

    2014-10-01

    The vestibular system plays a crucial role in the sense of balance and spatial orientation in mammals. It is a sensory system that detects both rotational and translational motion of the head, via its semicircular canals and otoliths respectively. In this work, we propose a real-time hardware model of an artificial vestibular system, implemented using a custom neuromorphic Very Large Scale Integration (VLSI) multi-neuron chip interfaced to a commercial Inertial Measurement Unit (IMU). The artificial vestibular system is realized with spiking neurons that reproduce the responses of biological hair cells present in the real semicircular canals and otholitic organs. We demonstrate the real-time performance of the hybrid analog-digital system and characterize its response properties, presenting measurements of a successful encoding of angular velocities as well as linear accelerations. As an application, we realized a novel implementation of a recurrent integrator network capable of keeping track of the current angular position. The experimental results provided validate the hardware implementation via comparisons with a detailed computational neuroscience model. In addition to being an ideal tool for developing bio-inspired robotic technologies, this work provides a basis for developing a complete low-power neuromorphic vestibular system which integrates the hardware model of the neural signal processing pathway described with custom bio-mimetic gyroscopic sensors, exploiting neuromorphic principles in both mechanical and electronic aspects.

  3. Neural Mechanisms of Cortical Motion Computation Based on a Neuromorphic Sensory System

    Science.gov (United States)

    Abdul-Kreem, Luma Issa; Neumann, Heiko

    2015-01-01

    The visual cortex analyzes motion information along hierarchically arranged visual areas that interact through bidirectional interconnections. This work suggests a bio-inspired visual model focusing on the interactions of the cortical areas in which a new mechanism of feedforward and feedback processing are introduced. The model uses a neuromorphic vision sensor (silicon retina) that simulates the spike-generation functionality of the biological retina. Our model takes into account two main model visual areas, namely V1 and MT, with different feature selectivities. The initial motion is estimated in model area V1 using spatiotemporal filters to locally detect the direction of motion. Here, we adapt the filtering scheme originally suggested by Adelson and Bergen to make it consistent with the spike representation of the DVS. The responses of area V1 are weighted and pooled by area MT cells which are selective to different velocities, i.e. direction and speed. Such feature selectivity is here derived from compositions of activities in the spatio-temporal domain and integrating over larger space-time regions (receptive fields). In order to account for the bidirectional coupling of cortical areas we match properties of the feature selectivity in both areas for feedback processing. For such linkage we integrate the responses over different speeds along a particular preferred direction. Normalization of activities is carried out over the spatial as well as the feature domains to balance the activities of individual neurons in model areas V1 and MT. Our model was tested using different stimuli that moved in different directions. The results reveal that the error margin between the estimated motion and synthetic ground truth is decreased in area MT comparing with the initial estimation of area V1. In addition, the modulated V1 cell activations shows an enhancement of the initial motion estimation that is steered by feedback signals from MT cells. PMID:26554589

  4. Neural Mechanisms of Cortical Motion Computation Based on a Neuromorphic Sensory System.

    Directory of Open Access Journals (Sweden)

    Luma Issa Abdul-Kreem

    Full Text Available The visual cortex analyzes motion information along hierarchically arranged visual areas that interact through bidirectional interconnections. This work suggests a bio-inspired visual model focusing on the interactions of the cortical areas in which a new mechanism of feedforward and feedback processing are introduced. The model uses a neuromorphic vision sensor (silicon retina that simulates the spike-generation functionality of the biological retina. Our model takes into account two main model visual areas, namely V1 and MT, with different feature selectivities. The initial motion is estimated in model area V1 using spatiotemporal filters to locally detect the direction of motion. Here, we adapt the filtering scheme originally suggested by Adelson and Bergen to make it consistent with the spike representation of the DVS. The responses of area V1 are weighted and pooled by area MT cells which are selective to different velocities, i.e. direction and speed. Such feature selectivity is here derived from compositions of activities in the spatio-temporal domain and integrating over larger space-time regions (receptive fields. In order to account for the bidirectional coupling of cortical areas we match properties of the feature selectivity in both areas for feedback processing. For such linkage we integrate the responses over different speeds along a particular preferred direction. Normalization of activities is carried out over the spatial as well as the feature domains to balance the activities of individual neurons in model areas V1 and MT. Our model was tested using different stimuli that moved in different directions. The results reveal that the error margin between the estimated motion and synthetic ground truth is decreased in area MT comparing with the initial estimation of area V1. In addition, the modulated V1 cell activations shows an enhancement of the initial motion estimation that is steered by feedback signals from MT cells.

  5. Flexible Sensory Platform Based on Oxide-based Neuromorphic Transistors.

    Science.gov (United States)

    Liu, Ning; Zhu, Li Qiang; Feng, Ping; Wan, Chang Jin; Liu, Yang Hui; Shi, Yi; Wan, Qing

    2015-12-11

    Inspired by the dendritic integration and spiking operation of a biological neuron, flexible oxide-based neuromorphic transistors with multiple input gates are fabricated on flexible plastic substrates for pH sensor applications. When such device is operated in a quasi-static dual-gate synergic sensing mode, it shows a high pH sensitivity of ~105 mV/pH. Our results also demonstrate that single-spike dynamic mode can remarkably improve pH sensitivity and reduce response/recover time and power consumption. Moreover, we find that an appropriate negative bias applied on the sensing gate electrode can further enhance the pH sensitivity and reduce the power consumption. Our flexible neuromorphic transistors provide a new-concept sensory platform for biochemical detection with high sensitivity, rapid response and ultralow power consumption.

  6. Flexible Sensory Platform Based on Oxide-based Neuromorphic Transistors

    Science.gov (United States)

    Liu, Ning; Zhu, Li Qiang; Feng, Ping; Wan, Chang Jin; Liu, Yang Hui; Shi, Yi; Wan, Qing

    2015-01-01

    Inspired by the dendritic integration and spiking operation of a biological neuron, flexible oxide-based neuromorphic transistors with multiple input gates are fabricated on flexible plastic substrates for pH sensor applications. When such device is operated in a quasi-static dual-gate synergic sensing mode, it shows a high pH sensitivity of ~105 mV/pH. Our results also demonstrate that single-spike dynamic mode can remarkably improve pH sensitivity and reduce response/recover time and power consumption. Moreover, we find that an appropriate negative bias applied on the sensing gate electrode can further enhance the pH sensitivity and reduce the power consumption. Our flexible neuromorphic transistors provide a new-concept sensory platform for biochemical detection with high sensitivity, rapid response and ultralow power consumption. PMID:26656113

  7. Network-driven design principles for neuromorphic systems

    OpenAIRE

    Partzsch, Johannes; Sch?ffny, Rene

    2015-01-01

    Synaptic connectivity is typically the most resource-demanding part of neuromorphic systems. Commonly, the architecture of these systems is chosen mainly on technical considerations. As a consequence, the potential for optimization arising from the inherent constraints of connectivity models is left unused. In this article, we develop an alternative, network-driven approach to neuromorphic architecture design. We describe methods to analyse performance of existing neuromorphic architectures i...

  8. Neuromorphic cognitive systems a learning and memory centered approach

    CERN Document Server

    Yu, Qiang; Hu, Jun; Tan Chen, Kay

    2017-01-01

    This book presents neuromorphic cognitive systems from a learning and memory-centered perspective. It illustrates how to build a system network of neurons to perform spike-based information processing, computing, and high-level cognitive tasks. It is beneficial to a wide spectrum of readers, including undergraduate and postgraduate students and researchers who are interested in neuromorphic computing and neuromorphic engineering, as well as engineers and professionals in industry who are involved in the design and applications of neuromorphic cognitive systems, neuromorphic sensors and processors, and cognitive robotics. The book formulates a systematic framework, from the basic mathematical and computational methods in spike-based neural encoding, learning in both single and multi-layered networks, to a near cognitive level composed of memory and cognition. Since the mechanisms for integrating spiking neurons integrate to formulate cognitive functions as in the brain are little understood, studies of neuromo...

  9. Systematic configuration and automatic tuning of neuromorphic systems

    OpenAIRE

    Sheik Sadique; Stefanini Fabio; Neftci Emre; Chicca Elisabetta; Indiveri Giacomo

    2011-01-01

    In the past recent years several research groups have proposed neuromorphic Very Large Scale Integration (VLSI) devices that implement event-based sensors or biophysically realistic networks of spiking neurons. It has been argued that these devices can be used to build event-based systems, for solving real-world applications in real-time, with efficiencies and robustness that cannot be achieved with conventional computing technologies. In order to implement complex event-based neuromorphic sy...

  10. Network-driven design principles for neuromorphic systems

    Directory of Open Access Journals (Sweden)

    Johannes ePartzsch

    2015-10-01

    Full Text Available Synaptic connectivity is typically the most resource-demanding part of neuromorphic systems. Commonly, the architecture of these systems is chosen mainly on technical considerations. As a consequence, the potential for optimization arising from the inherent constraints of connectivity models is left unused. In this article, we develop an alternative, network-driven approach to neuromorphic architecture design. We describe methods to analyse performance of existing neuromorphic architectures in emulating certain connectivity models. Furthermore, we show step-by-step how to derive a neuromorphic architecture from a given connectivity model. For this, we introduce a generalized description for architectures with a synapse matrix, which takes into account shared use of circuit components for reducing total silicon area. Architectures designed with this approach are fitted to a connectivity model, essentially adapting to its connection density. They are guaranteeing faithful reproduction of the model on chip, while requiring less total silicon area. In total, our methods allow designers to implement more area-efficient neuromorphic systems and verify usability of the connectivity resources in these systems.

  11. Network-driven design principles for neuromorphic systems.

    Science.gov (United States)

    Partzsch, Johannes; Schüffny, Rene

    2015-01-01

    Synaptic connectivity is typically the most resource-demanding part of neuromorphic systems. Commonly, the architecture of these systems is chosen mainly on technical considerations. As a consequence, the potential for optimization arising from the inherent constraints of connectivity models is left unused. In this article, we develop an alternative, network-driven approach to neuromorphic architecture design. We describe methods to analyse performance of existing neuromorphic architectures in emulating certain connectivity models. Furthermore, we show step-by-step how to derive a neuromorphic architecture from a given connectivity model. For this, we introduce a generalized description for architectures with a synapse matrix, which takes into account shared use of circuit components for reducing total silicon area. Architectures designed with this approach are fitted to a connectivity model, essentially adapting to its connection density. They are guaranteeing faithful reproduction of the model on chip, while requiring less total silicon area. In total, our methods allow designers to implement more area-efficient neuromorphic systems and verify usability of the connectivity resources in these systems.

  12. Finding a Roadmap to achieve Large Neuromorphic Hardware Systems

    Directory of Open Access Journals (Sweden)

    Jennifer eHasler

    2013-09-01

    Full Text Available Neuromorphic systems are gaining increasing importance in an era where CMOS digital computing techniques are meeting hard physical limits. These silicon systems mimic extremely energy efficient neural computing structures, potentially both for solving engineering applications as well as understanding neural computation. Towards this end, the authors provide a glimpse at what the technology evolution roadmap looks like for these systems so that Neuromorphic engineers may gain the same benefit of anticipation and foresight that IC designers gained from Moore's law many years ago. Scaling of energy efficiency, performance, and size will be discussed as well as how the implementation and application space of Neuromorphic systems are expected to evolve over time.

  13. PyNCS: a microkernel for high-level definition and configuration of neuromorphic electronic systems

    Directory of Open Access Journals (Sweden)

    Fabio eStefanini

    2014-08-01

    Full Text Available Neuromorphic hardware offers an electronic substrate for the realization of asynchronousevent-based sensory-motor systems and large-scale spiking neural network architectures. Inorder to characterize these systems, configure them, and carry out modeling experiments, it isoften necessary to interface them to workstations. The software used for this purpose typicallyconsists of a large monolithic block of code highly specific to the hardware setup used. While thisapproach can lead to highly integrated hardware/software systems, it hampers the developmentof modular and neuromorphic infrastructures. To alleviate this problem, we propose PyNCS,an open-source front-end for the definition of neural network models that is interfaced to thehardware through a set of Python Application Programming Interfaces (APIs. The designof PyNCS promotes modularity, portability and expandability and separates implementationfrom hardware description. The high-level front-end that comes with PyNCS includes tools todefine neural network models as well as to create, monitor and analyze spiking data. Here wereport the design philosophy behind the PyNCS framework and describe its implementation.We demonstrate its functionality with two representative case studies, one using an event-based neuromorphic vision sensor, and one using a set of multi-neuron devices for carryingout a cognitive decision-making task involving state-dependent computation. PyNCS, alreadyapplicable to a wide range of existing spike-based neuromorphic setups, will accelerate thedevelopment of hybrid software/hardware neuromorphic systems, thanks to its code flexibility.The code developed is open-source and available online at https://github.com/inincs/pyNCS.

  14. Neuromorphic vision sensors and preprocessors in system applications

    Science.gov (United States)

    Kramer, Joerg; Indiveri, Giacomo

    1998-09-01

    A partial review of neuromorphic vision sensors that are suitable for use in autonomous systems is presented. Interfaces are being developed to multiplex the high- dimensional output signals of arrays of such sensors and to communicate them in standard formats to off-chip devices for higher-level processing, actuation, storage and display. Alternatively, on-chip processing stages may be implemented to extract sparse image parameters, thereby obviating the need for multiplexing. Autonomous robots are used to test neuromorphic vision chips in real-world environments and to explore the possibilities of data fusion from different sensing modalities. Examples of autonomous mobile systems that use neuromorphic vision chips for line tracking and optical flow matching are described.

  15. A neuromorphic VLSI device for implementing 2-D selective attention systems.

    Science.gov (United States)

    Indiveri, G

    2001-01-01

    Selective attention is a mechanism used to sequentially select and process salient subregions of the input space, while suppressing inputs arriving from nonsalient regions. By processing small amounts of sensory information in a serial fashion, rather than attempting to process all the sensory data in parallel, this mechanism overcomes the problem of flooding limited processing capacity systems with sensory inputs. It is found in many biological systems and can be a useful engineering tool for developing artificial systems that need to process in real-time sensory data. In this paper we present a neuromorphic hardware model of a selective attention mechanism implemented on a very large scale integration (VLSI) chip, using analog circuits. The chip makes use of a spike-based representation for receiving input signals, transmitting output signals and for shifting the selection of the attended input stimulus over time. It can be interfaced to neuromorphic sensors and actuators, for implementing multichip selective attention systems. We describe the characteristics of the circuits used in the architecture and present experimental data measured from the system.

  16. Emergent auditory feature tuning in a real-time neuromorphic VLSI system

    Directory of Open Access Journals (Sweden)

    Sadique eSheik

    2012-02-01

    Full Text Available Many sounds of ecological importance, such as communication calls, are characterised by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamocortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP, which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectrotemporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step towards the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems.

  17. Emergent Auditory Feature Tuning in a Real-Time Neuromorphic VLSI System.

    Science.gov (United States)

    Sheik, Sadique; Coath, Martin; Indiveri, Giacomo; Denham, Susan L; Wennekers, Thomas; Chicca, Elisabetta

    2012-01-01

    Many sounds of ecological importance, such as communication calls, are characterized by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamo-cortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP), which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectro-temporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step toward the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems.

  18. PyNCS: a microkernel for high-level definition and configuration of neuromorphic electronic systems.

    Science.gov (United States)

    Stefanini, Fabio; Neftci, Emre O; Sheik, Sadique; Indiveri, Giacomo

    2014-01-01

    Neuromorphic hardware offers an electronic substrate for the realization of asynchronous event-based sensory-motor systems and large-scale spiking neural network architectures. In order to characterize these systems, configure them, and carry out modeling experiments, it is often necessary to interface them to workstations. The software used for this purpose typically consists of a large monolithic block of code which is highly specific to the hardware setup used. While this approach can lead to highly integrated hardware/software systems, it hampers the development of modular and reconfigurable infrastructures thus preventing a rapid evolution of such systems. To alleviate this problem, we propose PyNCS, an open-source front-end for the definition of neural network models that is interfaced to the hardware through a set of Python Application Programming Interfaces (APIs). The design of PyNCS promotes modularity, portability and expandability and separates implementation from hardware description. The high-level front-end that comes with PyNCS includes tools to define neural network models as well as to create, monitor and analyze spiking data. Here we report the design philosophy behind the PyNCS framework and describe its implementation. We demonstrate its functionality with two representative case studies, one using an event-based neuromorphic vision sensor, and one using a set of multi-neuron devices for carrying out a cognitive decision-making task involving state-dependent computation. PyNCS, already applicable to a wide range of existing spike-based neuromorphic setups, will accelerate the development of hybrid software/hardware neuromorphic systems, thanks to its code flexibility. The code is open-source and available online at https://github.com/inincs/pyNCS.

  19. PyNCS: a microkernel for high-level definition and configuration of neuromorphic electronic systems

    Science.gov (United States)

    Stefanini, Fabio; Neftci, Emre O.; Sheik, Sadique; Indiveri, Giacomo

    2014-01-01

    Neuromorphic hardware offers an electronic substrate for the realization of asynchronous event-based sensory-motor systems and large-scale spiking neural network architectures. In order to characterize these systems, configure them, and carry out modeling experiments, it is often necessary to interface them to workstations. The software used for this purpose typically consists of a large monolithic block of code which is highly specific to the hardware setup used. While this approach can lead to highly integrated hardware/software systems, it hampers the development of modular and reconfigurable infrastructures thus preventing a rapid evolution of such systems. To alleviate this problem, we propose PyNCS, an open-source front-end for the definition of neural network models that is interfaced to the hardware through a set of Python Application Programming Interfaces (APIs). The design of PyNCS promotes modularity, portability and expandability and separates implementation from hardware description. The high-level front-end that comes with PyNCS includes tools to define neural network models as well as to create, monitor and analyze spiking data. Here we report the design philosophy behind the PyNCS framework and describe its implementation. We demonstrate its functionality with two representative case studies, one using an event-based neuromorphic vision sensor, and one using a set of multi-neuron devices for carrying out a cognitive decision-making task involving state-dependent computation. PyNCS, already applicable to a wide range of existing spike-based neuromorphic setups, will accelerate the development of hybrid software/hardware neuromorphic systems, thanks to its code flexibility. The code is open-source and available online at https://github.com/inincs/pyNCS. PMID:25232314

  20. Neuromorphic elements and systems as the basis for the physical implementation of artificial intelligence technologies

    Science.gov (United States)

    Demin, V. A.; Emelyanov, A. V.; Lapkin, D. A.; Erokhin, V. V.; Kashkarov, P. K.; Kovalchuk, M. V.

    2016-11-01

    The instrumental realization of neuromorphic systems may form the basis of a radically new social and economic setup, redistributing roles between humans and complex technical aggregates. The basic elements of any neuromorphic system are neurons and synapses. New memristive elements based on both organic (polymer) and inorganic materials have been formed, and the possibilities of instrumental implementation of very simple neuromorphic systems with different architectures on the basis of these elements have been demonstrated.

  1. Neuromorphic adaptive plastic scalable electronics: analog learning systems.

    Science.gov (United States)

    Srinivasa, Narayan; Cruz-Albrecht, Jose

    2012-01-01

    Decades of research to build programmable intelligent machines have demonstrated limited utility in complex, real-world environments. Comparing their performance with biological systems, these machines are less efficient by a factor of 1 million1 billion in complex, real-world environments. The Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) program is a multifaceted Defense Advanced Research Projects Agency (DARPA) project that seeks to break the programmable machine paradigm and define a new path for creating useful, intelligent machines. Since real-world systems exhibit infinite combinatorial complexity, electronic neuromorphic machine technology would be preferable in a host of applications, but useful and practical implementations still do not exist. HRL Laboratories LLC has embarked on addressing these challenges, and, in this article, we provide an overview of our project and progress made thus far.

  2. Integrated neuron circuit for implementing neuromorphic system with synaptic device

    Science.gov (United States)

    Lee, Jeong-Jun; Park, Jungjin; Kwon, Min-Woo; Hwang, Sungmin; Kim, Hyungjin; Park, Byung-Gook

    2018-02-01

    In this paper, we propose and fabricate Integrate & Fire neuron circuit for implementing neuromorphic system. Overall operation of the circuit is verified by measuring discrete devices and the output characteristics of the circuit. Since the neuron circuit shows asymmetric output characteristic that can drive synaptic device with Spike-Timing-Dependent-Plasticity (STDP) characteristic, the autonomous weight update process is also verified by connecting the synaptic device and the neuron circuit. The timing difference of the pre-neuron and the post-neuron induce autonomous weight change of the synaptic device. Unlike 2-terminal devices, which is frequently used to implement neuromorphic system, proposed scheme of the system enables autonomous weight update and simple configuration by using 4-terminal synapse device and appropriate neuron circuit. Weight update process in the multi-layer neuron-synapse connection ensures implementation of the hardware-based artificial intelligence, based on Spiking-Neural- Network (SNN).

  3. Neuromorphic Computing – From Materials Research to Systems Architecture Roundtable

    Energy Technology Data Exchange (ETDEWEB)

    Schuller, Ivan K. [Univ. of California, San Diego, CA (United States); Stevens, Rick [Argonne National Lab. (ANL), Argonne, IL (United States); Univ. of Chicago, IL (United States); Pino, Robinson [Dept. of Energy (DOE) Office of Science, Washington, DC (United States); Pechan, Michael [Dept. of Energy (DOE) Office of Science, Washington, DC (United States)

    2015-10-29

    Computation in its many forms is the engine that fuels our modern civilization. Modern computation—based on the von Neumann architecture—has allowed, until now, the development of continuous improvements, as predicted by Moore’s law. However, computation using current architectures and materials will inevitably—within the next 10 years—reach a limit because of fundamental scientific reasons. DOE convened a roundtable of experts in neuromorphic computing systems, materials science, and computer science in Washington on October 29-30, 2015 to address the following basic questions: Can brain-like (“neuromorphic”) computing devices based on new material concepts and systems be developed to dramatically outperform conventional CMOS based technology? If so, what are the basic research challenges for materials sicence and computing? The overarching answer that emerged was: The development of novel functional materials and devices incorporated into unique architectures will allow a revolutionary technological leap toward the implementation of a fully “neuromorphic” computer. To address this challenge, the following issues were considered: The main differences between neuromorphic and conventional computing as related to: signaling models, timing/clock, non-volatile memory, architecture, fault tolerance, integrated memory and compute, noise tolerance, analog vs. digital, and in situ learning New neuromorphic architectures needed to: produce lower energy consumption, potential novel nanostructured materials, and enhanced computation Device and materials properties needed to implement functions such as: hysteresis, stability, and fault tolerance Comparisons of different implementations: spin torque, memristors, resistive switching, phase change, and optical schemes for enhanced breakthroughs in performance, cost, fault tolerance, and/or manufacturability.

  4. Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems.

    Science.gov (United States)

    Indiveri, Giacomo

    2008-09-03

    Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computational resources. One of the main computational primitives used to perform these selection operations is the Winner-Take-All (WTA) network. These types of networks are formed by arrays of coupled computational nodes that selectively amplify the strongest input signals, and suppress the weaker ones. Neuromorphic circuits are an optimal medium for constructing WTA networks and for implementing efficient hardware models of selective attention systems. In this paper we present an overview of selective attention systems based on neuromorphic WTA circuits ranging from single-chip vision sensors for selecting and tracking the position of salient features, to multi-chip systems implement saliency-map based models of selective attention.

  5. Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems

    Directory of Open Access Journals (Sweden)

    Giacomo Indiveri

    2008-09-01

    Full Text Available Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computational resources. One of the main computational primitives used to perform these selection operations is the Winner-Take-All (WTA network. These types of networks are formed by arrays of coupled computational nodes that selectively amplify the strongest input signals, and suppress the weaker ones. Neuromorphic circuits are an optimal medium for constructing WTA networks and for implementing efficient hardware models of selective attention systems. In this paper we present an overview of selective attention systems based on neuromorphic WTA circuits ranging from single-chip vision sensors for selecting and tracking the position of salient features, to multi-chip systems implement saliency-map based models of selective attention.

  6. Generalized reconfigurable memristive dynamical system (MDS) for neuromorphic applications.

    Science.gov (United States)

    Bavandpour, Mohammad; Soleimani, Hamid; Linares-Barranco, Bernabé; Abbott, Derek; Chua, Leon O

    2015-01-01

    This study firstly presents (i) a novel general cellular mapping scheme for two dimensional neuromorphic dynamical systems such as bio-inspired neuron models, and (ii) an efficient mixed analog-digital circuit, which can be conveniently implemented on a hybrid memristor-crossbar/CMOS platform, for hardware implementation of the scheme. This approach employs 4n memristors and no switch for implementing an n-cell system in comparison with 2n (2) memristors and 2n switches of a Cellular Memristive Dynamical System (CMDS). Moreover, this approach allows for dynamical variables with both analog and one-hot digital values opening a wide range of choices for interconnections and networking schemes. Dynamical response analyses show that this circuit exhibits various responses based on the underlying bifurcation scenarios which determine the main characteristics of the neuromorphic dynamical systems. Due to high programmability of the circuit, it can be applied to a variety of learning systems, real-time applications, and analytically indescribable dynamical systems. We simulate the FitzHugh-Nagumo (FHN), Adaptive Exponential (AdEx) integrate and fire, and Izhikevich neuron models on our platform, and investigate the dynamical behaviors of these circuits as case studies. Moreover, error analysis shows that our approach is suitably accurate. We also develop a simple hardware prototype for experimental demonstration of our approach.

  7. An Investigation into Spike-Based Neuromorphic Approaches for Artificial Olfactory Systems

    Directory of Open Access Journals (Sweden)

    Anup Vanarse

    2017-11-01

    Full Text Available The implementation of neuromorphic methods has delivered promising results for vision and auditory sensors. These methods focus on mimicking the neuro-biological architecture to generate and process spike-based information with minimal power consumption. With increasing interest in developing low-power and robust chemical sensors, the application of neuromorphic engineering concepts for electronic noses has provided an impetus for research focusing on improving these instruments. While conventional e-noses apply computationally expensive and power-consuming data-processing strategies, neuromorphic olfactory sensors implement the biological olfaction principles found in humans and insects to simplify the handling of multivariate sensory data by generating and processing spike-based information. Over the last decade, research on neuromorphic olfaction has established the capability of these sensors to tackle problems that plague the current e-nose implementations such as drift, response time, portability, power consumption and size. This article brings together the key contributions in neuromorphic olfaction and identifies future research directions to develop near-real-time olfactory sensors that can be implemented for a range of applications such as biosecurity and environmental monitoring. Furthermore, we aim to expose the computational parallels between neuromorphic olfaction and gustation for future research focusing on the correlation of these senses.

  8. Understanding a Deep Learning Technique through a Neuromorphic System a Case Study with SpiNNaker Neuromorphic Platform

    Directory of Open Access Journals (Sweden)

    Sugiarto Indar

    2018-01-01

    Full Text Available Deep learning (DL has been considered as a breakthrough technique in the field of artificial intelligence and machine learning. Conceptually, it relies on a many-layer network that exhibits a hierarchically non-linear processing capability. Some DL architectures such as deep neural networks, deep belief networks and recurrent neural networks have been developed and applied to many fields with incredible results, even comparable to human intelligence. However, many researchers are still sceptical about its true capability: can the intelligence demonstrated by deep learning technique be applied for general tasks? This question motivates the emergence of another research discipline: neuromorphic computing (NC. In NC, researchers try to identify the most fundamental ingredients that construct intelligence behaviour produced by the brain itself. To achieve this, neuromorphic systems are developed to mimic the brain functionality down to cellular level. In this paper, a neuromorphic platform called SpiNNaker is described and evaluated in order to understand its potential use as a platform for a deep learning approach. This paper is a literature review that contains comparative study on algorithms that have been implemented in SpiNNaker.

  9. Neuromodulated Synaptic Plasticity on the SpiNNaker Neuromorphic System

    Directory of Open Access Journals (Sweden)

    Mantas Mikaitis

    2018-02-01

    Full Text Available SpiNNaker is a digital neuromorphic architecture, designed specifically for the low power simulation of large-scale spiking neural networks at speeds close to biological real-time. Unlike other neuromorphic systems, SpiNNaker allows users to develop their own neuron and synapse models as well as specify arbitrary connectivity. As a result SpiNNaker has proved to be a powerful tool for studying different neuron models as well as synaptic plasticity—believed to be one of the main mechanisms behind learning and memory in the brain. A number of Spike-Timing-Dependent-Plasticity(STDP rules have already been implemented on SpiNNaker and have been shown to be capable of solving various learning tasks in real-time. However, while STDP is an important biological theory of learning, it is a form of Hebbian or unsupervised learning and therefore does not explain behaviors that depend on feedback from the environment. Instead, learning rules based on neuromodulated STDP (three-factor learning rules have been shown to be capable of solving reinforcement learning tasks in a biologically plausible manner. In this paper we demonstrate for the first time how a model of three-factor STDP, with the third-factor representing spikes from dopaminergic neurons, can be implemented on the SpiNNaker neuromorphic system. Using this learning rule we first show how reward and punishment signals can be delivered to a single synapse before going on to demonstrate it in a larger network which solves the credit assignment problem in a Pavlovian conditioning experiment. Because of its extra complexity, we find that our three-factor learning rule requires approximately 2× as much processing time as the existing SpiNNaker STDP learning rules. However, we show that it is still possible to run our Pavlovian conditioning model with up to 1 × 104 neurons in real-time, opening up new research opportunities for modeling behavioral learning on SpiNNaker.

  10. Neuromorphic neural interfaces: from neurophysiological inspiration to biohybrid coupling with nervous systems

    Science.gov (United States)

    Broccard, Frédéric D.; Joshi, Siddharth; Wang, Jun; Cauwenberghs, Gert

    2017-08-01

    Objective. Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use of physical resources such as time, space and energy. In an effort to better understand neural computation on a physical medium with similar spatiotemporal and energetic constraints, the field of neuromorphic engineering aims to design and implement electronic systems that emulate in very large-scale integration (VLSI) hardware the organization and functions of neural systems at multiple levels of biological organization, from individual neurons up to large circuits and networks. Mixed analog/digital neuromorphic VLSI systems are compact, consume little power and operate in real time independently of the size and complexity of the model. Approach. This article highlights the current efforts to interface neuromorphic systems with neural systems at multiple levels of biological organization, from the synaptic to the system level, and discusses the prospects for future biohybrid systems with neuromorphic circuits of greater complexity. Main results. Single silicon neurons have been interfaced successfully with invertebrate and vertebrate neural networks. This approach allowed the investigation of neural properties that are inaccessible with traditional techniques while providing a realistic biological context not achievable with traditional numerical modeling methods. At the network level, populations of neurons are envisioned to communicate bidirectionally with neuromorphic processors of hundreds or thousands of silicon neurons. Recent work on brain-machine interfaces suggests that this is feasible with current neuromorphic technology. Significance. Biohybrid interfaces between biological neurons and VLSI neuromorphic systems of varying complexity have started to emerge in the literature. Primarily intended as a

  11. Neuromorphic olfaction neuromorphic olfaction

    CERN Document Server

    Persaud, Krishna C; Marco, Santiago

    2016-01-01

    Engineering Aspects of Olfaction; Krishna C. PersaudStudy of the Coding Efficiency of Populations of OlfactoryReceptor Neurons and Olfactory Glomeruli; Agustín Gutiérrez-Gálvez and Santiago MarcoMimicking Biological Olfaction with Very Large ChemicalArrays; Mara Bernabei, Romeo Beccherelli, Emiliano Zampetti,Simone Pantalei, and Krishna C. PersaudThe Synthetic Moth: A Neuromorphic Approach towardArtificial Olfaction in Robots; Vasiliki Vouloutsi, Lucas L. Lopez-Serrano,Zenon Mathews, Alex Escuredo Chimeno, Andrey Ziyatdinov, Alexandre Perera i Lluna, Sergi Bermúdez i Badia, and Paul F. M. J. Verschure Reactive and Cognitive Search Strategies for Olfactory Robots; Dominique Martinez and Eduardo Martin MoraudPerformance of a Computational Model of the MammalianOlfactory System; Simon Benjaminsson, Pawel Herman, and Anders LansnerIndex.

  12. Establishing a novel modeling tool: a python-based interface for a neuromorphic hardware system

    Directory of Open Access Journals (Sweden)

    Daniel Brüderle

    2009-06-01

    Full Text Available Neuromorphic hardware systems provide new possibilities for the neuroscience modeling community. Due to the intrinsic parallelism of the micro-electronic emulation of neural computation, such models are highly scalable without a loss of speed. However, the communities of software simulator users and neuromorphic engineering in neuroscience are rather disjoint. We present a software concept that provides the possibility to establish such hardware devices as valuable modeling tools. It is based on the integration of the hardware interface into a simulator-independent language which allows for unified experiment descriptions that can be run on various simulation platforms without modification, implying experiment portability and a huge simplification of the quantitative comparison of hardware and simulator results. We introduce an accelerated neuromorphic hardware device and describe the implementation of the proposed concept for this system. An example setup and results acquired by utilizing both the hardware system and a software simulator are demonstrated.

  13. Establishing a novel modeling tool: a python-based interface for a neuromorphic hardware system.

    Science.gov (United States)

    Brüderle, Daniel; Müller, Eric; Davison, Andrew; Muller, Eilif; Schemmel, Johannes; Meier, Karlheinz

    2009-01-01

    Neuromorphic hardware systems provide new possibilities for the neuroscience modeling community. Due to the intrinsic parallelism of the micro-electronic emulation of neural computation, such models are highly scalable without a loss of speed. However, the communities of software simulator users and neuromorphic engineering in neuroscience are rather disjoint. We present a software concept that provides the possibility to establish such hardware devices as valuable modeling tools. It is based on the integration of the hardware interface into a simulator-independent language which allows for unified experiment descriptions that can be run on various simulation platforms without modification, implying experiment portability and a huge simplification of the quantitative comparison of hardware and simulator results. We introduce an accelerated neuromorphic hardware device and describe the implementation of the proposed concept for this system. An example setup and results acquired by utilizing both the hardware system and a software simulator are demonstrated.

  14. Recent Advances on Neuromorphic Systems Using Phase-Change Materials

    Science.gov (United States)

    Wang, Lei; Lu, Shu-Ren; Wen, Jing

    2017-05-01

    Realization of brain-like computer has always been human's ultimate dream. Today, the possibility of having this dream come true has been significantly boosted due to the advent of several emerging non-volatile memory devices. Within these innovative technologies, phase-change memory device has been commonly regarded as the most promising candidate to imitate the biological brain, owing to its excellent scalability, fast switching speed, and low energy consumption. In this context, a detailed review concerning the physical principles of the neuromorphic circuit using phase-change materials as well as a comprehensive introduction of the currently available phase-change neuromorphic prototypes becomes imperative for scientists to continuously progress the technology of artificial neural networks. In this paper, we first present the biological mechanism of human brain, followed by a brief discussion about physical properties of phase-change materials that recently receive a widespread application on non-volatile memory field. We then survey recent research on different types of neuromorphic circuits using phase-change materials in terms of their respective geometrical architecture and physical schemes to reproduce the biological events of human brain, in particular for spike-time-dependent plasticity. The relevant virtues and limitations of these devices are also evaluated. Finally, the future prospect of the neuromorphic circuit based on phase-change technologies is envisioned.

  15. Recent Advances on Neuromorphic Systems Using Phase-Change Materials.

    Science.gov (United States)

    Wang, Lei; Lu, Shu-Ren; Wen, Jing

    2017-12-01

    Realization of brain-like computer has always been human's ultimate dream. Today, the possibility of having this dream come true has been significantly boosted due to the advent of several emerging non-volatile memory devices. Within these innovative technologies, phase-change memory device has been commonly regarded as the most promising candidate to imitate the biological brain, owing to its excellent scalability, fast switching speed, and low energy consumption. In this context, a detailed review concerning the physical principles of the neuromorphic circuit using phase-change materials as well as a comprehensive introduction of the currently available phase-change neuromorphic prototypes becomes imperative for scientists to continuously progress the technology of artificial neural networks. In this paper, we first present the biological mechanism of human brain, followed by a brief discussion about physical properties of phase-change materials that recently receive a widespread application on non-volatile memory field. We then survey recent research on different types of neuromorphic circuits using phase-change materials in terms of their respective geometrical architecture and physical schemes to reproduce the biological events of human brain, in particular for spike-time-dependent plasticity. The relevant virtues and limitations of these devices are also evaluated. Finally, the future prospect of the neuromorphic circuit based on phase-change technologies is envisioned.

  16. Neuromorphic Data Microscope

    Energy Technology Data Exchange (ETDEWEB)

    Naegle, John H.; Suppona, Roger A.; Aimone, James Bradley; James, Conrad D.; Follett, David R.; Townsend, Duncan C.M.; Follett, Pamela L.; Karpman, Gabe D.

    2017-08-01

    In 2016, Lewis Rhodes Labs, (LRL), shipped the first commercially viable Neuromorphic Processing Unit, (NPU), branded as a Neuromorphic Data Microscope (NDM). This product leverages architectural mechanisms derived from the sensory cortex of the human brain to efficiently implement pattern matching. LRL and Sandia National Labs have optimized this product for streaming analytics, and demonstrated a 1,000x power per operation reduction in an FPGA format. When reduced to an ASIC, the efficiency will improve to 1,000,000x. Additionally, the neuromorphic nature of the device gives it powerful computational attributes that are counterintuitive to those schooled in traditional von Neumann architectures. The Neuromorphic Data Microscope is the first of a broad class of brain-inspired, time domain processors that will profoundly alter the functionality and economics of data processing.

  17. An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

    Science.gov (United States)

    Rasouli, Mahdi; Chen, Yi; Basu, Arindam; Kukreja, Sunil L; Thakor, Nitish V

    2018-04-01

    Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim to develop a neuromorphic system for tactile pattern recognition. We particularly target texture recognition as it is one of the most necessary and challenging tasks for artificial sensory systems. Our system consists of a piezoresistive fabric material as the sensor to emulate skin, an interface that produces spike patterns to mimic neural signals from mechanoreceptors, and an extreme learning machine (ELM) chip to analyze spiking activity. Benefiting from intrinsic advantages of biologically inspired event-driven systems and massively parallel and energy-efficient processing capabilities of the ELM chip, the proposed architecture offers a fast and energy-efficient alternative for processing tactile information. Moreover, it provides the opportunity for the development of low-cost tactile modules for large-area applications by integration of sensors and processing circuits. We demonstrate the recognition capability of our system in a texture discrimination task, where it achieves a classification accuracy of 92% for categorization of ten graded textures. Our results confirm that there exists a tradeoff between response time and classification accuracy (and information transfer rate). A faster decision can be achieved at early time steps or by using a shorter time window. This, however, results in deterioration of the classification accuracy and information transfer rate. We further observe that there exists a tradeoff between the classification accuracy and the input spike rate (and thus energy consumption). Our work substantiates the importance of development of efficient sparse codes for encoding sensory data to improve the energy efficiency. These results have a significance for a wide range of wearable, robotic

  18. Event-Driven Contrastive Divergence for Spiking Neuromorphic Systems

    Directory of Open Access Journals (Sweden)

    Emre eNeftci

    2014-01-01

    Full Text Available Restricted Boltzmann Machines (RBMs and Deep Belief Networks have been demonstrated to perform efficiently in variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissipation and real-time interfacing with the environment. However the traditional RBM architecture and the commonly used training algorithm known as Contrastive Divergence (CD are based on discrete updates and exact arithmetics which do not directly map onto a dynamical neural substrate. Here, we present an event-driven variation of CD to train a RBM constructed with Integrate & Fire (I&F neurons, that is constrained by the limitations of existing and near future neuromorphic hardware platforms. Our strategy is based on neural sampling, which allows us to synthesize a spiking neural network that samples from a target Boltzmann distribution. The reverberating activity of the network replaces the discrete steps of the CD algorithm, while Spike Time Dependent Plasticity (STDP carries out the weight updates in an online, asynchronous fashion.We demonstrate our approach by training an RBM composed of leaky I&F neurons with STDP synapses to learn a generative model of the MNIST hand-written digit dataset, and by testing it in recognition, generation and cue integration tasks. Our results contribute to a machine learning-driven approach for synthesizing networks of spiking neurons capable of carrying out practical, high-level functionality.

  19. Event-driven contrastive divergence for spiking neuromorphic systems.

    Science.gov (United States)

    Neftci, Emre; Das, Srinjoy; Pedroni, Bruno; Kreutz-Delgado, Kenneth; Cauwenberghs, Gert

    2013-01-01

    Restricted Boltzmann Machines (RBMs) and Deep Belief Networks have been demonstrated to perform efficiently in a variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissipation and real-time interfacing with the environment. However, the traditional RBM architecture and the commonly used training algorithm known as Contrastive Divergence (CD) are based on discrete updates and exact arithmetics which do not directly map onto a dynamical neural substrate. Here, we present an event-driven variation of CD to train a RBM constructed with Integrate & Fire (I&F) neurons, that is constrained by the limitations of existing and near future neuromorphic hardware platforms. Our strategy is based on neural sampling, which allows us to synthesize a spiking neural network that samples from a target Boltzmann distribution. The recurrent activity of the network replaces the discrete steps of the CD algorithm, while Spike Time Dependent Plasticity (STDP) carries out the weight updates in an online, asynchronous fashion. We demonstrate our approach by training an RBM composed of leaky I&F neurons with STDP synapses to learn a generative model of the MNIST hand-written digit dataset, and by testing it in recognition, generation and cue integration tasks. Our results contribute to a machine learning-driven approach for synthesizing networks of spiking neurons capable of carrying out practical, high-level functionality.

  20. Energy-efficient neuromorphic classifiers

    OpenAIRE

    Martí, Daniel; Rigotti, Mattia; Seok, Mingoo; Fusi, Stefano

    2015-01-01

    Neuromorphic engineering combines the architectural and computational principles of systems neuroscience with semiconductor electronics, with the aim of building efficient and compact devices that mimic the synaptic and neural machinery of the brain. Neuromorphic engineering promises extremely low energy consumptions, comparable to those of the nervous system. However, until now the neuromorphic approach has been restricted to relatively simple circuits and specialized functions, rendering el...

  1. Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems

    OpenAIRE

    Massimiliano Giulioni; Federico Corradi; Vittorio Dante; Paolo del Giudice

    2015-01-01

    Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a 'basin' of attraction compri...

  2. A robust and scalable neuromorphic communication system by combining synaptic time multiplexing and MIMO-OFDM.

    Science.gov (United States)

    Srinivasa, Narayan; Zhang, Deying; Grigorian, Beayna

    2014-03-01

    This paper describes a novel architecture for enabling robust and efficient neuromorphic communication. The architecture combines two concepts: 1) synaptic time multiplexing (STM) that trades space for speed of processing to create an intragroup communication approach that is firing rate independent and offers more flexibility in connectivity than cross-bar architectures and 2) a wired multiple input multiple output (MIMO) communication with orthogonal frequency division multiplexing (OFDM) techniques to enable a robust and efficient intergroup communication for neuromorphic systems. The MIMO-OFDM concept for the proposed architecture was analyzed by simulating large-scale spiking neural network architecture. Analysis shows that the neuromorphic system with MIMO-OFDM exhibits robust and efficient communication while operating in real time with a high bit rate. Through combining STM with MIMO-OFDM techniques, the resulting system offers a flexible and scalable connectivity as well as a power and area efficient solution for the implementation of very large-scale spiking neural architectures in hardware.

  3. Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems

    Science.gov (United States)

    Giulioni, Massimiliano; Corradi, Federico; Dante, Vittorio; Del Giudice, Paolo

    2015-10-01

    Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a ‘basin’ of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases.

  4. Implementation of neuromorphic systems: from discrete components to analog VLSI chips (testing and communication issues).

    Science.gov (United States)

    Dante, V; Del Giudice, P; Mattia, M

    2001-01-01

    We review a series of implementations of electronic devices aiming at imitating to some extent structure and function of simple neural systems, with particular emphasis on communication issues. We first provide a short overview of general features of such "neuromorphic" devices and the implications of setting up "tests" for them. We then review the developments directly related to our work at the Istituto Superiore di Sanità (ISS): a pilot electronic neural network implementing a simple classifier, autonomously developing internal representations of incoming stimuli; an output network, collecting information from the previous classifier and extracting the relevant part to be forwarded to the observer; an analog, VLSI (very large scale integration) neural chip implementing a recurrent network of spiking neurons and plastic synapses, and the test setup for it; a board designed to interface the standard PCI (peripheral component interconnect) bus of a PC with a special purpose, asynchronous bus for communication among neuromorphic chips; a short and preliminary account of an application-oriented device, taking advantage of the above communication infrastructure.

  5. Silicon synaptic transistor for hardware-based spiking neural network and neuromorphic system

    Science.gov (United States)

    Kim, Hyungjin; Hwang, Sungmin; Park, Jungjin; Park, Byung-Gook

    2017-10-01

    Brain-inspired neuromorphic systems have attracted much attention as new computing paradigms for power-efficient computation. Here, we report a silicon synaptic transistor with two electrically independent gates to realize a hardware-based neural network system without any switching components. The spike-timing dependent plasticity characteristics of the synaptic devices are measured and analyzed. With the help of the device model based on the measured data, the pattern recognition capability of the hardware-based spiking neural network systems is demonstrated using the modified national institute of standards and technology handwritten dataset. By comparing systems with and without inhibitory synapse part, it is confirmed that the inhibitory synapse part is an essential element in obtaining effective and high pattern classification capability.

  6. Neuromorphic VLSI vision system for real-time texture segregation.

    Science.gov (United States)

    Shimonomura, Kazuhiro; Yagi, Tetsuya

    2008-10-01

    The visual system of the brain can perceive an external scene in real-time with extremely low power dissipation, although the response speed of an individual neuron is considerably lower than that of semiconductor devices. The neurons in the visual pathway generate their receptive fields using a parallel and hierarchical architecture. This architecture of the visual cortex is interesting and important for designing a novel perception system from an engineering perspective. The aim of this study is to develop a vision system hardware, which is designed inspired by a hierarchical visual processing in V1, for real time texture segregation. The system consists of a silicon retina, orientation chip, and field programmable gate array (FPGA) circuit. The silicon retina emulates the neural circuits of the vertebrate retina and exhibits a Laplacian-Gaussian-like receptive field. The orientation chip selectively aggregates multiple pixels of the silicon retina in order to produce Gabor-like receptive fields that are tuned to various orientations by mimicking the feed-forward model proposed by Hubel and Wiesel. The FPGA circuit receives the output of the orientation chip and computes the responses of the complex cells. Using this system, the neural images of simple cells were computed in real-time for various orientations and spatial frequencies. Using the orientation-selective outputs obtained from the multi-chip system, a real-time texture segregation was conducted based on a computational model inspired by psychophysics and neurophysiology. The texture image was filtered by the two orthogonally oriented receptive fields of the multi-chip system and the filtered images were combined to segregate the area of different texture orientation with the aid of FPGA. The present system is also useful for the investigation of the functions of the higher-order cells that can be obtained by combining the simple and complex cells.

  7. 2D MoS2 Neuromorphic Devices for Brain-Like Computational Systems.

    Science.gov (United States)

    Jiang, Jie; Guo, Junjie; Wan, Xiang; Yang, Yi; Xie, Haipeng; Niu, Dongmei; Yang, Junliang; He, Jun; Gao, Yongli; Wan, Qing

    2017-08-01

    Hardware implementation of artificial synapses/neurons with 2D solid-state devices is of great significance for nanoscale brain-like computational systems. Here, 2D MoS 2 synaptic/neuronal transistors are fabricated by using poly(vinyl alcohol) as the laterally coupled, proton-conducting electrolytes. Fundamental synaptic functions, such as an excitatory postsynaptic current, paired-pulse facilitation, and a dynamic filter for information transmission of biological synapse, are successfully emulated. Most importantly, with multiple input gates and one modulatory gate, spiking-dependent logic operation/modulation, multiplicative neural coding, and neuronal gain modulation are also experimentally demonstrated. The results indicate that the intriguing 2D MoS 2 transistors are also very promising for the next-generation of nanoscale neuromorphic device applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. An Energy Efficient Neuromorphic Computing System Using Real Time Sensing Method

    DEFF Research Database (Denmark)

    Farkhani, Hooman; Tohidi, Mohammad; Farkhani, Sadaf

    2017-01-01

    In spintronic-based neuromorphic computing systems (NCS), the switching of magnetic moment in a magnetic tunnel junction (MTJ) is used to mimic neuron firing. However, the stochastic switching behavior of the MTJ and process variations effect leads to extra stimulation time. This leads to extra...... energy consumption and delay of such NCSs. In this paper, a new real-time sensing (RTS) circuit is proposed to track the MTJ state and terminate stimulation phase immediately after MTJ switching. This leads to significant degradation in energy consumption and delay of NCS. The simulation results using...... a 65-nm CMOS technology and a 40-nm MTJ technology confirm that the energy consumption of a RTS-based NCS is improved by 50% in comparison with a typical NCS. Moreover, utilizing RTS circuit improves the overall speed of an NCS by 2.75x....

  9. Serendipitous Offline Learning in a Neuromorphic Robot

    Directory of Open Access Journals (Sweden)

    Terrence C Stewart

    2016-02-01

    Full Text Available We demonstrate a hybrid neuromorphic learning paradigm that learns complex sensorimotor mappings based on a small set of hard-coded reflex behaviours. A mobile robot is first controlled by a basic set of reflexive hand-designed behaviours. All sensor data is provided via a spike-based silicon retina camera (eDVS, and all control is implemented via spiking neurons simulated on neuromorphic hardware (SpiNNaker. Given this control system, the robot is capable of simple obstacle avoidance and random exploration. To train the robot to perform more complex tasks, we observe the robot and find instances where he robot accidentally performs the desired action. Data recorded from the robot during these times is then used to update the neural control system, increasing the likelihood of the robot performing that task in the future, given a similar sensor state. As an example application of this general-purpose method of training, we demonstrate the robot learning to respond to novel sensory stimuli (a mirror by turning right if it is present at an intersection, and otherwise turning left. In general, this system can learn arbitrary relations between sensory input and motor behaviour.

  10. Modeling selective attention using a neuromorphic analog VLSI device.

    Science.gov (United States)

    Indiveri, G

    2000-12-01

    Attentional mechanisms are required to overcome the problem of flooding a limited processing capacity system with information. They are present in biological sensory systems and can be a useful engineering tool for artificial visual systems. In this article we present a hardware model of a selective attention mechanism implemented on a very large-scale integration (VLSI) chip, using analog neuromorphic circuits. The chip exploits a spike-based representation to receive, process, and transmit signals. It can be used as a transceiver module for building multichip neuromorphic vision systems. We describe the circuits that carry out the main processing stages of the selective attention mechanism and provide experimental data for each circuit. We demonstrate the expected behavior of the model at the system level by stimulating the chip with both artificially generated control signals and signals obtained from a saliency map, computed from an image containing several salient features.

  11. A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systems.

    Science.gov (United States)

    Wang, Zhongqiang; Ambrogio, Stefano; Balatti, Simone; Ielmini, Daniele

    2014-01-01

    Resistive (or memristive) switching devices based on metal oxides find applications in memory, logic and neuromorphic computing systems. Their small area, low power operation, and high functionality meet the challenges of brain-inspired computing aiming at achieving a huge density of active connections (synapses) with low operation power. This work presents a new artificial synapse scheme, consisting of a memristive switch connected to 2 transistors responsible for gating the communication and learning operations. Spike timing dependent plasticity (STDP) is achieved through appropriate shaping of the pre-synaptic and the post synaptic spikes. Experiments with integrated artificial synapses demonstrate STDP with stochastic behavior due to (i) the natural variability of set/reset processes in the nanoscale switch, and (ii) the different response of the switch to a given stimulus depending on the initial state. Experimental results are confirmed by model-based simulations of the memristive switching. Finally, system-level simulations of a 2-layer neural network and a simplified STDP model show random learning and recognition of patterns.

  12. An exploration of neuromorphic systems and related design issues/challenges in dark silicon era

    Science.gov (United States)

    Chandaliya, Mudit; Chaturvedi, Nitin; Gurunarayanan, S.

    2018-03-01

    The current microprocessors has shown a remarkable performance and memory capacity improvement since its innovation. However, due to power and thermal limitations, only a fraction of cores can operate at full frequency at any instant of time irrespective of the advantages of new technology generation. This phenomenon of under-utilization of microprocessor is called as dark silicon which leads to distraction in innovative computing. To overcome the limitation of utilization wall, IBM technologies explored and invented neurosynaptic system chips. It has opened a wide scope of research in the field of innovative computing, technology, material sciences, machine learning etc. In this paper, we first reviewed the diverse stages of research that have been influential in the innovation of neurosynaptic architectures. These, architectures focuses on the development of brain-like framework which is efficient enough to execute a broad set of computations in real time while maintaining ultra-low power consumption as well as area considerations in mind. We also reveal the inadvertent challenges and the opportunities of designing neuromorphic systems as presented by the existing technologies in the dark silicon era, which constitute the utmost area of research in future.

  13. Quasiperiodic AlGaAs superlattices for neuromorphic networks and nonlinear control systems

    Energy Technology Data Exchange (ETDEWEB)

    Malyshev, K. V., E-mail: malyshev@bmstu.ru [Electronics and Laser Technology Department, Bauman Moscow State Technical University, Moscow 105005 (Russian Federation)

    2015-01-28

    The application of quasiperiodic AlGaAs superlattices as a nonlinear element of the FitzHugh–Nagumo neuromorphic network is proposed and theoretically investigated on the example of Fibonacci and figurate superlattices. The sequences of symbols for the figurate superlattices were produced by decomposition of the Fibonacci superlattices' symbolic sequences. A length of each segment of the decomposition was equal to the corresponding figurate number. It is shown that a nonlinear network based upon Fibonacci and figurate superlattices provides better parallel filtration of a half-tone picture; then, a network based upon traditional diodes which have cubic voltage-current characteristics. It was found that the figurate superlattice F{sup 0}{sub 11}(1) as a nonlinear network's element provides the filtration error almost twice less than the conventional “cubic” diode. These advantages are explained by a wavelike shape of the decreasing part of the quasiperiodic superlattice's voltage-current characteristic, which leads to multistability of the network's cell. This multistability promises new interesting nonlinear dynamical phenomena. A variety of wavy forms of voltage-current characteristics opens up new interesting possibilities for quasiperiodic superlattices and especially for figurate superlattices in many areas—from nervous system modeling to nonlinear control systems development.

  14. Energy-Efficient Neuromorphic Classifiers.

    Science.gov (United States)

    Martí, Daniel; Rigotti, Mattia; Seok, Mingoo; Fusi, Stefano

    2016-10-01

    Neuromorphic engineering combines the architectural and computational principles of systems neuroscience with semiconductor electronics, with the aim of building efficient and compact devices that mimic the synaptic and neural machinery of the brain. The energy consumptions promised by neuromorphic engineering are extremely low, comparable to those of the nervous system. Until now, however, the neuromorphic approach has been restricted to relatively simple circuits and specialized functions, thereby obfuscating a direct comparison of their energy consumption to that used by conventional von Neumann digital machines solving real-world tasks. Here we show that a recent technology developed by IBM can be leveraged to realize neuromorphic circuits that operate as classifiers of complex real-world stimuli. Specifically, we provide a set of general prescriptions to enable the practical implementation of neural architectures that compete with state-of-the-art classifiers. We also show that the energy consumption of these architectures, realized on the IBM chip, is typically two or more orders of magnitude lower than that of conventional digital machines implementing classifiers with comparable performance. Moreover, the spike-based dynamics display a trade-off between integration time and accuracy, which naturally translates into algorithms that can be flexibly deployed for either fast and approximate classifications, or more accurate classifications at the mere expense of longer running times and higher energy costs. This work finally proves that the neuromorphic approach can be efficiently used in real-world applications and has significant advantages over conventional digital devices when energy consumption is considered.

  15. Validity of Sensory Systems as Distinct Constructs

    OpenAIRE

    Su, Chia-Ting; Parham, L. Diane

    2014-01-01

    Confirmatory factor analysis testing whether sensory questionnaire items represented distinct sensory system constructs found, using data from two age groups, that such constructs can be measured validly using questionnaire data.

  16. A FPGA-Based, Granularity-Variable Neuromorphic Processor and Its Application in a MIMO Real-Time Control System.

    Science.gov (United States)

    Zhang, Zhen; Ma, Cheng; Zhu, Rong

    2017-08-23

    Artificial Neural Networks (ANNs), including Deep Neural Networks (DNNs), have become the state-of-the-art methods in machine learning and achieved amazing success in speech recognition, visual object recognition, and many other domains. There are several hardware platforms for developing accelerated implementation of ANN models. Since Field Programmable Gate Array (FPGA) architectures are flexible and can provide high performance per watt of power consumption, they have drawn a number of applications from scientists. In this paper, we propose a FPGA-based, granularity-variable neuromorphic processor (FBGVNP). The traits of FBGVNP can be summarized as granularity variability, scalability, integrated computing, and addressing ability: first, the number of neurons is variable rather than constant in one core; second, the multi-core network scale can be extended in various forms; third, the neuron addressing and computing processes are executed simultaneously. These make the processor more flexible and better suited for different applications. Moreover, a neural network-based controller is mapped to FBGVNP and applied in a multi-input, multi-output, (MIMO) real-time, temperature-sensing and control system. Experiments validate the effectiveness of the neuromorphic processor. The FBGVNP provides a new scheme for building ANNs, which is flexible, highly energy-efficient, and can be applied in many areas.

  17. A FPGA-Based, Granularity-Variable Neuromorphic Processor and Its Application in a MIMO Real-Time Control System

    Directory of Open Access Journals (Sweden)

    Zhen Zhang

    2017-08-01

    Full Text Available Artificial Neural Networks (ANNs, including Deep Neural Networks (DNNs, have become the state-of-the-art methods in machine learning and achieved amazing success in speech recognition, visual object recognition, and many other domains. There are several hardware platforms for developing accelerated implementation of ANN models. Since Field Programmable Gate Array (FPGA architectures are flexible and can provide high performance per watt of power consumption, they have drawn a number of applications from scientists. In this paper, we propose a FPGA-based, granularity-variable neuromorphic processor (FBGVNP. The traits of FBGVNP can be summarized as granularity variability, scalability, integrated computing, and addressing ability: first, the number of neurons is variable rather than constant in one core; second, the multi-core network scale can be extended in various forms; third, the neuron addressing and computing processes are executed simultaneously. These make the processor more flexible and better suited for different applications. Moreover, a neural network-based controller is mapped to FBGVNP and applied in a multi-input, multi-output, (MIMO real-time, temperature-sensing and control system. Experiments validate the effectiveness of the neuromorphic processor. The FBGVNP provides a new scheme for building ANNs, which is flexible, highly energy-efficient, and can be applied in many areas.

  18. Neuromorphic atomic switch networks.

    Directory of Open Access Journals (Sweden)

    Audrius V Avizienis

    Full Text Available Efforts to emulate the formidable information processing capabilities of the brain through neuromorphic engineering have been bolstered by recent progress in the fabrication of nonlinear, nanoscale circuit elements that exhibit synapse-like operational characteristics. However, conventional fabrication techniques are unable to efficiently generate structures with the highly complex interconnectivity found in biological neuronal networks. Here we demonstrate the physical realization of a self-assembled neuromorphic device which implements basic concepts of systems neuroscience through a hardware-based platform comprised of over a billion interconnected atomic-switch inorganic synapses embedded in a complex network of silver nanowires. Observations of network activation and passive harmonic generation demonstrate a collective response to input stimulus in agreement with recent theoretical predictions. Further, emergent behaviors unique to the complex network of atomic switches and akin to brain function are observed, namely spatially distributed memory, recurrent dynamics and the activation of feedforward subnetworks. These devices display the functional characteristics required for implementing unconventional, biologically and neurally inspired computational methodologies in a synthetic experimental system.

  19. Foundations of Neuromorphic Computing

    Science.gov (United States)

    2013-05-01

    paradigms: few sensors/complex computations and many sensors/simple computation. Challenges with Nano-enabled Neuromorphic Chips A wide variety of...FOUNDATIONS OF NEUROMORPHIC COMPUTING MAY 2013 FINAL TECHNICAL REPORT APPROVED FOR PUBLIC RELEASE; DISTRIBUTION...2009 – SEP 2012 4. TITLE AND SUBTITLE FOUNDATIONS OF NEUROMORPHIC COMPUTING 5a. CONTRACT NUMBER IN-HOUSE 5b. GRANT NUMBER N/A 5c. PROGRAM

  20. Neuromorphic VLSI Models of Selective Attention: From Single Chip Vision Sensors to Multi-chip Systems

    OpenAIRE

    Giacomo Indiveri

    2008-01-01

    Biological organisms perform complex selective attention operations continuously and effortlessly. These operations allow them to quickly determine the motor actions to take in response to combinations of external stimuli and internal states, and to pay attention to subsets of sensory inputs suppressing non salient ones. Selective attention strategies are extremely effective in both natural and artificial systems which have to cope with large amounts of input data and have limited computation...

  1. Neuromorphic Modeling of Moving Target Detection in Insects

    Science.gov (United States)

    2007-12-31

    Standard Form 298 (Rev. 8/98) Prescribed by ANSI Std. Z39, 18 Grants FA9550-04-1-0283 and FA9550-04-1-0294 Neuromorphic Modeling of Moving Target Detection...natural for neuromorphic sensory processing. We developed visual motion detection circuitry, including photodetectors, early vision, and models for both...Lincoln Labs 3DM2 run, Tanner Research reserved and utilized space corresponding to two MOSIS ’tiny chips ’ (2mm square each), each with three interconnected

  2. Neuromorphic Silicon Neuron Circuits

    Science.gov (United States)

    Indiveri, Giacomo; Linares-Barranco, Bernabé; Hamilton, Tara Julia; van Schaik, André; Etienne-Cummings, Ralph; Delbruck, Tobi; Liu, Shih-Chii; Dudek, Piotr; Häfliger, Philipp; Renaud, Sylvie; Schemmel, Johannes; Cauwenberghs, Gert; Arthur, John; Hynna, Kai; Folowosele, Fopefolu; Saighi, Sylvain; Serrano-Gotarredona, Teresa; Wijekoon, Jayawan; Wang, Yingxue; Boahen, Kwabena

    2011-01-01

    Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain–machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this paper we describe the most common building blocks and techniques used to implement these circuits, and present an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance-based Hodgkin–Huxley models to bi-dimensional generalized adaptive integrate and fire models. We compare the different design methodologies used for each silicon neuron design described, and demonstrate their features with experimental results, measured from a wide range of fabricated VLSI chips. PMID:21747754

  3. Neuromorphic silicon neuron circuits

    Directory of Open Access Journals (Sweden)

    Giacomo eIndiveri

    2011-05-01

    Full Text Available Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain-machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this paper we describe the most common building blocks and techniques used to implement these circuits, and present an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance based Hodgkin-Huxley models to bi-dimensional generalized adaptive Integrate and Fire models. We compare the different design methodologies used for each silicon neuron design described, and demonstrate their features with experimental results, measured from a wide range of fabricated VLSI chips.

  4. A Low-Power High-Speed Spintronics-Based Neuromorphic Computing System Using Real Time Tracking Method

    DEFF Research Database (Denmark)

    Farkhani, Hooman; Tohidi, Mohammad; Farkhani, Sadaf

    2018-01-01

    In spintronic-based neuromorphic computing systems (NCS), the switching of magnetic moment in a magnetic tunnel junction (MTJ) is used to mimic neuron firing. However, the stochastic switching behavior of the MTJ and process variations effect lead to a significant increase in stimulation time...... of such NCSs. Moreover, current NCSs need an extra phase to read the MTJ state after stimulation which is in contrast with real neuron functionality in human body. In this paper, the read circuit is replaced with a proposed real-time sensing (RTS) circuit. The RTS circuit tracks the MTJ state during...... stimulation phase. As soon as switching happens, the RTS circuit terminates the MTJ current and stimulates the post neuron. Hence, the RTS circuit not only improves the energy consumption and speed, but also makes the operation of NCS similar to real neuron functionality. The simulation results in 65-nm CMOS...

  5. Neuromorphic walking gait control.

    Science.gov (United States)

    Still, Susanne; Hepp, Klaus; Douglas, Rodney J

    2006-03-01

    We present a neuromorphic pattern generator for controlling the walking gaits of four-legged robots which is inspired by central pattern generators found in the nervous system and which is implemented as a very large scale integrated (VLSI) chip. The chip contains oscillator circuits that mimic the output of motor neurons in a strongly simplified way. We show that four coupled oscillators can produce rhythmic patterns with phase relationships that are appropriate to generate all four-legged animal walking gaits. These phase relationships together with frequency and duty cycle of the oscillators determine the walking behavior of a robot driven by the chip, and they depend on a small set of stationary bias voltages. We give analytic expressions for these dependencies. This chip reduces the complex, dynamic inter-leg control problem associated with walking gait generation to the problem of setting a few stationary parameters. It provides a compact and low power solution for walking gait control in robots.

  6. Foldable neuromorphic memristive electronics

    KAUST Repository

    Ghoneim, Mohamed T.; Zidan, Mohammed A.; Salama, Khaled N.; Hussain, Muhammad Mustafa

    2014-01-01

    foldable and densely integrated neuromorphic devices for non-volatile memory applications. We report the first ever memristive devices with the size of a motor neuron on bulk mono-crystalline silicon (100) and then with trench

  7. The human brain on a computer, the design neuromorphic chips aims to process information as does the mind

    International Nuclear Information System (INIS)

    Pajuelo, L.

    2015-01-01

    Develop chips that mimic the brain processes It will help create computers capable of interpreting information from image, sound and touch so that it may offer answers intelligent-not programmed before- according to these sensory data. chips neuromorphic may mimic the electrical activity neurons and brain synapses, and will be key to intelligence systems artificial (ia) that require interaction with the environment being able to extract information cognitive of what surrounds them. (Author)

  8. Parallel Evolutionary Optimization for Neuromorphic Network Training

    Energy Technology Data Exchange (ETDEWEB)

    Schuman, Catherine D [ORNL; Disney, Adam [University of Tennessee (UT); Singh, Susheela [North Carolina State University (NCSU), Raleigh; Bruer, Grant [University of Tennessee (UT); Mitchell, John Parker [University of Tennessee (UT); Klibisz, Aleksander [University of Tennessee (UT); Plank, James [University of Tennessee (UT)

    2016-01-01

    One of the key impediments to the success of current neuromorphic computing architectures is the issue of how best to program them. Evolutionary optimization (EO) is one promising programming technique; in particular, its wide applicability makes it especially attractive for neuromorphic architectures, which can have many different characteristics. In this paper, we explore different facets of EO on a spiking neuromorphic computing model called DANNA. We focus on the performance of EO in the design of our DANNA simulator, and on how to structure EO on both multicore and massively parallel computing systems. We evaluate how our parallel methods impact the performance of EO on Titan, the U.S.'s largest open science supercomputer, and BOB, a Beowulf-style cluster of Raspberry Pi's. We also focus on how to improve the EO by evaluating commonality in higher performing neural networks, and present the result of a study that evaluates the EO performed by Titan.

  9. Specialized Cilia in Mammalian Sensory Systems

    Directory of Open Access Journals (Sweden)

    Nathalie Falk

    2015-09-01

    Full Text Available Cilia and flagella are highly conserved and important microtubule-based organelles that project from the surface of eukaryotic cells and act as antennae to sense extracellular signals. Moreover, cilia have emerged as key players in numerous physiological, developmental, and sensory processes such as hearing, olfaction, and photoreception. Genetic defects in ciliary proteins responsible for cilia formation, maintenance, or function underlie a wide array of human diseases like deafness, anosmia, and retinal degeneration in sensory systems. Impairment of more than one sensory organ results in numerous syndromic ciliary disorders like the autosomal recessive genetic diseases Bardet-Biedl and Usher syndrome. Here we describe the structure and distinct functional roles of cilia in sensory organs like the inner ear, the olfactory epithelium, and the retina of the mouse. The spectrum of ciliary function in fundamental cellular processes highlights the importance of elucidating ciliopathy-related proteins in order to find novel potential therapies.

  10. Bioinspired sensory systems for local flow characterization

    Science.gov (United States)

    Colvert, Brendan; Chen, Kevin; Kanso, Eva

    2016-11-01

    Empirical evidence suggests that many aquatic organisms sense differential hydrodynamic signals.This sensory information is decoded to extract relevant flow properties. This task is challenging because it relies on local and partial measurements, whereas classical flow characterization methods depend on an external observer to reconstruct global flow fields. Here, we introduce a mathematical model in which a bioinspired sensory array measuring differences in local flow velocities characterizes the flow type and intensity. We linearize the flow field around the sensory array and express the velocity gradient tensor in terms of frame-independent parameters. We develop decoding algorithms that allow the sensory system to characterize the local flow and discuss the conditions under which this is possible. We apply this framework to the canonical problem of a circular cylinder in uniform flow, finding excellent agreement between sensed and actual properties. Our results imply that combining suitable velocity sensors with physics-based methods for decoding sensory measurements leads to a powerful approach for understanding and developing underwater sensory systems.

  11. Dynamic Neural Fields as a Step Towards Cognitive Neuromorphic Architectures

    Directory of Open Access Journals (Sweden)

    Yulia eSandamirskaya

    2014-01-01

    Full Text Available Dynamic Field Theory (DFT is an established framework for modelling embodied cognition. In DFT, elementary cognitive functions such as memory formation, formation of grounded representations, attentional processes, decision making, adaptation, and learning emerge from neuronal dynamics. The basic computational element of this framework is a Dynamic Neural Field (DNF. Under constraints on the time-scale of the dynamics, the DNF is computationally equivalent to a soft winner-take-all (WTA network, which is considered one of the basic computational units in neuronal processing. Recently, it has been shown how a WTA network may be implemented in neuromorphic hardware, such as analogue Very Large Scale Integration (VLSI device. This paper leverages the relationship between DFT and soft WTA networks to systematically revise and integrate established DFT mechanisms that have previously been spread among different architectures. In addition, I also identify some novel computational and architectural mechanisms of DFT which may be implemented in neuromorphic VLSI devices using WTA networks as an intermediate computational layer. These specific mechanisms include the stabilization of working memory, the coupling of sensory systems to motor dynamics, intentionality, and autonomous learning. I further demonstrate how all these elements may be integrated into a unified architecture to generate behavior and autonomous learning.

  12. Progress in neuromorphic photonics

    Science.gov (United States)

    Ferreira de Lima, Thomas; Shastri, Bhavin J.; Tait, Alexander N.; Nahmias, Mitchell A.; Prucnal, Paul R.

    2017-03-01

    As society's appetite for information continues to grow, so does our need to process this information with increasing speed and versatility. Many believe that the one-size-fits-all solution of digital electronics is becoming a limiting factor in certain areas such as data links, cognitive radio, and ultrafast control. Analog photonic devices have found relatively simple signal processing niches where electronics can no longer provide sufficient speed and reconfigurability. Recently, the landscape for commercially manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. By bridging the mathematical prowess of artificial neural networks to the underlying physics of optoelectronic devices, neuromorphic photonics could breach new domains of information processing demanding significant complexity, low cost, and unmatched speed. In this article, we review the progress in neuromorphic photonics, focusing on photonic integrated devices. The challenges and design rules for optoelectronic instantiation of artificial neurons are presented. The proposed photonic architecture revolves around the processing network node composed of two parts: a nonlinear element and a network interface. We then survey excitable lasers in the recent literature as candidates for the nonlinear node and microring-resonator weight banks as the network interface. Finally, we compare metrics between neuromorphic electronics and neuromorphic photonics and discuss potential applications.

  13. Sensory reactivity, empathizing and systemizing in autism spectrum conditions and sensory processing disorder

    Directory of Open Access Journals (Sweden)

    Teresa Tavassoli

    2018-01-01

    Full Text Available Although the DSM-5 added sensory symptoms as a criterion for ASC, there is a group of children who display sensory symptoms but do not have ASC; children with sensory processing disorder (SPD. To be able to differentiate these two disorders, our aim was to evaluate whether children with ASC show more sensory symptomatology and/or different cognitive styles in empathy and systemizing compared to children with SPD and typically developing (TD children. The study included 210 participants: 68 children with ASC, 79 with SPD and 63 TD children. The Sensory Processing Scale Inventory was used to measure sensory symptoms, the Autism Spectrum Quotient (AQ to measure autistic traits, and the Empathy Quotient (EQ and Systemizing Quotient (SQ to measure cognitive styles. Across groups, a greater sensory symptomatology was associated with lower empathy. Further, both the ASC and SPD groups showed more sensory symptoms than TD children. Children with ASC and SPD only differed on sensory under-reactivity. The ASD group did, however, show lower empathy and higher systemizing scores than the SPD group. Together, this suggest that sensory symptoms alone may not be adequate to differentiate children with ASC and SPD but that cognitive style measures could be used for differential diagnosis. Keywords: Autism spectrum conditions, Sensory processing disorder, Sensory symptoms, Empathy, Systemizing

  14. The human brain on a computer, the design neuromorphic chips aims to process information as does the mind; El cerebro humano en un ordenador

    Energy Technology Data Exchange (ETDEWEB)

    Pajuelo, L.

    2015-07-01

    Develop chips that mimic the brain processes It will help create computers capable of interpreting information from image, sound and touch so that it may offer answers intelligent-not programmed before- according to these sensory data. chips neuromorphic may mimic the electrical activity neurons and brain synapses, and will be key to intelligence systems artificial (ia) that require interaction with the environment being able to extract information cognitive of what surrounds them. (Author)

  15. Delay dynamics of neuromorphic optoelectronic nanoscale resonators: Perspectives and applications

    OpenAIRE

    Romeira, B.; Figueiredo, J. M. L.; Javaloyes, J.

    2017-01-01

    With the recent exponential growth of applications using artificial intelligence (AI), the development of efficient and ultrafast brain-like (neuromorphic) systems is crucial for future information and communication technologies. While the implementation of AI systems using computer algorithms of neural networks is emerging rapidly, scientists are just taking the very first steps in the development of the hardware elements of an artificial brain, specifically neuromorphic microchips. In this ...

  16. Foldable neuromorphic memristive electronics

    KAUST Repository

    Ghoneim, Mohamed T.

    2014-07-01

    Neuromorphic computer will need folded architectural form factor to match brain cortex\\'s folded pattern for ultra-compact design. In this work, we show a state-of-the-art CMOS compatible pragmatic fabrication approach of building structurally foldable and densely integrated neuromorphic devices for non-volatile memory applications. We report the first ever memristive devices with the size of a motor neuron on bulk mono-crystalline silicon (100) and then with trench-protect-release-recycle process transform the silicon wafer with devices into a flexible and semi-transparent silicon fabric while recycling the remaining wafer for further use. This process unconditionally offers the ultra-large-scale-integration opportunity-increasingly critical for ultra-compact memory.

  17. Neuromorphic Deep Learning Machines

    OpenAIRE

    Neftci, E; Augustine, C; Paul, S; Detorakis, G

    2017-01-01

    An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Back Propagation (BP) rule, often relies on the immediate availability of network-wide...

  18. Memristor-Based Synapse Design and Training Scheme for Neuromorphic Computing Architecture

    Science.gov (United States)

    2012-06-01

    system level built upon the conventional Von Neumann computer architecture [2][3]. Developing the neuromorphic architecture at chip level by...SCHEME FOR NEUROMORPHIC COMPUTING ARCHITECTURE 5a. CONTRACT NUMBER FA8750-11-2-0046 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER 62788F 6...creation of memristor-based neuromorphic computing architecture. Rather than the existing crossbar-based neuron network designs, we focus on memristor

  19. Adaptive stimulus optimization for sensory systems neuroscience

    OpenAIRE

    DiMattina, Christopher; Zhang, Kechen

    2013-01-01

    In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system...

  20. Toward exascale computing through neuromorphic approaches.

    Energy Technology Data Exchange (ETDEWEB)

    James, Conrad D.

    2010-09-01

    While individual neurons function at relatively low firing rates, naturally-occurring nervous systems not only surpass manmade systems in computing power, but accomplish this feat using relatively little energy. It is asserted that the next major breakthrough in computing power will be achieved through application of neuromorphic approaches that mimic the mechanisms by which neural systems integrate and store massive quantities of data for real-time decision making. The proposed LDRD provides a conceptual foundation for SNL to make unique advances toward exascale computing. First, a team consisting of experts from the HPC, MESA, cognitive and biological sciences and nanotechnology domains will be coordinated to conduct an exercise with the outcome being a concept for applying neuromorphic computing to achieve exascale computing. It is anticipated that this concept will involve innovative extension and integration of SNL capabilities in MicroFab, material sciences, high-performance computing, and modeling and simulation of neural processes/systems.

  1. A functional hybrid memristor crossbar-array/CMOS system for data storage and neuromorphic applications.

    Science.gov (United States)

    Kim, Kuk-Hwan; Gaba, Siddharth; Wheeler, Dana; Cruz-Albrecht, Jose M; Hussain, Tahir; Srinivasa, Narayan; Lu, Wei

    2012-01-11

    Crossbar arrays based on two-terminal resistive switches have been proposed as a leading candidate for future memory and logic applications. Here we demonstrate a high-density, fully operational hybrid crossbar/CMOS system composed of a transistor- and diode-less memristor crossbar array vertically integrated on top of a CMOS chip by taking advantage of the intrinsic nonlinear characteristics of the memristor element. The hybrid crossbar/CMOS system can reliably store complex binary and multilevel 1600 pixel bitmap images using a new programming scheme. © 2011 American Chemical Society

  2. Adaptive stimulus optimization for sensory systems neuroscience.

    Science.gov (United States)

    DiMattina, Christopher; Zhang, Kechen

    2013-01-01

    In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system identification paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of non-linear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify non-linear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and toward a new paradigm of real-time model estimation and comparison.

  3. Neuron Design in Neuromorphic Computing Systems and Its Application in Wireless Communications

    Science.gov (United States)

    2017-03-01

    26 21 Measurement Results of Two Samples……………………………………………………….26 22 Normalized Verification Value……………………………………………………………….27 23...currently the most popular choice, and has been adopted in modern Long-Term Evolution ( LTE )/ LTE -Advanced systems. The result of this task included a...reviews, a final technical report, as well as the following items: • Circuit design, fabrication, and measurement materials including SPICE (Simulation

  4. Proprioceptive Feedback through a Neuromorphic Muscle Spindle Model

    Directory of Open Access Journals (Sweden)

    Lorenzo Vannucci

    2017-06-01

    Full Text Available Connecting biologically inspired neural simulations to physical or simulated embodiments can be useful both in robotics, for the development of a new kind of bio-inspired controllers, and in neuroscience, to test detailed brain models in complete action-perception loops. The aim of this work is to develop a fully spike-based, biologically inspired mechanism for the translation of proprioceptive feedback. The translation is achieved by implementing a computational model of neural activity of type Ia and type II afferent fibers of muscle spindles, the primary source of proprioceptive information, which, in mammals is regulated through fusimotor activation and provides necessary adjustments during voluntary muscle contractions. As such, both static and dynamic γ-motoneurons activities are taken into account in the proposed model. Information from the actual proprioceptive sensors (i.e., motor encoders is then used to simulate the spindle contraction and relaxation, and therefore drive the neural activity. To assess the feasibility of this approach, the model is implemented on the NEST spiking neural network simulator and on the SpiNNaker neuromorphic hardware platform and tested on simulated and physical robotic platforms. The results demonstrate that the model can be used in both simulated and real-time robotic applications to translate encoder values into a biologically plausible neural activity. Thus, this model provides a completely spike-based building block, suitable for neuromorphic platforms, that will enable the development of sensory-motor closed loops which could include neural simulations of areas of the central nervous system or of low-level reflexes.

  5. Complete functional characterization of sensory neurons by system identification.

    Science.gov (United States)

    Wu, Michael C-K; David, Stephen V; Gallant, Jack L

    2006-01-01

    System identification is a growing approach to sensory neurophysiology that facilitates the development of quantitative functional models of sensory processing. This approach provides a clear set of guidelines for combining experimental data with other knowledge about sensory function to obtain a description that optimally predicts the way that neurons process sensory information. This prediction paradigm provides an objective method for evaluating and comparing computational models. In this chapter we review many of the system identification algorithms that have been used in sensory neurophysiology, and we show how they can be viewed as variants of a single statistical inference problem. We then review many of the practical issues that arise when applying these methods to neurophysiological experiments: stimulus selection, behavioral control, model visualization, and validation. Finally we discuss several problems to which system identification has been applied recently, including one important long-term goal of sensory neuroscience: developing models of sensory systems that accurately predict neuronal responses under completely natural conditions.

  6. Detection of Visual Events in Underwater Video Using a Neuromorphic Saliency-based Attention System

    Science.gov (United States)

    Edgington, D. R.; Walther, D.; Cline, D. E.; Sherlock, R.; Salamy, K. A.; Wilson, A.; Koch, C.

    2003-12-01

    The Monterey Bay Aquarium Research Institute (MBARI) uses high-resolution video equipment on remotely operated vehicles (ROV) to obtain quantitative data on the distribution and abundance of oceanic animals. High-quality video data supplants the traditional approach of assessing the kinds and numbers of animals in the oceanic water column through towing collection nets behind ships. Tow nets are limited in spatial resolution, and often destroy abundant gelatinous animals resulting in species undersampling. Video camera-based quantitative video transects (QVT) are taken through the ocean midwater, from 50m to 4000m, and provide high-resolution data at the scale of the individual animals and their natural aggregation patterns. However, the current manual method of analyzing QVT video by trained scientists is labor intensive and poses a serious limitation to the amount of information that can be analyzed from ROV dives. Presented here is an automated system for detecting marine animals (events) visible in the videos. Automated detection is difficult due to the low contrast of many translucent animals and due to debris ("marine snow") cluttering the scene. Video frames are processed with an artificial intelligence attention selection algorithm that has proven a robust means of target detection in a variety of natural terrestrial scenes. The candidate locations identified by the attention selection module are tracked across video frames using linear Kalman filters. Typically, the occurrence of visible animals in the video footage is sparse in space and time. A notion of "boring" video frames is developed by detecting whether or not there is an interesting candidate object for an animal present in a particular sequence of underwater video -- video frames that do not contain any "interesting" events. If objects can be tracked successfully over several frames, they are stored as potentially "interesting" events. Based on low-level properties, interesting events are

  7. STDP and STDP Variations with Memristors for Spiking Neuromorphic Learning Systems

    Directory of Open Access Journals (Sweden)

    Teresa eSerrano-Gotarredona

    2013-02-01

    Full Text Available In this paper we review several ways of realizing asynchronous Spike-Timing Dependent Plasticity (STDP using memristors as synapses. Our focus is on how to use individual memristors to implement synaptic weight multiplications, in a way such that it is not necessary to (a introduce global synchronization and (b to separate memristor learning phases from memristor performing phases. In the approaches described, neurons fire spikes asynchronously when they wish and memristive synapses perform computation and learn at their own pace, as it happens in biological neural systems. We distinguish between two different memristor physics, depending on whether they respond to the original ``moving wall'' or to the ``filament creation and annihilation'' models. Independent of the memristor physics, we discuss two different types of STDP rules that can be implemented with memristors: either the pure timing-based rule that takes into account the arrival time of the spikes from the pre- and the post-synaptic neurons, or a hybrid rule that takes into account only the timing of pre-synaptic spikes and the membrane potential and other state variables of the post-synaptic neuron. We show how to implement these rules in cross-bar architectures that comprise massive arrays of memristors, and we discuss applications for artificial vision.

  8. Neuromorphic implementations of neurobiological learning algorithms for spiking neural networks.

    Science.gov (United States)

    Walter, Florian; Röhrbein, Florian; Knoll, Alois

    2015-12-01

    The application of biologically inspired methods in design and control has a long tradition in robotics. Unlike previous approaches in this direction, the emerging field of neurorobotics not only mimics biological mechanisms at a relatively high level of abstraction but employs highly realistic simulations of actual biological nervous systems. Even today, carrying out these simulations efficiently at appropriate timescales is challenging. Neuromorphic chip designs specially tailored to this task therefore offer an interesting perspective for neurorobotics. Unlike Von Neumann CPUs, these chips cannot be simply programmed with a standard programming language. Like real brains, their functionality is determined by the structure of neural connectivity and synaptic efficacies. Enabling higher cognitive functions for neurorobotics consequently requires the application of neurobiological learning algorithms to adjust synaptic weights in a biologically plausible way. In this paper, we therefore investigate how to program neuromorphic chips by means of learning. First, we provide an overview over selected neuromorphic chip designs and analyze them in terms of neural computation, communication systems and software infrastructure. On the theoretical side, we review neurobiological learning techniques. Based on this overview, we then examine on-die implementations of these learning algorithms on the considered neuromorphic chips. A final discussion puts the findings of this work into context and highlights how neuromorphic hardware can potentially advance the field of autonomous robot systems. The paper thus gives an in-depth overview of neuromorphic implementations of basic mechanisms of synaptic plasticity which are required to realize advanced cognitive capabilities with spiking neural networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. A Review of Current Neuromorphic Approaches for Vision, Auditory, and Olfactory Sensors.

    Science.gov (United States)

    Vanarse, Anup; Osseiran, Adam; Rassau, Alexander

    2016-01-01

    Conventional vision, auditory, and olfactory sensors generate large volumes of redundant data and as a result tend to consume excessive power. To address these shortcomings, neuromorphic sensors have been developed. These sensors mimic the neuro-biological architecture of sensory organs using aVLSI (analog Very Large Scale Integration) and generate asynchronous spiking output that represents sensing information in ways that are similar to neural signals. This allows for much lower power consumption due to an ability to extract useful sensory information from sparse captured data. The foundation for research in neuromorphic sensors was laid more than two decades ago, but recent developments in understanding of biological sensing and advanced electronics, have stimulated research on sophisticated neuromorphic sensors that provide numerous advantages over conventional sensors. In this paper, we review the current state-of-the-art in neuromorphic implementation of vision, auditory, and olfactory sensors and identify key contributions across these fields. Bringing together these key contributions we suggest a future research direction for further development of the neuromorphic sensing field.

  10. Processing of Sensory Information in the Olfactory System

    DEFF Research Database (Denmark)

    The olfactory system is an attractive model system due to the easy control of sensory input and the experimental accessibility in animal studies. The odorant signals are processed from receptor neurons to a neural network of mitral and granular cells while various types of nonlinear behaviour can...... and equation-free techniques allow for a better reproduction and understanding of recent experimental findings. Talks: Olfaction as a Model System for Sensory-Processing Neural Networks (Jens Midtgaard, University of Copenhagen, Denmark) Nonlinear Effects of Signal Transduction in Olfactory Sensory Neurons...

  11. An Application Development Platform for Neuromorphic Computing

    Energy Technology Data Exchange (ETDEWEB)

    Dean, Mark [University of Tennessee (UT); Chan, Jason [University of Tennessee (UT); Daffron, Christopher [University of Tennessee (UT); Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT); Rose, Garrett [University of Tennessee (UT); Plank, James [University of Tennessee (UT); Birdwell, John Douglas [University of Tennessee (UT); Schuman, Catherine D [ORNL

    2016-01-01

    Dynamic Adaptive Neural Network Arrays (DANNAs) are neuromorphic computing systems developed as a hardware based approach to the implementation of neural networks. They feature highly adaptive and programmable structural elements, which model arti cial neural networks with spiking behavior. We design them to solve problems using evolutionary optimization. In this paper, we highlight the current hardware and software implementations of DANNA, including their features, functionalities and performance. We then describe the development of an Application Development Platform (ADP) to support efficient application implementation and testing of DANNA based solutions. We conclude with future directions.

  12. Sensory system plasticity in a visually specialized, nocturnal spider.

    Science.gov (United States)

    Stafstrom, Jay A; Michalik, Peter; Hebets, Eileen A

    2017-04-21

    The interplay between an animal's environmental niche and its behavior can influence the evolutionary form and function of its sensory systems. While intraspecific variation in sensory systems has been documented across distant taxa, fewer studies have investigated how changes in behavior might relate to plasticity in sensory systems across developmental time. To investigate the relationships among behavior, peripheral sensory structures, and central processing regions in the brain, we take advantage of a dramatic within-species shift of behavior in a nocturnal, net-casting spider (Deinopis spinosa), where males cease visually-mediated foraging upon maturation. We compared eye diameters and brain region volumes across sex and life stage, the latter through micro-computed X-ray tomography. We show that mature males possess altered peripheral visual morphology when compared to their juvenile counterparts, as well as juvenile and mature females. Matching peripheral sensory structure modifications, we uncovered differences in relative investment in both lower-order and higher-order processing regions in the brain responsible for visual processing. Our study provides evidence for sensory system plasticity when individuals dramatically change behavior across life stages, uncovering new avenues of inquiry focusing on altered reliance of specific sensory information when entering a new behavioral niche.

  13. A bidirectional brain-machine interface featuring a neuromorphic hardware decoder

    Directory of Open Access Journals (Sweden)

    Fabio Boi

    2016-12-01

    Full Text Available Bidirectional brain-machine interfaces (BMIs establish a two-way direct communication link4 between the brain and the external world. A decoder translates recorded neural activity into motor5 commands and an encoder delivers sensory information collected from the environment directly6 to the brain creating a closed-loop system. These two modules are typically integrated in bulky7 external devices. However, the clinical support of patients with severe motor and sensory deficits8 requires compact, low-power, and fully implantable systems that can decode neural signals to9 control external devices. As a first step toward this goal, we developed a modular bidirectional BMI10 setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented11 a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits.12 On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn13 to decode neural signals recorded from the brain into motor outputs controlling the movements14 of an external device. The modularity of the BMI allowed us to tune the individual components15 of the setup without modifying the whole system. In this paper we present the features of16 this modular BMI, and describe how we configured the network of spiking neuron circuits to17 implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm18 that connects bidirectionally the brain of an anesthetized rat with an external object. We show that19 the chip learned the decoding task correctly, allowing the interfaced brain to control the object’s20 trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is21 mature enough for the development of BMI modules that are sufficiently low-power and compact,22 while being highly computationally powerful and adaptive.

  14. A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder.

    Science.gov (United States)

    Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro

    2016-01-01

    Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive.

  15. All-memristive neuromorphic computing with level-tuned neurons

    Science.gov (United States)

    Pantazi, Angeliki; Woźniak, Stanisław; Tuma, Tomas; Eleftheriou, Evangelos

    2016-09-01

    In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from many sources. Brain-inspired neuromorphic computing systems increasingly attract research interest as an alternative to the classical von Neumann processor architecture, mainly because of the coexistence of memory and processing units. In these systems, the basic components are neurons interconnected by synapses. The neurons, based on their nonlinear dynamics, generate spikes that provide the main communication mechanism. The computational tasks are distributed across the neural network, where synapses implement both the memory and the computational units, by means of learning mechanisms such as spike-timing-dependent plasticity. In this work, we present an all-memristive neuromorphic architecture comprising neurons and synapses realized by using the physical properties and state dynamics of phase-change memristors. The architecture employs a novel concept of interconnecting the neurons in the same layer, resulting in level-tuned neuronal characteristics that preferentially process input information. We demonstrate the proposed architecture in the tasks of unsupervised learning and detection of multiple temporal correlations in parallel input streams. The efficiency of the neuromorphic architecture along with the homogenous neuro-synaptic dynamics implemented with nanoscale phase-change memristors represent a significant step towards the development of ultrahigh-density neuromorphic co-processors.

  16. All-memristive neuromorphic computing with level-tuned neurons.

    Science.gov (United States)

    Pantazi, Angeliki; Woźniak, Stanisław; Tuma, Tomas; Eleftheriou, Evangelos

    2016-09-02

    In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from many sources. Brain-inspired neuromorphic computing systems increasingly attract research interest as an alternative to the classical von Neumann processor architecture, mainly because of the coexistence of memory and processing units. In these systems, the basic components are neurons interconnected by synapses. The neurons, based on their nonlinear dynamics, generate spikes that provide the main communication mechanism. The computational tasks are distributed across the neural network, where synapses implement both the memory and the computational units, by means of learning mechanisms such as spike-timing-dependent plasticity. In this work, we present an all-memristive neuromorphic architecture comprising neurons and synapses realized by using the physical properties and state dynamics of phase-change memristors. The architecture employs a novel concept of interconnecting the neurons in the same layer, resulting in level-tuned neuronal characteristics that preferentially process input information. We demonstrate the proposed architecture in the tasks of unsupervised learning and detection of multiple temporal correlations in parallel input streams. The efficiency of the neuromorphic architecture along with the homogenous neuro-synaptic dynamics implemented with nanoscale phase-change memristors represent a significant step towards the development of ultrahigh-density neuromorphic co-processors.

  17. Delay dynamics of neuromorphic optoelectronic nanoscale resonators: Perspectives and applications

    Science.gov (United States)

    Romeira, Bruno; Figueiredo, José M. L.; Javaloyes, Julien

    2017-11-01

    With the recent exponential growth of applications using artificial intelligence (AI), the development of efficient and ultrafast brain-like (neuromorphic) systems is crucial for future information and communication technologies. While the implementation of AI systems using computer algorithms of neural networks is emerging rapidly, scientists are just taking the very first steps in the development of the hardware elements of an artificial brain, specifically neuromorphic microchips. In this review article, we present the current state of the art of neuromorphic photonic circuits based on solid-state optoelectronic oscillators formed by nanoscale double barrier quantum well resonant tunneling diodes. We address, both experimentally and theoretically, the key dynamic properties of recently developed artificial solid-state neuron microchips with delayed perturbations and describe their role in the study of neural activity and regenerative memory. This review covers our recent research work on excitable and delay dynamic characteristics of both single and autaptic (delayed) artificial neurons including all-or-none response, spike-based data encoding, storage, signal regeneration and signal healing. Furthermore, the neural responses of these neuromorphic microchips display all the signatures of extended spatio-temporal localized structures (LSs) of light, which are reviewed here in detail. By taking advantage of the dissipative nature of LSs, we demonstrate potential applications in optical data reconfiguration and clock and timing at high-speeds and with short transients. The results reviewed in this article are a key enabler for the development of high-performance optoelectronic devices in future high-speed brain-inspired optical memories and neuromorphic computing.

  18. Sensor selection and chemo-sensory optimization: toward an adaptable chemo-sensory system

    Directory of Open Access Journals (Sweden)

    Alexander eVergara

    2012-01-01

    Full Text Available Over the past two decades, despite the tremendous research effort performed on chemical sensors and machine olfaction to develop micro-sensory systems that will accomplish the growing existent needs in personal health (implantable sensors, environment monitoring (widely distributed sensor networks, and security/threat detection (chemo/bio warfare agents, simple, low-cost molecular sensing platforms capable of long-term autonomous operation remain beyond the current state-of-the-art of chemical sensing. A fundamental issue within this context is that most of the chemical sensors depend on interactions between the targeted species and the surfaces functionalized with receptors that bind the target species selectively, and that these binding events are coupled with transduction processes that begin to change when they are exposed to the messy world of real samples. With the advent of fundamental breakthroughs at the intersection of materials science, micro/nano-technology, and signal processing, hybrid chemo-sensory systems have incorporated tunable, optimizable operating parameters, through which changes in the response characteristics can be modeled and compensated as the environmental conditions or application needs change.The objective of this article, in this context, is to bring together the key advances at the device, data processing, and system levels that enable chemo-sensory systems to adapt in response to their environments. Accordingly, in this review we will feature the research effort made by selected experts on chemical sensing and information theory, whose work has been devoted to develop strategies that provide tunability and adaptability to single sensor devices or sensory array systems. Particularly, we consider sensor-array selection, modulation of internal sensing parameters, and active sensing. The article ends with some conclusions drawn from the results presented and a visionary look toward the future in terms of how the

  19. A neuromorphic controller for a robotic vehicle equipped with a dynamic vision sensor

    OpenAIRE

    Blum, Hermann; Dietmüller, Alexander; Milde, Moritz; Conradt, Jörg; Indiveri, Giacomo; Sandamirskaya, Yulia

    2017-01-01

    Neuromorphic electronic systems exhibit advantageous characteristics, in terms of low energy consumption and low response latency, which can be useful in robotic applications that require compact and low power embedded computing resources. However, these neuromorphic circuits still face significant limitations that make their usage challenging: these include low precision, variability of components, sensitivity to noise and temperature drifts, as well as the currently limited number of neuron...

  20. [The mirror neuron system in motor and sensory rehabilitation].

    Science.gov (United States)

    Oouchida, Yutaka; Izumi, Shinichi

    2014-06-01

    The discovery of the mirror neuron system has dramatically changed the study of motor control in neuroscience. The mirror neuron system provides a conceptual framework covering the aspects of motor as well as sensory functions in motor control. Previous studies of motor control can be classified as studies of motor or sensory functions, and these two classes of studies appear to have advanced independently. In rehabilitation requiring motor learning, such as relearning movement after limb paresis, however, sensory information of feedback for motor output as well as motor command are essential. During rehabilitation from chronic pain, motor exercise is one of the most effective treatments for pain caused by dysfunction in the sensory system. In rehabilitation where total intervention unifying the motor and sensory aspects of motor control is important, learning through imitation, which is associated with the mirror neuron system can be effective and suitable. In this paper, we introduce the clinical applications of imitated movement in rehabilitation from motor impairment after brain damage and phantom limb pain after limb amputation.

  1. Digital characterization of a neuromorphic IRFPA

    Science.gov (United States)

    Caulfield, John T.; Fisher, John; Zadnik, Jerome A.; Mak, Ernest S.; Scribner, Dean A.

    1995-05-01

    This paper reports on the performance of the Neuromorphic IRFPA, the first IRFPA designed and fabricated to conduct temporal and spatial processing on the focal plane. The Neuromorphic IRFPA's unique on-chip processing capability can perform retina-like functions such as lateral inhibition and contrast enhancement, spatial and temporal filtering, image compression and edge enhancement, and logarithmic response. Previously, all evaluations of the Neuromorphic IRFPA camera have been performed on the analog video output. In the work leading up to this paper, the Neuromorphic was integrated to a digital recorder to collect quantitative laboratory and field data. This paper describes the operation and characterization of specific on-chip processes such as spatial and temporal kernel size control. The use of Neuromorphic on-chip processing in future IRFPAs is analyzed as applied to improving SNR via adaptive nonuniformity, charge handling, and dynamic range problems.

  2. Neuromorphic photonic networks using silicon photonic weight banks.

    Science.gov (United States)

    Tait, Alexander N; de Lima, Thomas Ferreira; Zhou, Ellen; Wu, Allie X; Nahmias, Mitchell A; Shastri, Bhavin J; Prucnal, Paul R

    2017-08-07

    Photonic systems for high-performance information processing have attracted renewed interest. Neuromorphic silicon photonics has the potential to integrate processing functions that vastly exceed the capabilities of electronics. We report first observations of a recurrent silicon photonic neural network, in which connections are configured by microring weight banks. A mathematical isomorphism between the silicon photonic circuit and a continuous neural network model is demonstrated through dynamical bifurcation analysis. Exploiting this isomorphism, a simulated 24-node silicon photonic neural network is programmed using "neural compiler" to solve a differential system emulation task. A 294-fold acceleration against a conventional benchmark is predicted. We also propose and derive power consumption analysis for modulator-class neurons that, as opposed to laser-class neurons, are compatible with silicon photonic platforms. At increased scale, Neuromorphic silicon photonics could access new regimes of ultrafast information processing for radio, control, and scientific computing.

  3. Six networks on a universal neuromorphic computing substrate

    Directory of Open Access Journals (Sweden)

    Thomas ePfeil

    2013-02-01

    Full Text Available In this study, we present a highly configurable neuromorphic computing substrate and use it for emulating several types of neural networks. At the heart of this system lies a mixed-signal chip, with analog implementations of neurons and synapses and digital transmission of action potentials. Major advantages of this emulation device, which has been explicitly designed as a universal neural network emulator, are its inherent parallelism and high acceleration factor compared to conventional computers. Its configurability allows the realization of almost arbitrary network topologies and the use of widely varied neuronal and synaptic parameters. Fixed-pattern noise inherent to analog circuitry is reduced by calibration routines. An integrated development environment allows neuroscientists to operate the device without any prior knowledge of neuromorphic circuit design. As a showcase for the capabilities of the system, we describe the successful emulation of six different neural networks which cover a broad spectrum of both structure and functionality.

  4. Six networks on a universal neuromorphic computing substrate.

    Science.gov (United States)

    Pfeil, Thomas; Grübl, Andreas; Jeltsch, Sebastian; Müller, Eric; Müller, Paul; Petrovici, Mihai A; Schmuker, Michael; Brüderle, Daniel; Schemmel, Johannes; Meier, Karlheinz

    2013-01-01

    In this study, we present a highly configurable neuromorphic computing substrate and use it for emulating several types of neural networks. At the heart of this system lies a mixed-signal chip, with analog implementations of neurons and synapses and digital transmission of action potentials. Major advantages of this emulation device, which has been explicitly designed as a universal neural network emulator, are its inherent parallelism and high acceleration factor compared to conventional computers. Its configurability allows the realization of almost arbitrary network topologies and the use of widely varied neuronal and synaptic parameters. Fixed-pattern noise inherent to analog circuitry is reduced by calibration routines. An integrated development environment allows neuroscientists to operate the device without any prior knowledge of neuromorphic circuit design. As a showcase for the capabilities of the system, we describe the successful emulation of six different neural networks which cover a broad spectrum of both structure and functionality.

  5. Binary Associative Memories as a Benchmark for Spiking Neuromorphic Hardware

    Directory of Open Access Journals (Sweden)

    Andreas Stöckel

    2017-08-01

    Full Text Available Large-scale neuromorphic hardware platforms, specialized computer systems for energy efficient simulation of spiking neural networks, are being developed around the world, for example as part of the European Human Brain Project (HBP. Due to conceptual differences, a universal performance analysis of these systems in terms of runtime, accuracy and energy efficiency is non-trivial, yet indispensable for further hard- and software development. In this paper we describe a scalable benchmark based on a spiking neural network implementation of the binary neural associative memory. We treat neuromorphic hardware and software simulators as black-boxes and execute exactly the same network description across all devices. Experiments on the HBP platforms under varying configurations of the associative memory show that the presented method allows to test the quality of the neuron model implementation, and to explain significant deviations from the expected reference output.

  6. Anthropomorphic reasoning about neuromorphic AGI safety

    Science.gov (United States)

    Jilk, David J.; Herd, Seth J.; Read, Stephen J.; O'Reilly, Randall C.

    2017-11-01

    One candidate approach to creating artificial general intelligence (AGI) is to imitate the essential computations of human cognition. This process is sometimes called 'reverse-engineering the brain' and the end product called 'neuromorphic.' We argue that, unlike with other approaches to AGI, anthropomorphic reasoning about behaviour and safety concerns is appropriate and crucial in a neuromorphic context. Using such reasoning, we offer some initial ideas to make neuromorphic AGI safer. In particular, we explore how basic drives that promote social interaction may be essential to the development of cognitive capabilities as well as serving as a focal point for human-friendly outcomes.

  7. Exploring the Homeostatic and Sensory Roles of the Immune System.

    Science.gov (United States)

    Marques, Rafael Elias; Marques, Pedro Elias; Guabiraba, Rodrigo; Teixeira, Mauro Martins

    2016-01-01

    Immunology developed under the notion of the immune system exists to fight pathogens. Recently, the discovery of interactions with commensal microbiota that are essential to human health initiated a change in this old paradigm. Here, we argue that the immune system has major physiological roles extending far beyond defending the host. Immune and inflammatory responses share the core property of sensing, defining the immune system also as a sensory system. The inference with the immune system collects, interprets, and stores information, while creating an identity of self, places it in close relationship to the nervous system, which suggests that these systems may have a profound evolutionary connection.

  8. Sensory systems II senses other than vision

    CERN Document Server

    Wolfe, Jeremy M

    1988-01-01

    This series of books, "Readings from the Encyclopedia of Neuroscience." consists of collections of subject-clustered articles taken from the Encyclopedia of Neuroscience. The Encyclopedia of Neuroscience is a reference source and compendium of more than 700 articles written by world authorities and covering all of neuroscience. We define neuroscience broadly as including all those fields that have as a primary goal the under­ standing of how the brain and nervous system work to mediate/control behavior, including the mental behavior of humans. Those interested in specific aspects of the neurosciences, particular subject areas or specialties, can of course browse through the alphabetically arranged articles of the En­ cyclopedia or use its index to find the topics they wish to read. However. for those readers-students, specialists, or others-who will find it useful to have collections of subject-clustered articles from the Encyclopedia, we issue this series of "Readings" in paperback. Students in neuroscienc...

  9. An MRI-compatible hand sensory vibrotactile system

    International Nuclear Information System (INIS)

    Wang, Fa; Lakshminarayanan, Kishor; Slota, Gregory P; Seo, Na Jin; Webster, John G

    2015-01-01

    Recently, the application of vibrotactile noise to the wrist or back of the hand has been shown to enhance fingertip tactile sensory perception (Enders et al 2013), supporting the potential for an assistive device worn at the wrist, that generates minute vibrations to help the elderly or patients with sensory deficit. However, knowledge regarding the detailed physiological mechanism behind this sensory improvement in the central nervous system, especially in the human brain, is limited, hindering progress in development and use of such assistive devices. To enable investigation of the impact of vibrotactile noise on sensorimotor brain activity in humans, a magnetic resonance imaging (MRI)-compatible vibrotactile system was developed to provide vibrotactile noise during an MRI of the brain. The vibrotactile system utilizes a remote (outside the MR room) signal amplifier which provides a voltage from –40 to +40 V to drive a 12 mm diameter piezoelectric vibrator (inside the MR room). It is portable and is found to be MRI-compatible which enables its use for neurologic investigation with MRI. The system was also found to induce an improvement in fingertip tactile sensation, consistent with the previous study. (note)

  10. Sensory evaluation of heating and air conditioning systems

    Energy Technology Data Exchange (ETDEWEB)

    Evin, F.; Siekierski, E. [Electricite de France, Research and Development Division, Les Renardieres, Moret Sur Loing (France)

    2002-07-01

    Existing standards and models, such as ISO 7730 or the work of Fanger [Thermal Comfort], are not sufficient to characterise the satisfaction and pleasantness of end-users provided by heating or air conditioning systems. For this reason Electricite de France (EDF) has initiated a project with the aim of using sensory evaluation techniques in the design of HVAC systems. Sensory evaluation has been used for more than 30 years in the food industry, and now involves the cosmetics, the phone and the automotive industries. It is based on a dual evaluation: sensation measurements carried out by a small panel of trained expert assessors; preference studies performed by a large panel of representative consumers. A correlation between the data of both studies is then used to explain the preferences in terms of sensations (preference mapping). The first experiments performed in 1999 and 2000 have provided lists of descriptors of thermal sensation and acoustic sensation associated with heating and air conditioning appliances. They show that it is possible to define discriminative descriptors, to train a panel and to reliably quantify these descriptors. It is then possible to draw the sensory profiles of different heating, ventilation and air conditioning (HVAC) systems. The future experimental laboratory that EDF has decided to build is also presented, where the trained panels and end-users will evaluate the sensations and the preferences of real systems in eight 'realistic environmental chambers' designed, furnished and decorated like offices and flats. (author)

  11. Neuromorphic UAS Collision Avoidance

    Data.gov (United States)

    National Aeronautics and Space Administration — Collision avoidance for unmanned aerial systems (UAS) traveling at high relative speeds is a challenging task. It requires both the detection of a possible collision...

  12. Full Wafer Redistribution and Wafer Embedding as Key Technologies for a Multi-Scale Neuromorphic Hardware Cluster

    OpenAIRE

    Zoschke, Kai; Güttler, Maurice; Böttcher, Lars; Grübl, Andreas; Husmann, Dan; Schemmel, Johannes; Meier, Karlheinz; Ehrmann, Oswin

    2018-01-01

    Together with the Kirchhoff-Institute for Physics(KIP) the Fraunhofer IZM has developed a full wafer redistribution and embedding technology as base for a large-scale neuromorphic hardware system. The paper will give an overview of the neuromorphic computing platform at the KIP and the associated hardware requirements which drove the described technological developments. In the first phase of the project standard redistribution technologies from wafer level packaging were adapted to enable a ...

  13. Neuromorphic Configurable Architecture for Robust Motion Estimation

    Directory of Open Access Journals (Sweden)

    Guillermo Botella

    2008-01-01

    Full Text Available The robustness of the human visual system recovering motion estimation in almost any visual situation is enviable, performing enormous calculation tasks continuously, robustly, efficiently, and effortlessly. There is obviously a great deal we can learn from our own visual system. Currently, there are several optical flow algorithms, although none of them deals efficiently with noise, illumination changes, second-order motion, occlusions, and so on. The main contribution of this work is the efficient implementation of a biologically inspired motion algorithm that borrows nature templates as inspiration in the design of architectures and makes use of a specific model of human visual motion perception: Multichannel Gradient Model (McGM. This novel customizable architecture of a neuromorphic robust optical flow can be constructed with FPGA or ASIC device using properties of the cortical motion pathway, constituting a useful framework for building future complex bioinspired systems running in real time with high computational complexity. This work includes the resource usage and performance data, and the comparison with actual systems. This hardware has many application fields like object recognition, navigation, or tracking in difficult environments due to its bioinspired and robustness properties.

  14. Serendipitous offline learning in a neuromorphic robot

    CSIR Research Space (South Africa)

    Stewart, TC

    2016-02-01

    Full Text Available ) by turning right if it is present at an intersection, and otherwise turning left. In general, this system can learn arbitrary relations between sensory input and motor behavior....

  15. Delay effects in the human sensory system during balancing.

    Science.gov (United States)

    Stepan, Gabor

    2009-03-28

    Mechanical models of human self-balancing often use the Newtonian equations of inverted pendula. While these mathematical models are precise enough on the mechanical side, the ways humans balance themselves are still quite unexplored on the control side. Time delays in the sensory and motoric neural pathways give essential limitations to the stabilization of the human body as a multiple inverted pendulum. The sensory systems supporting each other provide the necessary signals for these control tasks; but the more complicated the system is, the larger delay is introduced. Human ageing as well as our actual physical and mental state affects the time delays in the neural system, and the mechanical structure of the human body also changes in a large range during our lives. The human balancing organ, the labyrinth, and the vision system essentially adapted to these relatively large time delays and parameter regions occurring during balancing. The analytical study of the simplified large-scale time-delayed models of balancing provides a Newtonian insight into the functioning of these organs that may also serve as a basis to support theories and hypotheses on balancing and vision.

  16. Computational intelligence and neuromorphic computing potential for cybersecurity applications

    Science.gov (United States)

    Pino, Robinson E.; Shevenell, Michael J.; Cam, Hasan; Mouallem, Pierre; Shumaker, Justin L.; Edwards, Arthur H.

    2013-05-01

    In today's highly mobile, networked, and interconnected internet world, the flow and volume of information is overwhelming and continuously increasing. Therefore, it is believed that the next frontier in technological evolution and development will rely in our ability to develop intelligent systems that can help us process, analyze, and make-sense of information autonomously just as a well-trained and educated human expert. In computational intelligence, neuromorphic computing promises to allow for the development of computing systems able to imitate natural neurobiological processes and form the foundation for intelligent system architectures.

  17. Neuromorphic computing enabled by physics of electron spins: Prospects and perspectives

    Science.gov (United States)

    Sengupta, Abhronil; Roy, Kaushik

    2018-03-01

    “Spintronics” refers to the understanding of the physics of electron spin-related phenomena. While most of the significant advancements in this field has been driven primarily by memory, recent research has demonstrated that various facets of the underlying physics of spin transport and manipulation can directly mimic the functionalities of the computational primitives in neuromorphic computation, i.e., the neurons and synapses. Given the potential of these spintronic devices to implement bio-mimetic computations at very low terminal voltages, several spin-device structures have been proposed as the core building blocks of neuromorphic circuits and systems to implement brain-inspired computing. Such an approach is expected to play a key role in circumventing the problems of ever-increasing power dissipation and hardware requirements for implementing neuro-inspired algorithms in conventional digital CMOS technology. Perspectives on spin-enabled neuromorphic computing, its status, and challenges and future prospects are outlined in this review article.

  18. Neuromorphic meets neuromechanics, part I: the methodology and implementation

    Science.gov (United States)

    Niu, Chuanxin M.; Jalaleddini, Kian; Sohn, Won Joon; Rocamora, John; Sanger, Terence D.; Valero-Cuevas, Francisco J.

    2017-04-01

    Objective: One goal of neuromorphic engineering is to create ‘realistic’ robotic systems that interact with the physical world by adopting neuromechanical principles from biology. Critical to this is the methodology to implement the spinal circuitry responsible for the behavior of afferented muscles. At its core, muscle afferentation is the closed-loop behavior arising from the interactions among populations of muscle spindle afferents, alpha and gamma motoneurons, and muscle fibers to enable useful behaviors. Approach. We used programmable very- large-scale-circuit (VLSI) hardware to implement simple models of spiking neurons, skeletal muscles, muscle spindle proprioceptors, alpha-motoneuron recruitment, gamma motoneuron control of spindle sensitivity, and the monosynaptic circuitry connecting them. This multi-scale system of populations of spiking neurons emulated the physiological properties of a pair of antagonistic afferented mammalian muscles (each simulated by 1024 alpha- and gamma-motoneurones) acting on a joint via long tendons. Main results. This integrated system was able to maintain a joint angle, and reproduced stretch reflex responses even when driving the nonlinear biomechanics of an actual cadaveric finger. Moreover, this system allowed us to explore numerous values and combinations of gamma-static and gamma-dynamic gains when driving a robotic finger, some of which replicated some human pathological conditions. Lastly, we explored the behavioral consequences of adopting three alternative models of isometric muscle force production. We found that the dynamic responses to rate-coded spike trains produce force ramps that can be very sensitive to tendon elasticity, especially at high force output. Significance. Our methodology produced, to our knowledge, the first example of an autonomous, multi-scale, neuromorphic, neuromechanical system capable of creating realistic reflex behavior in cadaveric fingers. This research platform allows us to explore

  19. Neurophysiological aspects of the trigeminal sensory system: an update.

    Science.gov (United States)

    Van der Cruyssen, Frederic; Politis, Constantinus

    2018-02-23

    The trigeminal system is one of the most complex cranial nerve systems of the human body. Research on it has vastly grown in recent years and concentrated more and more on molecular mechanisms and pathophysiology, but thorough reviews on this topic are lacking, certainly on the normal physiology of the trigeminal sensory system. Here we review the current literature on neurophysiology of the trigeminal nerve from peripheral receptors up to its central projections toward the somatosensory cortex. We focus on the most recent scientific discoveries and describe historical relevant research to substantiate further. One chapter on new insights of the pathophysiology of pain at the level of the trigeminal system is added. A database search of Medline, Embase and Cochrane was conducted with the search terms 'animal study', 'neurophysiology', 'trigeminal', 'oral' and 'sensory'. Articles were manually selected after reading the abstract and where needed the article. Reference lists also served to include relevant research articles. Fifty-six articles were included after critical appraisal. Physiological aspects on mechanoreceptors, trigeminal afferents, trigeminal ganglion and central projections are reviewed in light of reference works. Embryologic and anatomic insights are cited where needed. A brief description of pathophysiology of pain pathways in the trigeminal area and recent advances in dental stem cell research are also discussed. Neurophysiology at the level of the central nervous system is not reviewed. The current body of knowledge is mainly based on animal and cadaveric studies, but recent advancements in functional imaging and molecular neuroscience are elucidating the pathways and functioning of this mixed nerve system. Extrapolation of animal studies or functioning of peripheral nerves should be warranted.

  20. Flexible Metal Oxide/Graphene Oxide Hybrid Neuromorphic Devices on Flexible Conducting Graphene Substrates

    OpenAIRE

    Wan, Chang Jin; Wang, Wei; Zhu, Li Qiang; Liu, Yang Hui; Feng, Ping; Liu, Zhao Ping; Shi, Yi; Wan, Qing

    2016-01-01

    Flexible metal oxide/graphene oxide hybrid multi-gate neuron transistors were fabricated on flexible graphene substrates. Dendritic integrations in both spatial and temporal modes were successfully emulated, and spatiotemporal correlated logics were obtained. A proof-of-principle visual system model for emulating lobula giant motion detector neuron was investigated. Our results are of great interest for flexible neuromorphic cognitive systems.

  1. Thermodynamic limits to information harvesting by sensory systems

    International Nuclear Information System (INIS)

    Bo, Stefano; Giudice, Marco Del; Celani, Antonio

    2015-01-01

    In view of the relation between information and thermodynamics we investigate how much information about an external protocol can be stored in the memory of a stochastic measurement device given an energy budget. We consider a layered device with a memory component storing information about the external environment by monitoring the history of a sensory part coupled to the environment. We derive an integral fluctuation theorem for the entropy production and a measure of the information accumulated in the memory device. Its most immediate consequence is that the amount of information is bounded by the average thermodynamic entropy produced by the process. At equilibrium no entropy is produced and therefore the memory device does not add any information about the environment to the sensory component. Consequently, if the system operates at equilibrium the addition of a memory component is superfluous. Such a device can be used to model the sensing process of a cell measuring the external concentration of a chemical compound and encoding the measurement in the amount of phosphorylated cytoplasmic proteins. (paper)

  2. The Specificity of Action Knowledge in Sensory and Motor Systems

    Directory of Open Access Journals (Sweden)

    Christine E Watson

    2014-05-01

    Full Text Available Neuroimaging studies have found that sensorimotor systems are engaged when participants observe actions or comprehend action language. However, most of these studies have asked the binary question of whether action concepts are embodied or not, rather than whether sensory and motor areas of the brain contain graded amounts of information during putative action simulations. To address this question, we used repetition suppression (RS functional magnetic resonance imaging to determine if functionally-localized motor movement and visual motion regions-of-interest (ROI and two anatomical ROIs (inferior frontal gyrus, IFG; left posterior middle temporal gyrus were sensitive to changes in the exemplar (e.g., two different people kicking or representational format (e.g., photograph or schematic drawing of someone kicking within pairs of action images. We also investigated whether concrete versus more symbolic depictions of actions (i.e., photographs versus schematic drawings yielded different patterns of activation throughout the brain. We found that during a conceptual task, sensory and motor systems represent actions at different levels of specificity. While the visual motion ROI did not exhibit RS to different exemplars of the same action or to the same action depicted by different formats, the motor movement ROI did. These effects are consistent with person-specific action simulations: if the motor system is recruited for action understanding, it does so by activating one’s own motor program for an action. We also observed significant repetition enhancement within the IFG ROI to different exemplars or formats of the same action, a result that may indicate additional cognitive processing on these trials. Finally, we found that the recruitment of posterior brain regions by action concepts depends on the format of the input: left lateral occipital cortex and right supramarginal gyrus responded more strongly to symbolic depictions of actions than

  3. A Scalable Multicore Architecture With Heterogeneous Memory Structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs).

    Science.gov (United States)

    Moradi, Saber; Qiao, Ning; Stefanini, Fabio; Indiveri, Giacomo

    2018-02-01

    Neuromorphic computing systems comprise networks of neurons that use asynchronous events for both computation and communication. This type of representation offers several advantages in terms of bandwidth and power consumption in neuromorphic electronic systems. However, managing the traffic of asynchronous events in large scale systems is a daunting task, both in terms of circuit complexity and memory requirements. Here, we present a novel routing methodology that employs both hierarchical and mesh routing strategies and combines heterogeneous memory structures for minimizing both memory requirements and latency, while maximizing programming flexibility to support a wide range of event-based neural network architectures, through parameter configuration. We validated the proposed scheme in a prototype multicore neuromorphic processor chip that employs hybrid analog/digital circuits for emulating synapse and neuron dynamics together with asynchronous digital circuits for managing the address-event traffic. We present a theoretical analysis of the proposed connectivity scheme, describe the methods and circuits used to implement such scheme, and characterize the prototype chip. Finally, we demonstrate the use of the neuromorphic processor with a convolutional neural network for the real-time classification of visual symbols being flashed to a dynamic vision sensor (DVS) at high speed.

  4. Physiological targets of artificial gravity: the sensory-motor system

    NARCIS (Netherlands)

    Groen, E.L.; Clarke, A.; Bles, W.; Wuyts, F.; Paloski, W.; Clément, G.

    2007-01-01

    This chapter describes the pros and cons of artificial gravity applications in relation to human sensory-motor functioning in space. Spaceflight creates a challenge for sensory-motor functions that depend on gravity, which include postural balance, locomotion, eye-hand coordination, and spatial

  5. A robust sound perception model suitable for neuromorphic implementation.

    Science.gov (United States)

    Coath, Martin; Sheik, Sadique; Chicca, Elisabetta; Indiveri, Giacomo; Denham, Susan L; Wennekers, Thomas

    2013-01-01

    We have recently demonstrated the emergence of dynamic feature sensitivity through exposure to formative stimuli in a real-time neuromorphic system implementing a hybrid analog/digital network of spiking neurons. This network, inspired by models of auditory processing in mammals, includes several mutually connected layers with distance-dependent transmission delays and learning in the form of spike timing dependent plasticity, which effects stimulus-driven changes in the network connectivity. Here we present results that demonstrate that the network is robust to a range of variations in the stimulus pattern, such as are found in naturalistic stimuli and neural responses. This robustness is a property critical to the development of realistic, electronic neuromorphic systems. We analyze the variability of the response of the network to "noisy" stimuli which allows us to characterize the acuity in information-theoretic terms. This provides an objective basis for the quantitative comparison of networks, their connectivity patterns, and learning strategies, which can inform future design decisions. We also show, using stimuli derived from speech samples, that the principles are robust to other challenges, such as variable presentation rate, that would have to be met by systems deployed in the real world. Finally we demonstrate the potential applicability of the approach to real sounds.

  6. A Robust Sound Perception Model Suitable for Neuromorphic Implementation

    Directory of Open Access Journals (Sweden)

    Martin eCoath

    2014-01-01

    Full Text Available We have recently demonstrated the emergence of dynamic feature sensitivity through exposure to formative stimuli in a real-time neuromorphic system implementing a hybrid analogue/digital network of spiking neurons. This network, inspired by models of auditory processing in mammals, includes several mutually connected layers with distance-dependent transmission delays and learning in the form of spike timing dependent plasticity, which effects stimulus-driven changes in the network connectivity.Here we present results that demonstrate that the network is robust to a range of variations in the stimulus pattern, such as are found in naturalistic stimuli and neural responses. This robustness is a property critical to the development of realistic, electronic neuromorphic systems.We analyse the variability of the response of the network to `noisy' stimuli which allows us to characterize the acuity in information-theoretic terms. This provides an objective basis for the quantitative comparison of networks, their connectivity patterns, and learning strategies, which can inform future design decisions. We also show, using stimuli derived from speech samples, that the principles are robust to other challenges, such as variable presentation rate, that would have to be met by systems deployed in the real world. Finally we demonstrate the potential applicability of the approach to real sounds.

  7. On Multiple AER Handshaking Channels Over High-Speed Bit-Serial Bidirectional LVDS Links With Flow-Control and Clock-Correction on Commercial FPGAs for Scalable Neuromorphic Systems.

    Science.gov (United States)

    Yousefzadeh, Amirreza; Jablonski, Miroslaw; Iakymchuk, Taras; Linares-Barranco, Alejandro; Rosado, Alfredo; Plana, Luis A; Temple, Steve; Serrano-Gotarredona, Teresa; Furber, Steve B; Linares-Barranco, Bernabe

    2017-10-01

    Address event representation (AER) is a widely employed asynchronous technique for interchanging "neural spikes" between different hardware elements in neuromorphic systems. Each neuron or cell in a chip or a system is assigned an address (or ID), which is typically communicated through a high-speed digital bus, thus time-multiplexing a high number of neural connections. Conventional AER links use parallel physical wires together with a pair of handshaking signals (request and acknowledge). In this paper, we present a fully serial implementation using bidirectional SATA connectors with a pair of low-voltage differential signaling (LVDS) wires for each direction. The proposed implementation can multiplex a number of conventional parallel AER links for each physical LVDS connection. It uses flow control, clock correction, and byte alignment techniques to transmit 32-bit address events reliably over multiplexed serial connections. The setup has been tested using commercial Spartan6 FPGAs attaining a maximum event transmission speed of 75 Meps (Mega events per second) for 32-bit events at a line rate of 3.0 Gbps. Full HDL codes (vhdl/verilog) and example demonstration codes for the SpiNNaker platform will be made available.

  8. Sensory Perception and Aging in Model Systems: From the Outside In

    Science.gov (United States)

    Linford, Nancy J.; Kuo, Tsung-Han; Chan, Tammy P.; Pletcher, Scott D.

    2014-01-01

    Sensory systems provide organisms from bacteria to human with the ability to interact with the world. Numerous senses have evolved that allow animals to detect and decode cues from sources in both their external and internal environments. Recent advances in understanding the central mechanisms by which the brains of simple organisms evaluate different cues and initiate behavioral decisions, coupled with observations that sensory manipulations are capable of altering organism lifespan, have opened the door for powerful new research into aging. While direct links between sensory perception and aging have been established only recently, here we discuss these initial discoveries and evaluate the potential for different forms of sensory processing to modulate lifespan across taxa. Harnessing the neurobiology of simple model systems to study the biological impact of sensory experiences will yield insights into the broad influence of sensory perception in mammals and may help uncover new mechanisms of healthy aging. PMID:21756108

  9. Sensory perception and aging in model systems: from the outside in.

    Science.gov (United States)

    Linford, Nancy J; Kuo, Tsung-Han; Chan, Tammy P; Pletcher, Scott D

    2011-01-01

    Sensory systems provide organisms from bacteria to humans with the ability to interact with the world. Numerous senses have evolved that allow animals to detect and decode cues from sources in both their external and internal environments. Recent advances in understanding the central mechanisms by which the brains of simple organisms evaluate different cues and initiate behavioral decisions, coupled with observations that sensory manipulations are capable of altering organismal lifespan, have opened the door for powerful new research into aging. Although direct links between sensory perception and aging have been established only recently, here we discuss these initial discoveries and evaluate the potential for different forms of sensory processing to modulate lifespan across taxa. Harnessing the neurobiology of simple model systems to study the biological impact of sensory experiences will yield insights into the broad influence of sensory perception in mammals and may help uncover new mechanisms of healthy aging.

  10. An FPGA-Based Massively Parallel Neuromorphic Cortex Simulator.

    Science.gov (United States)

    Wang, Runchun M; Thakur, Chetan S; van Schaik, André

    2018-01-01

    This paper presents a massively parallel and scalable neuromorphic cortex simulator designed for simulating large and structurally connected spiking neural networks, such as complex models of various areas of the cortex. The main novelty of this work is the abstraction of a neuromorphic architecture into clusters represented by minicolumns and hypercolumns, analogously to the fundamental structural units observed in neurobiology. Without this approach, simulating large-scale fully connected networks needs prohibitively large memory to store look-up tables for point-to-point connections. Instead, we use a novel architecture, based on the structural connectivity in the neocortex, such that all the required parameters and connections can be stored in on-chip memory. The cortex simulator can be easily reconfigured for simulating different neural networks without any change in hardware structure by programming the memory. A hierarchical communication scheme allows one neuron to have a fan-out of up to 200 k neurons. As a proof-of-concept, an implementation on one Altera Stratix V FPGA was able to simulate 20 million to 2.6 billion leaky-integrate-and-fire (LIF) neurons in real time. We verified the system by emulating a simplified auditory cortex (with 100 million neurons). This cortex simulator achieved a low power dissipation of 1.62 μW per neuron. With the advent of commercially available FPGA boards, our system offers an accessible and scalable tool for the design, real-time simulation, and analysis of large-scale spiking neural networks.

  11. Programming time-multiplexed reconfigurable hardware using a scalable neuromorphic compiler.

    Science.gov (United States)

    Minkovich, Kirill; Srinivasa, Narayan; Cruz-Albrecht, Jose M; Cho, Youngkwan; Nogin, Aleksey

    2012-06-01

    Scalability and connectivity are two key challenges in designing neuromorphic hardware that can match biological levels. In this paper, we describe a neuromorphic system architecture design that addresses an approach to meet these challenges using traditional complementary metal-oxide-semiconductor (CMOS) hardware. A key requirement in realizing such neural architectures in hardware is the ability to automatically configure the hardware to emulate any neural architecture or model. The focus for this paper is to describe the details of such a programmable front-end. This programmable front-end is composed of a neuromorphic compiler and a digital memory, and is designed based on the concept of synaptic time-multiplexing (STM). The neuromorphic compiler automatically translates any given neural architecture to hardware switch states and these states are stored in digital memory to enable desired neural architectures. STM enables our proposed architecture to address scalability and connectivity using traditional CMOS hardware. We describe the details of the proposed design and the programmable front-end, and provide examples to illustrate its capabilities. We also provide perspectives for future extensions and potential applications.

  12. Noise-exploitation and adaptation in neuromorphic sensors

    Science.gov (United States)

    Hindo, Thamira; Chakrabartty, Shantanu

    2012-04-01

    Even though current micro-nano fabrication technology has reached integration levels where ultra-sensitive sensors can be fabricated, the sensing performance (resolution per joule) of synthetic systems are still orders of magnitude inferior to those observed in neurobiology. For example, the filiform hairs in crickets operate at fundamental limits of noise; auditory sensors in a parasitoid fly can overcome fundamental limitations to precisely localize ultra-faint acoustic signatures. Even though many of these biological marvels have served as inspiration for different types of neuromorphic sensors, the main focus these designs have been to faithfully replicate the biological functionalities, without considering the constructive role of "noise". In man-made sensors device and sensor noise are typically considered as a nuisance, where as in neurobiology "noise" has been shown to be a computational aid that enables biology to sense and operate at fundamental limits of energy efficiency and performance. In this paper, we describe some of the important noise-exploitation and adaptation principles observed in neurobiology and how they can be systematically used for designing neuromorphic sensors. Our focus will be on two types of noise-exploitation principles, namely, (a) stochastic resonance; and (b) noise-shaping, which are unified within our previously reported framework called Σ▵ learning. As a case-study, we describe the application of Σ▵ learning for the design of a miniature acoustic source localizer whose performance matches that of its biological counterpart(Ormia Ochracea).

  13. Nonvolatile Memory Materials for Neuromorphic Intelligent Machines.

    Science.gov (United States)

    Jeong, Doo Seok; Hwang, Cheol Seong

    2018-04-18

    Recent progress in deep learning extends the capability of artificial intelligence to various practical tasks, making the deep neural network (DNN) an extremely versatile hypothesis. While such DNN is virtually built on contemporary data centers of the von Neumann architecture, physical (in part) DNN of non-von Neumann architecture, also known as neuromorphic computing, can remarkably improve learning and inference efficiency. Particularly, resistance-based nonvolatile random access memory (NVRAM) highlights its handy and efficient application to the multiply-accumulate (MAC) operation in an analog manner. Here, an overview is given of the available types of resistance-based NVRAMs and their technological maturity from the material- and device-points of view. Examples within the strategy are subsequently addressed in comparison with their benchmarks (virtual DNN in deep learning). A spiking neural network (SNN) is another type of neural network that is more biologically plausible than the DNN. The successful incorporation of resistance-based NVRAM in SNN-based neuromorphic computing offers an efficient solution to the MAC operation and spike timing-based learning in nature. This strategy is exemplified from a material perspective. Intelligent machines are categorized according to their architecture and learning type. Also, the functionality and usefulness of NVRAM-based neuromorphic computing are addressed. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. High-precision shape representation using a neuromorphic vision sensor with synchronous address-event communication interface

    Science.gov (United States)

    Belbachir, A. N.; Hofstätter, M.; Litzenberger, M.; Schön, P.

    2009-10-01

    A synchronous communication interface for neuromorphic temporal contrast vision sensors is described and evaluated in this paper. This interface has been designed for ultra high-speed synchronous arbitration of a temporal contrast image sensors pixels' data. Enabling high-precision timestamping, this system demonstrates its uniqueness for handling peak data rates and preserving the main advantage of the neuromorphic electronic systems, that is high and accurate temporal resolution. Based on a synchronous arbitration concept, the timestamping has a resolution of 100 ns. Both synchronous and (state-of-the-art) asynchronous arbiters have been implemented in a neuromorphic dual-line vision sensor chip in a standard 0.35 µm CMOS process. The performance analysis of both arbiters and the advantages of the synchronous arbitration over asynchronous arbitration in capturing high-speed objects are discussed in detail.

  15. High-precision shape representation using a neuromorphic vision sensor with synchronous address-event communication interface

    International Nuclear Information System (INIS)

    Belbachir, A N; Hofstätter, M; Litzenberger, M; Schön, P

    2009-01-01

    A synchronous communication interface for neuromorphic temporal contrast vision sensors is described and evaluated in this paper. This interface has been designed for ultra high-speed synchronous arbitration of a temporal contrast image sensors pixels' data. Enabling high-precision timestamping, this system demonstrates its uniqueness for handling peak data rates and preserving the main advantage of the neuromorphic electronic systems, that is high and accurate temporal resolution. Based on a synchronous arbitration concept, the timestamping has a resolution of 100 ns. Both synchronous and (state-of-the-art) asynchronous arbiters have been implemented in a neuromorphic dual-line vision sensor chip in a standard 0.35 µm CMOS process. The performance analysis of both arbiters and the advantages of the synchronous arbitration over asynchronous arbitration in capturing high-speed objects are discussed in detail

  16. Dynamic Adaptive Neural Network Arrays: A Neuromorphic Architecture

    Energy Technology Data Exchange (ETDEWEB)

    Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT)

    2015-01-01

    Dynamic Adaptive Neural Network Array (DANNA) is a neuromorphic hardware implementation. It differs from most other neuromorphic projects in that it allows for programmability of structure, and it is trained or designed using evolutionary optimization. This paper describes the DANNA structure, how DANNA is trained using evolutionary optimization, and an application of DANNA to a very simple classification task.

  17. An artificial arm/hand system with a haptic sensory function using electric stimulation of peripheral sensory nerve fibers.

    Science.gov (United States)

    Mabuchi, Kunihiko

    2013-01-01

    We are currently developing an artificial arm/hand system which is capable of sensing stimuli and then transferring these stimuli to users as somatic sensations. Presently, we are evoking the virtual somatic sensations by electrically stimulating a sensory nerve fiber which innervates a single mechanoreceptor unit at the target area; this is done using a tungsten microelectrode that was percutaneously inserted into the use's peripheral nerve (a microstimulation method). The artificial arm/hand system is composed of a robot hand equipped with a pressure sensor system on its fingers. The sensor system detects mechanical stimuli, which are transferred to the user by means of the microstimulation method so that the user experiences the stimuli as the corresponding somatic sensations. In trials, the system worked satisfactorily and there was a good correlation between the pressure applied to the pressure sensors on the robot fingers and the subjective intensities of the evoked pressure sensations.

  18. The sensory system of the esophagus--what do we know?

    Science.gov (United States)

    Brock, Christina; Gregersen, Hans; Gyawali, C Prakash; Lottrup, Christian; Furnari, Manuele; Savarino, Edoardo; Novais, Luis; Frøkjaer, Jens Brøndum; Bor, Serhat; Drewes, Asbjørn Mohr

    2016-09-01

    The nervous innervation and complex mechanical function of the esophagus make sensory evaluation difficult. However, during the last decades, several new techniques have made it possible to gain insight into pain processing of nociceptive signals. The current review highlights the sensory innervation and possibilities for quantitative sensory testing, the mechanosensory properties, the potential of high-resolution manometry and imaging, and the sensory system in special conditions, such as Barrett's esophagus. It is mandatory to understand the complex pathophysiology of the esophagus to enhance our understanding of esophageal disorders, but it also increases the complexity of future experimental and clinical studies. The new methods, as outlined in the current review, provide the possibility for researchers to enhance the quality of interdisciplinary research and to gain more knowledge about sensory symptoms and treatment possibilities. © 2016 New York Academy of Sciences.

  19. Sensory Systems and Environmental Change on Behavior during Social Interactions

    Directory of Open Access Journals (Sweden)

    S. M. Bierbower

    2013-01-01

    Full Text Available The impact of environmental conditions for transmitting sensory cues and the ability of crayfish to utilize olfaction and vision were examined in regards to social interactive behavior. The duration and intensity of interactions were examined for conspecific crayfish with different sensory abilities. Normally, vision and chemosensory have roles in agonistic communication of Procambarus clarkii; however, for the blind cave crayfish (Orconectes australis packardi, that lack visual capabilities, olfaction is assumed to be the primary sensory modality. To test this, we paired conspecifics in water and out of water in the presence and absence of white light to examine interactive behaviors when these various sensory modalities are altered. For sighted crayfish, in white light, interactions occurred and escalated; however, when the water was removed, interactions and aggressiveness decreased, but, there was an increase in visual displays out of the water. The loss of olfaction abilities for blind cave and sighted crayfish produced fewer social interactions. The importance of environmental conditions is illustrated for social interactions among sighted and blind crayfish. Importantly, this study shows the relevance in the ecological arena in nature for species survival and how environmental changes disrupt innate behaviors.

  20. A forecast-based STDP rule suitable for neuromorphic implementation.

    Science.gov (United States)

    Davies, S; Galluppi, F; Rast, A D; Furber, S B

    2012-08-01

    Artificial neural networks increasingly involve spiking dynamics to permit greater computational efficiency. This becomes especially attractive for on-chip implementation using dedicated neuromorphic hardware. However, both spiking neural networks and neuromorphic hardware have historically found difficulties in implementing efficient, effective learning rules. The best-known spiking neural network learning paradigm is Spike Timing Dependent Plasticity (STDP) which adjusts the strength of a connection in response to the time difference between the pre- and post-synaptic spikes. Approaches that relate learning features to the membrane potential of the post-synaptic neuron have emerged as possible alternatives to the more common STDP rule, with various implementations and approximations. Here we use a new type of neuromorphic hardware, SpiNNaker, which represents the flexible "neuromimetic" architecture, to demonstrate a new approach to this problem. Based on the standard STDP algorithm with modifications and approximations, a new rule, called STDP TTS (Time-To-Spike) relates the membrane potential with the Long Term Potentiation (LTP) part of the basic STDP rule. Meanwhile, we use the standard STDP rule for the Long Term Depression (LTD) part of the algorithm. We show that on the basis of the membrane potential it is possible to make a statistical prediction of the time needed by the neuron to reach the threshold, and therefore the LTP part of the STDP algorithm can be triggered when the neuron receives a spike. In our system these approximations allow efficient memory access, reducing the overall computational time and the memory bandwidth required. The improvements here presented are significant for real-time applications such as the ones for which the SpiNNaker system has been designed. We present simulation results that show the efficacy of this algorithm using one or more input patterns repeated over the whole time of the simulation. On-chip results show that

  1. Computing with networks of spiking neurons on a biophysically motivated floating-gate based neuromorphic integrated circuit.

    Science.gov (United States)

    Brink, S; Nease, S; Hasler, P

    2013-09-01

    Results are presented from several spiking network experiments performed on a novel neuromorphic integrated circuit. The networks are discussed in terms of their computational significance, which includes applications such as arbitrary spatiotemporal pattern generation and recognition, winner-take-all competition, stable generation of rhythmic outputs, and volatile memory. Analogies to the behavior of real biological neural systems are also noted. The alternatives for implementing the same computations are discussed and compared from a computational efficiency standpoint, with the conclusion that implementing neural networks on neuromorphic hardware is significantly more power efficient than numerical integration of model equations on traditional digital hardware. Copyright © 2013 Elsevier Ltd. All rights reserved.

  2. Microfluidic Neurons, a New Way in Neuromorphic Engineering?

    Directory of Open Access Journals (Sweden)

    Timothée Levi

    2016-08-01

    Full Text Available This article describes a new way to explore neuromorphic engineering, the biomimetic artificial neuron using microfluidic techniques. This new device could replace silicon neurons and solve the issues of biocompatibility and power consumption. The biological neuron transmits electrical signals based on ion flow through their plasma membrane. Action potentials are propagated along axons and represent the fundamental electrical signals by which information are transmitted from one place to another in the nervous system. Based on this physiological behavior, we propose a microfluidic structure composed of chambers representing the intra and extracellular environments, connected by channels actuated by Quake valves. These channels are equipped with selective ion permeable membranes to mimic the exchange of chemical species found in the biological neuron. A thick polydimethylsiloxane (PDMS membrane is used to create the Quake valve membrane. Integrated electrodes are used to measure the potential difference between the intracellular and extracellular environments: the membrane potential.

  3. Advances in neuromorphic hardware exploiting emerging nanoscale devices

    CERN Document Server

    2017-01-01

    This book covers all major aspects of cutting-edge research in the field of neuromorphic hardware engineering involving emerging nanoscale devices. Special emphasis is given to leading works in hybrid low-power CMOS-Nanodevice design. The book offers readers a bidirectional (top-down and bottom-up) perspective on designing efficient bio-inspired hardware. At the nanodevice level, it focuses on various flavors of emerging resistive memory (RRAM) technology. At the algorithm level, it addresses optimized implementations of supervised and stochastic learning paradigms such as: spike-time-dependent plasticity (STDP), long-term potentiation (LTP), long-term depression (LTD), extreme learning machines (ELM) and early adoptions of restricted Boltzmann machines (RBM) to name a few. The contributions discuss system-level power/energy/parasitic trade-offs, and complex real-world applications. The book is suited for both advanced researchers and students interested in the field.

  4. Stochastic learning in oxide binary synaptic device for neuromorphic computing.

    Science.gov (United States)

    Yu, Shimeng; Gao, Bin; Fang, Zheng; Yu, Hongyu; Kang, Jinfeng; Wong, H-S Philip

    2013-01-01

    Hardware implementation of neuromorphic computing is attractive as a computing paradigm beyond the conventional digital computing. In this work, we show that the SET (off-to-on) transition of metal oxide resistive switching memory becomes probabilistic under a weak programming condition. The switching variability of the binary synaptic device implements a stochastic learning rule. Such stochastic SET transition was statistically measured and modeled for a simulation of a winner-take-all network for competitive learning. The simulation illustrates that with such stochastic learning, the orientation classification function of input patterns can be effectively realized. The system performance metrics were compared between the conventional approach using the analog synapse and the approach in this work that employs the binary synapse utilizing the stochastic learning. The feasibility of using binary synapse in the neurormorphic computing may relax the constraints to engineer continuous multilevel intermediate states and widens the material choice for the synaptic device design.

  5. An FPGA-Based Massively Parallel Neuromorphic Cortex Simulator

    Directory of Open Access Journals (Sweden)

    Runchun M. Wang

    2018-04-01

    Full Text Available This paper presents a massively parallel and scalable neuromorphic cortex simulator designed for simulating large and structurally connected spiking neural networks, such as complex models of various areas of the cortex. The main novelty of this work is the abstraction of a neuromorphic architecture into clusters represented by minicolumns and hypercolumns, analogously to the fundamental structural units observed in neurobiology. Without this approach, simulating large-scale fully connected networks needs prohibitively large memory to store look-up tables for point-to-point connections. Instead, we use a novel architecture, based on the structural connectivity in the neocortex, such that all the required parameters and connections can be stored in on-chip memory. The cortex simulator can be easily reconfigured for simulating different neural networks without any change in hardware structure by programming the memory. A hierarchical communication scheme allows one neuron to have a fan-out of up to 200 k neurons. As a proof-of-concept, an implementation on one Altera Stratix V FPGA was able to simulate 20 million to 2.6 billion leaky-integrate-and-fire (LIF neurons in real time. We verified the system by emulating a simplified auditory cortex (with 100 million neurons. This cortex simulator achieved a low power dissipation of 1.62 μW per neuron. With the advent of commercially available FPGA boards, our system offers an accessible and scalable tool for the design, real-time simulation, and analysis of large-scale spiking neural networks.

  6. The sensory system acts with a neuromedin U signaling pathway to mediate food type-dependent effects on lifespan

    OpenAIRE

    Adilov, Bakhtiyor

    2010-01-01

    In order to survive, the animal uses its sensory system to interpret the complexity of its environment. Interestingly, a subset of sensory neurons, which function in taste or olfaction, has been found to influence the lifespan of C. elegans and Drosophila. Although the mechanisms by which these neurons affect lifespan are unknown, the nature of these neurons suggest that the sensory influence on lifespan is mediated by food-derived cues. This thesis shows that sensory neurons r...

  7. An Adaptable Neuromorphic Model of Orientation Selectivity Based On Floating Gate Dynamics

    Directory of Open Access Journals (Sweden)

    Priti eGupta

    2014-04-01

    Full Text Available The biggest challenge that the neuromorphic community faces today is to build systems that can be considered truly cognitive. Adaptation and self-organization are the two basic principles that underlie any cognitive function that the brain performs. If we can replicate this behavior in hardware, we move a step closer to our goal of having cognitive neuromorphic systems. Adaptive feature selectivity is a mechanism by which nature optimizes resources so as to have greater acuity for more abundant features. Developing neuromorphic feature maps can help design generic machines that can emulate this adaptive behavior. Most neuromorphic models that have attempted to build self-organizing systems, follow the approach of modeling abstract theoretical frameworks in hardware. While this is good from a modeling and analysis perspective, it may not lead to the most efficient hardware. On the other hand, exploiting hardware dynamics to build adaptive systems rather than forcing the hardware to behave like mathematical equations, seems to be a more robust methodology when it comes to developing actual hardware for real world applications. In this paper we use a novel time-staggered Winner Take All circuit, that exploits the adaptation dynamics of floating gate transistors, to model an adaptive cortical cell that demonstrates Orientation Selectivity, a well-known biological phenomenon observed in the visual cortex. The cell performs competitive learning, refining its weights in response to input patterns resembling different oriented bars, becoming selective to a particular oriented pattern. Different analysis performed on the cell such as orientation tuning, application of abnormal inputs, response to spatial frequency and periodic patterns reveal close similarity between our cell and its biological counterpart. Embedded in a RC grid, these cells interact diffusively exhibiting cluster formation, making way for adaptively building orientation selective maps

  8. An Evolutionary Optimization Framework for Neural Networks and Neuromorphic Architectures

    Energy Technology Data Exchange (ETDEWEB)

    Schuman, Catherine D [ORNL; Plank, James [University of Tennessee (UT); Disney, Adam [University of Tennessee (UT); Reynolds, John [University of Tennessee (UT)

    2016-01-01

    As new neural network and neuromorphic architectures are being developed, new training methods that operate within the constraints of the new architectures are required. Evolutionary optimization (EO) is a convenient training method for new architectures. In this work, we review a spiking neural network architecture and a neuromorphic architecture, and we describe an EO training framework for these architectures. We present the results of this training framework on four classification data sets and compare those results to other neural network and neuromorphic implementations. We also discuss how this EO framework may be extended to other architectures.

  9. Memristive and neuromorphic behavior in a LixCoO2 nanobattery

    Science.gov (United States)

    Mai, V. H.; Moradpour, A.; Senzier, P. Auban; Pasquier, C.; Wang, K.; Rozenberg, M. J.; Giapintzakis, J.; Mihailescu, C. N.; Orfanidou, C. M.; Svoukis, E.; Breza, A.; Lioutas, Ch B.; Franger, S.; Revcolevschi, A.; Maroutian, T.; Lecoeur, P.; Aubert, P.; Agnus, G.; Salot, R.; Albouy, P. A.; Weil, R.; Alamarguy, D.; March, K.; Jomard, F.; Chrétien, P.; Schneegans, O.

    2015-01-01

    The phenomenon of resistive switching (RS), which was initially linked to non-volatile resistive memory applications, has recently also been associated with the concept of memristors, whose adjustable multilevel resistance characteristics open up unforeseen perspectives in cognitive computing. Herein, we demonstrate that the resistance states of LixCoO2 thin film-based metal-insulator-metal (MIM) solid-state cells can be tuned by sequential programming voltage pulses, and that these resistance states are dramatically dependent on the pulses input rate, hence emulating biological synapse plasticity. In addition, we identify the underlying electrochemical processes of RS in our MIM cells, which also reveal a nanobattery-like behavior, leading to the generation of electrical signals that bring an unprecedented new dimension to the connection between memristors and neuromorphic systems. Therefore, these LixCoO2-based MIM devices allow for a combination of possibilities, offering new perspectives of usage in nanoelectronics and bio-inspired neuromorphic circuits.

  10. FPGA implementation of a configurable neuromorphic CPG-based locomotion controller.

    Science.gov (United States)

    Barron-Zambrano, Jose Hugo; Torres-Huitzil, Cesar

    2013-09-01

    Neuromorphic engineering is a discipline devoted to the design and development of computational hardware that mimics the characteristics and capabilities of neuro-biological systems. In recent years, neuromorphic hardware systems have been implemented using a hybrid approach incorporating digital hardware so as to provide flexibility and scalability at the cost of power efficiency and some biological realism. This paper proposes an FPGA-based neuromorphic-like embedded system on a chip to generate locomotion patterns of periodic rhythmic movements inspired by Central Pattern Generators (CPGs). The proposed implementation follows a top-down approach where modularity and hierarchy are two desirable features. The locomotion controller is based on CPG models to produce rhythmic locomotion patterns or gaits for legged robots such as quadrupeds and hexapods. The architecture is configurable and scalable for robots with either different morphologies or different degrees of freedom (DOFs). Experiments performed on a real robot are presented and discussed. The obtained results demonstrate that the CPG-based controller provides the necessary flexibility to generate different rhythmic patterns at run-time suitable for adaptable locomotion. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. Neuromorphic computing with nanoscale spintronic oscillators.

    Science.gov (United States)

    Torrejon, Jacob; Riou, Mathieu; Araujo, Flavio Abreu; Tsunegi, Sumito; Khalsa, Guru; Querlioz, Damien; Bortolotti, Paolo; Cros, Vincent; Yakushiji, Kay; Fukushima, Akio; Kubota, Hitoshi; Yuasa, Shinji; Stiles, Mark D; Grollier, Julie

    2017-07-26

    Neurons in the brain behave as nonlinear oscillators, which develop rhythmic activity and interact to process information. Taking inspiration from this behaviour to realize high-density, low-power neuromorphic computing will require very large numbers of nanoscale nonlinear oscillators. A simple estimation indicates that to fit 10 8 oscillators organized in a two-dimensional array inside a chip the size of a thumb, the lateral dimension of each oscillator must be smaller than one micrometre. However, nanoscale devices tend to be noisy and to lack the stability that is required to process data in a reliable way. For this reason, despite multiple theoretical proposals and several candidates, including memristive and superconducting oscillators, a proof of concept of neuromorphic computing using nanoscale oscillators has yet to be demonstrated. Here we show experimentally that a nanoscale spintronic oscillator (a magnetic tunnel junction) can be used to achieve spoken-digit recognition with an accuracy similar to that of state-of-the-art neural networks. We also determine the regime of magnetization dynamics that leads to the greatest performance. These results, combined with the ability of the spintronic oscillators to interact with each other, and their long lifetime and low energy consumption, open up a path to fast, parallel, on-chip computation based on networks of oscillators.

  12. Encoding neural and synaptic functionalities in electron spin: A pathway to efficient neuromorphic computing

    Science.gov (United States)

    Sengupta, Abhronil; Roy, Kaushik

    2017-12-01

    Present day computers expend orders of magnitude more computational resources to perform various cognitive and perception related tasks that humans routinely perform every day. This has recently resulted in a seismic shift in the field of computation where research efforts are being directed to develop a neurocomputer that attempts to mimic the human brain by nanoelectronic components and thereby harness its efficiency in recognition problems. Bridging the gap between neuroscience and nanoelectronics, this paper attempts to provide a review of the recent developments in the field of spintronic device based neuromorphic computing. Description of various spin-transfer torque mechanisms that can be potentially utilized for realizing device structures mimicking neural and synaptic functionalities is provided. A cross-layer perspective extending from the device to the circuit and system level is presented to envision the design of an All-Spin neuromorphic processor enabled with on-chip learning functionalities. Device-circuit-algorithm co-simulation framework calibrated to experimental results suggest that such All-Spin neuromorphic systems can potentially achieve almost two orders of magnitude energy improvement in comparison to state-of-the-art CMOS implementations.

  13. Neuromorphic Kalman filter implementation in IBM’s TrueNorth

    Science.gov (United States)

    Carney, R.; Bouchard, K.; Calafiura, P.; Clark, D.; Donofrio, D.; Garcia-Sciveres, M.; Livezey, J.

    2017-10-01

    Following the advent of a post-Moore’s law field of computation, novel architectures continue to emerge. With composite, multi-million connection neuromorphic chips like IBM’s TrueNorth, neural engineering has now become a feasible technology in this novel computing paradigm. High Energy Physics experiments are continuously exploring new methods of computation and data handling, including neuromorphic, to support the growing challenges of the field and be prepared for future commodity computing trends. This work details the first instance of a Kalman filter implementation in IBM’s neuromorphic architecture, TrueNorth, for both parallel and serial spike trains. The implementation is tested on multiple simulated systems and its performance is evaluated with respect to an equivalent non-spiking Kalman filter. The limits of the implementation are explored whilst varying the size of weight and threshold registers, the number of spikes used to encode a state, size of neuron block for spatial encoding, and neuron potential reset schemes.

  14. Discrimination of Dynamic Tactile Contact by Temporally Precise Event Sensing in Spiking Neuromorphic Networks.

    Science.gov (United States)

    Lee, Wang Wei; Kukreja, Sunil L; Thakor, Nitish V

    2017-01-01

    This paper presents a neuromorphic tactile encoding methodology that utilizes a temporally precise event-based representation of sensory signals. We introduce a novel concept where touch signals are characterized as patterns of millisecond precise binary events to denote pressure changes. This approach is amenable to a sparse signal representation and enables the extraction of relevant features from thousands of sensing elements with sub-millisecond temporal precision. We also proposed measures adopted from computational neuroscience to study the information content within the spiking representations of artificial tactile signals. Implemented on a state-of-the-art 4096 element tactile sensor array with 5.2 kHz sampling frequency, we demonstrate the classification of transient impact events while utilizing 20 times less communication bandwidth compared to frame based representations. Spiking sensor responses to a large library of contact conditions were also synthesized using finite element simulations, illustrating an 8-fold improvement in information content and a 4-fold reduction in classification latency when millisecond-precise temporal structures are available. Our research represents a significant advance, demonstrating that a neuromorphic spatiotemporal representation of touch is well suited to rapid identification of critical contact events, making it suitable for dynamic tactile sensing in robotic and prosthetic applications.

  15. Closed-loop neuromorphic benchmarks

    CSIR Research Space (South Africa)

    Stewart, TC

    2015-11-01

    Full Text Available Benchmarks   Terrence C. Stewart 1* , Travis DeWolf 1 , Ashley Kleinhans 2 , Chris Eliasmith 1   1 University of Waterloo, Canada, 2 Council for Scientific and Industrial Research, South Africa   Submitted to Journal:   Frontiers in Neuroscience   Specialty... Eliasmith 1 1Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, ON, Canada 2Mobile Intelligent Autonomous Systems group, Council for Scientific and Industrial Research, Pretoria, South Africa Correspondence*: Terrence C. Stewart Centre...

  16. Cercal sensory system and giant interneurons in Gryllodes sigillatus.

    Science.gov (United States)

    Kanou, Masamichi; Nawae, Miyuki; Kuroishi, Hiroyuki

    2006-04-01

    The external morphologies of two cricket species, Gryllodes sigillatus and Gryllus bimaculatus, were investigated. Despite its small body length, G. sigillatus possessed longer cerci and longer cercal filiform hairs than G. bimaculatus. The estimated number of filiform hairs on a cercus was also larger in G. sigillatus than in G. bimaculatus. Wind-sensitive interneurons receiving sensory inputs from cercal filiform hairs and running in the ventral nerve cord (VNC) were investigated in G. sigillatus both morphologically and physiologically. By intracellular staining, these interneurons were proved to be morphologically homologous with previously identified giant interneurons (GIs 8-1, 9-1, 9-2, 9-3, 10-2, and 10-3) in G. bimaculatus and Acheta domesticus. In G. sigillatus, the intensity-response relationship (I-R curve) for each GI was investigated using a unidirectional air current stimulus. The stimulus was applied from 12 different directions, and an I-R curve was obtained for each stimulus direction. Each GI showed a characteristic I-R curve depending on stimulus direction. The directionality curve expressed in terms of threshold velocity showed that each GI had a distinctive directional characteristic. The functional properties of GIs in G. sigillatus, such as I-R curve, threshold velocity, and directional characteristics, were compared with those of homologous GIs in G. bimaculatus in Discussion.

  17. Effect of sensory substitution on suture-manipulation forces for robotic surgical systems.

    Science.gov (United States)

    Kitagawa, Masaya; Dokko, Daniell; Okamura, Allison M; Yuh, David D

    2005-01-01

    Direct haptic (force or tactile) feedback is not yet available in commercial robotic surgical systems. Previous work by our group and others suggests that haptic feedback might significantly enhance the execution of surgical tasks requiring fine suture manipulation, specifically those encountered in cardiothoracic surgery. We studied the effects of substituting direct haptic feedback with visual and auditory cues to provide the operating surgeon with a representation of the forces he or she is applying with robotic telemanipulators. Using the robotic da Vinci surgical system (Intuitive Surgical, Inc, Sunnyvale, Calif), we compared applied forces during a standardized surgical knot-tying task under 4 different sensory-substitution scenarios: no feedback, auditory feedback, visual feedback, and combined auditory-visual feedback. The forces applied with these sensory-substitution modes more closely approximate suture tensions achieved under ideal haptic conditions (ie, hand ties) than forces applied without such sensory feedback. The consistency of applied forces during robot-assisted suture tying aided by visual feedback or combined auditory-visual feedback sensory substitution is superior to that achieved with hand ties. Robot-assisted ties aided with auditory feedback revealed levels of consistency that were generally equivalent or superior to those attained with hand ties. Visual feedback and auditory feedback improve the consistency of robotically applied forces. Sensory substitution, in the form of visual feedback, auditory feedback, or both, confers quantifiable advantages in applied force accuracy and consistency during the performance of a simple surgical task.

  18. ERP evaluation of auditory sensory memory systems in adults with intellectual disability.

    Science.gov (United States)

    Ikeda, Kazunari; Hashimoto, Souichi; Hayashi, Akiko; Kanno, Atsushi

    2009-01-01

    Auditory sensory memory stage can be functionally divided into two subsystems; transient-detector system and permanent feature-detector system (Naatanen, 1992). We assessed these systems in persons with intellectual disability by measuring event-related potentials (ERPs) N1 and mismatch negativity (MMN), which reflect the two auditory subsystems, respectively. Added to these, P3a (an ERP reflecting stage after sensory memory) was evaluated. Either synthesized vowels or simple tones were delivered during a passive oddball paradigm to adults with and without intellectual disability. ERPs were recorded from midline scalp sites (Fz, Cz, and Pz). Relative to control group, participants with the disability exhibited greater N1 latency and less MMN amplitude. The results for N1 amplitude and MMN latency were basically comparable between both groups. IQ scores in participants with the disability revealed no significant relation with N1 and MMN measures, whereas the IQ scores tended to increase significantly as P3a latency reduced. These outcomes suggest that persons with intellectual disability might own discrete malfunctions for the two detector systems in auditory sensory-memory stage. Moreover, the processes following sensory memory might be partly related to a determinant of mental development.

  19. Does (Non-)Meaningful Sensori-Motor Engagement Promote Learning With Animated Physical Systems?

    NARCIS (Netherlands)

    Pouw, Wim T J L; Eielts, Charly; van Gog, Tamara; Zwaan, Rolf A.; Paas, Fred

    2016-01-01

    Previous research indicates that sensori-motor experience with physical systems can have a positive effect on learning. However, it is not clear whether this effect is caused by mere bodily engagement or the intrinsically meaningful information that such interaction affords in performing the

  20. Adaptive WTA with an analog VLSI neuromorphic learning chip.

    Science.gov (United States)

    Häfliger, Philipp

    2007-03-01

    In this paper, we demonstrate how a particular spike-based learning rule (where exact temporal relations between input and output spikes of a spiking model neuron determine the changes of the synaptic weights) can be tuned to express rate-based classical Hebbian learning behavior (where the average input and output spike rates are sufficient to describe the synaptic changes). This shift in behavior is controlled by the input statistic and by a single time constant. The learning rule has been implemented in a neuromorphic very large scale integration (VLSI) chip as part of a neurally inspired spike signal image processing system. The latter is the result of the European Union research project Convolution AER Vision Architecture for Real-Time (CAVIAR). Since it is implemented as a spike-based learning rule (which is most convenient in the overall spike-based system), even if it is tuned to show rate behavior, no explicit long-term average signals are computed on the chip. We show the rule's rate-based Hebbian learning ability in a classification task in both simulation and chip experiment, first with artificial stimuli and then with sensor input from the CAVIAR system.

  1. Sensory and Physical Effects of Sugar Reduction in a Caramel Coating System.

    Science.gov (United States)

    Mayhew, Emily J; Schmidt, Shelly J; Lee, Soo-Yeun

    2017-08-01

    Sugar reduction in processed foods is a pressing and complex problem, as sugars contribute important sensory and physical properties to foods. Composed of sugars and lipids, caramel coating systems, like the coating in caramel popcorns, exemplify this challenge. In order to probe the feasibility and consequences of sugar reduction, both sensory and physical properties were measured for 3 types of caramel coating systems. Four commonly used sugar alcohols, isomalt, maltitol, mannitol, and sorbitol, with different thermal properties and relative sweetness values were chosen to replace sugar in the caramel coating systems at 25% and 50% sugar reduction levels. Full sugar (control) and reduced sugar caramel coating samples were prepared in duplicate. Ten trained panelists participated in a 6-wk descriptive analysis panel to define and quantify the intensity of important sensory characteristics. All 24 sensory terms generated by the panel differed significantly across caramel type and sugar replacer. Thermal properties were measured through differential scanning calorimetry, and textural properties were measured through texture profile analysis. Replacement of sugar with sugar alcohols was found to decrease the glass transition temperature and systematically alter the hardness and resilience of caramel samples. Principal component analysis of sensory and physical data revealed that caramel coating type dictates caramel aroma, aroma by mouth, taste, and aftertaste, while sugar replacer and replacement level dictate texture. This research represents the first comprehensive study of the effects of sugar reduction in a caramel coating system and suggests successful strategies for sugar reduction and key parameters to control in reduced sugar systems. © 2017 Institute of Food Technologists®.

  2. Hospital catering systems and their impact on the sensorial profile of foods provided to older patients in the UK.

    Science.gov (United States)

    Mavrommatis, Yiannis; Moynihan, Paula J; Gosney, Margot A; Methven, Lisa

    2011-08-01

    Impaired sensorial perception is very common in older people and low sensorial quality of foods is associated with decreased appetite and dietary intake. Hospital undernutrition in older patients could be linked to sensorial quality of hospital food if the quality were low or inappropriate for older people. The aim of this study was to examine changes in the sensorial quality of different foods that occur as a result of the food journey (i.e. freezing, regeneration, etc.) in the most common hospital catering systems in the UK. A trained sensory panel assessed sensorial descriptors of certain foods with and without the hospital food journey as it occurs in the in-house and cook/freeze systems. The results showed effects of the food journey on a small number of sensorial descriptors related to flavour, appearance and mouthfeel. The majority of these effects were due to temperature changes, which caused accumulation of condensation. A daily variation in sensorial descriptors was also detected and in some cases it was greater than the effect of the food journey. This study has shown that changes occur in the sensory quality of meals due to hospital food journeys, however these changes were small and are not expected to substantially contribute to acceptability or have a major role in hospital malnutrition. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. Chemical and texture characteristics and sensory properties of “mozzarella” cheese from different feeding systems

    Directory of Open Access Journals (Sweden)

    R. Rubino

    2010-02-01

    Full Text Available The aim of this study was describing the chemical composition, the rheological characteristics and the sensory properties of “mozzarella” cheese produced with milk from buffalos fed with different diets. The study involved two farms and four feeding systems. In farm C, one group was mostly fed with Ryegrass Hay (RH and the other group with Ryegrass Silage (RS. In farm T, instead, one group was mostly fed with Corn Silage (CS and the other one with a Sorghum Silage (SS. In summer, three cheesemakings, for each farm and for each feeding system, were carried out at C.R.A. of Bella. In each farm, data were processed by the analysis of variance in order to compare the effects of two feeding systems. Some parameters of chemical and texture characteristics and sensory properties were influenced by the feeding system. Results were remarkable for the DOP products.

  4. Optimized Vibration Chamber for Landslide Sensory and Alarm System

    Science.gov (United States)

    Ismail, Eliza Sabira Binti; Hadi Habaebi, Mohamed; Daoud, Jamal I.; Rafiqul Islam, Md

    2017-11-01

    Landslide is one of natural hazard that is not unfamiliar disaster in Malaysia. Malaysia has experienced this disaster many times since 1969. This natural hazard has become a major research concern for Malaysian government when many people were injured badly and even had been killed. Many previous research works published in the open literature aimed at designing a system that could detect landslide in early stage before the landslide becomes catastrophic. This paper presents the early works on a major work-in-progress landslide early warning system for Malaysian environment. The aim of this system is to develop the most efficiently reliable cost-effective system in which slight earth movements are monitored continuously. The challenge this work aims at is to work with a low budget system that produces efficient performance. Hence, the material used is off-the-shelf. Early design optimization results of the vibration sensor used is quite promising detecting the slightest faint tremors, which are amplified using the best vibration chamber available. It is shown that the choice of proper pipe length and diameter dimensions in combination to a gravel to exaggerate the produced higher sensitivity level noise of 5 dB.

  5. Talent in autism: hyper-systemizing, hyper-attention to detail and sensory hypersensitivity.

    Science.gov (United States)

    Baron-Cohen, Simon; Ashwin, Emma; Ashwin, Chris; Tavassoli, Teresa; Chakrabarti, Bhismadev

    2009-05-27

    We argue that hyper-systemizing predisposes individuals to show talent, and review evidence that hyper-systemizing is part of the cognitive style of people with autism spectrum conditions (ASC). We then clarify the hyper-systemizing theory, contrasting it to the weak central coherence (WCC) and executive dysfunction (ED) theories. The ED theory has difficulty explaining the existence of talent in ASC. While both hyper-systemizing and WCC theories postulate excellent attention to detail, by itself excellent attention to detail will not produce talent. By contrast, the hyper-systemizing theory argues that the excellent attention to detail is directed towards detecting 'if p, then q' rules (or [input-operation-output] reasoning). Such law-based pattern recognition systems can produce talent in systemizable domains. Finally, we argue that the excellent attention to detail in ASC is itself a consequence of sensory hypersensitivity. We review an experiment from our laboratory demonstrating sensory hypersensitivity detection thresholds in vision. We conclude that the origins of the association between autism and talent begin at the sensory level, include excellent attention to detail and end with hyper-systemizing.

  6. Design of fresh food sensory perceptual system for cold chain logistics

    OpenAIRE

    Zhang Ying; Cheng Ruqi; Chen Shaohui

    2018-01-01

    According to the present stage low-level information of China's cold chain preservation, designed a kind of fresh food sensory perceptual system for cold chain logistics based on Internet of things. This system highly integrated applied many technologies such as the Internet of things technology, forecasting technology for fruits and vegetables preservation period, RFID and Planar bar code technology, big data and cloud computing technology and so on.Designed as a four-layer structure includi...

  7. Neuromorphic circuits impart a sense of touch

    Science.gov (United States)

    Bartolozzi, Chiara

    2018-06-01

    The sense of touch is the ability to perceive consistency, texture, and shape of objects that we manipulate, and the forces we exchange with them. Touch is a source of information that we effortlessly decode to smoothly and naturally grasp and manipulate objects, maintain our posture while walking, or avoid stumbling into obstacles, allowing us to plan, adapt, and correct actions in an ever-changing external world. As such, artificial devices, such as robots or prostheses, that aim to accomplish similar tasks must possess artificial tactile-sensing systems. On page 998 of this issue, Kim et al. (1) report on a “neuromorphic” tactile sensory system based on organic, flexible, electronic circuits that can measure the force applied on the sensing regions. The encoding of the signal is similar to that used by human nerves that are sensitive to tactile stimuli (mechanoreceptors), so the device outputs can substitute for them and communicate with other nerves (e.g., residual nerve fibers of amputees or motor neurons). The proposed system exploits organic electronics that allow for three-dimensional printing of flexible structures that conform to large curved surfaces, as required for placing sensors on robots (2) and prostheses.

  8. Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI.

    Science.gov (United States)

    Wang, Jun; Breen, Daniel; Akinin, Abraham; Broccard, Frederic; Abarbanel, Henry D I; Cauwenberghs, Gert

    2017-12-01

    Representing the biophysics of neuronal dynamics and behavior offers a principled analysis-by-synthesis approach toward understanding mechanisms of nervous system functions. We report on a set of procedures assimilating and emulating neurobiological data on a neuromorphic very large scale integrated (VLSI) circuit. The analog VLSI chip, NeuroDyn, features 384 digitally programmable parameters specifying for 4 generalized Hodgkin-Huxley neurons coupled through 12 conductance-based chemical synapses. The parameters also describe reversal potentials, maximal conductances, and spline regressed kinetic functions for ion channel gating variables. In one set of experiments, we assimilated membrane potential recorded from one of the neurons on the chip to the model structure upon which NeuroDyn was designed using the known current input sequence. We arrived at the programmed parameters except for model errors due to analog imperfections in the chip fabrication. In a related set of experiments, we replicated songbird individual neuron dynamics on NeuroDyn by estimating and configuring parameters extracted using data assimilation from intracellular neural recordings. Faithful emulation of detailed biophysical neural dynamics will enable the use of NeuroDyn as a tool to probe electrical and molecular properties of functional neural circuits. Neuroscience applications include studying the relationship between molecular properties of neurons and the emergence of different spike patterns or different brain behaviors. Clinical applications include studying and predicting effects of neuromodulators or neurodegenerative diseases on ion channel kinetics.

  9. Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform.

    Science.gov (United States)

    Giulioni, Massimiliano; Lagorce, Xavier; Galluppi, Francesco; Benosman, Ryad B

    2016-01-01

    Estimating the speed and direction of moving objects is a crucial component of agents behaving in a dynamic world. Biological organisms perform this task by means of the neural connections originating from their retinal ganglion cells. In artificial systems the optic flow is usually extracted by comparing activity of two or more frames captured with a vision sensor. Designing artificial motion flow detectors which are as fast, robust, and efficient as the ones found in biological systems is however a challenging task. Inspired by the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina, we introduce an architecture for robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission, and the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. Mimicking ganglion cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. Hereby we describe the architectural aspects, discuss its latency, scalability, and robustness properties and demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene. This work shows how precise time of spike emission used as a computational basis, biological inspiration, and neuromorphic systems can be used together for solving specific tasks.

  10. Large-scale simulations of plastic neural networks on neuromorphic hardware

    Directory of Open Access Journals (Sweden)

    James Courtney Knight

    2016-04-01

    Full Text Available SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Rather than using bespoke analog or digital hardware, the basic computational unit of a SpiNNaker system is a general-purpose ARM processor, allowing it to be programmed to simulate a wide variety of neuron and synapse models. This flexibility is particularly valuable in the study of biological plasticity phenomena. A recently proposed learning rule based on the Bayesian Confidence Propagation Neural Network (BCPNN paradigm offers a generic framework for modeling the interaction of different plasticity mechanisms using spiking neurons. However, it can be computationally expensive to simulate large networks with BCPNN learning since it requires multiple state variables for each synapse, each of which needs to be updated every simulation time-step. We discuss the trade-offs in efficiency and accuracy involved in developing an event-based BCPNN implementation for SpiNNaker based on an analytical solution to the BCPNN equations, and detail the steps taken to fit this within the limited computational and memory resources of the SpiNNaker architecture. We demonstrate this learning rule by learning temporal sequences of neural activity within a recurrent attractor network which we simulate at scales of up to 20000 neurons and 51200000 plastic synapses: the largest plastic neural network ever to be simulated on neuromorphic hardware. We also run a comparable simulation on a Cray XC-30 supercomputer system and find that, if it is to match the run-time of our SpiNNaker simulation, the super computer system uses approximately more power. This suggests that cheaper, more power efficient neuromorphic systems are becoming useful discovery tools in the study of plasticity in large-scale brain models.

  11. Mutations in the nervous system--specific HSN2 exon of WNK1 cause hereditary sensory neuropathy type II.

    Science.gov (United States)

    Shekarabi, Masoud; Girard, Nathalie; Rivière, Jean-Baptiste; Dion, Patrick; Houle, Martin; Toulouse, André; Lafrenière, Ronald G; Vercauteren, Freya; Hince, Pascale; Laganiere, Janet; Rochefort, Daniel; Faivre, Laurence; Samuels, Mark; Rouleau, Guy A

    2008-07-01

    Hereditary sensory and autonomic neuropathy type II (HSANII) is an early-onset autosomal recessive disorder characterized by loss of perception to pain, touch, and heat due to a loss of peripheral sensory nerves. Mutations in hereditary sensory neuropathy type II (HSN2), a single-exon ORF originally identified in affected families in Quebec and Newfoundland, Canada, were found to cause HSANII. We report here that HSN2 is a nervous system-specific exon of the with-no-lysine(K)-1 (WNK1) gene. WNK1 mutations have previously been reported to cause pseudohypoaldosteronism type II but have not been studied in the nervous system. Given the high degree of conservation of WNK1 between mice and humans, we characterized the structure and expression patterns of this isoform in mice. Immunodetections indicated that this Wnk1/Hsn2 isoform was expressed in sensory components of the peripheral nervous system and CNS associated with relaying sensory and nociceptive signals, including satellite cells, Schwann cells, and sensory neurons. We also demonstrate that the novel protein product of Wnk1/Hsn2 was more abundant in sensory neurons than motor neurons. The characteristics of WNK1/HSN2 point to a possible role for this gene in the peripheral sensory perception deficits characterizing HSANII.

  12. Development of sensory system s related with postural - locomotor function in toddler ́s age, possibilities of assessmen

    OpenAIRE

    Blažková, Markéta

    2014-01-01

    Bachelor's thesis "Development of sensory systems related with postural-locomotor function in toddler's age, possibilities of assessment" summarizes function of visual, vestibular and somatosensory system and maturation of these systems in toddler's age. Next part describes the development of postural- locomotor function related to maturation of sensory systems. The last part of the work deals with the issue of assessment in toddler's age. Three toddlers are described in the practical part of...

  13. Peripheral nervous system maturation in preterm infants: longitudinal motor and sensory nerve conduction studies.

    Science.gov (United States)

    Lori, S; Bertini, Giovanna; Bastianelli, M; Gabbanini, S; Gualandi, D; Molesti, E; Dani, C

    2018-04-10

    To study the evolution of sensory-motor nerves in the upper and lower limbs in neurologically healthy preterm infants and to use sensory-motor studies to compare the rate of maturation in preterm infants at term age and full-term healthy neonates. The study comprised 26 neurologically normal preterm infants born at 23-33 weeks of gestational age, who underwent sensory nerve conduction and motor nerve conduction studies from plantar medial and median nerves and from tibial and ulnar nerves, respectively. We repeated the same neurophysiological studies in 19 of the preterm infants every 2 weeks until postnatal term age. The data from the preterm infants at term was matched with a group of ten full-term babies a few days after birth. The motor nerve conduction velocity of the tibial and ulnar nerves showed progressive increases in values in relation to gestational age, but there was a decrease of values in distal latencies and F wave latencies. Similarly, there was a gradual increase of sensory nerve conduction velocity values of the medial plantar and median nerves and decreases in latencies in relation to gestational age. At term age, the preterm infants showed significantly lower values of conduction velocities and distal latencies than the full-term neonates. These results were probably because the preterm infants had significantly lower weights, total length and, in particular, distal segments of the limbs at term age. The sensory-motor conduction parameters were clearly related to gestational age, but extrauterine life did not affect the maturation of the peripheral nervous system in the very preterm babies who were neurologically healthy.

  14. Gradual Reduction in Sodium Content in Cooked Ham, with Corresponding Change in Sensorial Properties Measured by Sensory Evaluation and a Multimodal Machine Vision System.

    Directory of Open Access Journals (Sweden)

    Kirsti Greiff

    Full Text Available The European diet today generally contains too much sodium (Na(+. A partial substitution of NaCl by KCl has shown to be a promising method for reducing sodium content. The aim of this work was to investigate the sensorial changes of cooked ham with reduced sodium content. Traditional sensorial evaluation and objective multimodal machine vision were used. The salt content in the hams was decreased from 3.4% to 1.4%, and 25% of the Na(+ was replaced by K(+. The salt reduction had highest influence on the sensory attributes salty taste, after taste, tenderness, hardness and color hue. The multimodal machine vision system showed changes in lightness, as a function of reduced salt content. Compared to the reference ham (3.4% salt, a replacement of Na(+-ions by K(+-ions of 25% gave no significant changes in WHC, moisture, pH, expressed moisture, the sensory profile attributes or the surface lightness and shininess. A further reduction of salt down to 1.7-1.4% salt, led to a decrease in WHC and an increase in expressible moisture.

  15. Gradual Reduction in Sodium Content in Cooked Ham, with Corresponding Change in Sensorial Properties Measured by Sensory Evaluation and a Multimodal Machine Vision System.

    Science.gov (United States)

    Greiff, Kirsti; Mathiassen, John Reidar; Misimi, Ekrem; Hersleth, Margrethe; Aursand, Ida G

    2015-01-01

    The European diet today generally contains too much sodium (Na(+)). A partial substitution of NaCl by KCl has shown to be a promising method for reducing sodium content. The aim of this work was to investigate the sensorial changes of cooked ham with reduced sodium content. Traditional sensorial evaluation and objective multimodal machine vision were used. The salt content in the hams was decreased from 3.4% to 1.4%, and 25% of the Na(+) was replaced by K(+). The salt reduction had highest influence on the sensory attributes salty taste, after taste, tenderness, hardness and color hue. The multimodal machine vision system showed changes in lightness, as a function of reduced salt content. Compared to the reference ham (3.4% salt), a replacement of Na(+)-ions by K(+)-ions of 25% gave no significant changes in WHC, moisture, pH, expressed moisture, the sensory profile attributes or the surface lightness and shininess. A further reduction of salt down to 1.7-1.4% salt, led to a decrease in WHC and an increase in expressible moisture.

  16. Fine-scale topography in sensory systems: insights from Drosophila and vertebrates.

    Science.gov (United States)

    Kaneko, Takuya; Ye, Bing

    2015-09-01

    To encode the positions of sensory stimuli, sensory circuits form topographic maps in the central nervous system through specific point-to-point connections between pre- and postsynaptic neurons. In vertebrate visual systems, the establishment of topographic maps involves the formation of a coarse topography followed by that of fine-scale topography that distinguishes the axon terminals of neighboring neurons. It is known that intrinsic differences in the form of broad gradients of guidance molecules instruct coarse topography while neuronal activity is required for fine-scale topography. On the other hand, studies in the Drosophila visual system have shown that intrinsic differences in cell adhesion among the axon terminals of neighboring neurons instruct the fine-scale topography. Recent studies on activity-dependent topography in the Drosophila somatosensory system have revealed a role of neuronal activity in creating molecular differences among sensory neurons for establishing fine-scale topography, implicating a conserved principle. Here we review the findings in both Drosophila and vertebrates and propose an integrated model for fine-scale topography.

  17. Bidirectional communication between sensory neurons and osteoblasts in an in vitro coculture system.

    Science.gov (United States)

    Kodama, Daisuke; Hirai, Takao; Kondo, Hisataka; Hamamura, Kazunori; Togari, Akifumi

    2017-02-01

    Recent studies have revealed that the sensory nervous system is involved in bone metabolism. However, the mechanism of communication between neurons and osteoblasts is yet to be elucidated. In this study, we investigated the signaling pathways between sensory neurons of the dorsal root ganglion (DRG) and the osteoblast-like MC3T3-E1 cells using an in vitro coculture system. Our findings indicate that signal transduction from DRG-derived neurons to MC3T3-E1 cells is suppressed by antagonists of the AMPA receptor and the NK 1 receptor. Conversely, signal transduction from MC3T3-E1 cells to DRG-derived neurons is suppressed by a P2X 7 receptor antagonist. Our results suggest that these cells communicate with each other by exocytosis of glutamate, substance P in the efferent signal, and ATP in the afferent signal. © 2017 Federation of European Biochemical Societies.

  18. Synapse-centric mapping of cortical models to the SpiNNaker neuromorphic architecture

    Directory of Open Access Journals (Sweden)

    James Courtney Knight

    2016-09-01

    Full Text Available While the adult human brain has approximately 8.8x10^10 neurons, this number is dwarfed by its 1x10^15 synapses. From the point of view of neuromorphic engineering and neural simulation in general this makes the simulation of these synapses a particularly complex problem. SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Current solutions for simulating spiking neural networks on SpiNNaker are heavily inspired by work on distributed high-performance computing. However, while SpiNNaker shares many characteristics with such distributed systems, its component nodes have much more limited resources and, as the system lacks global synchronization, the computation performed on each node must complete within a fixed time step. We first analyze the performance of the current SpiNNaker neural simulation software and identify several problems that occur when it is used to simulate networks of the type often used to model the cortex which contain large numbers of sparsely connected synapses. We then present a new, more flexible approach for mapping the simulation of such networks to SpiNNaker which solves many of these problems. Finally we analyze the performance of our new approach using both benchmarks, designed to represent cortical connectivity, and larger, functional cortical models. In a benchmark network where neurons receive input from 8000 STDP synapses, our new approach allows more neurons to be simulated on each SpiNNaker core than has been previously possible. We also demonstrate that the largest plastic neural network previously simulated on neuromorphic hardware can be run in real time using our new approach: double the speed that was previously achieved. Additionally this network contains two types of plastic synapse which previously had to be trained separately but, using our new approach, can be trained simultaneously.

  19. Sensory System for Implementing a Human—Computer Interface Based on Electrooculography

    Directory of Open Access Journals (Sweden)

    Sergio Ortega

    2010-12-01

    Full Text Available This paper describes a sensory system for implementing a human–computer interface based on electrooculography. An acquisition system captures electrooculograms and transmits them via the ZigBee protocol. The data acquired are analysed in real time using a microcontroller-based platform running the Linux operating system. The continuous wavelet transform and neural network are used to process and analyse the signals to obtain highly reliable results in real time. To enhance system usability, the graphical interface is projected onto special eyewear, which is also used to position the signal-capturing electrodes.

  20. Selective Attention in Multi-Chip Address-Event Systems

    Directory of Open Access Journals (Sweden)

    Giacomo Indiveri

    2009-06-01

    Full Text Available Selective attention is the strategy used by biological systems to cope with the inherent limits in their available computational resources, in order to efficiently process sensory information. The same strategy can be used in artificial systems that have to process vast amounts of sensory data with limited resources. In this paper we present a neuromorphic VLSI device, the “Selective Attention Chip” (SAC, which can be used to implement these models in multi-chip address-event systems. We also describe a real-time sensory-motor system, which integrates the SAC with a dynamic vision sensor and a robotic actuator. We present experimental results from each component in the system, and demonstrate how the complete system implements a real-time stimulus-driven selective attention model.

  1. Selective attention in multi-chip address-event systems.

    Science.gov (United States)

    Bartolozzi, Chiara; Indiveri, Giacomo

    2009-01-01

    Selective attention is the strategy used by biological systems to cope with the inherent limits in their available computational resources, in order to efficiently process sensory information. The same strategy can be used in artificial systems that have to process vast amounts of sensory data with limited resources. In this paper we present a neuromorphic VLSI device, the "Selective Attention Chip" (SAC), which can be used to implement these models in multi-chip address-event systems. We also describe a real-time sensory-motor system, which integrates the SAC with a dynamic vision sensor and a robotic actuator. We present experimental results from each component in the system, and demonstrate how the complete system implements a real-time stimulus-driven selective attention model.

  2. Using neuromorphic optical sensors for spacecraft absolute and relative navigation

    Science.gov (United States)

    Shake, Christopher M.

    We develop a novel attitude determination system (ADS) for use on nano spacecraft using neuromorphic optical sensors. The ADS intends to support nano-satellite operations by providing low-cost, low-mass, low-volume, low-power, and redundant attitude determination capabilities with quick and straightforward onboard programmability for real time spacecraft operations. The ADS is experimentally validated with commercial-off-the-shelf optical devices that perform sensing and image processing on the same circuit board and are biologically inspired by insects' vision systems, which measure optical flow while navigating in the environment. The firmware on the devices is modified to both perform the additional biologically inspired task of tracking objects and communicate with a PC/104 form-factor embedded computer running Real Time Application Interface Linux used on a spacecraft simulator. Algorithms are developed for operations using optical flow, point tracking, and hybrid modes with the sensors, and the performance of the system in all three modes is assessed using a spacecraft simulator in the Advanced Autonomous Multiple Spacecraft (ADAMUS) laboratory at Rensselaer. An existing relative state determination method is identified to be combined with the novel ADS to create a self-contained navigation system for nano spacecraft. The performance of the method is assessed in simulation and found not to match the results from its authors using only conditions and equations already published. An improved target inertia tensor method is proposed as an update to the existing relative state method, but found not to perform as expected, but is presented for others to build upon.

  3. ChR2 transgenic animals in peripheral sensory system: Sensing light as various sensations.

    Science.gov (United States)

    Ji, Zhi-Gang; Wang, Hongxia

    2016-04-01

    Since the introduction of Channelrhodopsin-2 (ChR2) to neuroscience, optogenetics technology was developed, making it possible to activate specific neurons or circuits with spatial and temporal precision. Various ChR2 transgenic animal models have been generated and are playing important roles in revealing the mechanisms of neural activities, mapping neural circuits, controlling the behaviors of animals as well as exploring new strategy for treating the neurological diseases in both central and peripheral nervous system. An animal including humans senses environments through Aristotle's five senses (sight, hearing, smell, taste and touch). Usually, each sense is associated with a kind of sensory organ (eyes, ears, nose, tongue and skin). Is it possible that one could hear light, smell light, taste light and touch light? When ChR2 is targeted to different peripheral sensory neurons by viral vectors or generating ChR2 transgenic animals, the animals can sense the light as various sensations such as hearing, touch, pain, smell and taste. In this review, we focus on ChR2 transgenic animals in the peripheral nervous system. Firstly the working principle of ChR2 as an optogenetic actuator is simply described. Then the current transgenic animal lines where ChR2 was expressed in peripheral sensory neurons are presented and the findings obtained by these animal models are reviewed. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. A Radiation Learning Support System by Tri-sensory Augmented Reality using a Mobile Phone

    International Nuclear Information System (INIS)

    Shimoda, Hiroshi; Zhao, Yue; Yan, Weida; Ishii, Hirotake

    2011-01-01

    A radiation learning support system has been developed to support learning basic knowledge of radiation and its influence on the human body by using tri-sensory Augmented Reality (AR) technology with presenting information to visual, auditory and tactile sensation. The system consists of a knowledge learning mode in which learners can learn basic knowledge of radiation and an experience learning mode in which they can virtually experience its influence on the human body under various conditions. As the result of a simple evaluation, it was suggested that the system improves the learners' intuitive understanding, and information presentation to auditory and tactile sensation is more effective than that to visual sensation

  5. American Sign Language Alphabet Recognition Using a Neuromorphic Sensor and an Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Miguel Rivera-Acosta

    2017-09-01

    Full Text Available This paper reports the design and analysis of an American Sign Language (ASL alphabet translation system implemented in hardware using a Field-Programmable Gate Array. The system process consists of three stages, the first being the communication with the neuromorphic camera (also called Dynamic Vision Sensor, DVS sensor using the Universal Serial Bus protocol. The feature extraction of the events generated by the DVS is the second part of the process, consisting of a presentation of the digital image processing algorithms developed in software, which aim to reduce redundant information and prepare the data for the third stage. The last stage of the system process is the classification of the ASL alphabet, achieved with a single artificial neural network implemented in digital hardware for higher speed. The overall result is the development of a classification system using the ASL signs contour, fully implemented in a reconfigurable device. The experimental results consist of a comparative analysis of the recognition rate among the alphabet signs using the neuromorphic camera in order to prove the proper operation of the digital image processing algorithms. In the experiments performed with 720 samples of 24 signs, a recognition accuracy of 79.58% was obtained.

  6. Pursuit, Avoidance, and Cohesion in Flight: Multi-Purpose Control Laws and Neuromorphic VLSI

    Science.gov (United States)

    2010-10-01

    spatial navigation in mammals. We have designed, fabricated, and are now testing a neuromorphic VLSI chip that implements a spike-based, attractor...Control Laws and Neuromorphic VLSI 5a. CONTRACT NUMBER 070402-7705 5b. GRANT NUMBER FA9550-07-1-0446 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S...implementations (custom Neuromorphic VLSI and robotics) we will apply important practical constraints that can lead to deeper insight into how and why efficient

  7. Correlation Of An E-Nose System For Odor Assessment Of Shoe/Sock Systems With A Human Sensory Panel

    International Nuclear Information System (INIS)

    Horras, Stephan; Reimann, Peter; Schuetze, Andreas; Gaiotto, Alessandra; Mayer, Maria

    2009-01-01

    Evaluation of strength and quality of smell is today still primarily done with human sensory panels. For a range of applications, technical systems for an objective smell assessment would provide a great benefit in R and D and also day-to-day application. The project presented here specifically addresses the problem of assessing the strength and unpleasantness of smell caused by sweat in shoes and socks by an E-nose system. The ultimate goal is to provide a tool for developing improved shoe/sock systems with optimized materials.The main approach to achieve this goal is to find a correlation between the assessment of a human sensory panel and the complex sensor response patterns of an E-Nose system to appraise the smell of sweat in shoes and socks. Therefore a range of test persons wear shoes and socks under defined ambient conditions in a controlled test environment as well as during everyday use. Afterwards the smell of the shoes and socks is both measured with the E-Nose system and assessed by a human sensory panel. We report here the results of the first larger test series and the identified correlation between the E-Nose system and the human assessment of the smell of sweat.

  8. Wrist ambulatory monitoring system and smart glove for real time emotional, sensorial and physiological analysis.

    Science.gov (United States)

    Axisa, F; Gehin, C; Delhomme, G; Collet, C; Robin, O; Dittmar, A

    2004-01-01

    Improvement of the quality and efficiency of the quality of health in medicine, at home and in hospital becomes more and more important Designed to be user-friendly, smart clothes and gloves fit well for such a citizen use and health monitoring. Analysis of the autonomic nervous system using non-invasive sensors provides information for the emotional, sensorial, cognitive and physiological analysis. MARSIAN (modular autonomous recorder system for the measurement of autonomic nervous system) is a wrist ambulatory monitoring and recording system with a smart glove with sensors for the detection of the activity of the autonomic nervous system. It is composed of a "smart tee shirt", a "smart glove", a wrist device and PC which records data. The smart glove is one of the key point of MARSIAN. Complex movements, complex geometry, sensation make smart glove designing a challenge. MARSIAN has a large field of applications and researches (vigilance, behaviour, sensorial analysis, thermal environment for human, cognition science, sport, etc...) in various fields like neurophysiology, affective computing and health monitoring.

  9. Adaptive stimulus optimization and model-based experiments for sensory systems neuroscience

    Directory of Open Access Journals (Sweden)

    Christopher eDiMattina

    2013-06-01

    Full Text Available In this paper we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical textit{optimal stimulus} paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the textit{iso-response} paradigm which finds sets of stimuli giving rise to constant responses, and the textit{system identification} paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of nonlinear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify nonlinear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and towards a new paradigm of real-time model estimation and comparison.

  10. Mini-UAV based sensory system for measuring environmental variables in greenhouses.

    Science.gov (United States)

    Roldán, Juan Jesús; Joossen, Guillaume; Sanz, David; del Cerro, Jaime; Barrientos, Antonio

    2015-02-02

    This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV). The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover). The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor.

  11. Mini-UAV Based Sensory System for Measuring Environmental Variables in Greenhouses

    Directory of Open Access Journals (Sweden)

    Juan Jesús Roldán

    2015-02-01

    Full Text Available This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV. The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover. The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor.

  12. Functional consequences of structural differences in stingray sensory systems. Part I: mechanosensory lateral line canals.

    Science.gov (United States)

    Jordan, Laura K; Kajiura, Stephen M; Gordon, Malcolm S

    2009-10-01

    Short range hydrodynamic and electrosensory signals are important during final stages of prey capture in elasmobranchs (sharks, skates and rays), and may be particularly useful for dorso-ventrally flattened batoids with mouths hidden from their eyes. In stingrays, both the lateral line canal and electrosensory systems are highly modified and complex with significant differences on ventral surfaces that relate to feeding ecology. This study tests functional hypotheses based on quantified differences in sensory system morphology of three stingray species, Urobatis halleri, Myliobatis californica and Pteroplatytrygon violacea. Part I investigates the mechanosensory lateral line canal system whereas part II focuses on the electrosensory system. Stingray lateral line canals include both pored and non-pored sections and differ in branching complexity and distribution. A greater proportion of pored canals and high pore numbers were predicted to correspond to increased response to water flow. Behavioral experiments were performed to compare responses of stingrays to weak water jets mimicking signals produced by potential prey at velocities of 10-20 cm s(-1). Bat rays, M. californica, have the most complex and broadly distributed pored canal network and demonstrated both the highest response rate and greater response intensity to water jet signals. Results suggest that U. halleri and P. violacea may rely on additional sensory input, including tactile and visual cues, respectively, to initiate stronger feeding responses. These results suggest that stingray lateral line canal morphology can indicate detection capabilities through responsiveness to weak water jets.

  13. Features functional activity kinesthetic and visual sensory systems in athletes of different specializations

    Directory of Open Access Journals (Sweden)

    Anatoliy Rovnyy

    2015-02-01

    Full Text Available Purpose: to establish specific effects of different sports on functional status and co mood kinesthetic and visual analyzers skilled athletes. Materials and Methods: the study was conducted on athletes qualified five sports: modern pentathlon, volleyball, basketball, handball and fencing. We used methods of difference sensometry and mathematical statistics. Results revealed that the sensitivity of sensor systems depend on the specifics of sports activities and sports equipment. Conclusions: the complex is set internally sensor and between sensory bonds that are formed on the basis of the specific sports activity.

  14. A Multimodal Learning System for Individuals with Sensorial, Neuropsychological, and Relational Impairments

    Directory of Open Access Journals (Sweden)

    Sergio Canazza

    2013-01-01

    Full Text Available This paper presents a system for an interactive multimodal environment able (i to train the listening comprehension in various populations of pupils, both Italian and immigrants, having different disabilities and (ii to assess speech production and discrimination. The proposed system is the result of a research project focused on pupils with sensorial, neuropsychological, and relational impairments. The project involves innovative technological systems that the users (speech terabits psychologists and preprimary and primary schools teachers could adopt for training and assessment of language and speech. Because the system is used in a real scenario (the Italian schools are often affected by poor funding for education and teachers without informatics skills, the guidelines adopted are low-cost technology; usability; customizable system; robustness.

  15. Development of Neuromorphic Sift Operator with Application to High Speed Image Matching

    Science.gov (United States)

    Shankayi, M.; Saadatseresht, M.; Bitetto, M. A. V.

    2015-12-01

    There was always a speed/accuracy challenge in photogrammetric mapping process, including feature detection and matching. Most of the researches have improved algorithm's speed with simplifications or software modifications which increase the accuracy of the image matching process. This research tries to improve speed without enhancing the accuracy of the same algorithm using Neuromorphic techniques. In this research we have developed a general design of a Neuromorphic ASIC to handle algorithms such as SIFT. We also have investigated neural assignment in each step of the SIFT algorithm. With a rough estimation based on delay of the used elements including MAC and comparator, we have estimated the resulting chip's performance for 3 scenarios, Full HD movie (Videogrammetry), 24 MP (UAV photogrammetry), and 88 MP image sequence. Our estimations led to approximate 3000 fps for Full HD movie, 250 fps for 24 MP image sequence and 68 fps for 88MP Ultracam image sequence which can be a huge improvement for current photogrammetric processing systems. We also estimated the power consumption of less than10 watts which is not comparable to current workflows.

  16. Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform

    Directory of Open Access Journals (Sweden)

    Massimiliano eGiulioni

    2016-02-01

    Full Text Available We demonstrate robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission and follows the basic theoretical principles presented in (Benosman et al. 2014: the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. The same basic principle is embedded in the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina. Mimicking those cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. We built a 3x3 test grid of independent detectors, each observing a different portion of the scene, so that our final output is a spike train encoding a 3x3 optical flow vector field. In this work we focus on the architectural aspects, and we demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene.

  17. Functional imaging of the semantic system: retrieval of sensory-experienced and verbally learned knowledge.

    Science.gov (United States)

    Noppeney, Uta; Price, Cathy J

    2003-01-01

    This paper considers how functional neuro-imaging can be used to investigate the organization of the semantic system and the limitations associated with this technique. The majority of the functional imaging studies of the semantic system have looked for divisions by varying stimulus category. These studies have led to divergent results and no clear anatomical hypotheses have emerged to account for the dissociations seen in behavioral studies. Only a few functional imaging studies have used task as a variable to differentiate the neural correlates of semantic features more directly. We extend these findings by presenting a new study that contrasts tasks that differentially weight sensory (color and taste) and verbally learned (origin) semantic features. Irrespective of the type of semantic feature retrieved, a common semantic system was activated as demonstrated in many previous studies. In addition, the retrieval of verbally learned, but not sensory-experienced, features enhanced activation in medial and lateral posterior parietal areas. We attribute these "verbally learned" effects to differences in retrieval strategy and conclude that evidence for segregation of semantic features at an anatomical level remains weak. We believe that functional imaging has the potential to increase our understanding of the neuronal infrastructure that sustains semantic processing but progress may require multiple experiments until a consistent explanatory framework emerges.

  18. Static Posturography and Falls According to Pyramidal, Sensory and Cerebellar Functional Systems in People with Multiple Sclerosis

    Science.gov (United States)

    Kalron, Alon; Givon, Uri; Frid, Lior; Dolev, Mark; Achiron, Anat

    2016-01-01

    Balance impairment is common in people with multiple sclerosis (PwMS) and frequently impacts quality of life by decreasing mobility and increasing the risk of falling. However, there are only scarce data examining the contribution of specific neurological functional systems on balance measures in MS. Therefore, the primary aim of our study was to examine the differences in posturography parameters and fall incidence according to the pyramidal, cerebellar and sensory systems functional systems in PwMS. The study included 342 PwMS, 211 women and mean disease duration of 8.2 (S.D = 8.3) years. The study sample was divided into six groups according to the pyramidal, cerebellar and sensory functional system scores, derived from the Expanded Disability Status Scale (EDSS) data. Static postural control parameters were obtained from the Zebris FDM-T Treadmill (zebris® Medical GmbH, Germany). Participants were defined as "fallers" and "non-fallers" based on their fall history. Our findings revealed a trend that PwMS affected solely in the pyramidal system, have reduced stability compared to patients with cerebellar and sensory dysfunctions. Moreover, the addition of sensory impairments to pyramidal dysfunction does not exacerbate postural control. The patients in the pure sensory group demonstrated increased stability compared to each of the three combined groups; pyramidal-cerebellar, pyramidal-sensory and pyramidal-cerebellar-sensory groups. As for fall status, the percentage of fallers in the pure pyramidal, cerebellar and sensory groups were 44.3%, 33.3% and 19.5%, respectively. As for the combined functional system groups, the percentage of fallers in the pyramidal-cerebellar, pyramidal-sensory and pyramidal-cerebellar-sensory groups were 59.7%, 40.7% and 65%, respectively. This study confirms that disorders in neurological functional systems generate different effects on postural control and incidence of falls in the MS population. From a clinical standpoint, the

  19. Static Posturography and Falls According to Pyramidal, Sensory and Cerebellar Functional Systems in People with Multiple Sclerosis.

    Science.gov (United States)

    Kalron, Alon; Givon, Uri; Frid, Lior; Dolev, Mark; Achiron, Anat

    2016-01-01

    Balance impairment is common in people with multiple sclerosis (PwMS) and frequently impacts quality of life by decreasing mobility and increasing the risk of falling. However, there are only scarce data examining the contribution of specific neurological functional systems on balance measures in MS. Therefore, the primary aim of our study was to examine the differences in posturography parameters and fall incidence according to the pyramidal, cerebellar and sensory systems functional systems in PwMS. The study included 342 PwMS, 211 women and mean disease duration of 8.2 (S.D = 8.3) years. The study sample was divided into six groups according to the pyramidal, cerebellar and sensory functional system scores, derived from the Expanded Disability Status Scale (EDSS) data. Static postural control parameters were obtained from the Zebris FDM-T Treadmill (zebris® Medical GmbH, Germany). Participants were defined as "fallers" and "non-fallers" based on their fall history. Our findings revealed a trend that PwMS affected solely in the pyramidal system, have reduced stability compared to patients with cerebellar and sensory dysfunctions. Moreover, the addition of sensory impairments to pyramidal dysfunction does not exacerbate postural control. The patients in the pure sensory group demonstrated increased stability compared to each of the three combined groups; pyramidal-cerebellar, pyramidal-sensory and pyramidal-cerebellar-sensory groups. As for fall status, the percentage of fallers in the pure pyramidal, cerebellar and sensory groups were 44.3%, 33.3% and 19.5%, respectively. As for the combined functional system groups, the percentage of fallers in the pyramidal-cerebellar, pyramidal-sensory and pyramidal-cerebellar-sensory groups were 59.7%, 40.7% and 65%, respectively. This study confirms that disorders in neurological functional systems generate different effects on postural control and incidence of falls in the MS population. From a clinical standpoint, the

  20. Experimental System for Investigation of Visual Sensory Input in Postural Feedback Control

    Directory of Open Access Journals (Sweden)

    Jozef Pucik

    2012-01-01

    Full Text Available The human postural control system represents a biological feedback system responsible for maintenance of upright stance. Vestibular, proprioceptive and visual sensory inputs provide the most important information into the control system, which controls body centre of mass (COM in order to stabilize the human body resembling an inverted pendulum. The COM can be measured indirectly by means of a force plate as the centre of pressure (COP. Clinically used measurement method is referred to as posturography. In this paper, the conventional static posturography is extended by visual stimulation, which provides insight into a role of visual information in balance control. Visual stimuli have been designed to induce body sway in four specific directions – forward, backward, left and right. Stabilograms were measured using proposed single-PC based system and processed to calculate velocity waveforms and posturographic parameters. The parameters extracted from pre-stimulus and on-stimulus periods exhibit statistically significant differences.

  1. A neuromorphic circuit mimicking biological short-term memory.

    Science.gov (United States)

    Barzegarjalali, Saeid; Parker, Alice C

    2016-08-01

    Research shows that the way we remember things for a few seconds is a different mechanism from the way we remember things for a longer time. Short-term memory is based on persistently firing neurons, whereas storing information for a longer time is based on strengthening the synapses or even forming new neural connections. Information about location and appearance of an object is segregated and processed by separate neurons. Furthermore neurons can continue firing using different mechanisms. Here, we have designed a biomimetic neuromorphic circuit that mimics short-term memory by firing neurons, using biological mechanisms to remember location and shape of an object. Our neuromorphic circuit has a hybrid architecture. Neurons are designed with CMOS 45nm technology and synapses are designed with carbon nanotubes (CNT).

  2. Towards neuromorphic electronics: Memristors on foldable silicon fabric

    KAUST Repository

    Ghoneim, Mohamed T.

    2014-11-01

    The advantages associated with neuromorphic computation are rich areas of complex research. We address the fabrication challenge of building neuromorphic devices on structurally foldable platform with high integration density. We present a CMOS compatible fabrication process to demonstrate for the first time memristive devices fabricated on bulk monocrystalline silicon (100) which is next transformed into a flexible thin sheet of silicon fabric with all the pre-fabricated devices. This process preserves the ultra-high integration density advantage unachievable on other flexible substrates. In addition, the memristive devices are of the size of a motor neuron and the flexible/folded architectural form factor is critical to match brain cortex\\'s folded pattern for ultra-compact design.

  3. Qualitative Functional Decomposition Analysis of Evolved Neuromorphic Flight Controllers

    Directory of Open Access Journals (Sweden)

    Sanjay K. Boddhu

    2012-01-01

    Full Text Available In the previous work, it was demonstrated that one can effectively employ CTRNN-EH (a neuromorphic variant of EH method methodology to evolve neuromorphic flight controllers for a flapping wing robot. This paper describes a novel frequency grouping-based analysis technique, developed to qualitatively decompose the evolved controllers into explainable functional control blocks. A summary of the previous work related to evolving flight controllers for two categories of the controller types, called autonomous and nonautonomous controllers, is provided, and the applicability of the newly developed decomposition analysis for both controller categories is demonstrated. Further, the paper concludes with appropriate discussion of ongoing work and implications for possible future work related to employing the CTRNN-EH methodology and the decomposition analysis techniques presented in this paper.

  4. Peptidomics and Secretomics of the Mammalian Peripheral Sensory-Motor System

    Science.gov (United States)

    Tillmaand, Emily G.; Yang, Ning; Kindt, Callie A. C.; Romanova, Elena V.; Rubakhin, Stanislav S.; Sweedler, Jonathan V.

    2015-12-01

    The dorsal root ganglion (DRG) and its anatomically and functionally associated spinal nerve and ventral and dorsal roots are important components of the peripheral sensory-motor system in mammals. The cells within these structures use a number of peptides as intercellular signaling molecules. We performed a variety of mass spectrometry (MS)-based characterizations of peptides contained within and secreted from these structures, and from isolated and cultured DRG cells. Liquid chromatography-Fourier transform MS was utilized in DRG and nerve peptidome analysis. In total, 2724 peptides from 296 proteins were identified in tissue extracts. Neuropeptides are among those detected, including calcitonin gene-related peptide I, little SAAS, and known hemoglobin-derived peptides. Solid phase extraction combined with direct matrix-assisted laser desorption/ionization time-of-flight MS was employed to investigate the secretome of these structures. A number of peptides were detected in the releasate from semi-intact preparations of DRGs and associated nerves, including neurofilament- and myelin basic protein-related peptides. A smaller set of analytes was observed in releasates from cultured DRG neurons. The peptide signals observed in the releasates have been mass-matched to those characterized and identified in homogenates of entire DRGs and associated nerves. This data aids our understanding of the chemical composition of the mammalian peripheral sensory-motor system, which is involved in key physiological functions such as nociception, thermoreception, itch sensation, and proprioception.

  5. Weighted integration of short-term memory and sensory signals in the oculomotor system.

    Science.gov (United States)

    Deravet, Nicolas; Blohm, Gunnar; de Xivry, Jean-Jacques Orban; Lefèvre, Philippe

    2018-05-01

    Oculomotor behaviors integrate sensory and prior information to overcome sensory-motor delays and noise. After much debate about this process, reliability-based integration has recently been proposed and several models of smooth pursuit now include recurrent Bayesian integration or Kalman filtering. However, there is a lack of behavioral evidence in humans supporting these theoretical predictions. Here, we independently manipulated the reliability of visual and prior information in a smooth pursuit task. Our results show that both smooth pursuit eye velocity and catch-up saccade amplitude were modulated by visual and prior information reliability. We interpret these findings as the continuous reliability-based integration of a short-term memory of target motion with visual information, which support modeling work. Furthermore, we suggest that saccadic and pursuit systems share this short-term memory. We propose that this short-term memory of target motion is quickly built and continuously updated, and constitutes a general building block present in all sensorimotor systems.

  6. Systemic Chemical Desensitization of Peptidergic Sensory Neurons with Resiniferatoxin Inhibits Experimental Periodontitis

    Science.gov (United States)

    Breivik, Torbjørn; Gundersen, Yngvar; Gjermo, Per; Fristad, Inge; Opstad, Per Kristian

    2011-01-01

    Background and objective: The immune system is an important player in the pathophysiology of periodontitis. The brain controls immune responses via neural and hormonal pathways, and brain-neuro-endocrine dysregulation may be a central determinant for pathogenesis. Our current knowledge also emphasizes the central role of sensory nerves. In line with this, we wanted to investigate how desensitization of peptidergic sensory neurons influences the progression of ligature-induced periodontitis, and, furthermore, how selected cytokine and stress hormone responses to Gram-negative bacterial lipopolysaccharide (LPS) stimulation are affected. Material and methods: Resiniferatoxin (RTX; 50 μg/kg) or vehicle was injected subcutaneously on days 1, 2, and 3 in stress high responding and periodontitis-susceptible Fischer 344 rats. Periodontitis was induced 2 days thereafter. Progression of the disease was assessed after the ligatures had been in place for 20 days. Two h before decapitation all rats received LPS (150 μg/kg i.p.) to induce a robust immune and stress response. Results: Desensitization with RTX significantly reduced bone loss as measured by digital X-rays. LPS provoked a significantly higher increase in serum levels of the pro-inflammatory cytokine tumour necrosis factor (TNF)-α, but lower serum levels of the anti-inflammatory cytokine interleukin (IL)-10 and the stress hormone corticosterone. Conclusions: In this model RTX-induced chemical desensitization of sensory peptidergic neurons attenuated ligature-induced periodontitis and promoted a shift towards stronger pro-inflammatory cytokine and weaker stress hormone responses to LPS. The results may partly be explained by the attenuated transmission of immuno-inflammatory signals to the brain. In turn, this may weaken the anti-inflammatory brain-derived pathways. PMID:21339860

  7. Regenerative memory in time-delayed neuromorphic photonic resonators

    OpenAIRE

    Romeira, B.; Avó, R.; Figueiredo, José M. L.; Barland, S.; Javaloyes, J.

    2016-01-01

    We investigate a photonic regenerative memory based upon a neuromorphic oscillator with a delayed self-feedback (autaptic) connection. We disclose the existence of a unique temporal response characteristic of localized structures enabling an ideal support for bits in an optical buffer memory for storage and reshaping of data information. We link our experimental implementation, based upon a nanoscale nonlinear resonant tunneling diode driving a laser, to the paradigm of neuronal activity, the...

  8. A radiation learning support system by tri-sensory augmented reality using a mobile phone

    International Nuclear Information System (INIS)

    Shimoda, Hiroshi; Zhao, Yue; Yan, Weida; Ishii, Hirotake

    2011-01-01

    A radiation learning support system has been developed to support learning basic knowledge of radiation and its strength of human body impact by using tri-sensory Augmented Reality (AR) technology with presenting information to visual, auditory and haptic sensation. The system consists of a knowledge learning mode in which learners can learn basic knowledge of radiation and an experience learning mode in which they can virtually experience its strength of human body impact under various conditions. As the result of a simple evaluation, it was suggested that the system improves the learners' intuitive understanding, and information presentation of the radiation strength to auditory and haptic sensation is more comprehensive than that to visual sensation. (author)

  9. Design of fresh food sensory perceptual system for cold chain logistics

    Directory of Open Access Journals (Sweden)

    Zhang Ying

    2018-01-01

    Full Text Available According to the present stage low-level information of China's cold chain preservation, designed a kind of fresh food sensory perceptual system for cold chain logistics based on Internet of things. This system highly integrated applied many technologies such as the Internet of things technology, forecasting technology for fruits and vegetables preservation period, RFID and Planar bar code technology, big data and cloud computing technology and so on.Designed as a four-layer structure including sensing layer, network layer, control layer and user layer. The system can implement the real-time temperature and humidity environment parameters monitoring and early warning of the whole cold chain logistics for fresh agricultural products from picking, storage, transportation and processing link. It greatly improved the information level of cold chain circulation in our country and has a strong marketing value.

  10. Convolutional networks for fast, energy-efficient neuromorphic computing.

    Science.gov (United States)

    Esser, Steven K; Merolla, Paul A; Arthur, John V; Cassidy, Andrew S; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J; McKinstry, Jeffrey L; Melano, Timothy; Barch, Davis R; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D; Modha, Dharmendra S

    2016-10-11

    Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware's underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer.

  11. Convolutional networks for fast, energy-efficient neuromorphic computing

    Science.gov (United States)

    Esser, Steven K.; Merolla, Paul A.; Arthur, John V.; Cassidy, Andrew S.; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J.; McKinstry, Jeffrey L.; Melano, Timothy; Barch, Davis R.; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D.; Modha, Dharmendra S.

    2016-01-01

    Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware’s underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer. PMID:27651489

  12. Virtual Neurorobotics (VNR) to Accelerate Development of Plausible Neuromorphic Brain Architectures.

    Science.gov (United States)

    Goodman, Philip H; Buntha, Sermsak; Zou, Quan; Dascalu, Sergiu-Mihai

    2007-01-01

    Traditional research in artificial intelligence and machine learning has viewed the brain as a specially adapted information-processing system. More recently the field of social robotics has been advanced to capture the important dynamics of human cognition and interaction. An overarching societal goal of this research is to incorporate the resultant knowledge about intelligence into technology for prosthetic, assistive, security, and decision support applications. However, despite many decades of investment in learning and classification systems, this paradigm has yet to yield truly "intelligent" systems. For this reason, many investigators are now attempting to incorporate more realistic neuromorphic properties into machine learning systems, encouraged by over two decades of neuroscience research that has provided parameters that characterize the brain's interdependent genomic, proteomic, metabolomic, anatomic, and electrophysiological networks. Given the complexity of neural systems, developing tenable models to capture the essence of natural intelligence for real-time application requires that we discriminate features underlying information processing and intrinsic motivation from those reflecting biological constraints (such as maintaining structural integrity and transporting metabolic products). We propose herein a conceptual framework and an iterative method of virtual neurorobotics (VNR) intended to rapidly forward-engineer and test progressively more complex putative neuromorphic brain prototypes for their ability to support intrinsically intelligent, intentional interaction with humans. The VNR system is based on the viewpoint that a truly intelligent system must be driven by emotion rather than programmed tasking, incorporating intrinsic motivation and intentionality. We report pilot results of a closed-loop, real-time interactive VNR system with a spiking neural brain, and provide a video demonstration as online supplemental material.

  13. Virtual neurorobotics (VNR to accelerate development of plausible neuromorphic brain architectures

    Directory of Open Access Journals (Sweden)

    Philip H Goodman

    2007-11-01

    Full Text Available Traditional research in artificial intelligence and machine learning has viewed the brain as a specially adapted information-processing system. More recently the field of social robotics has been advanced to capture the important dynamics of human cognition and interaction. An overarching societal goal of this research is to incorporate the resultant knowledge about intelligence into technology for prosthetic, assistive, security, and decision support applications. However, despite many decades of investment in learning and classification systems, this paradigm has yet to yield truly “intelligent” systems. For this reason, many investigators are now attempting to incorporate more realistic neuromorphic properties into machine learning systems, encouraged by over two decades of neuroscience research that has provided parameters that characterize the brain’s interdependent genomic, proteomic, metabolomic, anatomic, and electrophysiological networks. Given the complexity of neural systems, developing tenable models to capture the essence of natural intelligence for real-time application requires that we discriminate features underlying information processing and intrinsic motivation from those reflecting biological constraints (such as maintaining structural integrity and transporting metabolic products. We propose herein a conceptual framework and an iterative method of virtual neurorobotics (VNR intended to rapidly forward-engineer and test progressively more complex putative neuromorphic brain prototypes for their ability to support intrinsically intelligent, intentional interaction with humans. The VNR system is based on the viewpoint that a truly intelligent system must be driven by emotion rather than programmed tasking, incorporating intrinsic motivation and intentionality. We report pilot results of a closed-loop, real-time interactive VNR system with a spiking neural brain, and provide a video demonstration as online supplemental

  14. Chemical and visual sensory systems in feeding behaviour of the Antarctic fish Ophthalmolycus amberensis (Zoarcidae

    Directory of Open Access Journals (Sweden)

    Edith Fanta

    2001-03-01

    Full Text Available The Antarctic eelpout Ophthalmolycus amberensis occurs in Admiralty Bay (King George Island, South Shetlands, at 140-200m depth, where light intensity is low. To assess behavioural and sensory adaptations for feeding under these conditions, laboratory tests were undertaken. Dead krill, fish fillet, and live amphipods were the preferred food items. Feeding responses were mainly induced by chemical stimuli. Visual stimuli were weak elicitors, leading to a long delay in the initiation of feeding behaviour. These fishes present a large olfactory epithelium, a high density of taste buds on the snout and close to the nostrils, and a retina that contained long rods, but no cones. Food selection was observed. Varied types of taste buds were present on the lips and in the oro-pharyngeal cavity. The capacity to use a chemo-sensory system as first elicitor for food detection, either in the absence or presence of light, allows O. amberensis to efficiently exploit different habitats at the sea bottom, in all Antarctic seasons.

  15. Anticipation from sensation: using anticipating synchronization to stabilize a system with inherent sensory delay.

    Science.gov (United States)

    Eberle, Henry; Nasuto, Slawomir J; Hayashi, Yoshikatsu

    2018-03-01

    We present a novel way of using a dynamical model for predictive tracking control that can adapt to a wide range of delays without parameter update. This is achieved by incorporating the paradigm of anticipating synchronization (AS), where a 'slave' system predicts a 'master' via delayed self-feedback. By treating the delayed output of the plant as one half of a 'sensory' AS coupling, the plant and an internal dynamical model can be synchronized such that the plant consistently leads the target's motion. We use two simulated robotic systems with differing arrangements of the plant and internal model ('parallel' and 'serial') to demonstrate that this form of control adapts to a wide range of delays without requiring the parameters of the controller to be changed.

  16. Sensory response system of social behavior tied to female reproductive traits.

    Directory of Open Access Journals (Sweden)

    Jennifer M Tsuruda

    Full Text Available Honey bees display a complex set of anatomical, physiological, and behavioral traits that correlate with the colony storage of surplus pollen (pollen hoarding. We hypothesize that the association of these traits is a result of pleiotropy in a gene signaling network that was co-opted by natural selection to function in worker division of labor and foraging specialization. By acting on the gene network, selection can change a suite of traits, including stimulus/response relationships that affect individual foraging behavior and alter the colony level trait of pollen hoarding. The 'pollen-hoarding syndrome' of honey bees is the best documented syndrome of insect social organization. It can be exemplified as a link between reproductive anatomy (ovary size, physiology (yolk protein level, and foraging behavior in honey bee strains selected for pollen hoarding, a colony level trait. The syndrome gave rise to the forager-Reproductive Ground Plan Hypothesis (RGPH, which proposes that the regulatory control of foraging onset and foraging preference toward nectar or pollen was derived from a reproductive signaling network. This view was recently challenged. To resolve the controversy, we tested the associations between reproductive anatomy, physiology, and stimulus/response relationships of behavior in wild-type honey bees.Central to the stimulus/response relationships of honey bee foraging behavior and pollen hoarding is the behavioral trait of sensory sensitivity to sucrose (an important sugar in nectar. To test the linkage of reproductive traits and sensory response systems of social behavior, we measured sucrose responsiveness with the proboscis extension response (PER assay and quantified ovary size and vitellogenin (yolk precursor gene expression in 6-7-day-old bees by counting ovarioles (ovary filaments and by using semiquantitative real time RT-PCR. We show that bees with larger ovaries (more ovarioles are characterized by higher levels of

  17. Research on the Sensory Design and Evaluation System for Food Shape and Color

    OpenAIRE

    Zhuo Yang

    2015-01-01

    Food sensory analysis technology is an important branch of Food Science, it is significant in new products development and innovation in food industry. In this study, food sensory analysis and evaluation technologies were studied based on the development and characters of food science. The results showed that sensory analysis could not only help in grasping characters of different food products, but also provide physicochemical and practice basis for food production management and process con...

  18. Interplay of multiple synaptic plasticity features in filamentary memristive devices for neuromorphic computing

    Science.gov (United States)

    La Barbera, Selina; Vincent, Adrien F.; Vuillaume, Dominique; Querlioz, Damien; Alibart, Fabien

    2016-12-01

    Bio-inspired computing represents today a major challenge at different levels ranging from material science for the design of innovative devices and circuits to computer science for the understanding of the key features required for processing of natural data. In this paper, we propose a detail analysis of resistive switching dynamics in electrochemical metallization cells for synaptic plasticity implementation. We show how filament stability associated to joule effect during switching can be used to emulate key synaptic features such as short term to long term plasticity transition and spike timing dependent plasticity. Furthermore, an interplay between these different synaptic features is demonstrated for object motion detection in a spike-based neuromorphic circuit. System level simulation presents robust learning and promising synaptic operation paving the way to complex bio-inspired computing systems composed of innovative memory devices.

  19. Coupling an aVLSI neuromorphic vision chip to a neurotrophic model of synaptic plasticity: the development of topography.

    Science.gov (United States)

    Elliott, Terry; Kramer, Jörg

    2002-10-01

    We couple a previously studied, biologically inspired neurotrophic model of activity-dependent competitive synaptic plasticity and neuronal development to a neuromorphic retina chip. Using this system, we examine the development and refinement of a topographic mapping between an array of afferent neurons (the retinal ganglion cells) and an array of target neurons. We find that the plasticity model can indeed drive topographic refinement in the presence of afferent activity patterns generated by a real-world device. We examine the resilience of the developing system to the presence of high levels of noise by adjusting the spontaneous firing rate of the silicon neurons.

  20. Sensory rhodopsins I and II modulate a methylation/demethylation system in Halobacterium halobium phototaxis

    International Nuclear Information System (INIS)

    Spudich, E.N.; Takahashi, T.; Spudich, J.L.

    1989-01-01

    This work demonstrates that phototaxis stimuli in the archaebacterium Halobacterium halobium control a methylation/demethylation system in vivo through photoactivation of sensory rhodopsin I (SR-I) in either its attractant or repellent signaling form as well as through the repellent receptor sensory rhodopsin II (SR-II, also called phoborhodopsin). The effects of positive stimuli that suppress swimming reversals (i.e., an increase in attractant or decrease in repellent light) and negative stimuli that induce swimming reversals (i.e., a decrease in attractant or increase in repellent light) through each photoreceptor were monitored by assaying release of volatile [3H]methyl groups. This assay has been used to measure [3H]methanol produced during the process of adaptation to chemotactic stimuli in eubacteria. In H. halobium positive photostimuli produce a transient increase in the rate of demethylation followed by a decrease below the unstimulated value, whereas negative photostimuli cause an increase followed by a rate similar to that of the unstimulated value. Photoactivation of the SR-I attractant and simultaneous photoactivation of the SR-II repellent receptors cancel in their effects on demethylation, demonstrating the methylation system is regulated by an integrated signal. Analysis of mutants indicates that the source for the volatile methyl groups is intrinsic membrane proteins distinct from the chromoproteins that share the membrane. A methyl-accepting protein (94 kDa) previously correlated in amount with the SR-I chromoprotein (25 kDa) is shown here to be missing in a recently isolated SR-I-SR-II+ mutant (Flx3b), thus confirming the association of this protein with SR-I. Photoactivated SR-II in mutant Flx3b controls demethylation, predicting the existence of a photomodulated methyl-accepting component distinct from the 94-kDa protein of SR-I

  1. Development of postural control and maturation of sensory systems in children of different ages a cross-sectional study.

    Science.gov (United States)

    Sá, Cristina Dos Santos Cardoso de; Boffino, Catarina Costa; Ramos, Renato Teodoro; Tanaka, Clarice

    To evaluate the stability, postural adjustments and contributions of sensory information for postural control in children. 40 boys and 40 girls were equally divided into groups of 5, 7, 9 and 12 years (G5, G7, G9 and G12). All children were submitted to dynamic posturography using a modified sensory organization test, using four sensory conditions: combining stable or sway referencing platform with eyes opened, or closed. The area and displacements of the center of pressure were used to determine stability, while the adjustments were used to measure the speed of the center of pressure displacements. These measurements were compared between groups and test conditions. Stability tends to increase with age and to decrease with sensory manipulation with significant differences between G5 and G7 in different measures. G7 differed from G12 under the conditions of stable and sway platform with eyes open. G9 did not differ from G12. Similar behavior was observed for adjustments, especially in anterior-posterior directions. Postural stability and adjustments were associated with age and were influenced by sensory manipulation. The ability to perform anterior-posterior adjustments was more evident and sensory maturation occurred firstly on the visual system, then proprioceptive system, and finally, the vestibular system, reaching functional maturity at nine years of age. Seven-year-olds seem to go through a period of differentiated singularity in postural control. Copyright © 2017 Associação Brasileira de Pesquisa e Pós-Graduação em Fisioterapia. Publicado por Elsevier Editora Ltda. All rights reserved.

  2. Optical bi-sensorial measurement system for production control of extruded profiles

    Science.gov (United States)

    Weckenmann, A.; Bernstein, J.

    2008-09-01

    Extruded profiles are semi-finished products (made out of steel, brass, aluminum, synthetics...) which are appointed for wide applications in manufacturing of technical products. As yet used optical sensors in process control working to the shading technology detect the object's shadow orthographically to the axis of illumination. As a consequence they record it unattached by the profiles coat in measurement range at any point of the measured profile with high precision. As a matter of fact, concave zones cannot be captured. Alternatively the measurement of concave zones can be arranged by light-section systems. These do not comply with the required accuracy, are comparatively slow and moreover affected by dislocations of the section of the profile. A measurement system including a light-section and a shading system combines the advantages of both optical systems. It is to serve with a reliable conception for the assembly of a bi-sensorial measurement system consisting of both systems as well as suitable methods of analysis for the in-line inspection of concave profiles. As a result it contains conclusions concerning requirements of the light source, the arrangement of this source and the cameras, obtainable precision and sampling rate as well as the essential synchronization of both systems. After designing an appropriate prototype, the selected light-section system and the shading system will be synchronized and aligned. Therefore, the metered geometrical data will be merged for the evaluation of form deviation. So, developed and adapted software supports and contains proposals to the uncertainty after successful tests. The system and a calibration method will be proved in production where robustness will be a most critical despite of heat, dust and vibrations. The target uncertainty of less than 0.1 mm at every section of the profiles coat has to be met.

  3. Neuromorphic Audio-Visual Sensor Fusion on a Sound-Localising Robot

    Directory of Open Access Journals (Sweden)

    Vincent Yue-Sek Chan

    2012-02-01

    Full Text Available This paper presents the first robotic system featuring audio-visual sensor fusion with neuromorphic sensors. We combine a pair of silicon cochleae and a silicon retina on a robotic platform to allow the robot to learn sound localisation through self-motion and visual feedback, using an adaptive ITD-based sound localisation algorithm. After training, the robot can localise sound sources (white or pink noise in a reverberant environment with an RMS error of 4 to 5 degrees in azimuth. In the second part of the paper, we investigate the source binding problem. An experiment is conducted to test the effectiveness of matching an audio event with a corresponding visual event based on their onset time. The results show that this technique can be quite effective, despite its simplicity.

  4. Sensory profiles of breast meat from broilers reared in an organic niche production system and conventional standard broilers

    DEFF Research Database (Denmark)

    Horsted, Klaus; Allesen-Holm, Bodil Helene; Hermansen, John E.

    2012-01-01

    BACKGROUND: Breast meat from broilers produced in very different production systems may vary considerable in sensory profile, which may affect consumer interests. In this study the aim was to evaluate differences in the sensory profiles of breast meat from five broiler products: two conventional...... standard products (A and B) and three organic niche genotypes (I657, L40 and K8) reared in an apple orchard. RESULTS: Thirteen out of 22 sensory attributes differed significantly between the products. The aroma attributes `chicken', `bouillon' and `fat' scored highest and the `iron/liver' aroma lowest...... of `sweet/maize' than the standard products. The `overall liking' score was significantly higher for the `K 8' product than for the `Standard A' and `L 40' products. The `overall liking' score was significantly correlated with the scores for aroma and taste of `chicken', `umami/bouillon', `iron...

  5. Sound stream segregation: a neuromorphic approach to solve the "cocktail party problem" in real-time.

    Science.gov (United States)

    Thakur, Chetan Singh; Wang, Runchun M; Afshar, Saeed; Hamilton, Tara J; Tapson, Jonathan C; Shamma, Shihab A; van Schaik, André

    2015-01-01

    The human auditory system has the ability to segregate complex auditory scenes into a foreground component and a background, allowing us to listen to specific speech sounds from a mixture of sounds. Selective attention plays a crucial role in this process, colloquially known as the "cocktail party effect." It has not been possible to build a machine that can emulate this human ability in real-time. Here, we have developed a framework for the implementation of a neuromorphic sound segregation algorithm in a Field Programmable Gate Array (FPGA). This algorithm is based on the principles of temporal coherence and uses an attention signal to separate a target sound stream from background noise. Temporal coherence implies that auditory features belonging to the same sound source are coherently modulated and evoke highly correlated neural response patterns. The basis for this form of sound segregation is that responses from pairs of channels that are strongly positively correlated belong to the same stream, while channels that are uncorrelated or anti-correlated belong to different streams. In our framework, we have used a neuromorphic cochlea as a frontend sound analyser to extract spatial information of the sound input, which then passes through band pass filters that extract the sound envelope at various modulation rates. Further stages include feature extraction and mask generation, which is finally used to reconstruct the targeted sound. Using sample tonal and speech mixtures, we show that our FPGA architecture is able to segregate sound sources in real-time. The accuracy of segregation is indicated by the high signal-to-noise ratio (SNR) of the segregated stream (90, 77, and 55 dB for simple tone, complex tone, and speech, respectively) as compared to the SNR of the mixture waveform (0 dB). This system may be easily extended for the segregation of complex speech signals, and may thus find various applications in electronic devices such as for sound segregation and

  6. Gamma-band synchronization in the neocortex: novel analysis methods and their application to sensory and motivational systems

    NARCIS (Netherlands)

    Vinck, M.A.

    2013-01-01

    Vinck et al. develop new statistical techniques for the analysis of electrophysiological brain data, and applied these techniques to the study of brainwaves in sensory and motivational systems. Chapter 2 develops a new measure of phase locking between spike trains and Local Field Potentials (LFP)

  7. Sound stream segregation: a neuromorphic approach to solve the “cocktail party problem” in real-time

    OpenAIRE

    Thakur, Chetan Singh; Wang, Runchun M.; Afshar, Saeed; Hamilton, Tara J.; Tapson, Jonathan C.; Shamma, Shihab A.; van Schaik, André

    2015-01-01

    The human auditory system has the ability to segregate complex auditory scenes into a foreground component and a background, allowing us to listen to specific speech sounds from a mixture of sounds. Selective attention plays a crucial role in this process, colloquially known as the “cocktail party effect.” It has not been possible to build a machine that can emulate this human ability in real-time. Here, we have developed a framework for the implementation of a neuromorphic sound segregation ...

  8. Regenerative memory in time-delayed neuromorphic photonic resonators

    Science.gov (United States)

    Romeira, B.; Avó, R.; Figueiredo, José M. L.; Barland, S.; Javaloyes, J.

    2016-01-01

    We investigate a photonic regenerative memory based upon a neuromorphic oscillator with a delayed self-feedback (autaptic) connection. We disclose the existence of a unique temporal response characteristic of localized structures enabling an ideal support for bits in an optical buffer memory for storage and reshaping of data information. We link our experimental implementation, based upon a nanoscale nonlinear resonant tunneling diode driving a laser, to the paradigm of neuronal activity, the FitzHugh-Nagumo model with delayed feedback. This proof-of-concept photonic regenerative memory might constitute a building block for a new class of neuron-inspired photonic memories that can handle high bit-rate optical signals.

  9. A neuromorphic architecture for object recognition and motion anticipation using burst-STDP.

    Directory of Open Access Journals (Sweden)

    Andrew Nere

    Full Text Available In this work we investigate the possibilities offered by a minimal framework of artificial spiking neurons to be deployed in silico. Here we introduce a hierarchical network architecture of spiking neurons which learns to recognize moving objects in a visual environment and determine the correct motor output for each object. These tasks are learned through both supervised and unsupervised spike timing dependent plasticity (STDP. STDP is responsible for the strengthening (or weakening of synapses in relation to pre- and post-synaptic spike times and has been described as a Hebbian paradigm taking place both in vitro and in vivo. We utilize a variation of STDP learning, called burst-STDP, which is based on the notion that, since spikes are expensive in terms of energy consumption, then strong bursting activity carries more information than single (sparse spikes. Furthermore, this learning algorithm takes advantage of homeostatic renormalization, which has been hypothesized to promote memory consolidation during NREM sleep. Using this learning rule, we design a spiking neural network architecture capable of object recognition, motion detection, attention towards important objects, and motor control outputs. We demonstrate the abilities of our design in a simple environment with distractor objects, multiple objects moving concurrently, and in the presence of noise. Most importantly, we show how this neural network is capable of performing these tasks using a simple leaky-integrate-and-fire (LIF neuron model with binary synapses, making it fully compatible with state-of-the-art digital neuromorphic hardware designs. As such, the building blocks and learning rules presented in this paper appear promising for scalable fully neuromorphic systems to be implemented in hardware chips.

  10. An Embedded Sensory System for Worker Safety: Prototype Development and Evaluation.

    Science.gov (United States)

    Cho, Chunhee; Park, JeeWoong

    2018-04-14

    At a construction site, workers mainly rely on two senses, which are sight and sound, in order to perceive their physical surroundings. However, they are often hindered by the nature of most construction sites, which are usually dynamic, loud, and complicated. To overcome these challenges, this research explored a method using an embedded sensory system that might offer construction workers an artificial sensing ability to better perceive their surroundings. This study identified three parameters (i.e., intensity, signal length, and delay between consecutive pulses) needed for tactile-based signals for the construction workers to communicate quickly. We developed a prototype system based on these parameters, conducted experimental studies to quantify and validate the sensitivity of the parameters for quick communication, and analyzed test data to reveal what was added by this method in order to perceive information from the tactile signals. The findings disclosed that the parameters of tactile-based signals and their distinguishable ranges could be perceived in a short amount of time (i.e., a fraction of a second). Further experimentation demonstrated the capability of the identified unit signals combined with a signal mapping technique to effectively deliver simple information to individuals and offer an additional sense of awareness to the surroundings. The findings of this study could serve as a basis for future research in exploring advanced tactile-based messages to overcome challenges in environments for which communication is a struggle.

  11. An Embedded Sensory System for Worker Safety: Prototype Development and Evaluation

    Science.gov (United States)

    Cho, Chunhee; Park, JeeWoong

    2018-01-01

    At a construction site, workers mainly rely on two senses, which are sight and sound, in order to perceive their physical surroundings. However, they are often hindered by the nature of most construction sites, which are usually dynamic, loud, and complicated. To overcome these challenges, this research explored a method using an embedded sensory system that might offer construction workers an artificial sensing ability to better perceive their surroundings. This study identified three parameters (i.e., intensity, signal length, and delay between consecutive pulses) needed for tactile-based signals for the construction workers to communicate quickly. We developed a prototype system based on these parameters, conducted experimental studies to quantify and validate the sensitivity of the parameters for quick communication, and analyzed test data to reveal what was added by this method in order to perceive information from the tactile signals. The findings disclosed that the parameters of tactile-based signals and their distinguishable ranges could be perceived in a short amount of time (i.e., a fraction of a second). Further experimentation demonstrated the capability of the identified unit signals combined with a signal mapping technique to effectively deliver simple information to individuals and offer an additional sense of awareness to the surroundings. The findings of this study could serve as a basis for future research in exploring advanced tactile-based messages to overcome challenges in environments for which communication is a struggle. PMID:29662008

  12. Complementary roles of systems representing sensory evidence and systems detecting task difficulty during perceptual decision making

    Directory of Open Access Journals (Sweden)

    Douglas A Ruff

    2010-11-01

    Full Text Available Perceptual decision making is a multi-stage process where incoming sensory information is used to select one option from several alternatives. Researchers typically have adopted one of two conceptual frameworks to define the criteria for determining whether a brain region is involved in decision computations. One framework, building on single unite recordings in monkeys, posits that activity in a region involved in decision making reflects the accumulation of evidence toward a decision threshold, thus showing the lowest level of BOLD signal during the hardest decisions. The other framework instead posits that activity in a decision-making region reflects the difficulty of a decision, thus showing the highest level of BOLD signal during the hardest decisions. We had subjects perform a face detection task on degraded face images while we simultaneously recorded BOLD activity. We searched for brain regions where changes in BOLD activity during this task supported either of these frameworks by calculating the correlation of BOLD activity with reaction time - a measure of task difficulty. We found that the right supplementary eye field, right frontal eye field and right inferior frontal gyrus had increased activity relative to baseline that positively correlated with reaction time, while the left superior frontal sulcus and left middle temporal gyrus had decreased activity relative to baseline that negatively correlated with reaction time. We propose that a simple mechanism that scales a region’s activity based on task demands can explain our results.

  13. [Neurophysiological investigations of information processing in the somato-sensory system].

    Science.gov (United States)

    Kunesch, E

    2009-08-01

    The ability of the human hand to perform complex sensorimotor tasks such as tactile exploration and grasping is based on 1. exact encoding of somatosensory information by cutaneous mechanoreceptors, 2. elaborated processing of afferent signals in somatosensory relay stations and cortex fields, 3. rapid and effective interaction of sensory feedback with motor programs, and 4. different modes of sensory control, which can be switched over. (c) Georg Thieme Verlag KG Stuttgart-New York.

  14. Probabilistic sensory recoding.

    Science.gov (United States)

    Jazayeri, Mehrdad

    2008-08-01

    A hallmark of higher brain functions is the ability to contemplate the world rather than to respond reflexively to it. To do so, the nervous system makes use of a modular architecture in which sensory representations are dissociated from areas that control actions. This flexibility however necessitates a recoding scheme that would put sensory information to use in the control of behavior. Sensory recoding faces two important challenges. First, recoding must take into account the inherent variability of sensory responses. Second, it must be flexible enough to satisfy the requirements of different perceptual goals. Recent progress in theory, psychophysics, and neurophysiology indicate that cortical circuitry might meet these challenges by evaluating sensory signals probabilistically.

  15. Neuromorphic Implementation of Attractor Dynamics in a Two-Variable Winner-Take-All Circuit with NMDARs: A Simulation Study.

    Science.gov (United States)

    You, Hongzhi; Wang, Da-Hui

    2017-01-01

    Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems.

  16. Spike Neuromorphic VLSI-Based Bat Echolocation for Micro-Aerial Vehicle Guidance

    Science.gov (United States)

    2007-03-31

    IFinal 03/01/04 - 02/28/07 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Neuromorphic VLSI-based Bat Echolocation for Micro-aerial 5b.GRANTNUMBER Vehicle...uncovered interesting new issues in our choice for representing the intensity of signals. We have just finished testing the first chip version of an echo...timing-based algorithm (’openspace’) for sonar-guided navigation amidst multiple obstacles. 15. SUBJECT TERMS Neuromorphic VLSI, bat echolocation

  17. Noise-driven neuromorphic tuned amplifier

    Science.gov (United States)

    Fanelli, Duccio; Ginelli, Francesco; Livi, Roberto; Zagli, Niccoló; Zankoc, Clement

    2017-12-01

    We study a simple stochastic model of neuronal excitatory and inhibitory interactions. The model is defined on a directed lattice and internodes couplings are modulated by a nonlinear function that mimics the process of synaptic activation. We prove that such a system behaves as a fully tunable amplifier: the endogenous component of noise, stemming from finite size effects, seeds a coherent (exponential) amplification across the chain generating giant oscillations with tunable frequencies, a process that the brain could exploit to enhance, and eventually encode, different signals. On a wider perspective, the characterized amplification process could provide a reliable pacemaking mechanism for biological systems. The device extracts energy from the finite size bath and operates as an out of equilibrium thermal machine, under stationary conditions.

  18. Nanotube devices based crossbar architecture: toward neuromorphic computing

    International Nuclear Information System (INIS)

    Zhao, W S; Gamrat, C; Agnus, G; Derycke, V; Filoramo, A; Bourgoin, J-P

    2010-01-01

    Nanoscale devices such as carbon nanotube and nanowires based transistors, memristors and molecular devices are expected to play an important role in the development of new computing architectures. While their size represents a decisive advantage in terms of integration density, it also raises the critical question of how to efficiently address large numbers of densely integrated nanodevices without the need for complex multi-layer interconnection topologies similar to those used in CMOS technology. Two-terminal programmable devices in crossbar geometry seem particularly attractive, but suffer from severe addressing difficulties due to cross-talk, which implies complex programming procedures. Three-terminal devices can be easily addressed individually, but with limited gain in terms of interconnect integration. We show how optically gated carbon nanotube devices enable efficient individual addressing when arranged in a crossbar geometry with shared gate electrodes. This topology is particularly well suited for parallel programming or learning in the context of neuromorphic computing architectures.

  19. Neuromorphic model of magnocellular and parvocellular visual paths: spatial resolution

    International Nuclear Information System (INIS)

    Aguirre, Rolando C; Felice, Carmelo J; Colombo, Elisa M

    2007-01-01

    Physiological studies of the human retina show the existence of at least two visual information processing channels, the magnocellular and the parvocellular ones. Both have different spatial, temporal and chromatic features. This paper focuses on the different spatial resolution of these two channels. We propose a neuromorphic model, so that they match the retina's physiology. Considering the Deutsch and Deutsch model (1992), we propose two configurations (one for each visual channel) of the connection between the retina's different cell layers. The responses of the proposed model have similar behaviour to those of the visual cells: each channel has an optimum response corresponding to a given stimulus size which decreases for larger or smaller stimuli. This size is bigger for the magno path than for the parvo path and, in the end, both channels produce a magnifying of the borders of a stimulus

  20. Neuromorphic function learning with carbon nanotube based synapses

    International Nuclear Information System (INIS)

    Gacem, Karim; Filoramo, Arianna; Derycke, Vincent; Retrouvey, Jean-Marie; Chabi, Djaafar; Zhao, Weisheng; Klein, Jacques-Olivier

    2013-01-01

    The principle of using nanoscale memory devices as artificial synapses in neuromorphic circuits is recognized as a promising way to build ground-breaking circuit architectures tolerant to defects and variability. Yet, actual experimental demonstrations of the neural network type of circuits based on non-conventional/non-CMOS memory devices and displaying function learning capabilities remain very scarce. We show here that carbon-nanotube-based memory elements can be used as artificial synapses, combined with conventional neurons and trained to perform functions through the application of a supervised learning algorithm. The same ensemble of eight devices can notably be trained multiple times to code successively any three-input linearly separable Boolean logic function despite device-to-device variability. This work thus represents one of the very few demonstrations of actual function learning with synapses based on nanoscale building blocks. The potential of such an approach for the parallel learning of multiple and more complex functions is also evaluated. (paper)

  1. Reduced connectivity and inter-hemispheric symmetry of the sensory system in a rat model of vulnerability to developing depression.

    Science.gov (United States)

    Ben-Shimol, E; Gass, N; Vollmayr, B; Sartorius, A; Goelman, G

    2015-12-03

    Defining the markers corresponding to a high risk of developing depression in humans would have major clinical significance; however, few studies have been conducted since they are not only complex but also require homogeneous groups. This study compared congenital learned helpless (cLH) rats, selectively bred for high stress sensitivity and learned helplessness (LH) behavior, to congenital non-learned helpless (cNLH) rats that were bred for resistance to uncontrollable stress. Naïve cLH rats show some depression-like behavior but full LH behavior need additional stress, making this model ideal for studying vulnerability to depression. Resting-state functional connectivity obtained from seed correlation analysis was calculated for multiple regions that were selected by anatomy AND by a data-driven approach, independently. Significance was determined by t-statistic AND by permutation analysis, independently. A significant reduction in functional connectivity was observed by both analyses in the cLH rats in the sensory, motor, cingulate, infralimbic, accumbens and the raphe nucleus. These reductions corresponded primarily to reduced inter-hemispheric connectivity. The main reduction however was in the sensory system. It is argued that reduced connectivity and inter-hemispheric connectivity of the sensory system reflects an internal convergence state which may precede other depressive symptomatology and therefore could be used as markers for vulnerability to the development of depression. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

  2. Sensory systems for a control rod position using reed switches for the integral reactor

    International Nuclear Information System (INIS)

    Yu, J. Y.; Choi, S.; Kim, J. H.; Lee, D. J.

    2007-01-01

    shaft of the rotary step motor. The permanent magnet positioned in the planetary gear holder which is designed to rotate of 60 degree in corresponding to each step of the rotary step motor. Therefore the angular position detector can measure one step angular increase of the rotary step motor by means of detecting the angular position of the permanent magnet using the reed switch assembly outside the pressure housing of the angular position detector. The angular position detector with planetary gear can measure precisely the control rod position by considering the gear ratio and the ball screw lead as well as can check the operating condition of the rotary step motor of CEDM at real time. The two sensory systems of the position indicator and the angular position detector will cooperate to measure the position of the control rod more reliably

  3. Documentation of Sensory Information in the Operation of Unmanned Aircraft Systems

    Science.gov (United States)

    2008-10-01

    spercepton.s.a. msmatch.between.vsual.and.vestbular.or.proproceptve. stmul.(Reed,.1977) . Advantages and disadvantages of sensory Modes G...and that are approved for IFR operations, a third attitude instrument must be provided that: (i) Is powered from a source independent of the...indicator, if the aircraft has a retractable landing gear. … B-17 (d) Instrument flight rules. For IFR flight, the following instruments and equipment

  4. Central representation of sensory inputs from the cardio-renal system in Aplysia depilans.

    Science.gov (United States)

    Rózsa, K S; Salánki, J; Véró, M; Kovacević, N; Konjevic, D

    1980-01-01

    Studying the central representation of sensory inputs originating from the heart in Aplysia depilans, it was found that: 1. Neurons responding to heart stimulation can be found in the abdominal, pedal and pleural ganglia alike. 2. The representation of heart input signals was more abundant in the left hemisphere of the abdominal ganglion and in the left pedal and pleural ganglia. 3. The giant neurons of Aplysia depilans can be compared to the homologous cells of Aplysia californica. Two motoneurons (RBHE, LDHI) and one interneuron (L10) proved to be identical in the two subspecies. 4. Sensory inputs originating from the heart may modify the pattern of both heart regulatory motoneurons and interneurons. 5. Nine giant and 19 small neurons of the abdominal ganglion, 3--3 neurons of the right and left pleural ganglion, 6 neurons of the left pedal ganglion responded to heart stimulation. 6. The bursting patterns of cells R15 and L4 were modified to tonic discharge in response to heart stimulation. 7. The representation of sensory inputs originating from the heart is scattered throughout the CNS of Aplysia depilans and heart regulation is based on a feedback mechanism similar to that found in other gastropod species.

  5. A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses.

    Science.gov (United States)

    Qiao, Ning; Mostafa, Hesham; Corradi, Federico; Osswald, Marc; Stefanini, Fabio; Sumislawska, Dora; Indiveri, Giacomo

    2015-01-01

    Implementing compact, low-power artificial neural processing systems with real-time on-line learning abilities is still an open challenge. In this paper we present a full-custom mixed-signal VLSI device with neuromorphic learning circuits that emulate the biophysics of real spiking neurons and dynamic synapses for exploring the properties of computational neuroscience models and for building brain-inspired computing systems. The proposed architecture allows the on-chip configuration of a wide range of network connectivities, including recurrent and deep networks, with short-term and long-term plasticity. The device comprises 128 K analog synapse and 256 neuron circuits with biologically plausible dynamics and bi-stable spike-based plasticity mechanisms that endow it with on-line learning abilities. In addition to the analog circuits, the device comprises also asynchronous digital logic circuits for setting different synapse and neuron properties as well as different network configurations. This prototype device, fabricated using a 180 nm 1P6M CMOS process, occupies an area of 51.4 mm(2), and consumes approximately 4 mW for typical experiments, for example involving attractor networks. Here we describe the details of the overall architecture and of the individual circuits and present experimental results that showcase its potential. By supporting a wide range of cortical-like computational modules comprising plasticity mechanisms, this device will enable the realization of intelligent autonomous systems with on-line learning capabilities.

  6. Metabolomic profiling and sensorial quality of 'Golden Delicious', 'Liberty', 'Santana', and 'Topaz' apples grown using organic and integrated production systems.

    Science.gov (United States)

    Vanzo, Andreja; Jenko, Mojca; Vrhovsek, Urska; Stopar, Matej

    2013-07-03

    Apple quality was investigated in the scab-resistant 'Liberty', 'Santana', and 'Topaz' cultivars and the scab-susceptible 'Golden Delicious' cultivar. Trees subjected to the same crop load were cultivated using either an organic (ORG) or an integrated production (IP) system. Physicochemical properties, phenolic content, and sensorial quality of fruit from both systems were compared. There were no significant differences in fruit mass, starch, and total soluble solid content (the latter was higher in ORG 'Liberty') between ORG and IP fruit, whereas significantly higher flesh firmness was found in ORG fruit (except no difference in 'Golden Delicious'). Significantly higher total phenolic content in ORG fruit was found in 'Golden Delicious', whereas differences in other cultivars were not significant. Targeted metabolomic profiling of multiple classes of phenolics confirmed the impact of the production system on the 'Golden Delicious' phenolic profile as higher levels of 4-hydroxybenzoic acid, neo- and chlorogenic acids, phloridzin, procyanidin B2+B4, -3-O-glucoside and -3-O-galactoside of quercetin, kaempferol-3-O-rutinoside, and rutin being found in ORG fruit. The results obtained suggested that scab resistance influenced the phenolic biosynthesis in relation to the agricultural system. Sensorial evaluation indicated significantly better flavor (except for 'Topaz') and better appearance of IP fruit.

  7. Bacillus subtilis Two-Component System Sensory Kinase DegS Is Regulated by Serine Phosphorylation in Its Input Domain

    DEFF Research Database (Denmark)

    Jers, Carsten; Kobir, Ahasanul; Søndergaard, Elsebeth Oline

    2011-01-01

    Bacillus subtilis two-component system DegS/U is well known for the complexity of its regulation. The cytosolic sensory kinase DegS does not receive a single predominant input signal like most two-component kinases, instead it integrates a wide array of metabolic inputs that modulate its activity......S phosphorylation can be carried out by at least two B. subtilis Hanks-type kinases in vitro, and this stimulates the phosphate transfer towards DegU. The consequences of this process were studied in vivo, using phosphomimetic (Ser76Asp) and non-phosphorylatable (Ser76Ala) mutants of DegS. In a number...

  8. Modularity in Sensory Auditory Memory

    OpenAIRE

    Clement, Sylvain; Moroni, Christine; Samson, Séverine

    2004-01-01

    The goal of this paper was to review various experimental and neuropsychological studies that support the modular conception of auditory sensory memory or auditory short-term memory. Based on initial findings demonstrating that verbal sensory memory system can be dissociated from a general auditory memory store at the functional and anatomical levels. we reported a series of studies that provided evidence in favor of multiple auditory sensory stores specialized in retaining eit...

  9. Neural system for updating object working memory from different sources: sensory stimuli or long-term memory.

    Science.gov (United States)

    Roth, Jennifer K; Courtney, Susan M

    2007-11-15

    Working memory (WM) is the active maintenance of currently relevant information so that it is available for use. A crucial component of WM is the ability to update the contents when new information becomes more relevant than previously maintained information. New information can come from different sources, including from sensory stimuli (SS) or from long-term memory (LTM). Updating WM may involve a single neural system regardless of source, distinct systems for each source, or a common network with additional regions involved specifically in sensory or LTM processes. The current series of experiments indicates that a single fronto-parietal network (including supplementary motor area, parietal, left inferior frontal junction, middle frontal gyrus) is active in updating WM regardless of the source of information. Bilateral cuneus was more active during updating WM from LTM than updating from SS, but the activity in this region was attributable to recalling information from LTM regardless of whether that information was to be entered into WM for future use or not. No regions were found to be more active during updating from SS than updating from LTM. Functional connectivity analysis revealed that different regions within this common update network were differentially more correlated with visual processing regions when participants updated from SS, and more correlated with LTM processing regions when participants updated from the contents of LTM. These results suggest that a single neural mechanism is responsible for controlling the contents of WM regardless of whether that information originates from a sensory stimulus or from LTM. This network of regions involved in updating WM interacts with the rest of the brain differently depending on the source of newly relevant information.

  10. Towards an Analogue Neuromorphic VLSI Instrument for the Sensing of Complex Odours

    Science.gov (United States)

    Ab Aziz, Muhammad Fazli; Harun, Fauzan Khairi Che; Covington, James A.; Gardner, Julian W.

    2011-09-01

    Almost all electronic nose instruments reported today employ pattern recognition algorithms written in software and run on digital processors, e.g. micro-processors, microcontrollers or FPGAs. Conversely, in this paper we describe the analogue VLSI implementation of an electronic nose through the design of a neuromorphic olfactory chip. The modelling, design and fabrication of the chip have already been reported. Here a smart interface has been designed and characterised for thisneuromorphic chip. Thus we can demonstrate the functionality of the a VLSI neuromorphic chip, producing differing principal neuron firing patterns to real sensor response data. Further work is directed towards integrating 9 separate neuromorphic chips to create a large neuronal network to solve more complex olfactory problems.

  11. A theoretical and experimental study of neuromorphic atomic switch networks for reservoir computing.

    Science.gov (United States)

    Sillin, Henry O; Aguilera, Renato; Shieh, Hsien-Hang; Avizienis, Audrius V; Aono, Masakazu; Stieg, Adam Z; Gimzewski, James K

    2013-09-27

    Atomic switch networks (ASNs) have been shown to generate network level dynamics that resemble those observed in biological neural networks. To facilitate understanding and control of these behaviors, we developed a numerical model based on the synapse-like properties of individual atomic switches and the random nature of the network wiring. We validated the model against various experimental results highlighting the possibility to functionalize the network plasticity and the differences between an atomic switch in isolation and its behaviors in a network. The effects of changing connectivity density on the nonlinear dynamics were examined as characterized by higher harmonic generation in response to AC inputs. To demonstrate their utility for computation, we subjected the simulated network to training within the framework of reservoir computing and showed initial evidence of the ASN acting as a reservoir which may be optimized for specific tasks by adjusting the input gain. The work presented represents steps in a unified approach to experimentation and theory of complex systems to make ASNs a uniquely scalable platform for neuromorphic computing.

  12. Polymer-electrolyte-gated nanowire synaptic transistors for neuromorphic applications

    Science.gov (United States)

    Zou, Can; Sun, Jia; Gou, Guangyang; Kong, Ling-An; Qian, Chuan; Dai, Guozhang; Yang, Junliang; Guo, Guang-hua

    2017-09-01

    Polymer-electrolytes are formed by dissolving a salt in polymer instead of water, the conducting mechanism involves the segmental motion-assisted diffusion of ion in the polymer matrix. Here, we report on the fabrication of tin oxide (SnO2) nanowire synaptic transistors using polymer-electrolyte gating. A thin layer of poly(ethylene oxide) and lithium perchlorate (PEO/LiClO4) was deposited on top of the devices, which was used to boost device performances. A voltage spike applied on the in-plane gate attracts ions toward the polymer-electrolyte/SnO2 nanowire interface and the ions are gradually returned after the pulse is removed, which can induce a dynamic excitatory postsynaptic current in the nanowire channel. The SnO2 synaptic transistors exhibit the behavior of short-term plasticity like the paired-pulse facilitation and self-adaptation, which is related to the electric double-effect regulation. In addition, the synaptic logic functions and the logical function transformation are also discussed. Such single SnO2 nanowire-based synaptic transistors are of great importance for future neuromorphic devices.

  13. A Dataset for Visual Navigation with Neuromorphic Methods

    Directory of Open Access Journals (Sweden)

    Francisco eBarranco

    2016-02-01

    Full Text Available Standardized benchmarks in Computer Vision have greatly contributed to the advance of approaches to many problems in the field. If we want to enhance the visibility of event-driven vision and increase its impact, we will need benchmarks that allow comparison among different neuromorphic methods as well as comparison to Computer Vision conventional approaches. We present datasets to evaluate the accuracy of frame-free and frame-based approaches for tasks of visual navigation. Similar to conventional Computer Vision datasets, we provide synthetic and real scenes, with the synthetic data created with graphics packages, and the real data recorded using a mobile robotic platform carrying a dynamic and active pixel vision sensor (DAVIS and an RGB+Depth sensor. For both datasets the cameras move with a rigid motion in a static scene, and the data includes the images, events, optic flow, 3D camera motion, and the depth of the scene, along with calibration procedures. Finally, we also provide simulated event data generated synthetically from well-known frame-based optical flow datasets.

  14. Neuromorphic transistor achieved by redox reaction of WO3 thin film

    Science.gov (United States)

    Tsuchiya, Takashi; Jayabalan, Manikandan; Kawamura, Kinya; Takayanagi, Makoto; Higuchi, Tohru; Jayavel, Ramasamy; Terabe, Kazuya

    2018-04-01

    An all-solid-state neuromorphic transistor composed of a WO3 thin film and a proton-conducting electrolyte was fabricated for application to next-generation information and communication technology including artificial neural networks. The drain current exhibited a 4-order-of-magnitude increment by redox reaction of the WO3 thin film owing to proton migration. Learning and forgetting characteristics were well tuned by the gate control of WO3 redox reactions owing to the separation of the current reading path and pulse application path in the transistor structure. This technique should lead to the development of versatile and low-power-consumption neuromorphic devices.

  15. Design of a Nanoscale, CMOS-Integrable, Thermal-Guiding Structure for Boolean-Logic and Neuromorphic Computation.

    Science.gov (United States)

    Loke, Desmond; Skelton, Jonathan M; Chong, Tow-Chong; Elliott, Stephen R

    2016-12-21

    One of the requirements for achieving faster CMOS electronics is to mitigate the unacceptably large chip areas required to steer heat away from or, more recently, toward the critical nodes of state-of-the-art devices. Thermal-guiding (TG) structures can efficiently direct heat by "meta-materials" engineering; however, some key aspects of the behavior of these systems are not fully understood. Here, we demonstrate control of the thermal-diffusion properties of TG structures by using nanometer-scale, CMOS-integrable, graphene-on-silica stacked materials through finite-element-methods simulations. It has been shown that it is possible to implement novel, controllable, thermally based Boolean-logic and spike-timing-dependent plasticity operations for advanced (neuromorphic) computing applications using such thermal-guide architectures.

  16. Neuromorphic meets neuromechanics, part II: the role of fusimotor drive

    Science.gov (United States)

    Jalaleddini, Kian; Minos Niu, Chuanxin; Chakravarthi Raja, Suraj; Sohn, Won Joon; Loeb, Gerald E.; Sanger, Terence D.; Valero-Cuevas, Francisco J.

    2017-04-01

    Objective. We studied the fundamentals of muscle afferentation by building a Neuro-mechano-morphic system actuating a cadaveric finger. This system is a faithful implementation of the stretch reflex circuitry. It allowed the systematic exploration of the effects of different fusimotor drives to the muscle spindle on the closed-loop stretch reflex response. Approach. As in Part I of this work, sensory neurons conveyed proprioceptive information from muscle spindles (with static and dynamic fusimotor drive) to populations of α-motor neurons (with recruitment and rate coding properties). The motor commands were transformed into tendon forces by a Hill-type muscle model (with activation-contraction dynamics) via brushless DC motors. Two independent afferented muscles emulated the forces of flexor digitorum profundus and the extensor indicis proprius muscles, forming an antagonist pair at the metacarpophalangeal joint of a cadaveric index finger. We measured the physical response to repetitions of bi-directional ramp-and-hold rotational perturbations for 81 combinations of static and dynamic fusimotor drives, across four ramp velocities, and three levels of constant cortical drive to the α-motor neuron pool. Main results. We found that this system produced responses compatible with the physiological literature. Fusimotor and cortical drives had nonlinear effects on the reflex forces. In particular, only cortical drive affected the sensitivity of reflex forces to static fusimotor drive. In contrast, both static fusimotor and cortical drives reduced the sensitivity to dynamic fusimotor drive. Interestingly, realistic signal-dependent motor noise emerged naturally in our system without having been explicitly modeled. Significance. We demonstrate that these fundamental features of spinal afferentation sufficed to produce muscle function. As such, our Neuro-mechano-morphic system is a viable platform to study the spinal mechanisms for healthy muscle function—and its

  17. [Age-related changes of sensory peripheral nerve system in healthy subjects.

    Science.gov (United States)

    Voitenkov, V B; Ekusheva, E V; Komancev, V N; Skripchenko, N V; Grigoryev, S G; Klimkin, A V; Aksenova, A I

    2017-01-01

    Our aim was to present and evaluate age-related changes of peripheral nerves of limbs on a huge population of healthy subjects of different ages. In 2009-2016 subjects aged from 1months to 90 years were studied by nerve conduction velocity studies (NCV). Data of those confirmed healthy was included in our study. In total there were 372 healthy subjects. NCV for nn. Medianus et Ulnaris was registered, with NCV and amplitude of compound sensory action potential (CSAP) being analyzed. There were significant differences on both these parameters between different age groups. Since the childhood the improvement of conduction (which was reflected in rising of CSAP amplitudes and NCV quickening) was registered; from 40-50 years steady decline of both these parameters were observed in both nerves. Conduction studies of peripheral nerves may be implemented in gerontology for early detection of neurophysiology patterns reflecting physiological aging. Also our results may be implemented for accelerated aging detection.

  18. Sound stream segregation: a neuromorphic approach to solve the “cocktail party problem” in real-time

    Science.gov (United States)

    Thakur, Chetan Singh; Wang, Runchun M.; Afshar, Saeed; Hamilton, Tara J.; Tapson, Jonathan C.; Shamma, Shihab A.; van Schaik, André

    2015-01-01

    The human auditory system has the ability to segregate complex auditory scenes into a foreground component and a background, allowing us to listen to specific speech sounds from a mixture of sounds. Selective attention plays a crucial role in this process, colloquially known as the “cocktail party effect.” It has not been possible to build a machine that can emulate this human ability in real-time. Here, we have developed a framework for the implementation of a neuromorphic sound segregation algorithm in a Field Programmable Gate Array (FPGA). This algorithm is based on the principles of temporal coherence and uses an attention signal to separate a target sound stream from background noise. Temporal coherence implies that auditory features belonging to the same sound source are coherently modulated and evoke highly correlated neural response patterns. The basis for this form of sound segregation is that responses from pairs of channels that are strongly positively correlated belong to the same stream, while channels that are uncorrelated or anti-correlated belong to different streams. In our framework, we have used a neuromorphic cochlea as a frontend sound analyser to extract spatial information of the sound input, which then passes through band pass filters that extract the sound envelope at various modulation rates. Further stages include feature extraction and mask generation, which is finally used to reconstruct the targeted sound. Using sample tonal and speech mixtures, we show that our FPGA architecture is able to segregate sound sources in real-time. The accuracy of segregation is indicated by the high signal-to-noise ratio (SNR) of the segregated stream (90, 77, and 55 dB for simple tone, complex tone, and speech, respectively) as compared to the SNR of the mixture waveform (0 dB). This system may be easily extended for the segregation of complex speech signals, and may thus find various applications in electronic devices such as for sound segregation

  19. Sound stream segregation: a neuromorphic approach to solve the ‘cocktail party problem’ in real-time

    Directory of Open Access Journals (Sweden)

    Chetan Singh Thakur

    2015-09-01

    Full Text Available The human auditory system has the ability to segregate complex auditory scenes into a foreground component and a background, allowing us to listen to specific speech sounds from a mixture of sounds. Selective attention plays a crucial role in this process, colloquially known as the ‘cocktail party effect’. It has not been possible to build a machine that can emulate this human ability in real-time. Here, we have developed a framework for the implementation of a neuromorphic sound segregation algorithm in a Field Programmable Gate Array (FPGA. This algorithm is based on the principles of temporal coherence and uses an attention signal to separate a target sound stream from background noise. Temporal coherence implies that auditory features belonging to the same sound source are coherently modulated and evoke highly correlated neural response patterns. The basis for this form of sound segregation is that responses from pairs of channels that are strongly positively correlated belong to the same stream, while channels that are uncorrelated or anti-correlated belong to different streams. In our framework, we have used a neuromorphic cochlea as a frontend sound analyser to extract spatial information of the sound input, which then passes through band pass filters that extract the sound envelope at various modulation rates. Further stages include feature extraction and mask generation, which is finally used to reconstruct the targeted sound. Using sample tonal and speech mixtures, we show that our FPGA architecture is able to segregate sound sources in real-time. The accuracy of segregation is indicated by the high signal-to-noise ratio (SNR of the segregated stream (90, 77 and 55 dB for simple tone, complex tone and speech, respectively as compared to the SNR of the mixture waveform (0 dB. This system may be easily extended for the segregation of complex speech signals, and may thus find various applications in electronic devices such as for

  20. The Botulinum Toxin as a Therapeutic Agent: Molecular Structure and Mechanism of Action in Motor and Sensory Systems.

    Science.gov (United States)

    Kumar, Raj; Dhaliwal, Harkiran Preet; Kukreja, Roshan Vijay; Singh, Bal Ram

    2016-02-01

    Botulinum neurotoxin (BoNT) produced by Clostridium botulinum is the most potent molecule known to mankind. Higher potency of BoNT is attributed to several factors, including structural and functional uniqueness, target specificity, and longevity. Although BoNT is an extremely toxic molecule, it is now increasingly used for the treatment of disorders related to muscle hyperactivity and glandular hyperactivity. Weakening of muscles due to peripheral action of BoNT produces a therapeutic effect. Depending on the target tissue, BoNT can block the cholinergic neuromuscular or cholinergic autonomic innervation of exocrine glands and smooth muscles. In recent observations of the analgesic properties of BoNT, the toxin modifies the sensory feedback loop to the central nervous system. Differential effects of BoNT in excitatory and inhibitory neurons provide a unique therapeutic tool. In this review the authors briefly summarize the structure and mechanism of actions of BoNT on motor and sensory neurons to explain its therapeutic effects and future potential. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

  1. I Feel, Therefore, I am: The Insula and Its Role in Human Emotion, Cognition and the Sensory-Motor System

    Directory of Open Access Journals (Sweden)

    Mani Pavuluri

    2015-02-01

    Full Text Available Background: The insula is instrumental in integrating the emotional, cognitive, and sensory-motor systems. This manuscript lays a foundational framework for understanding the insula’s mechanistic role in moderating brain networks in illness and wellness. Methods: Reviewed here is the select literature on the brain anatomy and function relevant to the insula’s role in psychiatrically ill and normative populations. Results: The insula is a hub for moderating social cognition, empathy, reward-driven decision-making, arousal, reactivity to emotional stimuli, and somatic pain processing. Findings indicate a spectrum of increasing complexity in insular function – from receiving and interpreting sensorimotor sensations in the posterior insula to subjective perception of emotions in the anterior insula. The insula plays a key role at the interface of cognitive and emotional domains, functioning in concert with other brain regions that share common cytoarchitecture, such as the ventrolateral prefrontal cortex and the anterior cingulate cortex. Pharmacotherapy and mindfulness-based interventions can alter insular activation. Conclusion: The insula serves as a receiver and interpreter of emotions in the context of cognitive and sensory-motor information. Therefore, insular function and connectivity may potentially be utilized as a biomarker for treatment selection and outcome.

  2. Antioxidant activity and sensory analysis of murtilla (Ugni molinae Turcz.) fruit extracts in an oil model system

    International Nuclear Information System (INIS)

    Augusto-Obara, T.R.; Pirce, F.; Scheuermann, E.; Spoto, M.H.F.; Vieira, T.M.F.S.

    2017-01-01

    An oil model system was used to analyze the antioxidant activity of Chilean fruit extracts and to determine their odor sensory effect. Hydroalcoholic extracts from wild and 14-4 genotype murtilla (Ugni molinae Turcz.) fruit were assessed by the Response Surface Methodology. The optimal conditions for producing high total phenolic-content extracts were 49.5% (v/v) ethanol at 30 ºC, which yielded 18.39 and 26.14 mg GAE·g−1 dry matter, respectively. The optimized extracts were added to a lipid model system and evaluated via the Schaal Oven Test. After 96 hours, 150 and 200 mg·kg−1 oil of the wild and 14-4 genotype extracts, respectively, showed an antioxidant capacity similar to TBHQ (200 mg·kg−1 oil) in terms of peroxide values and odor. Thus, murtilla fruit extracts are a natural source of antioxidants for protecting lipidic foods, such as soybean oil. [es

  3. Reward-based learning under hardware constraints - Using a RISC processor embedded in a neuromorphic substrate

    Directory of Open Access Journals (Sweden)

    Simon eFriedmann

    2013-09-01

    Full Text Available In this study, we propose and analyze in simulations a new, highly flexible method of imple-menting synaptic plasticity in a wafer-scale, accelerated neuromorphic hardware system. Thestudy focuses on globally modulated STDP, as a special use-case of this method. Flexibility isachieved by embedding a general-purpose processor dedicated to plasticity into the wafer. Toevaluate the suitability of the proposed system, we use a reward modulated STDP rule in a spiketrain learning task. A single layer of neurons is trained to fire at specific points in time withonly the reward as feedback. This model is simulated to measure its performance, i.e. the in-crease in received reward after learning. Using this performance as baseline, we then simulatethe model with various constraints imposed by the proposed implementation and compare theperformance. The simulated constraints include discretized synaptic weights, a restricted inter-face between analog synapses and embedded processor, and mismatch of analog circuits. Wefind that probabilistic updates can increase the performance of low-resolution weights, a simpleinterface between analog synapses and processor is sufficient for learning, and performance isinsensitive to mismatch. Further, we consider communication latency between wafer and theconventional control computer system that is simulating the environment. This latency increasesthe delay, with which the reward is sent to the embedded processor. Because of the time continu-ous operation of the analog synapses, delay can cause a deviation of the updates as compared tothe not delayed situation. We find that for highly accelerated systems latency has to be kept to aminimum. This study demonstrates the suitability of the proposed implementation to emulatethe selected reward modulated STDP learning rule. It is therefore an ideal candidate for imple-mentation in an upgraded version of the wafer-scale system developed within the BrainScaleSproject.

  4. Brain-Based Devices for Neuromorphic Computer Systems

    Science.gov (United States)

    2013-07-01

    Science. 233(4771):1416-9. Goldman-Rakic, P.S. (1995). Cellular basis of working memory. Neuron. 14(3):477-85. Haider, B., Krause, M.R., Duque , A., Yu...Haider, B., Krause, M. R., Duque , A., Yu, Y., Touryan, J., Mazer, J. A., and McCormick, D. A. (2010). Synaptic and network mechanisms of sparse and

  5. An Address Event Representation-Based Processing System for a Biped Robot

    Directory of Open Access Journals (Sweden)

    Uziel Jaramillo-Avila

    2016-02-01

    Full Text Available In recent years, several important advances have been made in the fields of both biologically inspired sensorial processing and locomotion systems, such as Address Event Representation-based cameras (or Dynamic Vision Sensors and in human-like robot locomotion, e.g., the walking of a biped robot. However, making these fields merge properly is not an easy task. In this regard, Neuromorphic Engineering is a fast-growing research field, the main goal of which is the biologically inspired design of hybrid hardware systems in order to mimic neural architectures and to process information in the manner of the brain. However, few robotic applications exist to illustrate them. The main goal of this work is to demonstrate, by creating a closed-loop system using only bio-inspired techniques, how such applications can work properly. We present an algorithm using Spiking Neural Networks (SNN for a biped robot equipped with a Dynamic Vision Sensor, which is designed to follow a line drawn on the floor. This is a commonly used method for demonstrating control techniques. Most of them are fairly simple to implement without very sophisticated components; however, it can still serve as a good test in more elaborate circumstances. In addition, the locomotion system proposed is able to coordinately control the six DOFs of a biped robot in switching between basic forms of movement. The latter has been implemented as a FPGA-based neuromorphic system. Numerical tests and hardware validation are presented.

  6. Validation of a paper-disk approach to facilitate the sensory evaluation of bitterness in dairy protein hydrolysates from a newly developed food-grade fractionation system.

    Science.gov (United States)

    Murray, Niamh M; O'Riordan, Dolores; Jacquier, Jean-Christophe; O'Sullivan, Michael; Cohen, Joshua L; Heymann, Hildegarde; Barile, Daniela; Dallas, David C

    2017-06-01

    Casein-hydrolysates (NaCaH) are desirable functional ingredients, but their bitterness impedes usage in foods. This study sought to validate a paper-disk approach to help evaluate bitterness in NaCaHs and to develop a food-grade approach to separate a NaCaH into distinct fractions, which could be evaluated by a sensory panel. Membrane filtration generated sensory evaluation. Bitterness differences observed in the membrane fractions using this sensory evaluation approach reflected those observed for the same fractions presented as a liquid. The flash-chromatography fractions increased in bitterness with an increase in hydrophobicity, except for the 50% EtOH fraction which had little bitterness. Amino acid analysis of the fractions showed enrichment of different essential amino acids in both the bitter and less bitter fractions. The developed food-grade fractionation system, allowed for a simple and reasonably scaled approach to separating a NaCaH, into physicochemically different fractions that could be evaluated by a sensory panel. The method of sensory evaluation used in this study, in which NaCaH samples are impregnated into paper-disks, provided potential solutions for issues such as sample insolubility and limited quantities of sample. As the impregnated paper-disk samples were dehydrated, their long storage life could also be suitable for sensory evaluations distributed by mail for large consumer studies. The research, in this study, allowed for a greater understanding of the physicochemical basis for bitterness in this NaCaH. As some essential amino acids were enriched in the less bitter fractions, selective removal of bitter fractions could allow for the incorporation of the less bitter NaCaH fractions into food products for added nutritional value, without negatively impacting sensory properties. There is potential for this approach to be applied to other food ingredients with undesirable tastes, such as polyphenols.

  7. Antioxidant activity and sensory analysis of murtilla (Ugni molinae Turcz. fruit extracts in an oil model system

    Directory of Open Access Journals (Sweden)

    T. R. Augusto-Obara

    2017-03-01

    Full Text Available An oil model system was used to analyze the antioxidant activity of Chilean fruit extracts and to determine their odor sensory effect. Hydroalcoholic extracts from wild and 14-4 genotype murtilla (Ugni molinae Turcz. fruit were assessed by the Response Surface Methodology. The optimal conditions for producing high total phenolic-content extracts were 49.5% (v/v ethanol at 30 ºC, which yielded 18.39 and 26.14 mg GAE·g-1 dry matter, respectively. The optimized extracts were added to a lipid model system and evaluated via the Schaal Oven Test. After 96 hours, 150 and 200 mg·kg-1 oil of the wild and 14-4 genotype extracts, respectively, showed an antioxidant capacity similar to TBHQ (200 mg·kg-1 oil in terms of peroxide values and odor. Thus, murtilla fruit extracts are a natural source of antioxidants for protecting lipidic foods, such as soybean oil.

  8. Psycho-physiological assessment of a prosthetic hand sensory feedback system based on an auditory display: a preliminary study.

    Science.gov (United States)

    Gonzalez, Jose; Soma, Hirokazu; Sekine, Masashi; Yu, Wenwei

    2012-06-09

    Prosthetic hand users have to rely extensively on visual feedback, which seems to lead to a high conscious burden for the users, in order to manipulate their prosthetic devices. Indirect methods (electro-cutaneous, vibrotactile, auditory cues) have been used to convey information from the artificial limb to the amputee, but the usability and advantages of these feedback methods were explored mainly by looking at the performance results, not taking into account measurements of the user's mental effort, attention, and emotions. The main objective of this study was to explore the feasibility of using psycho-physiological measurements to assess cognitive effort when manipulating a robot hand with and without the usage of a sensory substitution system based on auditory feedback, and how these psycho-physiological recordings relate to temporal and grasping performance in a static setting. 10 male subjects (26+/-years old), participated in this study and were asked to come for 2 consecutive days. On the first day the experiment objective, tasks, and experiment setting was explained. Then, they completed a 30 minutes guided training. On the second day each subject was tested in 3 different modalities: Auditory Feedback only control (AF), Visual Feedback only control (VF), and Audiovisual Feedback control (AVF). For each modality they were asked to perform 10 trials. At the end of each test, the subject had to answer the NASA TLX questionnaire. Also, during the test the subject's EEG, ECG, electro-dermal activity (EDA), and respiration rate were measured. The results show that a higher mental effort is needed when the subjects rely only on their vision, and that this effort seems to be reduced when auditory feedback is added to the human-machine interaction (multimodal feedback). Furthermore, better temporal performance and better grasping performance was obtained in the audiovisual modality. The performance improvements when using auditory cues, along with vision

  9. Psycho-physiological assessment of a prosthetic hand sensory feedback system based on an auditory display: a preliminary study

    Directory of Open Access Journals (Sweden)

    Gonzalez Jose

    2012-06-01

    Full Text Available Abstract Background Prosthetic hand users have to rely extensively on visual feedback, which seems to lead to a high conscious burden for the users, in order to manipulate their prosthetic devices. Indirect methods (electro-cutaneous, vibrotactile, auditory cues have been used to convey information from the artificial limb to the amputee, but the usability and advantages of these feedback methods were explored mainly by looking at the performance results, not taking into account measurements of the user’s mental effort, attention, and emotions. The main objective of this study was to explore the feasibility of using psycho-physiological measurements to assess cognitive effort when manipulating a robot hand with and without the usage of a sensory substitution system based on auditory feedback, and how these psycho-physiological recordings relate to temporal and grasping performance in a static setting. Methods 10 male subjects (26+/-years old, participated in this study and were asked to come for 2 consecutive days. On the first day the experiment objective, tasks, and experiment setting was explained. Then, they completed a 30 minutes guided training. On the second day each subject was tested in 3 different modalities: Auditory Feedback only control (AF, Visual Feedback only control (VF, and Audiovisual Feedback control (AVF. For each modality they were asked to perform 10 trials. At the end of each test, the subject had to answer the NASA TLX questionnaire. Also, during the test the subject’s EEG, ECG, electro-dermal activity (EDA, and respiration rate were measured. Results The results show that a higher mental effort is needed when the subjects rely only on their vision, and that this effort seems to be reduced when auditory feedback is added to the human-machine interaction (multimodal feedback. Furthermore, better temporal performance and better grasping performance was obtained in the audiovisual modality. Conclusions The performance

  10. Conceptual Network Model From Sensory Neurons to Astrocytes of the Human Nervous System.

    Science.gov (United States)

    Yang, Yiqun; Yeo, Chai Kiat

    2015-07-01

    From a single-cell animal like paramecium to vertebrates like ape, the nervous system plays an important role in responding to the variations of the environment. Compared to animals, the nervous system in the human body possesses more intricate organization and utility. The nervous system anatomy has been understood progressively, yet the explanation at the cell level regarding complete information transmission is still lacking. Along the signal pathway toward the brain, an external stimulus first activates action potentials in the sensing neuron and these electric pulses transmit along the spinal nerve or cranial nerve to the neurons in the brain. Second, calcium elevation is triggered in the branch of astrocyte at the tripartite synapse. Third, the local calcium wave expands to the entire territory of the astrocyte. Finally, the calcium wave propagates to the neighboring astrocyte via gap junction channel. In our study, we integrate the existing mathematical model and biological experiments in each step of the signal transduction to establish a conceptual network model for the human nervous system. The network is composed of four layers and the communication protocols of each layer could be adapted to entities with different characterizations. We verify our simulation results against the available biological experiments and mathematical models and provide a test case of the integrated network. As the production of conscious episode in the human nervous system is still under intense research, our model serves as a useful tool to facilitate, complement and verify current and future study in human cognition.

  11. Compact modeling of CRS devices based on ECM cells for memory, logic and neuromorphic applications

    International Nuclear Information System (INIS)

    Linn, E; Ferch, S; Waser, R; Menzel, S

    2013-01-01

    Dynamic physics-based models of resistive switching devices are of great interest for the realization of complex circuits required for memory, logic and neuromorphic applications. Here, we apply such a model of an electrochemical metallization (ECM) cell to complementary resistive switches (CRSs), which are favorable devices to realize ultra-dense passive crossbar arrays. Since a CRS consists of two resistive switching devices, it is straightforward to apply the dynamic ECM model for CRS simulation with MATLAB and SPICE, enabling study of the device behavior in terms of sweep rate and series resistance variations. Furthermore, typical memory access operations as well as basic implication logic operations can be analyzed, revealing requirements for proper spike and level read operations. This basic understanding facilitates applications of massively parallel computing paradigms required for neuromorphic applications. (paper)

  12. Coincidence of pheromone and plant odor leads to sensory plasticity in the heliothine olfactory system.

    Directory of Open Access Journals (Sweden)

    Elena Ian

    Full Text Available Male moths possess a highly specialized olfactory system comprised of two segregated sub-arrangements dedicated to processing information about plant odors and pheromones, respectively. Communication between these two sub-systems has been described at the peripheral level, but relatively little is known about putative interactions at subsequent synaptic relays. The male moth faces the challenge of seeking out the conspecific female in a highly dynamic odor world. The female-produced pheromone blend, which is a limited resource serving as guidance for the male, will reach his antennae in intermittent pockets of odor filaments mixed with volatiles from various plants. In the present study we performed calcium imaging for measuring odor-evoked responses in the uni-glomerular antennal-lobe projection neurons (analog to mitral cells in the vertebrate olfactory bulb of Helicoverpa armigera. In order to investigate putative interactions between the two sub-systems tuned to plant volatiles and pheromones, respectively, we performed repeated stimulations with a selection of biologically relevant odors. We found that paired stimulation with a plant odor and the pheromone led to suppressed responses in both sub-systems as compared to those evoked during initial stimulation including application of each odor stimulus alone. The fact that the suppression persisted also after pairing, indicates the existence of a Hebbian-like plasticity in the primary olfactory center established by temporal pairing of the two odor stimulation categories.

  13. Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

    OpenAIRE

    Neftci, Emre O.; Augustine, Charles; Paul, Somnath; Detorakis, Georgios

    2017-01-01

    An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of net...

  14. System model the processing of heterogeneous sensory information in robotized complex

    Science.gov (United States)

    Nikolaev, V.; Titov, V.; Syryamkin, V.

    2018-05-01

    Analyzed the scope and the types of robotic systems consisting of subsystems of the form "a heterogeneous sensors data processing subsystem". On the basis of the Queuing theory model is developed taking into account the unevenness of the intensity of information flow from the sensors to the subsystem of information processing. Analytical solution to assess the relationship of subsystem performance and uneven flows. The research of the obtained solution in the range of parameter values of practical interest.

  15. Road structural elements temperature trends diagnostics using sensory system of own design

    Science.gov (United States)

    Dudak, Juraj; Gaspar, Gabriel; Sedivy, Stefan; Pepucha, Lubomir; Florkova, Zuzana

    2017-09-01

    A considerable funds is spent for the roads maintenance in large areas during the winter. The road maintenance is significantly affected by the temperature change of the road structure. In remote locations may occur a situation, when it is not clear whether the sanding is actually needed because the lack of information on road conditions. In these cases, the actual road conditions are investigated by a personal inspection or by sending out a gritting vehicle. Here, however, is a risk of unnecessary trip the sanding vehicle. This situation is economically and environmentally unfavorable. The proposed system solves the problem of measuring the temperature profile of the road and the utilization of the predictive model to determine the future development trend of temperature. The system was technically designed as a set of sensors to monitor environmental values such as the temperature of the road, ambient temperature, relative air humidity, solar radiation and atmospheric pressure at the measuring point. An important part of the proposal is prediction model which based on the inputs from sensors and historical measurements can, with some probability, predict temperature trends at the measuring point. The proposed system addresses the economic and environmental aspects of winter road maintenance.

  16. Optimized pulsed write schemes improve linearity and write speed for low-power organic neuromorphic devices

    Science.gov (United States)

    Keene, Scott T.; Melianas, Armantas; Fuller, Elliot J.; van de Burgt, Yoeri; Talin, A. Alec; Salleo, Alberto

    2018-06-01

    Neuromorphic devices are becoming increasingly appealing as efficient emulators of neural networks used to model real world problems. However, no hardware to date has demonstrated the necessary high accuracy and energy efficiency gain over CMOS in both (1) training via backpropagation and (2) in read via vector matrix multiplication. Such shortcomings are due to device non-idealities, particularly asymmetric conductance tuning in response to uniform voltage pulse inputs. Here, by formulating a general circuit model for capacitive ion-exchange neuromorphic devices, we show that asymmetric nonlinearity in organic electrochemical neuromorphic devices (ENODes) can be suppressed by an appropriately chosen write scheme. Simulations based upon our model suggest that a nonlinear write-selector could reduce the switching voltage and energy, enabling analog tuning via a continuous set of resistance states (100 states) with extremely low switching energy (~170 fJ · µm‑2). This work clarifies the pathway to neural algorithm accelerators capable of parallelism during both read and write operations.

  17. Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines.

    Science.gov (United States)

    Neftci, Emre O; Augustine, Charles; Paul, Somnath; Detorakis, Georgios

    2017-01-01

    An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP) rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F) neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning.

  18. Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

    Directory of Open Access Journals (Sweden)

    Emre O. Neftci

    2017-06-01

    Full Text Available An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning.

  19. A digital implementation of neuron-astrocyte interaction for neuromorphic applications.

    Science.gov (United States)

    Nazari, Soheila; Faez, Karim; Amiri, Mahmood; Karami, Ehsan

    2015-06-01

    Recent neurophysiologic findings have shown that astrocytes play important roles in information processing and modulation of neuronal activity. Motivated by these findings, in the present research, a digital neuromorphic circuit to study neuron-astrocyte interaction is proposed. In this digital circuit, the firing dynamics of the neuron is described by Izhikevich model and the calcium dynamics of a single astrocyte is explained by a functional model introduced by Postnov and colleagues. For digital implementation of the neuron-astrocyte signaling, Single Constant Multiply (SCM) technique and several linear approximations are used for efficient low-cost hardware implementation on digital platforms. Using the proposed neuron-astrocyte circuit and based on the results of MATLAB simulations, hardware synthesis and FPGA implementation, it is demonstrated that the proposed digital astrocyte is able to change the firing patterns of the neuron through bidirectional communication. Utilizing the proposed digital circuit, it will be illustrated that information processing in synaptic clefts is strongly regulated by astrocyte. Moreover, our results suggest that the digital circuit of neuron-astrocyte crosstalk produces diverse neural responses and therefore enhances the information processing capabilities of the neuromorphic circuits. This is suitable for applications in reconfigurable neuromorphic devices which implement biologically brain circuits. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. MemFlash device: floating gate transistors as memristive devices for neuromorphic computing

    Science.gov (United States)

    Riggert, C.; Ziegler, M.; Schroeder, D.; Krautschneider, W. H.; Kohlstedt, H.

    2014-10-01

    Memristive devices are promising candidates for future non-volatile memory applications and mixed-signal circuits. In the field of neuromorphic engineering these devices are especially interesting to emulate neuronal functionality. Therefore, new materials and material combinations are currently investigated, which are often not compatible with Si-technology processes. The underlying mechanisms of the device often remain unclear and are paired with low device endurance and yield. These facts define the current most challenging development tasks towards a reliable memristive device technology. In this respect, the MemFlash concept is of particular interest. A MemFlash device results from a diode configuration wiring scheme of a floating gate transistor, which enables the persistent device resistance to be varied according to the history of the charge flow through the device. In this study, we investigate the scaling conditions of the floating gate oxide thickness with respect to possible applications in the field of neuromorphic engineering. We show that MemFlash cells exhibit essential features with respect to neuromorphic applications. In particular, cells with thin floating gate oxides show a limited synaptic weight growth together with low energy dissipation. MemFlash cells present an attractive alternative for state-of-art memresitive devices. The emulation of associative learning is discussed by implementing a single MemFlash cell in an analogue circuit.

  1. MemFlash device: floating gate transistors as memristive devices for neuromorphic computing

    International Nuclear Information System (INIS)

    Riggert, C; Ziegler, M; Kohlstedt, H; Schroeder, D; Krautschneider, W H

    2014-01-01

    Memristive devices are promising candidates for future non-volatile memory applications and mixed-signal circuits. In the field of neuromorphic engineering these devices are especially interesting to emulate neuronal functionality. Therefore, new materials and material combinations are currently investigated, which are often not compatible with Si-technology processes. The underlying mechanisms of the device often remain unclear and are paired with low device endurance and yield. These facts define the current most challenging development tasks towards a reliable memristive device technology. In this respect, the MemFlash concept is of particular interest. A MemFlash device results from a diode configuration wiring scheme of a floating gate transistor, which enables the persistent device resistance to be varied according to the history of the charge flow through the device. In this study, we investigate the scaling conditions of the floating gate oxide thickness with respect to possible applications in the field of neuromorphic engineering. We show that MemFlash cells exhibit essential features with respect to neuromorphic applications. In particular, cells with thin floating gate oxides show a limited synaptic weight growth together with low energy dissipation. MemFlash cells present an attractive alternative for state-of-art memresitive devices. The emulation of associative learning is discussed by implementing a single MemFlash cell in an analogue circuit. (paper)

  2. Dendritic development of Drosophila high order visual system neurons is independent of sensory experience

    Directory of Open Access Journals (Sweden)

    Reuter John E

    2003-06-01

    Full Text Available Abstract Background The complex and characteristic structures of dendrites are a crucial part of the neuronal architecture that underlies brain function, and as such, their development has been a focal point of recent research. It is generally believed that dendritic development is controlled by a combination of endogenous genetic mechanisms and activity-dependent mechanisms. Therefore, it is of interest to test the relative contributions of these two types of mechanisms towards the construction of specific dendritic trees. In this study, we make use of the highly complex Vertical System (VS of motion sensing neurons in the lobula plate of the Drosophila visual system to gauge the importance of visual input and synaptic activity to dendritic development. Results We find that the dendrites of VS1 neurons are unchanged in dark-reared flies as compared to control flies raised on a 12 hour light, 12 hour dark cycle. The dendrites of these flies show no differences from control in dendrite complexity, spine number, spine density, or axon complexity. Flies with genetically ablated eyes show a slight but significant reduction in the complexity and overall length of VS1 dendrites, although this effect may be due to a reduction in the overall size of the dendritic field in these flies. Conclusions Overall, our results indicate no role for visual experience in the development of VS dendrites, while spontaneous activity from photoreceptors may play at most a subtle role in the formation of fully complex dendrites in these high-order visual processing neurons.

  3. Cellular and circuit properties supporting different sensory coding strategies in electric fish and other systems.

    Science.gov (United States)

    Marsat, Gary; Longtin, André; Maler, Leonard

    2012-08-01

    Neural codes often seem tailored to the type of information they must carry. Here we contrast the encoding strategies for two different communication signals in electric fish and describe the underlying cellular and network properties that implement them. We compare an aggressive signal that needs to be quickly detected, to a courtship signal whose quality needs to be evaluated. The aggressive signal is encoded by synchronized bursts and a predictive feedback input is crucial in separating background noise from the communication signal. The courtship signal is accurately encoded through a heterogenous population response allowing the discrimination of signal differences. Most importantly we show that the same strategies are used in other systems arguing that they evolved similar solutions because they faced similar tasks. Copyright © 2012 Elsevier Ltd. All rights reserved.

  4. Understanding a Deep Learning Technique through a Neuromorphic System a Case Study with SpiNNaker Neuromorphic Platform

    OpenAIRE

    Sugiarto Indar; Pasila Felix

    2018-01-01

    Deep learning (DL) has been considered as a breakthrough technique in the field of artificial intelligence and machine learning. Conceptually, it relies on a many-layer network that exhibits a hierarchically non-linear processing capability. Some DL architectures such as deep neural networks, deep belief networks and recurrent neural networks have been developed and applied to many fields with incredible results, even comparable to human intelligence. However, many researchers are still scept...

  5. How sensory-motor systems impact the neural organization for language: direct contrasts between spoken and signed language

    Science.gov (United States)

    Emmorey, Karen; McCullough, Stephen; Mehta, Sonya; Grabowski, Thomas J.

    2014-01-01

    To investigate the impact of sensory-motor systems on the neural organization for language, we conducted an H215O-PET study of sign and spoken word production (picture-naming) and an fMRI study of sign and audio-visual spoken language comprehension (detection of a semantically anomalous sentence) with hearing bilinguals who are native users of American Sign Language (ASL) and English. Directly contrasting speech and sign production revealed greater activation in bilateral parietal cortex for signing, while speaking resulted in greater activation in bilateral superior temporal cortex (STC) and right frontal cortex, likely reflecting auditory feedback control. Surprisingly, the language production contrast revealed a relative increase in activation in bilateral occipital cortex for speaking. We speculate that greater activation in visual cortex for speaking may actually reflect cortical attenuation when signing, which functions to distinguish self-produced from externally generated visual input. Directly contrasting speech and sign comprehension revealed greater activation in bilateral STC for speech and greater activation in bilateral occipital-temporal cortex for sign. Sign comprehension, like sign production, engaged bilateral parietal cortex to a greater extent than spoken language. We hypothesize that posterior parietal activation in part reflects processing related to spatial classifier constructions in ASL and that anterior parietal activation may reflect covert imitation that functions as a predictive model during sign comprehension. The conjunction analysis for comprehension revealed that both speech and sign bilaterally engaged the inferior frontal gyrus (with more extensive activation on the left) and the superior temporal sulcus, suggesting an invariant bilateral perisylvian language system. We conclude that surface level differences between sign and spoken languages should not be dismissed and are critical for understanding the neurobiology of language

  6. Synaptic learning rules and sparse coding in a model sensory system.

    Directory of Open Access Journals (Sweden)

    Luca A Finelli

    2008-04-01

    Full Text Available Neural circuits exploit numerous strategies for encoding information. Although the functional significance of individual coding mechanisms has been investigated, ways in which multiple mechanisms interact and integrate are not well understood. The locust olfactory system, in which dense, transiently synchronized spike trains across ensembles of antenna lobe (AL neurons are transformed into a sparse representation in the mushroom body (MB; a region associated with memory, provides a well-studied preparation for investigating the interaction of multiple coding mechanisms. Recordings made in vivo from the insect MB demonstrated highly specific responses to odors in Kenyon cells (KCs. Typically, only a few KCs from the recorded population of neurons responded reliably when a specific odor was presented. Different odors induced responses in different KCs. Here, we explored with a biologically plausible model the possibility that a form of plasticity may control and tune synaptic weights of inputs to the mushroom body to ensure the specificity of KCs' responses to familiar or meaningful odors. We found that plasticity at the synapses between the AL and the MB efficiently regulated the delicate tuning necessary to selectively filter the intense AL oscillatory output and condense it to a sparse representation in the MB. Activity-dependent plasticity drove the observed specificity, reliability, and expected persistence of odor representations, suggesting a role for plasticity in information processing and making a testable prediction about synaptic plasticity at AL-MB synapses.

  7. Investigation of Acupuncture Sensation Patterns under Sensory Deprivation Using a Geographic Information System

    Science.gov (United States)

    Beissner, Florian; Marzolff, Irene

    2012-01-01

    The study of acupuncture-related sensations, like deqi and propagated sensations along channels (PSCs), has a long tradition in acupuncture basic research. The phenomenon itself, however, remains poorly understood. To study the connection between PSC and classical meridians, we applied a geographic information system (GIS) to analyze sketches of acupuncture sensations from healthy volunteers after laser acupuncture. As PSC can be subtle, we aimed at reducing the confounding impact of external stimuli by carrying out the experiment in a floatation tank under restricted environmental stimulation. 82.4% of the subjects experienced PSC, that is, they had line-like or 2-dimensional sensations, although there were some doubts that these were related to the laser stimulation. Line-like sensations on the same limb were averaged to calculate sensation mean courses, which were then compared to classical meridians by measuring the mean distance between the two. Distances ranged from 0.83 cm in the case of the heart (HT) and spleen (SP) meridian to 6.27 cm in the case of the kidney (KI) meridian. Furthermore, PSC was observed to “jump” between adjacent meridians. In summary, GIS has proven to be a valuable tool to study PSC, and our results suggest a close connection between PSC and classical meridians. PMID:23243458

  8. Importance of Applying Condiments in a Commonly Consumed Food System for Understanding the Association Between Familiarity and Sensory Drivers of Liking: A Study Focused on Doenjang.

    Science.gov (United States)

    Roh, Soo Hyun; Lee, Soh Min; Kim, Sang Sook; Kim, Kwang-Ok

    2018-02-01

    Doenjang, a Korean traditional fermented soybean paste, is one of the most essential condiments in Korean cuisine. Condiments are rarely consumed as it is, and are generally applied to other foods. The objective of this study was to understand how sensory drivers of liking of Doenjang would be affected according to food forms in which it is evaluated: the original paste form compared with a normally consumed soup form, and to understand the association of familiarity of evaluated food form. Descriptive analysis and consumer acceptability test was performed in 2 consumption forms: the original paste form and the Doenjang soup from. For consumer liking test, elderly consumers who have more experience to traditional Deonjang were compared to the young in their response to Doenjang paste and soup. The descriptive analysis results showed that the characteristic sensory features of the Deonjang samples were little affected based on the food system in which it was evaluated. However, when the paste was applied in soup, the intensities of the characteristic sensory features were reduced. Acceptability and familiarity of traditional type Doenjang samples for the young and for the elderly consumers were very similar in paste, but it differed when the samples were evaluated in soup. Thus, expectation difference between the young and the elderly was better revealed in soup, a more common food form consumed in practice. The results of this study indicate the importance of understanding sensory drivers of liking for a condiment such as Doenjang in their commonly consumed forms. Compared to the original condiment form, expectation difference between the young and the elderly were better revealed in Deonjang soup, a food form normally consumed in practice. Thus, the results of this study reinforced the importance of investigating sensory drivers of liking for a condiment in a food form that is normally consumed in practice for accurate understanding on consumer preference. © 2018

  9. A Re-configurable On-line Learning Spiking Neuromorphic Processor comprising 256 neurons and 128K synapses

    Directory of Open Access Journals (Sweden)

    Ning eQiao

    2015-04-01

    Full Text Available Implementing compact, low-power artificial neural processing systems with real-time on-line learning abilities is still an open challenge. In this paper we present a full-custom mixed-signal VLSI device with neuromorphic learning circuits that emulate the biophysics of real spiking neurons and dynamic synapses for exploring the properties of computational neuroscience models and for building brain-inspired computing systems. The proposed architecture allows the on-chip configuration of a wide range of network connectivities, including recurrent and deep networks with short-term and long-term plasticity. The device comprises 128 K analog synapse and 256 neuron circuits with biologically plausible dynamics and bi-stable spike-based plasticity mechanisms that endow it with on-line learning abilities. In addition to the analog circuits, the device comprises also asynchronous digital logic circuits for setting different synapse and neuron properties as well as different network configurations. This prototype device, fabricated using a 180 nm 1P6M CMOS process, occupies an area of 51.4 mm 2 , and consumes approximately 4 mW for typical experiments, for example involving attractor networks. Here we describe the details of the overall architecture and of the individual circuits and present experimental results that showcase its potential. By supporting a wide range of cortical-like computational modules comprising plasticity mechanisms, this device will enable the realization of intelligent autonomous systems with on-line learning capabilities.

  10. Circuit motifs for contrast-adaptive differentiation in early sensory systems: the role of presynaptic inhibition and short-term plasticity.

    Science.gov (United States)

    Zhang, Danke; Wu, Si; Rasch, Malte J

    2015-01-01

    In natural signals, such as the luminance value across of a visual scene, abrupt changes in intensity value are often more relevant to an organism than intensity values at other positions and times. Thus to reduce redundancy, sensory systems are specialized to detect the times and amplitudes of informative abrupt changes in the input stream rather than coding the intensity values at all times. In theory, a system that responds transiently to fast changes is called a differentiator. In principle, several different neural circuit mechanisms exist that are capable of responding transiently to abrupt input changes. However, it is unclear which circuit would be best suited for early sensory systems, where the dynamic range of the natural input signals can be very wide. We here compare the properties of different simple neural circuit motifs for implementing signal differentiation. We found that a circuit motif based on presynaptic inhibition (PI) is unique in a sense that the vesicle resources in the presynaptic site can be stably maintained over a wide range of stimulus intensities, making PI a biophysically plausible mechanism to implement a differentiator with a very wide dynamical range. Moreover, by additionally considering short-term plasticity (STP), differentiation becomes contrast adaptive in the PI-circuit but not in other potential neural circuit motifs. Numerical simulations show that the behavior of the adaptive PI-circuit is consistent with experimental observations suggesting that adaptive presynaptic inhibition might be a good candidate neural mechanism to achieve differentiation in early sensory systems.

  11. Contribution of crosslinking products in the flavour enhancer processing: the new concept of Maillard peptide in sensory characteristics of Maillard reaction systems.

    Science.gov (United States)

    Karangwa, Eric; Murekatete, Nicole; Habimana, Jean de Dieu; Masamba, Kingsley; Duhoranimana, Emmanuel; Muhoza, Bertrand; Zhang, Xiaoming

    2016-06-01

    In this study, the flavour-enhancing properties of the Maillard reaction products (MRPs) for different systems consisted of different peptides (sunflower, SFP; corn, CP and soyabean SP) with, xylose and cysteine were investigated. Maillard systems from peptides of sunflower, corn and soyabean with xylose and cysteine were designated as PXC, MCP and MSP, respectively. The Maillard systems were prepared at pH of 7.4 using temperature of 120C for 2 h. Results showed that all systems were significantly different in all sensory attributes. The highest scores for mouthfulness and continuity were observed for MCP with the lowest peptides distribution between 1000 and 5000 Da, known as Maillard peptide. This revealed that the MCP with the lowest Maillard peptide content had the strongest "Kokumi" effect compared to the other MRPsand demonstrated that "kokumi effect" of MRPs was contributed by not only the "Maillard peptide" defined by the molecular weight (1000-5000 Da). Results on sensory evaluation after fractionation of PXC followed by enzymatic hydrolysis showed no significant differences between PXC, P-PXC and their hydrolysates. This observation therefore confirmed that the presence of other contributors attributed to the "Kokumi" effect rather than the Maillard peptide. It can be deduced that the unhydrolyzed crosslinking products might have contributed to the "Kokumi" effect of MRPs. The structures of four probable crosslinking compounds were proposed and the findings have provided new insights in the sensory characteristics of xylose, cysteine and sunflower peptide MRPs.

  12. Endocranial anatomy of the charadriiformes: sensory system variation and the evolution of wing-propelled diving.

    Directory of Open Access Journals (Sweden)

    N Adam Smith

    Full Text Available Just as skeletal characteristics provide clues regarding behavior of extinct vertebrates, phylogenetically-informed evaluation of endocranial morphology facilitates comparisons among extinct taxa and extant taxa with known behavioral characteristics. Previous research has established that endocranial morphology varies across Aves; however, variation of those systems among closely related species remains largely unexplored. The Charadriiformes (shorebirds and allies are an ecologically diverse clade with a comparatively rich fossil record, and therefore, are well suited for investigating interspecies variation, and potential links between endocranial morphology, phylogeny, ecology and other life history attributes. Endocranial endocasts were rendered from high resolution X-ray computed tomography data for 17 charadriiforms (15 extant and two flightless extinct species. Evaluation of endocranial character state changes on a phylogeny for Charadriiformes resulted in identification of characters that vary in taxa with distinct feeding and locomotor ecologies. In comparison with all other charadriiforms, stem and crown clade wing-propelled diving Pan-Alcidae displayed compressed semicircular canals, and indistinct occipital sinuses and cerebellar fissures. Flightless wing-propelled divers have relatively smaller brains for their body mass and smaller optic lobes than volant pan-alcids. Observed differences between volant and flightless wing-propelled sister taxa are striking given that flightless pan-alcids continue to rely on the flight stroke for underwater propulsion. Additionally, the brain of the Black Skimmer Rynchops niger, a taxon with a unique feeding ecology that involves continuous forward aerial motion and touch-based prey detection used both at day and night, is discovered to be unlike that of any other sampled charadriiform in having an extremely large wulst as well as a small optic lobe and distinct occipital sinus. Notably, the

  13. Is a 4-bit synaptic weight resolution enough? - constraints on enabling spike-timing dependent plasticity in neuromorphic hardware.

    Science.gov (United States)

    Pfeil, Thomas; Potjans, Tobias C; Schrader, Sven; Potjans, Wiebke; Schemmel, Johannes; Diesmann, Markus; Meier, Karlheinz

    2012-01-01

    Large-scale neuromorphic hardware systems typically bear the trade-off between detail level and required chip resources. Especially when implementing spike-timing dependent plasticity, reduction in resources leads to limitations as compared to floating point precision. By design, a natural modification that saves resources would be reducing synaptic weight resolution. In this study, we give an estimate for the impact of synaptic weight discretization on different levels, ranging from random walks of individual weights to computer simulations of spiking neural networks. The FACETS wafer-scale hardware system offers a 4-bit resolution of synaptic weights, which is shown to be sufficient within the scope of our network benchmark. Our findings indicate that increasing the resolution may not even be useful in light of further restrictions of customized mixed-signal synapses. In addition, variations due to production imperfections are investigated and shown to be uncritical in the context of the presented study. Our results represent a general framework for setting up and configuring hardware-constrained synapses. We suggest how weight discretization could be considered for other backends dedicated to large-scale simulations. Thus, our proposition of a good hardware verification practice may rise synergy effects between hardware developers and neuroscientists.

  14. Is a 4-bit synaptic weight resolution enough? - Constraints on enabling spike-timing dependent plasticity in neuromorphic hardware

    Directory of Open Access Journals (Sweden)

    Thomas ePfeil

    2012-07-01

    Full Text Available Large-scale neuromorphic hardware systems typically bear the trade-off be-tween detail level and required chip resources. Especially when implementingspike-timing-dependent plasticity, reduction in resources leads to limitations ascompared to floating point precision. By design, a natural modification that savesresources would be reducing synaptic weight resolution. In this study, we give anestimate for the impact of synaptic weight discretization on different levels, rangingfrom random walks of individual weights to computer simulations of spiking neuralnetworks. The FACETS wafer-scale hardware system offers a 4-bit resolution ofsynaptic weights, which is shown to be sufficient within the scope of our networkbenchmark. Our findings indicate that increasing the resolution may not even beuseful in light of further restrictions of customized mixed-signal synapses. In ad-dition, variations due to production imperfections are investigated and shown tobe uncritical in the context of the presented study. Our results represent a generalframework for setting up and configuring hardware-constrained synapses. We sug-gest how weight discretization could be considered for other backends dedicatedto large-scale simulations. Thus, our proposition of a good hardware verificationpractice may rise synergy effects between hardware developers and neuroscientists.

  15. Evaluation of umami taste in mushroom extracts by chemical analysis, sensory evaluation, and an electronic tongue system.

    Science.gov (United States)

    Phat, Chanvorleak; Moon, BoKyung; Lee, Chan

    2016-02-01

    Seventeen edible mushrooms commercially available in Korea were analysed for their umami taste compounds (5'-nucleotides: AMP, GMP, IMP, UMP, XMP; free amino acids: aspartic, glutamic acid) and subjected to human sensory evaluation and electronic tongue measurements. Amanita virgineoides featured the highest total 5'-nucleotide content (36.9 ± 1.50 mg/g), while monosodium glutamate-like components (42.4 ± 6.90 mg/g) were highest in Agaricus bisporus. The equivalent umami concentration (EUC) ranged from 1.51 ± 0.42 to 3890 ± 833 mg MSG/g dry weight; most mushrooms exhibited a high umami taste. Pleurotus ostreatus scored the highest in the human sensory evaluation, while Flammulina velutipes obtained the maximum score in the electronic tongue measurement. The EUC and the sensory score from the electronic tongue test were highly correlated, and also showed significant correlation with the human sensory evaluation score. These results suggest that the electronic tongue is suitable to determine the characteristic umami taste of mushrooms. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Do male and female cowbirds see their world differently? Implications for sex differences in the sensory system of an avian brood parasite.

    Directory of Open Access Journals (Sweden)

    Esteban Fernández-Juricic

    Full Text Available BACKGROUND: Male and female avian brood parasites are subject to different selection pressures: males compete for mates but do not provide parental care or territories and only females locate hosts to lay eggs. This sex difference may affect brain architecture in some avian brood parasites, but relatively little is known about their sensory systems and behaviors used to obtain sensory information. Our goal was to study the visual resolution and visual information gathering behavior (i.e., scanning of brown-headed cowbirds. METHODOLOGY/PRINCIPAL FINDINGS: We measured the density of single cone photoreceptors, associated with chromatic vision, and double cone photoreceptors, associated with motion detection and achromatic vision. We also measured head movement rates, as indicators of visual information gathering behavior, when exposed to an object. We found that females had significantly lower density of single and double cones than males around the fovea and in the periphery of the retina. Additionally, females had significantly higher head-movement rates than males. CONCLUSIONS: Overall, we suggest that female cowbirds have lower chromatic and achromatic visual resolution than males (without sex differences in visual contrast perception. Females might compensate for the lower visual resolution by gazing alternatively with both foveae in quicker succession than males, increasing their head movement rates. However, other physiological factors may have influenced the behavioral differences observed. Our results bring up relevant questions about the sensory basis of sex differences in behavior. One possibility is that female and male cowbirds differentially allocate costly sensory resources, as a recent study found that females actually have greater auditory resolution than males.

  17. Training and operation of an integrated neuromorphic network based on metal-oxide memristors

    Science.gov (United States)

    Prezioso, M.; Merrikh-Bayat, F.; Hoskins, B. D.; Adam, G. C.; Likharev, K. K.; Strukov, D. B.

    2015-05-01

    Despite much progress in semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex, with its approximately 1014 synapses, makes the hardware implementation of neuromorphic networks with a comparable number of devices exceptionally challenging. To provide comparable complexity while operating much faster and with manageable power dissipation, networks based on circuits combining complementary metal-oxide-semiconductors (CMOSs) and adjustable two-terminal resistive devices (memristors) have been developed. In such circuits, the usual CMOS stack is augmented with one or several crossbar layers, with memristors at each crosspoint. There have recently been notable improvements in the fabrication of such memristive crossbars and their integration with CMOS circuits, including first demonstrations of their vertical integration. Separately, discrete memristors have been used as artificial synapses in neuromorphic networks. Very recently, such experiments have been extended to crossbar arrays of phase-change memristive devices. The adjustment of such devices, however, requires an additional transistor at each crosspoint, and hence these devices are much harder to scale than metal-oxide memristors, whose nonlinear current-voltage curves enable transistor-free operation. Here we report the experimental implementation of transistor-free metal-oxide memristor crossbars, with device variability sufficiently low to allow operation of integrated neural networks, in a simple network: a single-layer perceptron (an algorithm for linear classification). The network can be taught in situ using a coarse-grain variety of the delta rule algorithm to perform the perfect classification of 3 × 3-pixel black/white images into three classes (representing letters). This demonstration is an important step towards much larger and more complex memristive neuromorphic networks.

  18. Neuromorphic Computing, Architectures, Models, and Applications. A Beyond-CMOS Approach to Future Computing, June 29-July 1, 2016, Oak Ridge, TN

    Energy Technology Data Exchange (ETDEWEB)

    Potok, Thomas [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Schuman, Catherine [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Patton, Robert [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hylton, Todd [Brain Corporation, San Diego, CA (United States); Li, Hai [Univ. of Pittsburgh, PA (United States); Pino, Robinson [US Dept. of Energy, Washington, DC (United States)

    2016-12-31

    The White House and Department of Energy have been instrumental in driving the development of a neuromorphic computing program to help the United States continue its lead in basic research into (1) Beyond Exascale—high performance computing beyond Moore’s Law and von Neumann architectures, (2) Scientific Discovery—new paradigms for understanding increasingly large and complex scientific data, and (3) Emerging Architectures—assessing the potential of neuromorphic and quantum architectures. Neuromorphic computing spans a broad range of scientific disciplines from materials science to devices, to computer science, to neuroscience, all of which are required to solve the neuromorphic computing grand challenge. In our workshop we focus on the computer science aspects, specifically from a neuromorphic device through an application. Neuromorphic devices present a very different paradigm to the computer science community from traditional von Neumann architectures, which raises six major questions about building a neuromorphic application from the device level. We used these fundamental questions to organize the workshop program and to direct the workshop panels and discussions. From the white papers, presentations, panels, and discussions, there emerged several recommendations on how to proceed.

  19. A THEORY OF MAXIMIZING SENSORY INFORMATION

    NARCIS (Netherlands)

    Hateren, J.H. van

    1992-01-01

    A theory is developed on the assumption that early sensory processing aims at maximizing the information rate in the channels connecting the sensory system to more central parts of the brain, where it is assumed that these channels are noisy and have a limited dynamic range. Given a stimulus power

  20. Reward-based learning under hardware constraints-using a RISC processor embedded in a neuromorphic substrate.

    Science.gov (United States)

    Friedmann, Simon; Frémaux, Nicolas; Schemmel, Johannes; Gerstner, Wulfram; Meier, Karlheinz

    2013-01-01

    In this study, we propose and analyze in simulations a new, highly flexible method of implementing synaptic plasticity in a wafer-scale, accelerated neuromorphic hardware system. The study focuses on globally modulated STDP, as a special use-case of this method. Flexibility is achieved by embedding a general-purpose processor dedicated to plasticity into the wafer. To evaluate the suitability of the proposed system, we use a reward modulated STDP rule in a spike train learning task. A single layer of neurons is trained to fire at specific points in time with only the reward as feedback. This model is simulated to measure its performance, i.e., the increase in received reward after learning. Using this performance as baseline, we then simulate the model with various constraints imposed by the proposed implementation and compare the performance. The simulated constraints include discretized synaptic weights, a restricted interface between analog synapses and embedded processor, and mismatch of analog circuits. We find that probabilistic updates can increase the performance of low-resolution weights, a simple interface between analog synapses and processor is sufficient for learning, and performance is insensitive to mismatch. Further, we consider communication latency between wafer and the conventional control computer system that is simulating the environment. This latency increases the delay, with which the reward is sent to the embedded processor. Because of the time continuous operation of the analog synapses, delay can cause a deviation of the updates as compared to the not delayed situation. We find that for highly accelerated systems latency has to be kept to a minimum. This study demonstrates the suitability of the proposed implementation to emulate the selected reward modulated STDP learning rule. It is therefore an ideal candidate for implementation in an upgraded version of the wafer-scale system developed within the BrainScaleS project.

  1. A Multi-Sensorial Simultaneous Localization and Mapping (SLAM) System for Low-Cost Micro Aerial Vehicles in GPS-Denied Environments.

    Science.gov (United States)

    López, Elena; García, Sergio; Barea, Rafael; Bergasa, Luis M; Molinos, Eduardo J; Arroyo, Roberto; Romera, Eduardo; Pardo, Samuel

    2017-04-08

    One of the main challenges of aerial robots navigation in indoor or GPS-denied environments is position estimation using only the available onboard sensors. This paper presents a Simultaneous Localization and Mapping (SLAM) system that remotely calculates the pose and environment map of different low-cost commercial aerial platforms, whose onboard computing capacity is usually limited. The proposed system adapts to the sensory configuration of the aerial robot, by integrating different state-of-the art SLAM methods based on vision, laser and/or inertial measurements using an Extended Kalman Filter (EKF). To do this, a minimum onboard sensory configuration is supposed, consisting of a monocular camera, an Inertial Measurement Unit (IMU) and an altimeter. It allows to improve the results of well-known monocular visual SLAM methods (LSD-SLAM and ORB-SLAM are tested and compared in this work) by solving scale ambiguity and providing additional information to the EKF. When payload and computational capabilities permit, a 2D laser sensor can be easily incorporated to the SLAM system, obtaining a local 2.5D map and a footprint estimation of the robot position that improves the 6D pose estimation through the EKF. We present some experimental results with two different commercial platforms, and validate the system by applying it to their position control.

  2. Robust working memory in an asynchronously spiking neural network realized in neuromorphic VLSI

    Directory of Open Access Journals (Sweden)

    Massimiliano eGiulioni

    2012-02-01

    Full Text Available We demonstrate bistable attractor dynamics in a spiking neural network implemented with neuromorphic VLSI hardware. The on-chip network consists of three interacting populations (two excitatory, one inhibitory of integrate-and-fire (LIF neurons. One excitatory population is distinguished by strong synaptic self-excitation, which sustains meta-stable states of ‘high’ and ‘low’-firing activity. Depending on the overall excitability, transitions to the ‘high’ state may be evoked by external stimulation, or may occur spontaneously due to random activity fluctuations. In the former case, the ‘high’ state retains a working memory of a stimulus until well after its release. In the latter case, ‘high’ states remain stable for seconds, three orders of magnitude longer than the largest time-scale implemented in the circuitry. Evoked and spontaneous transitions form a continuum and may exhibit a wide range of latencies, depending on the strength of external stimulation and of recurrent synaptic excitation. In addition, we investigated corrupted ‘high’ states comprising neurons of both excitatory populations. Within a basin of attraction, the network dynamics corrects such states and re-establishes the prototypical ‘high’ state. We conclude that, with effective theoretical guidance, full-fledged attractor dynamics can be realized with comparatively small populations of neuromorphic hardware neurons.

  3. Robust Working Memory in an Asynchronously Spiking Neural Network Realized with Neuromorphic VLSI.

    Science.gov (United States)

    Giulioni, Massimiliano; Camilleri, Patrick; Mattia, Maurizio; Dante, Vittorio; Braun, Jochen; Del Giudice, Paolo

    2011-01-01

    We demonstrate bistable attractor dynamics in a spiking neural network implemented with neuromorphic VLSI hardware. The on-chip network consists of three interacting populations (two excitatory, one inhibitory) of leaky integrate-and-fire (LIF) neurons. One excitatory population is distinguished by strong synaptic self-excitation, which sustains meta-stable states of "high" and "low"-firing activity. Depending on the overall excitability, transitions to the "high" state may be evoked by external stimulation, or may occur spontaneously due to random activity fluctuations. In the former case, the "high" state retains a "working memory" of a stimulus until well after its release. In the latter case, "high" states remain stable for seconds, three orders of magnitude longer than the largest time-scale implemented in the circuitry. Evoked and spontaneous transitions form a continuum and may exhibit a wide range of latencies, depending on the strength of external stimulation and of recurrent synaptic excitation. In addition, we investigated "corrupted" "high" states comprising neurons of both excitatory populations. Within a "basin of attraction," the network dynamics "corrects" such states and re-establishes the prototypical "high" state. We conclude that, with effective theoretical guidance, full-fledged attractor dynamics can be realized with comparatively small populations of neuromorphic hardware neurons.

  4. Neuromorphic optical sensor chip with color change-intensity change disambiguation

    Science.gov (United States)

    Fu, ZhenHong; Mao, Rui; Cartwright, Alexander N.; Titus, Albert H.

    2010-02-01

    In this paper, we describe the development of a novel, retina-like neuromorphic chip that has an array of two types of retina 'cells' arranged to mimic the fovea structure in certain animals. One of the two retina cell types performs irradiance detection and the other can perform color detection. Together, via the two parallel pathways the retina chip can perform color change intensity change disambiguation (CCICD). The irradiance detection cell has a wide-dynamic detection range that spans almost 3 orders of magnitude. The color detection cell has a buried double junction (BDJ) photodiode as the photoreceptor followed by two parallel logarithmic I-V convertors. The output from this is a color response which has at least a 50nm resolution for wavelengths from 400nm to 900nm. With these two cells, the array can perform color change -intensity change disambiguation (CCICD) to determine if a change in the output of the irradiance pathway is because of irradiance change, color change, or both. This biological retina-like neuromorphic sensor array is implemented in ON-SEMI 0.5μm technology, a standard CMOS fabrication process available at MOSIS.

  5. Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications

    Science.gov (United States)

    Pastur-Romay, Lucas Antón; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana Belén

    2016-01-01

    Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL) and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs). All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS), Quantitative Structure–Activity Relationship (QSAR) research, protein structure prediction and genomics (and other omics) data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron–Astrocyte Networks (DANAN) could overcome the difficulties in architecture design, learning process and scalability of the current ML methods. PMID:27529225

  6. Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications.

    Science.gov (United States)

    Pastur-Romay, Lucas Antón; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana Belén

    2016-08-11

    Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL) and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs). All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS), Quantitative Structure-Activity Relationship (QSAR) research, protein structure prediction and genomics (and other omics) data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron-Astrocyte Networks (DANAN) could overcome the difficulties in architecture design, learning process and scalability of the current ML methods.

  7. Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications

    Directory of Open Access Journals (Sweden)

    Lucas Antón Pastur-Romay

    2016-08-01

    Full Text Available Over the past decade, Deep Artificial Neural Networks (DNNs have become the state-of-the-art algorithms in Machine Learning (ML, speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs. All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS, Quantitative Structure–Activity Relationship (QSAR research, protein structure prediction and genomics (and other omics data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron–Astrocyte Networks (DANAN could overcome the difficulties in architecture design, learning process and scalability of the current ML methods.

  8. Calcitonin gene-related peptide and its receptor components in the human sphenopalatine ganglion -- interaction with the sensory system

    DEFF Research Database (Denmark)

    Csati, Anett; Tajti, Janos; Tuka, Bernadett

    2012-01-01

    , Western blot technique was used to demonstrate the existence of CGRP receptor components in rat SPG. CGRP immunoreactive fibers were frequently found intraganglionic in the SPG in the vicinity of neurons. CLR immunoreactivity was observed in satellite glial cells (SGCs) as well as in nerve fibers......, but not in neurons. RAMP1 immunoreactivity was localized in many neurons and SGCs. Thus, the two CGRP receptor components together were found in the SGCs. In addition, Western blot revealed the presence of RAMP1 and CLR in rat SPG. Our results suggest a possible sensory influence in the parasympathetic cranial...

  9. Flexibility and Stability in Sensory Processing Revealed Using Visual-to-Auditory Sensory Substitution

    Science.gov (United States)

    Hertz, Uri; Amedi, Amir

    2015-01-01

    The classical view of sensory processing involves independent processing in sensory cortices and multisensory integration in associative areas. This hierarchical structure has been challenged by evidence of multisensory responses in sensory areas, and dynamic weighting of sensory inputs in associative areas, thus far reported independently. Here, we used a visual-to-auditory sensory substitution algorithm (SSA) to manipulate the information conveyed by sensory inputs while keeping the stimuli intact. During scan sessions before and after SSA learning, subjects were presented with visual images and auditory soundscapes. The findings reveal 2 dynamic processes. First, crossmodal attenuation of sensory cortices changed direction after SSA learning from visual attenuations of the auditory cortex to auditory attenuations of the visual cortex. Secondly, associative areas changed their sensory response profile from strongest response for visual to that for auditory. The interaction between these phenomena may play an important role in multisensory processing. Consistent features were also found in the sensory dominance in sensory areas and audiovisual convergence in associative area Middle Temporal Gyrus. These 2 factors allow for both stability and a fast, dynamic tuning of the system when required. PMID:24518756

  10. Sensory perception in autism.

    Science.gov (United States)

    Robertson, Caroline E; Baron-Cohen, Simon

    2017-11-01

    Autism is a complex neurodevelopmental condition, and little is known about its neurobiology. Much of autism research has focused on the social, communication and cognitive difficulties associated with the condition. However, the recent revision of the diagnostic criteria for autism has brought another key domain of autistic experience into focus: sensory processing. Here, we review the properties of sensory processing in autism and discuss recent computational and neurobiological insights arising from attention to these behaviours. We argue that sensory traits have important implications for the development of animal and computational models of the condition. Finally, we consider how difficulties in sensory processing may relate to the other domains of behaviour that characterize autism.

  11. Learning from sensory and reward prediction errors during motor adaptation.

    Science.gov (United States)

    Izawa, Jun; Shadmehr, Reza

    2011-03-01

    Voluntary motor commands produce two kinds of consequences. Initially, a sensory consequence is observed in terms of activity in our primary sensory organs (e.g., vision, proprioception). Subsequently, the brain evaluates the sensory feedback and produces a subjective measure of utility or usefulness of the motor commands (e.g., reward). As a result, comparisons between predicted and observed consequences of motor commands produce two forms of prediction error. How do these errors contribute to changes in motor commands? Here, we considered a reach adaptation protocol and found that when high quality sensory feedback was available, adaptation of motor commands was driven almost exclusively by sensory prediction errors. This form of learning had a distinct signature: as motor commands adapted, the subjects altered their predictions regarding sensory consequences of motor commands, and generalized this learning broadly to neighboring motor commands. In contrast, as the quality of the sensory feedback degraded, adaptation of motor commands became more dependent on reward prediction errors. Reward prediction errors produced comparable changes in the motor commands, but produced no change in the predicted sensory consequences of motor commands, and generalized only locally. Because we found that there was a within subject correlation between generalization patterns and sensory remapping, it is plausible that during adaptation an individual's relative reliance on sensory vs. reward prediction errors could be inferred. We suggest that while motor commands change because of sensory and reward prediction errors, only sensory prediction errors produce a change in the neural system that predicts sensory consequences of motor commands.

  12. Understanding the sensory irregularities of esophageal disease.

    Science.gov (United States)

    Farmer, Adam D; Brock, Christina; Frøkjaer, Jens Brøndum; Gregersen, Hans; Khan, Sheeba; Lelic, Dina; Lottrup, Christian; Drewes, Asbjørn Mohr

    2016-08-01

    Symptoms relating to esophageal sensory abnormalities can be encountered in the clinical environment. Such sensory abnormalities may be present in demonstrable disease, such as erosive esophagitis, and in the ostensibly normal esophagus, such as non-erosive reflux disease or functional chest pain. In this review, the authors discuss esophageal sensation and the esophageal pain system. In addition, the authors provide a primer concerning the techniques that are available for investigating the autonomic nervous system, neuroimaging and neurophysiology of esophageal sensory function. Such technological advances, whilst not readily available in the clinic may facilitate the stratification and individualization of therapy in disorders of esophageal sensation in the future.

  13. UNCOMMON SENSORY METHODOLOGIES

    Directory of Open Access Journals (Sweden)

    Vladimír Vietoris

    2015-02-01

    Full Text Available Sensory science is the young but the rapidly developing field of the food industry. Actually, the great emphasis is given to the production of rapid techniques of data collection, the difference between consumers and trained panel is obscured and the role of sensory methodologists is to prepare the ways for evaluation, by which a lay panel (consumers can achieve identical results as a trained panel. Currently, there are several conventional methods of sensory evaluation of food (ISO standards, but more sensory laboratories are developing methodologies that are not strict enough in the selection of evaluators, their mechanism is easily understandable and the results are easily interpretable. This paper deals with mapping of marginal methods used in sensory evaluation of food (new types of profiles, CATA, TDS, napping.

  14. Clonidine used as a perineural adjuvant to ropivacaine, does not prolong the duration of sensory block when controlling for systemic effects

    DEFF Research Database (Denmark)

    Andersen, Jakob Hessel; Jaeger, Pia; Sonne, Tobias Laier

    2017-01-01

    BACKGROUND: Clonidine used as an adjuvant to ropivacaine have been shown to prolong the duration of peripheral nerve blocks. The mechanism of action remains unclear. We hypothesized, that clonidine used as an adjuvant to ropivacaine extends the duration of an adductor canal block (ACB) by a perip......BACKGROUND: Clonidine used as an adjuvant to ropivacaine have been shown to prolong the duration of peripheral nerve blocks. The mechanism of action remains unclear. We hypothesized, that clonidine used as an adjuvant to ropivacaine extends the duration of an adductor canal block (ACB......) by a peripheral mechanism, compared to ropivacaine alone when controlling for systemic effects. METHODS: We conducted a paired, blinded, randomized trial in healthy volunteers. Participants received bilateral ACBs containing 20 ml ropivacaine 0.5% + 1 ml clonidine 150μg/ml in one leg and 20 ml ropivacaine 0.......5% + 1 ml saline in the other leg. The primary outcome measure was duration of sensory block assessed by temperature sensation (alcohol swab). Secondary outcome measures were duration of sensory block assessed by: pinprick, maximum pain during tonic heat stimulation, warmth detection threshold and heat...

  15. The synaptic pharmacology underlying sensory processing in the superior colliculus.

    Science.gov (United States)

    Binns, K E

    1999-10-01

    The superior colliculus (SC) is one of the most ancient regions of the vertebrate central sensory system. In this hub afferents from several sensory pathways converge, and an extensive range of neural circuits enable primary sensory processing, multi-sensory integration and the generation of motor commands for orientation behaviours. The SC has a laminar structure and is usually considered in two parts; the superficial visual layers and the deep multi-modal/motor layers. Neurones in the superficial layers integrate visual information from the retina, cortex and other sources, while the deep layers draw together data from many cortical and sub-cortical sensory areas, including the superficial layers, to generate motor commands. Functional studies in anaesthetized subjects and in slice preparations have used pharmacological tools to probe some of the SC's interacting circuits. The studies reviewed here reveal important roles for ionotropic glutamate receptors in the mediation of sensory inputs to the SC and in transmission between the superficial and deep layers. N-methyl-D-aspartate receptors appear to have special responsibility for the temporal matching of retinal and cortical activity in the superficial layers and for the integration of multiple sensory data-streams in the deep layers. Sensory responses are shaped by intrinsic inhibitory mechanisms mediated by GABA(A) and GABA(B) receptors and influenced by nicotinic acetylcholine receptors. These sensory and motor-command activities of SC neurones are modulated by levels of arousal through extrinsic connections containing GABA, serotonin and other transmitters. It is possible to naturally stimulate many of the SC's sensory and non-sensory inputs either independently or simultaneously and this brain area is an ideal location in which to study: (a) interactions between inputs from the same sensory system; (b) the integration of inputs from several sensory systems; and (c) the influence of non-sensory systems on

  16. Antioxidant activity and sensory analysis of murtilla (Ugni molinae Turcz.) fruit extracts in an oil model system; Actividad antioxidante y evaluación sensorial de extractos de frutos de murtilla (Ugni molinae Turcz.) en un sistema modelo aceitoso

    Energy Technology Data Exchange (ETDEWEB)

    Augusto-Obara, T.R.; Pirce, F.; Scheuermann, E.; Spoto, M.H.F.; Vieira, T.M.F.S.

    2017-07-01

    An oil model system was used to analyze the antioxidant activity of Chilean fruit extracts and to determine their odor sensory effect. Hydroalcoholic extracts from wild and 14-4 genotype murtilla (Ugni molinae Turcz.) fruit were assessed by the Response Surface Methodology. The optimal conditions for producing high total phenolic-content extracts were 49.5% (v/v) ethanol at 30 ºC, which yielded 18.39 and 26.14 mg GAE·g−1 dry matter, respectively. The optimized extracts were added to a lipid model system and evaluated via the Schaal Oven Test. After 96 hours, 150 and 200 mg·kg−1 oil of the wild and 14-4 genotype extracts, respectively, showed an antioxidant capacity similar to TBHQ (200 mg·kg−1 oil) in terms of peroxide values and odor. Thus, murtilla fruit extracts are a natural source of antioxidants for protecting lipidic foods, such as soybean oil. [Spanish] Se analizó la actividad antioxidante de extractos de una fruta chilena en un sistema modelo aceitoso y se determinó el efecto sobre las características organolépticas. Se utilizaron extractos hidroalcohólicos de frutos de murtilla (Ugni molinae Turcz.) silvestre y del genotipo 14-4, y se aplicó la Metodología de Superficie de Respuesta. Las condiciones óptimas para obtener extractos con altos contenidos de fenoles totales fueron 49,5% (v/v) de etanol a 30 °C, lo que produjo 18,39 y 26,14 mg AGE g−1 materia seca, respectivamente. Los extractos optimizados se añadieron a un sistema modelo aceitoso y se evaluaron a través de una prueba de estabilidad en horno Schaal. Después de 96 horas, los extractos de frutos silvestre (150 mg·kg−1 aceite) y genotipo 14-4 (200 mg·kg−1 aceite) mostraron una capacidad antioxidante similar al TBHQ (200 mg·kg−1 aceite) en términos de índice de peróxido y respecto a las características organolépticas. Se concluye que los extractos de frutos de murtilla son una fuente natural de antioxidantes para la protección de los alimentos lip

  17. Ab Initio Molecular-Dynamics Simulation of Neuromorphic Computing in Phase-Change Memory Materials.

    Science.gov (United States)

    Skelton, Jonathan M; Loke, Desmond; Lee, Taehoon; Elliott, Stephen R

    2015-07-08

    We present an in silico study of the neuromorphic-computing behavior of the prototypical phase-change material, Ge2Sb2Te5, using ab initio molecular-dynamics simulations. Stepwise changes in structural order in response to temperature pulses of varying length and duration are observed, and a good reproduction of the spike-timing-dependent plasticity observed in nanoelectronic synapses is demonstrated. Short above-melting pulses lead to instantaneous loss of structural and chemical order, followed by delayed partial recovery upon structural relaxation. We also investigate the link between structural order and electrical and optical properties. These results pave the way toward a first-principles understanding of phase-change physics beyond binary switching.

  18. Progression of changes in the sensorial elements of the cochlear and peripheral vestibular systems: The otitis media continuum.

    Science.gov (United States)

    Monsanto, Rafael da Costa; Schachern, Patricia; Paparella, Michael M; Cureoglu, Sebahattin; Penido, Norma de Oliveira

    2017-08-01

    Our study aimed to evaluate pathologic changes in the cochlear (inner and outer hair cells and stria vascularis) and vestibular (vestibular hair cells, dark, and transitional cells) sensorial elements in temporal bones from donors who had otitis media. We studied 40 temporal bones from such donors, which were categorized in serous otitis media (SOM), serous-purulent otitis media (SPOM), mucoid/mucoid-purulent otitis media (MOM/MPOM), and chronic otitis media (COM); control group comprised 10 nondiseased temporal bones. We found significant loss of inner and outer cochlear hair cells in the basal turn of the SPOM, MOM/MPOM and COM groups; significant loss of vestibular hair cells was observed in the MOM/MPOM and COM groups. All otitis media groups had smaller mean area of the stria vascularis in the basal turn of the cochlea when compared to controls. In conclusion, our study demonstrated more severe pathologic changes in the later stages of the continuum of otitis media (MOM/MPOM and COM). Those changes seem to progress from the basal turn of the cochlea (stria vascularis, then inner and outer hair cells) to the middle turn of the cochlea and to the saccule and utricle in the MOM/MPOM and COM stages. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Organization of sensory input to the nociceptive-specific cutaneous trunk muscle reflex in rat, an effective experimental system for examining nociception and plasticity

    Science.gov (United States)

    Petruska, Jeffrey C.; Barker, Darrell F.; Garraway, Sandra M.; Trainer, Robert; Fransen, James W.; Seidman, Peggy A.; Soto, Roy G.; Mendell, Lorne M.; Johnson, Richard D.

    2013-01-01

    Detailed characterization of neural circuitries furthers our understanding of how nervous systems perform specific functions and enables the use of those systems to test hypotheses. We have characterized the sensory input to the cutaneous trunk muscle (CTM; also cutaneus trunci (rat) or cutaneus maximus (mouse)) reflex (CTMR), which manifests as a puckering of the dorsal thoracolumbar skin and is selectively driven by noxious stimuli. CTM electromyography (EMG) and neurogram recordings in naïve rats revealed that CTMR responses were elicited by natural stimuli and electrical stimulation of all segments from C4 to L6, a much greater extent of segmental drive to the CTMR than previously described. Stimulation of some subcutaneous paraspinal tissue can also elicit this reflex. Using a selective neurotoxin, we also demonstrate differential drive of the CTMR by trkA-expressing and non-expressing small diameter afferents. These observations highlight aspects of the organization of the CTMR system which make it attractive for studies of nociception and anesthesiology and plasticity of primary afferents, motoneurons, and the propriospinal system. We use the CTMR system to qualitatively and quantitatively demonstrate that experimental pharmacological treatments can be compared to controls applied either to the contralateral side or to another segment, with the remaining segments providing controls for systemic or other treatment effects. These data indicate the potential for using the CTMR system as both an invasive and non-invasive quantitative assessment tool providing improved statistical power and reduced animal use. PMID:23983104

  20. Accessibility and sensory experiences

    DEFF Research Database (Denmark)

    Ryhl, Camilla

    2010-01-01

    and accessibility. Sensory accessibility accommodates aspects of a sensory disability and describes architectural design requirements needed to ensure access to architectural experiences. In the context of architecture accessibility has become a design concept of its own. It is generally described as ensuring...... physical access to the built environment by accommodating physical disabilities. While the existing concept of accessibility ensures the physical access of everyone to a given space, sensory accessibility ensures the choice of everyone to stay and be able to participate and experience....

  1. Clonidine used as a perineural adjuvant to ropivacaine, does not prolong the duration of sensory block when controlling for systemic effects

    DEFF Research Database (Denmark)

    Andersen, Jakob Hessel; Jaeger, Pia; Sonne, Tobias Laier

    2017-01-01

    BACKGROUND: Clonidine used as an adjuvant to ropivacaine have been shown to prolong the duration of peripheral nerve blocks. The mechanism of action remains unclear. We hypothesized, that clonidine used as an adjuvant to ropivacaine extends the duration of an adductor canal block (ACB......) by a peripheral mechanism, compared to ropivacaine alone when controlling for systemic effects. METHODS: We conducted a paired, blinded, randomized trial in healthy volunteers. Participants received bilateral ACBs containing 20 ml ropivacaine 0.5% + 1 ml clonidine 150μg/ml in one leg and 20 ml ropivacaine 0...... pain detection threshold. RESULTS: We enrolled 21 volunteers and all completed the trial. There was no difference in duration of sensory block assessed with an alcohol swab: Mean duration in the leg receiving ropivacaine + clonidine was 19.4h (SD 2.7) compared to 19.3h (SD 2.4) in the leg receiving...

  2. Dysregulation of the descending pain system in temporomandibular disorders revealed by low-frequency sensory transcutaneous electrical nerve stimulation: a pupillometric study.

    Directory of Open Access Journals (Sweden)

    Annalisa Monaco

    Full Text Available Using computerized pupillometry, our previous research established that the autonomic nervous system (ANS is dysregulated in patients suffering from temporomandibular disorders (TMDs, suggesting a potential role for ANS dysfunction in pain modulation and the etiology of TMD. However, pain modulation hypotheses for TMD are still lacking. The periaqueductal gray (PAG is involved in the descending modulation of defensive behavior and pain through μ, κ, and δ opioid receptors. Transcutaneous electrical nerve stimulation (TENS has been extensively used for pain relief, as low-frequency stimulation can activate µ receptors. Our aim was to use pupillometry to evaluate the effect of low-frequency TENS stimulation of μ receptors on opioid descending pathways in TMD patients. In accordance with the Research Diagnostic Criteria for TMD, 18 females with myogenous TMD and 18 matched-controls were enrolled. All subjects underwent subsequent pupillometric evaluations under dark and light conditions before, soon after (end of stimulation and long after (recovery period sensorial TENS. The overall statistics derived from the darkness condition revealed no significant differences in pupil size between cases and controls; indeed, TENS stimulation significantly reduced pupil size in both groups. Controls, but not TMD patients, displayed significant differences in pupil size before compared with after TENS. Under light conditions, TMD patients presented a smaller pupil size compared with controls; the pupil size was reduced only in the controls. Pupil size differences were found before and during TENS and before and after TENS in the controls only. Pupillometry revealed that stimulating the descending opioid pathway with low-frequency sensory TENS of the fifth and seventh pairs of cranial nerves affects the peripheral target. The TMD patients exhibited a different pattern of response to TENS stimulation compared with the controls, suggesting that impaired

  3. Sensory evaluation techniques

    National Research Council Canada - National Science Library

    Meilgaard, Morten; Civille, Gail Vance; Carr, B. Thomas

    1991-01-01

    ..., #2 as a textbook for courses at the academic level, it aims to provide just enough theoretical background to enable the student to understand which sensory methods are best suited to particular...

  4. Are Sema5a mutant mice a good model of autism? A behavioral analysis of sensory systems, emotionality and cognition

    Science.gov (United States)

    Gunn, Rhian K.; Huentelman, Matthew J.; Brown, Richard E.

    2011-01-01

    Semaphorin 5A (Sema5A) expression is reduced in the brain of individuals with autism, thus mice with reduced Sema5A levels may serve as a model of this neurodevelopmental disorder. We tested male and female Sema5a knockout mice (B6.129P2SEMA5A/J) and C57BL/6J controls for emotionality, visual ability, prepulse inhibition, motor learning and cognition. Overall, there were only two genotype differences in emotionality: Sema5a mutant mice had more stretch-attend postures in the elevated plus-maze and more defecations in the open field. All mice could see, but Sema5a mice had better visual ability than C57BL/6J mice. There were no genotype differences in sensory-motor gating. Sema5a mice showed higher levels of activity in the elevated plus-maze and light/dark transition box, and there were sex by genotype differences in the Rotarod, suggesting a sex difference in balance and coordination differentially affected by Sema5a. There were no genotype effects on cognition: Sema5a mice did not differ from C57BL/6J in the Morris water maze, set-shifting or cued and contextual fear conditioning. In the social recognition test, all mice preferred social stimuli, but there was no preference for social novelty, thus the Sema5A mice do not have a deficit in social behavior. Overall, there were a number of sex differences, with females showing greater activity and males performing better in tests of spatial learning and memory, but no deficits in the behavior of Sema5A mice. We conclude that the Sema5a mice do not meet the behavioral criteria for a mouse model of autism. PMID:21777623

  5. The Study on Food Sensory Evaluation based on Particle Swarm Optimization Algorithm

    OpenAIRE

    Hairong Wang; Huijuan Xu

    2015-01-01

    In this study, it explores the procedures and methods of the system for establishing food sensory evaluation based on particle swarm optimization algorithm, by means of explaining the interpretation of sensory evaluation and sensory analysis, combined with the applying situation of sensory evaluation in food industry.

  6. Effect of including whole linseed and vitamin E in the diet of young bulls slaughtered at two fat covers on the sensory quality of beef packaged in two different packaging systems.

    Science.gov (United States)

    Albertí, Pere; Campo, María M; Beriain, María J; Ripoll, Guillermo; Sañudo, Carlos

    2017-02-01

    Forty-six Pirenaica young bulls, slaughtered at two levels of fatness (3 and 4 mm), were used to evaluate the effect of the inclusion of 50 g kg -1 linseed alone or with 200 IU vitamin E kg -1 in the concentrate and of the meat packaging system (vacuum or modified atmosphere packaging (MAP)) on the beef sensory quality. The inclusion of linseed or supplementation with vitamin E in the concentrate induced no significant differences in the main meat sensory scores and overall appraisal except under MAP, where small differences due to concentrate ingredients were found in juiciness and metallic flavor intensity. Extending the display time up to 4 or 8 days in high-oxygen MAP had detrimental effects on sensory attributes. Meat from animals with 4 mm fat cover depth were rated more tender and juicy, less fibrous and with a higher intensity of beef flavor and rancid odor than meat from 3 mm fat cover bulls when both samples were vacuum packaged. The inclusion of 50 g kg -1 linseed in the concentrate fed to bulls had no detrimental effect on the beef sensory quality. The vacuum-packaged meat of bulls slaughtered at 4 mm fat cover was rated higher on sensory analysis than that at 3 mm fat cover. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  7. Sensory Entrainment Mechanisms in Auditory Perception: Neural Synchronization Cortico-Striatal Activation.

    Science.gov (United States)

    Sameiro-Barbosa, Catia M; Geiser, Eveline

    2016-01-01

    The auditory system displays modulations in sensitivity that can align with the temporal structure of the acoustic environment. This sensory entrainment can facilitate sensory perception and is particularly relevant for audition. Systems neuroscience is slowly uncovering the neural mechanisms underlying the behaviorally observed sensory entrainment effects in the human sensory system. The present article summarizes the prominent behavioral effects of sensory entrainment and reviews our current understanding of the neural basis of sensory entrainment, such as synchronized neural oscillations, and potentially, neural activation in the cortico-striatal system.

  8. Sensory Entrainment Mechanisms in Auditory Perception: Neural Synchronization Cortico-Striatal Activation

    Science.gov (United States)

    Sameiro-Barbosa, Catia M.; Geiser, Eveline

    2016-01-01

    The auditory system displays modulations in sensitivity that can align with the temporal structure of the acoustic environment. This sensory entrainment can facilitate sensory perception and is particularly relevant for audition. Systems neuroscience is slowly uncovering the neural mechanisms underlying the behaviorally observed sensory entrainment effects in the human sensory system. The present article summarizes the prominent behavioral effects of sensory entrainment and reviews our current understanding of the neural basis of sensory entrainment, such as synchronized neural oscillations, and potentially, neural activation in the cortico-striatal system. PMID:27559306

  9. Crocodylians evolved scattered multi-sensory micro-organs

    Science.gov (United States)

    2013-01-01

    Background During their evolution towards a complete life cycle on land, stem reptiles developed both an impermeable multi-layered keratinized epidermis and skin appendages (scales) providing mechanical, thermal, and chemical protection. Previous studies have demonstrated that, despite the presence of a particularly armored skin, crocodylians have exquisite mechanosensory abilities thanks to the presence of small integumentary sensory organs (ISOs) distributed on postcranial and/or cranial scales. Results Here, we analyze and compare the structure, innervation, embryonic morphogenesis and sensory functions of postcranial, cranial, and lingual sensory organs of the Nile crocodile (Crocodylus niloticus) and the spectacled caiman (Caiman crocodilus). Our molecular analyses indicate that sensory neurons of crocodylian ISOs express a large repertoire of transduction channels involved in mechano-, thermo-, and chemosensory functions, and our electrophysiological analyses confirm that each ISO exhibits a combined sensitivity to mechanical, thermal and pH stimuli (but not hyper-osmotic salinity), making them remarkable multi-sensorial micro-organs with no equivalent in the sensory systems of other vertebrate lineages. We also show that ISOs all exhibit similar morphologies and modes of development, despite forming at different stages of scale morphogenesis across the body. Conclusions The ancestral vertebrate diffused sensory system of the skin was transformed in the crocodylian lineages into an array of discrete multi-sensory micro-organs innervated by multiple pools of sensory neurons. This discretization of skin sensory expression sites is unique among vertebrates and allowed crocodylians to develop a highly-armored, but very sensitive, skin. PMID:23819918

  10. [Treatment of sensory information in neurodevelopmental disorders].

    Science.gov (United States)

    Zoenen, D; Delvenne, V

    2018-01-01

    The processing of information coming from the elementary sensory systems conditions the development and fulfilment of a child's abilities. A dysfunction in the sensory stimuli processing may generate behavioural patterns that might affect a child's learning capacities as well as his relational sphere. The DSM-5 recognizes the sensory abnormalities as part of the symptomatology of Autism Spectrum Disorders. However, similar features are observed in other neurodevelopmental disorders. Over the years, these conditions have been the subject of numerous controversies. Nowadays, they are all grouped together under the term of Neurodevelopmental Disorders in DSM-5. The semiology of these disorders is rich and complex due to the frequent presence of comorbidities and their impact on cognitive, behavioural, and sensorimotor organization but also on a child's personality, as well as his family, his school, or his social relationships. We carried out a review of the literature on the alterations in the treatment of sensory information in ASD but also on the different neurodevelopmental clinical panels in order to show their impact on child development. Atypical sensory profiles have been demonstrated in several neurodevelopmental clinical populations such as Autism Spectrum Disorder, Attention Deficit/Hyperactivity Disorders, Dysphasia and Intellectual Disability. Abnomalies in the processing of sensory information should be systematically evaluated in child developmental disorders.

  11. Neuropathic pain: is quantitative sensory testing helpful?

    Science.gov (United States)

    Krumova, Elena K; Geber, Christian; Westermann, Andrea; Maier, Christoph

    2012-08-01

    Neuropathic pain arises as a consequence of a lesion or disease affecting the somatosensory system and is characterised by a combination of positive and negative sensory symptoms. Quantitative sensory testing (QST) examines the sensory perception after application of different mechanical and thermal stimuli of controlled intensity and the function of both large (A-beta) and small (A-delta and C) nerve fibres, including the corresponding central pathways. QST can be used to determine detection, pain thresholds and stimulus-response curves and can thus detect both negative and positive sensory signs, the second ones not being assessed by other methods. Similarly to all other psychophysical tests QST requires standardised examination, instructions and data evaluation to receive valid and reliable results. Since normative data are available, QST can contribute also to the individual diagnosis of neuropathy, especially in the case of isolated small-fibre neuropathy, in contrast to the conventional electrophysiology which assesses only large myelinated fibres. For example, detection of early stages of subclinical neuropathy in symptomatic or asymptomatic patients with diabetes mellitus can be helpful to optimise treatment and identify diabetic foot at risk of ulceration. QST assessed the individual's sensory profile and thus can be valuable to evaluate the underlying pain mechanisms which occur in different frequencies even in the same neuropathic pain syndromes. Furthermore, assessing the exact sensory phenotype by QST might be useful in the future to identify responders to certain treatments in accordance to the underlying pain mechanisms.

  12. Recent progress on fabrication of memristor and transistor-based neuromorphic devices for high signal processing speed with low power consumption

    Science.gov (United States)

    Hadiyawarman; Budiman, Faisal; Goldianto Octensi Hernowo, Detiza; Pandey, Reetu Raj; Tanaka, Hirofumi

    2018-03-01

    The advanced progress of electronic-based devices for artificial neural networks and recent trends in neuromorphic engineering are discussed in this review. Recent studies indicate that the memristor and transistor are two types of devices that can be implemented as neuromorphic devices. The electrical switching characteristics and physical mechanism of neuromorphic devices based on metal oxide, metal sulfide, silicon, and carbon materials are broadly covered in this review. Moreover, the switching performance comparison of several materials mentioned above are well highlighted, which would be useful for the further development of memristive devices. Recent progress in synaptic devices and the application of a switching device in the learning process is also discussed in this paper.

  13. Effects of Agar Gel Strength and Fat on Oral Breakdown, Volatile Release, and Sensory Perception Using in Vivo and in Vitro Systems.

    Science.gov (United States)

    Frank, Damian; Eyres, Graham T; Piyasiri, Udayasika; Cochet-Broch, Maeva; Delahunty, Conor M; Lundin, Leif; Appelqvist, Ingrid M

    2015-10-21

    The density and composition of a food matrix affect the rates of oral breakdown and in-mouth flavor release as well as the overall sensory experience. Agar gels of increasing concentration (1.0, 1.7, 2.9, and 5% agarose) with and without added fat (0, 2, 5, and 10%) were spiked with seven aroma volatiles. Differences in oral processing and sensory perception were systematically measured by a trained panel using a discrete interval time intensity method. Volatile release was measured in vivo and in vitro by proton transfer reaction mass spectrometry. Greater oral processing was required as agar gel strength increased, and the intensity of flavor-related sensory attributes decreased. Volatile release was inversely related to gel strength, showing that physicochemical phenomena were the main mechanisms underlying the perceived sensory changes. Fat addition reduced the amount of oral processing and had differential effects on release, depending on the fat solubility or lipophilicity of the volatiles.

  14. Clinical neurophysiology and quantitative sensory testing in the investigation of orofacial pain and sensory function.

    Science.gov (United States)

    Jääskeläinen, Satu K

    2004-01-01

    Chronic orofacial pain represents a diagnostic and treatment challenge for the clinician. Some conditions, such as atypical facial pain, still lack proper diagnostic criteria, and their etiology is not known. The recent development of neurophysiological methods and quantitative sensory testing for the examination of the trigeminal somatosensory system offers several tools for diagnostic and etiological investigation of orofacial pain. This review presents some of these techniques and the results of their application in studies on orofacial pain and sensory dysfunction. Clinical neurophysiological investigation has greater diagnostic accuracy and sensitivity than clinical examination in the detection of the neurogenic abnormalities of either peripheral or central origin that may underlie symptoms of orofacial pain and sensory dysfunction. Neurophysiological testing may also reveal trigeminal pathology when magnetic resonance imaging has failed to detect it, so these methods should be considered complementary to each other in the investigation of orofacial pain patients. The blink reflex, corneal reflex, jaw jerk, sensory neurography of the inferior alveolar nerve, and the recording of trigeminal somatosensory-evoked potentials with near-nerve stimulation have all proved to be sensitive and reliable in the detection of dysfunction of the myelinated sensory fibers of the trigeminal nerve or its central connections within the brainstem. With appropriately small thermodes, thermal quantitative sensory testing is useful for the detection of trigeminal small-fiber dysfunction (Adelta and C). In neuropathic conditions, it is most sensitive to lesions causing axonal injury. By combining different techniques for investigation of the trigeminal system, an accurate topographical diagnosis and profile of sensory fiber pathology can be determined. Neurophysiological and quantitative sensory tests have already highlighted some similarities among various orofacial pain conditions

  15. SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations

    Science.gov (United States)

    Choi, Shinhyun; Tan, Scott H.; Li, Zefan; Kim, Yunjo; Choi, Chanyeol; Chen, Pai-Yu; Yeon, Hanwool; Yu, Shimeng; Kim, Jeehwan

    2018-01-01

    Although several types of architecture combining memory cells and transistors have been used to demonstrate artificial synaptic arrays, they usually present limited scalability and high power consumption. Transistor-free analog switching devices may overcome these limitations, yet the typical switching process they rely on—formation of filaments in an amorphous medium—is not easily controlled and hence hampers the spatial and temporal reproducibility of the performance. Here, we demonstrate analog resistive switching devices that possess desired characteristics for neuromorphic computing networks with minimal performance variations using a single-crystalline SiGe layer epitaxially grown on Si as a switching medium. Such epitaxial random access memories utilize threading dislocations in SiGe to confine metal filaments in a defined, one-dimensional channel. This confinement results in drastically enhanced switching uniformity and long retention/high endurance with a high analog on/off ratio. Simulations using the MNIST handwritten recognition data set prove that epitaxial random access memories can operate with an online learning accuracy of 95.1%.

  16. Lie group model neuromorphic geometric engine for real-time terrain reconstruction from stereoscopic aerial photos

    Science.gov (United States)

    Tsao, Thomas R.; Tsao, Doris

    1997-04-01

    In the 1980's, neurobiologist suggested a simple mechanism in primate visual cortex for maintaining a stable and invariant representation of a moving object. The receptive field of visual neurons has real-time transforms in response to motion, to maintain a stable representation. When the visual stimulus is changed due to motion, the geometric transform of the stimulus triggers a dual transform of the receptive field. This dual transform in the receptive fields compensates geometric variation in the stimulus. This process can be modelled using a Lie group method. The massive array of affine parameter sensing circuits will function as a smart sensor tightly coupled to the passive imaging sensor (retina). Neural geometric engine is a neuromorphic computing device simulating our Lie group model of spatial perception of primate's primal visual cortex. We have developed the computer simulation and experimented on realistic and synthetic image data, and performed a preliminary research of using analog VLSI technology for implementation of the neural geometric engine. We have benchmark tested on DMA's terrain data with their result and have built an analog integrated circuit to verify the computational structure of the engine. When fully implemented on ANALOG VLSI chip, we will be able to accurately reconstruct a 3D terrain surface in real-time from stereoscopic imagery.

  17. Spin-neurons: A possible path to energy-efficient neuromorphic computers

    Energy Technology Data Exchange (ETDEWEB)

    Sharad, Mrigank; Fan, Deliang; Roy, Kaushik [School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907 (United States)

    2013-12-21

    Recent years have witnessed growing interest in the field of brain-inspired computing based on neural-network architectures. In order to translate the related algorithmic models into powerful, yet energy-efficient cognitive-computing hardware, computing-devices beyond CMOS may need to be explored. The suitability of such devices to this field of computing would strongly depend upon how closely their physical characteristics match with the essential computing primitives employed in such models. In this work, we discuss the rationale of applying emerging spin-torque devices for bio-inspired computing. Recent spin-torque experiments have shown the path to low-current, low-voltage, and high-speed magnetization switching in nano-scale magnetic devices. Such magneto-metallic, current-mode spin-torque switches can mimic the analog summing and “thresholding” operation of an artificial neuron with high energy-efficiency. Comparison with CMOS-based analog circuit-model of a neuron shows that “spin-neurons” (spin based circuit model of neurons) can achieve more than two orders of magnitude lower energy and beyond three orders of magnitude reduction in energy-delay product. The application of spin-neurons can therefore be an attractive option for neuromorphic computers of future.

  18. Nanoscale RRAM-based synaptic electronics: toward a neuromorphic computing device.

    Science.gov (United States)

    Park, Sangsu; Noh, Jinwoo; Choo, Myung-Lae; Sheri, Ahmad Muqeem; Chang, Man; Kim, Young-Bae; Kim, Chang Jung; Jeon, Moongu; Lee, Byung-Geun; Lee, Byoung Hun; Hwang, Hyunsang

    2013-09-27

    Efforts to develop scalable learning algorithms for implementation of networks of spiking neurons in silicon have been hindered by the considerable footprints of learning circuits, which grow as the number of synapses increases. Recent developments in nanotechnologies provide an extremely compact device with low-power consumption.In particular, nanoscale resistive switching devices (resistive random-access memory (RRAM)) are regarded as a promising solution for implementation of biological synapses due to their nanoscale dimensions, capacity to store multiple bits and the low energy required to operate distinct states. In this paper, we report the fabrication, modeling and implementation of nanoscale RRAM with multi-level storage capability for an electronic synapse device. In addition, we first experimentally demonstrate the learning capabilities and predictable performance by a neuromorphic circuit composed of a nanoscale 1 kbit RRAM cross-point array of synapses and complementary metal-oxide-semiconductor neuron circuits. These developments open up possibilities for the development of ubiquitous ultra-dense, ultra-low-power cognitive computers.

  19. Nanoscale RRAM-based synaptic electronics: toward a neuromorphic computing device

    International Nuclear Information System (INIS)

    Park, Sangsu; Noh, Jinwoo; Choo, Myung-lae; Sheri, Ahmad Muqeem; Jeon, Moongu; Lee, Byung-Geun; Lee, Byoung Hun; Chang, Man; Kim, Young-Bae; Kim, Chang Jung; Hwang, Hyunsang

    2013-01-01

    Efforts to develop scalable learning algorithms for implementation of networks of spiking neurons in silicon have been hindered by the considerable footprints of learning circuits, which grow as the number of synapses increases. Recent developments in nanotechnologies provide an extremely compact device with low-power consumption. In particular, nanoscale resistive switching devices (resistive random-access memory (RRAM)) are regarded as a promising solution for implementation of biological synapses due to their nanoscale dimensions, capacity to store multiple bits and the low energy required to operate distinct states. In this paper, we report the fabrication, modeling and implementation of nanoscale RRAM with multi-level storage capability for an electronic synapse device. In addition, we first experimentally demonstrate the learning capabilities and predictable performance by a neuromorphic circuit composed of a nanoscale 1 kbit RRAM cross-point array of synapses and complementary metal–oxide–semiconductor neuron circuits. These developments open up possibilities for the development of ubiquitous ultra-dense, ultra-low-power cognitive computers. (paper)

  20. Studying Sensory Perception.

    Science.gov (United States)

    Ackerly, Spafford C.

    2001-01-01

    Explains the vestibular organ's role in balancing the body and stabilizing the visual world using the example of a hunter. Describes the relationship between sensory perception and learning. Recommends using optical illusions to illustrate the distinctions between external realities and internal perceptions. (Contains 13 references.) (YDS)

  1. Transcendence and Sensoriness

    DEFF Research Database (Denmark)

    Protestant theology and culture are known for a reserved, at times skeptical, attitude to the use of art and aesthetic forms of expression in a religious context. In Transcendence and Sensoriness, this attitude is analysed and discussed both theoretically and through case studies considered...

  2. Sensory matched filters.

    Science.gov (United States)

    Warrant, Eric J

    2016-10-24

    As animals move through their environments they are subjected to an endless barrage of sensory signals. Of these, some will be of utmost importance, such as the tell-tale aroma of a potential mate, the distinctive appearance of a vital food source or the unmistakable sound of an approaching predator. Others will be less important. Indeed some will not be important at all. There are, for instance, wide realms of the sensory world that remain entirely undetected, simply because an animal lacks the physiological capacity to detect and analyse the signals that characterise this realm. Take ourselves for example: we are completely insensitive to the Earth's magnetic field, a sensory cue of vital importance as a compass for steering the long distance migration of animals as varied as birds, lobsters and sea turtles. We are also totally oblivious to the rich palette of ultraviolet colours that exist all around us, colours seen by insects, crustaceans, birds, fish and lizards (in fact perhaps by most animals). Nor can we hear the ultrasonic sonar pulses emitted by bats in hot pursuit of flying insect prey. The simple reason for these apparent deficiencies is that we either lack the sensory capacity entirely (as in the case of magnetoreception) or that our existing senses are incapable of detecting specific ranges of the stimulus (such as the ultraviolet wavelength range of light). Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Impact of production location, production system, and variety on the volatile organic compounds fingerprints and sensory characteristics of tomatoes

    NARCIS (Netherlands)

    Muilwijk, Mirthe; Heenan, Samuel; Koot, Alex; Ruth, Van Saskia M.

    2015-01-01

    Consumers have more and more interest in where and how their foods are produced. However, it is often challenging to discriminate products from different production locations and systems. The objective of this study was to examine fingerprinting of volatile organic compounds (VOCs) as an approach

  4. Postural Stability of Patients with Schizophrenia during Challenging Sensory Conditions: Implication of Sensory Integration for Postural Control.

    Directory of Open Access Journals (Sweden)

    Ya-Ling Teng

    Full Text Available Postural dysfunctions are prevalent in patients with schizophrenia and affect their daily life and ability to work. In addition, sensory functions and sensory integration that are crucial for postural control are also compromised. This study intended to examine how patients with schizophrenia coordinate multiple sensory systems to maintain postural stability in dynamic sensory conditions. Twenty-nine patients with schizophrenia and 32 control subjects were recruited. Postural stability of the participants was examined in six sensory conditions of different level of congruency of multiple sensory information, which was based on combinations of correct, removed, or conflicting sensory inputs from visual, somatosensory, and vestibular systems. The excursion of the center of pressure was measured by posturography. Equilibrium scores were derived to indicate the range of anterior-posterior (AP postural sway, and sensory ratios were calculated to explore ability to use sensory information to maintain balance. The overall AP postural sway was significantly larger for patients with schizophrenia compared to the controls [patients (69.62±8.99; controls (76.53±7.47; t1,59 = -3.28, p<0.001]. The results of mixed-model ANOVAs showed a significant interaction between the group and sensory conditions [F5,295 = 5.55, p<0.001]. Further analysis indicated that AP postural sway was significantly larger for patients compared to the controls in conditions containing unreliable somatosensory information either with visual deprivation or with conflicting visual information. Sensory ratios were not significantly different between groups, although small and non-significant difference in inefficiency to utilize vestibular information was also noted. No significant correlations were found between postural stability and clinical characteristics. To sum up, patients with schizophrenia showed increased postural sway and a higher rate of falls during challenging sensory

  5. Construction of taste-odor recognitition system using optimized sensory device; Kankaku tekio sensa wo mochiita aji/nioi shikibetsu sisutemu no kosei

    Energy Technology Data Exchange (ETDEWEB)

    Osada, H.; Yoshida, H.; Omamiuda, Y.; Ajishi, Y.; Seki, K. [Iwate University, Iwate (Japan); Kikuchi, S. [Tohoku Gakuin University, Miyagi (Japan)

    1997-06-20

    Until now, the quality of foods, that is, as the electrical measuring method of taste and odor, the utilizing method of artificial fatty films and ceramics of ZnO and so on are devised and put to practical use. However, the field of measuring of taste and odor is a comparative new field, and it is still developing stage in the lasting quality and so on. To measure the quality of foods holds an important position in the safety management, together with supporting the development of products as the needs of user. Authors studied a new taste/odor sensor utilizing the optimized sensory device (OSD) which is prepared from sintering the mixture of the magnetic semiconductor powder such as Mn-An ferrite and ruthenium compound. When various taste and odor components included in food adheres to the OSD, resistance or electromotive force faced on surface electric conduction of the OSD change, therefore it can be clearly discriminated the sort and quality of foods. This paper describes preparation of a thick-film OSD and construction of the multi-channel taste/odor recognition system for some drinks. 12 refs., 13 figs.

  6. Using semantic technologies and the OSU ontology for modelling context and activities in multi-sensory surveillance systems

    Science.gov (United States)

    Gómez A, Héctor F.; Martínez-Tomás, Rafael; Arias Tapia, Susana A.; Rincón Zamorano, Mariano

    2014-04-01

    Automatic systems that monitor human behaviour for detecting security problems are a challenge today. Previously, our group defined the Horus framework, which is a modular architecture for the integration of multi-sensor monitoring stages. In this work, structure and technologies required for high-level semantic stages of Horus are proposed, and the associated methodological principles established with the aim of recognising specific behaviours and situations. Our methodology distinguishes three semantic levels of events: low level (compromised with sensors), medium level (compromised with context), and high level (target behaviours). The ontology for surveillance and ubiquitous computing has been used to integrate ontologies from specific domains and together with semantic technologies have facilitated the modelling and implementation of scenes and situations by reusing components. A home context and a supermarket context were modelled following this approach, where three suspicious activities were monitored via different virtual sensors. The experiments demonstrate that our proposals facilitate the rapid prototyping of this kind of systems.

  7. Damage tolerance modeling and validation of a wireless sensory composite panel for a structural health monitoring system

    Science.gov (United States)

    Talagani, Mohamad R.; Abdi, Frank; Saravanos, Dimitris; Chrysohoidis, Nikos; Nikbin, Kamran; Ragalini, Rose; Rodov, Irena

    2013-05-01

    The paper proposes the diagnostic and prognostic modeling and test validation of a Wireless Integrated Strain Monitoring and Simulation System (WISMOS). The effort verifies a hardware and web based software tool that is able to evaluate and optimize sensorized aerospace composite structures for the purpose of Structural Health Monitoring (SHM). The tool is an extension of an existing suite of an SHM system, based on a diagnostic-prognostic system (DPS) methodology. The goal of the extended SHM-DPS is to apply multi-scale nonlinear physics-based Progressive Failure analyses to the "as-is" structural configuration to determine residual strength, remaining service life, and future inspection intervals and maintenance procedures. The DPS solution meets the JTI Green Regional Aircraft (GRA) goals towards low weight, durable and reliable commercial aircraft. It will take advantage of the currently developed methodologies within the European Clean sky JTI project WISMOS, with the capability to transmit, store and process strain data from a network of wireless sensors (e.g. strain gages, FBGA) and utilize a DPS-based methodology, based on multi scale progressive failure analysis (MS-PFA), to determine structural health and to advice with respect to condition based inspection and maintenance. As part of the validation of the Diagnostic and prognostic system, Carbon/Epoxy ASTM coupons were fabricated and tested to extract the mechanical properties. Subsequently two composite stiffened panels were manufactured, instrumented and tested under compressive loading: 1) an undamaged stiffened buckling panel; and 2) a damaged stiffened buckling panel including an initial diamond cut. Next numerical Finite element models of the two panels were developed and analyzed under test conditions using Multi-Scale Progressive Failure Analysis (an extension of FEM) to evaluate the damage/fracture evolution process, as well as the identification of contributing failure modes. The comparisons

  8. Multiple signalling systems controlling expression of luminescence in Vibrio harveyi: sequence and function of genes encoding a second sensory pathway.

    Science.gov (United States)

    Bassler, B L; Wright, M; Silverman, M R

    1994-07-01

    Density-dependent expression of luminescence in Vibrio harveyi is regulated by the concentration of extracellular signal molecules (autoinducers) in the culture medium. One signal-response system is encoded by the luxL,M,N locus. The luxL and luxM genes are required for the production of an autoinducer (probably beta-hydroxybutyl homoserine lactone), and the luxN gene is required for the response to that autoinducer. Analysis of the phenotypes of LuxL,M and N mutants indicated that an additional signal-response system also controls density sensing. We report here the identification, cloning and analysis of luxP and luxQ, which encode functions required for a second density-sensing system. Mutants with defects in luxP and luxQ are defective in response to a second autoinducer substance. LuxQ, like LuxN, is similar to members of the family of two-component, signal transduction proteins and contains both a histidine protein kinase and a response regulator domain. Analysis of signalling mutant phenotypes indicates that there are at least two separate signal-response pathways which converge to regulate expression of luminescence in V. harveyi.

  9. Descriptive sensory evaluations

    DEFF Research Database (Denmark)

    Dehlholm, Christian

    A recent trend in descriptive sensory evaluation methodology has been the application of rapid evaluation techniques. The ease in use makes the techniques extremely easy to implement by industry and university environments. Thus, one might not consider validity in the choice of method. The overall...... aim of this thesis is to compare and evaluate selected rapid evaluation techniques for sensory profiling. Method variations have been suggested for evaluations in product development and quality control, and method insight is provided. The thesis includes three original studies, designed...... as a consequence of the current practices and needs faced in the industry. Study I compared applicability and validity of rapid methods across several panels of trained assessors. Two rapid approaches were introduced for the evaluation of foods. The first method, ‘Free Multiple Sorting’, allows subjects to perform...

  10. Postural Stability of Patients with Schizophrenia during Challenging Sensory Conditions: Implication of Sensory Integration for Postural Control.

    Science.gov (United States)

    Teng, Ya-Ling; Chen, Chiung-Ling; Lou, Shu-Zon; Wang, Wei-Tsan; Wu, Jui-Yen; Ma, Hui-Ing; Chen, Vincent Chin-Hung

    2016-01-01

    Postural dysfunctions are prevalent in patients with schizophrenia and affect their daily life and ability to work. In addition, sensory functions and sensory integration that are crucial for postural control are also compromised. This study intended to examine how patients with schizophrenia coordinate multiple sensory systems to maintain postural stability in dynamic sensory conditions. Twenty-nine patients with schizophrenia and 32 control subjects were recruited. Postural stability of the participants was examined in six sensory conditions of different level of congruency of multiple sensory information, which was based on combinations of correct, removed, or conflicting sensory inputs from visual, somatosensory, and vestibular systems. The excursion of the center of pressure was measured by posturography. Equilibrium scores were derived to indicate the range of anterior-posterior (AP) postural sway, and sensory ratios were calculated to explore ability to use sensory information to maintain balance. The overall AP postural sway was significantly larger for patients with schizophrenia compared to the controls [patients (69.62±8.99); controls (76.53±7.47); t1,59 = -3.28, pmaintain balance compared to the controls.

  11. Changes in sensory reweighting of proprioceptive information during standing balance with age and disease

    NARCIS (Netherlands)

    Pasma, J.H.; Engelhart, D.; Maier, A.B.; Schouten, A.C.; van der Kooij, H.; Meskers, C.G.M.

    2015-01-01

    With sensory reweighting, reliable sensory information is selected over unreliable information during balance by dynamically combining this information. We used system identification techniques to show the weight and the adaptive process of weight change of proprioceptive information during standing

  12. Resistive Random Access Memory from Materials Development fnd Engineering to Novel Encryption and Neuromorphic Applications

    Science.gov (United States)

    Beckmann, Karsten

    Resistive random access memory (ReRAM or RRAM) is a novel form of non-volatile memory that is expected to play a major role in future computing and memory solutions. It has been shown that the resistance state of ReRAM devices can be precisely tuned by modulating switching voltages, by limiting peak current, and by adjusting the switching pulse properties. This enables the realization of novel applications such as memristive neuromorphic computing and neural network computing. I have developed two processes based on 100 and 300mm wafer platforms to demonstrate functional HfO2 based ReRAM devices. The first process is designed for a rapid materials engineering and device characterization, while the second is an advanced hybrid ReRAM/CMOS combination based on the IBM 65nm 10LPe process technology. The 100mm wafer efforts were used to show impacts of etch processes on ReRAM switching performance and the need for a rigorous structural evaluation of ReRAM devices before starting materials development. After an etch development, a bottom electrode comparison between the inert materials Pt, Ru and W was performed where Ru showed superior results with respect to yield and resilience against environmental impacts such as humidity over a 2-month period. A comparison of amorphous and crystalline devices showed no statistical difference in the performance with respect to random telegraph noise. This demonstrates, that the forming process fundamentally alters the crystallographic structure within and around the filament. The 300mm wafer development efforts were aimed towards implementing ReRAM in the FEOL, combined with CMOS, to yield a seamless process flow of 1 transistor 1 ReRAM structures (1T1R). This technology was customized with custom-developed tungsten metal 1 (M1) and dual tungsten/copper via 1 (V1) structures, within which the ReRAM stack is embedded. The ReRAM itself consists of an inert W bottom electrode, HfO2 based active switching layer, a Ti oxygen scavenger

  13. Integrated annotation and analysis of in situ hybridization images using the ImAnno system: application to the ear and sensory organs of the fetal mouse.

    Science.gov (United States)

    Romand, Raymond; Ripp, Raymond; Poidevin, Laetitia; Boeglin, Marcel; Geffers, Lars; Dollé, Pascal; Poch, Olivier

    2015-01-01

    An in situ hybridization (ISH) study was performed on 2000 murine genes representing around 10% of the protein-coding genes present in the mouse genome using data generated by the EURExpress consortium. This study was carried out in 25 tissues of late gestation embryos (E14.5), with a special emphasis on the developing ear and on five distinct developing sensory organs, including the cochlea, the vestibular receptors, the sensory retina, the olfactory organ, and the vibrissae follicles. The results obtained from an analysis of more than 11,000 micrographs have been integrated in a newly developed knowledgebase, called ImAnno. In addition to managing the multilevel micrograph annotations performed by human experts, ImAnno provides public access to various integrated databases and tools. Thus, it facilitates the analysis of complex ISH gene expression patterns, as well as functional annotation and interaction of gene sets. It also provides direct links to human pathways and diseases. Hierarchical clustering of expression patterns in the 25 tissues revealed three main branches corresponding to tissues with common functions and/or embryonic origins. To illustrate the integrative power of ImAnno, we explored the expression, function and disease traits of the sensory epithelia of the five presumptive sensory organs. The study identified 623 genes (out of 2000) concomitantly expressed in the five embryonic epithelia, among which many (∼12%) were involved in human disorders. Finally, various multilevel interaction networks were characterized, highlighting differential functional enrichments of directly or indirectly interacting genes. These analyses exemplify an under-represention of "sensory" functions in the sensory gene set suggests that E14.5 is a pivotal stage between the developmental stage and the functional phase that will be fully reached only after birth.

  14. Sensory Synergy as Environmental Input Integration

    Directory of Open Access Journals (Sweden)

    Fady eAlnajjar

    2015-01-01

    Full Text Available The development of a method to feed proper environmental inputs back to the central nervous system (CNS remains one of the challenges in achieving natural movement when part of the body is replaced with an artificial device. Muscle synergies are widely accepted as a biologically plausible interpretation of the neural dynamics between the CNS and the muscular system. Yet the sensorineural dynamics of environmental feedback to the CNS has not been investigated in detail. In this study, we address this issue by exploring the concept of sensory synergy. In contrast to muscle synergy, we hypothesize that sensory synergy plays an essential role in integrating the overall environmental inputs to provide low-dimensional information to the CNS. We assume that sensor synergy and muscle synergy communicate using these low-dimensional signals. To examine our hypothesis, we conducted posture control experiments involving lateral disturbance with 9 healthy participants. Proprioceptive information represented by the changes on muscle lengths were estimated by using the musculoskeletal model analysis software SIMM. Changes on muscles lengths were then used to compute sensory synergies. The experimental results indicate that the environmental inputs were translated into the two dimensional signals and used to move the upper limb to the desired position immediately after the lateral disturbance. Participants who showed high skill in posture control were found to be likely to have a strong correlation between sensory and muscle signaling as well as high coordination between the utilized sensory synergies. These results suggest the importance of integrating environmental inputs into suitable low-dimensional signals before providing them to the CNS. This mechanism should be essential when designing the prosthesis’ sensory system to make the controller simpler

  15. Sensory synergy as environmental input integration.

    Science.gov (United States)

    Alnajjar, Fady; Itkonen, Matti; Berenz, Vincent; Tournier, Maxime; Nagai, Chikara; Shimoda, Shingo

    2014-01-01

    The development of a method to feed proper environmental inputs back to the central nervous system (CNS) remains one of the challenges in achieving natural movement when part of the body is replaced with an artificial device. Muscle synergies are widely accepted as a biologically plausible interpretation of the neural dynamics between the CNS and the muscular system. Yet the sensorineural dynamics of environmental feedback to the CNS has not been investigated in detail. In this study, we address this issue by exploring the concept of sensory synergy. In contrast to muscle synergy, we hypothesize that sensory synergy plays an essential role in integrating the overall environmental inputs to provide low-dimensional information to the CNS. We assume that sensor synergy and muscle synergy communicate using these low-dimensional signals. To examine our hypothesis, we conducted posture control experiments involving lateral disturbance with nine healthy participants. Proprioceptive information represented by the changes on muscle lengths were estimated by using the musculoskeletal model analysis software SIMM. Changes on muscles lengths were then used to compute sensory synergies. The experimental results indicate that the environmental inputs were translated into the two dimensional signals and used to move the upper limb to the desired position immediately after the lateral disturbance. Participants who showed high skill in posture control were found to be likely to have a strong correlation between sensory and muscle signaling as well as high coordination between the utilized sensory synergies. These results suggest the importance of integrating environmental inputs into suitable low-dimensional signals before providing them to the CNS. This mechanism should be essential when designing the prosthesis' sensory system to make the controller simpler.

  16. Sensory source strength of used ventilation filters

    DEFF Research Database (Denmark)

    Clausen, Geo; Alm, Ole Martin; Fanger, Povl Ole

    2002-01-01

    A two-year-old filter was placed in a ventilation system recirculating the air in an experimental space. Via glass tubes supplied with a small fan it was possible to extract air upstream and downstream of the filter to an adjacent room. A panel could thus perform sensory assessments of the air fr...

  17. Stochastic resonance in an ensemble of single-electron neuromorphic devices and its application to competitive neural networks

    International Nuclear Information System (INIS)

    Oya, Takahide; Asai, Tetsuya; Amemiya, Yoshihito

    2007-01-01

    Neuromorphic computing based on single-electron circuit technology is gaining prominence because of its massively increased computational efficiency and the increasing relevance of computer technology and nanotechnology [Likharev K, Mayr A, Muckra I, Tuerel O. CrossNets: High-performance neuromorphic architectures for CMOL circuits. Molec Electron III: Ann NY Acad Sci 1006;2003:146-63; Oya T, Schmid A, Asai T, Leblebici Y, Amemiya Y. On the fault tolerance of a clustered single-electron neural network for differential enhancement. IEICE Electron Expr 2;2005:76-80]. The maximum impact of these technologies will be strongly felt when single-electron circuits based on fault- and noise-tolerant neural structures can operate at room temperature. In this paper, inspired by stochastic resonance (SR) in an ensemble of spiking neurons [Collins JJ, Chow CC, Imhoff TT. Stochastic resonance without tuning. Nature 1995;376:236-8], we propose our design of a basic single-electron neural component and report how we examined its statistical results on a network

  18. Compliance-Free, Digital SET and Analog RESET Synaptic Characteristics of Sub-Tantalum Oxide Based Neuromorphic Device.

    Science.gov (United States)

    Abbas, Yawar; Jeon, Yu-Rim; Sokolov, Andrey Sergeevich; Kim, Sohyeon; Ku, Boncheol; Choi, Changhwan

    2018-01-19

    A two terminal semiconducting device like a memristor is indispensable to emulate the function of synapse in the working memory. The analog switching characteristics of memristor play a vital role in the emulation of biological synapses. The application of consecutive voltage sweeps or pulses (action potentials) changes the conductivity of the memristor which is considered as the fundamental cause of the synaptic plasticity. In this study, a neuromorphic device using an in-situ growth of sub-tantalum oxide switching layer is fabricated, which exhibits the digital SET and analog RESET switching with an electroforming process without any compliance current (compliance free). The process of electroforming and SET is observed at the positive sweeps of +2.4 V and +0.86 V, respectively, while multilevel RESET is observed with the consecutive negative sweeps in the range of 0 V to -1.2 V. The movement of oxygen vacancies and gradual change in the anatomy of the filament is attributed to digital SET and analog RESET switching characteristics. For the Ti/Ta 2 O 3-x /Pt neuromorphic device, the Ti top and Pt bottom electrodes are considered as counterparts of the pre-synaptic input terminal and a post-synaptic output terminal, respectively.

  19. A neuromorphic implementation of multiple spike-timing synaptic plasticity rules for large-scale neural networks

    Directory of Open Access Journals (Sweden)

    Runchun Mark Wang

    2015-05-01

    Full Text Available We present a neuromorphic implementation of multiple synaptic plasticity learning rules, which include both Spike Timing Dependent Plasticity (STDP and Spike Timing Dependent Delay Plasticity (STDDP. We present a fully digital implementation as well as a mixed-signal implementation, both of which use a novel dynamic-assignment time-multiplexing approach and support up to 2^26 (64M synaptic plasticity elements. Rather than implementing dedicated synapses for particular types of synaptic plasticity, we implemented a more generic synaptic plasticity adaptor array that is separate from the neurons in the neural network. Each adaptor performs synaptic plasticity according to the arrival times of the pre- and post-synaptic spikes assigned to it, and sends out a weighted and/or delayed pre-synaptic spike to the target synapse in the neural network. This strategy provides great flexibility for building complex large-scale neural networks, as a neural network can be configured for multiple synaptic plasticity rules without changing its structure. We validate the proposed neuromorphic implementations with measurement results and illustrate that the circuits are capable of performing both STDP and STDDP. We argue that it is practical to scale the work presented here up to 2^36 (64G synaptic adaptors on a current high-end FPGA platform.

  20. Neuromorphic infrared focal plane performs sensor fusion on-plane local-contrast-enhancement spatial and temporal filtering

    Science.gov (United States)

    Massie, Mark A.; Woolaway, James T., II; Curzan, Jon P.; McCarley, Paul L.

    1993-08-01

    An infrared focal plane has been simulated, designed and fabricated which mimics the form and function of the vertebrate retina. The `Neuromorphic' focal plane has the capability of performing pixel-based sensor fusion and real-time local contrast enhancement, much like the response of the human eye. The device makes use of an indium antimonide detector array with a 3 - 5 micrometers spectral response, and a switched capacitor resistive network to compute a real-time 2D spatial average. This device permits the summation of other sensor outputs to be combined on-chip with the infrared detections of the focal plane itself. The resulting real-time analog processed information thus represents the combined information of many sensors with the advantage that analog spatial and temporal signal processing is performed at the focal plane. A Gaussian subtraction method is used to produce the pixel output which when displayed produces an image with enhanced edges, representing spatial and temporal derivatives in the scene. The spatial and temporal responses of the device are tunable during operation, permitting the operator to `peak up' the response of the array to spatial and temporally varying signals. Such an array adapts to ambient illumination conditions without loss of detection performance. This paper reviews the Neuromorphic infrared focal plane from initial operational simulations to detailed design characteristics, and concludes with a presentation of preliminary operational data for the device as well as videotaped imagery.

  1. Sensory Science Education

    DEFF Research Database (Denmark)

    Otrel-Cass, Kathrin

    2018-01-01

    little note of the body-mind interactions we have with the material world. Utilizing examples from primary schools, it is argued that a sensory pedagogy in science requires a deliberate sensitization and validation of the senses’ presence and that a sensor pedagogy approach may reveal the unique ways...... in how we all experience the world. Troubling science education pedagogy is therefore also a reconceptualization of who we are and how we make sense of the world and the acceptance that the body-mind is present, imbalanced and complex....

  2. The changing sensory room

    DEFF Research Database (Denmark)

    2018-01-01

    In 2017 the kindergarten The Milky Way in the city Vejle in Denmark made a sensory room that has the special ability change whenever wanted by the children and social educators. Kjetil Sandvik (to the right) from Copenhagen University and Klaus Thestrup from Aarhus University reflects upon what...... they saw, took part in and talked with the social educators about. Jacob Knudsen from VIFIN filmed the two gentlemen and organised the project. it is a room composed around common experiments, many self-made objects, open narrative structures. and a combination of digital and analogue elements....

  3. Feasibility of neuro-morphic computing to emulate error-conflict based decision making.

    Energy Technology Data Exchange (ETDEWEB)

    Branch, Darren W.

    2009-09-01

    A key aspect of decision making is determining when errors or conflicts exist in information and knowing whether to continue or terminate an action. Understanding the error-conflict processing is crucial in order to emulate higher brain functions in hardware and software systems. Specific brain regions, most notably the anterior cingulate cortex (ACC) are known to respond to the presence of conflicts in information by assigning a value to an action. Essentially, this conflict signal triggers strategic adjustments in cognitive control, which serve to prevent further conflict. The most probable mechanism is the ACC reports and discriminates different types of feedback, both positive and negative, that relate to different adaptations. Unique cells called spindle neurons that are primarily found in the ACC (layer Vb) are known to be responsible for cognitive dissonance (disambiguation between alternatives). Thus, the ACC through a specific set of cells likely plays a central role in the ability of humans to make difficult decisions and solve challenging problems in the midst of conflicting information. In addition to dealing with cognitive dissonance, decision making in high consequence scenarios also relies on the integration of multiple sets of information (sensory, reward, emotion, etc.). Thus, a second area of interest for this proposal lies in the corticostriatal networks that serve as an integration region for multiple cognitive inputs. In order to engineer neurological decision making processes in silicon devices, we will determine the key cells, inputs, and outputs of conflict/error detection in the ACC region. The second goal is understand in vitro models of corticostriatal networks and the impact of physical deficits on decision making, specifically in stressful scenarios with conflicting streams of data from multiple inputs. We will elucidate the mechanisms of cognitive data integration in order to implement a future corticostriatal-like network in silicon

  4. SENSORY AND CONSUMER TESTING LABORATORY

    Data.gov (United States)

    Federal Laboratory Consortium — These laboratories conduct a wide range of studies to characterize the sensory properties of and consumer responses to foods, beverages, and other consumer products....

  5. Variable sensory perception in autism.

    Science.gov (United States)

    Haigh, Sarah M

    2018-03-01

    Autism is associated with sensory and cognitive abnormalities. Individuals with autism generally show normal or superior early sensory processing abilities compared to healthy controls, but deficits in complex sensory processing. In the current opinion paper, it will be argued that sensory abnormalities impact cognition by limiting the amount of signal that can be used to interpret and interact with environment. There is a growing body of literature showing that individuals with autism exhibit greater trial-to-trial variability in behavioural and cortical sensory responses. If multiple sensory signals that are highly variable are added together to process more complex sensory stimuli, then this might destabilise later perception and impair cognition. Methods to improve sensory processing have shown improvements in more general cognition. Studies that specifically investigate differences in sensory trial-to-trial variability in autism, and the potential changes in variability before and after treatment, could ascertain if trial-to-trial variability is a good mechanism to target for treatment in autism. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  6. HIV Associated Sensory Neuropathy.

    Science.gov (United States)

    G, Amruth; S, Praveen-Kumar; B, Nataraju; Bs, Nagaraja

    2014-07-01

    In the era of highly active antiretroviral therapy, sensory neuropathies have increased in prevalence. We have documented the frequency and profile of the two most common forms of sensory neuropathies associated with Human Immunodeficiency Virus (HIV) infection and looked into clinicoelectrophysiological correlates to differentiate the two entities. The study population comprised of all consecutive patients detected to be HIV positive and attending the Neurology outpatient department (from March 2011 to March 2012) who were aged ≥ 18 years and were able to give informed consent. The data were collected from the patient records (including CD4 counts and treatment details) and questionnaire based interview with each patient. All patients underwent detailed clinical examination and nerve conduction studies (NCSs). Among the total study population of 50 patients, there were 31 men and 19 women. Thirty two patients were in age range of 21 - 40 years and rest were above 40 years. 25 were on antiretroviral therapy (18 on regimen containing zidovudine; seven on regimen containing stavudine). The mean duration of antiretroviral therapy was 16.6±8.4 months. Low CD4 counts ( 40 years. Subclinical neuropathy was common in those on antiretroviral therapy. Axonal neuropathy was the commonest pattern noted in patients who were receiving antiretroviral therapy and demyelinating neuropathy in patients not on antiretroviral therapy. Surprisingly no significant correlation was found between low CD4 counts and symptomatic neuropathy.

  7. Sex differences in chemosensation: sensory or cognitive?

    Directory of Open Access Journals (Sweden)

    Kathrin eOhla

    2013-09-01

    Full Text Available Although the first sex-dependent differences for chemosensory processing were reported in the scientific literature over 60 years ago, the underlying mechanisms are still unknown. Generally, more pronounced sex-dependent differences are noted with increased task difficulty or with increased levels of intranasal irritation produced by the stimulus. Whether differences between the sexes arise from differences in chemosensory sensitivity of the two intranasal sensory systems involved or from differences in cognitive processing associated with emotional evaluation of the stimulants is still not known. We used simultaneous and complementary measures of electrophysiological (EEG, psychophysiological, and psychological responses to stimuli varying in intranasal irritation and oldorousness to investigate whether sex differences in the processing of intranasal irritation are mediated by varying sensitivity of the involved sensory systems or by differences in cognitive and/or emotional evaluation of the irritants. Women perceived all stimulants more irritating and they exhibited larger amplitudes of the late positive deflection of the event-related potential than men. No significant differences in sensory sensitivity, anxiety and arousal responses could be detected. Our findings suggest that men and women process intranasal irritation differently. Importantly, the differences cannot be explained by variation in sensory sensitivity to irritants, differences in anxiety or differences in physiological arousal. We propose that women allocate attention stronger to potentially noxious stimuli, which eventually causes differences in cognitive appraisal and subjective perception.

  8. Think like a sponge: The genetic signal of sensory cells in sponges.

    Science.gov (United States)

    Mah, Jasmine L; Leys, Sally P

    2017-11-01

    A complex genetic repertoire underlies the apparently simple body plan of sponges. Among the genes present in poriferans are those fundamental to the sensory and nervous systems of other animals. Sponges are dynamic and sensitive animals and it is intuitive to link these genes to behaviour. The proposal that ctenophores are the earliest diverging metazoan has led to the question of whether sponges possess a 'pre-nervous' system or have undergone nervous system loss. Both lines of thought generally assume that the last common ancestor of sponges and eumetazoans possessed the genetic modules that underlie sensory abilities. By corollary extant sponges may possess a sensory cell homologous to one present in the last common ancestor, a hypothesis that has been studied by gene expression. We have performed a meta-analysis of all gene expression studies published to date to explore whether gene expression is indicative of a feature's sensory function. In sponges we find that eumetazoan sensory-neural markers are not particularly expressed in structures with known sensory functions. Instead it is common for these genes to be expressed in cells with no known or uncharacterized sensory function. Indeed, many sensory-neural markers so far studied are expressed during development, perhaps because many are transcription factors. This suggests that the genetic signal of a sponge sensory cell is dissimilar enough to be unrecognizable when compared to a bilaterian sensory or neural cell. It is possible that sensory-neural markers have as yet unknown functions in sponge cells, such as assembling an immunological synapse in the larval globular cell. Furthermore, the expression of sensory-neural markers in non-sensory cells, such as adult and larval epithelial cells, suggest that these cells may have uncharacterized sensory functions. While this does not rule out the co-option of ancestral sensory modules in later evolving groups, a distinct genetic foundation may underlie the

  9. Effect of farming systems on the yield, quality parameters and sensory properties of conventionally and organically grown potato (Solanum tuberosum L.) tubers.

    Science.gov (United States)

    Brazinskiene, V; Asakaviciute, R; Miezeliene, A; Alencikiene, G; Ivanauskas, L; Jakstas, V; Viskelis, P; Razukas, A

    2014-02-15

    The objectives of this two-year research were to study the impact of two different farming types, conventional and organic, on the yield and sensory properties of five Lithuanian varieties of potato tuber. The parameters and properties examined were: phenolic acids; dry matter and starch content; and the spread and intensity of Phytophthora infestans growth. It was determined that potato yield fluctuates with the variety, but for conventional farming it is significantly (p0.05) on the content of phenolic acids. No significant effect (p>0.05) of farming type on dry matter and starch content, or sensory properties was found. No significant relation (p>0.05) was found between the content of phenolic acids and P. infestans spread. The spread of P. infestans was faster and infection was heavier in organically grown potatoes. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. Locomotor sensory organization test: a novel paradigm for the assessment of sensory contributions in gait.

    Science.gov (United States)

    Chien, Jung Hung; Eikema, Diderik-Jan Anthony; Mukherjee, Mukul; Stergiou, Nicholas

    2014-12-01

    Feedback based balance control requires the integration of visual, proprioceptive and vestibular input to detect the body's movement within the environment. When the accuracy of sensory signals is compromised, the system reorganizes the relative contributions through a process of sensory recalibration, for upright postural stability to be maintained. Whereas this process has been studied extensively in standing using the Sensory Organization Test (SOT), less is known about these processes in more dynamic tasks such as locomotion. In the present study, ten healthy young adults performed the six conditions of the traditional SOT to quantify standing postural control when exposed to sensory conflict. The same subjects performed these six conditions using a novel experimental paradigm, the Locomotor SOT (LSOT), to study dynamic postural control during walking under similar types of sensory conflict. To quantify postural control during walking, the net Center of Pressure sway variability was used. This corresponds to the Performance Index of the center of pressure trajectory, which is used to quantify postural control during standing. Our results indicate that dynamic balance control during locomotion in healthy individuals is affected by the systematic manipulation of multisensory inputs. The sway variability patterns observed during locomotion reflect similar balance performance with standing posture, indicating that similar feedback processes may be involved. However, the contribution of visual input is significantly increased during locomotion, compared to standing in similar sensory conflict conditions. The increased visual gain in the LSOT conditions reflects the importance of visual input for the control of locomotion. Since balance perturbations tend to occur in dynamic tasks and in response to environmental constraints not present during the SOT, the LSOT may provide additional information for clinical evaluation on healthy and deficient sensory processing.

  11. Sensory adaptation for timing perception.

    Science.gov (United States)

    Roseboom, Warrick; Linares, Daniel; Nishida, Shin'ya

    2015-04-22

    Recent sensory experience modifies subjective timing perception. For example, when visual events repeatedly lead auditory events, such as when the sound and video tracks of a movie are out of sync, subsequent vision-leads-audio presentations are reported as more simultaneous. This phenomenon could provide insights into the fundamental problem of how timing is represented in the brain, but the underlying mechanisms are poorly understood. Here, we show that the effect of recent experience on timing perception is not just subjective; recent sensory experience also modifies relative timing discrimination. This result indicates that recent sensory history alters the encoding of relative timing in sensory areas, excluding explanations of the subjective phenomenon based only on decision-level changes. The pattern of changes in timing discrimination suggests the existence of two sensory components, similar to those previously reported for visual spatial attributes: a lateral shift in the nonlinear transducer that maps relative timing into perceptual relative timing and an increase in transducer slope around the exposed timing. The existence of these components would suggest that previous explanations of how recent experience may change the sensory encoding of timing, such as changes in sensory latencies or simple implementations of neural population codes, cannot account for the effect of sensory adaptation on timing perception.

  12. Sensory characteristics of camphor.

    Science.gov (United States)

    Green, B G

    1990-05-01

    The perceptual effects of camphor on hairy skin were measured in a psychophysical experiment. Subjects rated the intensity and quality of sensations produced when a solution of 20% camphor (in a vehicle of ethanol and deionized H2O) was applied topically to the volar forearm. Under conditions in which skin temperature was varied either from 33-43 degrees C or from 33-18 degrees C, it was found that camphor increased the perceived intensity of the cutaneous sensations produced during heating and cooling. Although camphor's effect appeared to be greater during warming, neither effect was large. Camphor also produced a significant increase in the frequency of reports of "burning." It is concluded that camphor is a relatively weak sensory irritant that may have a modest excitatory effect on thermosensitive (and perhaps nociceptive) cutaneous fibers.

  13. The Sensory Neocortex and Associative Memory.

    Science.gov (United States)

    Aschauer, Dominik; Rumpel, Simon

    2018-01-01

    Most behaviors in mammals are directly or indirectly guided by prior experience and therefore depend on the ability of our brains to form memories. The ability to form an association between an initially possibly neutral sensory stimulus and its behavioral relevance is essential for our ability to navigate in a changing environment. The formation of a memory is a complex process involving many areas of the brain. In this chapter we review classic and recent work that has shed light on the specific contribution of sensory cortical areas to the formation of associative memories. We discuss synaptic and circuit mechanisms that mediate plastic adaptations of functional properties in individual neurons as well as larger neuronal populations forming topographically organized representations. Furthermore, we describe commonly used behavioral paradigms that are used to study the mechanisms of memory formation. We focus on the auditory modality that is receiving increasing attention for the study of associative memory in rodent model systems. We argue that sensory cortical areas may play an important role for the memory-dependent categorical recognition of previously encountered sensory stimuli.

  14. Minimizing the effect of process mismatch in a neuromorphic system using spike-timing-dependent adaptation.

    Science.gov (United States)

    Cameron, Katherine; Murray, Alan

    2008-05-01

    This paper investigates whether spike-timing-dependent plasticity (STDP) can minimize the effect of mismatch within the context of a depth-from-motion algorithm. To improve noise rejection, this algorithm contains a spike prediction element, whose performance is degraded by analog very large scale integration (VLSI) mismatch. The error between the actual spike arrival time and the prediction is used as the input to an STDP circuit, to improve future predictions. Before STDP adaptation, the error reflects the degree of mismatch within the prediction circuitry. After STDP adaptation, the error indicates to what extent the adaptive circuitry can minimize the effect of transistor mismatch. The circuitry is tested with static and varying prediction times and chip results are presented. The effect of noisy spikes is also investigated. Under all conditions the STDP adaptation is shown to improve performance.

  15. Low-power, ultra-fast deep learning neuromorphic chip for unmanned aircraft systems, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Artificial Intelligence (AI) is driving the fourth industrial revolution as well as permeating every aspect of our day-to-day life. From big data analysis to...

  16. Tic Modulation Using Sensory Tricks

    Directory of Open Access Journals (Sweden)

    Rebecca W. Gilbert

    2013-04-01

    Full Text Available Background: A sensory trick, or geste antagoniste, is defined as a physical gesture (such as a touch on a particular body part that mitigates the production of an involuntary movement. This phenomenon is most commonly described as a feature of dystonia. Here we present a case of successful modulation of tics using sensory tricks.Case Report:: A case report and video are presented. The case and video demonstrate a 19-year-old male who successfully controlled his tics with various sensory tricks.Discussion: It is underappreciated by movement disorder physicians that sensory tricks can play a role in tics. Introducing this concept to patients could potentially help in tic control. In addition, understanding the pathophysiological underpinnings of sensory tricks could help in the understanding of the pathophysiology of tics.

  17. Sensory analysis of pet foods.

    Science.gov (United States)

    Koppel, Kadri

    2014-08-01

    Pet food palatability depends first and foremost on the pet and is related to the pet food sensory properties such as aroma, texture and flavor. Sensory analysis of pet foods may be conducted by humans via descriptive or hedonic analysis, pets via acceptance or preference tests, and through a number of instrumental analysis methods. Sensory analysis of pet foods provides additional information on reasons behind palatable and unpalatable foods as pets lack linguistic capabilities. Furthermore, sensory analysis may be combined with other types of information such as personality and environment factors to increase understanding of acceptable pet foods. Most pet food flavor research is proprietary and, thus, there are a limited number of publications available. Funding opportunities for pet food studies would increase research and publications and this would help raise public awareness of pet food related issues. This mini-review addresses current pet food sensory analysis literature and discusses future challenges and possibilities. © 2014 Society of Chemical Industry.

  18. Diverse spike-timing-dependent plasticity based on multilevel HfO x memristor for neuromorphic computing

    Science.gov (United States)

    Lu, Ke; Li, Yi; He, Wei-Fan; Chen, Jia; Zhou, Ya-Xiong; Duan, Nian; Jin, Miao-Miao; Gu, Wei; Xue, Kan-Hao; Sun, Hua-Jun; Miao, Xiang-Shui

    2018-06-01

    Memristors have emerged as promising candidates for artificial synaptic devices, serving as the building block of brain-inspired neuromorphic computing. In this letter, we developed a Pt/HfO x /Ti memristor with nonvolatile multilevel resistive switching behaviors due to the evolution of the conductive filaments and the variation in the Schottky barrier. Diverse state-dependent spike-timing-dependent-plasticity (STDP) functions were implemented with different initial resistance states. The measured STDP forms were adopted as the learning rule for a three-layer spiking neural network which achieves a 75.74% recognition accuracy for MNIST handwritten digit dataset. This work has shown the capability of memristive synapse in spiking neural networks for pattern recognition application.

  19. Uranium-induced sensory alterations in the zebrafish Danio rerio

    Energy Technology Data Exchange (ETDEWEB)

    Faucher, K., E-mail: kfaucher@hotmail.fr [Laboratoire d' ecotoxicologie des radionucleides (LECO), Institut de Radioprotection et Surete Nucleaire, Centre de Cadarache, Batiment 186, BP3, 13115 Saint Paul lez Durance (France); Floriani, M.; Gilbin, R.; Adam-Guillermin, C. [Laboratoire d' ecotoxicologie des radionucleides (LECO), Institut de Radioprotection et Surete Nucleaire, Centre de Cadarache, Batiment 186, BP3, 13115 Saint Paul lez Durance (France)

    2012-11-15

    The effect of chronic exposure to uranium ions (UO{sub 2}{sup 2+}) on sensory tissues including the olfactory and lateral line systems was investigated in zebrafish (Danio rerio) using scanning electron microscopy. The aim of this study was to determine whether exposure to uranium damaged sensory tissues in fish. The fish were exposed to uranium at the concentration of 250 {mu}g l{sup -1} for 10 days followed by a depuration period of 23 days. Measurements of uranium uptake in different fish organs: olfactory rosettes and bulbs, brain, skin, and muscles, were also determined by ICP-AES and ICP-MS during the entire experimental period. The results showed that uranium displayed a strong affinity for sensory structures in direct contact with the surrounding medium, such as the olfactory and lateral line systems distributed on the skin. A decreasing gradient of uranium concentration was found: olfactory rosettes > olfactory bulbs > skin > muscles > brain. At the end of the experiment, uranium was present in non-negligible quantities in sensory tissues. In parallel, fish exposed to uranium showed severe sensory tissue alterations at the level of the olfactory and lateral line systems. In both sensory systems, the gross morphology was altered and the sensory hair cells were significantly damaged very early after the initiation of exposure (from the 3rd day). At the end of the experiment, after 23 days of depuration, the lateral line system still displayed slight tissue alterations, but approximately 80% of the neuromasts in this system had regenerated. In contrast, the olfactory system took more time to recover, as more than half of the olfactory rosettes observed remained destroyed at the end of the experiment. This study showed, for the first time, that uranium is able to damage fish sensory tissues to such an extent that tissue regeneration is delayed.

  20. Sensory optimization by stochastic tuning.

    Science.gov (United States)

    Jurica, Peter; Gepshtein, Sergei; Tyukin, Ivan; van Leeuwen, Cees

    2013-10-01

    Individually, visual neurons are each selective for several aspects of stimulation, such as stimulus location, frequency content, and speed. Collectively, the neurons implement the visual system's preferential sensitivity to some stimuli over others, manifested in behavioral sensitivity functions. We ask how the individual neurons are coordinated to optimize visual sensitivity. We model synaptic plasticity in a generic neural circuit and find that stochastic changes in strengths of synaptic connections entail fluctuations in parameters of neural receptive fields. The fluctuations correlate with uncertainty of sensory measurement in individual neurons: The higher the uncertainty the larger the amplitude of fluctuation. We show that this simple relationship is sufficient for the stochastic fluctuations to steer sensitivities of neurons toward a characteristic distribution, from which follows a sensitivity function observed in human psychophysics and which is predicted by a theory of optimal allocation of receptive fields. The optimal allocation arises in our simulations without supervision or feedback about system performance and independently of coupling between neurons, making the system highly adaptive and sensitive to prevailing stimulation. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  1. Behavioral guides for sensory neurophysiology.

    Science.gov (United States)

    Konishi, M

    2006-06-01

    The study of natural behavior is important for understanding the coding schemes of sensory systems. The jamming avoidance response of the weakly electric fish Eigenmannia is an excellent example of a bottom-up approach, in which behavioral analyses guided neurophysiological studies. These studies started from the electroreceptive sense organs to the motor output consisting of pacemaker neurons. Going in the opposite direction, from the central nervous system to lower centers, is the characteristic of the top-down approach. Although this approach is perhaps more difficult than the bottom-up approach, it was successfully employed in the neuroethological analysis of sound localization in the barn owl. In the latter studies, high-order neurons selective for complex natural stimuli led to the discovery of neural pathways and networks responsible for the genesis of the stimulus selectivity. Comparison of Eigenmannia and barn owls, and their neural systems, has revealed similarities in network designs, such as parallel pathways and their convergence to produce stimulus selectivity necessary for detection of natural stimuli.

  2. Odor-evoked inhibition of olfactory sensory neurons drives olfactory perception in Drosophila.

    Science.gov (United States)

    Cao, Li-Hui; Yang, Dong; Wu, Wei; Zeng, Xiankun; Jing, Bi-Yang; Li, Meng-Tong; Qin, Shanshan; Tang, Chao; Tu, Yuhai; Luo, Dong-Gen

    2017-11-07

    Inhibitory response occurs throughout the nervous system, including the peripheral olfactory system. While odor-evoked excitation in peripheral olfactory cells is known to encode odor information, the molecular mechanism and functional roles of odor-evoked inhibition remain largely unknown. Here, we examined Drosophila olfactory sensory neurons and found that inhibitory odors triggered outward receptor currents by reducing the constitutive activities of odorant receptors, inhibiting the basal spike firing in olfactory sensory neurons. Remarkably, this odor-evoked inhibition of olfactory sensory neurons elicited by itself a full range of olfactory behaviors from attraction to avoidance, as did odor-evoked olfactory sensory neuron excitation. These results indicated that peripheral inhibition is comparable to excitation in encoding sensory signals rather than merely regulating excitation. Furthermore, we demonstrated that a bidirectional code with both odor-evoked inhibition and excitation in single olfactory sensory neurons increases the odor-coding capacity, providing a means of efficient sensory encoding.

  3. Brief electrical stimulation accelerates axon regeneration in the peripheral nervous system and promotes sensory axon regeneration in the central nervous system.

    Science.gov (United States)

    Gordon, Tessa; Udina, Esther; Verge, Valerie M K; de Chaves, Elena I Posse

    2009-10-01

    Injured peripheral but not central nerves regenerate their axons but functional recovery is often poor. We demonstrate that prolonged periods of axon separation from targets and Schwann cell denervation eliminate regenerative capacity in the peripheral nervous system (PNS). A substantial delay of 4 weeks for all regenerating axons to cross a site of repair of sectioned nerve contributes to the long period of separation. Findings that 1h 20Hz bipolar electrical stimulation accelerates axon outgrowth across the repair site and the downstream reinnervation of denervated muscles in rats and human patients, provides a new and exciting method to improve functional recovery after nerve injuries. Drugs that elevate neuronal cAMP and activate PKA promote axon outgrowth in vivo and in vitro, mimicking the electrical stimulation effect. Rapid expression of neurotrophic factors and their receptors and then of growth associated proteins thereafter via cAMP, is the likely mechanism by which electrical stimulation accelerates axon outgrowth from the site of injury in both peripheral and central nervous systems.

  4. Parasympathetic functions in children with sensory processing disorder

    Directory of Open Access Journals (Sweden)

    Roseann C Schaaf

    2010-03-01

    Full Text Available The overall goal of this study was to determine if Parasympathetic Nervous System Activity (PsNS is a significant biomarker of sensory processing difficulties in children. Several studies have demonstrated that PsNS activity is an important regulator of reactivity in children, and thus, it is of interest to study whether PsNS functioning affects sensory reactivity in children who have a type of condition associated with Sensory Processing Disorders (SPD termed Sensory Modulation Dysfunction (SMD. If so, this will have important implications for understanding the mechanisms underlying sensory processing problems of children. The primary aims of this project were to: (1 evaluate PsNS activity in children with SMD compared to typically developing (TYP children, and (2 determine if PsNS activity is a significant predictor of sensory behaviors and adaptive functions among children with SMD. As a secondary aim we examined whether subgroups of children with specific physiological and behavioral sensory reactivity profiles can be identified. Results indicate that the children with severe SMD demonstrated a trend for low baseline parasympathetic activity, compared to TYP children, suggesting this may be a biomarker for severe SMD. In addition, children with SMD demonstrated significantly poorer adaptive behavior. These results provide preliminary evidence that children who demonstrate SMD may have physiological responses that are different from children without SMD, and that these physiological and behavioral manifestations of SMD may affect a child’s ability to engage in everyday social, communication, and daily living skills.

  5. Anterograde transneuronal viral tract tracing reveals central sensory circuits from brown fat and sensory denervation alters its thermogenic responses.

    Science.gov (United States)

    Vaughan, Cheryl H; Bartness, Timothy J

    2012-05-01

    Brown adipose tissue (BAT) thermogenic activity and growth are controlled by its sympathetic nervous system (SNS) innervation, but nerve fibers containing sensory-associated neuropeptides [substance P, calcitonin gene-related peptide (CGRP)] also suggest sensory innervation. The central nervous system (CNS) projections of BAT afferents are unknown. Therefore, we used the H129 strain of the herpes simplex virus-1 (HSV-1), an anterograde transneuronal viral tract tracer used to delineate sensory nerve circuits, to define these projections. HSV-1 was injected into interscapular BAT (IBAT) of Siberian hamsters and HSV-1 immunoreactivity (ir) was assessed 24, 48, 72, 96, and 114 h postinjection. The 96- and 114-h groups had the most HSV-1-ir neurons with marked infections in the hypothalamic paraventricular nucleus, periaqueductal gray, olivary areas, parabrachial nuclei, raphe nuclei, and reticular areas. These sites also are involved in sympathetic outflow to BAT suggesting possible BAT sensory-SNS thermogenesis feedback circuits. We tested the functional contribution of IBAT sensory innervation on thermogenic responses to an acute (24 h) cold exposure test by injecting the specific sensory nerve toxin capsaicin directly into IBAT pads and then measuring core (T(c)) and IBAT (T(IBAT)) temperature responses. CGRP content was significantly decreased in capsaicin-treated IBAT demonstrating successful sensory nerve destruction. T(IBAT) and T(c) were significantly decreased in capsaicin-treated hamsters compared with the saline controls at 2 h of cold exposure. Thus the central sensory circuits from IBAT have been delineated for the first time, and impairment of sensory feedback from BAT appears necessary for the appropriate, initial thermogenic response to acute cold exposure.

  6. Analyzing sensory data with R

    CERN Document Server

    Le, Sebastien

    2014-01-01

    Quantitative Descriptive Approaches When panelists rate products according to one single list of attributes Data, sensory issues, notations In practice For experienced users: Measuring the impact of the experimental design on the perception of the products? When products are rated according to one single list of attributesData, sensory issues, notations In practice For experienced users: Adding supplementary information to the product space When products are rated according to several lists

  7. Sensory Dissonance Using Memory Model

    DEFF Research Database (Denmark)

    Jensen, Karl Kristoffer

    2015-01-01

    Music may occur concurrently or in temporal sequences. Current machine-based methods for the estimation of qualities of the music are unable to take into account the influence of temporal context. A method for calculating dissonance from audio, called sensory dissonance is improved by the use of ...... of a memory model. This approach is validated here by the comparison of the sensory dissonance using memory model to data obtained using human subjects....

  8. Neuroimaging of multimodal sensory stimulation in Amyotrophic Lateral Sclerosis (ALS)

    OpenAIRE

    Lulé , Dorothée; Diekmann , Volker; Müller , Hans-Peter; Kassubek , Jan; Ludolph , Albert C; Birbaumer , Niels

    2010-01-01

    Abstract Aim: Structural and functional imaging techniques were combined to investigate sensory system function in amyotrophic lateral sclerosis (ALS). Methods: Functional magnetic resonance imaging (fMRI) was used to investigate cortical activity during visual, auditory, and somato-sensory stimulation in fourteen ALS patients and eighteen control subjects. Changes in amplitude, latency and duration of the BOLD response were modelled. Furthermore, diffusion tensor imaging was ...

  9. Approximate Sensory Data Collection: A Survey.

    Science.gov (United States)

    Cheng, Siyao; Cai, Zhipeng; Li, Jianzhong

    2017-03-10

    With the rapid development of the Internet of Things (IoTs), wireless sensor networks (WSNs) and related techniques, the amount of sensory data manifests an explosive growth. In some applications of IoTs and WSNs, the size of sensory data has already exceeded several petabytes annually, which brings too many troubles and challenges for the data collection, which is a primary operation in IoTs and WSNs. Since the exact data collection is not affordable for many WSN and IoT systems due to the limitations on bandwidth and energy, many approximate data collection algorithms have been proposed in the last decade. This survey reviews the state of the art of approximatedatacollectionalgorithms. Weclassifythemintothreecategories: themodel-basedones, the compressive sensing based ones, and the query-driven ones. For each category of algorithms, the advantages and disadvantages are elaborated, some challenges and unsolved problems are pointed out, and the research prospects are forecasted.

  10. Approximate Sensory Data Collection: A Survey

    Directory of Open Access Journals (Sweden)

    Siyao Cheng

    2017-03-01

    Full Text Available With the rapid development of the Internet of Things (IoTs, wireless sensor networks (WSNs and related techniques, the amount of sensory data manifests an explosive growth. In some applications of IoTs and WSNs, the size of sensory data has already exceeded several petabytes annually, which brings too many troubles and challenges for the data collection, which is a primary operation in IoTs and WSNs. Since the exact data collection is not affordable for many WSN and IoT systems due to the limitations on bandwidth and energy, many approximate data collection algorithms have been proposed in the last decade. This survey reviews the state of the art of approximatedatacollectionalgorithms. Weclassifythemintothreecategories: themodel-basedones, the compressive sensing based ones, and the query-driven ones. For each category of algorithms, the advantages and disadvantages are elaborated, some challenges and unsolved problems are pointed out, and the research prospects are forecasted.

  11. Overlapping structures in sensory-motor mappings.

    Directory of Open Access Journals (Sweden)

    Kevin Earland

    Full Text Available This paper examines a biologically-inspired representation technique designed for the support of sensory-motor learning in developmental robotics. An interesting feature of the many topographic neural sheets in the brain is that closely packed receptive fields must overlap in order to fully cover a spatial region. This raises interesting scientific questions with engineering implications: e.g. is overlap detrimental? does it have any benefits? This paper examines the effects and properties of overlap between elements arranged in arrays or maps. In particular we investigate how overlap affects the representation and transmission of spatial location information on and between topographic maps. Through a series of experiments we determine the conditions under which overlap offers advantages and identify useful ranges of overlap for building mappings in cognitive robotic systems. Our motivation is to understand the phenomena of overlap in order to provide guidance for application in sensory-motor learning robots.

  12. The Significance of Memory in Sensory Cortex.

    Science.gov (United States)

    Muckli, Lars; Petro, Lucy S

    2017-05-01

    Early sensory cortex is typically investigated in response to sensory stimulation, masking the contribution of internal signals. Recently, van Kerkoerle and colleagues reported that attention and memory signals segregate from sensory signals within specific layers of primary visual cortex, providing insight into the role of internal signals in sensory processing. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  13. The significance of memory in sensory cortex

    OpenAIRE

    Muckli, Lars; Petro, Lucy S.

    2017-01-01

    Early sensory cortex is typically investigated in response to sensory stimulation, masking the contribution of internal signals. Recently, van Kerkoerle and colleagues reported that attention and memory signals segregate from sensory signals within specific layers of primary visual cortex, providing insight into the role of internal signals in sensory processing.

  14. Expressing exogenous functional odorant receptors in cultured olfactory sensory neurons

    Directory of Open Access Journals (Sweden)

    Fomina Alla F

    2008-09-01

    Full Text Available Abstract Background Olfactory discrimination depends on the large numbers of odorant receptor genes and differential ligand-receptor signaling among neurons expressing different receptors. In this study, we describe an in vitro system that enables the expression of exogenous odorant receptors in cultured olfactory sensory neurons. Olfactory sensory neurons in the culture express characteristic signaling molecules and, therefore, provide a system to study receptor function within its intrinsic cellular environment. Results We demonstrate that cultured olfactory sensory neurons express endogenous odorant receptors. Lentiviral vector-mediated gene transfer enables successful ectopic expression of odorant receptors. We show that the ectopically expressed mouse I7 is functional in the cultured olfactory sensory neurons. When two different odorant receptors are ectopically expressed simultaneously, both receptor proteins co-localized in the same olfactory sensory neurons up to 10 days in vitro. Conclusion This culture technique provided an efficient method to culture olfactory sensory neurons whose morphology, molecular characteristics and maturation progression resembled those observed in vivo. Using this system, regulation of odorant receptor expression and its ligand specificity can be studied in its intrinsic cellular environment.

  15. Sensory Integration with Articulated Motion on a Humanoid Robot

    Directory of Open Access Journals (Sweden)

    J. Rojas

    2005-01-01

    Full Text Available This paper describes the integration of articulated motion with auditory and visual sensory information that enables a humanoid robot to achieve certain reflex actions that mimic those of people. Reflexes such as reach-and-grasp behavior enables the robot to learn, through experience, its own state and that of the world. A humanoid robot with binaural audio input, stereo vision, and pneumatic arms and hands exhibited tightly coupled sensory-motor behaviors in four different demonstrations. The complexity of successive demonstrations was increased to show that the reflexive sensory-motor behaviors combine to perform increasingly complex tasks. The humanoid robot executed these tasks effectively and established the groundwork for the further development of hardware and software systems, sensory-motor vector-space representations, and coupling with higher-level cognition.

  16. Sensory Hair Cells: An Introduction to Structure and Physiology.

    Science.gov (United States)

    McPherson, Duane R

    2018-06-18

    Sensory hair cells are specialized secondary sensory cells that mediate our senses of hearing, balance, linear acceleration, and angular acceleration (head rotation). In addition, hair cells in fish and amphibians mediate sensitivity to water movement through the lateral line system, and closely related electroreceptive cells mediate sensitivity to low-voltage electric fields in the aquatic environment of many fish species and several species of amphibian.Sensory hair cells share many structural and functional features across all vertebrate groups, while at the same time they are specialized for employment in a wide variety of sensory tasks. The complexity of hair cell structure is large, and the diversity of hair cell applications in sensory systems exceeds that seen for most, if not all, sensory cell types. The intent of this review is to summarize the more significant structural features and some of the more interesting and important physiological mechanisms that have been elucidated thus far. Outside vertebrates, hair cells are only known to exist in the coronal organ of tunicates. Electrical resonance, electromotility, and their exquisite mechanical sensitivity all contribute to the attractiveness of hair cells as a research subject.

  17. Focal Dystonia and the Sensory-Motor Integrative Loop for Enacting (SMILE)

    OpenAIRE

    David ePerruchoud; Micah M Murray; Micah M Murray; Jeremie eLefebvre; Silvio eIonta

    2014-01-01

    Performing accurate movements requires preparation, execution, and monitoring mechanisms. The first two are coded by the motor system, and the latter by the sensory system. To provide an adaptive neural basis to overt behaviors, motor and sensory information has to be properly integrated in a reciprocal feedback loop. Abnormalities in this sensory-motor loop are involved in movement disorders such as focal dystonia, a hyperkinetic alteration affecting only a specific body part and characteriz...

  18. Focal dystonia and the Sensory-Motor Integrative Loop for Enacting (SMILE)

    OpenAIRE

    Perruchoud David; Murray Micah; Lefebvre Jeremie; Ionta Silvio

    2014-01-01

    Performing accurate movements requires preparation, execution, and monitoring mechanisms. The first two are coded by the motor system, the latter by the sensory system. To provide an adaptive neural basis to overt behaviors, motor and sensory information has to be properly integrated in a reciprocal feedback loop. Abnormalities in this sensory-motor loop are involved in movement disorders such as focal dystonia, a hyperkinetic alteration affecting only a specific body part and characterized b...

  19. Designing sensory-substitution devices: Principles, pitfalls and potential1.

    Science.gov (United States)

    Kristjánsson, Árni; Moldoveanu, Alin; Jóhannesson, Ómar I; Balan, Oana; Spagnol, Simone; Valgeirsdóttir, Vigdís Vala; Unnthorsson, Rúnar

    2016-09-21

    An exciting possibility for compensating for loss of sensory function is to augment deficient senses by conveying missing information through an intact sense. Here we present an overview of techniques that have been developed for sensory substitution (SS) for the blind, through both touch and audition, with special emphasis on the importance of training for the use of such devices, while highlighting potential pitfalls in their design. One example of a pitfall is how conveying extra information about the environment risks sensory overload. Related to this, the limits of attentional capacity make it important to focus on key information and avoid redundancies. Also, differences in processing characteristics and bandwidth between sensory systems severely constrain the information that can be conveyed. Furthermore, perception is a continuous process and does not involve a snapshot of the environment. Design of sensory substitution devices therefore requires assessment of the nature of spatiotemporal continuity for the different senses. Basic psychophysical and neuroscientific research into representations of the environment and the most effective ways of conveying information should lead to better design of sensory substitution systems. Sensory substitution devices should emphasize usability, and should not interfere with other inter- or intramodal perceptual function. Devices should be task-focused since in many cases it may be impractical to convey too many aspects of the environment. Evidence for multisensory integration in the representation of the environment suggests that researchers should not limit themselves to a single modality in their design. Finally, we recommend active training on devices, especially since it allows for externalization, where proximal sensory stimulation is attributed to a distinct exterior object.

  20. Influence of Sensory Dependence on Postural Control

    Science.gov (United States)

    Santana, Patricia A.; Mulavara, Ajitkumar P.; Fiedler, Matthew J.

    2011-01-01

    The current project is part of an NSBRI funded project, "Development of Countermeasures to Aid Functional Egress from the Crew Exploration Vehicle Following Long-Duration Spaceflight." The development of this countermeasure is based on the use of imperceptible levels of electrical stimulation to the balance organs of the inner ear to assist and enhance the response of a person s sensorimotor function. These countermeasures could be used to increase an astronaut s re-adaptation rate to Earth s gravity following long-duration space flight. The focus of my project is to evaluate and examine the correlation of sensory preferences for vision and vestibular systems. Disruption of the sensorimotor functions following space flight affects posture, locomotion and spatial orientation tasks in astronauts. The Group Embedded Figures Test (GEFT), the Rod and Frame Test (RFT) and the Computerized Dynamic Posturography Test (CDP) are measurements used to examine subjects visual and vestibular sensory preferences. The analysis of data from these tasks will assist in relating the visual dependence measures recognized in the GEFT and RFT with vestibular dependence measures recognized in the stability measures obtained during CDP. Studying the impact of sensory dependence on the performance in varied tasks will help in the development of targeted countermeasures to help astronauts readapt to gravitational changes after long duration space flight.

  1. Motor and sensory alalia: diagnostic difficulties

    Directory of Open Access Journals (Sweden)

    M. Yu. Bobylova

    2017-01-01

    Full Text Available Alalia is a speech disorder that develops due to organic brain damage in children with normal hearing and intelligence during the first three year of life. Systemic speech underdevelopment in alalia is characterized by violations in the phonetic, phonemic, lexical, and grammatical structure. Patients with alalia can also have non-speech related impairments, including motor (impaired movement and coordination, sensory (impaired sensitivity and perception, and psychopathological disorders. There are three types of alalia: motor, sensory, and mixed. Children with motor alalia have expressive language disorders, speech praxis, poor speech fluency, impaired articulation, and other focal neurological symptoms; however, they understand speech directed to them. Patients with motor alalia are often left-handed. Regional slowing and epileptiform activity are often detected on their electroencephalogram.  Children with sensory alalia are characterized by poor speech understanding (despite normal hearing resulting in secondary underdevelopment of their own speech. These patients have problems with the analysis of sounds, including speech sounds (impaired speech gnosis, which prevents the development of association between the sound image and the object. Therefore, the child hears, but does not understand the speech directed at him/her (auditory agnosia. Differential diagnosis of alalia is challenging and may require several months of observation. It also implies the exclusion of hearing loss and mental disorders.

  2. Sensory Alterations in Patients with Isolated Idiopathic Dystonia: An Exploratory Quantitative Sensory Testing Analysis.

    Science.gov (United States)

    Paracka, Lejla; Wegner, Florian; Blahak, Christian; Abdallat, Mahmoud; Saryyeva, Assel; Dressler, Dirk; Karst, Matthias; Krauss, Joachim K

    2017-01-01

    Abnormalities in the somatosensory system are increasingly being recognized in patients with dystonia. The aim of this study was to investigate whether sensory abnormalities are confined to the dystonic body segments or whether there is a wider involvement in patients with idiopathic dystonia. For this purpose, we recruited 20 patients, 8 had generalized, 5 had segmental dystonia with upper extremity involvement, and 7 had cervical dystonia. In total, there were 13 patients with upper extremity involvement. We used Quantitative Sensory Testing (QST) at the back of the hand in all patients and at the shoulder in patients with cervical dystonia. The main finding on the hand QST was impaired cold detection threshold (CDT), dynamic mechanical allodynia (DMA), and thermal sensory limen (TSL). The alterations were present on both hands, but more pronounced on the side more affected with dystonia. Patients with cervical dystonia showed a reduced CDT and hot detection threshold (HDT), enhanced TSL and DMA at the back of the hand, whereas the shoulder QST only revealed increased cold pain threshold and DMA. In summary, QST clearly shows distinct sensory abnormalities in patients with idiopathic dystonia, which may also manifest in body regions without evident dystonia. Further studies with larger groups of dystonia patients are needed to prove the consistency of these findings.

  3. Memristors and memristive systems

    CERN Document Server

    2014-01-01

    This book provides a comprehensive overview of current research on memristors, memcapacitors and, meminductors. In addition to an historical overview of the research in this area, coverage includes the theory behind memristive circuits, as well as memcapacitance, and meminductance.  Details are shown for recent applications of memristors for resistive random access memories, neuromorphic systems and hybrid CMOS/memristor circuits. Methods for the simulation of memristors are demonstrated and an introduction to neuromorphic modeling is provided. ·         Provides a single-source reference to the state of the art in memristor research; ·         Explains the theory of memristors and memristive networks; ·         Demonstrates a variety of memristor realizations with focus on resistive random access memories; ·         Enables readers to use neuromorphic modeling to understand complex phenomena in biological systems.

  4. Sensory overload: A concept analysis.

    Science.gov (United States)

    Scheydt, Stefan; Müller Staub, Maria; Frauenfelder, Fritz; Nielsen, Gunnar H; Behrens, Johann; Needham, Ian

    2017-04-01

    In the context of mental disorders sensory overload is a widely described phenomenon used in conjunction with psychiatric interventions such as removal from stimuli. However, the theoretical foundation of sensory overload as addressed in the literature can be described as insufficient and fragmentary. To date, the concept of sensory overload has not yet been sufficiently specified or analyzed. The aim of the study was to analyze the concept of sensory overload in mental health care. A literature search was undertaken using specific electronic databases, specific journals and websites, hand searches, specific library catalogues, and electronic publishing databases. Walker and Avant's method of concept analysis was used to analyze the sources included in the analysis. All aspects of the method of Walker and Avant were covered in this concept analysis. The conceptual understanding has become more focused, the defining attributes, influencing factors and consequences are described and empirical referents identified. The concept analysis is a first step in the development of a middle-range descriptive theory of sensory overload based on social scientific and stress-theoretical approaches. This specification may serve as a fundament for further research, for the development of a nursing diagnosis or for guidelines. © 2017 Australian College of Mental Health Nurses Inc.

  5. The beauty of sensory ecology.

    Science.gov (United States)

    Otálora-Luna, Fernando; Aldana, Elis

    2017-08-10

    Sensory ecology is a discipline that focuses on how living creatures use information to survive, but not to live. By trans-defining the orthodox concept of sensory ecology, a serious heterodox question arises: how do organisms use their senses to live, i.e. to enjoy or suffer life? To respond to such a query the objective (time-independent) and emotional (non-rational) meaning of symbols must be revealed. Our program is distinct from both the neo-Darwinian and the classical ecological perspective because it does not focus on survival values of phenotypes and their functions, but asks for the aesthetic effect of biological structures and their symbolism. Our message recognizes that sensing apart from having a survival value also has a beauty value. Thus, we offer a provoking and inspiring new view on the sensory relations of 'living things' and their surroundings, where the innovating power of feelings have more weight than the privative power of reason.

  6. Sensory analysis in grapes benitaka

    Energy Technology Data Exchange (ETDEWEB)

    Santillo, Amanda G.; Rodrigues, Flavio T.; Arthur, Paula B.; Villavicencio, Ana Lucia C.H. [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2011-07-01

    Abstract Sensory analysis is considered one of the main techniques when you want to know the organoleptic qualities of foods. Marketing strategies, showing that some foods produced organically is more nutritious, flavorful than conventional ones are affecting some consumers. The advantages of using radiation in sensory analysis are not the formation of waste, the less nutritional loss and little change in taste of food. The possibility that the fruit is harvested at more advanced maturity, when all characteristics of flavor and external appearance are fully developed is another advantage. The possibility of fruits being packed irradiated prevents contamination after processing. This type of study, ionizing radiation associated with sensory evaluation scarce, making it necessary for future discoveries. The objective this paper was to evaluate the quality of grapes Benitaka after the irradiation process with doses 0,5; 1; 1,5 e 2 kGy. (author)

  7. Sensory analysis in grapes benitaka

    International Nuclear Information System (INIS)

    Santillo, Amanda G.; Rodrigues, Flavio T.; Arthur, Paula B.; Villavicencio, Ana Lucia C.H.

    2011-01-01

    Abstract Sensory analysis is considered one of the main techniques when you want to know the organoleptic qualities of foods. Marketing strategies, showing that some foods produced organically is more nutritious, flavorful than conventional ones are affecting some consumers. The advantages of using radiation in sensory analysis are not the formation of waste, the less nutritional loss and little change in taste of food. The possibility that the fruit is harvested at more advanced maturity, when all characteristics of flavor and external appearance are fully developed is another advantage. The possibility of fruits being packed irradiated prevents contamination after processing. This type of study, ionizing radiation associated with sensory evaluation scarce, making it necessary for future discoveries. The objective this paper was to evaluate the quality of grapes Benitaka after the irradiation process with doses 0,5; 1; 1,5 e 2 kGy. (author)

  8. Perceiving space and optical cues via a visuo-tactile sensory substitution system: a methodological approach for training of blind subjects for navigation.

    Science.gov (United States)

    Segond, Hervé; Weiss, Déborah; Kawalec, Magdalena; Sampaio, Eliana

    2013-01-01

    A methodological approach to perceptual learning was used to allow both early blind subjects (experimental group) and blindfolded sighted subjects (control group) to experience optical information and spatial phenomena, on the basis of visuo-tactile information transmitted by a 64-taxel pneumatic sensory substitution device. The learning process allowed the subjects to develop abilities in spatial localisation, shape recognition (with generalisation to different points of view), and monocular depth cue interpretation. During the training phase, early blind people initially experienced more difficulties than blindfolded sighted subjects (having previous perceptual experience of perspective) with interpreting and using monocular depth cues. The amelioration of the performance for all blind subjects during training sessions and the quite similar level of performance reached by two groups in the final navigation tasks suggested that early blind people were able to develop and apply cognitive understanding of depth cues. Both groups showed generalisation of the learning from the initial phases to cue identification in the maze, and subjectively experienced shapes facing them. Subjects' performance depended not only on their perceptual experience but also on their previous spatial competencies.

  9. Impacts of Ocean Acidification on Sensory Function in Marine Organisms.

    Science.gov (United States)

    Ashur, Molly M; Johnston, Nicole K; Dixson, Danielle L

    2017-07-01

    Ocean acidification has been identified as a major contributor to ocean ecosystem decline, impacting the calcification, survival, and behavior of marine organisms. Numerous studies have observed altered sensory perception of chemical, auditory, and visual cues after exposure to elevated CO2. Sensory systems enable the observation of the external environment and therefore play a critical role in survival, communication, and behavior of marine organisms. This review seeks to (1) summarize the current knowledge of sensory impairment caused by ocean acidification, (2) discuss potential mechanisms behind this disruption, and (3) analyze the expected taxa differences in sensitivities to elevated CO2 conditions. Although a lack of standardized methodology makes cross-study comparisons challenging, trends and biases arise from this synthesis including a substantial focus on vertebrates, larvae or juveniles, the reef ecosystem, and chemosensory perception. Future studies must broaden the scope of the field by diversifying the taxa and ecosystems studied, incorporating ontogenetic comparisons, and focusing on cryptic sensory systems such as electroreception, magnetic sense, and the lateral line system. A discussion of possible mechanisms reveals GABAA receptor reversal as the conspicuous physiological mechanism. However, the potential remains for alternative disruption through structure or cue changes. Finally, a taxonomic comparison of physiological complexity reveals few trends in sensory sensitivities to lowered pH, but we hypothesize potential correlations relating to habitat, life history or relative use of sensory systems. Elevated CO2, in concordance with other global and local stressors, has the potential to drastically shift community composition and structure. Therefore research addressing the extent of sensory impairment, the underlying mechanisms, and the differences between taxa is vital for improved predictions of organismal response to ocean acidification.

  10. Sensory impairments of the lower limb after stroke: a pooled analysis of individual patient data.

    Science.gov (United States)

    Tyson, Sarah F; Crow, J Lesley; Connell, Louise; Winward, Charlotte; Hillier, Susan

    2013-01-01

    To obtain more generalizable information on the frequency and factors influencing sensory impairment after stroke and their relationship to mobility and function. A pooled analysis of individual data of stroke survivors (N = 459); mean (SD) age = 67.2 (14.8) years, 54% male, mean (SD) time since stroke = 22.33 (63.1) days, 50% left-sided weakness. Where different measurement tools were used, data were recorded. Descriptive statistics described frequency of sensory impairments, kappa coefficients investigated relationships between sensory modalities, binary logistic regression explored the factors influencing sensory impairments, and linear regression assessed the impact of sensory impairments on activity limitations. Most patients' sensation was intact (55%), and individual sensory modalities were highly associated (κ = 0.60, P sensory impairment (P analysis showed sensation of the lower limb is grossly preserved in most stroke survivors but, when present, it affects function. Sensory modalities are highly interrelated; interventions that treat the motor system during functional tasks may be as effective at treating the sensory system as sensory retraining alone.

  11. Active sensing via movement shapes spatiotemporal patterns of sensory feedback.

    Science.gov (United States)

    Stamper, Sarah A; Roth, Eatai; Cowan, Noah J; Fortune, Eric S

    2012-05-01

    Previous work has shown that animals alter their locomotor behavior to increase sensing volumes. However, an animal's own movement also determines the spatial and temporal dynamics of sensory feedback. Because each sensory modality has unique spatiotemporal properties, movement has differential and potentially independent effects on each sensory system. Here we show that weakly electric fish dramatically adjust their locomotor behavior in relation to changes of modality-specific information in a task in which increasing sensory volume is irrelevant. We varied sensory information during a refuge-tracking task by changing illumination (vision) and conductivity (electroreception). The gain between refuge movement stimuli and fish tracking responses was functionally identical across all sensory conditions. However, there was a significant increase in the tracking error in the dark (no visual cues). This was a result of spontaneous whole-body oscillations (0.1 to 1 Hz) produced by the fish. These movements were costly: in the dark, fish swam over three times further when tracking and produced more net positive mechanical work. The magnitudes of these oscillations increased as electrosensory salience was degraded via increases in conductivity. In addition, tail bending (1.5 to 2.35 Hz), which has been reported to enhance electrosensory perception, occurred only during trials in the dark. These data show that both categories of movements - whole-body oscillations and tail bends - actively shape the spatiotemporal dynamics of electrosensory feedback.

  12. An On-Chip Learning Neuromorphic Autoencoder With Current-Mode Transposable Memory Read and Virtual Lookup Table.

    Science.gov (United States)

    Cho, Hwasuk; Son, Hyunwoo; Seong, Kihwan; Kim, Byungsub; Park, Hong-June; Sim, Jae-Yoon

    2018-02-01

    This paper presents an IC implementation of on-chip learning neuromorphic autoencoder unit in a form of rate-based spiking neural network. With a current-mode signaling scheme embedded in a 500 × 500 6b SRAM-based memory, the proposed architecture achieves simultaneous processing of multiplications and accumulations. In addition, a transposable memory read for both forward and backward propagations and a virtual lookup table are also proposed to perform an unsupervised learning of restricted Boltzmann machine. The IC is fabricated using 28-nm CMOS process and is verified in a three-layer network of encoder-decoder pair for training and recovery of images with two-dimensional pixels. With a dataset of 50 digits, the IC shows a normalized root mean square error of 0.078. Measured energy efficiencies are 4.46 pJ per synaptic operation for inference and 19.26 pJ per synaptic weight update for learning, respectively. The learning performance is also estimated by simulations if the proposed hardware architecture is extended to apply to a batch training of 60 000 MNIST datasets.

  13. Epileptic Seizure Prediction Using Big Data and Deep Learning: Toward a Mobile System

    Directory of Open Access Journals (Sweden)

    Isabell Kiral-Kornek

    2018-01-01

    Conclusion: This study demonstrates that deep learning in combination with neuromorphic hardware can provide the basis for a wearable, real-time, always-on, patient-specific seizure warning system with low power consumption and reliable long-term performance.

  14. Qualidade sensorial do café de lavouras em conversão para o sistema de produção orgânico Cup quality of traditional crop coffee converted to organic system

    Directory of Open Access Journals (Sweden)

    Marcelo Ribeiro Malta

    2008-01-01

    Full Text Available Com o objetivo de se verificar a qualidade sensorial do café de lavouras em conversão para o sistema de produção orgânico, foi instalado este experimento, no município de Lavras (MG. O experimento foi instalado em 2004, em uma lavoura de café Catuaí Amarelo IAC 86, espaçamento de 4,0 x 0,6 m, com seis anos de idade, anteriormente cultivada no sistema convencional. Nos tratamentos orgânicos, empregou-se o delineamento látice balanceado 4 x 4, com cinco repetições em esquema fatorial 3 x 2 x 2, mais quatro tratamentos adicionais. O fatorial constou da utilização de três fontes de matéria orgânica (farelo de mamona, cama de frango e esterco bovino, com ou sem aplicação de casca de café e de adubação verde com feijão-guandu (Cajanus cajan L. Millsp.. Os quatro tratamentos adicionais consistiram de: 1- esterco bovino + casca de café + moinha de carvão + sulfato duplo de potássio e magnésio; 2 - farelo de mamona + casca de café + farinha de rocha; 3 - casca de café e 4 - adubação verde. Para efeito de comparação, manteve-se no mesmo talhão uma lavoura com manejo convencional. Não foram observadas diferenças de qualidade de bebida entre os cafés submetidos aos diferentes tratamentos orgânicos, nem entre esses e a testemunha no primeiro ano de conversão. No segundo ano, observou-se superioridade das bebidas de cafés de alguns tratamentos orgânicos em relação ao da lavoura desenvolvida no sistema convencional. Verificou-se efeito positivo da utilização do esterco bovino isoladamente ou associado com a casca de café e adubação verde na qualidade sensorial do café.The main purpose of this study was to evaluate sensorial attributes of coffee grown under a transition cultivation system, from conventional to organic, in Lavras (MG. The experiment was established in 2004, in a conventional field with 6 year-old Catuaí Amarelo IAC86 coffee plants, planted using 4,0 X 0,6 m spacing system. The experimental

  15. Relationships among Sensory Responsiveness, Anxiety, and Ritual Behaviors in Children with and without Atypical Sensory Responsiveness.

    Science.gov (United States)

    Bart, Orit; Bar-Shalita, Tami; Mansour, Hanin; Dar, Reuven

    2017-08-01

    To explore relationships between sensory responsiveness, anxiety, and ritual behaviors in boys with typical and atypical sensory responsiveness. Forty-eight boys, ages 5-9 participated in the study (28 boys with atypical sensory responsiveness and 20 controls). Atypical sensory responsiveness was defined as a score of ≤154 on the Short Sensory Profile. Parents completed the Sensory Profile, the Screen for Child Anxiety Related Emotional Disorders, and the Childhood Routines Inventory. Children with atypical sensory responsiveness had significantly higher levels of anxiety and a higher frequency of ritual behaviors than controls. Atypical sensory responsiveness was significantly related to both anxiety and ritual behaviors, with anxiety mediating the relationship between sensory modulation and ritual behaviors. The findings elucidate the potential consequences of atypical sensory responsiveness and could support the notion that ritual behaviors develop as a coping mechanism in response to anxiety stemming from primary difficulty in modulating sensory input.

  16. No Sensory Compensation for Olfactory Memory: Differences between Blind and Sighted People

    OpenAIRE

    Agnieszka Sorokowska; Agnieszka Sorokowska; Maciej Karwowski

    2017-01-01

    Blindness can be a driving force behind a variety of changes in sensory systems. When vision is missing, other modalities and higher cognitive functions can become hyper-developed through a mechanism called sensory compensation. Overall, previous studies suggest that olfactory memory in blind people can be better than that of the sighted individuals. Better performance of blind individuals in other-sensory modalities was hypothesized to be a result of, among others, intense perceptual trainin...

  17. Multi-sensory Sculpting (MSS)

    DEFF Research Database (Denmark)

    von Wallpach, Sylvia; Kreuzer, Maria

    2013-01-01

    -conscious and modality-specific level and use multi-sensory metaphors to express embodied knowledge. Retrieving embodied brand knowledge requires methods that (a) stimulate various senses that have been involved in brand knowledge formation and (b) give consumers the opportunity to express themselves metaphorically...

  18. Sensory Robot Gripper

    DEFF Research Database (Denmark)

    Drimus, Alin

    The project researches and proposes a tactile sensor system for equipping robotic grippers, thus giving them a sense of touch. We start by reviewing work that covers the building of tactile sensors and we focus on the flexible sensors with multiple sensing elements. As the piezoresistive, capacit......The project researches and proposes a tactile sensor system for equipping robotic grippers, thus giving them a sense of touch. We start by reviewing work that covers the building of tactile sensors and we focus on the flexible sensors with multiple sensing elements. As the piezoresistive......, such as establishing of contact, release of contact or slip. The proposed applications are just a few examples of the advantages of equipping robotic grippers with such a tactile sensor system, that is robust, fast, affordable, adaptable to any kind of gripper and has properties similar to the human sense of touch....... Based on experimental validation, we are confident that our proposed tactile sensor solution can be successfully employed in other application areas like reactive grasping, exploration of unknown objects, slip avoidance, dexterous manipulation or service robotics....

  19. Motor-sensory confluence in tactile perception.

    Science.gov (United States)

    Saig, Avraham; Gordon, Goren; Assa, Eldad; Arieli, Amos; Ahissar, Ehud

    2012-10-03

    Perception involves motor control of sensory organs. However, the dynamics underlying emergence of perception from motor-sensory interactions are not yet known. Two extreme possibilities are as follows: (1) motor and sensory signals interact within an open-loop scheme in which motor signals determine sensory sampling but are not affected by sensory processing and (2) motor and sensory signals are affected by each other within a closed-loop scheme. We studied the scheme of motor-sensory interactions in humans using a novel object localization task that enabled monitoring the relevant overt motor and sensory variables. We found that motor variables were dynamically controlled within each perceptual trial, such that they gradually converged to steady values. Training on this task resulted in improvement in perceptual acuity, which was achieved solely by changes in motor variables, without any change in the acuity of sensory readout. The within-trial dynamics is captured by a hierarchical closed-loop model in which lower loops actively maintain constant sensory coding, and higher loops maintain constant sensory update flow. These findings demonstrate interchangeability of motor and sensory variables in perception, motor convergence during perception, and a consistent hierarchical closed-loop perceptual model.

  20. Localization of SSeCKS in unmyelinated primary sensory neurons

    Directory of Open Access Journals (Sweden)

    Siegel Sandra M

    2008-03-01

    Full Text Available Abstract Background SSeCKS (Src SupprEssed C Kinase Substrate is a proposed protein kinase C substrate/A kinase anchoring protein (AKAP that has recently been characterized in the rat peripheral nervous system. It has been shown that approximately 40% of small primary sensory neurons contain SSeCKS-immunoreactivity in a population largely separate from substance P (95.2%, calcitonin gene related peptide (95.3%, or fluoride resistant acid phosphatase (55.0% labeled cells. In the spinal cord, it was found that SSeCKS-immunoreactive axon collaterals terminate in the dorsal third of lamina II outer in a region similar to that of unmyelinated C-, or small diameter myelinated Aδ-, fibers. However, the precise characterization of the anatomical profile of the primary sensory neurons containing SSeCKS remains to be determined. Here, immunohistochemical labeling at the light and ultrastructural level is used to clarify the myelination status of SSeCKS-containing sensory neuron axons and to further clarify the morphometric, and provide insight into the functional, classification of SSeCKS-IR sensory neurons. Methods Colocalization studies of SSeCKS with myelination markers, ultrastructural localization of SSeCKS labeling and ablation of largely unmyelinated sensory fibers by neonatal capsaicin administration were all used to establish whether SSeCKS containing sensory neurons represent a subpopulation of unmyelinated primary sensory C-fibers. Results Double labeling studies of SSeCKS with CNPase in the dorsal horn and Pzero in the periphery showed that SSeCKS immunoreactivity was observed predominantly in association with unmyelinated primary sensory fibers. At the ultrastructural level, SSeCKS immunoreactivity was most commonly associated with axonal membrane margins of unmyelinated fibers. In capsaicin treated rats, SSeCKS immunoreactivity was essentially obliterated in the dorsal horn while in dorsal root ganglia quantitative analysis revealed a 43

  1. Focal Dystonia and the Sensory-Motor Integrative Loop for Enacting (SMILE

    Directory of Open Access Journals (Sweden)

    David ePerruchoud

    2014-06-01

    Full Text Available Performing accurate movements requires preparation, execution, and monitoring mechanisms. The first two are coded by the motor system, and the latter by the sensory system. To provide an adaptive neural basis to overt behaviors, motor and sensory information has to be properly integrated in a reciprocal feedback loop. Abnormalities in this sensory-motor loop are involved in movement disorders such as focal dystonia, a hyperkinetic alteration affecting only a specific body part and characterized by sensory and motor deficits in the absence of basic motor impairments. Despite the fundamental impact of sensory-motor integration mechanisms on daily life, the general principles of healthy and pathological anatomic-functional organization of sensory-motor integration remain to be clarified. Based on the available data from experimental psychology, neurophysiology, and neuroimaging, we propose a bio-computational model of sensory-motor integration: the Sensory-Motor Integrative Loop for Enacting (SMILE. Aiming at direct therapeutic implementations and with the final target of implementing novel intervention protocols for motor rehabilitation, our main goal is to provide the information necessary for further validating the SMILE model. By translating neuroscientific hypotheses into empirical investigations and clinically relevant questions, the prediction based on the SMILE model can be further extended to other pathological conditions characterized by impaired sensory-motor integration.

  2. Focal dystonia and the Sensory-Motor Integrative Loop for Enacting (SMILE).

    Science.gov (United States)

    Perruchoud, David; Murray, Micah M; Lefebvre, Jeremie; Ionta, Silvio

    2014-01-01

    Performing accurate movements requires preparation, execution, and monitoring mechanisms. The first two are coded by the motor system, the latter by the sensory system. To provide an adaptive neural basis to overt behaviors, motor and sensory information has to be properly integrated in a reciprocal feedback loop. Abnormalities in this sensory-motor loop are involved in movement disorders such as focal dystonia, a hyperkinetic alteration affecting only a specific body part and characterized by sensory and motor deficits in the absence of basic motor impairments. Despite the fundamental impact of sensory-motor integration mechanisms on daily life, the general principles of healthy and pathological anatomic-functional organization of sensory-motor integration remain to be clarified. Based on the available data from experimental psychology, neurophysiology, and neuroimaging, we propose a bio-computational model of sensory-motor integration: the Sensory-Motor Integrative Loop for Enacting (SMILE). Aiming at direct therapeutic implementations and with the final target of implementing novel intervention protocols for motor rehabilitation, our main goal is to provide the information necessary for further validating the SMILE model. By translating neuroscientific hypotheses into empirical investigations and clinically relevant questions, the prediction based on the SMILE model can be further extended to other pathological conditions characterized by impaired sensory-motor integration.

  3. SENSORY PROCESSING DURING CHILDHOOD IN PRETERM INFANTS: A SYSTEMATIC REVIEW.

    Science.gov (United States)

    Machado, Ana Carolina Cabral de Paula; Oliveira, Suelen Rosa de; Magalhães, Lívia de Castro; Miranda, Débora Marques de; Bouzada, Maria Cândida Ferrarez

    2017-01-01

    To conduct a systematic search for grounded and quality evidence of sensory processing in preterm infants during childhood. The search of the available literature on the theme was held in the following electronic databases: Medical Literature Analysis and Retrieval System Online (Medline)/PubMed, Latin American and Caribbean Literature in Health Sciences (Lilacs)/Virtual Library in Health (BVS), Índice Bibliográfico Español de Ciencias de la Salud (IBECS)/BVS, Scopus, and Web of Science. We included only original indexed studies with a quantitative approach, which were available in full text on digital media, published in Portuguese, English, or Spanish between 2005 and 2015, involving children aged 0-9years. 581 articles were identified and eight were included. Six studies (75%) found high frequency of dysfunction in sensory processing in preterm infants. The association of sensory processing with developmental outcomes was observed in three studies (37.5%). The association of sensory processing with neonatal characteristics was observed in five studies (62.5%), and the sensory processing results are often associated with gestational age, male gender, and white matter lesions. The current literature suggests that preterm birth affects the sensory processing, negatively. Gestational age, male gender, and white matter lesions appear as risk factors for sensoryprocessing disorders in preterm infants. The impairment in the ability to receivesensory inputs, to integrateand to adapt to them seems to have a negative effect on motor, cognitive, and language development of these children. We highlight the feasibility of identifying sensory processing disorders early in life, favoring early clinical interventions.

  4. Statin use and peripheral sensory perception: a pilot study.

    Science.gov (United States)

    West, Brenton; Williams, Cylie M; Jilbert, Elise; James, Alicia M; Haines, Terry P

    2014-06-01

    Peripheral sensory neuropathy is a neurological deficit resulting in decreased detection of sensation through the peripheral nervous system. Peripheral sensory neuropathy is commonly diagnosed with the use of a monofilament and either a tuning fork or neurothesiometer. Statins are a widely used medication and there has been some debate of association with their use and peripheral sensory neuropathy. This pilot study aimed to test the sensory perception of participants with long-term statin use and compare these results to their peers who were not taking statins. Thirty participants were recruited and equally divided into a statin and non-statin group. Healthy participants were screened by their medical and medication history, Australian Type 2 Diabetes Risk assessment, and random blood glucose level. An assessor who was blinded to the participant group conducted sensory assessments using a 10 g monofilament and neurothesiometer. There was no difference in monofilament testing results between the groups. The statin group was less sensate at the styloid process (p = 0.031) and medial malleolus (p = 0.003) than the control group. Results at the hallux were not statistically significant (p = 0.183). This result is suggestive of a potential association between long-term statin use and a decrease in peripheral sensory perception. This may be because of peripheral sensory neuropathy. Limitations such as consideration of participant height, participant numbers, and inability to analyze results against statin groups are reported. As statins are a life-saving medication, careful consideration should be applied to these results and further research be conducted to determine if these results are applicable to larger populations.

  5. Activation of Six1 Expression in Vertebrate Sensory Neurons.

    Directory of Open Access Journals (Sweden)

    Shigeru Sato

    Full Text Available SIX1 homeodomain protein is one of the essential key regulators of sensory organ development. Six1-deficient mice lack the olfactory epithelium, vomeronasal organs, cochlea, vestibule and vestibuloacoustic ganglion, and also show poor neural differentiation in the distal part of the cranial ganglia. Simultaneous loss of both Six1 and Six4 leads to additional abnormalities such as small trigeminal ganglion and abnormal dorsal root ganglia (DRG. The aim of this study was to understand the molecular mechanism that controls Six1 expression in sensory organs, particularly in the trigeminal ganglion and DRG. To this end, we focused on the sensory ganglia-specific Six1 enhancer (Six1-8 conserved between chick and mouse. In vivo reporter assays using both animals identified an important core region comprising binding consensus sequences for several transcription factors including nuclear hormone receptors, TCF/LEF, SMAD, POU homeodomain and basic-helix-loop-helix proteins. The results provided information on upstream factors and signals potentially relevant to Six1 regulation in sensory neurons. We also report the establishment of a new transgenic mouse line (mSix1-8-NLSCre that expresses Cre recombinase under the control of mouse Six1-8. Cre-mediated recombination was detected specifically in ISL1/2-positive sensory neurons of Six1-positive cranial sensory ganglia and DRG. The unique features of the mSix1-8-NLSCre line are the absence of Cre-mediated recombination in SOX10-positive glial cells and central nervous system and ability to induce recombination in a subset of neurons derived from the olfactory placode/epithelium. This mouse model can be potentially used to advance research on sensory development.

  6. Sensory modulation disorders in childhood epilepsy.

    Science.gov (United States)

    van Campen, Jolien S; Jansen, Floor E; Kleinrensink, Nienke J; Joëls, Marian; Braun, Kees Pj; Bruining, Hilgo

    2015-01-01

    Altered sensory sensitivity is generally linked to seizure-susceptibility in childhood epilepsy but may also be associated to the highly prevalent problems in behavioral adaptation. This association is further suggested by the frequent overlap of childhood epilepsy with autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD), conditions in which altered behavioral responses to sensory stimuli have been firmly established. A continuum of sensory processing defects due to imbalanced neuronal inhibition and excitation across these disorders has been hypothesizedthat may lead to common symptoms of inadequate modulation of behavioral responses to sensory stimuli. Here, we investigated the prevalence of sensory modulation disorders among children with epilepsy and their relation with symptomatology of neurodevelopmental disorders. We used the Sensory Profile questionnaire to assess behavioral responses to sensory stimuli and categorize sensory modulation disorders in children with active epilepsy (aged 4-17 years). We related these outcomes to epilepsy characteristics and tested their association with comorbid symptoms of ASD (Social Responsiveness Scale) and ADHD (Strengths and Difficulties Questionnaire). Sensory modulation disorders were reported in 49 % of the 158 children. Children with epilepsy reported increased behavioral responses associated with sensory "sensitivity," "sensory avoidance," and "poor registration" but not "sensory seeking." Comorbidity of ASD and ADHD was associated with more severe sensory modulation problems, although 27 % of typically developing children with epilepsy also reported a sensory modulation disorder. Sensory modulation disorders are an under-recognized problem in children with epilepsy. The extent of the modulation difficulties indicates a substantial burden on daily functioning and may explain an important part of the behavioral distress associated with childhood epilepsy.

  7. The neural career of sensory-motor metaphors.

    Science.gov (United States)

    Desai, Rutvik H; Binder, Jeffrey R; Conant, Lisa L; Mano, Quintino R; Seidenberg, Mark S

    2011-09-01

    The role of sensory-motor systems in conceptual understanding has been controversial. It has been proposed that many abstract concepts are understood metaphorically through concrete sensory-motor domains such as actions. Using fMRI, we compared neural responses with literal action (Lit; The daughter grasped the flowers), metaphoric action (Met; The public grasped the idea), and abstract (Abs; The public understood the idea) sentences of varying familiarity. Both Lit and Met sentences activated the left anterior inferior parietal lobule, an area involved in action planning, with Met sentences also activating a homologous area in the right hemisphere, relative to Abs sentences. Both Met and Abs sentences activated the left superior temporal regions associated with abstract language. Importantly, activation in primary motor and biological motion perception regions was inversely correlated with Lit and Met familiarity. These results support the view that the understanding of metaphoric action retains a link to sensory-motor systems involved in action performance. However, the involvement of sensory-motor systems in metaphor understanding changes through a gradual abstraction process whereby relatively detailed simulations are used for understanding unfamiliar metaphors, and these simulations become less detailed and involve only secondary motor regions as familiarity increases. Consistent with these data, we propose that anterior inferior parietal lobule serves as an interface between sensory-motor and conceptual systems and plays an important role in both domains. The similarity of abstract and metaphoric sentences in the activation of left superior temporal regions suggests that action metaphor understanding is not completely based on sensory-motor simulations but relies also on abstract lexical-semantic codes.

  8. Sensory Substitution and Multimodal Mental Imagery.

    Science.gov (United States)

    Nanay, Bence

    2017-09-01

    Many philosophers use findings about sensory substitution devices in the grand debate about how we should individuate the senses. The big question is this: Is "vision" assisted by (tactile) sensory substitution really vision? Or is it tactile perception? Or some sui generis novel form of perception? My claim is that sensory substitution assisted "vision" is neither vision nor tactile perception, because it is not perception at all. It is mental imagery: visual mental imagery triggered by tactile sensory stimulation. But it is a special form of mental imagery that is triggered by corresponding sensory stimulation in a different sense modality, which I call "multimodal mental imagery."

  9. Sensory augmentation for the blind

    Directory of Open Access Journals (Sweden)

    Silke Manuela Kärcher

    2012-03-01

    Full Text Available Enacted theories of consciousness conjecture that perception and cognition arise from an active experience of the regular relations that are tying together the sensory stimulation of different modalities and associated motor actions. Previous experiments investigated this concept by employing the technique of sensory substitution. Building on these studies, here we test a set of hypotheses derived from this framework and investigate the utility of sensory augmentation in handicapped people. We provide a late blind subject with a new set of sensorimotor laws: A vibro-tactile belt continually signals the direction of magnetic north. The subject completed a set of behavioral tests before and after an extended training period. The tests were complemented by questionnaires and interviews. This newly supplied information improved performance on different time scales. In a pointing task we demonstrate an instant improvement of performance based on the signal provided by the device. Furthermore, the signal was helpful in relevant daily tasks, often complicated for the blind, such as keeping a direction over longer distances or taking shortcuts in familiar environments. A homing task with an additional attentional load demonstrated a significant improvement after training. The subject found the directional information highly expedient for the adjustment of his inner maps of familiar environments and describes an increase in his feeling of security when exploring unfamiliar environments with the belt. The results give evidence for a firm integration of the newly supplied signals into the behavior of this late blind subject with better navigational performance and more courageous behavior in unfamiliar environments. Most importantly, the complementary information provided by the belt lead to a positive emotional impact with enhanced feeling of security. This experimental approach demonstrates the potential of sensory augmentation devices for the help of

  10. Sensory properties of irradiated foods

    International Nuclear Information System (INIS)

    Plestenjak, A.

    1997-01-01

    Food irradiation is a simple and effective preservation technique. The changes caused by irradiation depend on composition of food, on the absorbed dose, the water content and temperature during and after irradiation. In this paper the changes of food components caused by irradiation, doses for various food irradiation treatments, foods and countries where the irradiation is allowed, and sensory properties of irradiated food are reviewed

  11. Locomotor Sensory Organization Test: How Sensory Conflict Affects the Temporal Structure of Sway Variability During Gait.

    Science.gov (United States)

    Chien, Jung Hung; Mukherjee, Mukul; Siu, Ka-Chun; Stergiou, Nicholas

    2016-05-01

    When maintaining postural stability temporally under increased sensory conflict, a more rigid response is used where the available degrees of freedom are essentially frozen. The current study investigated if such a strategy is also utilized during more dynamic situations of postural control as is the case with walking. This study attempted to answer this question by using the Locomotor Sensory Organization Test (LSOT). This apparatus incorporates SOT inspired perturbations of the visual and the somatosensory system. Ten healthy young adults performed the six conditions of the traditional SOT and the corresponding six conditions on the LSOT. The temporal structure of sway variability was evaluated from all conditions. The results showed that in the anterior posterior direction somatosensory input is crucial for postural control for both walking and standing; visual input also had an effect but was not as prominent as the somatosensory input. In the medial lateral direction and with respect to walking, visual input has a much larger effect than somatosensory input. This is possibly due to the added contributions by peripheral vision during walking; in standing such contributions may not be as significant for postural control. In sum, as sensory conflict increases more rigid and regular sway patterns are found during standing confirming the previous results presented in the literature, however the opposite was the case with walking where more exploratory and adaptive movement patterns are present.

  12. Development of Metallic Sensory Alloys

    Science.gov (United States)

    Wallace Terryl A.; Newman, John A.; Horne, Michael R.; Messick, Peter L.

    2010-01-01

    Existing nondestructive evaluation (NDE) technologies are inherently limited by the physical response of the structural material being inspected and are therefore not generally effective at the identification of small discontinuities, making the detection of incipient damage extremely difficult. One innovative solution to this problem is to enhance or complement the NDE signature of structural materials to dramatically improve the ability of existing NDE tools to detect damage. To address this need, a multifunctional metallic material has been developed that can be used in structural applications. The material is processed to contain second phase sensory particles that significantly improve the NDE response, enhancing the ability of conventional NDE techniques to detect incipient damage both during and after flight. Ferromagnetic shape-memory alloys (FSMAs) are an ideal material for these sensory particles as they undergo a uniform and repeatable change in both magnetic properties and crystallographic structure (martensitic transformation) when subjected to strain and/or temperature changes which can be detected using conventional NDE techniques. In this study, the use of a ferromagnetic shape memory alloy (FSMA) as the sensory particles was investigated.

  13. Sensory impacts of food-packaging interactions.

    Science.gov (United States)

    Duncan, Susan E; Webster, Janet B

    2009-01-01

    Sensory changes in food products result from intentional or unintentional interactions with packaging materials and from failure of materials to protect product integrity or quality. Resolving sensory issues related to plastic food packaging involves knowledge provided by sensory scientists, materials scientists, packaging manufacturers, food processors, and consumers. Effective communication among scientists and engineers from different disciplines and industries can help scientists understand package-product interactions. Very limited published literature describes sensory perceptions associated with food-package interactions. This article discusses sensory impacts, with emphasis on oxidation reactions, associated with the interaction of food and materials, including taints, scalping, changes in food quality as a function of packaging, and examples of material innovations for smart packaging that can improve sensory quality of foods and beverages. Sensory evaluation is an important tool for improved package selection and development of new materials.

  14. The Chemical Background for Sensory Quality

    DEFF Research Database (Denmark)

    Zhang, Shujuan

    compounds and consequently change the sensory quality in wine which provide the useful information of wine quality management to winemakers to as well as knowledge on the behaviour of wine oxidation. Additional, studies focused on understanding the development of volatiles during accelerated cheese ripening......In the food industry, high sensory quality and stability of products are crucial factors for consumer satisfaction and market shares. Sensory quality is normally being evaluated by two major approaches: instrumental (volatile and nonvolatile compounds) approach and sensory approach by trained...... and sensory methods in understanding the pre-fermentation treatment on sensory quality of wine (Study 3). In Study 4, the RATA method was used to provide the intensity of significant sensory descriptors that discriminate the significant differences between chocolate samples. Part three step by step moves...

  15. Characterization, sensorial evaluation and moisturizing efficacy of nanolipidgel formulations.

    Science.gov (United States)

    Estanqueiro, M; Conceição, J; Amaral, M H; Sousa Lobo, J M

    2014-04-01

    Nanostructured lipid carriers (NLC) have been widely studied for cosmetic and dermatological applications due to their favourable properties that include the formation of an occlusive film on the skin surface that reduces the transepidermal water loss (TEWL) and increase in water content in the skin which improves the appearance on healthy human skin and reduces symptoms of some skin disorders like eczema. The main objective of this study was the development of semisolid formulations based NLC with argan oil or jojoba oil as liquid lipids, by addition of Carbopol®934 or Carbopol®980 as gelling agents, followed by comparison between instrumental analysis and sensorial evaluation and in vivo efficacy evaluation. Nanostructured lipid carriers dispersions were produced by the ultrasound technique, and to obtain a semisolid formulation, gelling agents were dispersed in the aqueous dispersion. Particle size, polydispersity index and zeta potential were determined. Instrumental characterization was performed by rheological and textural analysis; the sensorial evaluation was also performed. Finally, skin hydration and TEWL were studied by capacitance and evaporimetry evaluation, respectively. Particles showed a nanometric size in all the analysed formulations. All the gels present pseudoplastic behaviour. There is a correspondence between the properties firmness and adhesiveness as determined by textural analysis and the sensory evaluation. The formulations that showed a greater increase in skin hydration also presented appropriate technological and sensorial attributes for skin application. Nanolipidgel formulations with the addition of humectants are promising systems for cosmetic application with good sensory and instrumental attributes and moisturizing efficacy.

  16. Influence of Sensory Stimulation on Exhaled Volatile Organic Compounds.

    Science.gov (United States)

    Mazzatenta, A; Pokorski, M; Di Tano, A; Cacchio, M; Di Giulio, C

    2016-01-01

    The real-time exhaled volatile organic compounds (VOCs) have been suggested as a new biomarker to detect and monitor physiological processes in the respiratory system. The VOCs profile in exhaled breath reflects the biochemical alterations related to metabolic changes, organ failure, and neuronal activity, which are, at least in part, transmitted via the lungs to the alveolar exhaled breath. Breath analysis has been applied to investigate cancer, lung failure, and neurodegenerative diseases. There are by far no studies on the real-time monitoring of VOCs in sensory stimulation in healthy subjects. Therefore, in this study we investigated the breath parameters and exhaled VOCs in humans during sensory stimulation: smell, hearing, sight, and touch. Responses sensory stimulations were recorded in 12 volunteers using an iAQ-2000 sensor. We found significant effects of sensory stimulation. In particular, olfactory stimulation was the most effective stimulus that elicited the greatest VOCs variations in the exhaled breath. Since the olfactory pathway is distinctly driven by the hypothalamic and limbic circuitry, while other senses project first to the thalamic area and then re-project to other brain areas, the findings suggest the importance of olfaction and chemoreception in the regulation lung gas exchange. VOCs variations during sensory activation may become putative indicators of neural activity.

  17. Dissociating sensory from decision processes in human perceptual decision making.

    Science.gov (United States)

    Mostert, Pim; Kok, Peter; de Lange, Floris P

    2015-12-15

    A key question within systems neuroscience is how the brain translates physical stimulation into a behavioral response: perceptual decision making. To answer this question, it is important to dissociate the neural activity underlying the encoding of sensory information from the activity underlying the subsequent temporal integration into a decision variable. Here, we adopted a decoding approach to empirically assess this dissociation in human magnetoencephalography recordings. We used a functional localizer to identify the neural signature that reflects sensory-specific processes, and subsequently traced this signature while subjects were engaged in a perceptual decision making task. Our results revealed a temporal dissociation in which sensory processing was limited to an early time window and consistent with occipital areas, whereas decision-related processing became increasingly pronounced over time, and involved parietal and frontal areas. We found that the sensory processing accurately reflected the physical stimulus, irrespective of the eventual decision. Moreover, the sensory representation was stable and maintained over time when it was required for a subsequent decision, but unstable and variable over time when it was task-irrelevant. In contrast, decision-related activity displayed long-lasting sustained components. Together, our approach dissects neuro-anatomically and functionally distinct contributions to perceptual decisions.

  18. Dissociating sensory from decision processes in human perceptual decision making

    Science.gov (United States)

    Mostert, Pim; Kok, Peter; de Lange, Floris P.

    2015-01-01

    A key question within systems neuroscience is how the brain translates physical stimulation into a behavioral response: perceptual decision making. To answer this question, it is important to dissociate the neural activity underlying the encoding of sensory information from the activity underlying the subsequent temporal integration into a decision variable. Here, we adopted a decoding approach to empirically assess this dissociation in human magnetoencephalography recordings. We used a functional localizer to identify the neural signature that reflects sensory-specific processes, and subsequently traced this signature while subjects were engaged in a perceptual decision making task. Our results revealed a temporal dissociation in which sensory processing was limited to an early time window and consistent with occipital areas, whereas decision-related processing became increasingly pronounced over time, and involved parietal and frontal areas. We found that the sensory processing accurately reflected the physical stimulus, irrespective of the eventual decision. Moreover, the sensory representation was stable and maintained over time when it was required for a subsequent decision, but unstable and variable over time when it was task-irrelevant. In contrast, decision-related activity displayed long-lasting sustained components. Together, our approach dissects neuro-anatomically and functionally distinct contributions to perceptual decisions. PMID:26666393

  19. Online maintenance of sensory and motor representations: effects on corticospinal excitability.

    NARCIS (Netherlands)

    Hurk, P. van den; Mars, R.B.; Elswijk, G.A.F. van; Hegeman, J.; Pasman, J.W.; Bloem, B.R.; Toni, I.

    2007-01-01

    Flexible behavior requires the ability to delay a response until it is appropriate. This can be achieved by holding either a sensory or a motor representation online. Here we assess whether maintenance of sensory or motor material drives the motor system to different functional states, as indexed by

  20. Online maintenance of sensory and motor representations: Effects on corticospinal excitability

    NARCIS (Netherlands)

    Hurk, P.A.M. van den; Mars, R.B.; Elswijk, G.A.F. van; Hegeman, J.; Pasman, J.W.; Bloem, B.R.; Toni, I.

    2007-01-01

    Flexible behavior requires the ability to delay a response until it is appropriate. This can be achieved by holding either a sensory or a motor representation online. Here we assess whether maintenance of sensory or motor material drives the motor system to different functional states, as indexed by

  1. Associative Learning and Sensory Neuroplasticity: How Does It Happen and What Is It Good For?

    Science.gov (United States)

    McGann, John P.

    2015-01-01

    Historically, the body's sensory systems have been presumed to provide the brain with raw information about the external environment, which the brain must interpret to select a behavioral response. Consequently, studies of the neurobiology of learning and memory have focused on circuitry that interfaces between sensory inputs and behavioral…

  2. Sensory reweighting of proprioceptive information of the left and right leg during human balance control

    NARCIS (Netherlands)

    Pasma, Jantsje; Pasma, J.H.; Boonstra, Tjitske; Campfens, S.F.; Schouten, Alfred Christiaan; van der Kooij, Herman

    2012-01-01

    To keep balance, information from different sensory systems is integrated to generate corrective torques. Current literature suggests that this information is combined according to the sensory reweighting hypothesis, i.e., more reliable information is weighted more strongly than less reliable

  3. Neurolinguistic Programming: The Impact of Imagery Tasks on Sensory Predicate Usage.

    Science.gov (United States)

    Graunke, Bruce; Roberts, T. Kevin

    1985-01-01

    Investigated the impact of varied imagining tasks on individuals' use of sensory predicates. Results demonstrated that subjects were able to vary their type of sensory predicates according to the task demands or situational context. Findings are incongruent with Bandler and Grinder's (1979) conceptualization of representational systems.…

  4. Task-space sensory feedback control of robot manipulators

    CERN Document Server

    Cheah, Chien Chern

    2015-01-01

    This book presents recent advances in robot control theory on task space sensory feedback control of robot manipulators. By using sensory feedback information, the robot control systems are robust to various uncertainties in modelling and calibration errors of the sensors. Several sensory task space control methods that do not require exact knowledge of either kinematics or dynamics of robots, are presented. Some useful methods such as approximate Jacobian control, adaptive Jacobian control, region control and multiple task space regional feedback are included. These formulations and methods give robots a high degree of flexibility in dealing with unforeseen changes and uncertainties in its kinematics and dynamics, which is similar to human reaching movements and tool manipulation. It also leads to the solution of several long-standing problems and open issues in robot control, such as force control with constraint uncertainty, control of multi-fingered robot hand with uncertain contact points, singularity i...

  5. Multiple Sensory-Motor Pathways Lead to Coordinated Visual Attention

    Science.gov (United States)

    Yu, Chen; Smith, Linda B.

    2017-01-01

    Joint attention has been extensively studied in the developmental literature because of overwhelming evidence that the ability to socially coordinate visual attention to an object is essential to healthy developmental outcomes, including language learning. The goal of this study was to understand the complex system of sensory-motor behaviors that…

  6. The 'sensory tolerance limit': A hypothetical construct determining exercise performance?

    Science.gov (United States)

    Hureau, Thomas J; Romer, Lee M; Amann, Markus

    2018-02-01

    Neuromuscular fatigue compromises exercise performance and is determined by central and peripheral mechanisms. Interactions between the two components of fatigue can occur via neural pathways, including feedback and feedforward processes. This brief review discusses the influence of feedback and feedforward mechanisms on exercise limitation. In terms of feedback mechanisms, particular attention is given to group III/IV sensory neurons which link limb muscle with the central nervous system. Central corollary discharge, a copy of the neural drive from the brain to the working muscles, provides a signal from the motor system to sensory systems and is considered a feedforward mechanism that might influence fatigue and consequently exercise performance. We highlight findings from studies supporting the existence of a 'critical threshold of peripheral fatigue', a previously proposed hypothesis based on the idea that a negative feedback loop operates to protect the exercising limb muscle from severe threats to homeostasis during whole-body exercise. While the threshold theory remains to be disproven within a given task, it is not generalisable across different exercise modalities. The 'sensory tolerance limit', a more theoretical concept, may address this issue and explain exercise tolerance in more global terms and across exercise modalities. The 'sensory tolerance limit' can be viewed as a negative feedback loop which accounts for the sum of all feedback (locomotor muscles, respiratory muscles, organs, and muscles not directly involved in exercise) and feedforward signals processed within the central nervous system with the purpose of regulating the intensity of exercise to ensure that voluntary activity remains tolerable.

  7. Dissociating sensory from decision processes in human perceptual decision making

    NARCIS (Netherlands)

    Mostert, P.; Kok, P.; Lange, F.P. de

    2015-01-01

    A key question within systems neuroscience is how the brain translates physical stimulation into a behavioral response: perceptual decision making. To answer this question, it is important to dissociate the neural activity underlying the encoding of sensory information from the activity underlying

  8. Biological Correlates of Cognitive, Sensory and Motor Abilities

    Science.gov (United States)

    1975-04-01

    receptor organs are of great interest in a compre- hensive understanding of sensory systems (Harris, 1974). Taste buds disappear following...cold. The interoceptors include a variety of mechanoreceptors and chemoreceptors such as the skeletal muscle spindles, tendon end organs, end

  9. Sensory flow shaped by active sensing: sensorimotor strategies in electric fish.

    Science.gov (United States)

    Hofmann, Volker; Sanguinetti-Scheck, Juan I; Künzel, Silke; Geurten, Bart; Gómez-Sena, Leonel; Engelmann, Jacob

    2013-07-01

    Goal-directed behavior in most cases is composed of a sequential order of elementary motor patterns shaped by sensorimotor contingencies. The sensory information acquired thus is structured in both space and time. Here we review the role of motion during the generation of sensory flow focusing on how animals actively shape information by behavioral strategies. We use the well-studied examples of vision in insects and echolocation in bats to describe commonalities of sensory-related behavioral strategies across sensory systems, and evaluate what is currently known about comparable active sensing strategies in electroreception of electric fish. In this sensory system the sensors are dispersed across the animal's body and the carrier source emitting energy used for sensing, the electric organ, is moved while the animal moves. Thus ego-motions strongly influence sensory dynamics. We present, for the first time, data of electric flow during natural probing behavior in Gnathonemus petersii (Mormyridae), which provide evidence for this influence. These data reveal a complex interdependency between the physical input to the receptors and the animal's movements, posture and objects in its environment. Although research on spatiotemporal dynamics in electrolocation is still in its infancy, the emerging field of dynamical sensory systems analysis in electric fish is a promising approach to the study of the link between movement and acquisition of sensory information.

  10. Hereditary sensory neuropathy type I

    Directory of Open Access Journals (Sweden)

    Auer-Grumbach Michaela

    2008-03-01

    Full Text Available Abstract Hereditary sensory neuropathy type I (HSN I is a slowly progressive neurological disorder characterised by prominent predominantly distal sensory loss, autonomic disturbances, autosomal dominant inheritance, and juvenile or adulthood disease onset. The exact prevalence is unknown, but is estimated as very low. Disease onset varies between the 2nd and 5th decade of life. The main clinical feature of HSN I is the reduction of sensation sense mainly distributed to the distal parts of the upper and lower limbs. Variable distal muscle weakness and wasting, and chronic skin ulcers are characteristic. Autonomic features (usually sweating disturbances are invariably observed. Serious and common complications are spontaneous fractures, osteomyelitis and necrosis, as well as neuropathic arthropathy which may even necessitate amputations. Some patients suffer from severe pain attacks. Hypacusis or deafness, or cough and gastrooesophageal reflux have been observed in rare cases. HSN I is a genetically heterogenous condition with three loci and mutations in two genes (SPTLC1 and RAB7 identified so far. Diagnosis is based on the clinical observation and is supported by a family history. Nerve conduction studies confirm a sensory and motor neuropathy predominantly affecting the lower limbs. Radiological studies, including magnetic resonance imaging, are useful when bone infections or necrosis are suspected. Definitive diagnosis is based on the detection of mutations by direct sequencing of the SPTLC1 and RAB7 genes. Correct clinical assessment and genetic confirmation of the diagnosis are important for appropriate genetic counselling and prognosis. Differential diagnosis includes the other hereditary sensory and autonomic neuropathies (HSAN, especially HSAN II, as well as diabetic foot syndrome, alcoholic neuropathy, neuropathies caused by other neurotoxins/drugs, immune mediated neuropathy, amyloidosis, spinal cord diseases, tabes dorsalis, lepra

  11. Hereditary sensory neuropathy type I.

    Science.gov (United States)

    Auer-Grumbach, Michaela

    2008-03-18

    Hereditary sensory neuropathy type I (HSN I) is a slowly progressive neurological disorder characterised by prominent predominantly distal sensory loss, autonomic disturbances, autosomal dominant inheritance, and juvenile or adulthood disease onset. The exact prevalence is unknown, but is estimated as very low. Disease onset varies between the 2nd and 5th decade of life. The main clinical feature of HSN I is the reduction of sensation sense mainly distributed to the distal parts of the upper and lower limbs. Variable distal muscle weakness and wasting, and chronic skin ulcers are characteristic. Autonomic features (usually sweating disturbances) are invariably observed. Serious and common complications are spontaneous fractures, osteomyelitis and necrosis, as well as neuropathic arthropathy which may even necessitate amputations. Some patients suffer from severe pain attacks. Hypacusis or deafness, or cough and gastrooesophageal reflux have been observed in rare cases. HSN I is a genetically heterogenous condition with three loci and mutations in two genes (SPTLC1 and RAB7) identified so far. Diagnosis is based on the clinical observation and is supported by a family history. Nerve conduction studies confirm a sensory and motor neuropathy predominantly affecting the lower limbs. Radiological studies, including magnetic resonance imaging, are useful when bone infections or necrosis are suspected. Definitive diagnosis is based on the detection of mutations by direct sequencing of the SPTLC1 and RAB7 genes. Correct clinical assessment and genetic confirmation of the diagnosis are important for appropriate genetic counselling and prognosis. Differential diagnosis includes the other hereditary sensory and autonomic neuropathies (HSAN), especially HSAN II, as well as diabetic foot syndrome, alcoholic neuropathy, neuropathies caused by other neurotoxins/drugs, immune mediated neuropathy, amyloidosis, spinal cord diseases, tabes dorsalis, lepra neuropathy, or decaying skin

  12. Cognitive mechanisms associated with auditory sensory gating

    Science.gov (United States)

    Jones, L.A.; Hills, P.J.; Dick, K.M.; Jones, S.P.; Bright, P.

    2016-01-01

    Sensory gating is a neurophysiological measure of inhibition that is characterised by a reduction in the P50 event-related potential to a repeated identical stimulus. The objective of this work was to determine the cognitive mechanisms that relate to the neurological phenomenon of auditory sensory gating. Sixty participants underwent a battery of 10 cognitive tasks, including qualitatively different measures of attentional inhibition, working memory, and fluid intelligence. Participants additionally completed a paired-stimulus paradigm as a measure of auditory sensory gating. A correlational analysis revealed that several tasks correlated significantly with sensory gating. However once fluid intelligence and working memory were accounted for, only a measure of latent inhibition and accuracy scores on the continuous performance task showed significant sensitivity to sensory gating. We conclude that sensory gating reflects the identification of goal-irrelevant information at the encoding (input) stage and the subsequent ability to selectively attend to goal-relevant information based on that previous identification. PMID:26716891

  13. Sensory characteristics of different cod products

    DEFF Research Database (Denmark)

    Sveinsdottir, K.; Martinsdottir, E.; Hyldig, Grethe

    2010-01-01

    atmosphere) were evaluated with quantitative descriptive analysis by a trained sensory panel. Signal-to-noise analysis, p*MSE (discrimination and repeatability) and line plots proved to be very useful in studying panelists' performance. Most sensory attributes described significant differences between...... the products, and principal component analysis provided an overview of the differences and similarities between the products with regard to sensory characteristics. Farmed cod had different sensory characteristics compared with wild cod, such as more meat flavor, and rubbery and meaty texture. Different...... storage methods had minor influence on sensory characteristics of cod fillets after short storage time, but after extended storage, the groups were different with regard to most attributes. PRACTICAL APPLICATIONS This paper presents different ways of analyzing sensory data. The process of analysis...

  14. Multivariate analysis of data in sensory science

    CERN Document Server

    Naes, T; Risvik, E

    1996-01-01

    The state-of-the-art of multivariate analysis in sensory science is described in this volume. Both methods for aggregated and individual sensory profiles are discussed. Processes and results are presented in such a way that they can be understood not only by statisticians but also by experienced sensory panel leaders and users of sensory analysis. The techniques presented are focused on examples and interpretation rather than on the technical aspects, with an emphasis on new and important methods which are possibly not so well known to scientists in the field. Important features of the book are discussions on the relationship among the methods with a strong accent on the connection between problems and methods. All procedures presented are described in relation to sensory data and not as completely general statistical techniques. Sensory scientists, applied statisticians, chemometricians, those working in consumer science, food scientists and agronomers will find this book of value.

  15. Sensory cortex underpinnings of traumatic brain injury deficits.

    Directory of Open Access Journals (Sweden)

    Dasuni S Alwis

    Full Text Available Traumatic brain injury (TBI can result in persistent sensorimotor and cognitive deficits including long-term altered sensory processing. The few animal models of sensory cortical processing effects of TBI have been limited to examination of effects immediately after TBI and only in some layers of cortex. We have now used the rat whisker tactile system and the cortex processing whisker-derived input to provide a highly detailed description of TBI-induced long-term changes in neuronal responses across the entire columnar network in primary sensory cortex. Brain injury (n=19 was induced using an impact acceleration method and sham controls received surgery only (n=15. Animals were tested in a range of sensorimotor behaviour tasks prior to and up to 6 weeks post-injury when there were still significant sensorimotor behaviour deficits. At 8-10 weeks post-trauma, in terminal experiments, extracellular recordings were obtained from barrel cortex neurons in response to whisker motion, including motion that mimicked whisker motion observed in awake animals undertaking different tasks. In cortex, there were lamina-specific neuronal response alterations that appeared to reflect local circuit changes. Hyper-excitation was found only in supragranular layers involved in intra-areal processing and long-range integration, and only for stimulation with complex, naturalistic whisker motion patterns and not for stimulation with simple trapezoidal whisker motion. Thus TBI induces long-term directional changes in integrative sensory cortical layers that depend on the complexity of the incoming sensory information. The nature of these changes allow predictions as to what types of sensory processes may be affected in TBI and contribute to post-trauma sensorimotor deficits.

  16. Spike Neuromorphic VLSI-Based Bat Echolocation for Micro-Aerial Vehicle Guidance

    National Research Council Canada - National Science Library

    Horiuchi, Timothy K; Krishnaprasad, P. S

    2007-01-01

    .... This includes multiple efforts related to a VLSI-based echolocation system being developed in one of our laboratories from algorithm development, bat flight data analysis, to VLSI circuit design...

  17. Experienced Sensory Modalities in Dream Recall

    OpenAIRE

    岡田, 斉

    2000-01-01

    The purpose of the present study is to survey the frequency of visual, auditory, kinaesthetic, cutaneous, organic, gustatory, and olfactory experience in dream recall. A total of 1267 undergraduate students completed a dream recall frequency questionnaire, which contained a question about dream recall frequency and about recall frequency of seven sensory modalities. Results showed that seven sensory modalities were divided into two groups; normally perceived sensory modalities in dreaming, wh...

  18. Development of sensorial experiments and their implementation into undergraduate laboratories

    Science.gov (United States)

    Bromfield Lee, Deborah Christina

    "Visualization" of chemical phenomena often has been limited in the teaching laboratories to the sense of sight. We have developed chemistry experiments that rely on senses other than eyesight to investigate chemical concepts, make quantitative determinations, and familiarize students with chemical techniques traditionally designed using only eyesight. Multi-sensory learning can benefit all students by actively engaging them in learning through stimulation or an alternative way of experiencing a concept or ideas. Perception of events or concepts usually depends on the information from the different sensory systems combined. The use of multi-sensory learning can take advantage of all the senses to reinforce learning as each sense builds toward a more complete experience of scientific data. Research has shown that multi-sensory representations of scientific phenomena is a valuable tool for enhancing understanding of chemistry as well as displacing misconceptions through experience. Multi-sensory experiences have also been shown to enrich memory performance. There are few experiments published which utilize multiple senses in the teaching laboratory. The sensorial experiments chosen were conceptually similar to experiments currently performed in undergraduate laboratories; however students collect different types of data using multi-sensory observations. The experiments themselves were developed by using chemicals that would provide different sensory changes or capitalizing on sensory observations that were typically overlooked or ignored and obtain similar and precise results as in traditional experiments. Minimizing hazards and using safe practices are especially essential in these experiments as students utilize senses traditionally not allowed to be used in the laboratories. These sensorial experiments utilize typical equipment found in the teaching laboratories as well as inexpensive chemicals in order to aid implementation. All experiments are rigorously tested

  19. Do Birds Experience Sensory Pleasure?

    Directory of Open Access Journals (Sweden)

    Michel Cabanac

    2009-01-01

    Full Text Available To answer the question of whether sensory pleasure exists in birds, I trained an African-gray parrot (Psittacus erythacus named Aristote to speak. Stage 1 of the study consisted in gaining Aristote's affection. In Stage 2 Aristote was taught to speak, following Irene Pepperberg's triangular method: another person and I would talk together and look at Aristote only when it used understandable French words. Thus Aristote learned to say a few words for obtaining toys or getting my attention; e.g. “donne bouchon” (give cork or “donne gratte” (give scratch/tickle, with the appropriate reward. In Stage 3, the word bon (good was added to the short list of words used by Aristote. I said “bon” when giving Aristote the stimuli it requested and which would, presumably, be pleasurable; e.g. gratte bon. Aristote started to use short sentences such as “yaourt bon” (good yogurt. Eventually, Aristote transferred the word bon to new stimuli such as raisin (grape, an association I myself had never made. Such a use of vocabulary, and moreover its transfer, likely shows that this bird experienced sensory pleasure.

  20. Sensorial evaluation of irradiated mangoes

    International Nuclear Information System (INIS)

    Broisler, Paula Olhe; Cruz, Juliana Nunes da; Sabato, Susy Frey

    2007-01-01

    Mango (Mangifera indica L.) is a tropical fruit of great economical relevance in the world, mainly for tropical countries like Brazil. It consists in the second tropical fruit more important grown in the world. On the other hand it is a very perishable fruit and its delivery to distant points is restricted due to short shelf life at environmental temperature. Food irradiation process is applied to fruits for their preservation, once it promotes disinfestation and even maturation retard, among other mechanisms. The Brazilian legislation permits the food irradiation and does not restrict the doses to be delivered. In order to verify eventual changes, sensorial evaluation is very important to study how irradiation affects the quality of the fruit and its acceptability. Mangoes were irradiated in a Cobalto-60 source, from the Radiation Technology Center, CTR, of IPEN/CNEN-SP at doses 0,5 kGy e 0,75 kGy. The sensorial evaluation was measured through Acceptance Test where irradiated samples were offered together with control sample to the tasters who answered their perception through hedonic scale. The parameters Color, Odor, Flavor and Texture were analyzed. Statistical analysis showed that only Odor parameter was different from control (sample irradiated at 0.5 kGy). Few tasters indicated that irradiated mangoes had fewer odors in relation to non-irradiated samples. (author)

  1. Sensorial evaluation of irradiated mangoes

    Energy Technology Data Exchange (ETDEWEB)

    Broisler, Paula Olhe; Cruz, Juliana Nunes da; Sabato, Susy Frey [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)]. E-mails: paulabroisler@hotmail.com; juliananc@ig.com.br; sfsabato@ipen.br

    2007-07-01

    Mango (Mangifera indica L.) is a tropical fruit of great economical relevance in the world, mainly for tropical countries like Brazil. It consists in the second tropical fruit more important grown in the world. On the other hand it is a very perishable fruit and its delivery to distant points is restricted due to short shelf life at environmental temperature. Food irradiation process is applied to fruits for their preservation, once it promotes disinfestation and even maturation retard, among other mechanisms. The Brazilian legislation permits the food irradiation and does not restrict the doses to be delivered. In order to verify eventual changes, sensorial evaluation is very important to study how irradiation affects the quality of the fruit and its acceptability. Mangoes were irradiated in a Cobalto-60 source, from the Radiation Technology Center, CTR, of IPEN/CNEN-SP at doses 0,5 kGy e 0,75 kGy. The sensorial evaluation was measured through Acceptance Test where irradiated samples were offered together with control sample to the tasters who answered their perception through hedonic scale. The parameters Color, Odor, Flavor and Texture were analyzed. Statistical analysis showed that only Odor parameter was different from control (sample irradiated at 0.5 kGy). Few tasters indicated that irradiated mangoes had fewer odors in relation to non-irradiated samples. (author)

  2. The function and failure of sensory predictions.

    Science.gov (United States)

    Bansal, Sonia; Ford, Judith M; Spering, Miriam

    2018-04-23

    Humans and other primates are equipped with neural mechanisms that allow them to automatically make predictions about future events, facilitating processing of expected sensations and actions. Prediction-driven control and monitoring of perceptual and motor acts are vital to normal cognitive functioning. This review provides an overview of corollary discharge mechanisms involved in predictions across sensory modalities and discusses consequences of predictive coding for cognition and behavior. Converging evidence now links impairments in corollary discharge mechanisms to neuropsychiatric symptoms such as hallucinations and delusions. We review studies supporting a prediction-failure hypothesis of perceptual and cognitive disturbances. We also outline neural correlates underlying prediction function and failure, highlighting similarities across the visual, auditory, and somatosensory systems. In linking basic psychophysical and psychophysiological evidence of visual, auditory, and somatosensory prediction failures to neuropsychiatric symptoms, our review furthers our understanding of disease mechanisms. © 2018 New York Academy of Sciences.

  3. Could information theory provide an ecological theory of sensory processing?

    Science.gov (United States)

    Atick, Joseph J

    2011-01-01

    The sensory pathways of animals are well adapted to processing a special class of signals, namely stimuli from the animal's environment. An important fact about natural stimuli is that they are typically very redundant and hence the sampled representation of these signals formed by the array of sensory cells is inefficient. One could argue for some animals and pathways, as we do in this review, that efficiency of information representation in the nervous system has several evolutionary advantages. Consequently, one might expect that much of the processing in the early levels of these sensory pathways could be dedicated towards recoding incoming signals into a more efficient form. In this review, we explore the principle of efficiency of information representation as a design principle for sensory processing. We give a preliminary discussion on how this principle could be applied in general to predict neural processing and then discuss concretely some neural systems where it recently has been shown to be successful. In particular, we examine the fly's LMC coding strategy and the mammalian retinal coding in the spatial, temporal and chromatic domains.

  4. Sensory hair cell regeneration in the zebrafish lateral line.

    Science.gov (United States)

    Lush, Mark E; Piotrowski, Tatjana

    2014-10-01

    Damage or destruction of sensory hair cells in the inner ear leads to hearing or balance deficits that can be debilitating, especially in older adults. Unfortunately, the damage is permanent, as regeneration of the inner ear sensory epithelia does not occur in mammals. Zebrafish and other non-mammalian vertebrates have the remarkable ability to regenerate sensory hair cells and understanding the molecular and cellular basis for this regenerative ability will hopefully aid us in designing therapies to induce regeneration in mammals. Zebrafish not only possess hair cells in the ear but also in the sensory lateral line system. Hair cells in both organs are functionally analogous to hair cells in the inner ear of mammals. The lateral line is a mechanosensory system found in most aquatic vertebrates that detects water motion and aids in predator avoidance, prey capture, schooling, and mating. Although hair cell regeneration occurs in both the ear and lateral line, most research to date has focused on the lateral line due to its relatively simple structure and accessibility. Here we review the recent discoveries made during the characterization of hair cell regeneration in zebrafish. Copyright © 2014 Wiley Periodicals, Inc.

  5. Olfaction and Pheromones: Uncanonical Sensory Influences and Bulbar Interactions

    Directory of Open Access Journals (Sweden)

    Víctor Vargas-Barroso

    2017-11-01

    Full Text Available The rodent main and accessory olfactory systems (AOS are considered functionally and anatomically segregated information-processing pathways. Each system is devoted to the detection of volatile odorants and pheromones, respectively. However, a growing number of evidences supports a cooperative interaction between them. For instance, at least four non-canonical receptor families (i.e., different from olfactory and vomeronasal receptor families have been recently discovered. These atypical receptor families are expressed in the sensory organs of the nasal cavity and furnish parallel processing-pathways that detect specific stimuli and mediate specific behaviors as well. Aside from the receptor and functional diversity of these sensory modalities, they converge into a poorly understood bulbar area at the intersection of the main- main olfactory bulb (MOB and accessory olfactory bulb (AOB that has been termed olfactory limbus (OL. Given the intimate association the OL with specialized glomeruli (i.e., necklace and modified glomeruli receiving uncanonical sensory afferences and its interactions with the MOB and AOB, the possibility that OL is a site of non-olfactory and atypical vomeronasal sensory decoding is discussed.

  6. Sensory conflict in motion sickness: An observer theory approach

    Science.gov (United States)

    Oman, Charles M.

    1989-01-01

    Motion sickness is the general term describing a group of common nausea syndromes originally attributed to motion-induced cerebral ischemia, stimulation of abdominal organ afferent, or overstimulation of the vestibular organs of the inner ear. Sea-, car-, and airsicknesses are the most commonly experienced examples. However, the discovery of other variants such as Cinerama-, flight simulator-, spectacle-, and space sickness in which the physical motion of the head and body is normal or absent has led to a succession of sensory conflict theories which offer a more comprehensive etiologic perspective. Implicit in the conflict theory is the hypothesis that neutral and/or humoral signals originate in regions of the brain subversing spatial orientation, and that these signals somehow traverse to other centers mediating sickness symptoms. Unfortunately, the present understanding of the neurophysiological basis of motion sickness is far from complete. No sensory conflict neuron or process has yet been physiologically identified. To what extent can the existing theory be reconciled with current knowledge of the physiology and pharmacology of nausea and vomiting. The stimuli which causes sickness, synthesizes a contemporary Observer Theory view of the Sensory Conflict hypothesis are reviewed, and a revised model for the dynamic coupling between the putative conflict signals and nausea magnitude estimates is presented. The use of quantitative models for sensory conflict offers a possible new approach to improving the design of visual and motion systems for flight simulators and other virtual environment display systems.

  7. SENSORY HAIR CELL REGENERATION IN THE ZEBRAFISH LATERAL LINE

    Science.gov (United States)

    Lush, Mark E.; Piotrowski, Tatjana

    2014-01-01

    Damage or destruction of sensory hair cells in the inner ear leads to hearing or balance deficits that can be debilitating, especially in older adults. Unfortunately, the damage is permanent, as regeneration of the inner ear sensory epithelia does not occur in mammals. Zebrafish and other non-mammalian vertebrates have the remarkable ability to regenerate sensory hair cells and understanding the molecular and cellular basis for this regenerative ability will hopefully aid us in designing therapies to induce regeneration in mammals. Zebrafish not only possess hair cells in the ear but also in the sensory lateral line system. Hair cells in both organs are functionally analogous to hair cells in the inner ear of mammals. The lateral line is a mechanosensory system found in most aquatic vertebrates that detects water motion and aids in predator avoidance, prey capture, schooling and mating. Although hair cell regeneration occurs in both the ear and lateral line, most research to date has focused on the lateral line due to its relatively simple structure and accessibility. Here we review the recent discoveries made during the characterization of hair cell regeneration in zebrafish. PMID:25045019

  8. Why do unusual novel foods like insects lack sensory appeal? Investigating the underlying sensory perceptions

    NARCIS (Netherlands)

    Tan Hui Shan, Grace; Tibboel, Claudia Joyce; Stieger, Markus

    2017-01-01

    Unusual novel foods like insects generally hold little sensory appeal for consumers, but little is known about the underlying sensory perceptions and how the properties of the food contribute to acceptance. This study examined the sensory perceptions of 3 unusual novel foods (lamb brain, frog

  9. Differential Survival between Visual Environments Supports a Role of Divergent Sensory Drive in Cichlid Fish Speciation.

    Science.gov (United States)

    Maan, Martine E; Seehausen, Ole; Groothuis, Ton G G

    2017-01-01

    Identifying the selective forces that initiate ecological speciation is a major challenge in evolutionary biology. Sensory drive has been implicated in speciation in various taxa, largely based on phenotype-environment correlations and signatures of selection in sensory genes. Here, we present a reciprocal transplant experiment revealing species differences in performance in alternative visual environments, consistent with speciation by divergent sensory drive. The closely related cichlids Pundamilia pundamilia and Pundamilia nyererei inhabit different visual environments in Lake Victoria and show associated differences in visual system properties. Mimicking the two light environments in the laboratory, we find a substantial reduction in survival of both species when reared in the other species' visual environment. This implies that the observed differences in Pundamilia color vision are indeed adaptive and substantiates the implicit assumption in sensory drive speciation models that divergent environmental selection is strong enough to drive divergence in sensory properties.

  10. Nontargeted metabolite profiles and sensory properties of strawberry cultivars grown both organically and conventionally.

    Science.gov (United States)

    Kårlund, Anna; Hanhineva, Kati; Lehtonen, Marko; Karjalainen, Reijo O; Sandell, Mari

    2015-01-28

    Strawberry (Fragaria × ananassa Duch.) contains many secondary metabolites potentially beneficial for human health, and several of these compounds contribute to strawberry sensory properties, as well. In this study, three strawberry cultivars grown both conventionally and organically were subjected to nontargeted metabolite profiling analysis with LC-qTOF-ESI-MS and to descriptive sensory evaluation by a trained panel. Combined metabolome and sensory data (PLS model) revealed that 79% variation in the metabolome explained 88% variation in the sensory profiles. Flavonoids and condensed and hydrolyzable tannins determined the orosensory properties, and fatty acids contributed to the odor attributes of strawberry. Overall, the results indicated that the chemical composition and sensory quality of strawberries grown in different cultivation systems vary mostly according to cultivar. Organic farming practices may enhance the accumulation of some plant metabolites in specific strawberry genotypes. Careful cultivar selection is a key factor for the improvement of nutritional quality and marketing value of organic strawberries.

  11. Ravages of Diabetes on Gastrointestinal Sensory-Motor Function: Implications for Pathophysiology and Treatment.

    Science.gov (United States)

    Gregersen, Hans; Liao, Donghua; Drewes, Anne Mohr; Drewes, Asbjørn Mohr; Zhao, Jingbo

    2016-02-01

    Symptoms related to functional and sensory abnormalities are frequently encountered in patients with diabetes mellitus. Most symptoms are associated with impaired gastric and intestinal function. In this review, we discuss basic concepts of sensory-motor dysfunction and how they relate to clinical findings and gastrointestinal abnormalities that are commonly seen in diabetes. In addition, we review techniques that are available for investigating the autonomic nervous system, neuroimaging and neurophysiology of sensory-motor function. Such technological advances, while not readily available in the clinical setting, may facilitate stratification and individualization of therapy in diabetic patients in the future. Unraveling the structural, mechanical, and sensory remodeling in diabetes disease is based on a multidisciplinary approach that can bridge the knowledge from a variety of scientific disciplines. The final goal is to increase the understanding of the damage to GI structures and to sensory processing of symptoms, in order to assist clinicians with developing an optimal mechanics based treatment.

  12. Sensory Cortical Plasticity Participates in the Epigenetic Regulation of Robust Memory Formation

    Science.gov (United States)

    Phan, Mimi L.; Bieszczad, Kasia M.

    2016-01-01

    Neuroplasticity remodels sensory cortex across the lifespan. A function of adult sensory cortical plasticity may be capturing available information during perception for memory formation. The degree of experience-dependent remodeling in sensory cortex appears to determine memory strength and specificity for important sensory signals. A key open question is how plasticity is engaged to induce different degrees of sensory cortical remodeling. Neural plasticity for long-term memory requires the expression of genes underlying stable changes in neuronal function, structure, connectivity, and, ultimately, behavior. Lasting changes in transcriptional activity may depend on epigenetic mechanisms; some of the best studied in behavioral neuroscience are DNA methylation and histone acetylation and deacetylation, which, respectively, promote and repress gene expression. One purpose of this review is to propose epigenetic regulation of sensory cortical remodeling as a mechanism enabling the transformation of significant information from experiences into content-rich memories of those experiences. Recent evidence suggests how epigenetic mechanisms regulate highly specific reorganization of sensory cortical representations that establish a widespread network for memory. Thus, epigenetic mechanisms could initiate events to establish exceptionally persistent and robust memories at a systems-wide level by engaging sensory cortical plasticity for gating what and how much information becomes encoded. PMID:26881129

  13. Sensory Cortical Plasticity Participates in the Epigenetic Regulation of Robust Memory Formation.

    Science.gov (United States)

    Phan, Mimi L; Bieszczad, Kasia M

    2016-01-01

    Neuroplasticity remodels sensory cortex across the lifespan. A function of adult sensory cortical plasticity may be capturing available information during perception for memory formation. The degree of experience-dependent remodeling in sensory cortex appears to determine memory strength and specificity for important sensory signals. A key open question is how plasticity is engaged to induce different degrees of sensory cortical remodeling. Neural plasticity for long-term memory requires the expression of genes underlying stable changes in neuronal function, structure, connectivity, and, ultimately, behavior. Lasting changes in transcriptional activity may depend on epigenetic mechanisms; some of the best studied in behavioral neuroscience are DNA methylation and histone acetylation and deacetylation, which, respectively, promote and repress gene expression. One purpose of this review is to propose epigenetic regulation of sensory cortical remodeling as a mechanism enabling the transformation of significant information from experiences into content-rich memories of those experiences. Recent evidence suggests how epigenetic mechanisms regulate highly specific reorganization of sensory cortical representations that establish a widespread network for memory. Thus, epigenetic mechanisms could initiate events to establish exceptionally persistent and robust memories at a systems-wide level by engaging sensory cortical plasticity for gating what and how much information becomes encoded.

  14. Sensory Cortical Plasticity Participates in the Epigenetic Regulation of Robust Memory Formation

    Directory of Open Access Journals (Sweden)

    Mimi L. Phan

    2016-01-01

    Full Text Available Neuroplasticity remodels sensory cortex across the lifespan. A function of adult sensory cortical plasticity may be capturing available information during perception for memory formation. The degree of experience-dependent remodeling in sensory cortex appears to determine memory strength and specificity for important sensory signals. A key open question is how plasticity is engaged to induce different degrees of sensory cortical remodeling. Neural plasticity for long-term memory requires the expression of genes underlying stable changes in neuronal function, structure, connectivity, and, ultimately, behavior. Lasting changes in transcriptional activity may depend on epigenetic mechanisms; some of the best studied in behavioral neuroscience are DNA methylation and histone acetylation and deacetylation, which, respectively, promote and repress gene expression. One purpose of this review is to propose epigenetic regulation of sensory cortical remodeling as a mechanism enabling the transformation of significant information from experiences into content-rich memories of those experiences. Recent evidence suggests how epigenetic mechanisms regulate highly specific reorganization of sensory cortical representations that establish a widespread network for memory. Thus, epigenetic mechanisms could initiate events to establish exceptionally persistent and robust memories at a systems-wide level by engaging sensory cortical plasticity for gating what and how much information becomes encoded.

  15. Multisensory integration, sensory substitution and visual rehabilitation

    DEFF Research Database (Denmark)

    Proulx, Michael J; Ptito, Maurice; Amedi, Amir

    2014-01-01

    Sensory substitution has advanced remarkably over the past 35 years since first introduced to the scientific literature by Paul Bach-y-Rita. In this issue dedicated to his memory, we describe a collection of reviews that assess the current state of neuroscience research on sensory substitution...

  16. ASIC3 channels in multimodal sensory perception.

    Science.gov (United States)

    Li, Wei-Guang; Xu, Tian-Le

    2011-01-19

    Acid-sensing ion channels (ASICs), which are members of the sodium-selective cation channels belonging to the epithelial sodium channel/degenerin (ENaC/DEG) family, act as membrane-bound receptors for extracellular protons as well as nonproton ligands. At least five ASIC subunits have been identified in mammalian neurons, which form both homotrimeric and heterotrimeric channels. The highly proton sensitive ASIC3 channels are predominantly distributed in peripheral sensory neurons, correlating with their roles in multimodal sensory perception, including nociception, mechanosensation, and chemosensation. Different from other ASIC subunit composing ion channels, ASIC3 channels can mediate a sustained window current in response to mild extracellular acidosis (pH 7.3-6.7), which often occurs accompanied by many sensory stimuli. Furthermore, recent evidence indicates that the sustained component of ASIC3 currents can be enhanced by nonproton ligands including the endogenous metabolite agmatine. In this review, we first summarize the growing body of evidence for the involvement of ASIC3 channels in multimodal sensory perception and then discuss the potential mechanisms underlying ASIC3 activation and mediation of sensory perception, with a special emphasis on its role in nociception. We conclude that ASIC3 activation and modulation by diverse sensory stimuli represent a new avenue for understanding the role of ASIC3 channels in sensory perception. Furthermore, the emerging implications of ASIC3 channels in multiple sensory dysfunctions including nociception allow the development of new pharmacotherapy.

  17. CHEMICAL, SENSORY AND MICROBIOLOGICAL CHANGES OF ...

    African Journals Online (AJOL)

    Dr Adesola Osibona

    Presently, there are numerous problems facing the field of fisheries, some of which are related to the keeping ... The two main methods of assessing fish quality are sensory and non-sensory ... MATERIALS AND METHODS. Sample ..... The initial lag phase of micro-organisms in the stored fish was followed by an increase in ...

  18. Sensory testing of the human gastrointestinal tract.

    NARCIS (Netherlands)

    Brock, C.; Arendt-Nielsen, L.; Wilder-Smith, O.H.G.; Drewes, A.M.

    2009-01-01

    The objective of this appraisal is to shed light on the various approaches to screen sensory information in the human gut. Understanding and characterization of sensory symptoms in gastrointestinal disorders is poor. Experimental methods allowing the investigator to control stimulus intensity and

  19. Sensory neuropathy in two Border collie puppies.

    Science.gov (United States)

    Vermeersch, K; Van Ham, L; Braund, K G; Bhatti, S; Tshamala, M; Chiers, K; Schrauwen, E

    2005-06-01

    A peripheral sensory neuropathy was diagnosed in two Border collie puppies. Neurological, electrophysiological and histopathological examinations suggested a purely sensory neuropathy with mainly distal involvement. Urinary incontinence was observed in one of the puppies and histological examination of the vagus nerve revealed degenerative changes. An inherited disorder was suspected.

  20. Artificial sensory organs: latest progress.

    Science.gov (United States)

    Nakamura, Tatsuo; Inada, Yuji; Shigeno, Keiji

    2018-03-01

    This study introduces the latest progress on the study of artificial sensory organs, with a special emphasis on the clinical results of artificial nerves and the concept of in situ tissue engineering. Peripheral nerves have a strong potential for regeneration. An artificial nerve uses this potential to recover a damaged peripheral nerve. The polyglycolic acid collagen tube (PGA-C tube) is a bio-absorbable tube stuffed with collagen of multi-chamber structure that consists of thin collagen films. The clinical application of the PGA-C tube began in 2002 in Japan. The number of PGA-C tubes used is now beyond 300, and satisfactory results have been reported on peripheral nerve repairs. This PGA-C tube is also effective for patients suffering from neuropathic pain.

  1. [Sensory integration: hierarchy and synchronization].

    Science.gov (United States)

    Kriukov, V I

    2005-01-01

    This is the first in the series of mini-reviews devoted to the basic problems and most important effects of attention in terms of neuronal modeling. We believe that the absence of the unified view on wealth of new date on attention is the main obstacle for further understanding of higher nervous activity. The present work deals with the main ground problem of reconciling two competing architectures designed to integrate the sensory information in the brain. The other mini-reviews will be concerned with the remaining five or six problems of attention, all of them to be ultimately resolved uniformly in the framework of small modification of dominant model of attention and memory.

  2. Short-term depression and transient memory in sensory cortex.

    Science.gov (United States)

    Gillary, Grant; Heydt, Rüdiger von der; Niebur, Ernst

    2017-12-01

    Persistent neuronal activity is usually studied in the context of short-term memory localized in central cortical areas. Recent studies show that early sensory areas also can have persistent representations of stimuli which emerge quickly (over tens of milliseconds) and decay slowly (over seconds). Traditional positive feedback models cannot explain sensory persistence for at least two reasons: (i) They show attractor dynamics, with transient perturbations resulting in a quasi-permanent change of system state, whereas sensory systems return to the original state after a transient. (ii) As we show, those positive feedback models which decay to baseline lose their persistence when their recurrent connections are subject to short-term depression, a common property of excitatory connections in early sensory areas. Dual time constant network behavior has also been implemented by nonlinear afferents producing a large transient input followed by much smaller steady state input. We show that such networks require unphysiologically large onset transients to produce the rise and decay observed in sensory areas. Our study explores how memory and persistence can be implemented in another model class, derivative feedback networks. We show that these networks can operate with two vastly different time courses, changing their state quickly when new information is coming in but retaining it for a long time, and that these capabilities are robust to short-term depression. Specifically, derivative feedback networks with short-term depression that acts differentially on positive and negative feedback projections are capable of dynamically changing their time constant, thus allowing fast onset and slow decay of responses without requiring unrealistically large input transients.

  3. Diminished auditory sensory gating during active auditory verbal hallucinations.

    Science.gov (United States)

    Thoma, Robert J; Meier, Andrew; Houck, Jon; Clark, Vincent P; Lewine, Jeffrey D; Turner, Jessica; Calhoun, Vince; Stephen, Julia

    2017-10-01

    Auditory sensory gating, assessed in a paired-click paradigm, indicates the extent to which incoming stimuli are filtered, or "gated", in auditory cortex. Gating is typically computed as the ratio of the peak amplitude of the event related potential (ERP) to a second click (S2) divided by the peak amplitude of the ERP to a first click (S1). Higher gating ratios are purportedly indicative of incomplete suppression of S2 and considered to represent sensory processing dysfunction. In schizophrenia, hallucination severity is positively correlated with gating ratios, and it was hypothesized that a failure of sensory control processes early in auditory sensation (gating) may represent a larger system failure within the auditory data stream; resulting in auditory verbal hallucinations (AVH). EEG data were collected while patients (N=12) with treatment-resistant AVH pressed a button to indicate the beginning (AVH-on) and end (AVH-off) of each AVH during a paired click protocol. For each participant, separate gating ratios were computed for the P50, N100, and P200 components for each of the AVH-off and AVH-on states. AVH trait severity was assessed using the Psychotic Symptoms Rating Scales AVH Total score (PSYRATS). The results of a mixed model ANOVA revealed an overall effect for AVH state, such that gating ratios were significantly higher during the AVH-on state than during AVH-off for all three components. PSYRATS score was significantly and negatively correlated with N100 gating ratio only in the AVH-off state. These findings link onset of AVH with a failure of an empirically-defined auditory inhibition system, auditory sensory gating, and pave the way for a sensory gating model of AVH. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Age-Related Sensory Impairments and Risk of Cognitive Impairment

    Science.gov (United States)

    Fischer, Mary E; Cruickshanks, Karen J.; Schubert, Carla R; Pinto, Alex A; Carlsson, Cynthia M; Klein, Barbara EK; Klein, Ronald; Tweed, Ted S.

    2016-01-01

    Background/Objectives To evaluate the associations of sensory impairments with the 10-year risk of cognitive impairment. Previous work has primarily focused on the relationship between a single sensory system and cognition. Design The Epidemiology of Hearing Loss Study (EHLS) is a longitudinal, population-based study of aging in the Beaver Dam, WI community. Baseline examinations were conducted in 1993 and follow-up exams have been conducted every 5 years. Setting General community Participants EHLS members without cognitive impairment at EHLS-2 (1998–2000). There were 1,884 participants (mean age = 66.7 years) with complete EHLS-2 sensory data and follow-up information. Measurements Cognitive impairment was a Mini-Mental State Examination score of impairment was a pure-tone average of hearing thresholds (0.5, 1, 2 and 4 kHz) of > 25 decibel Hearing Level in either ear. Visual impairment was Pelli-Robson contrast sensitivity of impairment was a San Diego Odor Identification Test score of impairment were independently associated with cognitive impairment risk [Hearing: Hazard Ratio (HR) = 1.90, 95% Confidence Interval (C.I.) = 1.11, 3.26; Vision: HR = 2.05, 95% C.I. = 1.24, 3.38; Olfaction: HR = 3.92, 95% C.I. = 2.45, 6.26]. However, 85% with hearing impairment, 81% with visual impairment, and 76% with olfactory impairment did not develop cognitive impairment during follow-up. Conclusion The relationship between sensory impairment and cognitive impairment was not unique to one sensory system suggesting sensorineural health may be a marker of brain aging. The development of a combined sensorineurocognitive measure may be useful in uncovering mechanisms of healthy brain aging. PMID:27611845

  5. Sensory Metrics of Neuromechanical Trust.

    Science.gov (United States)

    Softky, William; Benford, Criscillia

    2017-09-01

    that individuals can improve sensory and sociosensory resolution through deliberate sensory reintegration practices. We conclude that we humans are the victims of our own success, our hands so skilled they fill the world with captivating things, our eyes so innocent they follow eagerly.

  6. Multistability in perception: binding sensory modalities, an overview.

    Science.gov (United States)

    Schwartz, Jean-Luc; Grimault, Nicolas; Hupé, Jean-Michel; Moore, Brian C J; Pressnitzer, Daniel

    2012-04-05

    This special issue presents research concerning multistable perception in different sensory modalities. Multistability occurs when a single physical stimulus produces alternations between different subjective percepts. Multistability was first described for vision, where it occurs, for example, when different stimuli are presented to the two eyes or for certain ambiguous figures. It has since been described for other sensory modalities, including audition, touch and olfaction. The key features of multistability are: (i) stimuli have more than one plausible perceptual organization; (ii) these organizations are not compatible with each other. We argue here that most if not all cases of multistability are based on competition in selecting and binding stimulus information. Binding refers to the process whereby the different attributes of objects in the environment, as represented in the sensory array, are bound together within our perceptual systems, to provide a coherent interpretation of the world around us. We argue that multistability can be used as a method for studying binding processes within and across sensory modalities. We emphasize this theme while presenting an outline of the papers in this issue. We end with some thoughts about open directions and avenues for further research.

  7. Multistability in perception: binding sensory modalities, an overview

    Science.gov (United States)

    Schwartz, Jean-Luc; Grimault, Nicolas; Hupé, Jean-Michel; Moore, Brian C. J.; Pressnitzer, Daniel

    2012-01-01

    This special issue presents research concerning multistable perception in different sensory modalities. Multistability occurs when a single physical stimulus produces alternations between different subjective percepts. Multistability was first described for vision, where it occurs, for example, when different stimuli are presented to the two eyes or for certain ambiguous figures. It has since been described for other sensory modalities, including audition, touch and olfaction. The key features of multistability are: (i) stimuli have more than one plausible perceptual organization; (ii) these organizations are not compatible with each other. We argue here that most if not all cases of multistability are based on competition in selecting and binding stimulus information. Binding refers to the process whereby the different attributes of objects in the environment, as represented in the sensory array, are bound together within our perceptual systems, to provide a coherent interpretation of the world around us. We argue that multistability can be used as a method for studying binding processes within and across sensory modalities. We emphasize this theme while presenting an outline of the papers in this issue. We end with some thoughts about open directions and avenues for further research. PMID:22371612

  8. Sensory memory during physiological aging indexed by mismatch negativity (MMN).

    Science.gov (United States)

    Ruzzoli, Manuela; Pirulli, Cornelia; Brignani, Debora; Maioli, Claudio; Miniussi, Carlo

    2012-03-01

    Physiological aging affects early sensory-perceptual processes. The aim of this experiment was to evaluate changes in auditory sensory memory in physiological aging using the Mismatch Negativity (MMN) paradigm as index. The MMN is a marker recorded through the electroencephalogram and is used to evaluate the integrity of the memory system. We adopted a new, faster paradigm to look for differences between 3 groups of subjects of different ages (young, middle age and older adults) as a function of short or long intervals between stimuli. We found that older adults did not show MMN at long interval condition and that the duration of MMN varied according to the participants' age. The current study provides electrophysiological evidence supporting the theory that the encoding of stimuli is preserved during normal aging, whereas the maintenance of sensory memory is impaired. Considering the advantage offered by the MMN paradigm used here, these data might be a useful reference point for the assessment of auditory sensory memory in pathological aging (e.g., in neurodegenerative diseases). Copyright © 2012 Elsevier Inc. All rights reserved.

  9. Remapping high-capacity, pre-attentive, fragile sensory memory.

    Science.gov (United States)

    Zerr, Paul; Gayet, Surya; Mulder, Kees; Pinto, Yaïr; Sligte, Ilja; Van der Stigchel, Stefan

    2017-11-21

    Humans typically make several saccades per second. This provides a challenge for the visual system as locations are largely coded in retinotopic (eye-centered) coordinates. Spatial remapping, the updating of retinotopic location coordinates of items in visuospatial memory, is typically assumed to be limited to robust, capacity-limited and attention-demanding working memory (WM). Are pre-attentive, maskable, sensory memory representations (e.g. fragile memory, FM) also remapped? We directly compared trans-saccadic WM (tWM) and trans-saccadic FM (tFM) in a retro-cue change-detection paradigm. Participants memorized oriented rectangles, made a saccade and reported whether they saw a change in a subsequent display. On some trials a retro-cue indicated the to-be-tested item prior to probe onset. This allowed sensory memory items to be included in the memory capacity estimate. The observed retro-cue benefit demonstrates a tFM capacity considerably above tWM. This provides evidence that some, if not all sensory memory was remapped to spatiotopic (world-centered, task-relevant) coordinates. In a second experiment, we show backward masks to be effective in retinotopic as well as spatiotopic coordinates, demonstrating that FM was indeed remapped to world-centered coordinates. Together this provides conclusive evidence that trans-saccadic spatial remapping is not limited to higher-level WM processes but also occurs for sensory memory representations.

  10. Measurement of pharyngeal sensory cortical processing: technique and physiologic implications

    Directory of Open Access Journals (Sweden)

    Ringelstein E Bernd

    2009-07-01

    Full Text Available Abstract Background Dysphagia is a major complication of different diseases affecting both the central and peripheral nervous system. Pharyngeal sensory impairment is one of the main features of neurogenic dysphagia. Therefore an objective technique to examine the cortical processing of pharyngeal sensory input would be a helpful diagnostic tool in this context. We developed a simple paradigm to perform pneumatic stimulation to both sides of the pharyngeal wall. Whole-head MEG was employed to study changes in cortical activation during this pharyngeal stimulation in nine healthy subjects. Data were analyzed by means of synthetic aperture magnetometry (SAM and the group analysis of individual SAM data was performed using a permutation test. Results Our results revealed bilateral activation of the caudolateral primary somatosensory cortex following sensory pharyngeal stimulation with a slight lateralization to the side of stimulation. Conclusion The method introduced here is simple and easy to perform and might be applicable in the clinical setting. The results are in keeping with previous findings showing bihemispheric involvement in the complex task of sensory pharyngeal processing. They might also explain changes in deglutition after hemispheric strokes. The ipsilaterally lateralized processing is surprising and needs further investigation.

  11. The neuroecology of cartilaginous fishes: sensory strategies for survival.

    Science.gov (United States)

    Collin, Shaun P

    2012-01-01

    As apex predators, chondrichthyans, or cartilaginous fishes, hold an important position within a range of aquatic ecosystems and influence the balance between species' abundance and biodiversity. Having been in existence for over 400 million years and representing the earliest stages of the evolution of jawed vertebrates, this group also covers a diverse range of eco-morphotypes, occupying both marine and freshwater habitats. The class Chondrichthyes is divided into two subclasses: the Elasmobranchii (sharks, skates, and rays) and the Holocephali (elephant sharks and chimaeras). However, many of their life history traits, such as low fecundity, the production of small numbers of highly precocious young, slow growth rates, and late maturity, make them highly susceptible to human exploitation. To mitigate the negative effects of human impacts, it is important that we understand the sensory strategies that elasmobranchs use for navigating within their environment, forming reproductive aggregations, feeding, and even communicating. One approach to investigate the sensory bases of their behavior is to examine the peripheral sense organs mediating vision, olfaction, gustation, lateral line, electroreception, and audition in a large range of species in order to identify specific adaptations, the range of sensitivity thresholds, and the compromise between sensory spatial resolution and sensitivity. In addition, we can quantitatively assess the convergence of sensory input to the central nervous system and the relative importance of different sensory modalities. Using a comparative approach and often a combination of anatomical, electrophysiological, and molecular techniques, significant variation has been identified in the spatial and chromatic sampling of the photoreceptors in the eye, the surface area and the number of olfactory lamellae within the nasal cavity, the level of gustatory sampling within the oral cavity, the type and innervation of neuromasts of the lateral

  12. Sensory profile of eleven peach cultivars

    Directory of Open Access Journals (Sweden)

    Francine Lorena Cuquel

    2012-03-01

    Full Text Available The goal of this study was to evaluate the sensory profile of eleven peach cultivars grown in an experimental orchard located in the city of Lapa (PR, Brazil in two seasons. The peach cultivars analyzed were Aurora I, Chimarrita, Chiripá, Coral, Eldorado, Granada, Leonense, Maciel, Marli, Premier, and Vanguarda. The sensory analysis was performed by previously trained panelists; 20 of them in the first season and 10 in the second season. The sensory evaluation was performed using Quantitative Descriptive Analysis, in which the following attributes were measured: appearance, aroma, flesh color, flesh firmness, flavor, and juiciness. The results showed preference for sweet, soft, and juicy fruits. Chimarrita, Chiripá, and Coral fruits showed better sensorial performance than the other peach cultivars. It was also verified that the analysis of the attributes aroma, flesh firmness, and flavor is enough for performing the sensory profile of peach fruits for in natura consumption.

  13. Sensory feedback in upper limb prosthetics.

    Science.gov (United States)

    Antfolk, Christian; D'Alonzo, Marco; Rosén, Birgitta; Lundborg, Göran; Sebelius, Fredrik; Cipriani, Christian

    2013-01-01

    One of the challenges facing prosthetic designers and engineers is to restore the missing sensory function inherit to hand amputation. Several different techniques can be employed to provide amputees with sensory feedback: sensory substitution methods where the recorded stimulus is not only transferred to the amputee, but also translated to a different modality (modality-matched feedback), which transfers the stimulus without translation and direct neural stimulation, which interacts directly with peripheral afferent nerves. This paper presents an overview of the principal works and devices employed to provide upper limb amputees with sensory feedback. The focus is on sensory substitution and modality matched feedback; the principal features, advantages and disadvantages of the different methods are presented.

  14. Sensory quality criteria for five fish species

    DEFF Research Database (Denmark)

    Warm, Karin; Nielsen, Jette; Hyldig, Grethe

    2000-01-01

    Sensory profiling has been used to develop one sensory vocabulary for five fish species: cod (Gadus morhua), saithe (Pollachius virens), rainbow trout (Salmo gardineri), herring (Clupea harengus) and flounder (Platichthys flessus). A nine- member trained panel assessed 18 samples with variation i...... variation and by presenting references, panel discussions and interpreting plots from multivariate data analysis. The developed profile can be used as a sensory wheel for these species, and with minor changes it may be adapted to similar species......Sensory profiling has been used to develop one sensory vocabulary for five fish species: cod (Gadus morhua), saithe (Pollachius virens), rainbow trout (Salmo gardineri), herring (Clupea harengus) and flounder (Platichthys flessus). A nine- member trained panel assessed 18 samples with variation...

  15. Enhancement of electromechanical manipulator performance by external sensory feedback

    International Nuclear Information System (INIS)

    Um, Taejun; Yoon, Jisup; Jung, Wootae; Lee, Jaesol.

    1990-01-01

    The electromechanical manipulator (EMM) is widely used in nuclear facilities because of its strength and mechanical reliability. Nevertheless, the lack of internal position or force feedback makes it unsuitable for many tasks that require a high level of dexterity. At the remote handling department of Korea Atomic Energy Research Institute, a series of research and development (R and D) activities was conducted to provide a higher degree of intelligence to the EMM with the aid of external sensory devices. These R and D activities focus on remote viewing and remote measurement in radioactive environments. As a result, an improved EMM system was achieved that incorporates various sensory devices such as a motion tracking system and a laser vision system. This paper presents detailed technical descriptions of these sensors and test results

  16. 多感官训练系统培养自闭症儿童交往能力的个案研究%On Cultivating Communicative Ability for Children Suffered from Autism with Multi-Sensory Training System

    Institute of Scientific and Technical Information of China (English)

    李亚华

    2014-01-01

    Known as autism, it is a developmental d isorder pervasive in infant period. Children with autism are indifferent to others. In addition to contacting with the familiar person, generally, they do not contact with strangers. Although the autistic children can understand language of their parents and teachers, but most of the time, they won't show active desire to act. To help children with autism improving interpersonal skills, with the help of multi sensory comprehensive training system in listening, visual, and tactile training, it can enhance the communication between the teacher and children with autism, and promote exchange between students with autism children, thus children with autism can express their ideas actively.%自闭症又称孤独症,是起病于婴幼儿期的一种广泛发育障碍。患有自闭症的儿童感情淡漠,除了能够与熟悉的人进行交往外,一般不会和陌生人交往。虽然自闭症儿童与能够听懂他们语言的家长、教师在一起时,会有一定的交往行为表现,但大多数时候他们不会表现出主动性交往行为。为帮助自闭症儿童改善人际交往能力,借助多感官综合训练系统中的听、视、触觉训练,增强老师与自闭症孩子的沟通,促进学生与自闭症孩子的交流,使之不愿交流为主动表达想法。

  17. Sensory nerve action potentials and sensory perception in women with arthritis of the hand.

    Science.gov (United States)

    Calder, Kristina M; Martin, Alison; Lydiate, Jessica; MacDermid, Joy C; Galea, Victoria; MacIntyre, Norma J

    2012-05-10

    Arthritis of the hand can limit a person's ability to perform daily activities. Whether or not sensory deficits contribute to the disability in this population remains unknown. The primary purpose of this study was to determine if women with osteoarthritis (OA) or rheumatoid arthritis (RA) of the hand have sensory impairments. Sensory function in the dominant hand of women with hand OA or RA and healthy women was evaluated by measuring sensory nerve action potentials (SNAPs) from the median, ulnar and radial nerves, sensory mapping (SM), and vibratory and current perception thresholds (VPT and CPT, respectively) of the second and fifth digits. All SNAP amplitudes were significantly lower for the hand OA and hand RA groups compared with the healthy group (p sensory fibers in the median, ulnar and radial nerves. Less apparent were losses in conduction speed or sensory perception.

  18. Sensory perception: lessons from synesthesia: using synesthesia to inform the understanding of sensory perception.

    Science.gov (United States)

    Harvey, Joshua Paul

    2013-06-01

    Synesthesia, the conscious, idiosyncratic, repeatable, and involuntary sensation of one sensory modality in response to another, is a condition that has puzzled both researchers and philosophers for centuries. Much time has been spent proving the condition's existence as well as investigating its etiology, but what can be learned from synesthesia remains a poorly discussed topic. Here, synaesthesia is presented as a possible answer rather than a question to the current gaps in our understanding of sensory perception. By first appreciating the similarities between normal sensory perception and synesthesia, one can use what is known about synaesthesia, from behavioral and imaging studies, to inform our understanding of "normal" sensory perception. In particular, in considering synesthesia, one can better understand how and where the different sensory modalities interact in the brain, how different sensory modalities can interact without confusion - the binding problem - as well as how sensory perception develops.

  19. Genetics Home Reference: hereditary sensory neuropathy type IA

    Science.gov (United States)

    ... sensory neuropathy type IA Hereditary sensory neuropathy type IA Printable PDF Open All Close All Enable Javascript ... expand/collapse boxes. Description Hereditary sensory neuropathy type IA is a condition characterized by nerve abnormalities in ...

  20. A neuron-astrocyte transistor-like model for neuromorphic dressed neurons.

    Science.gov (United States)

    Valenza, G; Pioggia, G; Armato, A; Ferro, M; Scilingo, E P; De Rossi, D

    2011-09-01

    Experimental evidences on the role of the synaptic glia as an active partner together with the bold synapse in neuronal signaling and dynamics of neural tissue strongly suggest to investigate on a more realistic neuron-glia model for better understanding human brain processing. Among the glial cells, the astrocytes play a crucial role in the tripartite synapsis, i.e. the dressed neuron. A well-known two-way astrocyte-neuron interaction can be found in the literature, completely revising the purely supportive role for the glia. The aim of this study is to provide a computationally efficient model for neuron-glia interaction. The neuron-glia interactions were simulated by implementing the Li-Rinzel model for an astrocyte and the Izhikevich model for a neuron. Assuming the dressed neuron dynamics similar to the nonlinear input-output characteristics of a bipolar junction transistor, we derived our computationally efficient model. This model may represent the fundamental computational unit for the development of real-time artificial neuron-glia networks opening new perspectives in pattern recognition systems and in brain neurophysiology. Copyright © 2011 Elsevier Ltd. All rights reserved.