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.

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.

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

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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

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

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.

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...

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...

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.

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.

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

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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.

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.

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).

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.

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.

A bidirectional brain-machine interface featuring a neuromorphic hardware decoder

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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.

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.

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

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.

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

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.

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.

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.

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.

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)

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.

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

Neuromodulated Synaptic Plasticity on the SpiNNaker Neuromorphic System

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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.

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.

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.

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.

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.

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 ...

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.

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.

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.

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.

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.

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.

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)

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...

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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...

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.

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.

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.

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.

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

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.

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.

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.

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

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.

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.

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

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

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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.

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

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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

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.

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

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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.

Binary Associative Memories as a Benchmark for Spiking Neuromorphic Hardware

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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.

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

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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.

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

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.

Convolutional networks for fast, energy-efficient neuromorphic computing.

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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.

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 ...

Selective Attention in Multi-Chip Address-Event Systems

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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.

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.

Large-scale simulations of plastic neural networks on neuromorphic hardware

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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.

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

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.

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

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....

Nonvolatile Memory Materials for Neuromorphic Intelligent Machines.

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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.

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.

A Robust Sound Perception Model Suitable for Neuromorphic Implementation

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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.

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.

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

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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

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.

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.

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.

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...

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.

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

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.

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.

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).

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.

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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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...

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...

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.

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.

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.

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.

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

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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.

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

[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.

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.

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)

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.

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...

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.

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.

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.

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)

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.

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.

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.

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.

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

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 ...

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.

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...

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)

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.

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.

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.

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....

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.

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.

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

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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.

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.

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)

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.

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.

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.

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®.

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.

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.

A light-stimulated synaptic device based on graphene hybrid phototransistor

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Qin, Shuchao; Wang, Fengqiu; Liu, Yujie; Wan, Qing; Wang, Xinran; Xu, Yongbing; Shi, Yi; Wang, Xiaomu; Zhang, Rong

2017-09-01

Neuromorphic chips refer to an unconventional computing architecture that is modelled on biological brains. They are increasingly employed for processing sensory data for machine vision, context cognition, and decision making. Despite rapid advances, neuromorphic computing has remained largely an electronic technology, making it a challenge to access the superior computing features provided by photons, or to directly process vision data that has increasing importance to artificial intelligence. Here we report a novel light-stimulated synaptic device based on a graphene-carbon nanotube hybrid phototransistor. Significantly, the device can respond to optical stimuli in a highly neuron-like fashion and exhibits flexible tuning of both short- and long-term plasticity. These features combined with the spatiotemporal processability make our device a capable counterpart to today’s electrically-driven artificial synapses, with superior reconfigurable capabilities. In addition, our device allows for generic optical spike processing, which provides a foundation for more sophisticated computing. The silicon-compatible, multifunctional photosensitive synapse opens up a new opportunity for neural networks enabled by photonics and extends current neuromorphic systems in terms of system complexities and functionalities.

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.

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.

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

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.

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...

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

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

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.

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.

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...

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

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.

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.

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.

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.

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.

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.

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

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

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.

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.

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)

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

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.

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.

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.

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

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.

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.

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.

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)

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.

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.

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

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

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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.

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...

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.

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.

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.

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.

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.

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.

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...

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.

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

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...

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

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

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

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.

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.

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

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

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...

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.

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.

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.

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)

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

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.

Uranium-induced sensory alterations in the zebrafish Danio rerio

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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.

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.

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.

A silicon central pattern generator controls locomotion in vivo.

Science.gov (United States)

Vogelstein, R J; Tenore, F; Guevremont, L; Etienne-Cummings, R; Mushahwar, V K

2008-09-01

We present a neuromorphic silicon chip that emulates the activity of the biological spinal central pattern generator (CPG) and creates locomotor patterns to support walking. The chip implements ten integrate-and-fire silicon neurons and 190 programmable digital-to-analog converters that act as synapses. This architecture allows for each neuron to make synaptic connections to any of the other neurons as well as to any of eight external input signals and one tonic bias input. The chip's functionality is confirmed by a series of experiments in which it controls the motor output of a paralyzed animal in real-time and enables it to walk along a three-meter platform. The walking is controlled under closed-loop conditions with the aide of sensory feedback that is recorded from the animal's legs and fed into the silicon CPG. Although we and others have previously described biomimetic silicon locomotor control systems for robots, this is the first demonstration of a neuromorphic device that can replace some functions of the central nervous system in vivo.

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.

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

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.

Peptidomics and Secretomics of the Mammalian Peripheral Sensory-Motor System

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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.

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

Anterograde transneuronal viral tract tracing reveals central sensory circuits from brown fat and sensory denervation alters its thermogenic responses.

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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.

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

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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.

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.

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

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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.

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.

Neuromorphic circuits impart a sense of touch

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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.

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.

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.

Anti-hebbian spike-timing-dependent plasticity and adaptive sensory processing.

Science.gov (United States)

Roberts, Patrick D; Leen, Todd K

2010-01-01

Adaptive sensory processing influences the central nervous system's interpretation of incoming sensory information. One of the functions of this adaptive sensory processing is to allow the nervous system to ignore predictable sensory information so that it may focus on important novel information needed to improve performance of specific tasks. The mechanism of spike-timing-dependent plasticity (STDP) has proven to be intriguing in this context because of its dual role in long-term memory and ongoing adaptation to maintain optimal tuning of neural responses. Some of the clearest links between STDP and adaptive sensory processing have come from in vitro, in vivo, and modeling studies of the electrosensory systems of weakly electric fish. Plasticity in these systems is anti-Hebbian, so that presynaptic inputs that repeatedly precede, and possibly could contribute to, a postsynaptic neuron's firing are weakened. The learning dynamics of anti-Hebbian STDP learning rules are stable if the timing relations obey strict constraints. The stability of these learning rules leads to clear predictions of how functional consequences can arise from the detailed structure of the plasticity. Here we review the connection between theoretical predictions and functional consequences of anti-Hebbian STDP, focusing on adaptive processing in the electrosensory system of weakly electric fish. After introducing electrosensory adaptive processing and the dynamics of anti-Hebbian STDP learning rules, we address issues of predictive sensory cancelation and novelty detection, descending control of plasticity, synaptic scaling, and optimal sensory tuning. We conclude with examples in other systems where these principles may apply.

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.

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.

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.

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

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.

A pilot study of sensory feedback by transcutaneous electrical nerve stimulation to improve manipulation deficit caused by severe sensory loss after stroke.

Science.gov (United States)

Kita, Kahori; Otaka, Yohei; Takeda, Kotaro; Sakata, Sachiko; Ushiba, Junichi; Kondo, Kunitsugu; Liu, Meigen; Osu, Rieko

2013-06-13

Sensory disturbance is common following stroke and can exacerbate functional deficits, even in patients with relatively good motor function. In particular, loss of appropriate sensory feedback in severe sensory loss impairs manipulation capability. We hypothesized that task-oriented training with sensory feedback assistance would improve manipulation capability even without sensory pathway recovery. We developed a system that provides sensory feedback by transcutaneous electrical nerve stimulation (SENS) for patients with sensory loss, and investigated the feasibility of the system in a stroke patient with severe sensory impairment and mild motor deficit. The electrical current was modulated by the force exerted by the fingertips so as to allow the patient to identify the intensity. The patient had severe sensory loss due to a right thalamic hemorrhage suffered 27 months prior to participation in the study. The patient first practiced a cylindrical grasp task with SENS for 1 hour daily over 29 days. Pressure information from the affected thumb was fed back to the unaffected shoulder. The same patient practiced a tip pinch task with SENS for 1 hour daily over 4 days. Pressure information from the affected thumb and index finger was fed back to the unaffected and affected shoulders, respectively. We assessed the feasibility of SENS and examined the improvement of manipulation capability after training with SENS. The fluctuation in fingertip force during the cylindrical grasp task gradually decreased as the training progressed. The patient was able to maintain a stable grip force after training, even without SENS. Pressure exerted by the tip pinch of the affected hand was unstable before intervention with SENS compared with that of the unaffected hand. However, they were similar to each other immediately after SENS was initiated, suggesting that the somatosensory information improved tip pinch performance. The patient's manipulation capability assessed by the Box

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.

[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.

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

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.

VLSI implementation of a 2.8 Gevent/s packet based AER interface with routing and event sorting functionality

Directory of Open Access Journals (Sweden)

Stefan eScholze

2011-10-01

Full Text Available State-of-the-art large scale neuromorphic systems require sophisticated spike event communication between units of the neural network. We present a high-speed communication infrastructure for a waferscale neuromorphic system, based on application-specific neuromorphic communication ICs in an FPGA-maintained environment. The ICs implement configurable axonal delays, as required for certain types of dynamic processing or for emulating spike based learning among distant cortical areas. Measurements are presented which show the efficacy of these delays in influencing behaviour of neuromorphic benchmarks. The specialized, dedicated AER communication in most current systems requires separate, low-bandwidth configuration channels. In contrast, the configuration of the waferscale neuromorphic system is also handled by the digital packet-based pulse channel, which transmits configuration data at the full bandwidth otherwise used for pulse transmission. The overall so-called pulse communication subgroup (ICs and FPGA delivers a factor 25-50 more event transmission rate than other current neuromorphic communication infrastructures.

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.

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.

Anti-Hebbian Spike Timing Dependent Plasticity and Adaptive Sensory Processing

Directory of Open Access Journals (Sweden)

Patrick D Roberts

2010-12-01

Full Text Available Adaptive processing influences the central nervous system's interpretation of incoming sensory information. One of the functions of this adaptative sensory processing is to allow the nervous system to ignore predictable sensory information so that it may focus on important new information needed to improve performance of specific tasks. The mechanism of spike timing-dependent plasticity (STDP has proven to be intriguing in this context because of its dual role in long-term memory and ongoing adaptation to maintain optimal tuning of neural responses. Some of the clearest links between STDP and adaptive sensory processing have come from in vitro, in vivo, and modeling studies of the electrosensory systems of fish. Plasticity in such systems is anti-Hebbian, i.e. presynaptic inputs that repeatedly precede and hence could contribute to a postsynaptic neuron’s firing are weakened. The learning dynamics of anti-Hebbian STDP learning rules are stable if the timing relations obey strict constraints. The stability of these learning rules leads to clear predictions of how functional consequences can arise from the detailed structure of the plasticity. Here we review the connection between theoretical predictions and functional consequences of anti-Hebbian STDP, focusing on adaptive processing in the electrosensory system of weakly electric fish. After introducing electrosensory adaptive processing and the dynamics of anti-Hebbian STDP learning rules, we address issues of predictive sensory cancellation and novelty detection, descending control of plasticity, synaptic scaling, and optimal sensory tuning. We conclude with examples in other systems where these principles may apply.

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.

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.

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.

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.

Focal Dystonia and the Sensory-Motor Integrative Loop for Enacting (SMILE

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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.

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.

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...

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...

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...

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

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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.

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

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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.

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.

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.

Sensory Flask Cells in Sponge Larvae Regulate Metamorphosis via Calcium Signaling.

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Nakanishi, Nagayasu; Stoupin, Daniel; Degnan, Sandie M; Degnan, Bernard M

2015-12-01

The Porifera (sponges) is one of the earliest phyletic lineages to branch off the metazoan tree. Although the body-plan of sponges is among the simplest in the animal kingdom and sponges lack nervous systems that communicate environmental signals to other cells, their larvae have sensory systems that generate coordinated responses to environmental cues. In eumetazoans (Cnidaria and Bilateria), the nervous systems of larvae often regulate metamorphosis through Ca(2+)-dependent signal transduction. In sponges, neither the identity of the receptor system that detects an inductive environmental cue (hereafter "metamorphic cues") nor the signaling system that mediates settlement and metamorphosis are known. Using a combination of behavioral assays and surgical manipulations, we show here that specialized epithelial cells-referred to as flask cells-enriched in the anterior third of the Amphimedon queenslandica larva are most likely to be the sensory cells that detect the metamorphic cues. Surgical removal of the region enriched in flask cells in a larva inhibits the initiation of metamorphosis. The flask cell has an apical sensory apparatus with a cilium surrounded by an apical F-actin-rich protrusion, and numerous vesicles, hallmarks of eumetazoan sensory-neurosecretory cells. We demonstrate that these flask cells respond to metamorphic cues by elevating intracellular Ca(2+) levels, and that this elevation is necessary for the initiation of metamorphosis. Taken together, these analyses suggest that sponge larvae have sensory-secretory epithelial cells capable of converting exogenous cues into internal signals via Ca(2+)-mediated signaling, which is necessary for the initiation of metamorphosis. Similarities in the morphology, physiology, and function of the sensory flask cells in sponge larvae with the sensory/neurosecretory cells in eumetazoan larvae suggest this sensory system predates the divergence of Porifera and Eumetazoa. © The Author 2015. Published by Oxford

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.

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.

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.

Sensory description of marine oils through development of a sensory wheel and vocabulary.

Science.gov (United States)

Larssen, W E; Monteleone, E; Hersleth, M

2018-04-01

The Omega-3 industry lacks a defined methodology and a vocabulary for evaluating the sensory quality of marine oils. This study was conducted to identify the sensory descriptors of marine oils and organize them in a sensory wheel for use as a tool in quality assessment. Samples of marine oils were collected from six of the largest producers of omega-3 products in Norway. The oils were selected to cover as much variation in sensory characteristics as possible, i.e. oils with different fatty acid content originating from different species. Oils were evaluated by six industry expert panels and one trained sensory panel to build up a vocabulary through a series of language sessions. A total of 184 aroma (odor by nose), flavor, taste and mouthfeel descriptors were generated. A sensory wheel based on 60 selected descriptors grouped together in 21 defined categories was created to form a graphical presentation of the sensory vocabulary. A selection of the oil samples was also evaluated by a trained sensory panel using descriptive analysis. Chemical analysis showed a positive correlation between primary and secondary oxidation products and sensory properties such as rancidity, chemical flavor and process flavor and a negative correlation between primary oxidation products and acidic. This research is a first step towards the broader objective of standardizing the sensory terminology related to marine oils. Copyright © 2017 Elsevier Ltd. All rights reserved.

[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.

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

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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.

Designing sensory-substitution devices: Principles, pitfalls and potential1.

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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.

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. �

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.

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...

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

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

At the interface of sensory and motor dysfunctions and Alzheimer’s Disease

Science.gov (United States)

Albers, Mark W.; Gilmore, Grover C.; Kaye, Jeffrey; Murphy, Claire; Wingfield, Arthur; Bennett, David A.; Boxer, Adam L.; Buchman, Aron S.; Cruickshanks, Karen J.; Devanand, Davangere P.; Duffy, Charles J.; Gall, Christine M.; Gates, George A.; Granholm, Ann-Charlotte; Hensch, Takao; Holtzer, Roee; Hyman, Bradley T.; Lin, Frank R.; McKee, Ann C.; Morris, John C.; Petersen, Ronald C.; Silbert, Lisa C.; Struble, Robert G.; Trojanowski, John Q.; Verghese, Joe; Wilson, Donald A.; Xu, Shunbin; Zhang, Li I.

2014-01-01

Recent evidence indicates that sensory and motor changes may precede the cognitive symptoms of Alzheimer’s disease (AD) by several years and may signify increased risk of developing AD. Traditionally, sensory and motor dysfunctions in aging and AD have been studied separately. To ascertain the evidence supporting the relationship between age-related changes in sensory and motor systems and the development of AD and to facilitate communication between several disciplines, the National Institute on Aging held an exploratory workshop titled “Sensory and Motor Dysfunctions in Aging and Alzheimer’s Disease”. The scientific sessions of the workshop focused on age-related and neuropathological changes in the olfactory, visual, auditory, and motor systems, followed by extensive discussion and hypothesis generation related to the possible links among sensory, cognitive, and motor domains in aging and AD. Based on the data presented and discussed at this workshop, it is clear that sensory and motor regions of the CNS are affected by Alzheimer pathology and that interventions targeting amelioration of sensory-motor deficits in AD may enhance patient function as AD progresses. PMID:25022540

Relationships among Sensory Responsiveness, Anxiety, and Ritual Behaviors in Children with and without Atypical Sensory Responsiveness.

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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.

Optogenetically enhanced axon regeneration: motor versus sensory neuron-specific stimulation.

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Ward, Patricia J; Clanton, Scott L; English, Arthur W

2018-02-01

Brief neuronal activation in injured peripheral nerves is both necessary and sufficient to enhance motor axon regeneration, and this effect is specific to the activated motoneurons. It is less clear whether sensory neurons respond in a similar manner to neuronal activation following peripheral axotomy. Further, it is unknown to what extent enhancement of axon regeneration with increased neuronal activity relies on a reflexive interaction within the spinal circuitry. We used mouse genetics and optical tools to evaluate the precision and selectivity of system-specific neuronal activation to enhance axon regeneration in a mixed nerve. We evaluated sensory and motor axon regeneration in two different mouse models expressing the light-sensitive cation channel, channelrhodopsin (ChR2). We selectively activated either sensory or motor axons using light stimulation combined with transection and repair of the sciatic nerve. Regardless of genotype, the number of ChR2-positive neurons whose axons had regenerated successfully was greater following system-specific optical treatment, with no effect on the number of ChR2-negative neurons (whether motor or sensory neurons). We conclude that acute system-specific neuronal activation is sufficient to enhance both motor and sensory axon regeneration. This regeneration-enhancing effect is likely cell autonomous. © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

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.

Sensory nerve action potentials and sensory perception in women with arthritis of the hand.

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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.

Variable sensory perception in autism.

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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.

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.

Sensory impairments of the lower limb after stroke: a pooled analysis of individual patient data.

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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.

3D hierarchical spatial representation and memory of multimodal sensory data

Science.gov (United States)

Khosla, Deepak; Dow, Paul A.; Huber, David J.

2009-04-01

This paper describes an efficient method and system for representing, processing and understanding multi-modal sensory data. More specifically, it describes a computational method and system for how to process and remember multiple locations in multimodal sensory space (e.g., visual, auditory, somatosensory, etc.). The multimodal representation and memory is based on a biologically-inspired hierarchy of spatial representations implemented with novel analogues of real representations used in the human brain. The novelty of the work is in the computationally efficient and robust spatial representation of 3D locations in multimodal sensory space as well as an associated working memory for storage and recall of these representations at the desired level for goal-oriented action. We describe (1) A simple and efficient method for human-like hierarchical spatial representations of sensory data and how to associate, integrate and convert between these representations (head-centered coordinate system, body-centered coordinate, etc.); (2) a robust method for training and learning a mapping of points in multimodal sensory space (e.g., camera-visible object positions, location of auditory sources, etc.) to the above hierarchical spatial representations; and (3) a specification and implementation of a hierarchical spatial working memory based on the above for storage and recall at the desired level for goal-oriented action(s). This work is most useful for any machine or human-machine application that requires processing of multimodal sensory inputs, making sense of it from a spatial perspective (e.g., where is the sensory information coming from with respect to the machine and its parts) and then taking some goal-oriented action based on this spatial understanding. A multi-level spatial representation hierarchy means that heterogeneous sensory inputs (e.g., visual, auditory, somatosensory, etc.) can map onto the hierarchy at different levels. When controlling various machine

Sex differences in chemosensation: sensory or cognitive?

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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.

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

Olfaction and Pheromones: Uncanonical Sensory Influences and Bulbar Interactions

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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.

Neuropathic pain: is quantitative sensory testing helpful?

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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.

Immunization Elicits Antigen-Specific Antibody Sequestration in Dorsal Root Ganglia Sensory Neurons

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Gunasekaran, Manojkumar; Chatterjee, Prodyot K.; Shih, Andrew; Imperato, Gavin H.; Addorisio, Meghan; Kumar, Gopal; Lee, Annette; Graf, John F.; Meyer, Dan; Marino, Michael; Puleo, Christopher; Ashe, Jeffrey; Cox, Maureen A.; Mak, Tak W.; Bouton, Chad; Sherry, Barbara; Diamond, Betty; Andersson, Ulf; Coleman, Thomas R.; Metz, Christine N.; Tracey, Kevin J.; Chavan, Sangeeta S.

2018-01-01

The immune and nervous systems are two major organ systems responsible for host defense and memory. Both systems achieve memory and learning that can be retained, retrieved, and utilized for decades. Here, we report the surprising discovery that peripheral sensory neurons of the dorsal root ganglia (DRGs) of immunized mice contain antigen-specific antibodies. Using a combination of rigorous molecular genetic analyses, transgenic mice, and adoptive transfer experiments, we demonstrate that DRGs do not synthesize these antigen-specific antibodies, but rather sequester primarily IgG1 subtype antibodies. As revealed by RNA-seq and targeted quantitative PCR (qPCR), dorsal root ganglion (DRG) sensory neurons harvested from either naïve or immunized mice lack enzymes (i.e., RAG1, RAG2, AID, or UNG) required for generating antibody diversity and, therefore, cannot make antibodies. Additionally, transgenic mice that express a reporter fluorescent protein under the control of Igγ1 constant region fail to express Ighg1 transcripts in DRG sensory neurons. Furthermore, neural sequestration of antibodies occurs in mice rendered deficient in neuronal Rag2, but antibody sequestration is not observed in DRG sensory neurons isolated from mice that lack mature B cells [e.g., Rag1 knock out (KO) or μMT mice]. Finally, adoptive transfer of Rag1-deficient bone marrow (BM) into wild-type (WT) mice or WT BM into Rag1 KO mice revealed that antibody sequestration was observed in DRG sensory neurons of chimeric mice with WT BM but not with Rag1-deficient BM. Together, these results indicate that DRG sensory neurons sequester and retain antigen-specific antibodies released by antibody-secreting plasma cells. Coupling this work with previous studies implicating DRG sensory neurons in regulating antigen trafficking during immunization raises the interesting possibility that the nervous system collaborates with the immune system to regulate antigen-mediated responses. PMID:29755449

Immunization Elicits Antigen-Specific Antibody Sequestration in Dorsal Root Ganglia Sensory Neurons

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Manojkumar Gunasekaran

2018-04-01

Full Text Available The immune and nervous systems are two major organ systems responsible for host defense and memory. Both systems achieve memory and learning that can be retained, retrieved, and utilized for decades. Here, we report the surprising discovery that peripheral sensory neurons of the dorsal root ganglia (DRGs of immunized mice contain antigen-specific antibodies. Using a combination of rigorous molecular genetic analyses, transgenic mice, and adoptive transfer experiments, we demonstrate that DRGs do not synthesize these antigen-specific antibodies, but rather sequester primarily IgG1 subtype antibodies. As revealed by RNA-seq and targeted quantitative PCR (qPCR, dorsal root ganglion (DRG sensory neurons harvested from either naïve or immunized mice lack enzymes (i.e., RAG1, RAG2, AID, or UNG required for generating antibody diversity and, therefore, cannot make antibodies. Additionally, transgenic mice that express a reporter fluorescent protein under the control of Igγ1 constant region fail to express Ighg1 transcripts in DRG sensory neurons. Furthermore, neural sequestration of antibodies occurs in mice rendered deficient in neuronal Rag2, but antibody sequestration is not observed in DRG sensory neurons isolated from mice that lack mature B cells [e.g., Rag1 knock out (KO or μMT mice]. Finally, adoptive transfer of Rag1-deficient bone marrow (BM into wild-type (WT mice or WT BM into Rag1 KO mice revealed that antibody sequestration was observed in DRG sensory neurons of chimeric mice with WT BM but not with Rag1-deficient BM. Together, these results indicate that DRG sensory neurons sequester and retain antigen-specific antibodies released by antibody-secreting plasma cells. Coupling this work with previous studies implicating DRG sensory neurons in regulating antigen trafficking during immunization raises the interesting possibility that the nervous system collaborates with the immune system to regulate antigen-mediated responses.

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.

Parasympathetic functions in children with sensory processing disorder

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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.

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)

Epileptic Seizure Prediction Using Big Data and Deep Learning: Toward a Mobile System

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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.

Sensory modulation disorders in childhood epilepsy.

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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.

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

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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.

Sensory Integration with Articulated Motion on a Humanoid Robot

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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.

Subsecond Sensory Modulation of Serotonin Levels in a Primary Sensory Area and Its Relation to Ongoing Communication Behavior in a Weakly Electric Fish.

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Fotowat, Haleh; Harvey-Girard, Erik; Cheer, Joseph F; Krahe, Rüdiger; Maler, Leonard

2016-01-01

Serotonergic neurons of the raphe nuclei of vertebrates project to most regions of the brain and are known to significantly affect sensory processing. The subsecond dynamics of sensory modulation of serotonin levels and its relation to behavior, however, remain unknown. We used fast-scan cyclic voltammetry to measure serotonin release in the electrosensory system of weakly electric fish, Apteronotus leptorhynchus . These fish use an electric organ to generate a quasi-sinusoidal electric field for communicating with conspecifics. In response to conspecific signals, they frequently produce signal modulations called chirps. We measured changes in serotonin concentration in the hindbrain electrosensory lobe (ELL) with a resolution of 0.1 s concurrently with chirping behavior evoked by mimics of conspecific electric signals. We show that serotonin release can occur phase locked to stimulus onset as well as spontaneously in the ELL region responsible for processing these signals. Intense auditory stimuli, on the other hand, do not modulate serotonin levels in this region, suggesting modality specificity. We found no significant correlation between serotonin release and chirp production on a trial-by-trial basis. However, on average, in the trials where the fish chirped, there was a reduction in serotonin release in response to stimuli mimicking similar-sized same-sex conspecifics. We hypothesize that the serotonergic system is part of an intricate sensory-motor loop: serotonin release in a sensory area is triggered by sensory input, giving rise to motor output, which can in turn affect serotonin release at the timescale of the ongoing sensory experience and in a context-dependent manner.

Sensory determinants of the autonomous sensory meridian response (ASMR): Understanding the triggers

OpenAIRE

Barratt, EL; Spence, CJ; Davis, NJ

2017-01-01

The autonomous sensory meridian response (ASMR) is an atypical sensory phenomenon involving electrostatic-like tingling sensations in response to certain sensory, primarily audio-visual, stimuli. The current study used an online questionnaire, completed by 130 people who self-reported experiencing ASMR. We aimed to extend preliminary investigations into the experience, and establish key multisensory factors contributing to the successful induction of ASMR through online media. Aspects such as...

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

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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%.

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.

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)

Sensory profiling: a method for describing the sensory characteristics of virgin olive oil

Directory of Open Access Journals (Sweden)

Lyon, David H.

1994-04-01

Full Text Available Sensory profiling is an objective, descriptive technique which uses a panel of trained assessors. It was used at Campden to differentiate olive oil which differed in terms of the country of origin, variety, ripeness and extraction techniques. The data were related to similar results from the Netherlands and Italy. The results indicated that all three sensory panels perceived the samples in the same way, however, the differed in the way the oils were described.
The new European legislation on olive oil is partially concerned with the sensory aspects of the oil. The sensory grading takes into account the 'positive' and 'negative' attributes in the oil before giving an overall quality grade. These attributes do not reflect the consumer requirements, therefore, the grading should be restricted to the assessment of the presence or absence of sensory defects.

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.

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

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.

A piece of the action: modulation of sensory-motor regions by action idioms and metaphors.

Science.gov (United States)

Desai, Rutvik H; Conant, Lisa L; Binder, Jeffrey R; Park, Haeil; Seidenberg, Mark S

2013-12-01

The idea that the conceptual system draws on sensory and motor systems has received considerable experimental support in recent years. Whether the tight coupling between sensory-motor and conceptual systems is modulated by factors such as context or task demands is a matter of controversy. Here, we tested the context sensitivity of this coupling by using action verbs in three different types of sentences in an fMRI study: literal action, apt but non-idiomatic action metaphors, and action idioms. Abstract sentences served as a baseline. The result showed involvement of sensory-motor areas for literal and metaphoric action sentences, but not for idiomatic ones. A trend of increasing sensory-motor activation from abstract to idiomatic to metaphoric to literal sentences was seen. These results support a gradual abstraction process whereby the reliance on sensory-motor systems is reduced as the abstractness of meaning as well as conventionalization is increased, highlighting the context sensitive nature of semantic processing. © 2013.

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.

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.

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

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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.

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.

What is Sensory about Multi-Sensory Enhancement of Vision by Sounds?

Directory of Open Access Journals (Sweden)

Alexis Pérez-Bellido

2011-10-01

Full Text Available Can auditory input influence the sensory processing of visual information? Many studies have reported cross-modal enhancement in visual tasks, but the nature of such gain is still unclear. Some authors argue for ‘high-order’ expectancy or attention effects, whereas others propose ‘low-order’ stimulus-driven multisensory integration. The present study applies a psychophysical analysis of reaction time distributions in order to disentangle sensory changes from other kind of high-order (not sensory-specific effects. Observers performed a speeded simple detection task on Gabor patches of different spatial frequencies and contrasts, with and without accompanying sounds. The data were adjusted using chronometric functions in order to separate changes is sensory evidence from changes in decision or motor times. The results supported the existence of a stimulus unspecific auditory-induced enhancement in RTs across all types of visual stimuli, probably mediated by higher-order effects (eg, reduction of temporal uncertainty. Critically, we also singled out a sensory gain that was selective to low spatial frequency stimuli, highlighting the role of the magno-cellular visual pathway in multisensory integration for fast detection. The present findings help clarify previous mixed findings in the area, and introduce a novel form to evaluate cross-modal enhancement.

The active electric sense of weakly electric fish: from electric organ discharge to sensory processing and behaviour

Directory of Open Access Journals (Sweden)

Krahe Rüdiger

2016-01-01

Full Text Available Sensory systems have been shaped by evolution to extract information that is relevant for decision making. In order to understand the mechanisms used by sensory systems for filtering the incoming stream of sensory input, it is important to have a quantitative understanding of the natural sensory scenes that are to be processed. Weakly electric fish lead a rather cryptic nocturnal life in often turbid tropical rainforest streams. They produce electric discharges and sense perturbations of their selfgenerated electric field for prey detection and navigation, and also use their active sense for communication in the context of courtship and aggression. The fact that they produce their electric signals throughout day and night permits the use of electrode arrays to track the movements of multiple individual fish and monitor their communication interactions, thus offering a window into their electrosensory world. This approach yields unprecedented access to information on the biology of these fishes and also on the statistical properties of the sensory scenes that are to be processed by their electrosensory system. The electrosensory system shares many organizational features with other sensory systems, in particular, the use of multiple topographic maps. In fact, the sensory surface (the skin is represented in three parallel maps in the hindbrain, with each map covering the receptor organ array with six different cell types that project to the next higher level of processing. Thus, the electroreceptive body surface is represented a total of 18 times in the hindbrain, with each representation having its specific filter properties and degree of response plasticity. Thus, the access to the sensory world of these fish as well as the manifold filtering of the sensory input makes these fish an excellent model system for exploring the cell-intrinsic and network characteristics underlying the extraction of behaviourally relevant sensory information.

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.

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.…

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.

Sensory memory for odors is encoded in spontaneous correlated activity between olfactory glomeruli.

Science.gov (United States)

Galán, Roberto F; Weidert, Marcel; Menzel, Randolf; Herz, Andreas V M; Galizia, C Giovanni

2006-01-01

Sensory memory is a short-lived persistence of a sensory stimulus in the nervous system, such as iconic memory in the visual system. However, little is known about the mechanisms underlying olfactory sensory memory. We have therefore analyzed the effect of odor stimuli on the first odor-processing network in the honeybee brain, the antennal lobe, which corresponds to the vertebrate olfactory bulb. We stained output neurons with a calcium-sensitive dye and measured across-glomerular patterns of spontaneous activity before and after a stimulus. Such a single-odor presentation changed the relative timing of spontaneous activity across glomeruli in accordance with Hebb's theory of learning. Moreover, during the first few minutes after odor presentation, correlations between the spontaneous activity fluctuations suffice to reconstruct the stimulus. As spontaneous activity is ubiquitous in the brain, modifiable fluctuations could provide an ideal substrate for Hebbian reverberations and sensory memory in other neural systems.

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...

Sensory quality of beef from different finishing diets.

Science.gov (United States)

Resconi, V C; Campo, M M; Font i Furnols, M; Montossi, F; Sañudo, C

2010-11-01

Beef production under different local husbandry systems might have meat sensory quality implications for the marketing of these products abroad. In order to assess the effect of finishing diet systems on beef quality, a trained sensory taste panel assessed meat aged for 20 days from 80 Uruguayan Hereford steers that were finished on one of the following diets: T1=Pasture [4% of animal live weight (LW)], T2=Pasture [3% LW plus concentrate (0.6% LW)], T3=Pasture [3% LW plus concentrate (1.2% LW)], or T4=Concentrate plus hay ad libitum. Beef odour and flavour intensities decreased with an increase in the energy content of the diet. The meat from T2 had the lowest acid flavour and strange odours intensities. In general, steers fed only concentrate plus hay (T4) produced meat that had an inferior sensory quality because they had more pronounced off-flavours and was tougher. Copyright © 2010 The American Meat Science Association. Published by Elsevier Ltd. All rights reserved.

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

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

Improvements of sensorimotor processes during action cascading associated with changes in sensory processing architecture-insights from sensory deprivation.

Science.gov (United States)

Gohil, Krutika; Hahne, Anja; Beste, Christian

2016-06-20

In most everyday situations sensorimotor processes are quite complex because situations often require to carry out several actions in a specific temporal order; i.e. one has to cascade different actions. While it is known that changes to stimuli affect action cascading mechanisms, it is unknown whether action cascading changes when sensory stimuli are not manipulated, but the neural architecture to process these stimuli is altered. In the current study we test this hypothesis using prelingually deaf subjects as a model to answer this question. We use a system neurophysiological approach using event-related potentials (ERPs) and source localization techniques. We show that prelingually deaf subjects show improvements in action cascading. However, this improvement is most likely not due to changes at the perceptual (P1-ERP) and attentional processing level (N1-ERP), but due to changes at the response selection level (P3-ERP). It seems that the temporo-parietal junction (TPJ) is important for these effects to occur, because the TPJ comprises overlapping networks important for the processing of sensory information and the selection of responses. Sensory deprivation thus affects cognitive processes downstream of sensory processing and only these seem to be important for behavioral improvements in situations requiring complex sensorimotor processes and action cascading.

Computational Cognition and Robust Decision Making

Science.gov (United States)

2013-03-06

much more powerful neuromorphic chips than current state of the art. L. Chua 10 DISTRIBUTION STATEMENT A – Unclassified, Unlimited Distribution 2...Cognition Program DARPA (Gill Pratt) • Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) Program IARPA (Brad Minnery...2012 - Four projects at SNU and KAIST co-funded with AOARD DARPA SyNAPSE Program: - Design, fabrication, and demonstration of neuromorphic

Evaluating Sensory Processing in Fragile X Syndrome: Psychometric Analysis of the Brain Body Center Sensory Scales (BBCSS).

Science.gov (United States)

Kolacz, Jacek; Raspa, Melissa; Heilman, Keri J; Porges, Stephen W

2018-06-01

Individuals with fragile X syndrome (FXS), especially those co-diagnosed with autism spectrum disorder (ASD), face many sensory processing challenges. However, sensory processing measures informed by neurophysiology are lacking. This paper describes the development and psychometric properties of a parent/caregiver report, the Brain-Body Center Sensory Scales (BBCSS), based on Polyvagal Theory. Parents/guardians reported on 333 individuals with FXS, 41% with ASD features. Factor structure using a split-sample exploratory-confirmatory design conformed to neurophysiological predictions. Internal consistency, test-retest, and inter-rater reliability were good to excellent. BBCSS subscales converged with the Sensory Profile and Sensory Experiences Questionnaire. However, data also suggest that BBCSS subscales reflect unique features related to sensory processing. Individuals with FXS and ASD features displayed more sensory challenges on most subscales.

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.

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...

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

Sensory, yield and quality differences between organically and conventionally grown winter wheat.

Science.gov (United States)

Arncken, Christine M; Mäder, Paul; Mayer, Jochen; Weibel, Franco P

2012-11-01

Consumers expect organic produce to have higher environmental, health and sensory related qualities than conventional produce. In order to test sensory differences between bio-dynamically, bio-organically and conventionally grown winter wheat (Triticum aestivum L., cv. Runal), we performed double-blinded triangle tests with two panels on dry wholemeal flour from the harvest years 2006, 2007 and 2009 and from two field replicates of the 'DOK' long-term farming system comparison field trial near Basel, Switzerland. Yield and quality parameters were also assessed. Significant farming system effects were found for yield (up to 42% reduction in the organic system), thousand kernel weight, hectolitre weight and crude protein content across the three years. In the triangle tests one out of 12 pair-wise farming system comparisons (PFSCs) on wholemeal flour made from the different wheat samples showed significant sensory differentiation (between bio-dynamically and conventionally grown wheat). When all data from the three harvest years and two panels were aggregated, a statistically significant effect (P = 0.045) of PFSCs on the number of correct answers became evident. Although testing of dry wholemeal flour was very challenging for panellists, we were able to show that sensory differences between farming systems can occur. Copyright © 2012 Society of Chemical Industry.

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.

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.

Mapping the sensory perception of apple using descriptive sensory evaluation in a genome wide association study.

Science.gov (United States)

Amyotte, Beatrice; Bowen, Amy J; Banks, Travis; Rajcan, Istvan; Somers, Daryl J

2017-01-01

Breeding apples is a long-term endeavour and it is imperative that new cultivars are selected to have outstanding consumer appeal. This study has taken the approach of merging sensory science with genome wide association analyses in order to map the human perception of apple flavour and texture onto the apple genome. The goal was to identify genomic associations that could be used in breeding apples for improved fruit quality. A collection of 85 apple cultivars was examined over two years through descriptive sensory evaluation by a trained sensory panel. The trained sensory panel scored randomized sliced samples of each apple cultivar for seventeen taste, flavour and texture attributes using controlled sensory evaluation practices. In addition, the apple collection was subjected to genotyping by sequencing for marker discovery. A genome wide association analysis suggested significant genomic associations for several sensory traits including juiciness, crispness, mealiness and fresh green apple flavour. The findings include previously unreported genomic regions that could be used in apple breeding and suggest that similar sensory association mapping methods could be applied in other plants.

Mapping the sensory perception of apple using descriptive sensory evaluation in a genome wide association study

Science.gov (United States)

Amyotte, Beatrice; Bowen, Amy J.; Banks, Travis; Rajcan, Istvan; Somers, Daryl J.

2017-01-01

Breeding apples is a long-term endeavour and it is imperative that new cultivars are selected to have outstanding consumer appeal. This study has taken the approach of merging sensory science with genome wide association analyses in order to map the human perception of apple flavour and texture onto the apple genome. The goal was to identify genomic associations that could be used in breeding apples for improved fruit quality. A collection of 85 apple cultivars was examined over two years through descriptive sensory evaluation by a trained sensory panel. The trained sensory panel scored randomized sliced samples of each apple cultivar for seventeen taste, flavour and texture attributes using controlled sensory evaluation practices. In addition, the apple collection was subjected to genotyping by sequencing for marker discovery. A genome wide association analysis suggested significant genomic associations for several sensory traits including juiciness, crispness, mealiness and fresh green apple flavour. The findings include previously unreported genomic regions that could be used in apple breeding and suggest that similar sensory association mapping methods could be applied in other plants. PMID:28231290

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.

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.

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...

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....

The Sensory Perception Quotient (SPQ): development and validation of a new sensory questionnaire for adults with and without autism.

Science.gov (United States)

Tavassoli, Teresa; Hoekstra, Rosa A; Baron-Cohen, Simon

2014-01-01

Questionnaire-based studies suggest atypical sensory perception in over 90% of individuals with autism spectrum conditions (ASC). Sensory questionnaire-based studies in ASC mainly record parental reports of their child's sensory experience; less is known about sensory reactivity in adults with ASC. Given the DSM-5 criteria for ASC now include sensory reactivity, there is a need for an adult questionnaire investigating basic sensory functioning. We aimed to develop and validate the Sensory Perception Quotient (SPQ), which assesses basic sensory hyper- and hyposensitivity across all five modalities. A total of 359 adults with (n = 196) and without (n = 163) ASC were asked to fill in the SPQ, the Sensory Over-Responsivity Inventory (SensOR) and the Autism-Spectrum Quotient (AQ) online. Adults with ASC reported more sensory hypersensitivity on the SPQ compared to controls (P sensory hypersensitivity. The SPQ showed high internal consistency for both the total SPQ (Cronbach's alpha = .92) and the reduced 35-item version (alpha = .93). The SPQ was significantly correlated with the SensOR across groups (r = -.46) and within the ASC (r = -.49) and control group (r = -.21). The SPQ shows good internal consistency and concurrent validity and differentiates between adults with and without ASC. Adults with ASC report more sensitivity to sensory stimuli on the SPQ. Finally, greater sensory sensitivity is associated with more autistic traits. The SPQ provides a new tool to measure individual differences on this dimension.

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 ...

Oropharyngeal and laryngeal sensory innervation in the pathophysiology of swallowing disorders and sensory stimulation treatments.

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Alvarez-Berdugo, Daniel; Rofes, Laia; Casamitjana, J Francesc; Padrón, Andreína; Quer, Miquel; Clavé, Pere

2016-09-01

Oropharyngeal dysphagia (OD) affects older and neurological patients, causing malnutrition and dehydration and increasing the risk for aspiration pneumonia. There is evidence that sensory deficits in those populations are closely related to swallowing disorders, and several research groups are developing new therapies based on sensory stimulation of this area. More information on the sensory innervation participating in the swallow response is needed to better understand the pathophysiology of OD and to develop new treatments. This review focuses on the sensory innervation of the human oropharynx and larynx in healthy people compared with patients with swallowing disorders in order to unravel the abnormalities that may lead to the loss of sensitivity in patients with OD. We also hypothesize the pathway through which active sensory-enhancement treatments may elicit their therapeutic effect on patients with swallowing dysfunctions. As far as we know, this is the first time a review covers the anatomy, histology, ultrastructure, and molecular biology of the sensory innervation of the swallowing function. © 2016 New York Academy of Sciences.

Diagnostic value of the near-nerve needle sensory nerve conduction in sensory inflammatory demyelinating polyneuropathy.

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Odabasi, Zeki; Oh, Shin J

2018-03-01

In this study we report the diagnostic value of the near-nerve needle sensory nerve conduction study (NNN-SNCS) in sensory inflammatory demyelinating polyneuropathy (IDP) in which the routine nerve conduction study was normal or non-diagnostic. The NNN-SNCS was performed to identify demyelination in the plantar nerves in 14 patients and in the median or ulnar nerve in 2 patients with sensory IDP. In 16 patients with sensory IDP, routine NCSs were either normal or non-diagnostic for demyelination. Demyelination was identified by NNN-SNCS by dispersion and/or slow nerve conduction velocity (NCV) below the demyelination marker. Immunotherapy was initiated in 11 patients, 10 of whom improved or remained stable. NNN-SNCS played an essential role in identifying demyelinaton in 16 patients with sensory IDP, leading to proper treatment. Muscle Nerve 57: 414-418, 2018. © 2017 Wiley Periodicals, Inc.

Localization of SSeCKS in unmyelinated primary sensory neurons

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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

The neuroecology of cartilaginous fishes: sensory strategies for survival.

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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

Sensory Cortical Plasticity Participates in the Epigenetic Regulation of Robust Memory Formation

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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

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.

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.

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

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.

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.

Sensory Substitution and Multimodal Mental Imagery.

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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."

Activation of Six1 Expression in Vertebrate Sensory Neurons.

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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.

Age-Related Sensory Impairments and Risk of Cognitive Impairment

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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

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.

Influence of Sensory Stimulation on Exhaled Volatile Organic Compounds.

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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.

Simulation of a spiking neuron circuit using carbon nanotube transistors

Energy Technology Data Exchange (ETDEWEB)

Najari, Montassar, E-mail: malnjar@jazanu.edu.sa [Departement of Physics, Faculty of Sciences, University of Gabes, Gabes (Tunisia); IKCE unit, Jazan University, Jazan (Saudi Arabia); El-Grour, Tarek, E-mail: grour-tarek@hotmail.fr [Departement of Physics, Faculty of Sciences, University of Gabes, Gabes (Tunisia); Jelliti, Sami, E-mail: sjelliti@jazanu.edu.sa [IKCE unit, Jazan University, Jazan (Saudi Arabia); Hakami, Othman Mousa, E-mail: omhakami@jazanu.edu.sa [IKCE unit, Jazan University, Jazan (Saudi Arabia); Faculty of Sciences, Jazan University, Jazan (Saudi Arabia)

2016-06-10

Neuromorphic engineering is related to the existing analogies between the physical semiconductor VLSI (Very Large Scale Integration) and biophysics. Neuromorphic systems propose to reproduce the structure and function of biological neural systems for transferring their calculation capacity on silicon. Since the innovative research of Carver Mead, the neuromorphic engineering continues to emerge remarkable implementation of biological system. This work presents a simulation of an elementary neuron cell with a carbon nanotube transistor (CNTFET) based technology. The model of the cell neuron which was simulated is called integrate and fire (I&F) model firstly introduced by G. Indiveri in 2009. This circuit has been simulated with CNTFET technology using ADS environment to verify the neuromorphic activities in terms of membrane potential. This work has demonstrated the efficiency of this emergent device; i.e CNTFET on the design of such architecture in terms of power consumption and technology integration density.

Simulation of a spiking neuron circuit using carbon nanotube transistors

International Nuclear Information System (INIS)

Najari, Montassar; El-Grour, Tarek; Jelliti, Sami; Hakami, Othman Mousa

2016-01-01

Neuromorphic engineering is related to the existing analogies between the physical semiconductor VLSI (Very Large Scale Integration) and biophysics. Neuromorphic systems propose to reproduce the structure and function of biological neural systems for transferring their calculation capacity on silicon. Since the innovative research of Carver Mead, the neuromorphic engineering continues to emerge remarkable implementation of biological system. This work presents a simulation of an elementary neuron cell with a carbon nanotube transistor (CNTFET) based technology. The model of the cell neuron which was simulated is called integrate and fire (I&F) model firstly introduced by G. Indiveri in 2009. This circuit has been simulated with CNTFET technology using ADS environment to verify the neuromorphic activities in terms of membrane potential. This work has demonstrated the efficiency of this emergent device; i.e CNTFET on the design of such architecture in terms of power consumption and technology integration density.

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.

Sensory analysis of pet foods.

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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.

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

38 CFR 17.149 - Sensori-neural aids.

Science.gov (United States)

2010-07-01

... 38 Pensions, Bonuses, and Veterans' Relief 1 2010-07-01 2010-07-01 false Sensori-neural aids. 17... Prosthetic, Sensory, and Rehabilitative Aids § 17.149 Sensori-neural aids. (a) Notwithstanding any other provision of this part, VA will furnish needed sensori-neural aids (i.e., eyeglasses, contact lenses...

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.

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.

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.

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.

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.

StreamAR: incremental and active learning with evolving sensory data for activity recognition

OpenAIRE

Abdallah, Z.; Gaber, M.; Srinivasan, B.; Krishnaswamy, S.

2012-01-01

Activity recognition focuses on inferring current user activities by leveraging sensory data available on today’s sensor rich environment. Supervised learning has been applied pervasively for activity recognition. Typical activity recognition techniques process sensory data based on point-by-point approaches. In this paper, we propose a novel cluster-based classification for activity recognition Systems, termed StreamAR. The system incorporates incremental and active learning for mining user ...

Postural strategies and sensory integration: no turning point between childhood and adolescence.

Directory of Open Access Journals (Sweden)

Sophie Mallau

Full Text Available In this study, we investigated the sensory integration to postural control in children and adolescents from 5 to 15 years of age. We adopted the working hypothesis that considerable body changes occurring during these periods may lead subjects to under-use the information provided by the proprioceptive pathway and over-use other sensory systems such as vision to control their orientation and stabilize their body. It was proposed to determine which maturational differences may exist between the sensory integration used by children and adolescents in order to test the hypothesis that adolescence may constitute a specific phase in the development of postural control. This hypothesis was tested by applying an original protocol of slow oscillations below the detection threshold of the vestibular canal system, which mainly serves to mediate proprioceptive information, to the platform on which the subjects were standing. We highlighted the process of acquiring an accurate sensory and anatomical reference frame for functional movement. We asked children and adolescents to maintain a vertical stance while slow sinusoidal oscillations in the frontal plane were applied to the support at 0.01 Hz (below the detection threshold of the semicircular canal system and at 0.06 Hz (above the detection threshold of the semicircular canal system with their eyes either open or closed. This developmental study provided evidence that there are mild differences in the quality of sensory integration relative to postural control in children and adolescents. The results reported here confirmed the predominance of vision and the gradual mastery of somatosensory integration in postural control during a large period of ontogenesis including childhood and adolescence. The youngest as well as the oldest subjects adopted similar qualitative damping and segmental stabilization strategies that gradually improved with age without reaching an adult's level. Lastly, sensory

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.

Sensory regulation of neuroligins and neurexin I in the honeybee brain.

Directory of Open Access Journals (Sweden)

Sunita Biswas

2010-02-01

Full Text Available Neurexins and neuroligins, which have recently been associated with neurological disorders such as autism in humans, are highly conserved adhesive proteins found on synaptic membranes of neurons. These binding partners produce a trans-synaptic bridge that facilitates maturation and specification of synapses. It is believed that there exists an optimal spatio-temporal code of neurexin and neuroligin interactions that guide synapse formation in the postnatal developing brain. Therefore, we investigated whether neuroligins and neurexin are differentially regulated by sensory input using a behavioural model system with an advanced capacity for sensory processing, learning and memory, the honeybee.Whole brain expression levels of neuroligin 1-5 (NLG1-5 and neurexin I (NrxI were estimated by qRT-PCR analysis in three different behavioural paradigms: sensory deprivation, associative scent learning, and lateralised sensory input. Sensory deprived bees had a lower level of NLG1 expression, but a generally increased level of NLG2-5 and NrxI expression compared to hive bees. Bees that had undergone associative scent training had significantly increased levels of NrxI, NLG1 and NLG3 expression compared to untrained control bees. Bees that had lateralised sensory input after antennal amputation showed a specific increase in NLG1 expression compared to control bees, which only happened over time.Our results suggest that (1 there is a lack of synaptic pruning during sensory deprivation; (2 NLG1 expression increases with sensory stimulation; (3 concomitant changes in gene expression suggests NrxI interacts with all neuroligins; (4 there is evidence for synaptic compensation after lateralised injury.

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

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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.

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...

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

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.

Prestimulus influences on auditory perception from sensory representations and decision processes.

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Kayser, Stephanie J; McNair, Steven W; Kayser, Christoph

2016-04-26

The qualities of perception depend not only on the sensory inputs but also on the brain state before stimulus presentation. Although the collective evidence from neuroimaging studies for a relation between prestimulus state and perception is strong, the interpretation in the context of sensory computations or decision processes has remained difficult. In the auditory system, for example, previous studies have reported a wide range of effects in terms of the perceptually relevant frequency bands and state parameters (phase/power). To dissociate influences of state on earlier sensory representations and higher-level decision processes, we collected behavioral and EEG data in human participants performing two auditory discrimination tasks relying on distinct acoustic features. Using single-trial decoding, we quantified the relation between prestimulus activity, relevant sensory evidence, and choice in different task-relevant EEG components. Within auditory networks, we found that phase had no direct influence on choice, whereas power in task-specific frequency bands affected the encoding of sensory evidence. Within later-activated frontoparietal regions, theta and alpha phase had a direct influence on choice, without involving sensory evidence. These results delineate two consistent mechanisms by which prestimulus activity shapes perception. However, the timescales of the relevant neural activity depend on the specific brain regions engaged by the respective task.

An On-Chip Learning Neuromorphic Autoencoder With Current-Mode Transposable Memory Read and Virtual Lookup Table.

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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.

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.

Active inference, sensory attenuation and illusions.

Science.gov (United States)

Brown, Harriet; Adams, Rick A; Parees, Isabel; Edwards, Mark; Friston, Karl

2013-11-01

Active inference provides a simple and neurobiologically plausible account of how action and perception are coupled in producing (Bayes) optimal behaviour. This can be seen most easily as minimising prediction error: we can either change our predictions to explain sensory input through perception. Alternatively, we can actively change sensory input to fulfil our predictions. In active inference, this action is mediated by classical reflex arcs that minimise proprioceptive prediction error created by descending proprioceptive predictions. However, this creates a conflict between action and perception; in that, self-generated movements require predictions to override the sensory evidence that one is not actually moving. However, ignoring sensory evidence means that externally generated sensations will not be perceived. Conversely, attending to (proprioceptive and somatosensory) sensations enables the detection of externally generated events but precludes generation of actions. This conflict can be resolved by attenuating the precision of sensory evidence during movement or, equivalently, attending away from the consequences of self-made acts. We propose that this Bayes optimal withdrawal of precise sensory evidence during movement is the cause of psychophysical sensory attenuation. Furthermore, it explains the force-matching illusion and reproduces empirical results almost exactly. Finally, if attenuation is removed, the force-matching illusion disappears and false (delusional) inferences about agency emerge. This is important, given the negative correlation between sensory attenuation and delusional beliefs in normal subjects--and the reduction in the magnitude of the illusion in schizophrenia. Active inference therefore links the neuromodulatory optimisation of precision to sensory attenuation and illusory phenomena during the attribution of agency in normal subjects. It also provides a functional account of deficits in syndromes characterised by false inference

Stability and selectivity of a chronic, multi-contact cuff electrode for sensory stimulation in human amputees.

Science.gov (United States)

Tan, Daniel W; Schiefer, Matthew A; Keith, Michael W; Anderson, J Robert; Tyler, Dustin J

2015-04-01

Stability and selectivity are important when restoring long-term, functional sensory feedback in individuals with limb-loss. Our objective is to demonstrate a chronic, clinical neural stimulation system for providing selective sensory response in two upper-limb amputees. Multi-contact cuff electrodes were implanted in the median, ulnar, and radial nerves of the upper-limb. Nerve stimulation produced a selective sensory response on 19 of 20 contacts and 16 of 16 contacts in subjects 1 and 2, respectively. Stimulation elicited multiple, distinct percept areas on the phantom and residual limb. Consistent threshold, impedance, and percept areas have demonstrated that the neural interface is stable for the duration of this on-going, chronic study. We have achieved selective nerve response from multi-contact cuff electrodes by demonstrating characteristic percept areas and thresholds for each contact. Selective sensory response remains consistent in two upper-limb amputees for 1 and 2 years, the longest multi-contact sensory feedback system to date. Our approach demonstrates selectivity and stability can be achieved through an extraneural interface, which can provide sensory feedback to amputees.

The power of projectomes: genetic mosaic labeling in the larval zebrafish brain reveals organizing principles of sensory circuits.

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Robles, Estuardo

2017-09-01

In no vertebrate species do we possess an accurate, comprehensive tally of neuron types in the brain. This is in no small part due to the vast diversity of neuronal types that comprise complex vertebrate nervous systems. A fundamental goal of neuroscience is to construct comprehensive catalogs of cell types defined by structure, connectivity, and physiological response properties. This type of information will be invaluable for generating models of how assemblies of neurons encode and distribute sensory information and correspondingly alter behavior. This review summarizes recent efforts in the larval zebrafish to construct sensory projectomes, comprehensive analyses of axonal morphologies in sensory axon tracts. Focusing on the olfactory and optic tract, these studies revealed principles of sensory information processing in the olfactory and visual systems that could not have been directly quantified by other methods. In essence, these studies reconstructed the optic and olfactory tract in a virtual manner, providing insights into patterns of neuronal growth that underlie the formation of sensory axon tracts. Quantitative analysis of neuronal diversity revealed organizing principles that determine information flow through sensory systems in the zebrafish that are likely to be conserved across vertebrate species. The generation of comprehensive cell type classifications based on structural, physiological, and molecular features will lead to testable hypotheses on the functional role of individual sensory neuron subtypes in controlling specific sensory-evoked behaviors.

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.

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.

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

Shared sensory estimates for human motion perception and pursuit eye movements.

Science.gov (United States)

Mukherjee, Trishna; Battifarano, Matthew; Simoncini, Claudio; Osborne, Leslie C

2015-06-03

Are sensory estimates formed centrally in the brain and then shared between perceptual and motor pathways or is centrally represented sensory activity decoded independently to drive awareness and action? Questions about the brain's information flow pose a challenge because systems-level estimates of environmental signals are only accessible indirectly as behavior. Assessing whether sensory estimates are shared between perceptual and motor circuits requires comparing perceptual reports with motor behavior arising from the same sensory activity. Extrastriate visual cortex both mediates the perception of visual motion and provides the visual inputs for behaviors such as smooth pursuit eye movements. Pursuit has been a valuable testing ground for theories of sensory information processing because the neural circuits and physiological response properties of motion-responsive cortical areas are well studied, sensory estimates of visual motion signals are formed quickly, and the initiation of pursuit is closely coupled to sensory estimates of target motion. Here, we analyzed variability in visually driven smooth pursuit and perceptual reports of target direction and speed in human subjects while we manipulated the signal-to-noise level of motion estimates. Comparable levels of variability throughout viewing time and across conditions provide evidence for shared noise sources in the perception and action pathways arising from a common sensory estimate. We found that conditions that create poor, low-gain pursuit create a discrepancy between the precision of perception and that of pursuit. Differences in pursuit gain arising from differences in optic flow strength in the stimulus reconcile much of the controversy on this topic. Copyright © 2015 the authors 0270-6474/15/358515-16$15.00/0.

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

Effects of acupuncture on sensory perception: a systematic review and meta-analysis.

Science.gov (United States)

Baeumler, Petra I; Fleckenstein, Johannes; Takayama, Shin; Simang, Michael; Seki, Takashi; Irnich, Dominik

2014-01-01

The effect of acupuncture on sensory perception has never been systematically reviewed; although, studies on acupuncture mechanisms are frequently based on the idea that changes in sensory thresholds reflect its effect on the nervous system. Pubmed, EMBASE and Scopus were screened for studies investigating the effect of acupuncture on thermal or mechanical detection or pain thresholds in humans published in English or German. A meta-analysis of high quality studies was performed. Out of 3007 identified articles 85 were included. Sixty five studies showed that acupuncture affects at least one sensory threshold. Most studies assessed the pressure pain threshold of which 80% reported an increase after acupuncture. Significant short- and long-term effects on the pressure pain threshold in pain patients were revealed by two meta-analyses including four and two high quality studies, respectively. In over 60% of studies, acupuncture reduced sensitivity to noxious thermal stimuli, but measuring methods might influence results. Few but consistent data indicate that acupuncture reduces pin-prick like pain but not mechanical detection. Results on thermal detection are heterogeneous. Sensory threshold changes were equally frequent reported after manual acupuncture as after electroacupuncture. Among 48 sham-controlled studies, 25 showed stronger effects on sensory thresholds through verum than through sham acupuncture, but in 9 studies significant threshold changes were also observed after sham acupuncture. Overall, there is a lack of high quality acupuncture studies applying comprehensive assessments of sensory perception. Our findings indicate that acupuncture affects sensory perception. Results are most compelling for the pressure pain threshold, especially in pain conditions associated with tenderness. Sham acupuncture can also cause such effects. Future studies should incorporate comprehensive, standardized assessments of sensory profiles in order to fully characterize its

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.

Conscious and unconscious sensory inflows allow effective control of the functions of the human brain and heart at the initial ageing stage.

Science.gov (United States)

Bykov, Anatolij T; Malyarenko, Tatyana N; Malyarenko, Yurij E; Terentjev, Vladimir P; Dyuzhikov, Alexandr A

2006-11-01

The authors of the present article based their assumption on the concept that the sensory systems are the "windows to the brain" through which various functions of the human organism can be controlled. Comprehension of the fundamental mechanisms of the optimization of the sensory systems, brain, and cardiac functions has increased based on the prolonged sensory flows using conscious and unconscious aromatherapy and multimodal sensory activation. Sensory flow evoked stable systemic responses, including adaptive alteration of psycho-emotional state, attention, memory, sensorimotor reactions, intersensory interaction, visual information processing, statokinetic stability, and autonomic heart rhythm control. The efficacy and expediency of the use of sensory flow for non-medicinal correction of vital functions of the human organism at the initial stages of ageing was revealed.

The sensory side of post-stroke motor rehabilitation.

Science.gov (United States)

Bolognini, Nadia; Russo, Cristina; Edwards, Dylan J

2016-04-11

Contemporary strategies to promote motor recovery following stroke focus on repetitive voluntary movements. Although successful movement relies on efficient sensorimotor integration, functional outcomes often bias motor therapy toward motor-related impairments such as weakness, spasticity and synergies; sensory therapy and reintegration is implied, but seldom targeted. However, the planning and execution of voluntary movement requires that the brain extracts sensory information regarding body position and predicts future positions, by integrating a variety of sensory inputs with ongoing and planned motor activity. Neurological patients who have lost one or more of their senses may show profoundly affected motor functions, even if muscle strength remains unaffected. Following stroke, motor recovery can be dictated by the degree of sensory disruption. Consequently, a thorough account of sensory function might be both prognostic and prescriptive in neurorehabilitation. This review outlines the key sensory components of human voluntary movement, describes how sensory disruption can influence prognosis and expected outcomes in stroke patients, reports on current sensory-based approaches in post-stroke motor rehabilitation, and makes recommendations for optimizing rehabilitation programs based on sensory stimulation.

A review of invasive and non-invasive sensory feedback in upper limb prostheses.

Science.gov (United States)

Svensson, Pamela; Wijk, Ulrika; Björkman, Anders; Antfolk, Christian

2017-06-01

The constant challenge to restore sensory feedback in prosthetic hands has provided several research solutions, but virtually none has reached clinical fruition. A prosthetic hand with sensory feedback that closely imitates an intact hand and provides a natural feeling may induce the prosthetic hand to be included in the body image and also reinforces the control of the prosthesis. Areas covered: This review presents non-invasive sensory feedback systems such as mechanotactile, vibrotactile, electrotactile and combinational systems which combine the modalities; multi-haptic feedback. Invasive sensory feedback has been tried less, because of the inherent risk, but it has successfully shown to restore some afferent channels. In this review, invasive methods are also discussed, both extraneural and intraneural electrodes, such as cuff electrodes and transverse intrafascicular multichannel electrodes. The focus of the review is on non-invasive methods of providing sensory feedback to upper-limb amputees. Expert commentary: Invoking embodiment has shown to be of importance for the control of prosthesis and acceptance by the prosthetic wearers. It is a challenge to provide conscious feedback to cover the lost sensibility of a hand, not be overwhelming and confusing for the user, and to integrate technology within the constraint of a wearable prosthesis.

Sensory profile of eleven peach cultivars Perfil sensorial de onze cultivares de pêssegos

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.Este trabalho teve como objetivo avaliar o perfil sensorial de onze cultivares de pêssego produzidos em duas safras em um pomar experimental implantado na Lapa (PR, Brasil. Os cultivares analisados foram Aurora I, Chimarrita, Chiripá, Coral, Eldorado, Granada, Leonense, Maciel, Marli, Premier e Vanguarda. As análises sensoriais foram realizadas por julgadores previamente treinados, sendo 20 julgadores na primeira safra e 10 na segunda. O método de avaliação empregado foi a Análise Descritiva Quantitativa na qual foram mensurados os atributos aparência, aroma, cor de polpa, firmeza de polpa, sabor e suculência dos frutos. Os resultados obtidos demonstraram a preferência por frutos de sabor adocicado, com polpa macia e suculenta. Os cultivares Chimarrita, Chiripá e Coral obtiveram o melhor desempenho nas análises sensoriais. Foi verificado ainda que os atributos aroma, firmeza de polpa e sabor são considerados suficientes para a avaliação do perfil sensorial de

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.

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.

Integration of Plasticity Mechanisms within a Single Sensory Neuron of C. elegans Actuates a Memory.

Science.gov (United States)

Hawk, Josh D; Calvo, Ana C; Liu, Ping; Almoril-Porras, Agustin; Aljobeh, Ahmad; Torruella-Suárez, María Luisa; Ren, Ivy; Cook, Nathan; Greenwood, Joel; Luo, Linjiao; Wang, Zhao-Wen; Samuel, Aravinthan D T; Colón-Ramos, Daniel A

2018-01-17

Neural plasticity, the ability of neurons to change their properties in response to experiences, underpins the nervous system's capacity to form memories and actuate behaviors. How different plasticity mechanisms act together in vivo and at a cellular level to transform sensory information into behavior is not well understood. We show that in Caenorhabditis elegans two plasticity mechanisms-sensory adaptation and presynaptic plasticity-act within a single cell to encode thermosensory information and actuate a temperature preference memory. Sensory adaptation adjusts the temperature range of the sensory neuron (called AFD) to optimize detection of temperature fluctuations associated with migration. Presynaptic plasticity in AFD is regulated by the conserved kinase nPKCε and transforms thermosensory information into a behavioral preference. Bypassing AFD presynaptic plasticity predictably changes learned behavioral preferences without affecting sensory responses. Our findings indicate that two distinct neuroplasticity mechanisms function together through a single-cell logic system to enact thermotactic behavior. VIDEO ABSTRACT. Copyright © 2017 Elsevier Inc. All rights reserved.

Sensory determinants of the autonomous sensory meridian response (ASMR): understanding the triggers.

Science.gov (United States)

Barratt, Emma L; Spence, Charles; Davis, Nick J

2017-01-01

The autonomous sensory meridian response (ASMR) is an atypical sensory phenomenon involving electrostatic-like tingling sensations in response to certain sensory, primarily audio-visual, stimuli. The current study used an online questionnaire, completed by 130 people who self-reported experiencing ASMR. We aimed to extend preliminary investigations into the experience, and establish key multisensory factors contributing to the successful induction of ASMR through online media. Aspects such as timing and trigger load, atmosphere, and characteristics of ASMR content, ideal spatial distance from various types of stimuli, visual characteristics, context and use of ASMR triggers, and audio preferences are explored. Lower-pitched, complex sounds were found to be especially effective triggers, as were slow-paced, detail-focused videos. Conversely, background music inhibited the sensation for many respondents. These results will help in designing media for ASMR induction.

Sensory determinants of the autonomous sensory meridian response (ASMR: understanding the triggers

Directory of Open Access Journals (Sweden)

Emma L. Barratt

2017-10-01

Full Text Available The autonomous sensory meridian response (ASMR is an atypical sensory phenomenon involving electrostatic-like tingling sensations in response to certain sensory, primarily audio-visual, stimuli. The current study used an online questionnaire, completed by 130 people who self-reported experiencing ASMR. We aimed to extend preliminary investigations into the experience, and establish key multisensory factors contributing to the successful induction of ASMR through online media. Aspects such as timing and trigger load, atmosphere, and characteristics of ASMR content, ideal spatial distance from various types of stimuli, visual characteristics, context and use of ASMR triggers, and audio preferences are explored. Lower-pitched, complex sounds were found to be especially effective triggers, as were slow-paced, detail-focused videos. Conversely, background music inhibited the sensation for many respondents. These results will help in designing media for ASMR induction.

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.

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.

Color, flavor, and sensory characteristics of gamma-irradiated salted and fermented anchovy sauce[Gamma irradiation; Fermented anchovy; Color; Flavor compounds; Electronic nose; Sensory evaluation

Energy Technology Data Exchange (ETDEWEB)

Kim, J.H.; Ahn, Hyun Joo; Yook, Hong Sun; Kim, Kyong Soo; Rhee, Moon Soo; Ryu, Gi Hyung; Byun, Myung Woo E-mail: mwbyun@kaeri.re.kr

2004-02-01

Color, flavor, and sensory characteristics of irradiated salted and fermented anchovy sauce were investigated. The filtrate of salted and fermented anchovy was irradiated at 0, 2.5, 5, 7.5, and 10 kGy. After irradiation, Hunter's color values were increased, however, the color values were gradually decreased in all samples during storage. Amount of the aldehydes, esters, ketones, S-containing compounds, and the other groups were increased up to 7.5 kGy irradiation, then decreased at 10 kGy (P<0.05), while the alcohols and furan groups were increased by irradiation. Different odor patterns were observed among samples using electronic nose system analysis. Gamma-irradiated samples showed better sensory score and the quality was sustained during storage. In conclusion, gamma irradiation of salted and fermented anchovy sauce could improve its sensory quality by reducing typical fishy smell.

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.

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...

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

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.

BMP4 signaling is involved in the generation of inner ear sensory epithelia

Directory of Open Access Journals (Sweden)

Wang Yucheng

2005-08-01

Full Text Available Abstract Background The robust expression of BMP4 in the incipient sensory organs of the inner ear suggests possible roles for this signaling protein during induction and development of auditory and vestibular sensory epithelia. Homozygous BMP4-/- animals die before the inner ear's sensory organs develop, which precludes determining the role of BMP4 in these organs with simple gene knockout experiments. Results Here we use a chicken otocyst culture system to perform quantitative studies on the development of inner ear cell types and show that hair cell and supporting cell generation is remarkably reduced when BMP signaling is blocked, either with its antagonist noggin or by using soluble BMP receptors. Conversely, we observed an increase in the number of hair cells when cultured otocysts were treated with exogenous BMP4. BMP4 treatment additionally prompted down-regulation of Pax-2 protein in proliferating sensory epithelial progenitors, leading to reduced progenitor cell proliferation. Conclusion Our results implicate BMP4 in two events during chicken inner ear sensory epithelium formation: first, in inducing the switch from proliferative sensory epithelium progenitors to differentiating epithelial cells and secondly, in promoting the differentiation of hair cells within the developing sensory epithelia.

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.

Gain control network conditions in early sensory coding.

Directory of Open Access Journals (Sweden)

Eduardo Serrano

Full Text Available Gain control is essential for the proper function of any sensory system. However, the precise mechanisms for achieving effective gain control in the brain are unknown. Based on our understanding of the existence and strength of connections in the insect olfactory system, we analyze the conditions that lead to controlled gain in a randomly connected network of excitatory and inhibitory neurons. We consider two scenarios for the variation of input into the system. In the first case, the intensity of the sensory input controls the input currents to a fixed proportion of neurons of the excitatory and inhibitory populations. In the second case, increasing intensity of the sensory stimulus will both, recruit an increasing number of neurons that receive input and change the input current that they receive. Using a mean field approximation for the network activity we derive relationships between the parameters of the network that ensure that the overall level of activity of the excitatory population remains unchanged for increasing intensity of the external stimulation. We find that, first, the main parameters that regulate network gain are the probabilities of connections from the inhibitory population to the excitatory population and of the connections within the inhibitory population. Second, we show that strict gain control is not achievable in a random network in the second case, when the input recruits an increasing number of neurons. Finally, we confirm that the gain control conditions derived from the mean field approximation are valid in simulations of firing rate models and Hodgkin-Huxley conductance based models.

Differential and Cooperative Cell Adhesion Regulates Cellular Pattern in Sensory Epithelia.

Science.gov (United States)

Togashi, Hideru

2016-01-01

Animal tissues are composed of multiple cell types arranged in complex and elaborate patterns. In sensory epithelia, including the auditory epithelium and olfactory epithelium, different types of cells are arranged in unique mosaic patterns. These mosaic patterns are evolutionarily conserved, and are thought to be important for hearing and olfaction. Recent progress has provided accumulating evidence that the cellular pattern formation in epithelia involves cell rearrangements, movements, and shape changes. These morphogenetic processes are largely mediated by intercellular adhesion systems. Differential adhesion and cortical tension have been proposed to promote cell rearrangements. Many different types of cells in tissues express various types of cell adhesion molecules. Although cooperative mechanisms between multiple adhesive systems are likely to contribute to the production of complex cell patterns, our current understanding of the cooperative roles between multiple adhesion systems is insufficient to entirely explain the complex mechanisms underlying cellular patterning. Recent studies have revealed that nectins, in cooperation with cadherins, are crucial for the mosaic cellular patterning in sensory organs. The nectin and cadherin systems are interacted with one another, and these interactions provide cells with differential adhesive affinities for complex cellular pattern formations in sensory epithelia, which cannot be achieved by a single mechanism.

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...

Role of sufficient statistics in stochastic thermodynamics and its implication to sensory adaptation

Science.gov (United States)

Matsumoto, Takumi; Sagawa, Takahiro

2018-04-01

A sufficient statistic is a significant concept in statistics, which means a probability variable that has sufficient information required for an inference task. We investigate the roles of sufficient statistics and related quantities in stochastic thermodynamics. Specifically, we prove that for general continuous-time bipartite networks, the existence of a sufficient statistic implies that an informational quantity called the sensory capacity takes the maximum. Since the maximal sensory capacity imposes a constraint that the energetic efficiency cannot exceed one-half, our result implies that the existence of a sufficient statistic is inevitably accompanied by energetic dissipation. We also show that, in a particular parameter region of linear Langevin systems there exists the optimal noise intensity at which the sensory capacity, the information-thermodynamic efficiency, and the total entropy production are optimized at the same time. We apply our general result to a model of sensory adaptation of E. coli and find that the sensory capacity is nearly maximal with experimentally realistic parameters.

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.

Tactile and non-tactile sensory paradigms for fMRI and neurophysiologic studies in rodents.

Science.gov (United States)

Sanganahalli, Basavaraju G; Bailey, Christopher J; Herman, Peter; Hyder, Fahmeed

2009-01-01

Functional magnetic resonance imaging (fMRI) has become a popular functional imaging tool for human studies. Future diagnostic use of fMRI depends, however, on a suitable neurophysiologic interpretation of the blood oxygenation level dependent (BOLD) signal change. This particular goal is best achieved in animal models primarily due to the invasive nature of other methods used and/or pharmacological agents applied to probe different nuances of neuronal (and glial) activity coupled to the BOLD signal change. In the last decade, we have directed our efforts towards the development of stimulation protocols for a variety of modalities in rodents with fMRI. Cortical perception of the natural world relies on the formation of multi-dimensional representation of stimuli impinging on the different sensory systems, leading to the hypothesis that a sensory stimulus may have very different neurophysiologic outcome(s) when paired with a near simultaneous event in another modality. Before approaching this level of complexity, reliable measures must be obtained of the relatively small changes in the BOLD signal and other neurophysiologic markers (electrical activity, blood flow) induced by different peripheral stimuli. Here we describe different tactile (i.e., forepaw, whisker) and non-tactile (i.e., olfactory, visual) sensory paradigms applied to the anesthetized rat. The main focus is on development and validation of methods for reproducible stimulation of each sensory modality applied independently or in conjunction with one another, both inside and outside the magnet. We discuss similarities and/or differences across the sensory systems as well as advantages they may have for studying essential neuroscientific questions. We envisage that the different sensory paradigms described here may be applied directly to studies of multi-sensory interactions in anesthetized rats, en route to a rudimentary understanding of the awake functioning brain where various sensory cues presumably

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.

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.

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.

National Survey of Sensory Features in Children with ASD: Factor Structure of the Sensory Experience Questionnaire (3.0)

Science.gov (United States)

Ausderau, Karla; Sideris, John; Furlong, Melissa; Little, Lauren M.; Bulluck, John; Baranek, Grace T.

2014-01-01

This national online survey study characterized sensory features in 1,307 children with autism spectrum disorder (ASD) ages 2-12 years using the Sensory Experiences Questionnaire Version 3.0 (SEQ-3.0). Using the SEQ-3.0, a confirmatory factor analytic model with four substantive factors of hypothesized sensory response patterns (i.e.,…

Modelling the influence of sensory dynamics on linear and nonlinear driver steering control

Science.gov (United States)

Nash, C. J.; Cole, D. J.

2018-05-01

A recent review of the literature has indicated that sensory dynamics play an important role in the driver-vehicle steering task, motivating the design of a new driver model incorporating human sensory systems. This paper presents a full derivation of the linear driver model developed in previous work, and extends the model to control a vehicle with nonlinear tyres. Various nonlinear controllers and state estimators are compared with different approximations of the true system dynamics. The model simulation time is found to increase significantly with the complexity of the controller and state estimator. In general the more complex controllers perform best, although with certain vehicle and tyre models linearised controllers perform as well as a full nonlinear optimisation. Various extended Kalman filters give similar results, although the driver's sensory dynamics reduce control performance compared with full state feedback. The new model could be used to design vehicle systems which interact more naturally and safely with a human driver.

A Multi-Sensorial Hybrid Control for Robotic Manipulation in Human-Robot Workspaces

Directory of Open Access Journals (Sweden)

Juan A. Corrales

2011-10-01

Full Text Available Autonomous manipulation in semi-structured environments where human operators can interact is an increasingly common task in robotic applications. This paper describes an intelligent multi-sensorial approach that solves this issue by providing a multi-robotic platform with a high degree of autonomy and the capability to perform complex tasks. The proposed sensorial system is composed of a hybrid visual servo control to efficiently guide the robot towards the object to be manipulated, an inertial motion capture system and an indoor localization system to avoid possible collisions between human operators and robots working in the same workspace, and a tactile sensor algorithm to correctly manipulate the object. The proposed controller employs the whole multi-sensorial system and combines the measurements of each one of the used sensors during two different phases considered in the robot task: a first phase where the robot approaches the object to be grasped, and a second phase of manipulation of the object. In both phases, the unexpected presence of humans is taken into account. This paper also presents the successful results obtained in several experimental setups which verify the validity of the proposed approach.

Impairments of Multisensory Integration and Cross-Sensory Learning as Pathways to Dyslexia

Science.gov (United States)

Hahn, Noemi; Foxe, John J.; Molholm, Sophie

2014-01-01

Two sensory systems are intrinsic to learning to read. Written words enter the brain through the visual system and associated sounds through the auditory system. The task before the beginning reader is quite basic. She must learn correspondences between orthographic tokens and phonemic utterances, and she must do this to the point that there is seamless automatic ‘connection’ between these sensorially distinct units of language. It is self-evident then that learning to read requires formation of cross-sensory associations to the point that deeply encoded multisensory representations are attained. While the majority of individuals manage this task to a high degree of expertise, some struggle to attain even rudimentary capabilities. Why do dyslexic individuals, who learn well in myriad other domains, fail at this particular task? Here, we examine the literature as it pertains to multisensory processing in dyslexia. We find substantial support for multisensory deficits in dyslexia, and make the case that to fully understand its neurological basis, it will be necessary to thoroughly probe the integrity of auditory-visual integration mechanisms. PMID:25265514

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.

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

Multisensory representation of frequency across audition and touch: high density electrical mapping reveals early sensory-perceptual coupling.

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Butler, John S; Foxe, John J; Fiebelkorn, Ian C; Mercier, Manuel R; Molholm, Sophie

2012-10-31

The frequency of environmental vibrations is sampled by two of the major sensory systems, audition and touch, notwithstanding that these signals are transduced through very different physical media and entirely separate sensory epithelia. Psychophysical studies have shown that manipulating frequency in audition or touch can have a significant cross-sensory impact on perceived frequency in the other sensory system, pointing to intimate links between these senses during computation of frequency. In this regard, the frequency of a vibratory event can be thought of as a multisensory perceptual construct. In turn, electrophysiological studies point to temporally early multisensory interactions that occur in hierarchically early sensory regions where convergent inputs from the auditory and somatosensory systems are to be found. A key question pertains to the level of processing at which the multisensory integration of featural information, such as frequency, occurs. Do the sensory systems calculate frequency independently before this information is combined, or is this feature calculated in an integrated fashion during preattentive sensory processing? The well characterized mismatch negativity, an electrophysiological response that indexes preattentive detection of a change within the context of a regular pattern of stimulation, served as our dependent measure. High-density electrophysiological recordings were made in humans while they were presented with separate blocks of somatosensory, auditory, and audio-somatosensory "standards" and "deviants," where the deviant differed in frequency. Multisensory effects were identified beginning at ∼200 ms, with the multisensory mismatch negativity (MMN) significantly different from the sum of the unisensory MMNs. This provides compelling evidence for preattentive coupling between the somatosensory and auditory channels in the cortical representation of frequency.

Maturation of Sensori-Motor Functional Responses in the Preterm Brain.

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Allievi, Alessandro G; Arichi, Tomoki; Tusor, Nora; Kimpton, Jessica; Arulkumaran, Sophie; Counsell, Serena J; Edwards, A David; Burdet, Etienne

2016-01-01

Preterm birth engenders an increased risk of conditions like cerebral palsy and therefore this time may be crucial for the brain's developing sensori-motor system. However, little is known about how cortical sensori-motor function matures at this time, whether development is influenced by experience, and about its role in spontaneous motor behavior. We aimed to systematically characterize spatial and temporal maturation of sensori-motor functional brain activity across this period using functional MRI and a custom-made robotic stimulation device. We studied 57 infants aged from 30 + 2 to 43 + 2 weeks postmenstrual age. Following both induced and spontaneous right wrist movements, we saw consistent positive blood oxygen level-dependent functional responses in the contralateral (left) primary somatosensory and motor cortices. In addition, we saw a maturational trend toward faster, higher amplitude, and more spatially dispersed functional responses; and increasing integration of the ipsilateral hemisphere and sensori-motor associative areas. We also found that interhemispheric functional connectivity was significantly related to ex-utero exposure, suggesting the influence of experience-dependent mechanisms. At term equivalent age, we saw a decrease in both response amplitude and interhemispheric functional connectivity, and an increase in spatial specificity, culminating in the establishment of a sensori-motor functional response similar to that seen in adults. © The Author 2015. Published by Oxford University Press.