Oscillatory Reinstatement Enhances Declarative Memory.

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Javadi, Amir-Homayoun; Glen, James C; Halkiopoulos, Sara; Schulz, Mei; Spiers, Hugo J

2017-10-11

Declarative memory recall is thought to involve the reinstatement of neural activity patterns that occurred previously during encoding. Consistent with this view, greater similarity between patterns of activity recorded during encoding and retrieval has been found to predict better memory performance in a number of studies. Recent models have argued that neural oscillations may be crucial to reinstatement for successful memory retrieval. However, to date, no causal evidence has been provided to support this theory, nor has the impact of oscillatory electrical brain stimulation during encoding and retrieval been assessed. To explore this we used transcranial alternating current stimulation over the left dorsolateral prefrontal cortex of human participants [ n = 70, 45 females; age mean (SD) = 22.12 (2.16)] during a declarative memory task. Participants received either the same frequency during encoding and retrieval (60-60 or 90-90 Hz) or different frequencies (60-90 or 90-60 Hz). When frequencies matched there was a significant memory improvement (at both 60 and 90 Hz) relative to sham stimulation. No improvement occurred when frequencies mismatched. Our results provide support for the role of oscillatory reinstatement in memory retrieval. SIGNIFICANCE STATEMENT Recent neurobiological models of memory have argued that large-scale neural oscillations are reinstated to support successful memory retrieval. Here we used transcranial alternating current stimulation (tACS) to test these models. tACS has recently been shown to induce neural oscillations at the frequency stimulated. We stimulated over the left dorsolateral prefrontal cortex during a declarative memory task involving learning a set of words. We found that tACS applied at the same frequency during encoding and retrieval enhances memory. We also find no difference between the two applied frequencies. Thus our results are consistent with the proposal that reinstatement of neural oscillations during retrieval

Oscillatory activity reflects differential use of spatial reference frames by sighted and blind individuals in tactile attention.

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Schubert, Jonathan T W; Buchholz, Verena N; Föcker, Julia; Engel, Andreas K; Röder, Brigitte; Heed, Tobias

2015-08-15

Touch can be localized either on the skin in anatomical coordinates, or, after integration with posture, in external space. Sighted individuals are thought to encode touch in both coordinate systems concurrently, whereas congenitally blind individuals exhibit a strong bias for using anatomical coordinates. We investigated the neural correlates of this differential dominance in the use of anatomical and external reference frames by assessing oscillatory brain activity during a tactile spatial attention task. The EEG was recorded while sighted and congenitally blind adults received tactile stimulation to uncrossed and crossed hands while detecting rare tactile targets at one cued hand only. In the sighted group, oscillatory alpha-band activity (8-12Hz) in the cue-target interval was reduced contralaterally and enhanced ipsilaterally with uncrossed hands. Hand crossing attenuated the degree of posterior parietal alpha-band lateralization, indicating that attention deployment was affected by external spatial coordinates. Beamforming suggested that this posture effect originated in the posterior parietal cortex. In contrast, cue-related lateralization of central alpha-band as well as of beta-band activity (16-24Hz) were unaffected by hand crossing, suggesting that these oscillations exclusively encode anatomical coordinates. In the blind group, central alpha-band activity was lateralized, but did not change across postures. The pattern of beta-band activity was indistinguishable between groups. Because the neural mechanisms for posterior alpha-band generation seem to be linked to developmental vision, we speculate that the lack of this neural mechanism in blind individuals is related to their preferred use of anatomical over external spatial codes in sensory processing. Copyright © 2015 Elsevier Inc. All rights reserved.

Oscillatory integration windows in neurons

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Gupta, Nitin; Singh, Swikriti Saran; Stopfer, Mark

2016-01-01

Oscillatory synchrony among neurons occurs in many species and brain areas, and has been proposed to help neural circuits process information. One hypothesis states that oscillatory input creates cyclic integration windows: specific times in each oscillatory cycle when postsynaptic neurons become especially responsive to inputs. With paired local field potential (LFP) and intracellular recordings and controlled stimulus manipulations we directly test this idea in the locust olfactory system. We find that inputs arriving in Kenyon cells (KCs) sum most effectively in a preferred window of the oscillation cycle. With a computational model, we show that the non-uniform structure of noise in the membrane potential helps mediate this process. Further experiments performed in vivo demonstrate that integration windows can form in the absence of inhibition and at a broad range of oscillation frequencies. Our results reveal how a fundamental coincidence-detection mechanism in a neural circuit functions to decode temporally organized spiking. PMID:27976720

Brain oscillatory substrates of visual short-term memory capacity.

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Sauseng, Paul; Klimesch, Wolfgang; Heise, Kirstin F; Gruber, Walter R; Holz, Elisa; Karim, Ahmed A; Glennon, Mark; Gerloff, Christian; Birbaumer, Niels; Hummel, Friedhelm C

2009-11-17

The amount of information that can be stored in visual short-term memory is strictly limited to about four items. Therefore, memory capacity relies not only on the successful retention of relevant information but also on efficient suppression of distracting information, visual attention, and executive functions. However, completely separable neural signatures for these memory capacity-limiting factors remain to be identified. Because of its functional diversity, oscillatory brain activity may offer a utile solution. In the present study, we show that capacity-determining mechanisms, namely retention of relevant information and suppression of distracting information, are based on neural substrates independent of each other: the successful maintenance of relevant material in short-term memory is associated with cross-frequency phase synchronization between theta (rhythmical neural activity around 5 Hz) and gamma (> 50 Hz) oscillations at posterior parietal recording sites. On the other hand, electroencephalographic alpha activity (around 10 Hz) predicts memory capacity based on efficient suppression of irrelevant information in short-term memory. Moreover, repetitive transcranial magnetic stimulation at alpha frequency can modulate short-term memory capacity by influencing the ability to suppress distracting information. Taken together, the current study provides evidence for a double dissociation of brain oscillatory correlates of visual short-term memory capacity.

Cortical gamma activity during auditory tone omission provides evidence for the involvement of oscillatory activity in top-down processing.

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Gurtubay, I G; Alegre, M; Valencia, M; Artieda, J

2006-11-01

Perception is an active process in which our brains use top-down influences to modulate afferent information. To determine whether this modulation might be based on oscillatory activity, we asked seven subjects to detect a silence that appeared randomly in a rhythmic auditory sequence, counting the number of omissions ("count" task), or responding to each omission with a right index finger extension ("move" task). Despite the absence of physical stimuli, these tasks induced a 'non-phase-locked' gamma oscillation in temporal-parietal areas, providing evidence of intrinsically generated oscillatory activity during top-down processing. This oscillation is probably related to the local neural activation that takes place during the process of stimulus detection, involving the functional comparison between the tones and the absence of stimuli as well as the auditory echoic memory processes. The amplitude of the gamma oscillations was reduced with the repetition of the tasks. Moreover, it correlated positively with the number of correctly detected omissions and negatively with the reaction time. These findings indicate that these oscillations, like others described, may be modulated by attentional processes. In summary, our findings support the active and adaptive concept of brain function that has emerged over recent years, suggesting that the match of sensory information with memory contents generates gamma oscillations.

Cerebral oscillatory activity during simulated driving using MEG

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Kotoe eSakihara

2014-12-01

Full Text Available We aimed to examine cerebral oscillatory differences associated with psychological processes during simulated car driving. We recorded neuromagnetic signals in 14 healthy volunteers using magnetoencephalography (MEG during simulated driving. MEG data were analyzed using synthetic aperture magnetometry to detect the spatial distribution of cerebral oscillations. Group effects between subjects were analyzed statistically using a nonparametric permutation test. Oscillatory differences were calculated by comparison between passive viewing and active driving. Passive viewing was the baseline, and oscillatory differences during active driving showed an increase or decrease in comparison with a baseline. Power increase in the theta band was detected in the superior frontal gyrus (SFG during active driving. Power decreases in the alpha, beta, and low gamma bands were detected in the right inferior parietal lobe (IPL, left postcentral gyrus (PoCG, middle temporal gyrus (MTG, and posterior cingulate gyrus (PCiG during active driving. Power increase in the theta band in the SFG may play a role in attention. Power decrease in the right IPL may reflect selectively divided attention and visuospatial processing, whereas that in the left PoCG reflects sensorimotor activation related to driving manipulation. Power decreases in the MTG and PCiG may be associated with object recognition.

Enhanced Gamma Oscillatory Activity in Rats with Chronic Inflammatory Pain

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Wang, Jing; Wang, Jing; Xing, Guo-Gang; Li, Xiaoli; Wan, You

2016-01-01

It has been reported that oscillatory gamma activity participates in brief acute pain and tonic ongoing pain. It is of great interest to determine whether the gamma activity is involved in chronic pain since chronic pain is a more severe pathological condition characterized by pain persistency. To investigate the oscillatory gamma activity in chronic pain, in the present study, we recorded spontaneous electrocorticogram (ECoG) signals during chronic pain development in rats with chronic infla...

Changes of spontaneous oscillatory activity to tonic heat pain.

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Peng, Weiwei; Hu, Li; Zhang, Zhiguo; Hu, Yong

2014-01-01

Transient painful stimuli could induce suppression of alpha oscillatory activities and enhancement of gamma oscillatory activities that also could be greatly modulated by attention. Here, we attempted to characterize changes in cortical activities during tonic heat pain perception and investigated the influence of directed/distracted attention on these responses. We collected 5-minute long continuous Electroencephalography (EEG) data from 38 healthy volunteers during four conditions presented in a counterbalanced order: (A) resting condition; (B) innoxious-distracted condition; (C) noxious-distracted condition; (D) noxious-attended condition. The effects of tonic heat pain stimulation and selective attention on oscillatory activities were investigated by comparing the EEG power spectra among the four experimental conditions and assessing the relationship between spectral power difference and subjective pain intensity. The change of oscillatory activities in condition D was characterized by stable and persistent decrease of alpha oscillation power over contralateral-central electrodes and widespread increase of gamma oscillation power, which were even significantly correlated with subjective pain intensity. Since EEG responses in the alpha and gamma frequency band were affected by attention in different manners, they are likely related to different aspects of the multidimensional sensory experience of pain. The observed contralateral-central alpha suppression (conditions D vs. B and D vs. C) may reflect primarily a top-down cognitive process such as attention, while the widespread gamma enhancement (conditions D vs. A) may partly reflect tonic pain processing, representing the summary effects of bottom-up stimulus-related and top-down subject-driven cognitive processes.

Changes of spontaneous oscillatory activity to tonic heat pain.

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Weiwei Peng

Full Text Available Transient painful stimuli could induce suppression of alpha oscillatory activities and enhancement of gamma oscillatory activities that also could be greatly modulated by attention. Here, we attempted to characterize changes in cortical activities during tonic heat pain perception and investigated the influence of directed/distracted attention on these responses. We collected 5-minute long continuous Electroencephalography (EEG data from 38 healthy volunteers during four conditions presented in a counterbalanced order: (A resting condition; (B innoxious-distracted condition; (C noxious-distracted condition; (D noxious-attended condition. The effects of tonic heat pain stimulation and selective attention on oscillatory activities were investigated by comparing the EEG power spectra among the four experimental conditions and assessing the relationship between spectral power difference and subjective pain intensity. The change of oscillatory activities in condition D was characterized by stable and persistent decrease of alpha oscillation power over contralateral-central electrodes and widespread increase of gamma oscillation power, which were even significantly correlated with subjective pain intensity. Since EEG responses in the alpha and gamma frequency band were affected by attention in different manners, they are likely related to different aspects of the multidimensional sensory experience of pain. The observed contralateral-central alpha suppression (conditions D vs. B and D vs. C may reflect primarily a top-down cognitive process such as attention, while the widespread gamma enhancement (conditions D vs. A may partly reflect tonic pain processing, representing the summary effects of bottom-up stimulus-related and top-down subject-driven cognitive processes.

Saccadic reaction times to audiovisual stimuli show effects of oscillatory phase reset.

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Adele Diederich

Full Text Available Initiating an eye movement towards a suddenly appearing visual target is faster when an accessory auditory stimulus occurs in close spatiotemporal vicinity. Such facilitation of saccadic reaction time (SRT is well-documented, but the exact neural mechanisms underlying the crossmodal effect remain to be elucidated. From EEG/MEG studies it has been hypothesized that coupled oscillatory activity in primary sensory cortices regulates multisensory processing. Specifically, it is assumed that the phase of an ongoing neural oscillation is shifted due to the occurrence of a sensory stimulus so that, across trials, phase values become highly consistent (phase reset. If one can identify the phase an oscillation is reset to, it is possible to predict when temporal windows of high and low excitability will occur. However, in behavioral experiments the pre-stimulus phase will be different on successive repetitions of the experimental trial, and average performance over many trials will show no signs of the modulation. Here we circumvent this problem by repeatedly presenting an auditory accessory stimulus followed by a visual target stimulus with a temporal delay varied in steps of 2 ms. Performing a discrete time series analysis on SRT as a function of the delay, we provide statistical evidence for the existence of distinct peak spectral components in the power spectrum. These frequencies, although varying across participants, fall within the beta and gamma range (20 to 40 Hz of neural oscillatory activity observed in neurophysiological studies of multisensory integration. Some evidence for high-theta/alpha activity was found as well. Our results are consistent with the phase reset hypothesis and demonstrate that it is amenable to testing by purely psychophysical methods. Thus, any theory of multisensory processes that connects specific brain states with patterns of saccadic responses should be able to account for traces of oscillatory activity in observable

The role of high-frequency oscillatory activity in reward processing and learning.

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Marco-Pallarés, Josep; Münte, Thomas F; Rodríguez-Fornells, Antoni

2015-02-01

Oscillatory activity has been proposed as a key mechanism in the integration of brain activity of distant structures. Particularly, high frequency brain oscillatory activity in the beta and gamma range has received increasing interest in the domains of attention and memory. In addition, a number of recent studies have revealed an increase of beta-gamma activity (20-35 Hz) after unexpected or relevant positive reward outcomes. In the present manuscript we review the literature on this phenomenon and we propose that this activity is a brain signature elicited by unexpected positive outcomes in order to transmit a fast motivational value signal to the reward network. In addition, we hypothesize that beta-gamma oscillatory activity indexes the interaction between attentional and emotional systems, and that it directly reflects the appearance of unexpected positive rewards in learning-related contexts. Copyright © 2014 Elsevier Ltd. All rights reserved.

Psychoacoustic Tinnitus Loudness and Tinnitus-Related Distress Show Different Associations with Oscillatory Brain Activity

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Balkenhol, Tobias; Wallhäusser-Franke, Elisabeth; Delb, Wolfgang

2013-01-01

Background The phantom auditory perception of subjective tinnitus is associated with aberrant brain activity as evidenced by magneto- and electroencephalographic studies. We tested the hypotheses (1) that psychoacoustically measured tinnitus loudness is related to gamma oscillatory band power, and (2) that tinnitus loudness and tinnitus-related distress are related to distinct brain activity patterns as suggested by the distinction between loudness and distress experienced by tinnitus patients. Furthermore, we explored (3) how hearing impairment, minimum masking level, and (4) psychological comorbidities are related to spontaneous oscillatory brain activity in tinnitus patients. Methods and Findings Resting state oscillatory brain activity recorded electroencephalographically from 46 male tinnitus patients showed a positive correlation between gamma band oscillations and psychoacoustic tinnitus loudness determined with the reconstructed tinnitus sound, but not with the other psychoacoustic loudness measures that were used. Tinnitus-related distress did also correlate with delta band activity, but at electrode positions different from those associated with tinnitus loudness. Furthermore, highly distressed tinnitus patients exhibited a higher level of theta band activity. Moreover, mean hearing loss between 0.125 kHz and 16 kHz was associated with a decrease in gamma activity, whereas minimum masking levels correlated positively with delta band power. In contrast, psychological comorbidities did not express significant correlations with oscillatory brain activity. Conclusion Different clinically relevant tinnitus characteristics show distinctive associations with spontaneous brain oscillatory power. Results support hypothesis (1), but exclusively for the tinnitus loudness derived from matching to the reconstructed tinnitus sound. This suggests to preferably use the reconstructed tinnitus spectrum to determine psychoacoustic tinnitus loudness. Results also support

EEG neural oscillatory dynamics reveal semantic and response conflict at difference levels of conflict awareness.

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Jiang, Jun; Zhang, Qinglin; Van Gaal, Simon

2015-07-14

Although previous work has shown that conflict can be detected in the absence of awareness, it is unknown how different sources of conflict (i.e., semantic, response) are processed in the human brain and whether these processes are differently modulated by conflict awareness. To explore this issue, we extracted oscillatory power dynamics from electroencephalographic (EEG) data recorded while human participants performed a modified version of the Stroop task. Crucially, in this task conflict awareness was manipulated by masking a conflict-inducing color word preceding a color patch target. We isolated semantic from response conflict by introducing four color words/patches, of which two were matched to the same response. We observed that both semantic as well as response conflict were associated with mid-frontal theta-band and parietal alpha-band power modulations, irrespective of the level of conflict awareness (high vs. low), although awareness of conflict increased these conflict-related power dynamics. These results show that both semantic and response conflict can be processed in the human brain and suggest that the neural oscillatory mechanisms in EEG reflect mainly "domain general" conflict processing mechanisms, instead of conflict source specific effects.

EEG neural oscillatory dynamics reveal semantic and response conflict at difference levels of conflict awareness

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Jiang, Jun; Zhang, Qinglin; Van Gaal, Simon

2015-01-01

Although previous work has shown that conflict can be detected in the absence of awareness, it is unknown how different sources of conflict (i.e., semantic, response) are processed in the human brain and whether these processes are differently modulated by conflict awareness. To explore this issue, we extracted oscillatory power dynamics from electroencephalographic (EEG) data recorded while human participants performed a modified version of the Stroop task. Crucially, in this task conflict awareness was manipulated by masking a conflict-inducing color word preceding a color patch target. We isolated semantic from response conflict by introducing four color words/patches, of which two were matched to the same response. We observed that both semantic as well as response conflict were associated with mid-frontal theta-band and parietal alpha-band power modulations, irrespective of the level of conflict awareness (high vs. low), although awareness of conflict increased these conflict-related power dynamics. These results show that both semantic and response conflict can be processed in the human brain and suggest that the neural oscillatory mechanisms in EEG reflect mainly “domain general” conflict processing mechanisms, instead of conflict source specific effects. PMID:26169473

The emergence of two anti-phase oscillatory neural populations in a computational model of the Parkinsonian globus pallidus

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Robert John Merrison-Hort

2013-12-01

Full Text Available Experiments in rodent models of Parkinson's Disease have demonstrated a prominent increase of oscillatory firing patterns in neurons within the Parkinsonian globus pallidus (GP which may underlie some of the motor symptoms of the disease. There are two main pathways from the cortex to GP: via the striatum and via the subthalamic nucleus (STN, but it is not known how these inputs sculpt the pathological pallidal firing patterns. To study this we developed a novel neural network model of conductance-based spiking pallidal neurons with cortex-modulated input from STN neurons. Our results support the hypothesis that entrainment occurs primarily via the subthalamic pathway. We find that as a result of the interplay between excitatory input from the STN and mutual inhibitory coupling between GP neurons, a homogeneous population of GP neurons demonstrates a self-organising dynamical behaviour where two groups of neurons emerge: one spiking in-phase with the cortical rhythm and the other in anti-phase. This finding mirrors what is seen in recordings from the GP of rodents that have had Parkinsonism induced via brain lesions. Our model also includes downregulation of Hyperpolarization-activated Cyclic Nucleotide-gated (HCN channels in response to burst firing of GP neurons, since this has been suggested as a possible mechanism for the emergence of Parkinsonian activity. We found that the downregulation of HCN channels provides even better correspondence with experimental data but that it is not essential in order for the two groups of oscillatory neurons to appear. We discuss how the influence of inhibitory striatal input will strengthen our results.

Separation of transient and oscillatory cerebral activities using over-complete rational dilation wavelet transforms

International Nuclear Information System (INIS)

Chaibi, S.; Lajnef, T.; Samet, M.; Kachouri, A.

2011-01-01

Many natural signals EEG are comprised frequency overlapping of oscillatory and transient components. In our study the intracranial EEG signals of epilepsy are composed of the superposition of oscillatory signals (HFOs: High Frequency oscillations) and a transient signals (spikes and sharp waves, etc.). The oscillatory components (HFOs) exist in the frequency band 80-500Hz. The transient components comes from nonrhythmic brain activities (spikes, sharp waves and vertex waves of varying amplitude, shape and duration) and cover a continuous wide bandwidth from low to high frequencies and resemble an HFOs events when filtered using a band pass classical filter. The classical filtering methods based on FIR filters, Wavelet transforms and the Matching Pursuit cannot separate the oscillatory from transient activities. This paper describes an approach for decomposing an iEEG signals of epilepsy into the sum of oscillatory components and a transient components based on overcomplete rational dilation wavelet transforms (overcomplete RADWT) in conjunction with morphological component analysis (MCA).

Review of the Neural Oscillations Underlying Meditation

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Darrin J. Lee

2018-03-01

Full Text Available Objective: Meditation is one type of mental training that has been shown to produce many cognitive benefits. Meditation practice is associated with improvement in concentration and reduction of stress, depression, and anxiety symptoms. Furthermore, different forms of meditation training are now being used as interventions for a variety of psychological and somatic illnesses. These benefits are thought to occur as a result of neurophysiologic changes. The most commonly studied specific meditation practices are focused attention (FA, open-monitoring (OM, as well as transcendental meditation (TM, and loving-kindness (LK meditation. In this review, we compare the neural oscillatory patterns during these forms of meditation.Method: We performed a systematic review of neural oscillations during FA, OM, TM, and LK meditation practices, comparing meditators to meditation-naïve adults.Results: FA, OM, TM, and LK meditation are associated with global increases in oscillatory activity in meditators compared to meditation-naïve adults, with larger changes occurring as the length of meditation training increases. While FA and OM are related to increases in anterior theta activity, only FA is associated with changes in posterior theta oscillations. Alpha activity increases in posterior brain regions during both FA and OM. In anterior regions, FA shows a bilateral increase in alpha power, while OM shows a decrease only in left-sided power. Gamma activity in these meditation practices is similar in frontal regions, but increases are variable in parietal and occipital regions.Conclusions: The current literature suggests distinct differences in neural oscillatory activity among FA, OM, TM, and LK meditation practices. Further characterizing these oscillatory changes may better elucidate the cognitive and therapeutic effects of specific meditation practices, and potentially lead to the development of novel neuromodulation targets to take advantage of their

Oscillatory lower body negative pressure impairs working memory task-related functional hyperemia in healthy volunteers.

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Merchant, Sana; Medow, Marvin S; Visintainer, Paul; Terilli, Courtney; Stewart, Julian M

2017-04-01

Neurovascular coupling (NVC) describes the link between an increase in task-related neural activity and increased cerebral blood flow denoted "functional hyperemia." We previously showed induced cerebral blood flow oscillations suppressed functional hyperemia; conversely functional hyperemia also suppressed cerebral blood flow oscillations. We used lower body negative pressure (OLBNP) oscillations to force oscillations in middle cerebral artery cerebral blood flow velocity (CBFv). Here, we used N-back testing, an intellectual memory challenge as a neural activation task, to test the hypothesis that OLBNP-induced oscillatory cerebral blood flow can reduce functional hyperemia and NVC produced by a working memory task and can interfere with working memory. We used OLBNP (-30 mmHg) at 0.03, 0.05, and 0.10 Hz and measured spectral power of CBFv at all frequencies. Neither OLBNP nor N-back, alone or combined, affected hemodynamic parameters. 2-Back power and OLBNP individually were compared with 2-back power during OLBNP. 2-Back alone produced a narrow band increase in oscillatory arterial pressure (OAP) and oscillatory cerebral blood flow power centered at 0.0083 Hz. Functional hyperemia in response to 2-back was reduced to near baseline and 2-back memory performance was decreased by 0.03-, 0.05-, and 0.10-Hz OLBNP. OLBNP alone produced increased oscillatory power at frequencies of oscillation not suppressed by added 2-back. However, 2-back preceding OLBNP suppressed OLBNP power. OLBNP-driven oscillatory CBFv blunts NVC and memory performance, while memory task reciprocally interfered with forced CBFv oscillations. This shows that induced cerebral blood flow oscillations suppress functional hyperemia and functional hyperemia suppresses cerebral blood flow oscillations. NEW & NOTEWORTHY We show that induced cerebral blood flow oscillations suppress functional hyperemia produced by a working memory task as well as memory task performance. We conclude that oscillatory

Bidirectional Frontoparietal Oscillatory Systems Support Working Memory.

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Johnson, Elizabeth L; Dewar, Callum D; Solbakk, Anne-Kristin; Endestad, Tor; Meling, Torstein R; Knight, Robert T

2017-06-19

The ability to represent and select information in working memory provides the neurobiological infrastructure for human cognition. For 80 years, dominant views of working memory have focused on the key role of prefrontal cortex (PFC) [1-8]. However, more recent work has implicated posterior cortical regions [9-12], suggesting that PFC engagement during working memory is dependent on the degree of executive demand. We provide evidence from neurological patients with discrete PFC damage that challenges the dominant models attributing working memory to PFC-dependent systems. We show that neural oscillations, which provide a mechanism for PFC to communicate with posterior cortical regions [13], independently subserve communications both to and from PFC-uncovering parallel oscillatory mechanisms for working memory. Fourteen PFC patients and 20 healthy, age-matched controls performed a working memory task where they encoded, maintained, and actively processed information about pairs of common shapes. In controls, the electroencephalogram (EEG) exhibited oscillatory activity in the low-theta range over PFC and directional connectivity from PFC to parieto-occipital regions commensurate with executive processing demands. Concurrent alpha-beta oscillations were observed over parieto-occipital regions, with directional connectivity from parieto-occipital regions to PFC, regardless of processing demands. Accuracy, PFC low-theta activity, and PFC → parieto-occipital connectivity were attenuated in patients, revealing a PFC-independent, alpha-beta system. The PFC patients still demonstrated task proficiency, which indicates that the posterior alpha-beta system provides sufficient resources for working memory. Taken together, our findings reveal neurologically dissociable PFC and parieto-occipital systems and suggest that parallel, bidirectional oscillatory systems form the basis of working memory. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Oscillatory mechanisms of process binding in memory.

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Klimesch, Wolfgang; Freunberger, Roman; Sauseng, Paul

2010-06-01

A central topic in cognitive neuroscience is the question, which processes underlie large scale communication within and between different neural networks. The basic assumption is that oscillatory phase synchronization plays an important role for process binding--the transient linking of different cognitive processes--which may be considered a special type of large scale communication. We investigate this question for memory processes on the basis of different types of oscillatory synchronization mechanisms. The reviewed findings suggest that theta and alpha phase coupling (and phase reorganization) reflect control processes in two large memory systems, a working memory and a complex knowledge system that comprises semantic long-term memory. It is suggested that alpha phase synchronization may be interpreted in terms of processes that coordinate top-down control (a process guided by expectancy to focus on relevant search areas) and access to memory traces (a process leading to the activation of a memory trace). An analogous interpretation is suggested for theta oscillations and the controlled access to episodic memories. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Activation energies as the validity criterion of a model for complex reactions that can be in oscillatory states

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Anić S.

2007-01-01

Full Text Available Modeling of any complex reaction system is a difficult task. If the system under examination can be in various oscillatory dynamic states, the apparent activation energies corresponding to different pathways may be of crucial importance for this purpose. In that case the activation energies can be determined by means of the main characteristics of an oscillatory process such as pre-oscillatory period, duration of the oscillatory period, the period from the beginning of the process to the end of the last oscillation, number of oscillations and others. All is illustrated on the Bray-Liebhafsky oscillatory reaction.

The motor system plays the violin: a musical metaphor inferred from the oscillatory activity of the α-motoneuron pools during locomotion.

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Chiovetto, Enrico

2011-04-01

Despite substantial advances in the field, particularly resulting from physiological studies in animals, the neural mechanisms underlying the generation of many motor behaviors in humans remain unclear. A recent study (Cappellini G et al. J Neurophysiol 104: 3064-3073, 2010) sheds more light on this topic. Like the string of a violin, the α-motoneuron pools in the spinal cord during locomotion show continuous and oscillatory patterns of activation. In this report, the implications and relevance of this finding are discussed in a general framework that includes neurophysiology, optimal control theory, and robotics.

Oscillatory brain activity in spontaneous and induced sleep stages in flies.

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Yap, Melvyn H W; Grabowska, Martyna J; Rohrscheib, Chelsie; Jeans, Rhiannon; Troup, Michael; Paulk, Angelique C; van Alphen, Bart; Shaw, Paul J; van Swinderen, Bruno

2017-11-28

Sleep is a dynamic process comprising multiple stages, each associated with distinct electrophysiological properties and potentially serving different functions. While these phenomena are well described in vertebrates, it is unclear if invertebrates have distinct sleep stages. We perform local field potential (LFP) recordings on flies spontaneously sleeping, and compare their brain activity to flies induced to sleep using either genetic activation of sleep-promoting circuitry or the GABA A agonist Gaboxadol. We find a transitional sleep stage associated with a 7-10 Hz oscillation in the central brain during spontaneous sleep. Oscillatory activity is also evident when we acutely activate sleep-promoting neurons in the dorsal fan-shaped body (dFB) of Drosophila. In contrast, sleep following Gaboxadol exposure is characterized by low-amplitude LFPs, during which dFB-induced effects are suppressed. Sleep in flies thus appears to involve at least two distinct stages: increased oscillatory activity, particularly during sleep induction, followed by desynchronized or decreased brain activity.

Oscillations during observations: Dynamic oscillatory networks serving visuospatial attention.

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Wiesman, Alex I; Heinrichs-Graham, Elizabeth; Proskovec, Amy L; McDermott, Timothy J; Wilson, Tony W

2017-10-01

The dynamic allocation of neural resources to discrete features within a visual scene enables us to react quickly and accurately to salient environmental circumstances. A network of bilateral cortical regions is known to subserve such visuospatial attention functions; however the oscillatory and functional connectivity dynamics of information coding within this network are not fully understood. Particularly, the coding of information within prototypical attention-network hubs and the subsecond functional connections formed between these hubs have not been adequately characterized. Herein, we use the precise temporal resolution of magnetoencephalography (MEG) to define spectrally specific functional nodes and connections that underlie the deployment of attention in visual space. Twenty-three healthy young adults completed a visuospatial discrimination task designed to elicit multispectral activity in visual cortex during MEG, and the resulting data were preprocessed and reconstructed in the time-frequency domain. Oscillatory responses were projected to the cortical surface using a beamformer, and time series were extracted from peak voxels to examine their temporal evolution. Dynamic functional connectivity was then computed between nodes within each frequency band of interest. We find that visual attention network nodes are defined functionally by oscillatory frequency, that the allocation of attention to the visual space dynamically modulates functional connectivity between these regions on a millisecond timescale, and that these modulations significantly correlate with performance on a spatial discrimination task. We conclude that functional hubs underlying visuospatial attention are segregated not only anatomically but also by oscillatory frequency, and importantly that these oscillatory signatures promote dynamic communication between these hubs. Hum Brain Mapp 38:5128-5140, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Effects of musical expertise on oscillatory brain activity in response to emotional sounds.

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Nolden, Sophie; Rigoulot, Simon; Jolicoeur, Pierre; Armony, Jorge L

2017-08-01

Emotions can be conveyed through a variety of channels in the auditory domain, be it via music, non-linguistic vocalizations, or speech prosody. Moreover, recent studies suggest that expertise in one sound category can impact the processing of emotional sounds in other sound categories as they found that musicians process more efficiently emotional musical and vocal sounds than non-musicians. However, the neural correlates of these modulations, especially their time course, are not very well understood. Consequently, we focused here on how the neural processing of emotional information varies as a function of sound category and expertise of participants. Electroencephalogram (EEG) of 20 non-musicians and 17 musicians was recorded while they listened to vocal (speech and vocalizations) and musical sounds. The amplitude of EEG-oscillatory activity in the theta, alpha, beta, and gamma band was quantified and Independent Component Analysis (ICA) was used to identify underlying components of brain activity in each band. Category differences were found in theta and alpha bands, due to larger responses to music and speech than to vocalizations, and in posterior beta, mainly due to differential processing of speech. In addition, we observed greater activation in frontal theta and alpha for musicians than for non-musicians, as well as an interaction between expertise and emotional content of sounds in frontal alpha. The results reflect musicians' expertise in recognition of emotion-conveying music, which seems to also generalize to emotional expressions conveyed by the human voice, in line with previous accounts of effects of expertise on musical and vocal sounds processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

Stability switches, oscillatory multistability, and spatio-temporal patterns of nonlinear oscillations in recurrently delay coupled neural networks.

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Song, Yongli; Makarov, Valeri A; Velarde, Manuel G

2009-08-01

A model of time-delay recurrently coupled spatially segregated neural assemblies is here proposed. We show that it operates like some of the hierarchical architectures of the brain. Each assembly is a neural network with no delay in the local couplings between the units. The delay appears in the long range feedforward and feedback inter-assemblies communications. Bifurcation analysis of a simple four-units system in the autonomous case shows the richness of the dynamical behaviors in a biophysically plausible parameter region. We find oscillatory multistability, hysteresis, and stability switches of the rest state provoked by the time delay. Then we investigate the spatio-temporal patterns of bifurcating periodic solutions by using the symmetric local Hopf bifurcation theory of delay differential equations and derive the equation describing the flow on the center manifold that enables us determining the direction of Hopf bifurcations and stability of the bifurcating periodic orbits. We also discuss computational properties of the system due to the delay when an external drive of the network mimicks external sensory input.

Temporal entrainment of cognitive functions: musical mnemonics induce brain plasticity and oscillatory synchrony in neural networks underlying memory.

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Thaut, Michael H; Peterson, David A; McIntosh, Gerald C

2005-12-01

In a series of experiments, we have begun to investigate the effect of music as a mnemonic device on learning and memory and the underlying plasticity of oscillatory neural networks. We used verbal learning and memory tests (standardized word lists, AVLT) in conjunction with electroencephalographic analysis to determine differences between verbal learning in either a spoken or musical (verbal materials as song lyrics) modality. In healthy adults, learning in both the spoken and music condition was associated with significant increases in oscillatory synchrony across all frequency bands. A significant difference between the spoken and music condition emerged in the cortical topography of the learning-related synchronization. When using EEG measures as predictors during learning for subsequent successful memory recall, significantly increased coherence (phase-locked synchronization) within and between oscillatory brain networks emerged for music in alpha and gamma bands. In a similar study with multiple sclerosis patients, superior learning and memory was shown in the music condition when controlled for word order recall, and subjects were instructed to sing back the word lists. Also, the music condition was associated with a significant power increase in the low-alpha band in bilateral frontal networks, indicating increased neuronal synchronization. Musical learning may access compensatory pathways for memory functions during compromised PFC functions associated with learning and recall. Music learning may also confer a neurophysiological advantage through the stronger synchronization of the neuronal cell assemblies underlying verbal learning and memory. Collectively our data provide evidence that melodic-rhythmic templates as temporal structures in music may drive internal rhythm formation in recurrent cortical networks involved in learning and memory.

Dopaminergic modulation of the spectral characteristics in the rat brain oscillatory activity

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Valencia, Miguel; López-Azcárate, Jon; Nicolás, María Jesús; Alegre, Manuel; Artieda, Julio

2012-01-01

Highlights: ► The oscillatory activity recorded at different locations of the rat brain present a power law characteristic (PLC). ► Dopaminergic drugs are able to modify the power law spectral characteristic of the oscillatory activity. ► Drugs with opposite effects over the dopaminergic system (agonists/antagonists), induce opposite changes in the PLC. ► There is a fulcrum point for the modulation of the PLC around 20 Hz. ► The brain operates in a state of self-organized criticality (SOC) sensitive to dopaminergic modulation. - Abstract: Oscillatory activity can be widely recorded in the brain. It has been demonstrated to play an important role not only in the physiology of movement, perception and cognition, but also in the pathophysiology of a variety of diseases. In frequency domain, neurophysiological recordings show a power spectrum (PSD) following a log (PSD) ∝ log (f) −β , that reveals an intrinsic feature of many complex systems in nature: the presence of a scale-free dynamics characterized by a power-law component (PLC). Here we analyzed the influence of dopaminergic drugs over the PLC of the oscillatory activity recorded from different locations of the rat brain. Dopamine (DA) is a neurotransmitter that is required for a number of physiological functions like normal feeding, locomotion, posturing, grooming and reaction time. Alterations in the dopaminergic system cause vast effects in the dynamics of the brain activity, that may be crucial in the pathophysiology of neurological (like Parkinson’s disease) or psychiatric (like schizophrenia) diseases. Our results show that drugs with opposite effects over the dopaminergic system, induce opposite changes in the characteristics of the PLC: DA agonists/antagonists cause the PLC to swing around a fulcrum point in the range of 20 Hz. Changes in the harmonic component of the spectrum were also detected. However, differences between recordings are better explained by the modulation of the PLC

Aberrant Modulation of Brain Oscillatory Activity and Attentional Impairment in Attention-Deficit/Hyperactivity Disorder.

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Lenartowicz, Agatha; Mazaheri, Ali; Jensen, Ole; Loo, Sandra K

2018-01-01

Electroencephalography and magnetoencephalography are noninvasive neuroimaging techniques that have been used extensively to study various resting-state and cognitive processes in the brain. The purpose of this review is to highlight a number of recent studies that have investigated the alpha band (8-12 Hz) oscillatory activity present in magnetoencephalography and electroencephalography, to provide new insights into the maladaptive network activity underlying attentional impairments in attention-deficit/hyperactivity disorder (ADHD). Studies reviewed demonstrate that event-related decrease in alpha is attenuated during visual selective attention, primarily in ADHD inattentive type, and is often significantly associated with accuracy and reaction time during task performance. Furthermore, aberrant modulation of alpha activity has been reported across development and may have abnormal or atypical lateralization patterns in ADHD. Modulations in the alpha band thus represent a robust, relatively unexplored putative biomarker of attentional impairment and a strong prospect for future studies aimed at examining underlying neural mechanisms and treatment response among individuals with ADHD. Potential limitations of its use as a diagnostic biomarker and directions for future research are discussed. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Models of neural dynamics in brain information processing - the developments of 'the decade'

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Borisyuk, G N; Borisyuk, R M; Kazanovich, Yakov B; Ivanitskii, Genrikh R

2002-01-01

Neural network models are discussed that have been developed during the last decade with the purpose of reproducing spatio-temporal patterns of neural activity in different brain structures. The main goal of the modeling was to test hypotheses of synchronization, temporal and phase relations in brain information processing. The models being considered are those of temporal structure of spike sequences, of neural activity dynamics, and oscillatory models of attention and feature integration. (reviews of topical problems)

Oscillatory patterns in the light curves of five long-term monitored type 1 active galactic nuclei

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Kovačević, Andjelka B.; Pérez-Hernández, Ernesto; Popović, Luka Č.; Shapovalova, Alla I.; Kollatschny, Wolfram; Ilić, Dragana

2018-04-01

New combined data of five well-known type 1 active galactic nuclei (AGNs) are probed with a novel hybrid method in a search for oscillatory behaviour. Additional analysis of artificial light curves obtained from the coupled oscillatory models gives confirmation for detected periods that could have a physical background. We find periodic variations in the long-term light curves of 3C 390.3, NGC 4151 and NGC 5548, and E1821 + 643, with correlation coefficients larger than 0.6. We show that the oscillatory patterns of two binary black hole candidates, NGC 5548 and E1821 + 643, correspond to qualitatively different dynamical regimes of chaos and stability, respectively. We demonstrate that the absence of oscillatory patterns in Arp 102B could be the result of a weak coupling between oscillatory mechanisms. This is the first good evidence that 3C 390.3 and Arp 102B, categorized as double-peaked Balmer line objects, have qualitative different dynamics. Our analysis shows a novelty in the oscillatory dynamical patterns of the light curves of these type 1 AGNs.

Brain Oscillatory Correlates of Altered Executive Functioning in Positive and Negative Symptomatic Schizophrenia Patients and Healthy Controls.

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Berger, Barbara; Minarik, Tamas; Griesmayr, Birgit; Stelzig-Schoeler, Renate; Aichhorn, Wolfgang; Sauseng, Paul

2016-01-01

Working Memory and executive functioning deficits are core characteristics of patients suffering from schizophrenia. Electrophysiological research indicates that altered patterns of neural oscillatory mechanisms underpinning executive functioning are associated with the psychiatric disorder. Such brain oscillatory changes have been found in local amplitude differences at gamma and theta frequencies in task-specific cortical areas. Moreover, interregional interactions are also disrupted as signified by decreased phase coherence of fronto-posterior theta activity in schizophrenia patients. However, schizophrenia is not a one-dimensional psychiatric disorder but has various forms and expressions. A common distinction is between positive and negative symptomatology but most patients have both negative and positive symptoms to some extent. Here, we examined three groups-healthy controls, predominantly negative, and predominantly positive symptomatic schizophrenia patients-when performing a working memory task with increasing cognitive demand and increasing need for executive control. We analyzed brain oscillatory activity in the three groups separately and investigated how predominant symptomatology might explain differences in brain oscillatory patterns. Our results indicate that differences in task specific fronto-posterior network activity (i.e., executive control network) expressed by interregional phase synchronization are able to account for working memory dysfunctions between groups. Local changes in the theta and gamma frequency range also show differences between patients and healthy controls, and more importantly, between the two patient groups. We conclude that differences in oscillatory brain activation patterns related to executive processing can be an indicator for positive and negative symptomatology in schizophrenia. Furthermore, changes in cognitive and especially executive functioning in patients are expressed by alterations in a task-specific fronto

Role of synchronized oscillatory brain activity for human pain perception.

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Hauck, Michael; Lorenz, Jürgen; Engel, Andreas K

2008-01-01

The understanding of cortical pain processing in humans has significantly improved since the development of modern neuroimaging techniques. Non-invasive electrophysiological approaches such as electro- and magnetoencephalography have proven to be helpful tools for the real-time investigation of neuronal signals and synchronous communication between cortical areas. In particular, time-frequency decomposition of signals recorded with these techniques seems to be a promising approach because different pain-related oscillatory changes can be observed within different frequency bands, which are likely to be linked to specific sensory and motor functions. In this review we discuss the latest evidence on pain-induced time-frequency signals and propose that changes in oscillatory activity reflect an essential communication mechanism in the brain that is modulated during pain processing. The importance of synchronization processes for normal and pathological pain processing, such as chronic pain states, is discussed.

Working memory load related modulations of the oscillatory brain activity. N-back ERD/ERS study

International Nuclear Information System (INIS)

Nakao, Yoshiaki; Tamura, Toshiyo; Kodabashi, Atsushi; Fujimoto, Toshiro; Yarita, Masaru

2011-01-01

In recent cognitive neuroscience, a lot of studies of the human working memory were examined, and electroencephalography (EEG) measurements during n-back task were often used. However, they were almost studied by event related potentials (ERP) analysis. In the ERP study, time-locked components can be elicited, but non time-locked components such as the modulated brain oscillatory activity might be lost by an averaging procedure. To elucidate the contribution of the modulations of the brain oscillatory activity to the human working memory, we examined event related desynchronization (ERD)/event related synchronization (ERS) analysis on the source waveforms during n-back task. Source waveforms were calculated from a source model which was constructed with the sources seeded from fMRI meta-analysis of n-back task and additional sources in the orbitofrontal cortex and the visual cortex estimated with P100 and P360 components in the n-back ERP. Our results suggested the network which included the prefrontal cortex and the parietal lobe had a contribution to human working memory process, and it was mediated by theta oscillatory activity. (author)

Models of neural dynamics in brain information processing - the developments of 'the decade'

Energy Technology Data Exchange (ETDEWEB)

Borisyuk, G N; Borisyuk, R M; Kazanovich, Yakov B [Institute of Mathematical Problems of Biology, Russian Academy of Sciences, Pushchino, Moscow region (Russian Federation); Ivanitskii, Genrikh R [Institute for Theoretical and Experimental Biophysics, Russian Academy of Sciences, Pushchino, Moscow region (Russian Federation)

2002-10-31

Neural network models are discussed that have been developed during the last decade with the purpose of reproducing spatio-temporal patterns of neural activity in different brain structures. The main goal of the modeling was to test hypotheses of synchronization, temporal and phase relations in brain information processing. The models being considered are those of temporal structure of spike sequences, of neural activity dynamics, and oscillatory models of attention and feature integration. (reviews of topical problems)

Interactions between neural networks: a mechanism for tuning chaos and oscillations.

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Wang, Lipo

2007-06-01

We show that chaos and oscillations in a higher-order binary neural network can be tuned effectively using interactions between neural networks. Our results suggest that network interactions may be useful as a means of adjusting the level of dynamic activities in systems that employ chaos and oscillations for information processing, or as a means of suppressing oscillatory behaviors in systems that require stability.

Patterns of cortical oscillations organize neural activity into whole-brain functional networks evident in the fMRI BOLD signal

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Jennifer C Whitman

2013-03-01

Full Text Available Recent findings from electrophysiology and multimodal neuroimaging have elucidated the relationship between patterns of cortical oscillations evident in EEG / MEG and the functional brain networks evident in the BOLD signal. Much of the existing literature emphasized how high-frequency cortical oscillations are thought to coordinate neural activity locally, while low-frequency oscillations play a role in coordinating activity between more distant brain regions. However, the assignment of different frequencies to different spatial scales is an oversimplification. A more informative approach is to explore the arrangements by which these low- and high-frequency oscillations work in concert, coordinating neural activity into whole-brain functional networks. When relating such networks to the BOLD signal, we must consider how the patterns of cortical oscillations change at the same speed as cognitive states, which often last less than a second. Consequently, the slower BOLD signal may often reflect the summed neural activity of several transient network configurations. This temporal mismatch can be circumvented if we use spatial maps to assess correspondence between oscillatory networks and BOLD networks.

Neural electrical activity and neural network growth.

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Gafarov, F M

2018-05-01

The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Dynamic decomposition of spatiotemporal neural signals.

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Luca Ambrogioni

2017-05-01

Full Text Available Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to specific types of information processing. Here we present a data analysis framework that uses a linearized model of these dynamic states in order to decompose the measured neural signal into a series of components that capture both rhythmic and non-rhythmic neural activity. The method is based on stochastic differential equations and Gaussian process regression. Through computer simulations and analysis of magnetoencephalographic data, we demonstrate the efficacy of the method in identifying meaningful modulations of oscillatory signals corrupted by structured temporal and spatiotemporal noise. These results suggest that the method is particularly suitable for the analysis and interpretation of complex temporal and spatiotemporal neural signals.

Oscillatory activity in neocortical networks during tactile discrimination near the limit of spatial acuity.

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Adhikari, Bhim M; Sathian, K; Epstein, Charles M; Lamichhane, Bidhan; Dhamala, Mukesh

2014-05-01

Oscillatory interactions within functionally specialized but distributed brain regions are believed to be central to perceptual and cognitive functions. Here, using human scalp electroencephalography (EEG) recordings combined with source reconstruction techniques, we study how oscillatory activity functionally organizes different neocortical regions during a tactile discrimination task near the limit of spatial acuity. While undergoing EEG recordings, blindfolded participants felt a linear three-dot array presented electromechanically, under computer control, and reported whether the central dot was offset to the left or right. The average brain response differed significantly for trials with correct and incorrect perceptual responses in the timeframe approximately between 130 and 175ms. During trials with correct responses, source-level peak activity appeared in the left primary somatosensory cortex (SI) at around 45ms, in the right lateral occipital complex (LOC) at 130ms, in the right posterior intraparietal sulcus (pIPS) at 160ms, and finally in the left dorsolateral prefrontal cortex (dlPFC) at 175ms. Spectral interdependency analysis of activity in these nodes showed two distinct distributed networks, a dominantly feedforward network in the beta band (12-30Hz) that included all four nodes and a recurrent network in the gamma band (30-100Hz) that linked SI, pIPS and dlPFC. Measures of network activity in both bands were correlated with the accuracy of task performance. These findings suggest that beta and gamma band oscillatory networks coordinate activity between neocortical regions mediating sensory and cognitive processing to arrive at tactile perceptual decisions. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

The influence of low-grade glioma on resting state oscillatory brain activity: a magnetoencephalography study

NARCIS (Netherlands)

Bosma, I.; Stam, C. J.; Douw, L.; Bartolomei, F.; Heimans, J. J.; van Dijk, B. W.; Postma, T. J.; Klein, M.; Reijneveld, J. C.

2008-01-01

In the present MEG-study, power spectral analysis of oscillatory brain activity was used to compare resting state brain activity in both low-grade glioma (LGG) patients and healthy controls. We hypothesized that LGG patients show local as well as diffuse slowing of resting state brain activity

Dissociable influences of auditory object vs. spatial attention on visual system oscillatory activity.

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Jyrki Ahveninen

Full Text Available Given that both auditory and visual systems have anatomically separate object identification ("what" and spatial ("where" pathways, it is of interest whether attention-driven cross-sensory modulations occur separately within these feature domains. Here, we investigated how auditory "what" vs. "where" attention tasks modulate activity in visual pathways using cortically constrained source estimates of magnetoencephalograpic (MEG oscillatory activity. In the absence of visual stimuli or tasks, subjects were presented with a sequence of auditory-stimulus pairs and instructed to selectively attend to phonetic ("what" vs. spatial ("where" aspects of these sounds, or to listen passively. To investigate sustained modulatory effects, oscillatory power was estimated from time periods between sound-pair presentations. In comparison to attention to sound locations, phonetic auditory attention was associated with stronger alpha (7-13 Hz power in several visual areas (primary visual cortex; lingual, fusiform, and inferior temporal gyri, lateral occipital cortex, as well as in higher-order visual/multisensory areas including lateral/medial parietal and retrosplenial cortices. Region-of-interest (ROI analyses of dynamic changes, from which the sustained effects had been removed, suggested further power increases during Attend Phoneme vs. Location centered at the alpha range 400-600 ms after the onset of second sound of each stimulus pair. These results suggest distinct modulations of visual system oscillatory activity during auditory attention to sound object identity ("what" vs. sound location ("where". The alpha modulations could be interpreted to reflect enhanced crossmodal inhibition of feature-specific visual pathways and adjacent audiovisual association areas during "what" vs. "where" auditory attention.

Understanding Epileptiform After-Discharges as Rhythmic Oscillatory Transients.

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Baier, Gerold; Taylor, Peter N; Wang, Yujiang

2017-01-01

Electro-cortical activity in patients with epilepsy may show abnormal rhythmic transients in response to stimulation. Even when using the same stimulation parameters in the same patient, wide variability in the duration of transient response has been reported. These transients have long been considered important for the mapping of the excitability levels in the epileptic brain but their dynamic mechanism is still not well understood. To investigate the occurrence of abnormal transients dynamically, we use a thalamo-cortical neural population model of epileptic spike-wave activity and study the interaction between slow and fast subsystems. In a reduced version of the thalamo-cortical model, slow wave oscillations arise from a fold of cycles (FoC) bifurcation. This marks the onset of a region of bistability between a high amplitude oscillatory rhythm and the background state. In vicinity of the bistability in parameter space, the model has excitable dynamics, showing prolonged rhythmic transients in response to suprathreshold pulse stimulation. We analyse the state space geometry of the bistable and excitable states, and find that the rhythmic transient arises when the impending FoC bifurcation deforms the state space and creates an area of locally reduced attraction to the fixed point. This area essentially allows trajectories to dwell there before escaping to the stable steady state, thus creating rhythmic transients. In the full thalamo-cortical model, we find a similar FoC bifurcation structure. Based on the analysis, we propose an explanation of why stimulation induced epileptiform activity may vary between trials, and predict how the variability could be related to ongoing oscillatory background activity. We compare our dynamic mechanism with other mechanisms (such as a slow parameter change) to generate excitable transients, and we discuss the proposed excitability mechanism in the context of stimulation responses in the epileptic cortex.

Correlation of Infraslow Oscillatory Processes in the Body as an Integral Characteristic of Human Adaptation

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Doletskiy Aleksey Nikolaevich

2014-12-01

Full Text Available The aim of our study was to assess synchrony infraslow rhythm (frequency of less than 1 Hz when registering the electroencephalogram (EEG, electrocardiogram (ECG and reoentsefalogrammy (REG depending from the psychoemotional state. The severity of the infraslow oscillatory processes in the central nervous system, heart and circulatory system during meditation, biofeedback with heart rate control and rhythmic breathing at a given frequency was performed. The infraslow activity depending on the use of non-pharmacological methods of relaxation was evaluated. The method of determination of the dominant frequencies of the cardiovascular, neural infraslow activity (from 0.07 to 1 Hz was used. We compared dominant frequencies of the infraslow activity in difference relaxation states. The specific frequencies in different types of relaxation in the cardiovascular and neural systems were found. The severity of the infraslow activity correlates with the functional state of the nervous and cardiovascular systems. We found the syncronization frequency of 0.2 Hz, which is different from the frequency of cardiorespiratory synchronization of 0.1 Hz, commonly found in literature.

Slowing of oscillatory brain activity is a stable characteristic of Parkinson's disease without dementia

NARCIS (Netherlands)

Stoffers, D.; Bosboom, JL; Deijen, J.B.; Wolters, E.C.M.J.; Berendse, H.W.; Stam, L.

2007-01-01

Extensive changes in resting-state oscillatory brain activity have recently been demonstrated using magnetoencephalography (MEG) in moderately advanced, non-demented Parkinson's disease patients relative to age-matched controls. The aim of the present study was to determine the onset and evolution

The influence of low-grade glioma on resting state oscillatory brain activity: a magnetoencephalography study

NARCIS (Netherlands)

Bosma, I.; Stam, C.; Douw, L.; Bartolomei, F.; Heimans, J.; Dijk, van B.; Postma, T.; Klein, M.; Reijneveld, J.

2008-01-01

Purpose: In the present MEG-study, power spectral analysis of oscillatory brain activity was used to compare resting state brain activity in both low-grade glioma (LGG) patients and healthy controls. We hypothesized that LGG patients show local as well as diffuse slowing of resting state brain

A nonlinear oscillatory problem

International Nuclear Information System (INIS)

Zhou Qingqing.

1991-10-01

We have studied the nonlinear oscillatory problem of orthotropic cylindrical shell, we have analyzed the character of the oscillatory system. The stable condition of the oscillatory system has been given. (author). 6 refs

On the contribution of motor planning to the retroactive cuing benefit in working memory: Evidence by mu and beta oscillatory activity in the EEG.

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Schneider, Daniel; Barth, Anna; Wascher, Edmund

2017-11-15

Attention can be allocated toward mental representations in working memory also after the initial encoding of information has been completed. It was shown that focusing on only one item within working memory transfers this representation into a protected state, reducing its susceptibility to interference by incoming signals. The present study investigated the nature of this retroactive cue (retro-cue) benefit by means of oscillatory activity in the EEG. In a working memory task with a retro-cue indicating one, two or three memory representations as relevant and a block-wise distractor display presented after the retro-cue, participants had to remember the orientation of a colored bar. On behavioral level, we found that the interfering effect of the distractor display on memory performance could be prevented when a retro-cue reduced the number of attended representations in working memory. However, only the one-item retro-cue led to an overall increase in task performance compared to a condition without a retro-cue. The neural basis of this special representational status was investigated by means of oscillatory parameters in the EEG and a clustering approach on level of the independent components (ICs) in the signal. The retroactive reduction of attended working memory representations was reflected in a suppression of alpha power over right parietal and parieto-occipital sites. In addition, we found that an IC cluster representing oscillatory activity in the mu/beta range (10-12 Hz and 20-24 Hz) with a source in sensorimotor cortex revealed a power suppression already prior to the memory probe following the one-item retro-cue. This suggests that the retro-cue benefit results in large parts from the possibility to focus attention on one particular item in working memory and initiate motor planning processes already ahead of the probe stimulus indicating the respective response. Copyright © 2017 Elsevier Inc. All rights reserved.

One central oscillatory drive is compatible with experimental motor unit behaviour in essential and Parkinsonian tremor

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Dideriksen, Jakob L.; Gallego, Juan A.; Holobar, Ales; Rocon, Eduardo; Pons, Jose L.; Farina, Dario

2015-08-01

Objective. Pathological tremors are symptomatic to several neurological disorders that are difficult to differentiate and the way by which central oscillatory networks entrain tremorogenic contractions is unknown. We considered the alternative hypotheses that tremor arises from one oscillator (at the tremor frequency) or, as suggested by recent findings from the superimposition of two separate inputs (at the tremor frequency and twice that frequency). Approach. Assuming one central oscillatory network we estimated analytically the relative amplitude of the harmonics of the tremor frequency in the motor neuron output for different temporal behaviors of the oscillator. Next, we analyzed the bias in the relative harmonics amplitude introduced by superimposing oscillations at twice the tremor frequency. These findings were validated using experimental measurements of wrist angular velocity and surface electromyography (EMG) from 22 patients (11 essential tremor, 11 Parkinson’s disease). The ensemble motor unit action potential trains identified from the EMG represented the neural drive to the muscles. Main results. The analytical results showed that the relative power of the tremor harmonics in the analytical models of the neural drive was determined by the variability and duration of the tremor bursts and the presence of the second oscillator biased this power towards higher values. The experimental findings accurately matched the analytical model assuming one oscillator, indicating a negligible functional role of secondary oscillatory inputs. Furthermore, a significant difference in the relative power of harmonics in the neural drive was found across the patient groups, suggesting a diagnostic value of this measure (classification accuracy: 86%). This diagnostic power decreased substantially when estimated from limb acceleration or the EMG. Signficance. The results indicate that the neural drive in pathological tremor is compatible with one central network

Task-dependent changes in cross-level coupling between single neurons and oscillatory activity in multiscale networks.

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Ryan T Canolty

Full Text Available Understanding the principles governing the dynamic coordination of functional brain networks remains an important unmet goal within neuroscience. How do distributed ensembles of neurons transiently coordinate their activity across a variety of spatial and temporal scales? While a complete mechanistic account of this process remains elusive, evidence suggests that neuronal oscillations may play a key role in this process, with different rhythms influencing both local computation and long-range communication. To investigate this question, we recorded multiple single unit and local field potential (LFP activity from microelectrode arrays implanted bilaterally in macaque motor areas. Monkeys performed a delayed center-out reach task either manually using their natural arm (Manual Control, MC or under direct neural control through a brain-machine interface (Brain Control, BC. In accord with prior work, we found that the spiking activity of individual neurons is coupled to multiple aspects of the ongoing motor beta rhythm (10-45 Hz during both MC and BC, with neurons exhibiting a diversity of coupling preferences. However, here we show that for identified single neurons, this beta-to-rate mapping can change in a reversible and task-dependent way. For example, as beta power increases, a given neuron may increase spiking during MC but decrease spiking during BC, or exhibit a reversible shift in the preferred phase of firing. The within-task stability of coupling, combined with the reversible cross-task changes in coupling, suggest that task-dependent changes in the beta-to-rate mapping play a role in the transient functional reorganization of neural ensembles. We characterize the range of task-dependent changes in the mapping from beta amplitude, phase, and inter-hemispheric phase differences to the spike rates of an ensemble of simultaneously-recorded neurons, and discuss the potential implications that dynamic remapping from oscillatory activity to

Oscillatory brain activity related to control mechanisms during laboratory-induced reactive aggression

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Ulrike M Krämer

2009-11-01

Full Text Available Aggressive behavior is a common reaction in humans after an interpersonal provocation, but little is known about the underlying brain mechanisms. The present study analyzed oscillatory brain activity while participants were involved in an aggressive interaction to examine the neural processes subserving the associated decision and evaluation processes. Participants were selected from a larger sample because of their high scores in trait aggressiveness. We used a competitive reaction time task that induces aggressive behavior through provocation. Each trial is separated in a decision phase, during which the punishment for the opponent is set, and an outcome phase, during which the actual punishment is applied or received. We observed provocation-related differences during the decision phase in the theta band which differed depending on participants’ aggressive behavior: High provocation was associated with an increased frontal theta response in participants refraining from retaliation, but with reduced theta power in those who got back to the opponent. Moreover, more aggressive decisions after being punished were associated with a decrease of frontal theta power. Non-aggressive and aggressive participants differed also in their outcome-related response: Being punished led to an increased frontal theta power compared to win trials in the latter only, pointing to differences in evaluation processes associated with their different behavioral reactions. The data thus support previous evidence for a role of prefrontal areas in the control of reactive aggression and extend behavioral studies on associations between aggression or violence and impaired prefrontal functions.

Irreducible Representations of Oscillatory and Swirling Flows in Active Soft Matter

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Ghose, Somdeb; Adhikari, R.

2014-03-01

Recent experiments imaging fluid flow around swimming microorganisms have revealed complex time-dependent velocity fields that differ qualitatively from the stresslet flow commonly employed in theoretical descriptions of active matter. Here we obtain the most general flow around a finite sized active particle by expanding the surface stress in irreducible Cartesian tensors. This expansion, whose first term is the stresslet, must include, respectively, third-rank polar and axial tensors to minimally capture crucial features of the active oscillatory flow around translating Chlamydomonas and the active swirling flow around rotating Volvox. The representation provides explicit expressions for the irreducible symmetric, antisymmetric, and isotropic parts of the continuum active stress. Antisymmetric active stresses do not conserve orbital angular momentum and our work thus shows that spin angular momentum is necessary to restore angular momentum conservation in continuum hydrodynamic descriptions of active soft matter.

Emergence of Oscillatory Dynamics

DEFF Research Database (Denmark)

Laugesen, Jakob Lund; Mosekilde, Erik

2012-01-01

Besides their systems nature, as described in the preceding chapters, the single most characteristic feature of a living organism is the self-sustained activity it displays in the form of a wide variety of different oscillatory processes [25, 9, 22, 23]. The respiratory cycle and the beating...

Distinction between perceptual and attentional processing in working memory tasks: a study of phase-locked and induced oscillatory brain dynamics.

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Deiber, Marie-Pierre; Missonnier, Pascal; Bertrand, Olivier; Gold, Gabriel; Fazio-Costa, Lara; Ibañez, Vicente; Giannakopoulos, Panteleimon

2007-01-01

Working memory involves the short-term storage and manipulation of information necessary for cognitive performance, including comprehension, learning, reasoning and planning. Although electroencephalogram (EEG) rhythms are modulated during working memory, the temporal relationship of EEG oscillations with the eliciting event has not been well studied. In particular, the dynamics of the neural network supporting memory processes may be best captured in induced oscillations, characterized by a loose temporal link with the stimulus. In order to differentiate induced from evoked functional processes, the present study proposes a time-frequency analysis of the 3 to 30 Hz EEG oscillatory activity in a verbal n-back working memory paradigm. Control tasks were designed to identify oscillatory activity related to stimulus presentation (passive task) and focused attention to the stimulus (detection task). Evoked theta activity (4-8 Hz) phase-locked to the visual stimulus was evidenced in the parieto-occipital region for all tasks. In parallel, induced theta activity was recorded in the frontal region for detection and n-back memory tasks, but not for the passive task, suggesting its dependency on focused attention to the stimulus. Sustained induced oscillatory activity was identified in relation to working memory in the theta and beta (15-25 Hz) frequency bands, larger for the highest memory load. Its late occurrence limited to nonmatched items suggests that it could be related to item retention and active maintenance for further task requirements. Induced theta and beta activities displayed respectively a frontal and parietal topographical distribution, providing further functional information on the fronto-posterior network supporting working memory.

Beta and gamma oscillatory activities associated with olfactory memory tasks: different rhythms for different functional networks?

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Martin, Claire; Ravel, Nadine

2014-01-01

Olfactory processing in behaving animals, even at early stages, is inextricable from top down influences associated with odor perception. The anatomy of the olfactory network (olfactory bulb, piriform, and entorhinal cortices) and its unique direct access to the limbic system makes it particularly attractive to study how sensory processing could be modulated by learning and memory. Moreover, olfactory structures have been early reported to exhibit oscillatory population activities easy to capture through local field potential recordings. An attractive hypothesis is that neuronal oscillations would serve to "bind" distant structures to reach a unified and coherent perception. In relation to this hypothesis, we will assess the functional relevance of different types of oscillatory activity observed in the olfactory system of behaving animals. This review will focus primarily on two types of oscillatory activities: beta (15-40 Hz) and gamma (60-100 Hz). While gamma oscillations are dominant in the olfactory system in the absence of odorant, both beta and gamma rhythms have been reported to be modulated depending on the nature of the olfactory task. Studies from the authors of the present review and other groups brought evidence for a link between these oscillations and behavioral changes induced by olfactory learning. However, differences in studies led to divergent interpretations concerning the respective role of these oscillations in olfactory processing. Based on a critical reexamination of those data, we propose hypotheses on the functional involvement of beta and gamma oscillations for odor perception and memory.

Beta and gamma oscillatory activities associated with olfactory memory tasks: Different rhythms for different functional networks?

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Claire eMartin

2014-06-01

Full Text Available Olfactory processing in behaving animals, even at early stages, is inextricable from top down influences associated with odor perception. The anatomy of the olfactory network (olfactory bulb, piriform and entorhinal cortices and its unique direct access to the limbic system makes it particularly attractive to study how sensory processing could be modulated by learning and memory. Moreover, olfactory structures have been early reported to exhibit oscillatory population activities easy to capture through local field potential recordings. An attractive hypothesis is that neuronal oscillations would serve to ‘bind’ distant structures to reach a unified and coherent perception. In relation to this hypothesis, we will assess the functional relevance of different types of oscillatory activity observed in the olfactory system of behaving animals. This review will focus primarily on two types of oscillatory activities: beta (15-40 Hz and gamma (60-100 Hz. While gamma oscillations are dominant in the olfactory system in the absence of odorant, both beta and gamma rhythms have been reported to be modulated depending on the nature of the olfactory task. Studies from the authors of the present review and other groups brought evidence for a link between these oscillations and behavioral changes induced by olfactory learning. However, differences in studies led to divergent interpretations concerning the respective role of these oscillations in olfactory processing. Based on a critical reexamination of those data, we propose hypotheses on the functional involvement of beta and gamma oscillations for odor perception and memory.

Frequency Preference Response to Oscillatory Inputs in Two-dimensional Neural Models: A Geometric Approach to Subthreshold Amplitude and Phase Resonance.

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Rotstein, Horacio G

2014-01-01

We investigate the dynamic mechanisms of generation of subthreshold and phase resonance in two-dimensional linear and linearized biophysical (conductance-based) models, and we extend our analysis to account for the effect of simple, but not necessarily weak, types of nonlinearities. Subthreshold resonance refers to the ability of neurons to exhibit a peak in their voltage amplitude response to oscillatory input currents at a preferred non-zero (resonant) frequency. Phase-resonance refers to the ability of neurons to exhibit a zero-phase (or zero-phase-shift) response to oscillatory input currents at a non-zero (phase-resonant) frequency. We adapt the classical phase-plane analysis approach to account for the dynamic effects of oscillatory inputs and develop a tool, the envelope-plane diagrams, that captures the role that conductances and time scales play in amplifying the voltage response at the resonant frequency band as compared to smaller and larger frequencies. We use envelope-plane diagrams in our analysis. We explain why the resonance phenomena do not necessarily arise from the presence of imaginary eigenvalues at rest, but rather they emerge from the interplay of the intrinsic and input time scales. We further explain why an increase in the time-scale separation causes an amplification of the voltage response in addition to shifting the resonant and phase-resonant frequencies. This is of fundamental importance for neural models since neurons typically exhibit a strong separation of time scales. We extend this approach to explain the effects of nonlinearities on both resonance and phase-resonance. We demonstrate that nonlinearities in the voltage equation cause amplifications of the voltage response and shifts in the resonant and phase-resonant frequencies that are not predicted by the corresponding linearized model. The differences between the nonlinear response and the linear prediction increase with increasing levels of the time scale separation between

Attention training improves aberrant neural dynamics during working memory processing in veterans with PTSD.

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McDermott, Timothy J; Badura-Brack, Amy S; Becker, Katherine M; Ryan, Tara J; Bar-Haim, Yair; Pine, Daniel S; Khanna, Maya M; Heinrichs-Graham, Elizabeth; Wilson, Tony W

2016-12-01

Posttraumatic stress disorder (PTSD) is associated with executive functioning deficits, including disruptions in working memory (WM). Recent studies suggest that attention training reduces PTSD symptomatology, but the underlying neural mechanisms are unknown. We used high-density magnetoencephalography (MEG) to evaluate whether attention training modulates brain regions serving WM processing in PTSD. Fourteen veterans with PTSD completed a WM task during a 306-sensor MEG recording before and after 8 sessions of attention training treatment. A matched comparison sample of 12 combat-exposed veterans without PTSD completed the same WM task during a single MEG session. To identify the spatiotemporal dynamics, each group's data were transformed into the time-frequency domain, and significant oscillatory brain responses were imaged using a beamforming approach. All participants exhibited activity in left hemispheric language areas consistent with a verbal WM task. Additionally, veterans with PTSD and combat-exposed healthy controls each exhibited oscillatory responses in right hemispheric homologue regions (e.g., right Broca's area); however, these responses were in opposite directions. Group differences in oscillatory activity emerged in the theta band (4-8 Hz) during encoding and in the alpha band (9-12 Hz) during maintenance and were significant in right prefrontal and right supramarginal and inferior parietal regions. Importantly, following attention training, these significant group differences were reduced or eliminated. This study provides initial evidence that attention training improves aberrant neural activity in brain networks serving WM processing.

Characteristic effects of stochastic oscillatory forcing on neural firing: analytical theory and comparison to paddlefish electroreceptor data.

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Bauermeister, Christoph; Schwalger, Tilo; Russell, David F; Neiman, Alexander B; Lindner, Benjamin

2013-01-01

Stochastic signals with pronounced oscillatory components are frequently encountered in neural systems. Input currents to a neuron in the form of stochastic oscillations could be of exogenous origin, e.g. sensory input or synaptic input from a network rhythm. They shape spike firing statistics in a characteristic way, which we explore theoretically in this report. We consider a perfect integrate-and-fire neuron that is stimulated by a constant base current (to drive regular spontaneous firing), along with Gaussian narrow-band noise (a simple example of stochastic oscillations), and a broadband noise. We derive expressions for the nth-order interval distribution, its variance, and the serial correlation coefficients of the interspike intervals (ISIs) and confirm these analytical results by computer simulations. The theory is then applied to experimental data from electroreceptors of paddlefish, which have two distinct types of internal noisy oscillators, one forcing the other. The theory provides an analytical description of their afferent spiking statistics during spontaneous firing, and replicates a pronounced dependence of ISI serial correlation coefficients on the relative frequency of the driving oscillations, and furthermore allows extraction of certain parameters of the intrinsic oscillators embedded in these electroreceptors.

Spatially Nonlinear Interdependence of Alpha-Oscillatory Neural Networks under Chan Meditation

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Pei-Chen Lo

2013-01-01

Full Text Available This paper reports the results of our investigation of the effects of Chan meditation on brain electrophysiological behaviors from the viewpoint of spatially nonlinear interdependence among regional neural networks. Particular emphasis is laid on the alpha-dominated EEG (electroencephalograph. Continuous-time wavelet transform was adopted to detect the epochs containing substantial alpha activities. Nonlinear interdependence quantified by similarity index S(X∣Y, the influence of source signal Y on sink signal X, was applied to the nonlinear dynamical model in phase space reconstructed from multichannel EEG. Experimental group involved ten experienced Chan-Meditation practitioners, while control group included ten healthy subjects within the same age range, yet, without any meditation experience. Nonlinear interdependence among various cortical regions was explored for five local neural-network regions, frontal, posterior, right-temporal, left-temporal, and central regions. In the experimental group, the inter-regional interaction was evaluated for the brain dynamics under three different stages, at rest (stage R, pre-meditation background recording, in Chan meditation (stage M, and the unique Chakra-focusing practice (stage C. Experimental group exhibits stronger interactions among various local neural networks at stages M and C compared with those at stage R. The intergroup comparison demonstrates that Chan-meditation brain possesses better cortical inter-regional interactions than the resting brain of control group.

Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

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Takiyama, Ken

2017-12-01

How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.

Imaging of neural oscillations with embedded inferential and group prevalence statistics

Science.gov (United States)

2018-01-01

Magnetoencephalography and electroencephalography (MEG, EEG) are essential techniques for studying distributed signal dynamics in the human brain. In particular, the functional role of neural oscillations remains to be clarified. For that reason, imaging methods need to identify distinct brain regions that concurrently generate oscillatory activity, with adequate separation in space and time. Yet, spatial smearing and inhomogeneous signal-to-noise are challenging factors to source reconstruction from external sensor data. The detection of weak sources in the presence of stronger regional activity nearby is a typical complication of MEG/EEG source imaging. We propose a novel, hypothesis-driven source reconstruction approach to address these methodological challenges. The imaging with embedded statistics (iES) method is a subspace scanning technique that constrains the mapping problem to the actual experimental design. A major benefit is that, regardless of signal strength, the contributions from all oscillatory sources, which activity is consistent with the tested hypothesis, are equalized in the statistical maps produced. We present extensive evaluations of iES on group MEG data, for mapping 1) induced oscillations using experimental contrasts, 2) ongoing narrow-band oscillations in the resting-state, 3) co-modulation of brain-wide oscillatory power with a seed region, and 4) co-modulation of oscillatory power with peripheral signals (pupil dilation). Along the way, we demonstrate several advantages of iES over standard source imaging approaches. These include the detection of oscillatory coupling without rejection of zero-phase coupling, and detection of ongoing oscillations in deeper brain regions, where signal-to-noise conditions are unfavorable. We also show that iES provides a separate evaluation of oscillatory synchronization and desynchronization in experimental contrasts, which has important statistical advantages. The flexibility of iES allows it to be

Role of slow oscillatory activity and slow wave sleep in consolidation of episodic-like memory in rats.

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Oyanedel, Carlos N; Binder, Sonja; Kelemen, Eduard; Petersen, Kimberley; Born, Jan; Inostroza, Marion

2014-12-15

Our previous experiments showed that sleep in rats enhances consolidation of hippocampus dependent episodic-like memory, i.e. the ability to remember an event bound into specific spatio-temporal context. Here we tested the hypothesis that this enhancing effect of sleep is linked to the occurrence of slow oscillatory and spindle activity during slow wave sleep (SWS). Rats were tested on an episodic-like memory task and on three additional tasks covering separately the where (object place recognition), when (temporal memory), and what (novel object recognition) components of episodic memory. In each task, the sample phase (encoding) was followed by an 80-min retention interval that covered either a period of regular morning sleep or sleep deprivation. Memory during retrieval was tested using preferential exploration of novelty vs. familiarity. Consistent with previous findings, the rats which had slept during the retention interval showed significantly stronger episodic-like memory and spatial memory, and a trend of improved temporal memory (although not significant). Object recognition memory was similarly retained across sleep and sleep deprivation retention intervals. Recall of episodic-like memory was associated with increased slow oscillatory activity (0.85-2.0Hz) during SWS in the retention interval. Spatial memory was associated with increased proportions of SWS. Against our hypothesis, a relationship between spindle activity and episodic-like memory performance was not detected, but spindle activity was associated with object recognition memory. The results provide support for the role of SWS and slow oscillatory activity in consolidating hippocampus-dependent memory, the role of spindles in this process needs to be further examined. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Rhythmic neural activity indicates the contribution of attention and memory to the processing of occluded movements in 10-month-old infants.

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Bache, Cathleen; Kopp, Franziska; Springer, Anne; Stadler, Waltraud; Lindenberger, Ulman; Werkle-Bergner, Markus

2015-11-01

Infants possess the remarkable capacity to perceive occluded movements as ongoing and coherent. Little is known about the neural mechanisms that enable internal representation of conspecifics' and inanimate objects' movements during visual occlusion. In this study, 10-month-old infants watched briefly occluded human and object movements. Prior to occlusion, continuous and distorted versions of the movement were shown. EEG recordings were used to assess neural activity assumed to relate to processes of attention (occipital alpha), memory (frontal theta), and sensorimotor simulation (central alpha) before, during, and after occlusion. Oscillatory activity was analyzed using an individualized data approach taking idiosyncrasies into account. Results for occipital alpha were consistent with infants' preference for attending to social stimuli. Furthermore, frontal theta activity was more pronounced when tracking distorted as opposed to continuous movement, and when maintaining object as opposed to human movement. Central alpha did not discriminate between experimental conditions. In sum, we conclude that observing occluded movements recruits processes of attention and memory which are modulated by stimulus and movement properties. Copyright © 2015 Elsevier B.V. All rights reserved.

Two types of mental fatigue affect spontaneous oscillatory brain activities in different ways

OpenAIRE

Shigihara, Yoshihito; Tanaka, Masaaki; Ishii, Akira; Kanai, Etsuko; Funakura, Masami; Watanabe, Yasuyoshi

2013-01-01

Abstract Background Fatigue has a multi-factorial nature. We examined the effects of two types of mental fatigue on spontaneous oscillatory brain activity using magnetoencephalography (MEG). Methods Participants were randomly assigned to two groups in a single-blinded, crossover fashion to perform two types of mental fatigue-inducing experiments. Each experiment consisted of a 30-min fatigue-inducing 0- or 2-back test session and two evaluation sessions performed just before and after the fat...

The Functional Role of Neural Oscillations in Non-Verbal Emotional Communication.

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Symons, Ashley E; El-Deredy, Wael; Schwartze, Michael; Kotz, Sonja A

2016-01-01

Effective interpersonal communication depends on the ability to perceive and interpret nonverbal emotional expressions from multiple sensory modalities. Current theoretical models propose that visual and auditory emotion perception involves a network of brain regions including the primary sensory cortices, the superior temporal sulcus (STS), and orbitofrontal cortex (OFC). However, relatively little is known about how the dynamic interplay between these regions gives rise to the perception of emotions. In recent years, there has been increasing recognition of the importance of neural oscillations in mediating neural communication within and between functional neural networks. Here we review studies investigating changes in oscillatory activity during the perception of visual, auditory, and audiovisual emotional expressions, and aim to characterize the functional role of neural oscillations in nonverbal emotion perception. Findings from the reviewed literature suggest that theta band oscillations most consistently differentiate between emotional and neutral expressions. While early theta synchronization appears to reflect the initial encoding of emotionally salient sensory information, later fronto-central theta synchronization may reflect the further integration of sensory information with internal representations. Additionally, gamma synchronization reflects facilitated sensory binding of emotional expressions within regions such as the OFC, STS, and, potentially, the amygdala. However, the evidence is more ambiguous when it comes to the role of oscillations within the alpha and beta frequencies, which vary as a function of modality (or modalities), presence or absence of predictive information, and attentional or task demands. Thus, the synchronization of neural oscillations within specific frequency bands mediates the rapid detection, integration, and evaluation of emotional expressions. Moreover, the functional coupling of oscillatory activity across multiples

Functional localization and effective connectivity of cortical theta and alpha oscillatory activity during an attention task

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Yuichi Kitaura

Full Text Available Objectives: The aim of this paper is to investigate cortical electric neuronal activity as an indicator of brain function, in a mental arithmetic task that requires sustained attention, as compared to the resting state condition. The two questions of interest are the cortical localization of different oscillatory activities, and the directional effective flow of oscillatory activity between regions of interest, in the task condition compared to resting state. In particular, theta and alpha activity are of interest here, due to their important role in attention processing. Methods: We adapted mental arithmetic as an attention ask in this study. Eyes closed 61-channel EEG was recorded in 14 participants during resting and in a mental arithmetic task (“serial sevens subtraction”. Functional localization and connectivity analyses were based on cortical signals of electric neuronal activity estimated with sLORETA (standardized low resolution electromagnetic tomography. Functional localization was based on the comparison of the cortical distributions of the generators of oscillatory activity between task and resting conditions. Assessment of effective connectivity was based on the iCoh (isolated effective coherence method, which provides an appropriate frequency decomposition of the directional flow of oscillatory activity between brain regions. Nine regions of interest comprising nodes from the dorsal and ventral attention networks were selected for the connectivity analysis. Results: Cortical spectral density distribution comparing task minus rest showed significant activity increase in medial prefrontal areas and decreased activity in left parietal lobe for the theta band, and decreased activity in parietal-occipital regions for the alpha1 band. At a global level, connections among right hemispheric nodes were predominantly decreased during the task condition, while connections among left hemispheric nodes were predominantly increased. At more

Decomposing neural synchrony: toward an explanation for near-zero phase-lag in cortical oscillatory networks.

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Rajasimhan Rajagovindan

Full Text Available BACKGROUND: Synchronized oscillation in cortical networks has been suggested as a mechanism for diverse functions ranging from perceptual binding to memory formation to sensorimotor integration. Concomitant with synchronization is the occurrence of near-zero phase-lag often observed between network components. Recent theories have considered the importance of this phenomenon in establishing an effective communication framework among neuronal ensembles. METHODOLOGY/PRINCIPAL FINDINGS: Two factors, among possibly others, can be hypothesized to contribute to the near-zero phase-lag relationship: (1 positively correlated common input with no significant relative time delay and (2 bidirectional interaction. Thus far, no empirical test of these hypotheses has been possible for lack of means to tease apart the specific causes underlying the observed synchrony. In this work simulation examples were first used to illustrate the ideas. A quantitative method that decomposes the statistical interdependence between two cortical areas into a feed-forward, a feed-back and a common-input component was then introduced and applied to test the hypotheses on multichannel local field potential recordings from two behaving monkeys. CONCLUSION/SIGNIFICANCE: The near-zero phase-lag phenomenon is important in the study of large-scale oscillatory networks. A rigorous mathematical theorem is used for the first time to empirically examine the factors that contribute to this phenomenon. Given the critical role that oscillatory activity is likely to play in the regulation of biological processes at all levels, the significance of the proposed method may extend beyond systems neuroscience, the level at which the present analysis is conceived and performed.

EEG Mu (µ) rhythm spectra and oscillatory activity differentiate stuttering from non-stuttering adults.

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Saltuklaroglu, Tim; Harkrider, Ashley W; Thornton, David; Jenson, David; Kittilstved, Tiffani

2017-06-01

Stuttering is linked to sensorimotor deficits related to internal modeling mechanisms. This study compared spectral power and oscillatory activity of EEG mu (μ) rhythms between persons who stutter (PWS) and controls in listening and auditory discrimination tasks. EEG data were analyzed from passive listening in noise and accurate (same/different) discrimination of tones or syllables in quiet and noisy backgrounds. Independent component analysis identified left and/or right μ rhythms with characteristic alpha (α) and beta (β) peaks localized to premotor/motor regions in 23 of 27 people who stutter (PWS) and 24 of 27 controls. PWS produced μ spectra with reduced β amplitudes across conditions, suggesting reduced forward modeling capacity. Group time-frequency differences were associated with noisy conditions only. PWS showed increased μ-β desynchronization when listening to noise and early in discrimination events, suggesting evidence of heightened motor activity that might be related to forward modeling deficits. PWS also showed reduced μ-α synchronization in discrimination conditions, indicating reduced sensory gating. Together these findings indicate spectral and oscillatory analyses of μ rhythms are sensitive to stuttering. More specifically, they can reveal stuttering-related sensorimotor processing differences in listening and auditory discrimination that also may be influenced by basal ganglia deficits. Copyright © 2017 Elsevier Inc. All rights reserved.

1/f neural noise and electrophysiological indices of contextual prediction in aging.

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Dave, S; Brothers, T A; Swaab, T Y

2018-07-15

Prediction of upcoming words during reading has been suggested to enhance the efficiency of discourse processing. Emerging models have postulated that predictive mechanisms require synchronous firing of neural networks, but to date, this relationship has been investigated primarily through oscillatory activity in narrow frequency bands. A recently-developed measure proposed to reflect broadband neural activity - and thereby synchronous neuronal firing - is 1/f neural noise extracted from EEG spectral power. Previous research has indicated that this measure of 1/f neural noise changes across the lifespan, and these neural changes predict age-related behavioral impairments in visual working memory. Using a cross-sectional sample of young and older adults, we examined age-related changes in 1/f neural noise and whether this measure predicted ERP correlates of successful lexical prediction during discourse comprehension. 1/f neural noise across two different language tasks revealed high within-subject correlations, indicating that this measure can provide a reliable index of individualized patterns of neural activation. In addition to age, 1/f noise was a significant predictor of N400 effects of successful lexical prediction; however, noise did not mediate age-related declines in other ERP effects. We discuss broader implications of these findings for theories of predictive processing, as well as potential applications of 1/f noise across research populations. Copyright © 2018 Elsevier B.V. All rights reserved.

Relationship between oscillatory neuronal activity during reward processing and trait impulsivity and sensation seeking.

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Gregor Leicht

Full Text Available BACKGROUND: The processing of reward and punishment stimuli in humans appears to involve brain oscillatory activity of several frequencies, probably each with a distinct function. The exact nature of associations of these electrophysiological measures with impulsive or risk-seeking personality traits is not completely clear. Thus, the aim of the present study was to investigate event-related oscillatory activity during reward processing across a wide spectrum of frequencies, and its associations with impulsivity and sensation seeking in healthy subjects. METHODS: During recording of a 32-channel EEG 22 healthy volunteers were characterized with the Barratt Impulsiveness and the Sensation Seeking Scale and performed a computerized two-choice gambling task comprising different feedback options with positive vs. negative valence (gain or loss and high or low magnitude (5 vs. 25 points. RESULTS: We observed greater increases of amplitudes of the feedback-related negativity and of activity in the theta, alpha and low-beta frequency range following loss feedback and, in contrast, greater increase of activity in the high-beta frequency range following gain feedback. Significant magnitude effects were observed for theta and delta oscillations, indicating greater amplitudes upon feedback concerning large stakes. The theta amplitude changes during loss were negatively correlated with motor impulsivity scores, whereas alpha and low-beta increase upon loss and high-beta increase upon gain were positively correlated with various dimensions of sensation seeking. CONCLUSIONS: The findings suggest that the processing of feedback information involves several distinct processes, which are subserved by oscillations of different frequencies and are associated with different personality traits.

Oscillatory brain dynamics during sentence reading: A Fixation-related spectral perturbation analysis.

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Lorenzo eVignali

2016-04-01

Full Text Available The present study investigated oscillatory brain dynamics during self-paced sentence-level processing. Participants read fully correct sentences, sentences containing a semantic violation and sentences in which the order of the words was randomized. At the target word level, fixations on semantically unrelated words elicited a lower-beta band (13-18 Hz desynchronization. At the sentence level, gamma power (31-55 Hz increased linearly for syntactically correct sentences, but not when the order of the words was randomized. In the 300 to 900 ms time window after sentence onsets, theta power (4-7 Hz was greater for syntactically correct sentences as compared to sentences where no syntactic structure was preserved (random words condition. We interpret our results as conforming with a recently formulated predictive-coding framework for oscillatory neural dynamics during sentence-level language comprehension. Additionally, we discuss how our results relate to previous findings with serial visual presentation versus self-paced reading.

Active Neural Localization

OpenAIRE

Chaplot, Devendra Singh; Parisotto, Emilio; Salakhutdinov, Ruslan

2018-01-01

Localization is the problem of estimating the location of an autonomous agent from an observation and a map of the environment. Traditional methods of localization, which filter the belief based on the observations, are sub-optimal in the number of steps required, as they do not decide the actions taken by the agent. We propose "Active Neural Localizer", a fully differentiable neural network that learns to localize accurately and efficiently. The proposed model incorporates ideas of tradition...

Neuromuscular control of the point to point and oscillatory movements of a sagittal arm with the actor-critic reinforcement learning method.

Science.gov (United States)

Golkhou, Vahid; Parnianpour, Mohamad; Lucas, Caro

2005-04-01

In this study, we have used a single link system with a pair of muscles that are excited with alpha and gamma signals to achieve both point to point and oscillatory movements with variable amplitude and frequency.The system is highly nonlinear in all its physical and physiological attributes. The major physiological characteristics of this system are simultaneous activation of a pair of nonlinear muscle-like-actuators for control purposes, existence of nonlinear spindle-like sensors and Golgi tendon organ-like sensor, actions of gravity and external loading. Transmission delays are included in the afferent and efferent neural paths to account for a more accurate representation of the reflex loops.A reinforcement learning method with an actor-critic (AC) architecture instead of middle and low level of central nervous system (CNS), is used to track a desired trajectory. The actor in this structure is a two layer feedforward neural network and the critic is a model of the cerebellum. The critic is trained by state-action-reward-state-action (SARSA) method. The critic will train the actor by supervisory learning based on the prior experiences. Simulation studies of oscillatory movements based on the proposed algorithm demonstrate excellent tracking capability and after 280 epochs the RMS error for position and velocity profiles were 0.02, 0.04 rad and rad/s, respectively.

Global existence of periodic solutions of BAM neural networks with variable coefficients

International Nuclear Information System (INIS)

Guo Shangjiang; Huang Lihong; Dai Binxiang; Zhang Zhongzhi

2003-01-01

In this Letter, we study BAM (bidirectional associative memory) networks with variable coefficients. By some spectral theorems and a continuation theorem based on coincidence degree, we not only obtain some new sufficient conditions ensuring the existence, uniqueness, and global exponential stability of the periodic solution but also estimate the exponentially convergent rate. Our results are less restrictive than previously known criteria and can be applied to neural networks with a broad range of activation functions assuming neither differentiability nor strict monotonicity. Moreover, these conclusions are presented in terms of system parameters and can be easily verified for the globally Lipschitz and the spectral radius being less than 1. Therefore, our results should be useful in the design and applications of periodic oscillatory neural circuits for neural networks with delays

Resting-state oscillatory activity in children born small for gestational age: a magnetoencephalographic study

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Maria eBoersma

2013-09-01

Full Text Available Growth restriction in utero during a period that is critical for normal growth of the brain, has previously been associated with deviations in cognitive abilities and brain anatomical and functional changes. We measured magnetoencephalography (MEG in 4-7 year old children to test if children born small for gestational age (SGA show deviations in resting-state brain oscillatory activity. Children born SGA children with postnatally spontaneous catch-up growth (SGA+; 6 boys, 7 girls; mean age 6.3 y (SD=0.9 and children born appropriate for gestational age (AGA; 7 boys, 3 girls; mean age 6.0 y (SD=1.2 participated in a resting-state MEG study. We calculated absolute and relative power spectra and used nonparametric statistics to test for group differences. SGA+ and AGA born children showed no significant differences in absolute and relative power except for reduced absolute gamma band power in SGA children. At time of MEG investigation, SGA+ children showed was significantly lower head circumference (HC and a trend toward lower IQ, however there was no association of HC or IQ with absolute or relative power. Except for reduced absolute gamma band power, our findings suggest normal brain activity patterns at school age in a group of children born SGA in which spontaneous catch-up growth of bodily length after birth occurred. Although previous findings suggest that being born SGA alters brain oscillatory activity early in neonatal life, we show that these neonatal alterations do not persist at early school age when spontaneous postnatal catch-up growth occurs after birth.

Local correlations for flap gap oscillatory blowing active flow control technology

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Cătălin NAE

2010-09-01

Full Text Available Active technology for oscillatory blowing in the flap gap has been tested at INCAS subsonic wind tunnel in order to evaluate this technology for usage in high lift systems with active flow control. The main goal for this investigation was to validate TRL level 4 for this technology and to extend towards flight testing. CFD analysis was performed in order to identify local correlations with experimental data and to better formulate a design criteria so that a maximum increase in lift is possible under given geometrical constraints. Reference to a proposed metric for noise evaluation is also given. This includes basic 2D flow cases and also 2.5D configurations. In 2.5D test cases this work has been extended so that the proposed system may be selected as a mature technology in the JTI Clean Sky, Smart Fixed Wing Aircraft ITD. Complex post-processing of the experimental and CFD data was mainly oriented towards system efficiency and TRL evaluation for this active technology.

Neural activation in stress-related exhaustion

DEFF Research Database (Denmark)

Gavelin, Hanna Malmberg; Neely, Anna Stigsdotter; Andersson, Micael

2017-01-01

The primary purpose of this study was to investigate the association between burnout and neural activation during working memory processing in patients with stress-related exhaustion. Additionally, we investigated the neural effects of cognitive training as part of stress rehabilitation. Fifty...... association between burnout level and working memory performance was found, however, our findings indicate that frontostriatal neural responses related to working memory were modulated by burnout severity. We suggest that patients with high levels of burnout need to recruit additional cognitive resources...... to uphold task performance. Following cognitive training, increased neural activation was observed during 3-back in working memory-related regions, including the striatum, however, low sample size limits any firm conclusions....

Oscillatory systems in mitochondria

Energy Technology Data Exchange (ETDEWEB)

Gooch, V D; Packer, L

1974-01-01

Comparison of known mitochondrial oscillatory systems suggest that they all have a common mechanism. Investigation of the requirements of these various systems reveals a common set of basic features that indicate ion-transport processes to be the key components mediating oscillatory behavior. These ion-transport processes include (a) a diffusional transport of a cation and a H/sup +/, (b) a diffusional, non-ionic, coupled transport of a H/sup +/ with a weak acid anion, and (c) an energy-linked H/sup +/ transport. To adequately describe the oscillatory phenomenon, however, it is necessary to consider also the presence of (a) nonlinear concentration profiles of one or more ions within the membrane and its unstirred layers, and (b) feedback loops developed as a result of molecular conformational changes or membrane structural changes affecting ionic flows, each having a major influence on the other.

Frequency-Dependent Enhancement of Fluid Intelligence Induced by Transcranial Oscillatory Potentials

Energy Technology Data Exchange (ETDEWEB)

Santarnecchi, Emiliano [Univ. of Siena (Italy). Dept. of Medicine, Surgery and Neuroscience; Polizzotto, Nicola Riccardo [Univ. of Pittsburgh, PA (United States). Dept. of Psychiatry; Godone, Marco [Univ. of Siena (Italy). Dept. of Medicine, Surgery and Neuroscience; Giovannelli, Fabio [San Giovanni di Dio Hospital, Florence (Italy). Complex Unit of Neurology; Feurra, Matteo [Univ. of Siena (Italy). Dept. of Medicine, Surgery and Neuroscience; Matzen, Laura [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rossi, Alessandro [Univ. of Siena (Italy). Dept. of Medicine, Surgery and Neuroscience; Rossi, Simone [Univ. of Siena (Italy). Dept. of Medicine, Surgery and Neuroscience

2013-08-05

Everyday problem solving requires the ability to go beyond experience by efficiently encoding and manipulating new information, i.e., fluid intelligence (Gf) [1]. Performance in tasks involving Gf, such as logical and abstract reasoning, has been shown to rely on distributed neural networks, with a crucial role played by prefrontal regions [2]. Synchronization of neuronal activity in the gamma band is a ubiquitous phenomenon within the brain; however, no evidence of its causal involvement in cognition exists to date [3]. Here, we show an enhancement of Gf ability in a cognitive task induced by exogenous rhythmic stimulation within the gamma band. Imperceptible alternating current [4] delivered through the scalp over the left middle frontal gyrus resulted in a frequency-specific shortening of the time required to find the correct solution in a visuospatial abstract reasoning task classically employed to measure Gf abilities (i.e., Raven’s matrices) [5]. Crucially, gamma-band stimulation (γ-tACS) selectively enhanced performance only on more complex trials involving conditional/logical reasoning. The finding presented here supports a direct involvement of gamma oscillatory activity in the mechanisms underlying higher-order human cognition.

Impaired odour discrimination on desynchronization of odour-encoding neural assemblies

Science.gov (United States)

Stopfer, Mark; Bhagavan, Seetha; Smith, Brian H.; Laurent, Gilles

1997-11-01

Stimulus-evoked oscillatory synchronization of neural assemblies has been described in the olfactory and visual systems of several vertebrates and invertebrates. In locusts, information about odour identity is contained in the timing of action potentials in an oscillatory population response, suggesting that oscillations may reflect a common reference for messages encoded in time. Although the stimulus-evoked oscillatory phenomenon is reliable, its roles in sensation, perception, memory formation and pattern recognition remain to be demonstrated - a task requiring a behavioural paradigm. Using honeybees, we now demonstrate that odour encoding involves, as it does in locusts, the oscillatory synchronization of assemblies of projection neurons and that this synchronization is also selectively abolished by picrotoxin, an antagonist of the GABAA (γ-aminobutyric acid) receptor. By using a behavioural learning paradigm, we show that picrotoxin-induced desynchronization impairs the discrimination of molecularly similar odorants, but not that of dissimilar odorants. It appears, therefore, that oscillatory synchronization of neuronal assemblies is functionally relevant, and essential for fine sensory discrimination. This suggests that oscillatory synchronization and the kind of temporal encoding it affords provide an additional dimension by which the brain could segment spatially overlapping stimulus representations.

Resting-state oscillatory brain dynamics in Alzheimer disease

NARCIS (Netherlands)

de Haan, W.; Stam, C.J.; Jones, B.F.; Zuiderwijk, I.M.; van Dijk, B.W.; Scheltens, P.

2008-01-01

Altered oscillatory brain activity in Alzheimer disease (AD) may reflect underlying neuropathological changes, and its characterization might lead to new diagnostic possibilities. The present study using quantitative magnetoencephalography was set up to examine power spectrum changes in AD patients,

Excito-oscillatory dynamics as a mechanism of ventricular fibrillation.

Science.gov (United States)

Gray, Richard A; Huelsing, Delilah J

2008-04-01

The instabilities associated with reentrant spiral waves are of paramount importance to the initiation and maintenance of tachyarrhythmias, especially ventricular fibrillation (VF). In addition to tissue heterogeneities, there are only a few basic purported mechanisms of spiral wave breakup, most notably restitution. We test the hypothesis that oscillatory membrane properties act to destabilize spiral waves. We recorded transmembrane potential (V(m)) from isolated rabbit myocytes using a constant current stimulation protocol. We developed a mathematical model that included both the stable excitable equilibrium point at resting V(m) (-80 mV) and the unstable oscillatory equilibrium point at elevated V(m) (-10 mV). Spiral wave dynamics were studied in 2-dimensional grids using variants of the model. All models showed restitution and reproduced the experimental values of transmembrane resistance at rest and during the action potential plateau. Stable spiral waves were observed when the model showed only 1 equilibrium point. However, spatio-temporal complexity was observed if the model showed both excitable and oscillatory equilibrium points (i.e., excito-oscillatory models). The initial wave breaks resulted from oscillatory waves expanding in all directions; after a few beats, the patterns were characterized by a combination of unstable spiral waves and target patterns consistent with the patterns observed on the heart surface during VF. In our model, this VF-like activity only occurred when the single cell period of V(m) oscillations was within a specific range. The VF-like patterns observed in our excito-oscillatory models could not be explained by the existing proposed instability mechanisms. Our results introduce the important suggestion that membrane dynamics responsible for V(m) oscillations at elevated V(m) levels can destabilize spiral waves and thus may be a novel therapeutic target for preventing VF.

Identifying Emotions on the Basis of Neural Activation.

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Kassam, Karim S; Markey, Amanda R; Cherkassky, Vladimir L; Loewenstein, George; Just, Marcel Adam

2013-01-01

We attempt to determine the discriminability and organization of neural activation corresponding to the experience of specific emotions. Method actors were asked to self-induce nine emotional states (anger, disgust, envy, fear, happiness, lust, pride, sadness, and shame) while in an fMRI scanner. Using a Gaussian Naïve Bayes pooled variance classifier, we demonstrate the ability to identify specific emotions experienced by an individual at well over chance accuracy on the basis of: 1) neural activation of the same individual in other trials, 2) neural activation of other individuals who experienced similar trials, and 3) neural activation of the same individual to a qualitatively different type of emotion induction. Factor analysis identified valence, arousal, sociality, and lust as dimensions underlying the activation patterns. These results suggest a structure for neural representations of emotion and inform theories of emotional processing.

Establishing a Statistical Link between Network Oscillations and Neural Synchrony.

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Pengcheng Zhou

2015-10-01

Full Text Available Pairs of active neurons frequently fire action potentials or "spikes" nearly synchronously (i.e., within 5 ms of each other. This spike synchrony may occur by chance, based solely on the neurons' fluctuating firing patterns, or it may occur too frequently to be explicable by chance alone. When spike synchrony above chances levels is present, it may subserve computation for a specific cognitive process, or it could be an irrelevant byproduct of such computation. Either way, spike synchrony is a feature of neural data that should be explained. A point process regression framework has been developed previously for this purpose, using generalized linear models (GLMs. In this framework, the observed number of synchronous spikes is compared to the number predicted by chance under varying assumptions about the factors that affect each of the individual neuron's firing-rate functions. An important possible source of spike synchrony is network-wide oscillations, which may provide an essential mechanism of network information flow. To establish the statistical link between spike synchrony and network-wide oscillations, we have integrated oscillatory field potentials into our point process regression framework. We first extended a previously-published model of spike-field association and showed that we could recover phase relationships between oscillatory field potentials and firing rates. We then used this new framework to demonstrate the statistical relationship between oscillatory field potentials and spike synchrony in: 1 simulated neurons, 2 in vitro recordings of hippocampal CA1 pyramidal cells, and 3 in vivo recordings of neocortical V4 neurons. Our results provide a rigorous method for establishing a statistical link between network oscillations and neural synchrony.

The effect of the neural activity on topological properties of growing neural networks.

Science.gov (United States)

Gafarov, F M; Gafarova, V R

2016-09-01

The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network's activity influence on its topological properties we compared it with the random growth network not depending on network's activity. By using the random graphs theory methods for the analysis of the network's connections structure it is shown that the growth in neural networks results in the formation of a well-known "small-world" network.

Oscillatory magneto-convection under magnetic field modulation

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Palle Kiran

2018-03-01

Full Text Available In this paper we investigate an oscillatory mode of nonlinear magneto-convection under time dependant magnetic field. The time dependant magnetic field consists steady and oscillatory parts. The oscillatory part of the imposed magnetic field is assumed to be of third order. An externally imposed vertical magnetic field in an electrically conducting horizontal fluid layer is considered. The finite amplitude analysis is discussed while perturbing the system. The complex Ginzburg-Landau model is used to derive an amplitude of oscillatory convection for weakly nonlinear mode. Heat transfer is quantified in terms of the Nusselt number, which is governed by the Landau equation. The variation of the modulation excitation of the magnetic field alternates heat transfer in the layer. The modulation excitation of the magnetic field is used either to enhance or diminish the heat transfer in the system. Further, it is found that, oscillatory mode of convection enhances the heat transfer and than stationary convection. The results have possible technological applications in magnetic fluid based systems involving energy transmission. Keywords: Weakly nonlinear theory, Oscillatory convection, Complex Ginzburg Landau model, Magnetic modulation

Identifying Emotions on the Basis of Neural Activation.

Directory of Open Access Journals (Sweden)

Karim S Kassam

Full Text Available We attempt to determine the discriminability and organization of neural activation corresponding to the experience of specific emotions. Method actors were asked to self-induce nine emotional states (anger, disgust, envy, fear, happiness, lust, pride, sadness, and shame while in an fMRI scanner. Using a Gaussian Naïve Bayes pooled variance classifier, we demonstrate the ability to identify specific emotions experienced by an individual at well over chance accuracy on the basis of: 1 neural activation of the same individual in other trials, 2 neural activation of other individuals who experienced similar trials, and 3 neural activation of the same individual to a qualitatively different type of emotion induction. Factor analysis identified valence, arousal, sociality, and lust as dimensions underlying the activation patterns. These results suggest a structure for neural representations of emotion and inform theories of emotional processing.

Oscillatory activity in the human basal ganglia: more than just beta, more than just Parkinson's disease.

Science.gov (United States)

Alegre, Manuel; Valencia, Miguel

2013-10-01

The implantation of deep brain stimulators in different structures of the basal ganglia to treat neurological and psychiatric diseases has allowed the recording of local field potential activity in these structures. The analysis of these signals has helped our understanding of basal ganglia physiology in health and disease. However, there remain some major challenges and questions for the future. In a recent work, Tan et al. (Tan, H., Pogosyan, A., Anam, A., Foltynie, T., Limousin, P., Zrinzo, L., et al. 2013. Frequency specific activity in subthalamic nucleus correlates with hand bradykinesia in Parkinson's disease. Exp. Neurol. 240,122-129) take profit of these recordings to study the changes in subthalamic oscillatory activity during the hold and release phases of a grasping paradigm, and correlate the changes in different frequency bands with performance parameters. They found that beta activity was related to the release phase, while force maintenance related most to theta and gamma/HFO activity. There was no significant effect of the motor state of the patient on this latter association. These findings suggest that the alterations in the oscillatory activity of the basal ganglia in Parkinson's disease are not limited to the beta band, and they involve aspects different from movement preparation and initiation. Additionally, these results highlight the usefulness of the combination of well-designed paradigms with recordings in off and on motor states (in Parkinson's disease), or in different pathologies, in order to understand not only the pathophysiology of the diseases affecting the patients, but also the normal physiology of the basal ganglia. Copyright © 2013 Elsevier Inc. All rights reserved.

Race modulates neural activity during imitation

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Losin, Elizabeth A. Reynolds; Iacoboni, Marco; Martin, Alia; Cross, Katy A.; Dapretto, Mirella

2014-01-01

Imitation plays a central role in the acquisition of culture. People preferentially imitate others who are self-similar, prestigious or successful. Because race can indicate a person's self-similarity or status, race influences whom people imitate. Prior studies of the neural underpinnings of imitation have not considered the effects of race. Here we measured neural activity with fMRI while European American participants imitated meaningless gestures performed by actors of their own race, and two racial outgroups, African American, and Chinese American. Participants also passively observed the actions of these actors and their portraits. Frontal, parietal and occipital areas were differentially activated while participants imitated actors of different races. More activity was present when imitating African Americans than the other racial groups, perhaps reflecting participants' reported lack of experience with and negative attitudes towards this group, or the group's lower perceived social status. This pattern of neural activity was not found when participants passively observed the gestures of the actors or simply looked at their faces. Instead, during face-viewing neural responses were overall greater for own-race individuals, consistent with prior race perception studies not involving imitation. Our findings represent a first step in elucidating neural mechanisms involved in cultural learning, a process that influences almost every aspect of our lives but has thus far received little neuroscientific study. PMID:22062193

Neural synchrony in cortical networks: history, concept and current status

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Peter Uhlhaas

2009-07-01

Full Text Available Following the discovery of context-dependent synchronization of oscillatory neuronal responses in the visual system, the role of neural synchrony in cortical networks has been expanded to provide a general mechanism for the coordination of distributed neural activity patterns. In the current paper, we present an update of the status of this hypothesis through summarizing recent results from our laboratory that suggest important new insights regarding the mechanisms, function and relevance of this phenomenon. In the first part, we present recent results derived from animal experiments and mathematical simulations that provide novel explanations and mechanisms for zero and nero-zero phase lag synchronization. In the second part, we shall discuss the role of neural synchrony for expectancy during perceptual organization and its role in conscious experience. This will be followed by evidence that indicates that in addition to supporting conscious cognition, neural synchrony is abnormal in major brain disorders, such as schizophrenia and autism spectrum disorders. We conclude this paper with suggestions for further research as well as with critical issues that need to be addressed in future studies.

Face the hierarchy: ERP and oscillatory brain responses in social rank processing.

Science.gov (United States)

Breton, Audrey; Jerbi, Karim; Henaff, Marie-Anne; Cheylus, Anne; Baudouin, Jean-Yves; Schmitz, Christina; Krolak-Salmon, Pierre; Van der Henst, Jean-Baptiste

2014-01-01

Recognition of social hierarchy is a key feature that helps us navigate through our complex social environment. Neuroimaging studies have identified brain structures involved in the processing of hierarchical stimuli but the precise temporal dynamics of brain activity associated with such processing remains largely unknown. Here, we used electroencephalography to examine the effect of social hierarchy on neural responses elicited by faces. In contrast to previous studies, the key manipulation was that a hierarchical context was constructed, not by varying facial expressions, but by presenting neutral-expression faces in a game setting. Once the performance-based hierarchy was established, participants were presented with high-rank, middle-rank and low-rank player faces and had to evaluate the rank of each face with respect to their own position. Both event-related potentials and task-related oscillatory activity were investigated. Three main findings emerge from the study. First, the experimental manipulation had no effect on the early N170 component, which may suggest that hierarchy did not modulate the structural encoding of neutral-expression faces. Second, hierarchy significantly modulated the amplitude of the late positive potential (LPP) within a 400-700 ms time-window, with more a prominent LPP occurring when the participants processed the face of the highest-rank player. Third, high-rank faces were associated with the highest reduction of alpha power. Taken together these findings provide novel electrophysiological evidence for enhanced allocation of attentional resource in the presence of high-rank faces. At a broader level, this study brings new insights into the neural processing underlying social categorization.

Periodic oscillatory solution in delayed competitive-cooperative neural networks: A decomposition approach

International Nuclear Information System (INIS)

Yuan Kun; Cao Jinde

2006-01-01

In this paper, the problems of exponential convergence and the exponential stability of the periodic solution for a general class of non-autonomous competitive-cooperative neural networks are analyzed via the decomposition approach. The idea is to divide the connection weights into inhibitory or excitatory types and thereby to embed a competitive-cooperative delayed neural network into an augmented cooperative delay system through a symmetric transformation. Some simple necessary and sufficient conditions are derived to ensure the componentwise exponential convergence and the exponential stability of the periodic solution of the considered neural networks. These results generalize and improve the previous works, and they are easy to check and apply in practice

Oscillatory magneto-convection under magnetic field modulation

OpenAIRE

Kiran, Palle; Bhadauria, B.S.; Narasimhulu, Y.

2017-01-01

In this paper we investigate an oscillatory mode of nonlinear magneto-convection under time dependant magnetic field. The time dependant magnetic field consists steady and oscillatory parts. The oscillatory part of the imposed magnetic field is assumed to be of third order. An externally imposed vertical magnetic field in an electrically conducting horizontal fluid layer is considered. The finite amplitude analysis is discussed while perturbing the system. The complex Ginzburg-Landau model is...

Grasping hand verbs: oscillatory beta and alpha correlates of action-word processing.

Directory of Open Access Journals (Sweden)

Valentina Niccolai

Full Text Available The grounded cognition framework proposes that sensorimotor brain areas, which are typically involved in perception and action, also play a role in linguistic processing. We assessed oscillatory modulation during visual presentation of single verbs and localized cortical motor regions by means of isometric contraction of hand and foot muscles. Analogously to oscillatory activation patterns accompanying voluntary movements, we expected a somatotopically distributed suppression of beta and alpha frequencies in the motor cortex during processing of body-related action verbs. Magnetoencephalographic data were collected during presentation of verbs that express actions performed using the hands (H or feet (F. Verbs denoting no bodily movement (N were used as a control. Between 150 and 500 msec after visual word onset, beta rhythms were suppressed in H and F in comparison with N in the left hemisphere. Similarly, alpha oscillations showed left-lateralized power suppression in the H-N contrast, although at a later stage. The cortical oscillatory activity that typically occurs during voluntary movements is therefore found to somatotopically accompany the processing of body-related verbs. The combination of a localizer task with the oscillatory investigation applied to verb reading as in the present study provides further methodological possibilities of tracking language processing in the brain.

Disturbed oscillatory brain dynamics in subcortical ischemic vascular dementia

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van Straaten Elisabeth CW

2012-07-01

Full Text Available Abstract Background White matter hyperintensities (WMH can lead to dementia but the underlying physiological mechanisms are unclear. We compared relative oscillatory power from electroencephalographic studies (EEGs of 17 patients with subcortical ischemic vascular dementia, based on extensive white matter hyperintensities (SIVD-WMH with 17 controls to investigate physiological changes underlying this diagnosis. Results Differences between the groups were large, with a decrease of relative power of fast activity in patients (alpha power 0.25 ± 0.12 versus 0.38 ± 0.13, p = 0.01; beta power 0.08 ± 0.04 versus 0.19 ± 0.07; p Conclusions This pattern of disturbance in oscillatory brain activity indicate loss of connections between neurons, providing a first step in the understanding of cognitive dysfunction in SIVD-WMH.

Oscillatory serotonin function in depression.

Science.gov (United States)

Salomon, Ronald M; Cowan, Ronald L

2013-11-01

Oscillations in brain activities with periods of minutes to hours may be critical for normal mood behaviors. Ultradian (faster than circadian) rhythms of mood behaviors and associated central nervous system activities are altered in depression. Recent data suggest that ultradian rhythms in serotonin (5HT) function also change in depression. In two separate studies, 5HT metabolites in cerebrospinal fluid (CSF) were measured every 10 min for 24 h before and after chronic antidepressant treatment. Antidepressant treatments were associated with enhanced ultradian amplitudes of CSF metabolite levels. Another study used resting-state functional magnetic resonance imaging (fMRI) to measure amplitudes of dorsal raphé activation cycles following sham or active dietary depletions of the 5HT precursor (tryptophan). During depletion, amplitudes of dorsal raphé activation cycles increased with rapid 6 s periods (about 0.18 Hz) while functional connectivity weakened between dorsal raphé and thalamus at slower periods of 20 s (0.05 Hz). A third approach studied MDMA (ecstasy, 3,4-methylenedioxy-N-methylamphetamine) users because of their chronically diminished 5HT function compared with non-MDMA polysubstance users (Karageorgiou et al., 2009). Compared with a non-MDMA using cohort, MDMA users showed diminished fMRI intra-regional coherence in motor regions along with altered functional connectivity, again suggesting effects of altered 5HT oscillatory function. These data support a hypothesis that qualities of ultradian oscillations in 5HT function may critically influence moods and behaviors. Dysfunctional 5HT rhythms in depression may be a common endpoint and biomarker for depression, linking dysfunction of slow brain network oscillators to 5HT mechanisms affected by commonly available treatments. 5HT oscillatory dysfunction may define illness subtypes and predict responses to serotonergic agents. Further studies of 5HT oscillations in depression are indicated. Copyright �

Oscillatory neuronal activity reflects lexical-semantic feature integration within and across sensory modalities in distributed cortical networks.

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van Ackeren, Markus J; Schneider, Till R; Müsch, Kathrin; Rueschemeyer, Shirley-Ann

2014-10-22

Research from the previous decade suggests that word meaning is partially stored in distributed modality-specific cortical networks. However, little is known about the mechanisms by which semantic content from multiple modalities is integrated into a coherent multisensory representation. Therefore we aimed to characterize differences between integration of lexical-semantic information from a single modality compared with two sensory modalities. We used magnetoencephalography in humans to investigate changes in oscillatory neuronal activity while participants verified two features for a given target word (e.g., "bus"). Feature pairs consisted of either two features from the same modality (visual: "red," "big") or different modalities (auditory and visual: "red," "loud"). The results suggest that integrating modality-specific features of the target word is associated with enhanced high-frequency power (80-120 Hz), while integrating features from different modalities is associated with a sustained increase in low-frequency power (2-8 Hz). Source reconstruction revealed a peak in the anterior temporal lobe for low-frequency and high-frequency effects. These results suggest that integrating lexical-semantic knowledge at different cortical scales is reflected in frequency-specific oscillatory neuronal activity in unisensory and multisensory association networks. Copyright © 2014 the authors 0270-6474/14/3314318-06$15.00/0.

Large-scale multielectrode recording and stimulation of neural activity

International Nuclear Information System (INIS)

Sher, A.; Chichilnisky, E.J.; Dabrowski, W.; Grillo, A.A.; Grivich, M.; Gunning, D.; Hottowy, P.; Kachiguine, S.; Litke, A.M.; Mathieson, K.; Petrusca, D.

2007-01-01

Large circuits of neurons are employed by the brain to encode and process information. How this encoding and processing is carried out is one of the central questions in neuroscience. Since individual neurons communicate with each other through electrical signals (action potentials), the recording of neural activity with arrays of extracellular electrodes is uniquely suited for the investigation of this question. Such recordings provide the combination of the best spatial (individual neurons) and temporal (individual action-potentials) resolutions compared to other large-scale imaging methods. Electrical stimulation of neural activity in turn has two very important applications: it enhances our understanding of neural circuits by allowing active interactions with them, and it is a basis for a large variety of neural prosthetic devices. Until recently, the state-of-the-art in neural activity recording systems consisted of several dozen electrodes with inter-electrode spacing ranging from tens to hundreds of microns. Using silicon microstrip detector expertise acquired in the field of high-energy physics, we created a unique neural activity readout and stimulation framework that consists of high-density electrode arrays, multi-channel custom-designed integrated circuits, a data acquisition system, and data-processing software. Using this framework we developed a number of neural readout and stimulation systems: (1) a 512-electrode system for recording the simultaneous activity of as many as hundreds of neurons, (2) a 61-electrode system for electrical stimulation and readout of neural activity in retinas and brain-tissue slices, and (3) a system with telemetry capabilities for recording neural activity in the intact brain of awake, naturally behaving animals. We will report on these systems, their various applications to the field of neurobiology, and novel scientific results obtained with some of them. We will also outline future directions

EEG neural oscillatory dynamics reveal semantic and response conflict at difference levels of conflict awareness

OpenAIRE

Jun Jiang; Qinglin Zhang; Simon Van Gaal

2015-01-01

Although previous work has shown that conflict can be detected in the absence of awareness, it is unknown how different sources of conflict (i.e., semantic, response) are processed in the human brain and whether these processes are differently modulated by conflict awareness. To explore this issue, we extracted oscillatory power dynamics from electroencephalographic (EEG) data recorded while human participants performed a modified version of the Stroop task. Crucially, in this task conflict a...

Microfluidic mixing through oscillatory transverse perturbations

Science.gov (United States)

Wu, J. W.; Xia, H. M.; Zhang, Y. Y.; Zhu, P.

2018-05-01

Fluid mixing in miniaturized fluidic devices is a challenging task. In this work, the mixing enhancement through oscillatory transverse perturbations coupling with divergent circular chambers is studied. To simplify the design, an autonomous microfluidic oscillator is used to produce the oscillatory flow. It is then applied to four side-channels that intersect with a central channel of constant flow. The mixing performance is tested at high fluid viscosities of up to 16 cP. Results show that the oscillatory flow can cause strong transverse perturbations which effectively enhance the mixing. The influence of a fluidic capacitor in the central channel is also examined, which at low viscosities can intensify the perturbations and further improve the mixing.

Associative memory model with spontaneous neural activity

Science.gov (United States)

Kurikawa, Tomoki; Kaneko, Kunihiko

2012-05-01

We propose a novel associative memory model wherein the neural activity without an input (i.e., spontaneous activity) is modified by an input to generate a target response that is memorized for recall upon the same input. Suitable design of synaptic connections enables the model to memorize input/output (I/O) mappings equaling 70% of the total number of neurons, where the evoked activity distinguishes a target pattern from others. Spontaneous neural activity without an input shows chaotic dynamics but keeps some similarity with evoked activities, as reported in recent experimental studies.

Neural networks with discontinuous/impact activations

CERN Document Server

Akhmet, Marat

2014-01-01

This book presents as its main subject new models in mathematical neuroscience. A wide range of neural networks models with discontinuities are discussed, including impulsive differential equations, differential equations with piecewise constant arguments, and models of mixed type. These models involve discontinuities, which are natural because huge velocities and short distances are usually observed in devices modeling the networks. A discussion of the models, appropriate for the proposed applications, is also provided. This book also: Explores questions related to the biological underpinning for models of neural networks\\ Considers neural networks modeling using differential equations with impulsive and piecewise constant argument discontinuities Provides all necessary mathematical basics for application to the theory of neural networks Neural Networks with Discontinuous/Impact Activations is an ideal book for researchers and professionals in the field of engineering mathematics that have an interest in app...

Periodic bidirectional associative memory neural networks with distributed delays

Science.gov (United States)

Chen, Anping; Huang, Lihong; Liu, Zhigang; Cao, Jinde

2006-05-01

Some sufficient conditions are obtained for the existence and global exponential stability of a periodic solution to the general bidirectional associative memory (BAM) neural networks with distributed delays by using the continuation theorem of Mawhin's coincidence degree theory and the Lyapunov functional method and the Young's inequality technique. These results are helpful for designing a globally exponentially stable and periodic oscillatory BAM neural network, and the conditions can be easily verified and be applied in practice. An example is also given to illustrate our results.

iTBS-induced LTP-like plasticity parallels oscillatory activity changes in the primary sensory and motor areas of macaque monkeys.

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Papazachariadis, Odysseas; Dante, Vittorio; Verschure, Paul F M J; Del Giudice, Paolo; Ferraina, Stefano

2014-01-01

Recently, neuromodulation techniques based on the use of repetitive transcranial magnetic stimulation (rTMS) have been proposed as a non-invasive and efficient method to induce in vivo long-term potentiation (LTP)-like aftereffects. However, the exact impact of rTMS-induced perturbations on the dynamics of neuronal population activity is not well understood. Here, in two monkeys, we examine changes in the oscillatory activity of the sensorimotor cortex following an intermittent theta burst stimulation (iTBS) protocol. We first probed iTBS modulatory effects by testing the iTBS-induced facilitation of somatosensory evoked potentials (SEP). Then, we examined the frequency information of the electrocorticographic signal, obtained using a custom-made miniaturised multi-electrode array for electrocorticography, after real or sham iTBS. We observed that iTBS induced facilitation of SEPs and influenced spectral components of the signal, in both animals. The latter effect was more prominent on the θ band (4-8 Hz) and the high γ band (55-90 Hz), de-potentiated and potentiated respectively. We additionally found that the multi-electrode array uniformity of β (13-26 Hz) and high γ bands were also afflicted by iTBS. Our study suggests that enhanced cortical excitability promoted by iTBS parallels a dynamic reorganisation of the interested neural network. The effect in the γ band suggests a transient local modulation, possibly at the level of synaptic strength in interneurons. The effect in the θ band suggests the disruption of temporal coordination on larger spatial scales.

iTBS-induced LTP-like plasticity parallels oscillatory activity changes in the primary sensory and motor areas of macaque monkeys.

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Odysseas Papazachariadis

Full Text Available Recently, neuromodulation techniques based on the use of repetitive transcranial magnetic stimulation (rTMS have been proposed as a non-invasive and efficient method to induce in vivo long-term potentiation (LTP-like aftereffects. However, the exact impact of rTMS-induced perturbations on the dynamics of neuronal population activity is not well understood. Here, in two monkeys, we examine changes in the oscillatory activity of the sensorimotor cortex following an intermittent theta burst stimulation (iTBS protocol. We first probed iTBS modulatory effects by testing the iTBS-induced facilitation of somatosensory evoked potentials (SEP. Then, we examined the frequency information of the electrocorticographic signal, obtained using a custom-made miniaturised multi-electrode array for electrocorticography, after real or sham iTBS. We observed that iTBS induced facilitation of SEPs and influenced spectral components of the signal, in both animals. The latter effect was more prominent on the θ band (4-8 Hz and the high γ band (55-90 Hz, de-potentiated and potentiated respectively. We additionally found that the multi-electrode array uniformity of β (13-26 Hz and high γ bands were also afflicted by iTBS. Our study suggests that enhanced cortical excitability promoted by iTBS parallels a dynamic reorganisation of the interested neural network. The effect in the γ band suggests a transient local modulation, possibly at the level of synaptic strength in interneurons. The effect in the θ band suggests the disruption of temporal coordination on larger spatial scales.

A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback.

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Christopher L Buckley

2018-01-01

Full Text Available During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results

A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback.

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Buckley, Christopher L; Toyoizumi, Taro

2018-01-01

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence

The roles and mechanism of ultradian oscillatory expression of the mouse Hes genes.

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Harima, Yukiko; Imayoshi, Itaru; Shimojo, Hiromi; Kobayashi, Taeko; Kageyama, Ryoichiro

2014-10-01

Somites, metameric structures, give rise to the vertebral column, ribs, skeletal muscles and subcutaneous tissues. In mouse embryos, a pair of somites is formed every 2h by segmentation of the anterior parts of the presomitic mesoderm. This periodic event is regulated by a biological clock called the segmentation clock, which involves cyclic expression of the basic helix-loop-helix gene Hes7. Hes7 oscillation is regulated by negative feedback with a delayed timing. This process has been mathematically simulated by differential-delay equations, which predict that negative feedback with shorter delays would abolish oscillations or produce dampened but more rapid oscillations. We found that reducing the number of introns within the Hes7 gene shortens the delay and abolishes Hes7 oscillation or results in a more rapid tempo of Hes7 oscillation, increasing the number of somites and vertebrae in the cervical and upper thoracic region. We also found that Hes1, a Hes7-related gene, is expressed in an oscillatory manner by many cell types, including fibroblasts and neural stem cells. In these cells, Hes1 expression oscillates with a period of about 2-3h, and this oscillation is important for cell cycle progression. Furthermore, in neural stem cells, Hes1 oscillation drives cyclic expression of the proneural genes Ascl1 and Neurogenin2 and regulates multipotency. Hes1 expression oscillates more slowly in embryonic stem cells, and Hes1 oscillation regulates their fate preferences. Taken together, these results suggest that oscillatory expression with short periods (ultradian oscillation) is important for many biological events. Copyright © 2014 Elsevier Ltd. All rights reserved.

Male veterans with PTSD exhibit aberrant neural dynamics during working memory processing: an MEG study.

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McDermott, Timothy J; Badura-Brack, Amy S; Becker, Katherine M; Ryan, Tara J; Khanna, Maya M; Heinrichs-Graham, Elizabeth; Wilson, Tony W

2016-06-01

Posttraumatic stress disorder (PTSD) is associated with executive functioning deficits, including disruptions in working memory. In this study, we examined the neural dynamics of working memory processing in veterans with PTSD and a matched healthy control sample using magnetoencephalography (MEG). Our sample of recent combat veterans with PTSD and demographically matched participants without PTSD completed a working memory task during a 306-sensor MEG recording. The MEG data were preprocessed and transformed into the time-frequency domain. Significant oscillatory brain responses were imaged using a beamforming approach to identify spatiotemporal dynamics. Fifty-one men were included in our analyses: 27 combat veterans with PTSD and 24 controls. Across all participants, a dynamic wave of neural activity spread from posterior visual cortices to left frontotemporal regions during encoding, consistent with a verbal working memory task, and was sustained throughout maintenance. Differences related to PTSD emerged during early encoding, with patients exhibiting stronger α oscillatory responses than controls in the right inferior frontal gyrus (IFG). Differences spread to the right supramarginal and temporal cortices during later encoding where, along with the right IFG, they persisted throughout the maintenance period. This study focused on men with combat-related PTSD using a verbal working memory task. Future studies should evaluate women and the impact of various traumatic experiences using diverse tasks. Posttraumatic stress disorder is associated with neurophysiological abnormalities during working memory encoding and maintenance. Veterans with PTSD engaged a bilateral network, including the inferior prefrontal cortices and supramarginal gyri. Right hemispheric neural activity likely reflects compensatory processing, as veterans with PTSD work to maintain accurate performance despite known cognitive deficits associated with the disorder.

Selective Attention to Auditory Memory Neurally Enhances Perceptual Precision.

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Lim, Sung-Joo; Wöstmann, Malte; Obleser, Jonas

2015-12-09

Selective attention to a task-relevant stimulus facilitates encoding of that stimulus into a working memory representation. It is less clear whether selective attention also improves the precision of a stimulus already represented in memory. Here, we investigate the behavioral and neural dynamics of selective attention to representations in auditory working memory (i.e., auditory objects) using psychophysical modeling and model-based analysis of electroencephalographic signals. Human listeners performed a syllable pitch discrimination task where two syllables served as to-be-encoded auditory objects. Valid (vs neutral) retroactive cues were presented during retention to allow listeners to selectively attend to the to-be-probed auditory object in memory. Behaviorally, listeners represented auditory objects in memory more precisely (expressed by steeper slopes of a psychometric curve) and made faster perceptual decisions when valid compared to neutral retrocues were presented. Neurally, valid compared to neutral retrocues elicited a larger frontocentral sustained negativity in the evoked potential as well as enhanced parietal alpha/low-beta oscillatory power (9-18 Hz) during memory retention. Critically, individual magnitudes of alpha oscillatory power (7-11 Hz) modulation predicted the degree to which valid retrocues benefitted individuals' behavior. Our results indicate that selective attention to a specific object in auditory memory does benefit human performance not by simply reducing memory load, but by actively engaging complementary neural resources to sharpen the precision of the task-relevant object in memory. Can selective attention improve the representational precision with which objects are held in memory? And if so, what are the neural mechanisms that support such improvement? These issues have been rarely examined within the auditory modality, in which acoustic signals change and vanish on a milliseconds time scale. Introducing a new auditory memory

Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro.

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Kirwan, Peter; Turner-Bridger, Benita; Peter, Manuel; Momoh, Ayiba; Arambepola, Devika; Robinson, Hugh P C; Livesey, Frederick J

2015-09-15

A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. © 2015. Published by The Company of Biologists Ltd.

Windowed active sampling for reliable neural learning

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Barakova, E.I; Spaanenburg, L

The composition of the example set has a major impact on the quality of neural learning. The popular approach is focused on extensive pre-processing to bridge the representation gap between process measurement and neural presentation. In contrast, windowed active sampling attempts to solve these

PROGRANULIN MUTATIONS AFFECTS BRAIN OSCILLATORY ACTIVITY IN FRONTO-TEMPORAL DEMENTIA

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Davide Vito Moretti

2016-02-01

Full Text Available Background: mild cognitive impairment (MCI is a clinical stage indicating a prodromal phase of dementia. This practical concept could be used also for fronto-temporal dementia (FTD. Progranulin (PGRN has been recently recognized as a useful diagnostic biomarker for fronto-temporal lobe degeneration (FTLD due to GRN null mutations. Electroencephalography (EEG is a reliable tool in detecting brain networks changes. The working hypothesis of the present study is that EEG oscillations could detect different modifications among FTLD stages (FTD-MCI versus overt FTD as well as differences between GRN mutation carriers versus non carriers in patients with overt FTD. Methods: EEG in all patients and PGRN dosage in patients with a clear FTD were detected. The cognitive state has been investigated through mini mental state examination (MMSE. Results: MCI-FTD showed a significant lower spectral power in both alpha and theta oscillations as compared to overt FTD. GRN mutations carriers affected by FTLD show an increase in high alpha and decrease in theta oscillations as compared to non-carriers.Conclusion: EEG frequency rhythms are sensible to different stage of FTD and could detect changes in brain oscillatory activity affected by GRN mutations

Embedding responses in spontaneous neural activity shaped through sequential learning.

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Tomoki Kurikawa

Full Text Available Recent experimental measurements have demonstrated that spontaneous neural activity in the absence of explicit external stimuli has remarkable spatiotemporal structure. This spontaneous activity has also been shown to play a key role in the response to external stimuli. To better understand this role, we proposed a viewpoint, "memories-as-bifurcations," that differs from the traditional "memories-as-attractors" viewpoint. Memory recall from the memories-as-bifurcations viewpoint occurs when the spontaneous neural activity is changed to an appropriate output activity upon application of an input, known as a bifurcation in dynamical systems theory, wherein the input modifies the flow structure of the neural dynamics. Learning, then, is a process that helps create neural dynamical systems such that a target output pattern is generated as an attractor upon a given input. Based on this novel viewpoint, we introduce in this paper an associative memory model with a sequential learning process. Using a simple hebbian-type learning, the model is able to memorize a large number of input/output mappings. The neural dynamics shaped through the learning exhibit different bifurcations to make the requested targets stable upon an increase in the input, and the neural activity in the absence of input shows chaotic dynamics with occasional approaches to the memorized target patterns. These results suggest that these dynamics facilitate the bifurcations to each target attractor upon application of the corresponding input, which thus increases the capacity for learning. This theoretical finding about the behavior of the spontaneous neural activity is consistent with recent experimental observations in which the neural activity without stimuli wanders among patterns evoked by previously applied signals. In addition, the neural networks shaped by learning properly reflect the correlations of input and target-output patterns in a similar manner to those designed in

Synchronization in oscillatory networks

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Osipov, Grigory V; Zhou, Changsong

2007-01-01

The formation of collective behavior in large ensembles or networks of coupled oscillatory elements is one of the oldest and most fundamental aspects of dynamical systems theory. Potential and present applications span a vast spectrum of fields ranging from physics, chemistry, geoscience, through life- and neurosciences to engineering, the economic and the social sciences. This work systematically investigates a large number of oscillatory network configurations that are able to describe many real systems such as electric power grids, lasers or the heart muscle - to name but a few. This book is conceived as an introduction to the field for graduate students in physics and applied mathematics as well as being a compendium for researchers from any field of application interested in quantitative models.

Brain Oscillatory and Hemodynamic Activity in a Bimanual Coordination Task Following Transcranial Alternating Current Stimulation (tACS: A Combined EEG-fNIRS Study

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Alisa Berger

2018-04-01

Full Text Available Motor control is associated with synchronized oscillatory activity at alpha (8–12 Hz and beta (12–30 Hz frequencies in a cerebello-thalamo-cortical network. Previous studies demonstrated that transcranial alternating current stimulation (tACS is capable of entraining ongoing oscillatory activity while also modulating motor control. However, the modulatory effects of tACS on both motor control and its underlying electro- and neurophysiological mechanisms remain ambiguous. Thus, the purpose of this study was to contribute to gathering neurophysiological knowledge regarding tACS effects by investigating the after-effects of 10 Hz tACS and 20 Hz tACS at parietal brain areas on bimanual coordination and its concurrent oscillatory and hemodynamic activity. Twenty-four right-handed healthy volunteers (12 females aged between 18 and 30 (M = 22.35 ± 3.62 participated in the study and performed a coordination task requiring bimanual movements. Concurrent to bimanual motor training, participants received either 10 Hz tACS, 20 Hz tACS or a sham stimulation over the parietal cortex (at P3/P4 electrode positions for 20 min via small gel electrodes (3,14 cm2 Ag/AgCl, amperage = 1 mA. Before and three time-points after tACS (immediately, 30 min and 1 day, bimanual coordination performance was assessed. Oscillatory activities were measured by electroencephalography (EEG and hemodynamic changes were examined using functional near-infrared spectroscopy (fNIRS. Improvements of bimanual coordination performance were not differently between groups, thus, no tACS-specific effect on bimanual coordination performance emerged. However, physiological measures during the task revealed significant increases in parietal alpha activity immediately following 10 Hz tACS and 20 Hz tACS which were accompanied by significant decreases of Hboxy concentration in the right hemispheric motor cortex compared to the sham group. Based on the physiological responses, we conclude that

Brain Oscillatory and Hemodynamic Activity in a Bimanual Coordination Task Following Transcranial Alternating Current Stimulation (tACS): A Combined EEG-fNIRS Study.

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Berger, Alisa; Pixa, Nils H; Steinberg, Fabian; Doppelmayr, Michael

2018-01-01

Motor control is associated with synchronized oscillatory activity at alpha (8-12 Hz) and beta (12-30 Hz) frequencies in a cerebello-thalamo-cortical network. Previous studies demonstrated that transcranial alternating current stimulation (tACS) is capable of entraining ongoing oscillatory activity while also modulating motor control. However, the modulatory effects of tACS on both motor control and its underlying electro- and neurophysiological mechanisms remain ambiguous. Thus, the purpose of this study was to contribute to gathering neurophysiological knowledge regarding tACS effects by investigating the after-effects of 10 Hz tACS and 20 Hz tACS at parietal brain areas on bimanual coordination and its concurrent oscillatory and hemodynamic activity. Twenty-four right-handed healthy volunteers (12 females) aged between 18 and 30 ( M = 22.35 ± 3.62) participated in the study and performed a coordination task requiring bimanual movements. Concurrent to bimanual motor training, participants received either 10 Hz tACS, 20 Hz tACS or a sham stimulation over the parietal cortex (at P3/P4 electrode positions) for 20 min via small gel electrodes (3,14 cm 2 Ag/AgCl, amperage = 1 mA). Before and three time-points after tACS (immediately, 30 min and 1 day), bimanual coordination performance was assessed. Oscillatory activities were measured by electroencephalography (EEG) and hemodynamic changes were examined using functional near-infrared spectroscopy (fNIRS). Improvements of bimanual coordination performance were not differently between groups, thus, no tACS-specific effect on bimanual coordination performance emerged. However, physiological measures during the task revealed significant increases in parietal alpha activity immediately following 10 Hz tACS and 20 Hz tACS which were accompanied by significant decreases of Hboxy concentration in the right hemispheric motor cortex compared to the sham group. Based on the physiological responses, we conclude that t

Study on boiling heat transfer of subcooled flow under oscillatory flow condition

International Nuclear Information System (INIS)

Ohtake, Hiroyasu; Yamazaki, Satoshi; Koizumi, Yasuo

2004-01-01

The Onset of Nucleate Boiling, the point of Net Vapor Generation and Critical Heat Flux on subcooled flow boiling under oscillatory flow, focusing on liquid velocity, amplitude and frequency of oscillatory flow were investigated experimentally and analytically. Experiments were conducted using a copper thin-film and subcooled water in a range of the liquid velocity from 0.27 to 4.07 m/s at 0.10MPa. The liquid subcooling was 20K. Frequency of oscillatory flow was 2 and 4 Hz, respectively; amplitude of oscillatory flow was 25 and 50% in a ratio of main flow rate, respectively. Temperatures at Onset of Nuclear Boiling and Critical Heat Flux obtained in the experiments decreased with the oscillatory flow. The decrease of liquid velocity by oscillatory flow caused the ONB and the CHF to decrease. On the other hand, heat flux at Net Vapor Generation decreased with oscillatory flow; the increase of liquid velocity by oscillatory flow caused the NVG to decrease. (author)

Forced phase-locked states and information retrieval in a two-layer network of oscillatory neurons with directional connectivity

International Nuclear Information System (INIS)

Kazantsev, Victor; Pimashkin, Alexey

2007-01-01

We propose two-layer architecture of associative memory oscillatory network with directional interlayer connectivity. The network is capable to store information in the form of phase-locked (in-phase and antiphase) oscillatory patterns. The first (input) layer takes an input pattern to be recognized and their units are unidirectionally connected with all units of the second (control) layer. The connection strengths are weighted using the Hebbian rule. The output (retrieved) patterns appear as forced-phase locked states of the control layer. The conditions are found and analytically expressed for pattern retrieval in response on incoming stimulus. It is shown that the system is capable to recover patterns with a certain level of distortions or noises in their profiles. The architecture is implemented with the Kuramoto phase model and using synaptically coupled neural oscillators with spikes. It is found that the spiking model is capable to retrieve patterns using the spiking phase that translates memorized patterns into the spiking phase shifts at different time scales

Dynamic Control of Synchronous Activity in Networks of Spiking Neurons.

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Axel Hutt

Full Text Available Oscillatory brain activity is believed to play a central role in neural coding. Accumulating evidence shows that features of these oscillations are highly dynamic: power, frequency and phase fluctuate alongside changes in behavior and task demands. The role and mechanism supporting this variability is however poorly understood. We here analyze a network of recurrently connected spiking neurons with time delay displaying stable synchronous dynamics. Using mean-field and stability analyses, we investigate the influence of dynamic inputs on the frequency of firing rate oscillations. We show that afferent noise, mimicking inputs to the neurons, causes smoothing of the system's response function, displacing equilibria and altering the stability of oscillatory states. Our analysis further shows that these noise-induced changes cause a shift of the peak frequency of synchronous oscillations that scales with input intensity, leading the network towards critical states. We lastly discuss the extension of these principles to periodic stimulation, in which externally applied driving signals can trigger analogous phenomena. Our results reveal one possible mechanism involved in shaping oscillatory activity in the brain and associated control principles.

Dynamic Control of Synchronous Activity in Networks of Spiking Neurons.

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Hutt, Axel; Mierau, Andreas; Lefebvre, Jérémie

Oscillatory brain activity is believed to play a central role in neural coding. Accumulating evidence shows that features of these oscillations are highly dynamic: power, frequency and phase fluctuate alongside changes in behavior and task demands. The role and mechanism supporting this variability is however poorly understood. We here analyze a network of recurrently connected spiking neurons with time delay displaying stable synchronous dynamics. Using mean-field and stability analyses, we investigate the influence of dynamic inputs on the frequency of firing rate oscillations. We show that afferent noise, mimicking inputs to the neurons, causes smoothing of the system's response function, displacing equilibria and altering the stability of oscillatory states. Our analysis further shows that these noise-induced changes cause a shift of the peak frequency of synchronous oscillations that scales with input intensity, leading the network towards critical states. We lastly discuss the extension of these principles to periodic stimulation, in which externally applied driving signals can trigger analogous phenomena. Our results reveal one possible mechanism involved in shaping oscillatory activity in the brain and associated control principles.

Catalyst Initiation in the Oscillatory Carbonylation Reaction

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Katarina Novakovic

2011-01-01

Full Text Available Palladium(II iodide is used as a catalyst in the phenylacetylene oxidative carbonylation reaction that has demonstrated oscillatory behaviour in both pH and heat of reaction. In an attempt to extract the reaction network responsible for the oscillatory nature of this reaction, the system was divided into smaller parts and they were studied. This paper focuses on understanding the reaction network responsible for the initial reactions of palladium(II iodide within this oscillatory reaction. The species researched include methanol, palladium(II iodide, potassium iodide, and carbon monoxide. Several chemical reactions were considered and applied in a modelling study. The study revealed the significant role played by traces of water contained in the standard HPLC grade methanol used.

Design principles for robust oscillatory behavior.

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Castillo-Hair, Sebastian M; Villota, Elizabeth R; Coronado, Alberto M

2015-09-01

Oscillatory responses are ubiquitous in regulatory networks of living organisms, a fact that has led to extensive efforts to study and replicate the circuits involved. However, to date, design principles that underlie the robustness of natural oscillators are not completely known. Here we study a three-component enzymatic network model in order to determine the topological requirements for robust oscillation. First, by simulating every possible topological arrangement and varying their parameter values, we demonstrate that robust oscillators can be obtained by augmenting the number of both negative feedback loops and positive autoregulations while maintaining an appropriate balance of positive and negative interactions. We then identify network motifs, whose presence in more complex topologies is a necessary condition for obtaining oscillatory responses. Finally, we pinpoint a series of simple architectural patterns that progressively render more robust oscillators. Together, these findings can help in the design of more reliable synthetic biomolecular networks and may also have implications in the understanding of other oscillatory systems.

The Involvement of Endogenous Neural Oscillations in the Processing of Rhythmic Input: More Than a Regular Repetition of Evoked Neural Responses

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Zoefel, Benedikt; ten Oever, Sanne; Sack, Alexander T.

2018-01-01

It is undisputed that presenting a rhythmic stimulus leads to a measurable brain response that follows the rhythmic structure of this stimulus. What is still debated, however, is the question whether this brain response exclusively reflects a regular repetition of evoked responses, or whether it also includes entrained oscillatory activity. Here we systematically present evidence in favor of an involvement of entrained neural oscillations in the processing of rhythmic input while critically pointing out which questions still need to be addressed before this evidence could be considered conclusive. In this context, we also explicitly discuss the potential functional role of such entrained oscillations, suggesting that these stimulus-aligned oscillations reflect, and serve as, predictive processes, an idea often only implicitly assumed in the literature. PMID:29563860

Shadows of Music-Language Interaction on Low Frequency Brain Oscillatory Patterns

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Carrus, Elisa; Koelsch, Stefan; Bhattacharya, Joydeep

2011-01-01

Electrophysiological studies investigating similarities between music and language perception have relied exclusively on the signal averaging technique, which does not adequately represent oscillatory aspects of electrical brain activity that are relevant for higher cognition. The current study investigated the patterns of brain oscillations…

Cross-modal integration of lexical-semantic features during word processing: evidence from oscillatory dynamics during EEG.

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Markus J van Ackeren

Full Text Available In recent years, numerous studies have provided converging evidence that word meaning is partially stored in modality-specific cortical networks. However, little is known about the mechanisms supporting the integration of this distributed semantic content into coherent conceptual representations. In the current study we aimed to address this issue by using EEG to look at the spatial and temporal dynamics of feature integration during word comprehension. Specifically, participants were presented with two modality-specific features (i.e., visual or auditory features such as silver and loud and asked to verify whether these two features were compatible with a subsequently presented target word (e.g., WHISTLE. Each pair of features described properties from either the same modality (e.g., silver, tiny  =  visual features or different modalities (e.g., silver, loud  =  visual, auditory. Behavioral and EEG data were collected. The results show that verifying features that are putatively represented in the same modality-specific network is faster than verifying features across modalities. At the neural level, integrating features across modalities induces sustained oscillatory activity around the theta range (4-6 Hz in left anterior temporal lobe (ATL, a putative hub for integrating distributed semantic content. In addition, enhanced long-range network interactions in the theta range were seen between left ATL and a widespread cortical network. These results suggest that oscillatory dynamics in the theta range could be involved in integrating multimodal semantic content by creating transient functional networks linking distributed modality-specific networks and multimodal semantic hubs such as left ATL.

EEG-fMRI Bayesian framework for neural activity estimation: a simulation study

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Croce, Pierpaolo; Basti, Alessio; Marzetti, Laura; Zappasodi, Filippo; Del Gratta, Cosimo

2016-12-01

Objective. Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework. Approach. We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF). Main results. First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements. Significance. The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.

Internal mechanisms underlying anticipatory language processing: Evidence from event-related-potentials and neural oscillations.

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Li, Xiaoqing; Zhang, Yuping; Xia, Jinyan; Swaab, Tamara Y

2017-07-28

Although numerous studies have demonstrated that the language processing system can predict upcoming content during comprehension, there is still no clear picture of the anticipatory stage of predictive processing. This electroencephalograph study examined the cognitive and neural oscillatory mechanisms underlying anticipatory processing during language comprehension, and the consequences of this prediction for bottom-up processing of predicted/unpredicted content. Participants read Mandarin Chinese sentences that were either strongly or weakly constraining and that contained critical nouns that were congruent or incongruent with the sentence contexts. We examined the effects of semantic predictability on anticipatory processing prior to the onset of the critical nouns and on integration of the critical nouns. The results revealed that, at the integration stage, the strong-constraint condition (compared to the weak-constraint condition) elicited a reduced N400 and reduced theta activity (4-7Hz) for the congruent nouns, but induced beta (13-18Hz) and theta (4-7Hz) power decreases for the incongruent nouns, indicating benefits of confirmed predictions and potential costs of disconfirmed predictions. More importantly, at the anticipatory stage, the strongly constraining context elicited an enhanced sustained anterior negativity and beta power decrease (19-25Hz), which indicates that strong prediction places a higher processing load on the anticipatory stage of processing. The differences (in the ease of processing and the underlying neural oscillatory activities) between anticipatory and integration stages of lexical processing were discussed with regard to predictive processing models. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Effects of GABAergic Polarity Changes on Episodic Neural Network Activity in Developing Neural Systems

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Wilfredo Blanco

2017-09-01

Full Text Available Early in development, neural systems have primarily excitatory coupling, where even GABAergic synapses are excitatory. Many of these systems exhibit spontaneous episodes of activity that have been characterized through both experimental and computational studies. As development progress the neural system goes through many changes, including synaptic remodeling, intrinsic plasticity in the ion channel expression, and a transformation of GABAergic synapses from excitatory to inhibitory. What effect each of these, and other, changes have on the network behavior is hard to know from experimental studies since they all happen in parallel. One advantage of a computational approach is that one has the ability to study developmental changes in isolation. Here, we examine the effects of GABAergic synapse polarity change on the spontaneous activity of both a mean field and a neural network model that has both glutamatergic and GABAergic coupling, representative of a developing neural network. We find some intuitive behavioral changes as the GABAergic neurons go from excitatory to inhibitory, shared by both models, such as a decrease in the duration of episodes. We also find some paradoxical changes in the activity that are only present in the neural network model. In particular, we find that during early development the inter-episode durations become longer on average, while later in development they become shorter. In addressing this unexpected finding, we uncover a priming effect that is particularly important for a small subset of neurons, called the “intermediate neurons.” We characterize these neurons and demonstrate why they are crucial to episode initiation, and why the paradoxical behavioral change result from priming of these neurons. The study illustrates how even arguably the simplest of developmental changes that occurs in neural systems can present non-intuitive behaviors. It also makes predictions about neural network behavioral changes

Neural Activity Patterns in the Human Brain Reflect Tactile Stickiness Perception

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Kim, Junsuk; Yeon, Jiwon; Ryu, Jaekyun; Park, Jang-Yeon; Chung, Soon-Cheol; Kim, Sung-Phil

2017-01-01

Our previous human fMRI study found brain activations correlated with tactile stickiness perception using the uni-variate general linear model (GLM) (Yeon et al., 2017). Here, we conducted an in-depth investigation on neural correlates of sticky sensations by employing a multivoxel pattern analysis (MVPA) on the same dataset. In particular, we statistically compared multi-variate neural activities in response to the three groups of sticky stimuli: A supra-threshold group including a set of sticky stimuli that evoked vivid sticky perception; an infra-threshold group including another set of sticky stimuli that barely evoked sticky perception; and a sham group including acrylic stimuli with no physically sticky property. Searchlight MVPAs were performed to search for local activity patterns carrying neural information of stickiness perception. Similar to the uni-variate GLM results, significant multi-variate neural activity patterns were identified in postcentral gyrus, subcortical (basal ganglia and thalamus), and insula areas (insula and adjacent areas). Moreover, MVPAs revealed that activity patterns in posterior parietal cortex discriminated the perceptual intensities of stickiness, which was not present in the uni-variate analysis. Next, we applied a principal component analysis (PCA) to the voxel response patterns within identified clusters so as to find low-dimensional neural representations of stickiness intensities. Follow-up clustering analyses clearly showed separate neural grouping configurations between the Supra- and Infra-threshold groups. Interestingly, this neural categorization was in line with the perceptual grouping pattern obtained from the psychophysical data. Our findings thus suggest that different stickiness intensities would elicit distinct neural activity patterns in the human brain and may provide a neural basis for the perception and categorization of tactile stickiness. PMID:28936171

Fast neutron spectra determination by threshold activation detectors using neural networks

International Nuclear Information System (INIS)

Kardan, M.R.; Koohi-Fayegh, R.; Setayeshi, S.; Ghiassi-Nejad, M.

2004-01-01

Neural network method was used for fast neutron spectra unfolding in spectrometry by threshold activation detectors. The input layer of the neural networks consisted of 11 neurons for the specific activities of neutron-induced nuclear reaction products, while the output layers were fast neutron spectra which had been subdivided into 6, 8, 10, 12, 15 and 20 energy bins. Neural network training was performed by 437 fast neutron spectra and corresponding threshold activation detector readings. The trained neural network have been applied for unfolding 50 spectra, which were not in training sets and the results were compared with real spectra and unfolded spectra by SANDII. The best results belong to 10 energy bin spectra. The neural network was also trained by detector readings with 5% uncertainty and the response of the trained neural network to detector readings with 5%, 10%, 15%, 20%, 25% and 50% uncertainty was compared with real spectra. Neural network algorithm, in comparison with other unfolding methods, is very fast and needless to detector response matrix and any prior information about spectra and also the outputs have low sensitivity to uncertainty in the activity measurements. The results show that the neural network algorithm is useful when a fast response is required with reasonable accuracy

Biological oscillations for learning walking coordination: dynamic recurrent neural network functionally models physiological central pattern generator.

Science.gov (United States)

Hoellinger, Thomas; Petieau, Mathieu; Duvinage, Matthieu; Castermans, Thierry; Seetharaman, Karthik; Cebolla, Ana-Maria; Bengoetxea, Ana; Ivanenko, Yuri; Dan, Bernard; Cheron, Guy

2013-01-01

The existence of dedicated neuronal modules such as those organized in the cerebral cortex, thalamus, basal ganglia, cerebellum, or spinal cord raises the question of how these functional modules are coordinated for appropriate motor behavior. Study of human locomotion offers an interesting field for addressing this central question. The coordination of the elevation of the 3 leg segments under a planar covariation rule (Borghese et al., 1996) was recently modeled (Barliya et al., 2009) by phase-adjusted simple oscillators shedding new light on the understanding of the central pattern generator (CPG) processing relevant oscillation signals. We describe the use of a dynamic recurrent neural network (DRNN) mimicking the natural oscillatory behavior of human locomotion for reproducing the planar covariation rule in both legs at different walking speeds. Neural network learning was based on sinusoid signals integrating frequency and amplitude features of the first three harmonics of the sagittal elevation angles of the thigh, shank, and foot of each lower limb. We verified the biological plausibility of the neural networks. Best results were obtained with oscillations extracted from the first three harmonics in comparison to oscillations outside the harmonic frequency peaks. Physiological replication steadily increased with the number of neuronal units from 1 to 80, where similarity index reached 0.99. Analysis of synaptic weighting showed that the proportion of inhibitory connections consistently increased with the number of neuronal units in the DRNN. This emerging property in the artificial neural networks resonates with recent advances in neurophysiology of inhibitory neurons that are involved in central nervous system oscillatory activities. The main message of this study is that this type of DRNN may offer a useful model of physiological central pattern generator for gaining insights in basic research and developing clinical applications.

Noise measurements during high-frequency oscillatory and conventional mechanical ventilation.

Science.gov (United States)

Berens, R J; Weigle, C G

1995-10-01

To evaluate the noise levels with high-frequency oscillatory ventilation and conventional mechanical ventilation. An observational, prospective study. Pediatric intensive care unit. The caretakers and environment of the pediatric intensive care unit. High-frequency oscillatory and conventional mechanical ventilation. Caretakers evaluated noise using a visual analog scale. Noise was measured with a decibel meter and an octave band frequency filter. There was twice as much noise perceived by the caretakers and as measured on the decibel A scale. All measures showed significantly greater noise, especially at low frequencies, with high-frequency oscillatory ventilation. High-frequency oscillatory ventilation exposes the patient to twice as much noise as does the use of conventional mechanical ventilation.

Strobes: An oscillatory combustion

NARCIS (Netherlands)

Corbel, J.M.L.; Lingen, J.N.J. van; Zevenbergen, J.F.; Gijzeman, O.L.J.; Meijerink, A.

2012-01-01

Strobe compositions belong to the class of solid combustions. They are mixtures of powdered ingredients. When ignited, the combustion front evolves in an oscillatory fashion, and flashes of light are produced by intermittence. They have fascinated many scientists since their discovery at the

The role of oscillatory brain activity in object processing and figure-ground segmentation in human vision.

Science.gov (United States)

Kinsey, K; Anderson, S J; Hadjipapas, A; Holliday, I E

2011-03-01

The perception of an object as a single entity within a visual scene requires that its features are bound together and segregated from the background and/or other objects. Here, we used magnetoencephalography (MEG) to assess the hypothesis that coherent percepts may arise from the synchronized high frequency (gamma) activity between neurons that code features of the same object. We also assessed the role of low frequency (alpha, beta) activity in object processing. The target stimulus (i.e. object) was a small patch of a concentric grating of 3c/°, viewed eccentrically. The background stimulus was either a blank field or a concentric grating of 3c/° periodicity, viewed centrally. With patterned backgrounds, the target stimulus emerged--through rotation about its own centre--as a circular subsection of the background. Data were acquired using a 275-channel whole-head MEG system and analyzed using Synthetic Aperture Magnetometry (SAM), which allows one to generate images of task-related cortical oscillatory power changes within specific frequency bands. Significant oscillatory activity across a broad range of frequencies was evident at the V1/V2 border, and subsequent analyses were based on a virtual electrode at this location. When the target was presented in isolation, we observed that: (i) contralateral stimulation yielded a sustained power increase in gamma activity; and (ii) both contra- and ipsilateral stimulation yielded near identical transient power changes in alpha (and beta) activity. When the target was presented against a patterned background, we observed that: (i) contralateral stimulation yielded an increase in high-gamma (>55 Hz) power together with a decrease in low-gamma (40-55 Hz) power; and (ii) both contra- and ipsilateral stimulation yielded a transient decrease in alpha (and beta) activity, though the reduction tended to be greatest for contralateral stimulation. The opposing power changes across different regions of the gamma spectrum with

LES-based characterization of a suction and oscillatory blowing fluidic actuator

Science.gov (United States)

Kim, Jeonglae; Moin, Parviz

2015-11-01

Recently, a novel fluidic actuator using steady suction and oscillatory blowing was developed for control of turbulent flows. The suction and oscillatory blowing (SaOB) actuator combines steady suction and pulsed oscillatory blowing into a single device. The actuation is based upon a self-sustained mechanism of confined jets and does not require any moving parts. The control output is determined by a pressure source and the geometric details, and no additional input is needed. While its basic mechanisms have been investigated to some extent, detailed characteristics of internal turbulent flows are not well understood. In this study, internal flows of the SaOB actuator are simulated using large-eddy simulation (LES). Flow characteristics within the actuator are described in detail for a better understanding of the physical mechanisms and improving the actuator design. LES predicts the self-sustained oscillations of the turbulent jet. Switching frequency, maximum velocity at the actuator outlets, and wall pressure distribution are in good agreement with the experimental measurements. The computational results are used to develop simplified boundary conditions for numerical experiments of active flow control. Supported by the Boeing company.

Kinetic insights over a PEMFC operating on stationary and oscillatory states.

Science.gov (United States)

Mota, Andressa; Gonzalez, Ernesto R; Eiswirth, Markus

2011-12-01

Kinetic investigations in the oscillatory state have been carried out in order to shed light on the interplay between the complex kinetics exhibited by a proton exchange membrane fuel cell fed with poisoned H(2) (108 ppm of CO) and the other in serie process. The apparent activation energy (E(a)) in the stationary state was investigated in order to clarify the E(a) observed in the oscillatory state. The apparent activation energy in the stationary state, under potentiostatic control, rendered (a) E(a) ≈ 50-60 kJ mol(-1) over 0.8 V < E < 0.6 V and (b) E(a) ≈ 10 kJ mol(-1) at E = 0.3 V. The former is related to the H(2) adsorption in the vacancies of the surface poisoned by CO and the latter is correlated to the process of proton conductivity in the membrane. The dependence of the period-one oscillations on the temperature yielded a genuine Arrhenius dependence with two E(a) values: (a) E(a) around 70 kJ mol(-1), at high temperatures, and (b) E(a) around 10-15 kJ mol(-1), at lower temperatures. The latter E(a) indicates the presence of protonic mass transport coupled to the essential oscillatory mechanism. These insights point in the right direction to predict spatial couplings between anode and cathode as having the highest strength as well as to speculate the most likely candidates to promote spatial inhomogeneities. © 2011 American Chemical Society

Disk partition function and oscillatory rolling tachyons

International Nuclear Information System (INIS)

Jokela, Niko; Jaervinen, Matti; Keski-Vakkuri, Esko; Majumder, Jaydeep

2008-01-01

An exact cubic open string field theory rolling tachyon solution was recently found by Kiermaier et al and Schnabl. This oscillatory solution has been argued to be related by a field redefinition to the simple exponential rolling tachyon deformation of boundary conformal theory. In the latter approach, the disk partition function takes a simple form. Out of curiosity, we compute the disk partition function for an oscillatory tachyon profile, and find that the result is nevertheless almost the same

Characterization of Oscillatory Lift in MFC Airfoils

OpenAIRE

Lang Jr, Joseph Reagle

2014-01-01

The purpose of this research is to characterize the response of an airfoil with an oscillatory morphing, Macro-fiber composite (MFC) trailing edge. Correlation of the airfoil lift with the oscillatory input is presented. Modal analysis of the test airfoil and apparatus is used to determine the frequency response function. The effects of static MFC inputs on the FRF are presented and compared to the unactuated airfoil. The transfer function is then used to determine the lift component du...

What basal ganglia changes underlie the parkinsonian state? The significance of neuronal oscillatory activity

Science.gov (United States)

Quiroga-Varela, A.; Walters, J.R.; Brazhnik, E.; Marin, C.; Obeso, J.A.

2014-01-01

One well accepted functional feature of the parkinsonian state is the recording of enhanced beta oscillatory activity in the basal ganglia. This has been demonstrated in patients with Parkinson's disease (PD) and in animal models such as the rat with 6-hydroxydopamine (6-OHDA)-induced lesion and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated monkeys, all of which are associated with severe striatal dopamine depletion. Neuronal hyper-synchronization in the beta (or any other) band is not present despite the presence of bradykinetic features in the rat and monkey models, suggesting that increased beta band power may arise when nigro-striatal lesion is advanced and that it is not an essential feature of the early parkinsonian state. Similar observations and conclusions have been previously made for increased neuronal firing rate in the subthalamic and globus pallidus pars interna nuclei. Accordingly, it is suggested that early parkinsonism may be associated with dynamic changes in basal ganglia output activity leading to reduced movement facilitation that may be an earlier feature of the parkinsonian state. PMID:23727447

Cellular and oscillatory substrates of fear extinction learning.

Science.gov (United States)

Davis, Patrick; Zaki, Yosif; Maguire, Jamie; Reijmers, Leon G

2017-11-01

The mammalian brain contains dedicated circuits for both the learned expression and suppression of fear. These circuits require precise coordination to facilitate the appropriate expression of fear behavior, but the mechanisms underlying this coordination remain unclear. Using a combination of chemogenetics, activity-based neuronal-ensemble labeling and in vivo electrophysiology, we found that fear extinction learning confers on parvalbumin-expressing (PV) interneurons in the basolateral amygdala (BLA) a dedicated role in the selective suppression of a previously encoded fear memory and BLA fear-encoding neurons. In addition, following extinction learning, PV interneurons enable a competing interaction between a 6-12 Hz oscillation and a fear-associated 3-6 Hz oscillation within the BLA. Loss of this competition increases a 3-6 Hz oscillatory signature, with BLA→medial prefrontal cortex directionality signaling the recurrence of fear expression. The discovery of cellular and oscillatory substrates of fear extinction learning that critically depend on BLA PV interneurons could inform therapies aimed at preventing the pathological recurrence of fear following extinction learning.

Visual food stimulus changes resting oscillatory brain activities related to appetitive motive.

Science.gov (United States)

Yoshikawa, Takahiro; Tanaka, Masaaki; Ishii, Akira; Yamano, Yoko; Watanabe, Yasuyoshi

2016-09-26

Changes of resting brain activities after visual food stimulation might affect the feeling of pleasure in eating food in daily life and spontaneous appetitive motives. We used magnetoencephalography (MEG) to identify brain areas related to the activity changes. Fifteen healthy, right-handed males [age, 25.4 ± 5.5 years; body mass index, 22.5 ± 2.7 kg/m 2 (mean ± SD)] were enrolled. They were asked to watch food or mosaic pictures for 5 min and to close their eyes for 3 min before and after the picture presentation without thinking of anything. Resting brain activities were recorded during two eye-closed sessions. The feeling of pleasure in eating food in daily life and appetitive motives in the study setting were assessed by visual analogue scale (VAS) scores. The γ-band power of resting oscillatory brain activities was decreased after the food picture presentation in the right insula [Brodmann's area (BA) 13], the left orbitofrontal cortex (OFC) (BA11), and the left frontal pole (BA10). Significant reductions of the α-band power were observed in the dorsolateral prefrontal cortex (DLPFC) (BA46). Particularly, the feeling of pleasure in eating food was positively correlated with the power decrease in the insula and negatively with that in the DLPFC. The changes in appetitive motives were associated with the power decrease in the frontal pole. These findings suggest automatic brain mechanics whereby changes of the resting brain activity might be associated with positive feeling in dietary life and have an impact on the irresistible appetitive motives through emotional and cognitive brain functions.

Forecasting Flare Activity Using Deep Convolutional Neural Networks

Science.gov (United States)

Hernandez, T.

2017-12-01

Current operational flare forecasting relies on human morphological analysis of active regions and the persistence of solar flare activity through time (i.e. that the Sun will continue to do what it is doing right now: flaring or remaining calm). In this talk we present the results of applying deep Convolutional Neural Networks (CNNs) to the problem of solar flare forecasting. CNNs operate by training a set of tunable spatial filters that, in combination with neural layer interconnectivity, allow CNNs to automatically identify significant spatial structures predictive for classification and regression problems. We will start by discussing the applicability and success rate of the approach, the advantages it has over non-automated forecasts, and how mining our trained neural network provides a fresh look into the mechanisms behind magnetic energy storage and release.

Neural activation toward erotic stimuli in homosexual and heterosexual males.

Science.gov (United States)

Kagerer, Sabine; Klucken, Tim; Wehrum, Sina; Zimmermann, Mark; Schienle, Anne; Walter, Bertram; Vaitl, Dieter; Stark, Rudolf

2011-11-01

Studies investigating sexual arousal exist, yet there are diverging findings on the underlying neural mechanisms with regard to sexual orientation. Moreover, sexual arousal effects have often been confounded with general arousal effects. Hence, it is still unclear which structures underlie the sexual arousal response in homosexual and heterosexual men. Neural activity and subjective responses were investigated in order to disentangle sexual from general arousal. Considering sexual orientation, differential and conjoint neural activations were of interest. The functional magnetic resonance imaging (fMRI) study focused on the neural networks involved in the processing of sexual stimuli in 21 male participants (11 homosexual, 10 heterosexual). Both groups viewed pictures with erotic content as well as aversive and neutral stimuli. The erotic pictures were subdivided into three categories (most sexually arousing, least sexually arousing, and rest) based on the individual subjective ratings of each participant. Blood oxygen level-dependent responses measured by fMRI and subjective ratings. A conjunction analysis revealed conjoint neural activation related to sexual arousal in thalamus, hypothalamus, occipital cortex, and nucleus accumbens. Increased insula, amygdala, and anterior cingulate gyrus activation could be linked to general arousal. Group differences emerged neither when viewing the most sexually arousing pictures compared with highly arousing aversive pictures nor compared with neutral pictures. Results suggest that a widespread neural network is activated by highly sexually arousing visual stimuli. A partly distinct network of structures underlies sexual and general arousal effects. The processing of preferred, highly sexually arousing stimuli recruited similar structures in homosexual and heterosexual males. © 2011 International Society for Sexual Medicine.

Low frequency oscillatory flow in a rotating curved pipe

Institute of Scientific and Technical Information of China (English)

陈华军; 章本照; 苏霄燕

2003-01-01

The low frequency oscillatory flow in a rotating curved pipe was studied by using the method of bi-parameter perturbation. Perturbation solutions up to the second order were obtained and the effects of rotationon the low frequency oscillatory flow were examined in detail, The results indicated that there exists evident difference between the low frequency oscillatory flow in a rotating curved pipe and in a curved pipe without ro-tation. During a period, four secondary vortexes may exist on the circular cross-section and the distribution of axial velocity and wall shear stress are related to the ratio of the Coriolis foree to centrifugal foree and the axial pressure gradient.

Low frequency oscillatory flow in a rotating curved pipe

Institute of Scientific and Technical Information of China (English)

陈华军; 章本照; 苏霄燕

2003-01-01

The low frequency oscillatory flow in a rotating curved pipe was studied by using the method of bi-parameter perturbation. Perturbation solutions up to the second order were obtained and the effects of rotation on the low frequency oscillatory flow were examined in detail. The results indicated that there exists evident difference between the low frequency oscillatory flow in a rotating curved pipe and in a curved pipe without rotation. During a period, four secondary vortexes may exist on the circular cross-section and the distribution of axial velocity and wall shear stress are related to the ratio of the Coriolis force to centrifugal force and the axial pressure gradient.

Activity in part of the neural correlates of consciousness reflects integration.

Science.gov (United States)

Eriksson, Johan

2017-10-01

Integration is commonly viewed as a key process for generating conscious experiences. Accordingly, there should be increased activity within the neural correlates of consciousness when demands on integration increase. We used fMRI and "informational masking" to isolate the neural correlates of consciousness and measured how the associated brain activity changed as a function of required integration. Integration was manipulated by comparing the experience of hearing simple reoccurring tones to hearing harmonic tone triplets. The neural correlates of auditory consciousness included superior temporal gyrus, lateral and medial frontal regions, cerebellum, and also parietal cortex. Critically, only activity in left parietal cortex increased significantly as a function of increasing demands on integration. We conclude that integration can explain part of the neural activity associated with the generation conscious experiences, but that much of associated brain activity apparently reflects other processes. Copyright © 2017 Elsevier Inc. All rights reserved.

Delay selection by spike-timing-dependent plasticity in recurrent networks of spiking neurons receiving oscillatory inputs.

Directory of Open Access Journals (Sweden)

Robert R Kerr

Full Text Available Learning rules, such as spike-timing-dependent plasticity (STDP, change the structure of networks of neurons based on the firing activity. A network level understanding of these mechanisms can help infer how the brain learns patterns and processes information. Previous studies have shown that STDP selectively potentiates feed-forward connections that have specific axonal delays, and that this underlies behavioral functions such as sound localization in the auditory brainstem of the barn owl. In this study, we investigate how STDP leads to the selective potentiation of recurrent connections with different axonal and dendritic delays during oscillatory activity. We develop analytical models of learning with additive STDP in recurrent networks driven by oscillatory inputs, and support the results using simulations with leaky integrate-and-fire neurons. Our results show selective potentiation of connections with specific axonal delays, which depended on the input frequency. In addition, we demonstrate how this can lead to a network becoming selective in the amplitude of its oscillatory response to this frequency. We extend this model of axonal delay selection within a single recurrent network in two ways. First, we show the selective potentiation of connections with a range of both axonal and dendritic delays. Second, we show axonal delay selection between multiple groups receiving out-of-phase, oscillatory inputs. We discuss the application of these models to the formation and activation of neuronal ensembles or cell assemblies in the cortex, and also to missing fundamental pitch perception in the auditory brainstem.

An Activity for Demonstrating the Concept of a Neural Circuit

Science.gov (United States)

Kreiner, David S.

2012-01-01

College students in two sections of a general psychology course participated in a demonstration of a simple neural circuit. The activity was based on a neural circuit that Jeffress proposed for localizing sounds. Students in one section responded to a questionnaire prior to participating in the activity, while students in the other section…

SPR imaging combined with cyclic voltammetry for the detection of neural activity

Directory of Open Access Journals (Sweden)

Hui Li

2014-03-01

Full Text Available Surface plasmon resonance (SPR detects changes in refractive index at a metal-dielectric interface. In this study, SPR imaging (SPRi combined with cyclic voltammetry (CV was applied to detect neural activity in isolated bullfrog sciatic nerves. The neural activities induced by chemical and electrical stimulation led to an SPR response, and the activities were recorded in real time. The activities of different parts of the sciatic nerve were recorded and compared. The results demonstrated that SPR imaging combined with CV is a powerful tool for the investigation of neural activity.

Oscillatory EEG correlates of arithmetic strategies: A training study

Directory of Open Access Journals (Sweden)

Roland H. Grabner

2012-10-01

Full Text Available There has been a long tradition of research on mathematics education showing that children and adults use different strategies to solve arithmetic problems. Neurophysiological studies have recently begun to investigate the brain correlates of these strategies. The existing body of data, however, reflect static end points of the learning process and do not provide information on how brain activity changes in response to training or intervention. In this study, we explicitly address this issue by training participants in using fact retrieval strategies. We also investigate whether brain activity related to arithmetic fact learning is domain-specific or whether this generalizes to other learning materials, such as the solution of figural-spatial problems. Twenty adult students were trained on sets of two-digit multiplication problems and figural-spatial problems. After the training, they were presented with the trained and untrained problems while their brain activity was recorded by means of electroencephalography (EEG . In both problem types, the training resulted in accuracies over 90 % and significant decreases in solution times. Analyses of the oscillatory EEG data also revealed training effects across both problem types. Specifically, we observed training-related activity increases in the theta band (3-6 Hz and decreases in the lower alpha band (8-10 Hz, especially over parieto-occipital and parietal brain regions. These results provide the first evidence that a short term fact retrieval training results in significant changes in oscillatory EEG activity. These findings further corroborate the role of the theta band in the retrieval of semantic information from memory and suggest that theta activity is not only sensitive to fact retrieval in mental arithmetic but also in other domains.

Oscillatory brain correlates of live joint attention: a dual-EEG study

Directory of Open Access Journals (Sweden)

Fanny eLachat

2012-06-01

Full Text Available Joint attention consists in following another’s gaze onto an environmental object, which leads to the alignment of both subjects' attention onto this object. It is a fundamental mechanism of non-verbal communication, and it is essential for dynamic, online, interindividual synchronization during interactions. We aimed at investigating the oscillatory brain correlates of joint attention in a face-to-face paradigm where dyads of participants dynamically oriented their attention toward objects during joint and no-joint attention periods respectively. We also manipulated task instruction: in socially-driven instructions, the participants had to follow explicitly their partner’s gaze, while in color-driven instructions, the objects to be looked at were designated at by their color so that no explicit gaze following was required. We focused on oscillatory activities in the 10 Hz frequency range, where parieto-occipital alpha and the centro-parietal mu rhythms have been described, as these rhythms have been associated with attention and social coordination processes respectively. We tested the hypothesis of a modulation of these oscillatory activities by joint attention. We used dual EEG to record simultaneously the brain activities of the participant dyads during our live, face-to-face joint attention paradigm. We showed that joint attention periods – as compared to the no-joint attention periods – were associated with a decrease of signal power between 11 and 13 Hz over a large set of left centro-parieto-occipital electrodes, encompassing the scalp regions where alpha and mu rhythms have been described. This 11-13 Hz signal power decrease was observed independently of the task instruction: it was similar when joint versus no-joint attention situations were socially-driven and when they were color-driven. These results are interpreted in terms of the processes of attention mirroring, social coordination, and mutual attentiveness associated

State-dependent, bidirectional modulation of neural network activity by endocannabinoids.

Science.gov (United States)

Piet, Richard; Garenne, André; Farrugia, Fanny; Le Masson, Gwendal; Marsicano, Giovanni; Chavis, Pascale; Manzoni, Olivier J

2011-11-16

The endocannabinoid (eCB) system and the cannabinoid CB1 receptor (CB1R) play key roles in the modulation of brain functions. Although actions of eCBs and CB1Rs are well described at the synaptic level, little is known of their modulation of neural activity at the network level. Using microelectrode arrays, we have examined the role of CB1R activation in the modulation of the electrical activity of rat and mice cortical neural networks in vitro. We find that exogenous activation of CB1Rs expressed on glutamatergic neurons decreases the spontaneous activity of cortical neural networks. Moreover, we observe that the net effect of the CB1R antagonist AM251 inversely correlates with the initial level of activity in the network: blocking CB1Rs increases network activity when basal network activity is low, whereas it depresses spontaneous activity when its initial level is high. Our results reveal a complex role of CB1Rs in shaping spontaneous network activity, and suggest that the outcome of endogenous neuromodulation on network function might be state dependent.

Cultured Neural Networks: Optimization of Patterned Network Adhesiveness and Characterization of their Neural Activity

Directory of Open Access Journals (Sweden)

W. L. C. Rutten

2006-01-01

Full Text Available One type of future, improved neural interface is the “cultured probe”. It is a hybrid type of neural information transducer or prosthesis, for stimulation and/or recording of neural activity. It would consist of a microelectrode array (MEA on a planar substrate, each electrode being covered and surrounded by a local circularly confined network (“island” of cultured neurons. The main purpose of the local networks is that they act as biofriendly intermediates for collateral sprouts from the in vivo system, thus allowing for an effective and selective neuron–electrode interface. As a secondary purpose, one may envisage future information processing applications of these intermediary networks. In this paper, first, progress is shown on how substrates can be chemically modified to confine developing networks, cultured from dissociated rat cortex cells, to “islands” surrounding an electrode site. Additional coating of neurophobic, polyimide-coated substrate by triblock-copolymer coating enhances neurophilic-neurophobic adhesion contrast. Secondly, results are given on neuronal activity in patterned, unconnected and connected, circular “island” networks. For connected islands, the larger the island diameter (50, 100 or 150 μm, the more spontaneous activity is seen. Also, activity may show a very high degree of synchronization between two islands. For unconnected islands, activity may start at 22 days in vitro (DIV, which is two weeks later than in unpatterned networks.

Assessment of oscillatory stability constrained available transfer capability

International Nuclear Information System (INIS)

Jain, T.; Singh, S.N.; Srivastava, S.C.

2009-01-01

This paper utilizes a bifurcation approach to compute oscillatory stability constrained available transfer capability (ATC) in an electricity market having bilateral as well as multilateral transactions. Oscillatory instability in non-linear systems can be related to Hopf bifurcation. At the Hopf bifurcation, one pair of the critical eigenvalues of the system Jacobian reaches imaginary axis. A new optimization formulation, including Hopf bifurcation conditions, has been developed in this paper to obtain the dynamic ATC. An oscillatory stability based contingency screening index, which takes into account the impact of transactions on severity of contingency, has been utilized to identify critical contingencies to be considered in determining ATC. The proposed method has been applied for dynamic ATC determination on a 39-bus New England system and a practical 75-bus Indian system considering composite static load as well as dynamic load models. (author)

Decoding magnetoencephalographic rhythmic activity using spectrospatial information.

Science.gov (United States)

Kauppi, Jukka-Pekka; Parkkonen, Lauri; Hari, Riitta; Hyvärinen, Aapo

2013-12-01

We propose a new data-driven decoding method called Spectral Linear Discriminant Analysis (Spectral LDA) for the analysis of magnetoencephalography (MEG). The method allows investigation of changes in rhythmic neural activity as a result of different stimuli and tasks. The introduced classification model only assumes that each "brain state" can be characterized as a combination of neural sources, each of which shows rhythmic activity at one or several frequency bands. Furthermore, the model allows the oscillation frequencies to be different for each such state. We present decoding results from 9 subjects in a four-category classification problem defined by an experiment involving randomly alternating epochs of auditory, visual and tactile stimuli interspersed with rest periods. The performance of Spectral LDA was very competitive compared with four alternative classifiers based on different assumptions concerning the organization of rhythmic brain activity. In addition, the spectral and spatial patterns extracted automatically on the basis of trained classifiers showed that Spectral LDA offers a novel and interesting way of analyzing spectrospatial oscillatory neural activity across the brain. All the presented classification methods and visualization tools are freely available as a Matlab toolbox. © 2013.

Active Engine Mounting Control Algorithm Using Neural Network

Directory of Open Access Journals (Sweden)

Fadly Jashi Darsivan

2009-01-01

Full Text Available This paper proposes the application of neural network as a controller to isolate engine vibration in an active engine mounting system. It has been shown that the NARMA-L2 neurocontroller has the ability to reject disturbances from a plant. The disturbance is assumed to be both impulse and sinusoidal disturbances that are induced by the engine. The performance of the neural network controller is compared with conventional PD and PID controllers tuned using Ziegler-Nichols. From the result simulated the neural network controller has shown better ability to isolate the engine vibration than the conventional controllers.

Neural activity when people solve verbal problems with insight.

Directory of Open Access Journals (Sweden)

Mark Jung-Beeman

2004-04-01

Full Text Available People sometimes solve problems with a unique process called insight, accompanied by an "Aha!" experience. It has long been unclear whether different cognitive and neural processes lead to insight versus noninsight solutions, or if solutions differ only in subsequent subjective feeling. Recent behavioral studies indicate distinct patterns of performance and suggest differential hemispheric involvement for insight and noninsight solutions. Subjects solved verbal problems, and after each correct solution indicated whether they solved with or without insight. We observed two objective neural correlates of insight. Functional magnetic resonance imaging (Experiment 1 revealed increased activity in the right hemisphere anterior superior temporal gyrus for insight relative to noninsight solutions. The same region was active during initial solving efforts. Scalp electroencephalogram recordings (Experiment 2 revealed a sudden burst of high-frequency (gamma-band neural activity in the same area beginning 0.3 s prior to insight solutions. This right anterior temporal area is associated with making connections across distantly related information during comprehension. Although all problem solving relies on a largely shared cortical network, the sudden flash of insight occurs when solvers engage distinct neural and cognitive processes that allow them to see connections that previously eluded them.

Frequency-difference-dependent stochastic resonance in neural systems

Science.gov (United States)

Guo, Daqing; Perc, Matjaž; Zhang, Yangsong; Xu, Peng; Yao, Dezhong

2017-08-01

Biological neurons receive multiple noisy oscillatory signals, and their dynamical response to the superposition of these signals is of fundamental importance for information processing in the brain. Here we study the response of neural systems to the weak envelope modulation signal, which is superimposed by two periodic signals with different frequencies. We show that stochastic resonance occurs at the beat frequency in neural systems at the single-neuron as well as the population level. The performance of this frequency-difference-dependent stochastic resonance is influenced by both the beat frequency and the two forcing frequencies. Compared to a single neuron, a population of neurons is more efficient in detecting the information carried by the weak envelope modulation signal at the beat frequency. Furthermore, an appropriate fine-tuning of the excitation-inhibition balance can further optimize the response of a neural ensemble to the superimposed signal. Our results thus introduce and provide insights into the generation and modulation mechanism of the frequency-difference-dependent stochastic resonance in neural systems.

Simulations of oscillatory systems with award-winning software, physics of oscillations

CERN Document Server

Butikov, Eugene I

2015-01-01

Deepen Your Students' Understanding of Oscillations through Interactive Experiments Simulations of Oscillatory Systems: with Award-Winning Software, Physics of Oscillations provides a hands-on way of visualizing and understanding the fundamental concepts of the physics of oscillations. Both the textbook and software are designed as exploration-oriented supplements for courses in general physics and the theory of oscillations. The book is conveniently structured according to mathematical complexity. Each chapter in Part I contains activities, questions, exercises, and problems of varying levels of difficulty, from straightforward to quite challenging. Part II presents more sophisticated, highly mathematical material that delves into the serious theoretical background for the computer-aided study of oscillations. The software package allows students to observe the motion of linear and nonlinear mechanical oscillatory systems and to obtain plots of the variables that describe the systems along with phase diagram...

Weak correlations between hemodynamic signals and ongoing neural activity during the resting state

Science.gov (United States)

Winder, Aaron T.; Echagarruga, Christina; Zhang, Qingguang; Drew, Patrick J.

2017-01-01

Spontaneous fluctuations in hemodynamic signals in the absence of a task or overt stimulation are used to infer neural activity. We tested this coupling by simultaneously measuring neural activity and changes in cerebral blood volume (CBV) in the somatosensory cortex of awake, head-fixed mice during periods of true rest, and during whisker stimulation and volitional whisking. Here we show that neurovascular coupling was similar across states, and large spontaneous CBV changes in the absence of sensory input were driven by volitional whisker and body movements. Hemodynamic signals during periods of rest were weakly correlated with neural activity. Spontaneous fluctuations in CBV and vessel diameter persisted when local neural spiking and glutamatergic input was blocked, and during blockade of noradrenergic receptors, suggesting a non-neuronal origin for spontaneous CBV fluctuations. Spontaneous hemodynamic signals reflect a combination of behavior, local neural activity, and putatively non-neural processes. PMID:29184204

Oscillatory Convection in Rotating Liquid Metals

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Bertin, Vincent; Grannan, Alex; Aurnou, Jonathan

2016-11-01

We have performed laboratory experiments in a aspect ratio Γ = 2 cylinder using liquid gallium (Pr = 0 . 023) as the working fluid. The Ekman number varies from E = 4 ×10-5 to 4 ×10-6 and the Rayleigh number varies from Ra = 3 ×105 to 2 ×107 . Using heat transfer and temperature measurements within the fluid, we characterize the different styles of low Pr rotating convective flow. The convection threshold is first overcome in the form of a container scale inertial oscillatory mode. At stronger forcing, wall-localized modes develop, coexisting with the inertial oscillatory modes in the bulk. When the strength of the buoyancy increases further, the bulk flow becomes turbulent while the wall modes remain. Our results imply that rotating convective flows in liquid metals do not develop in the form of quasi-steady columns, as in Pr = 1 planetary and stellar dynamo models, but in the form of oscillatory motions. Therefore, convection driven dynamo action in low Pr fluids can differ substantively than that occurring in typical Pr = 1 numerical models. Our results also suggest that low wavenumber, wall modes may be dynamically and observationally important in liquid metal dynamo systems. We thank the NSF Geophysics Program for support of this project.

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

Science.gov (United States)

Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Portes, Jacob P.; Timerman, Dmitriy

2016-01-01

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI. PMID:27974609

Oscillatory solutions of the Cauchy problem for linear differential equations

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Gro Hovhannisyan

2015-06-01

Full Text Available We consider the Cauchy problem for second and third order linear differential equations with constant complex coefficients. We describe necessary and sufficient conditions on the data for the existence of oscillatory solutions. It is known that in the case of real coefficients the oscillatory behavior of solutions does not depend on initial values, but we show that this is no longer true in the complex case: hence in practice it is possible to control oscillatory behavior by varying the initial conditions. Our Proofs are based on asymptotic analysis of the zeros of solutions, represented as linear combinations of exponential functions.

Understanding the Implications of Neural Population Activity on Behavior

Science.gov (United States)

Briguglio, John

Learning how neural activity in the brain leads to the behavior we exhibit is one of the fundamental questions in Neuroscience. In this dissertation, several lines of work are presented to that use principles of neural coding to understand behavior. In one line of work, we formulate the efficient coding hypothesis in a non-traditional manner in order to test human perceptual sensitivity to complex visual textures. We find a striking agreement between how variable a particular texture signal is and how sensitive humans are to its presence. This reveals that the efficient coding hypothesis is still a guiding principle for neural organization beyond the sensory periphery, and that the nature of cortical constraints differs from the peripheral counterpart. In another line of work, we relate frequency discrimination acuity to neural responses from auditory cortex in mice. It has been previously observed that optogenetic manipulation of auditory cortex, in addition to changing neural responses, evokes changes in behavioral frequency discrimination. We are able to account for changes in frequency discrimination acuity on an individual basis by examining the Fisher information from the neural population with and without optogenetic manipulation. In the third line of work, we address the question of what a neural population should encode given that its inputs are responses from another group of neurons. Drawing inspiration from techniques in machine learning, we train Deep Belief Networks on fake retinal data and show the emergence of Garbor-like filters, reminiscent of responses in primary visual cortex. In the last line of work, we model the state of a cortical excitatory-inhibitory network during complex adaptive stimuli. Using a rate model with Wilson-Cowan dynamics, we demonstrate that simple non-linearities in the signal transferred from inhibitory to excitatory neurons can account for real neural recordings taken from auditory cortex. This work establishes and tests

On oscillatory microstructure during cellular growth of directionally solidified Sn–36at.%Ni peritectic alloy

Science.gov (United States)

Peng, Peng; Li, Xinzhong; Li, Jiangong; Su, Yanqing; Guo, Jingjie

2016-01-01

An oscillatory microstructure has been observed during deep-cellular growth of directionally solidified Sn–36at.%Ni hyperperitectic alloy containing intermetallic compounds with narrow solubility range. This oscillatory microstructure with a dimension of tens of micrometers has been observed for the first time. The morphology of this wave-like oscillatory structure is similar to secondary dendrite arms, and can be observed only in some local positions of the sample. Through analysis such as successive sectioning of the sample, it can be concluded that this oscillatory microstructure is caused by oscillatory convection of the mushy zone during solidification. And the influence of convection on this oscillatory microstructure was characterized through comparison between experimental and calculations results on the wavelength. Besides, the change in morphology of this oscillatory microstructure has been proved to be caused by peritectic transformation during solidification. Furthermore, the melt concentration increases continuously during solidification of intermetallic compounds with narrow solubility range, which helps formation of this oscillatory microstructure. PMID:27066761

On oscillatory microstructure during cellular growth of directionally solidified Sn-36at.%Ni peritectic alloy.

Science.gov (United States)

Peng, Peng; Li, Xinzhong; Li, Jiangong; Su, Yanqing; Guo, Jingjie

2016-04-12

An oscillatory microstructure has been observed during deep-cellular growth of directionally solidified Sn-36at.%Ni hyperperitectic alloy containing intermetallic compounds with narrow solubility range. This oscillatory microstructure with a dimension of tens of micrometers has been observed for the first time. The morphology of this wave-like oscillatory structure is similar to secondary dendrite arms, and can be observed only in some local positions of the sample. Through analysis such as successive sectioning of the sample, it can be concluded that this oscillatory microstructure is caused by oscillatory convection of the mushy zone during solidification. And the influence of convection on this oscillatory microstructure was characterized through comparison between experimental and calculations results on the wavelength. Besides, the change in morphology of this oscillatory microstructure has been proved to be caused by peritectic transformation during solidification. Furthermore, the melt concentration increases continuously during solidification of intermetallic compounds with narrow solubility range, which helps formation of this oscillatory microstructure.

A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

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Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2014-01-01

Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

A model of stimulus-specific neural assemblies in the insect antennal lobe.

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Dominique Martinez

2008-08-01

Full Text Available It has been proposed that synchronized neural assemblies in the antennal lobe of insects encode the identity of olfactory stimuli. In response to an odor, some projection neurons exhibit synchronous firing, phase-locked to the oscillations of the field potential, whereas others do not. Experimental data indicate that neural synchronization and field oscillations are induced by fast GABA(A-type inhibition, but it remains unclear how desynchronization occurs. We hypothesize that slow inhibition plays a key role in desynchronizing projection neurons. Because synaptic noise is believed to be the dominant factor that limits neuronal reliability, we consider a computational model of the antennal lobe in which a population of oscillatory neurons interact through unreliable GABA(A and GABA(B inhibitory synapses. From theoretical analysis and extensive computer simulations, we show that transmission failures at slow GABA(B synapses make the neural response unpredictable. Depending on the balance between GABA(A and GABA(B inputs, particular neurons may either synchronize or desynchronize. These findings suggest a wiring scheme that triggers stimulus-specific synchronized assemblies. Inhibitory connections are set by Hebbian learning and selectively activated by stimulus patterns to form a spiking associative memory whose storage capacity is comparable to that of classical binary-coded models. We conclude that fast inhibition acts in concert with slow inhibition to reformat the glomerular input into odor-specific synchronized neural assemblies.

The Relationship Between Brain Oscillatory Activity and Therapeutic Effectiveness of Transcranial Magnetic Stimulation in the Treatment of Major Depressive Disorder

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Andrew Francis Leuchter

2013-02-01

Full Text Available Major Depressive Disorder (MDD is marked by disturbances in brain functional connectivity. This connectivity is modulated by rhythmic oscillations of brain electrical activity, which enable coordinated functions across brain regions. Oscillatory activity plays a central role in regulating thinking and memory, mood, cerebral blood flow, and neurotransmitter levels, and restoration of normal oscillatory patterns is associated with effective treatment of MDD. Repetitive Transcranial Magnetic Stimulation (rTMS is a robust treatment for MDD, but the mechanism of action (MOA of its benefits for mood disorders remains incompletely understood. Benefits of rTMS have been tied to enhanced neuroplasticity in specific brain pathways. We summarize here the evidence that rTMS entrains and resets thalamocortical oscillators, normalizes regulation and facilitates reemergence of intrinsic cerebral rhythms, and through this mechanism restores normal brain function. This entrainment and resetting may be a critical step in engendering neuroplastic changes and the antidepressant effects of rTMS. It may be possible to modify the method of rTMS administration to enhance this mechanism of action and achieve better antidepressant effectiveness. We propose that rTMS can be administered: 1 synchronized to a patient’s individual alpha rhythm (IAF, or synchronized rTMS (sTMS; 2 as a low magnetic field strength sinusoidal wave form; and, 3 broadly to multiple brain areas simultaneously. We present here the theory and evidence indicating that these modifications could enhance the therapeutic effectiveness of rTMS for the treatment of MDD.

Synchrony-induced modes of oscillation of a neural field model

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Esnaola-Acebes, Jose M.; Roxin, Alex; Avitabile, Daniele; Montbrió, Ernest

2017-11-01

We investigate the modes of oscillation of heterogeneous ring networks of quadratic integrate-and-fire (QIF) neurons with nonlocal, space-dependent coupling. Perturbations of the equilibrium state with a particular wave number produce transient standing waves with a specific temporal frequency, analogously to those in a tense string. In the neuronal network, the equilibrium corresponds to a spatially homogeneous, asynchronous state. Perturbations of this state excite the network's oscillatory modes, which reflect the interplay of episodes of synchronous spiking with the excitatory-inhibitory spatial interactions. In the thermodynamic limit, an exact low-dimensional neural field model describing the macroscopic dynamics of the network is derived. This allows us to obtain formulas for the Turing eigenvalues of the spatially homogeneous state and hence to obtain its stability boundary. We find that the frequency of each Turing mode depends on the corresponding Fourier coefficient of the synaptic pattern of connectivity. The decay rate instead is identical for all oscillation modes as a consequence of the heterogeneity-induced desynchronization of the neurons. Finally, we numerically compute the spectrum of spatially inhomogeneous solutions branching from the Turing bifurcation, showing that similar oscillatory modes operate in neural bump states and are maintained away from onset.

Application of neural networks to seismic active control

International Nuclear Information System (INIS)

Tang, Yu.

1995-01-01

An exploratory study on seismic active control using an artificial neural network (ANN) is presented in which a singledegree-of-freedom (SDF) structural system is controlled by a trained neural network. A feed-forward neural network and the backpropagation training method are used in the study. In backpropagation training, the learning rate is determined by ensuring the decrease of the error function at each training cycle. The training patterns for the neural net are generated randomly. Then, the trained ANN is used to compute the control force according to the control algorithm. The control strategy proposed herein is to apply the control force at every time step to destroy the build-up of the system response. The ground motions considered in the simulations are the N21E and N69W components of the Lake Hughes No. 12 record that occurred in the San Fernando Valley in California on February 9, 1971. Significant reduction of the structural response by one order of magnitude is observed. Also, it is shown that the proposed control strategy has the ability to reduce the peak that occurs during the first few cycles of the time history. These promising results assert the potential of applying ANNs to active structural control under seismic loads

Self-reported empathy and neural activity during action imitation and observation in schizophrenia.

Science.gov (United States)

Horan, William P; Iacoboni, Marco; Cross, Katy A; Korb, Alex; Lee, Junghee; Nori, Poorang; Quintana, Javier; Wynn, Jonathan K; Green, Michael F

2014-01-01

Although social cognitive impairments are key determinants of functional outcome in schizophrenia their neural bases are poorly understood. This study investigated neural activity during imitation and observation of finger movements and facial expressions in schizophrenia, and their correlates with self-reported empathy. 23 schizophrenia outpatients and 23 healthy controls were studied with functional magnetic resonance imaging (fMRI) while they imitated, executed, or simply observed finger movements and facial emotional expressions. Between-group activation differences, as well as relationships between activation and self-reported empathy, were evaluated. Both patients and controls similarly activated neural systems previously associated with these tasks. We found no significant between-group differences in task-related activations. There were, however, between-group differences in the correlation between self-reported empathy and right inferior frontal (pars opercularis) activity during observation of facial emotional expressions. As in previous studies, controls demonstrated a positive association between brain activity and empathy scores. In contrast, the pattern in the patient group reflected a negative association between brain activity and empathy. Although patients with schizophrenia demonstrated largely normal patterns of neural activation across the finger movement and facial expression tasks, they reported decreased self perceived empathy and failed to show the typical relationship between neural activity and self-reported empathy seen in controls. These findings suggest that patients show a disjunction between automatic neural responses to low level social cues and higher level, integrative social cognitive processes involved in self-perceived empathy.

Two-scale approach to oscillatory singularly perturbed transport equations

CERN Document Server

Frénod, Emmanuel

2017-01-01

This book presents the classical results of the two-scale convergence theory and explains – using several figures – why it works. It then shows how to use this theory to homogenize ordinary differential equations with oscillating coefficients as well as oscillatory singularly perturbed ordinary differential equations. In addition, it explores the homogenization of hyperbolic partial differential equations with oscillating coefficients and linear oscillatory singularly perturbed hyperbolic partial differential equations. Further, it introduces readers to the two-scale numerical methods that can be built from the previous approaches to solve oscillatory singularly perturbed transport equations (ODE and hyperbolic PDE) and demonstrates how they can be used efficiently. This book appeals to master’s and PhD students interested in homogenization and numerics, as well as to the Iter community.

The fiber-optic imaging and manipulation of neural activity during animal behavior.

Science.gov (United States)

Miyamoto, Daisuke; Murayama, Masanori

2016-02-01

Recent progress with optogenetic probes for imaging and manipulating neural activity has further increased the relevance of fiber-optic systems for neural circuitry research. Optical fibers, which bi-directionally transmit light between separate sites (even at a distance of several meters), can be used for either optical imaging or manipulating neural activity relevant to behavioral circuitry mechanisms. The method's flexibility and the specifications of the light structure are well suited for following the behavior of freely moving animals. Furthermore, thin optical fibers allow researchers to monitor neural activity from not only the cortical surface but also deep brain regions, including the hippocampus and amygdala. Such regions are difficult to target with two-photon microscopes. Optogenetic manipulation of neural activity with an optical fiber has the advantage of being selective for both cell-types and projections as compared to conventional electrophysiological brain tissue stimulation. It is difficult to extract any data regarding changes in neural activity solely from a fiber-optic manipulation device; however, the readout of data is made possible by combining manipulation with electrophysiological recording, or the simultaneous application of optical imaging and manipulation using a bundle-fiber. The present review introduces recent progress in fiber-optic imaging and manipulation methods, while also discussing fiber-optic system designs that are suitable for a given experimental protocol. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Three-dimensional Oscillatory Magnetic Reconnection

Energy Technology Data Exchange (ETDEWEB)

Thurgood, Jonathan O.; McLaughlin, James A. [Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle upon Tyne, NE1 1ST (United Kingdom); Pontin, David I., E-mail: jonathan.thurgood@northumbria.ac.uk [Division of Mathematics, University of Dundee, Dundee, DD1 4HN (United Kingdom)

2017-07-20

Here we detail the dynamic evolution of localized reconnection regions about 3D magnetic null points using numerical simulation. We demonstrate for the first time that reconnection triggered by the localized collapse of a 3D null point that is due to an external magnetohydrodynamic (MHD) wave involves a self-generated oscillation, whereby the current sheet and outflow jets undergo a reconnection reversal process during which back-pressure formation at the jet heads acts to prise open the collapsed field before overshooting the equilibrium into an opposite-polarity configuration. The discovery that reconnection at fully 3D nulls can proceed naturally in a time-dependent and periodic fashion suggests that oscillatory reconnection mechanisms may play a role in explaining periodicity in astrophysical phenomena associated with magnetic reconnection, such as the observed quasi-periodicity of solar and stellar flare emission. Furthermore, we find that a consequence of oscillatory reconnection is the generation of a plethora of freely propagating MHD waves that escape the vicinity of the reconnection region.

Three-dimensional Oscillatory Magnetic Reconnection

International Nuclear Information System (INIS)

Thurgood, Jonathan O.; McLaughlin, James A.; Pontin, David I.

2017-01-01

Here we detail the dynamic evolution of localized reconnection regions about 3D magnetic null points using numerical simulation. We demonstrate for the first time that reconnection triggered by the localized collapse of a 3D null point that is due to an external magnetohydrodynamic (MHD) wave involves a self-generated oscillation, whereby the current sheet and outflow jets undergo a reconnection reversal process during which back-pressure formation at the jet heads acts to prise open the collapsed field before overshooting the equilibrium into an opposite-polarity configuration. The discovery that reconnection at fully 3D nulls can proceed naturally in a time-dependent and periodic fashion suggests that oscillatory reconnection mechanisms may play a role in explaining periodicity in astrophysical phenomena associated with magnetic reconnection, such as the observed quasi-periodicity of solar and stellar flare emission. Furthermore, we find that a consequence of oscillatory reconnection is the generation of a plethora of freely propagating MHD waves that escape the vicinity of the reconnection region.

Simultaneous multichannel signal transfers via chaos in a recurrent neural network.

Science.gov (United States)

Soma, Ken-ichiro; Mori, Ryota; Sato, Ryuichi; Furumai, Noriyuki; Nara, Shigetoshi

2015-05-01

We propose neural network model that demonstrates the phenomenon of signal transfer between separated neuron groups via other chaotic neurons that show no apparent correlations with the input signal. The model is a recurrent neural network in which it is supposed that synchronous behavior between small groups of input and output neurons has been learned as fragments of high-dimensional memory patterns, and depletion of neural connections results in chaotic wandering dynamics. Computer experiments show that when a strong oscillatory signal is applied to an input group in the chaotic regime, the signal is successfully transferred to the corresponding output group, although no correlation is observed between the input signal and the intermediary neurons. Signal transfer is also observed when multiple signals are applied simultaneously to separate input groups belonging to different memory attractors. In this sense simultaneous multichannel communications are realized, and the chaotic neural dynamics acts as a signal transfer medium in which the signal appears to be hidden.

Oscillatory neuronal dynamics associated with manual acupuncture: a magnetoencephalography study using beamforming analysis

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Aziz eAsghar

2012-11-01

Full Text Available Magnetoencephalography (MEG enables non-invasive recording of neuronal activity, with reconstruction methods providing estimates of underlying brain source locations and oscillatory dynamics from externally recorded neuromagnetic fields. The aim of our study was to use MEG to determine the effect of manual acupuncture on neuronal oscillatory dynamics. A major problem in MEG investigations of manual acupuncture is the absence of onset times for each needle manipulation. Given that beamforming (spatial filtering analysis is not dependent upon stimulus-driven responses being phase-locked to stimulus onset, we postulated that beamforming could reveal source locations and induced changes in neuronal activity during manual acupuncture. In a beamformer analysis, a two-minute period of manual acupuncture needle manipulation delivered to the ipsilateral right LI-4 (Hegu acupoint was contrasted with a two-minute baseline period. We considered oscillatory power changes in the theta (4-8Hz, alpha (8-13Hz, beta (13-30Hz and gamma (30-100Hz frequency bands. We found significant decreases in beta band power in the contralateral primary somatosensory cortex and superior frontal gyrus. In the ipsilateral cerebral hemisphere, we found significant power decreases in beta and gamma frequency bands in only the superior frontal gyrus. No significant power modulations were found in theta and alpha bands. Our results indicate that beamforming is a useful analytical tool to reconstruct underlying neuronal activity associated with manual acupuncture. Our main finding was of beta power decreases in primary somatosensory cortex and superior frontal gyrus, which opens up a line of future investigation regarding whether this contributes towards an underlying mechanism of acupuncture.

Simultaneous surface and depth neural activity recording with graphene transistor-based dual-modality probes.

Science.gov (United States)

Du, Mingde; Xu, Xianchen; Yang, Long; Guo, Yichuan; Guan, Shouliang; Shi, Jidong; Wang, Jinfen; Fang, Ying

2018-05-15

Subdural surface and penetrating depth probes are widely applied to record neural activities from the cortical surface and intracortical locations of the brain, respectively. Simultaneous surface and depth neural activity recording is essential to understand the linkage between the two modalities. Here, we develop flexible dual-modality neural probes based on graphene transistors. The neural probes exhibit stable electrical performance even under 90° bending because of the excellent mechanical properties of graphene, and thus allow multi-site recording from the subdural surface of rat cortex. In addition, finite element analysis was carried out to investigate the mechanical interactions between probe and cortex tissue during intracortical implantation. Based on the simulation results, a sharp tip angle of π/6 was chosen to facilitate tissue penetration of the neural probes. Accordingly, the graphene transistor-based dual-modality neural probes have been successfully applied for simultaneous surface and depth recording of epileptiform activity of rat brain in vivo. Our results show that graphene transistor-based dual-modality neural probes can serve as a facile and versatile tool to study tempo-spatial patterns of neural activities. Copyright © 2018 Elsevier B.V. All rights reserved.

Dynamics of a population of oscillatory and excitable elements.

Science.gov (United States)

O'Keeffe, Kevin P; Strogatz, Steven H

2016-06-01

We analyze a variant of a model proposed by Kuramoto, Shinomoto, and Sakaguchi for a large population of coupled oscillatory and excitable elements. Using the Ott-Antonsen ansatz, we reduce the behavior of the population to a two-dimensional dynamical system with three parameters. We present the stability diagram and calculate several of its bifurcation curves analytically, for both excitatory and inhibitory coupling. Our main result is that when the coupling function is broad, the system can display bistability between steady states of constant high and low activity, whereas when the coupling function is narrow and inhibitory, one of the states in the bistable regime can show persistent pulsations in activity.

Neural markers of loss aversion in resting-state brain activity.

Science.gov (United States)

Canessa, Nicola; Crespi, Chiara; Baud-Bovy, Gabriel; Dodich, Alessandra; Falini, Andrea; Antonellis, Giulia; Cappa, Stefano F

2017-02-01

Neural responses in striatal, limbic and somatosensory brain regions track individual differences in loss aversion, i.e. the higher sensitivity to potential losses compared with equivalent gains in decision-making under risk. The engagement of structures involved in the processing of aversive stimuli and experiences raises a further question, i.e. whether the tendency to avoid losses rather than acquire gains represents a transient fearful overreaction elicited by choice-related information, or rather a stable component of one's own preference function, reflecting a specific pattern of neural activity. We tested the latter hypothesis by assessing in 57 healthy human subjects whether the relationship between behavioral and neural loss aversion holds at rest, i.e. when the BOLD signal is collected during 5minutes of cross-fixation in the absence of an explicit task. Within the resting-state networks highlighted by a spatial group Independent Component Analysis (gICA), we found a significant correlation between strength of activity and behavioral loss aversion in the left ventral striatum and right posterior insula/supramarginal gyrus, i.e. the very same regions displaying a pattern of neural loss aversion during explicit choices. Cross-study analyses confirmed that this correlation holds when voxels identified by gICA are used as regions of interest in task-related activity and vice versa. These results suggest that the individual degree of (neural) loss aversion represents a stable dimension of decision-making, which reflects in specific metrics of intrinsic brain activity at rest possibly modulating cortical excitability at choice. Copyright © 2016 Elsevier Inc. All rights reserved.

On the neural mechanisms subserving consciousness and attention

Directory of Open Access Journals (Sweden)

Catherine eTallon-Baudry

2012-01-01

Full Text Available Consciousness, as described in the experimental literature, is a multi-faceted phenomenon, that impinges on other well-studied concepts such as attention and control. Do consciousness and attention refer to different aspects of the same core phenomenon, or do they correspond to distinct functions? One possibility to address this question is to examine the neural mechanisms underlying consciousness and attention. If consciousness and attention pertain to the same concept, they should rely on shared neural mechanisms. Conversely, if their underlying mechanisms are distinct, then consciousness and attention should be considered as distinct entities. This paper therefore reviews neurophysiological facts arguing in favor or against a tight relationship between consciousness and attention. Three neural mechanisms that have been associated with both attention and consciousness are examined (neural amplification, involvement of the fronto-parietal network, and oscillatory synchrony, to conclude that the commonalities between attention and consciousness at the neural level may have been overestimated. Last but not least, experiments in which both attention and consciousness were probed at the neural level point toward a dissociation between the two concepts. It therefore appears from this review that consciousness and attention rely on distinct neural properties, although they can interact at the behavioral level. It is proposed that a "cumulative influence model", in which attention and consciousness correspond to distinct neural mechanisms feeding a single decisional process leading to behavior, fits best with available neural and behavioral data. In this view, consciousness should not be considered as a top-level executive function but should rather be defined by its experiential properties.

Spatiotemporal oscillatory dynamics of visual selective attention during a flanker task.

Science.gov (United States)

McDermott, Timothy J; Wiesman, Alex I; Proskovec, Amy L; Heinrichs-Graham, Elizabeth; Wilson, Tony W

2017-08-01

The flanker task is a test of visual selective attention that has been widely used to probe error monitoring, response conflict, and related constructs. However, to date, few studies have focused on the selective attention component of this task and imaged the underlying oscillatory dynamics serving task performance. In this study, 21 healthy adults successfully completed an arrow-based version of the Eriksen flanker task during magnetoencephalography (MEG). All MEG data were pre-processed and transformed into the time-frequency domain. Significant oscillatory brain responses were imaged using a beamforming approach, and voxel time series were extracted from the peak responses to identify the temporal dynamics. Across both congruent and incongruent flanker conditions, our results indicated robust decreases in alpha (9-12Hz) activity in medial and lateral occipital regions, bilateral parietal cortices, and cerebellar areas during task performance. In parallel, increases in theta (3-7Hz) oscillatory activity were detected in dorsal and ventral frontal regions, and the anterior cingulate. As per conditional effects, stronger alpha responses (i.e., greater desynchronization) were observed in parietal, occipital, and cerebellar cortices during incongruent relative to congruent trials, whereas the opposite pattern emerged for theta responses (i.e., synchronization) in the anterior cingulate, left dorsolateral prefrontal, and ventral prefrontal cortices. Interestingly, the peak latency of theta responses in these latter brain regions was significantly correlated with reaction time, and may partially explain the amplitude difference observed between congruent and incongruent trials. Lastly, whole-brain exploratory analyses implicated the frontal eye fields, right temporoparietal junction, and premotor cortices. These findings suggest that regions of both the dorsal and ventral attention networks contribute to visual selective attention processes during incongruent trials

Spontaneous oscillatory rhythms in the degenerating mouse retina modulate retinal ganglion cell responses to electrical stimulation

Directory of Open Access Journals (Sweden)

Yong Sook eGoo

2016-01-01

Full Text Available Characterization of the electrical activity of the retina in the animal models of retinal degeneration has been carried out in part to understand the progression of retinal degenerative diseases like age-related macular degeneration (AMD and retinitis pigmentosa (RP, but also to determine optimum stimulus paradigms for use with retinal prosthetic devices. The models most studied in this regard have been the two lines of mice deficient in the β-subunit of phosphodiesterase (rd1 and rd10 mice, where the degenerating retinas exhibit characteristic spontaneous hyperactivity and oscillatory local field potentials (LFPs. Additionally, there is a robust ~10 Hz rhythmic burst of retinal ganglion cell (RGC spikes on the trough of the oscillatory LFP. In rd1 mice, the rhythmic burst of RGC spikes is always phase-locked with the oscillatory LFP and this phase-locking property is preserved regardless of postnatal ages. However, in rd10 mice, the frequency of the oscillatory rhythm changes according to postnatal age, suggesting that this rhythm might be a marker of the stage of degeneration. Furthermore when a biphasic current stimulus is applied to rd10 mice degenerate retina, distinct RGC response patterns that correlate with the stage of degeneration emerge. This review also considers the significance of these response properties.

Activity patterns of cultured neural networks on micro electrode arrays

NARCIS (Netherlands)

Rutten, Wim; van Pelt, J.

2001-01-01

A hybrid neuro-electronic interface is a cell-cultured micro electrode array, acting as a neural information transducer for stimulation and/or recording of neural activity in the brain or the spinal cord (ventral motor region or dorsal sensory region). It consists of an array of micro electrodes on

Death and rebirth of neural activity in sparse inhibitory networks

Science.gov (United States)

Angulo-Garcia, David; Luccioli, Stefano; Olmi, Simona; Torcini, Alessandro

2017-05-01

Inhibition is a key aspect of neural dynamics playing a fundamental role for the emergence of neural rhythms and the implementation of various information coding strategies. Inhibitory populations are present in several brain structures, and the comprehension of their dynamics is strategical for the understanding of neural processing. In this paper, we clarify the mechanisms underlying a general phenomenon present in pulse-coupled heterogeneous inhibitory networks: inhibition can induce not only suppression of neural activity, as expected, but can also promote neural re-activation. In particular, for globally coupled systems, the number of firing neurons monotonically reduces upon increasing the strength of inhibition (neuronal death). However, the random pruning of connections is able to reverse the action of inhibition, i.e. in a random sparse network a sufficiently strong synaptic strength can surprisingly promote, rather than depress, the activity of neurons (neuronal rebirth). Thus, the number of firing neurons reaches a minimum value at some intermediate synaptic strength. We show that this minimum signals a transition from a regime dominated by neurons with a higher firing activity to a phase where all neurons are effectively sub-threshold and their irregular firing is driven by current fluctuations. We explain the origin of the transition by deriving a mean field formulation of the problem able to provide the fraction of active neurons as well as the first two moments of their firing statistics. The introduction of a synaptic time scale does not modify the main aspects of the reported phenomenon. However, for sufficiently slow synapses the transition becomes dramatic, and the system passes from a perfectly regular evolution to irregular bursting dynamics. In this latter regime the model provides predictions consistent with experimental findings for a specific class of neurons, namely the medium spiny neurons in the striatum.

Effects of Electrical and Optogenetic Deep Brain Stimulation on Synchronized Oscillatory Activity in Parkinsonian Basal Ganglia.

Science.gov (United States)

Ratnadurai-Giridharan, Shivakeshavan; Cheung, Chung C; Rubchinsky, Leonid L

2017-11-01

Conventional deep brain stimulation of basal ganglia uses high-frequency regular electrical pulses to treat Parkinsonian motor symptoms but has a series of limitations. Relatively new and not yet clinically tested, optogenetic stimulation is an effective experimental stimulation technique to affect pathological network dynamics. We compared the effects of electrical and optogenetic stimulation of the basal gangliaon the pathologicalParkinsonian rhythmic neural activity. We studied the network response to electrical stimulation and excitatory and inhibitory optogenetic stimulations. Different stimulations exhibit different interactions with pathological activity in the network. We studied these interactions for different network and stimulation parameter values. Optogenetic stimulation was found to be more efficient than electrical stimulation in suppressing pathological rhythmicity. Our findings indicate that optogenetic control of neural synchrony may be more efficacious than electrical control because of the different ways of how stimulations interact with network dynamics.

Characterization of K-complexes and slow wave activity in a neural mass model.

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Arne Weigenand

2014-11-01

Full Text Available NREM sleep is characterized by two hallmarks, namely K-complexes (KCs during sleep stage N2 and cortical slow oscillations (SOs during sleep stage N3. While the underlying dynamics on the neuronal level is well known and can be easily measured, the resulting behavior on the macroscopic population level remains unclear. On the basis of an extended neural mass model of the cortex, we suggest a new interpretation of the mechanisms responsible for the generation of KCs and SOs. As the cortex transitions from wake to deep sleep, in our model it approaches an oscillatory regime via a Hopf bifurcation. Importantly, there is a canard phenomenon arising from a homoclinic bifurcation, whose orbit determines the shape of large amplitude SOs. A KC corresponds to a single excursion along the homoclinic orbit, while SOs are noise-driven oscillations around a stable focus. The model generates both time series and spectra that strikingly resemble real electroencephalogram data and points out possible differences between the different stages of natural sleep.

Neural mechanisms of human perceptual learning: electrophysiological evidence for a two-stage process.

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Hamamé, Carlos M; Cosmelli, Diego; Henriquez, Rodrigo; Aboitiz, Francisco

2011-04-26

Humans and other animals change the way they perceive the world due to experience. This process has been labeled as perceptual learning, and implies that adult nervous systems can adaptively modify the way in which they process sensory stimulation. However, the mechanisms by which the brain modifies this capacity have not been sufficiently analyzed. We studied the neural mechanisms of human perceptual learning by combining electroencephalographic (EEG) recordings of brain activity and the assessment of psychophysical performance during training in a visual search task. All participants improved their perceptual performance as reflected by an increase in sensitivity (d') and a decrease in reaction time. The EEG signal was acquired throughout the entire experiment revealing amplitude increments, specific and unspecific to the trained stimulus, in event-related potential (ERP) components N2pc and P3 respectively. P3 unspecific modification can be related to context or task-based learning, while N2pc may be reflecting a more specific attentional-related boosting of target detection. Moreover, bell and U-shaped profiles of oscillatory brain activity in gamma (30-60 Hz) and alpha (8-14 Hz) frequency bands may suggest the existence of two phases for learning acquisition, which can be understood as distinctive optimization mechanisms in stimulus processing. We conclude that there are reorganizations in several neural processes that contribute differently to perceptual learning in a visual search task. We propose an integrative model of neural activity reorganization, whereby perceptual learning takes place as a two-stage phenomenon including perceptual, attentional and contextual processes.

Altered Neural Activity Associated with Mindfulness during Nociception: A Systematic Review of Functional MRI

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Elena Bilevicius

2016-04-01

Full Text Available Objective: To assess the neural activity associated with mindfulness-based alterations of pain perception. Methods: The Cochrane Central, EMBASE, Ovid Medline, PsycINFO, Scopus, and Web of Science databases were searched on 2 February 2016. Titles, abstracts, and full-text articles were independently screened by two reviewers. Data were independently extracted from records that included topics of functional neuroimaging, pain, and mindfulness interventions. Results: The literature search produced 946 total records, of which five met the inclusion criteria. Records reported pain in terms of anticipation (n = 2, unpleasantness (n = 5, and intensity (n = 5, and how mindfulness conditions altered the neural activity during noxious stimulation accordingly. Conclusions: Although the studies were inconsistent in relating pain components to neural activity, in general, mindfulness was able to reduce pain anticipation and unpleasantness ratings, as well as alter the corresponding neural activity. The major neural underpinnings of mindfulness-based pain reduction consisted of altered activity in the anterior cingulate cortex, insula, and dorsolateral prefrontal cortex.

Altered Neural Activity Associated with Mindfulness during Nociception: A Systematic Review of Functional MRI.

Science.gov (United States)

Bilevicius, Elena; Kolesar, Tiffany A; Kornelsen, Jennifer

2016-04-19

To assess the neural activity associated with mindfulness-based alterations of pain perception. The Cochrane Central, EMBASE, Ovid Medline, PsycINFO, Scopus, and Web of Science databases were searched on 2 February 2016. Titles, abstracts, and full-text articles were independently screened by two reviewers. Data were independently extracted from records that included topics of functional neuroimaging, pain, and mindfulness interventions. The literature search produced 946 total records, of which five met the inclusion criteria. Records reported pain in terms of anticipation (n = 2), unpleasantness (n = 5), and intensity (n = 5), and how mindfulness conditions altered the neural activity during noxious stimulation accordingly. Although the studies were inconsistent in relating pain components to neural activity, in general, mindfulness was able to reduce pain anticipation and unpleasantness ratings, as well as alter the corresponding neural activity. The major neural underpinnings of mindfulness-based pain reduction consisted of altered activity in the anterior cingulate cortex, insula, and dorsolateral prefrontal cortex.

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

Oscillatory blood pressure response to the onset of cycling exercise in men

DEFF Research Database (Denmark)

Barbosa, Thales C; Fernandes, Igor A; Magalhães-Jr, Nisval

2015-01-01

to this pattern is unclear. What is the main finding and its importance? We demonstrate that attenuation of group III/IV muscle afferent feedback by spinal fentanyl impairs the pressor response after 10 s of moderate leg cycling exercise, but this afferent feedback does not appear to be necessary for induction...... of the oscillatory pattern of blood pressure at the onset of exercise. We investigated whether attenuation of the central projections of group III/IV skeletal muscle afferents via lumbar intrathecal administration of the μ-opioid receptor agonist fentanyl affects the oscillatory blood pressure (BP) response...... to the onset of dynamic exercise. Eight healthy, recreationally active men (28 ± 3 years old) performed 40 s of cycling at 80 W (60 r.p.m.) before (control) and after fentanyl administration, while heart rate, stroke volume, cardiac output, systolic, mean and diastolic BP and total vascular conductance were...

Optimal Hierarchical Modular Topologies for Producing Limited Sustained Activation of Neural Networks

OpenAIRE

Kaiser, Marcus; Hilgetag, Claus C.

2010-01-01

An essential requirement for the representation of functional patterns in complex neural networks, such as the mammalian cerebral cortex, is the existence of stable regimes of network activation, typically arising from a limited parameter range. In this range of limited sustained activity (LSA), the activity of neural populations in the network persists between the extremes of either quickly dying out or activating the whole network. Hierarchical modular networks were previously found to show...

Oscillatory Mechanisms of Stimulus Processing and Selection in the Visual and Auditory Systems: State-of-the-Art, Speculations and Suggestions

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Benedikt Zoefel

2017-05-01

Full Text Available All sensory systems need to continuously prioritize and select incoming stimuli in order to avoid overflow or interference, and provide a structure to the brain's input. However, the characteristics of this input differ across sensory systems; therefore, and as a direct consequence, each sensory system might have developed specialized strategies to cope with the continuous stream of incoming information. Neural oscillations are intimately connected with this selection process, as they can be used by the brain to rhythmically amplify or attenuate input and therefore represent an optimal tool for stimulus selection. In this paper, we focus on oscillatory processes for stimulus selection in the visual and auditory systems. We point out both commonalities and differences between the two systems and develop several hypotheses, inspired by recently published findings: (1 The rhythmic component in its input is crucial for the auditory, but not for the visual system. The alignment between oscillatory phase and rhythmic input (phase entrainment is therefore an integral part of stimulus selection in the auditory system whereas the visual system merely adjusts its phase to upcoming events, without the need for any rhythmic component. (2 When input is unpredictable, the visual system can maintain its oscillatory sampling, whereas the auditory system switches to a different, potentially internally oriented, “mode” of processing that might be characterized by alpha oscillations. (3 Visual alpha can be divided into a faster occipital alpha (10 Hz and a slower frontal alpha (7 Hz that critically depends on attention.

Self-reported empathy and neural activity during action imitation and observation in schizophrenia

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William P. Horan

2014-01-01

Conclusions: Although patients with schizophrenia demonstrated largely normal patterns of neural activation across the finger movement and facial expression tasks, they reported decreased self perceived empathy and failed to show the typical relationship between neural activity and self-reported empathy seen in controls. These findings suggest that patients show a disjunction between automatic neural responses to low level social cues and higher level, integrative social cognitive processes involved in self-perceived empathy.

Typology of nonlinear activity waves in a layered neural continuum.

Science.gov (United States)

Koch, Paul; Leisman, Gerry

2006-04-01

Neural tissue, a medium containing electro-chemical energy, can amplify small increments in cellular activity. The growing disturbance, measured as the fraction of active cells, manifests as propagating waves. In a layered geometry with a time delay in synaptic signals between the layers, the delay is instrumental in determining the amplified wavelengths. The growth of the waves is limited by the finite number of neural cells in a given region of the continuum. As wave growth saturates, the resulting activity patterns in space and time show a variety of forms, ranging from regular monochromatic waves to highly irregular mixtures of different spatial frequencies. The type of wave configuration is determined by a number of parameters, including alertness and synaptic conditioning as well as delay. For all cases studied, using numerical solution of the nonlinear Wilson-Cowan (1973) equations, there is an interval in delay in which the wave mixing occurs. As delay increases through this interval, during a series of consecutive waves propagating through a continuum region, the activity within that region changes from a single-frequency to a multiple-frequency pattern and back again. The diverse spatio-temporal patterns give a more concrete form to several metaphors advanced over the years to attempt an explanation of cognitive phenomena: Activity waves embody the "holographic memory" (Pribram, 1991); wave mixing provides a plausible cause of the competition called "neural Darwinism" (Edelman, 1988); finally the consecutive generation of growing neural waves can explain the discontinuousness of "psychological time" (Stroud, 1955).

A Simple Quantum Neural Net with a Periodic Activation Function

OpenAIRE

Daskin, Ammar

2018-01-01

In this paper, we propose a simple neural net that requires only $O(nlog_2k)$ number of qubits and $O(nk)$ quantum gates: Here, $n$ is the number of input parameters, and $k$ is the number of weights applied to these parameters in the proposed neural net. We describe the network in terms of a quantum circuit, and then draw its equivalent classical neural net which involves $O(k^n)$ nodes in the hidden layer. Then, we show that the network uses a periodic activation function of cosine values o...

Experimental study of the turbulent boundary layer in acceleration-skewed oscillatory flow

NARCIS (Netherlands)

van der A, D.A.; O' Donoghue, T.; Davies, A.G; Ribberink, Jan S.

2011-01-01

Experiments have been conducted in a large oscillatory flow tunnel to investigate the effects of acceleration skewness on oscillatory boundary layer flow over fixed beds. As well as enabling experimental investigation of the effects of acceleration skewness, the new experiments add substantially to

Nonlinearly Activated Neural Network for Solving Time-Varying Complex Sylvester Equation.

Science.gov (United States)

Li, Shuai; Li, Yangming

2013-10-28

The Sylvester equation is often encountered in mathematics and control theory. For the general time-invariant Sylvester equation problem, which is defined in the domain of complex numbers, the Bartels-Stewart algorithm and its extensions are effective and widely used with an O(n³) time complexity. When applied to solving the time-varying Sylvester equation, the computation burden increases intensively with the decrease of sampling period and cannot satisfy continuous realtime calculation requirements. For the special case of the general Sylvester equation problem defined in the domain of real numbers, gradient-based recurrent neural networks are able to solve the time-varying Sylvester equation in real time, but there always exists an estimation error while a recently proposed recurrent neural network by Zhang et al [this type of neural network is called Zhang neural network (ZNN)] converges to the solution ideally. The advancements in complex-valued neural networks cast light to extend the existing real-valued ZNN for solving the time-varying real-valued Sylvester equation to its counterpart in the domain of complex numbers. In this paper, a complex-valued ZNN for solving the complex-valued Sylvester equation problem is investigated and the global convergence of the neural network is proven with the proposed nonlinear complex-valued activation functions. Moreover, a special type of activation function with a core function, called sign-bi-power function, is proven to enable the ZNN to converge in finite time, which further enhances its advantage in online processing. In this case, the upper bound of the convergence time is also derived analytically. Simulations are performed to evaluate and compare the performance of the neural network with different parameters and activation functions. Both theoretical analysis and numerical simulations validate the effectiveness of the proposed method.

Modulation of Network Oscillatory Activity and GABAergic Synaptic Transmission by CB1 Cannabinoid Receptors in the Rat Medial Entorhinal Cortex

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Nicola H. Morgan

2008-01-01

Full Text Available Cannabinoids modulate inhibitory GABAergic neurotransmission in many brain regions. Within the temporal lobe, cannabinoid receptors are highly expressed, and are located presynaptically at inhibitory terminals. Here, we have explored the role of type-1 cannabinoid receptors (CB1Rs at the level of inhibitory synaptic currents and field-recorded network oscillations. We report that arachidonylcyclopropylamide (ACPA; 10 M, an agonist at CB1R, inhibits GABAergic synaptic transmission onto both superficial and deep medial entorhinal (mEC neurones, but this has little effect on network oscillations in beta/gamma frequency bands. By contrast, the CB1R antagonist/inverse agonist LY320135 (500 nM, increased GABAergic synaptic activity and beta/gamma oscillatory activity in superficial mEC, was suppressed, whilst that in deep mEC was enhanced. These data indicate that cannabinoid-mediated effects on inhibitory synaptic activity may be constitutively active in vitro, and that modulation of CB1R activation using inverse agonists unmasks complex effects of CBR function on network activity.

Neural activity predicts attitude change in cognitive dissonance.

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van Veen, Vincent; Krug, Marie K; Schooler, Jonathan W; Carter, Cameron S

2009-11-01

When our actions conflict with our prior attitudes, we often change our attitudes to be more consistent with our actions. This phenomenon, known as cognitive dissonance, is considered to be one of the most influential theories in psychology. However, the neural basis of this phenomenon is unknown. Using a Solomon four-group design, we scanned participants with functional MRI while they argued that the uncomfortable scanner environment was nevertheless a pleasant experience. We found that cognitive dissonance engaged the dorsal anterior cingulate cortex and anterior insula; furthermore, we found that the activation of these regions tightly predicted participants' subsequent attitude change. These effects were not observed in a control group. Our findings elucidate the neural representation of cognitive dissonance, and support the role of the anterior cingulate cortex in detecting cognitive conflict and the neural prediction of attitude change.

The effects of gratitude expression on neural activity.

Science.gov (United States)

Kini, Prathik; Wong, Joel; McInnis, Sydney; Gabana, Nicole; Brown, Joshua W

2016-03-01

Gratitude is a common aspect of social interaction, yet relatively little is known about the neural bases of gratitude expression, nor how gratitude expression may lead to longer-term effects on brain activity. To address these twin issues, we recruited subjects who coincidentally were entering psychotherapy for depression and/or anxiety. One group participated in a gratitude writing intervention, which required them to write letters expressing gratitude. The therapy-as-usual control group did not perform a writing intervention. After three months, subjects performed a "Pay It Forward" task in the fMRI scanner. In the task, subjects were repeatedly endowed with a monetary gift and then asked to pass it on to a charitable cause to the extent they felt grateful for the gift. Operationalizing gratitude as monetary gifts allowed us to engage the subjects and quantify the gratitude expression for subsequent analyses. We measured brain activity and found regions where activity correlated with self-reported gratitude experience during the task, even including related constructs such as guilt motivation and desire to help as statistical controls. These were mostly distinct from brain regions activated by empathy or theory of mind. Also, our between groups cross-sectional study found that a simple gratitude writing intervention was associated with significantly greater and lasting neural sensitivity to gratitude - subjects who participated in gratitude letter writing showed both behavioral increases in gratitude and significantly greater neural modulation by gratitude in the medial prefrontal cortex three months later. Copyright © 2015 Elsevier Inc. All rights reserved.

An extended discrete gradient formula for oscillatory Hamiltonian systems

International Nuclear Information System (INIS)

Liu Kai; Shi Wei; Wu Xinyuan

2013-01-01

In this paper, incorporating the idea of the discrete gradient method into the extended Runge–Kutta–Nyström integrator, we derive and analyze an extended discrete gradient formula for the oscillatory Hamiltonian system with the Hamiltonian H(p,q)= 1/2 p T p+ 1/2 q T Mq+U(q), where q:R→R d represents generalized positions, p:R→R d represents generalized momenta and M is an element of R dxd is a symmetric and positive semi-definite matrix. The solution of this system is a nonlinear oscillator. Basically, many nonlinear oscillatory mechanical systems with a partitioned Hamiltonian function lend themselves to this approach. The extended discrete gradient formula presented in this paper exactly preserves the energy H(p, q). We derive some properties of the new formula. The convergence is analyzed for the implicit schemes based on the discrete gradient formula, and it turns out that the convergence of the implicit schemes based on the extended discrete gradient formula is independent of ‖M‖, which is a significant property for the oscillatory Hamiltonian system. Thus, it transpires that a larger step size can be chosen for the new energy-preserving schemes than that for the traditional discrete gradient methods when applied to the oscillatory Hamiltonian system. Illustrative examples show the competence and efficiency of the new schemes in comparison with the traditional discrete gradient methods in the scientific literature. (paper)

Self-Sustained Oscillatory Sliding Movement of Doublet Microtubules and Flagellar Bend Formation.

Directory of Open Access Journals (Sweden)

Sumio Ishijima

Full Text Available It is well established that the basis for flagellar and ciliary movements is ATP-dependent sliding between adjacent doublet microtubules. However, the mechanism for converting microtubule sliding into flagellar and ciliary movements has long remained unresolved. The author has developed new sperm models that use bull spermatozoa divested of their plasma membrane and midpiece mitochondrial sheath by Triton X-100 and dithiothreitol. These models enable the observation of both the oscillatory sliding movement of activated doublet microtubules and flagellar bend formation in the presence of ATP. A long fiber of doublet microtubules extruded by synchronous sliding of the sperm flagella and a short fiber of doublet microtubules extruded by metachronal sliding exhibited spontaneous oscillatory movements and constructed a one beat cycle of flagellar bending by alternately actuating. The small sliding displacement generated by metachronal sliding formed helical bends, whereas the large displacement by synchronous sliding formed planar bends. Therefore, the resultant waveform is a half-funnel shape, which is similar to ciliary movements.

Localisation of the subthalamic nucleus in Parkinson's disease with neural beta and gamma activity of local field potentials

NARCIS (Netherlands)

Verhagen, R.; Zwartjes - de Klerk, D.G.M; Heida, Tjitske; Contarino, M.F.; de Bie, R.M.A.; van den Munckhof, P; Schuurman, P.R.; Martens, H.C.F.; Veltink, Petrus H.; Bour, L.J.

2013-01-01

To evaluate the nature of oscillatory activity in the subthalamic nucleus (STN) by means of intraoperative local field potential (LFP) recordings, its relationship with microelectrode recordings (MER) and its potential use to locate the STN and its sensorimotor sub-area in patients with Parkinson’s

Coupling Strength and System Size Induce Firing Activity of Globally Coupled Neural Network

International Nuclear Information System (INIS)

Wei Duqu; Luo Xiaoshu; Zou Yanli

2008-01-01

We investigate how firing activity of globally coupled neural network depends on the coupling strength C and system size N. Network elements are described by space-clamped FitzHugh-Nagumo (SCFHN) neurons with the values of parameters at which no firing activity occurs. It is found that for a given appropriate coupling strength, there is an intermediate range of system size where the firing activity of globally coupled SCFHN neural network is induced and enhanced. On the other hand, for a given intermediate system size level, there exists an optimal value of coupling strength such that the intensity of firing activity reaches its maximum. These phenomena imply that the coupling strength and system size play a vital role in firing activity of neural network

Oscillatory processes in plasma

International Nuclear Information System (INIS)

Gallin, E.

1980-01-01

The oscillatory process play an important part in plasma evolution, In hot plasma in particular, the interactions between the oscillation modes are preponderant in relation to the binary collisions between particles. The nonlineary interactions between collective plasma oscillations can generate, in this case, a non-balanced steady state of plasma (steady turbulence). The paper elucidates some aspects of the oscillatory phenomena which contribute to the plasma state evolution, especially of hot plasma. A major part of the paper is devoted to the study of parametric instabilities in plasma and their role in increasing the temperature of plasma components (electrons, ions). Both parametric instabilities in plasma in the vicinity of thermodynamic balance and parametric processes is steady turbulent plasma are analysed - in relation to additional heating of hot plasma. An important result of the thesis refers to the drowing-up of a non-lineary interaction model between the oscillation modes in turbulent plasma, being responsible for the electromagnetic radiation in hot plasma. On the basis of the model suggested in the paper the existence of a low frequency radiative mode in hot plasma in a turbulent state, can be demonstrated. Its frequency could be even lower than plasma frequency in the field of long waves be even lower than plasma frequency in the field of long waves. Such a radiative mode was detected experimentally in focussed plasma installations. (author)

Patterns recognition of electric brain activity using artificial neural networks

Science.gov (United States)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Can Neural Activity Propagate by Endogenous Electrical Field?

Science.gov (United States)

Qiu, Chen; Shivacharan, Rajat S.; Zhang, Mingming

2015-01-01

It is widely accepted that synaptic transmissions and gap junctions are the major governing mechanisms for signal traveling in the neural system. Yet, a group of neural waves, either physiological or pathological, share the same speed of ∼0.1 m/s without synaptic transmission or gap junctions, and this speed is not consistent with axonal conduction or ionic diffusion. The only explanation left is an electrical field effect. We tested the hypothesis that endogenous electric fields are sufficient to explain the propagation with in silico and in vitro experiments. Simulation results show that field effects alone can indeed mediate propagation across layers of neurons with speeds of 0.12 ± 0.09 m/s with pathological kinetics, and 0.11 ± 0.03 m/s with physiologic kinetics, both generating weak field amplitudes of ∼2–6 mV/mm. Further, the model predicted that propagation speed values are inversely proportional to the cell-to-cell distances, but do not significantly change with extracellular resistivity, membrane capacitance, or membrane resistance. In vitro recordings in mice hippocampi produced similar speeds (0.10 ± 0.03 m/s) and field amplitudes (2.5–5 mV/mm), and by applying a blocking field, the propagation speed was greatly reduced. Finally, osmolarity experiments confirmed the model's prediction that cell-to-cell distance inversely affects propagation speed. Together, these results show that despite their weak amplitude, electric fields can be solely responsible for spike propagation at ∼0.1 m/s. This phenomenon could be important to explain the slow propagation of epileptic activity and other normal propagations at similar speeds. SIGNIFICANCE STATEMENT Neural activity (waves or spikes) can propagate using well documented mechanisms such as synaptic transmission, gap junctions, or diffusion. However, the purpose of this paper is to provide an explanation for experimental data showing that neural signals can propagate by means other than synaptic

EEG Oscillatory States: Universality, Uniqueness and Specificity across Healthy-Normal, Altered and Pathological Brain Conditions

Science.gov (United States)

Fingelkurts, Alexander A.; Fingelkurts, Andrew A.

2014-01-01

For the first time the dynamic repertoires and oscillatory types of local EEG states in 13 diverse conditions (examined over 9 studies) that covered healthy-normal, altered and pathological brain states were quantified within the same methodological and conceptual framework. EEG oscillatory states were assessed by the probability-classification analysis of short-term EEG spectral patterns. The results demonstrated that brain activity consists of a limited repertoire of local EEG states in any of the examined conditions. The size of the state repertoires was associated with changes in cognition and vigilance or neuropsychopathologic conditions. Additionally universal, optional and unique EEG states across 13 diverse conditions were observed. It was demonstrated also that EEG oscillations which constituted EEG states were characteristic for different groups of conditions in accordance to oscillations’ functional significance. The results suggested that (a) there is a limit in the number of local states available to the cortex and many ways in which these local states can rearrange themselves and still produce the same global state and (b) EEG individuality is determined by varying proportions of universal, optional and unique oscillatory states. The results enriched our understanding about dynamic microstructure of EEG-signal. PMID:24505292

Multichannel brain recordings in behaving Drosophila reveal oscillatory activity and local coherence in response to sensory stimulation and circuit activation

Science.gov (United States)

Paulk, Angelique C.; Zhou, Yanqiong; Stratton, Peter; Liu, Li

2013-01-01

Neural networks in vertebrates exhibit endogenous oscillations that have been associated with functions ranging from sensory processing to locomotion. It remains unclear whether oscillations may play a similar role in the insect brain. We describe a novel “whole brain” readout for Drosophila melanogaster using a simple multichannel recording preparation to study electrical activity across the brain of flies exposed to different sensory stimuli. We recorded local field potential (LFP) activity from >2,000 registered recording sites across the fly brain in >200 wild-type and transgenic animals to uncover specific LFP frequency bands that correlate with: 1) brain region; 2) sensory modality (olfactory, visual, or mechanosensory); and 3) activity in specific neural circuits. We found endogenous and stimulus-specific oscillations throughout the fly brain. Central (higher-order) brain regions exhibited sensory modality-specific increases in power within narrow frequency bands. Conversely, in sensory brain regions such as the optic or antennal lobes, LFP coherence, rather than power, best defined sensory responses across modalities. By transiently activating specific circuits via expression of TrpA1, we found that several circuits in the fly brain modulate LFP power and coherence across brain regions and frequency domains. However, activation of a neuromodulatory octopaminergic circuit specifically increased neuronal coherence in the optic lobes during visual stimulation while decreasing coherence in central brain regions. Our multichannel recording and brain registration approach provides an effective way to track activity simultaneously across the fly brain in vivo, allowing investigation of functional roles for oscillations in processing sensory stimuli and modulating behavior. PMID:23864378

Multichannel brain recordings in behaving Drosophila reveal oscillatory activity and local coherence in response to sensory stimulation and circuit activation.

Science.gov (United States)

Paulk, Angelique C; Zhou, Yanqiong; Stratton, Peter; Liu, Li; van Swinderen, Bruno

2013-10-01

Neural networks in vertebrates exhibit endogenous oscillations that have been associated with functions ranging from sensory processing to locomotion. It remains unclear whether oscillations may play a similar role in the insect brain. We describe a novel "whole brain" readout for Drosophila melanogaster using a simple multichannel recording preparation to study electrical activity across the brain of flies exposed to different sensory stimuli. We recorded local field potential (LFP) activity from >2,000 registered recording sites across the fly brain in >200 wild-type and transgenic animals to uncover specific LFP frequency bands that correlate with: 1) brain region; 2) sensory modality (olfactory, visual, or mechanosensory); and 3) activity in specific neural circuits. We found endogenous and stimulus-specific oscillations throughout the fly brain. Central (higher-order) brain regions exhibited sensory modality-specific increases in power within narrow frequency bands. Conversely, in sensory brain regions such as the optic or antennal lobes, LFP coherence, rather than power, best defined sensory responses across modalities. By transiently activating specific circuits via expression of TrpA1, we found that several circuits in the fly brain modulate LFP power and coherence across brain regions and frequency domains. However, activation of a neuromodulatory octopaminergic circuit specifically increased neuronal coherence in the optic lobes during visual stimulation while decreasing coherence in central brain regions. Our multichannel recording and brain registration approach provides an effective way to track activity simultaneously across the fly brain in vivo, allowing investigation of functional roles for oscillations in processing sensory stimuli and modulating behavior.

Introduction to the oscillatory movement based on the rediscovery

International Nuclear Information System (INIS)

Concari, S.B.; Carreri, R.A.; Giorgi, S.M.; Camara, C.N.; Alzugaray, G.E.; Pozzo, R.L.

1997-01-01

In this work we present a proposal of a classroom in treating the them oscillatory movement for a basic university physics course for engineering students at university. The proposal is based on the rediscovery strategy and the active participation of the students. It is oriented to promote in the students the development of his/her operating capacities through the systematic application of a scientific method to the study of the dynamics of different types of pendulums. The criteria used to design the proposal have their fundament in the identification of psychological, didactic and epistemological variables that determine the way the student makes his/her learning process. The epistemological Gowin's V was applied as a tool to determine goals and to organizer activities. (Author) 23 refs

The neural mechanisms of re-experiencing mental fatigue sensation: a magnetoencephalography study.

Directory of Open Access Journals (Sweden)

Akira Ishii

Full Text Available There have been several studies which have tried to clarify the neural mechanisms of fatigue sensation; however fatigue sensation has multiple aspects. We hypothesized that past experience related to fatigue sensation is an important factor which contributes to future formation of fatigue sensation through the transfer to memories that are located within specific brain structures. Therefore, we aimed to investigate the neural mechanisms of fatigue sensation related to memory. In the present study, we investigated the neural activity caused by re-experiencing the fatigue sensation that had been experienced during a fatigue-inducing session. Thirteen healthy volunteers participated in fatigue and non-fatigue experiments in a crossover fashion. In the fatigue experiment, they performed a 2-back test session for 40 min to induce fatigue sensation, a rest session for 15 min to recover from fatigue, and a magnetoencephalography (MEG session in which they were asked to re-experience the state of their body with fatigue that they had experienced in the 2-back test session. In the non-fatigue experiment, the participants performed a free session for 15 min, a rest session for 15 min, and an MEG session in which they were asked to re-experience the state of their body without fatigue that they had experienced in the free session. Spatial filtering analyses of oscillatory brain activity showed that the delta band power in the left Brodmann's area (BA 39, alpha band power in the right pulvinar nucleus and the left BA 40, and beta band power in the left BA 40 were lower when they re-experienced the fatigue sensation than when they re-experienced the fatigue-free sensation, indicating that these brain regions are related to re-experiencing the fatigue sensation. Our findings may help clarify the neural mechanisms underlying fatigue sensation.

The neural mechanisms of re-experiencing mental fatigue sensation: a magnetoencephalography study.

Science.gov (United States)

Ishii, Akira; Karasuyama, Takuma; Kikuchi, Taiki; Tanaka, Masaaki; Yamano, Emi; Watanabe, Yasuyoshi

2015-01-01

There have been several studies which have tried to clarify the neural mechanisms of fatigue sensation; however fatigue sensation has multiple aspects. We hypothesized that past experience related to fatigue sensation is an important factor which contributes to future formation of fatigue sensation through the transfer to memories that are located within specific brain structures. Therefore, we aimed to investigate the neural mechanisms of fatigue sensation related to memory. In the present study, we investigated the neural activity caused by re-experiencing the fatigue sensation that had been experienced during a fatigue-inducing session. Thirteen healthy volunteers participated in fatigue and non-fatigue experiments in a crossover fashion. In the fatigue experiment, they performed a 2-back test session for 40 min to induce fatigue sensation, a rest session for 15 min to recover from fatigue, and a magnetoencephalography (MEG) session in which they were asked to re-experience the state of their body with fatigue that they had experienced in the 2-back test session. In the non-fatigue experiment, the participants performed a free session for 15 min, a rest session for 15 min, and an MEG session in which they were asked to re-experience the state of their body without fatigue that they had experienced in the free session. Spatial filtering analyses of oscillatory brain activity showed that the delta band power in the left Brodmann's area (BA) 39, alpha band power in the right pulvinar nucleus and the left BA 40, and beta band power in the left BA 40 were lower when they re-experienced the fatigue sensation than when they re-experienced the fatigue-free sensation, indicating that these brain regions are related to re-experiencing the fatigue sensation. Our findings may help clarify the neural mechanisms underlying fatigue sensation.

Bray–Liebhafsky oscillatory reaction in the radiofrequency electromagnetic field

Energy Technology Data Exchange (ETDEWEB)

Stanisavljev, Dragomir R., E-mail: dragisa@ffh.bg.ac.rs [Faculty of Physical Chemistry, University of Belgrade, Studentski trg 12-16, P.O. Box 473, 11001 Belgrade (Serbia); Velikić, Zoran [Institute of Physics, University of Belgrade, Pregrevica 118, Zemun (Serbia); Veselinović, Dragan S.; Jacić, Nevena V.; Milenković, Maja C. [Faculty of Physical Chemistry, University of Belgrade, Studentski trg 12-16, P.O. Box 473, 11001 Belgrade (Serbia)

2014-09-30

Highlights: • Oscillatory Bray–Liebhafsky reaction is coupled with the radiofrequency radiation. • The effects of radiofrequency field on oscillatory parameters are investigated. • Radiofrequency power of up to the 0.2 W did not produced observable changes. • The explanation related with dissipative and capacitive effects is given. • Open the possibility of investigations of reactive effects on biological systems. - Abstract: Oscillatory Bray–Liebhafsky (BL) reaction is capacitively coupled with the electromagnetic radiation in the frequency range 60–110 MHz. Because of the specific reaction dynamics characterized by several characteristic parameters (induction period, period between chemical oscillations and their amplitude) it served as a good model system for the investigation of the effects of radiofrequent (RF) radiation. RF power of up to 0.2 W did not produce observable changes of the BL reaction parameters in the limit of the experiment reproductivity. Results indicate that, under the given experimental conditions, both dissipative and reactive properties of the solution are not considerably coupled with the RF electrical field.

The Nonlinear Distortions in the Oscillatory System of Generator on CFOA

Directory of Open Access Journals (Sweden)

Yuriy Konstantinovich Rybin

2012-01-01

Full Text Available In recent years, many articles came out where one could find the analysis of oscillatory systems of electric sinusoid signals generators with amplifiers called CFOA—current feedback operational amplifiers. As a rule, the analysis of such systems is made by applying mathematical modeling methods on the basis of the amplifier linear model, which does not allow estimating advantages and disadvantages of the systems realized with those amplifiers in comparison with classical systems. A nonlinear model of a current feedback operational amplifier (CFOA is introduced in the paper; nonlinearity of “current mirror” is reflected in the form of current double limiting. The analysis of two known oscillatory systems has been carried out with the use of this non-linear model. Dependence between current limiting level, output voltage amplitude, and maximum oscillation frequency has been obtained. The paper shows that output current limiting under current output connection of capacitive load reduces frequency range and output voltage amplitude considerably and increases harmonic distortions in comparison with classical oscillatory systems. The research done has found that the application of new amplifiers does not give considerable advantages to the oscillatory systems with CFOA.

Oscillatory wake potential with exchange-correlation in plasmas

Science.gov (United States)

Khan, Arroj A.; Zeba, I.; Jamil, M.; Asif, M.

2017-12-01

The oscillatory wake potential of a moving test charge is studied in quantum dusty plasmas. The plasma system consisting of electrons, ions and negatively charged dust species is embedded in an ambient magnetic field. The modified equation of dispersion is derived using a Quantum Hydrodynamic Model for magnetized plasmas. The quantum effects are inculcated through Fermi degenerate pressure, the tunneling effect and exchange-correlation effects. The study of oscillatory wake is important to know the existence of silence zones in space and astrophysical objects as well as for crystal formation. The graphical description of the potential depicts the significance of the exchange and correlation effects arising through spin and other variables on the wake potential.

Correlation of neural activity with behavioral kinematics reveals distinct sensory encoding and evidence accumulation processes during active tactile sensing.

Science.gov (United States)

Delis, Ioannis; Dmochowski, Jacek P; Sajda, Paul; Wang, Qi

2018-03-23

Many real-world decisions rely on active sensing, a dynamic process for directing our sensors (e.g. eyes or fingers) across a stimulus to maximize information gain. Though ecologically pervasive, limited work has focused on identifying neural correlates of the active sensing process. In tactile perception, we often make decisions about an object/surface by actively exploring its shape/texture. Here we investigate the neural correlates of active tactile decision-making by simultaneously measuring electroencephalography (EEG) and finger kinematics while subjects interrogated a haptic surface to make perceptual judgments. Since sensorimotor behavior underlies decision formation in active sensing tasks, we hypothesized that the neural correlates of decision-related processes would be detectable by relating active sensing to neural activity. Novel brain-behavior correlation analysis revealed that three distinct EEG components, localizing to right-lateralized occipital cortex (LOC), middle frontal gyrus (MFG), and supplementary motor area (SMA), respectively, were coupled with active sensing as their activity significantly correlated with finger kinematics. To probe the functional role of these components, we fit their single-trial-couplings to decision-making performance using a hierarchical-drift-diffusion-model (HDDM), revealing that the LOC modulated the encoding of the tactile stimulus whereas the MFG predicted the rate of information integration towards a choice. Interestingly, the MFG disappeared from components uncovered from control subjects performing active sensing but not required to make perceptual decisions. By uncovering the neural correlates of distinct stimulus encoding and evidence accumulation processes, this study delineated, for the first time, the functional role of cortical areas in active tactile decision-making. Copyright © 2018 Elsevier Inc. All rights reserved.

Neural dynamics during repetitive visual stimulation

Science.gov (United States)

Tsoneva, Tsvetomira; Garcia-Molina, Gary; Desain, Peter

2015-12-01

Objective. Steady-state visual evoked potentials (SSVEPs), the brain responses to repetitive visual stimulation (RVS), are widely utilized in neuroscience. Their high signal-to-noise ratio and ability to entrain oscillatory brain activity are beneficial for their applications in brain-computer interfaces, investigation of neural processes underlying brain rhythmic activity (steady-state topography) and probing the causal role of brain rhythms in cognition and emotion. This paper aims at analyzing the space and time EEG dynamics in response to RVS at the frequency of stimulation and ongoing rhythms in the delta, theta, alpha, beta, and gamma bands. Approach.We used electroencephalography (EEG) to study the oscillatory brain dynamics during RVS at 10 frequencies in the gamma band (40-60 Hz). We collected an extensive EEG data set from 32 participants and analyzed the RVS evoked and induced responses in the time-frequency domain. Main results. Stable SSVEP over parieto-occipital sites was observed at each of the fundamental frequencies and their harmonics and sub-harmonics. Both the strength and the spatial propagation of the SSVEP response seem sensitive to stimulus frequency. The SSVEP was more localized around the parieto-occipital sites for higher frequencies (>54 Hz) and spread to fronto-central locations for lower frequencies. We observed a strong negative correlation between stimulation frequency and relative power change at that frequency, the first harmonic and the sub-harmonic components over occipital sites. Interestingly, over parietal sites for sub-harmonics a positive correlation of relative power change and stimulation frequency was found. A number of distinct patterns in delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz) and beta (15-30 Hz) bands were also observed. The transient response, from 0 to about 300 ms after stimulation onset, was accompanied by increase in delta and theta power over fronto-central and occipital sites, which returned to baseline

Strategies influence neural activity for feedback learning across child and adolescent development.

Science.gov (United States)

Peters, Sabine; Koolschijn, P Cédric M P; Crone, Eveline A; Van Duijvenvoorde, Anna C K; Raijmakers, Maartje E J

2014-09-01

Learning from feedback is an important aspect of executive functioning that shows profound improvements during childhood and adolescence. This is accompanied by neural changes in the feedback-learning network, which includes pre-supplementary motor area (pre- SMA)/anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), superior parietal cortex (SPC), and the basal ganglia. However, there can be considerable differences within age ranges in performance that are ascribed to differences in strategy use. This is problematic for traditional approaches of analyzing developmental data, in which age groups are assumed to be homogenous in strategy use. In this study, we used latent variable models to investigate if underlying strategy groups could be detected for a feedback-learning task and whether there were differences in neural activation patterns between strategies. In a sample of 268 participants between ages 8 to 25 years, we observed four underlying strategy groups, which were cut across age groups and varied in the optimality of executive functioning. These strategy groups also differed in neural activity during learning; especially the most optimal performing group showed more activity in DLPFC, SPC and pre-SMA/ACC compared to the other groups. However, age differences remained an important contributor to neural activation, even when correcting for strategy. These findings contribute to the debate of age versus performance predictors of neural development, and highlight the importance of studying individual differences in strategy use when studying development. Copyright © 2014 Elsevier Ltd. All rights reserved.

Active voltammetric microsensors with neural signal processing.

Energy Technology Data Exchange (ETDEWEB)

Vogt, M. C.

1998-12-11

Many industrial and environmental processes, including bioremediation, would benefit from the feedback and control information provided by a local multi-analyte chemical sensor. For most processes, such a sensor would need to be rugged enough to be placed in situ for long-term remote monitoring, and inexpensive enough to be fielded in useful numbers. The multi-analyte capability is difficult to obtain from common passive sensors, but can be provided by an active device that produces a spectrum-type response. Such new active gas microsensor technology has been developed at Argonne National Laboratory. The technology couples an electrocatalytic ceramic-metallic (cermet) microsensor with a voltammetric measurement technique and advanced neural signal processing. It has been demonstrated to be flexible, rugged, and very economical to produce and deploy. Both narrow interest detectors and wide spectrum instruments have been developed around this technology. Much of this technology's strength lies in the active measurement technique employed. The technique involves applying voltammetry to a miniature electrocatalytic cell to produce unique chemical ''signatures'' from the analytes. These signatures are processed with neural pattern recognition algorithms to identify and quantify the components in the analyte. The neural signal processing allows for innovative sampling and analysis strategies to be employed with the microsensor. In most situations, the whole response signature from the voltammogram can be used to identify, classify, and quantify an analyte, without dissecting it into component parts. This allows an instrument to be calibrated once for a specific gas or mixture of gases by simple exposure to a multi-component standard rather than by a series of individual gases. The sampled unknown analytes can vary in composition or in concentration, the calibration, sensing, and processing methods of these active voltammetric microsensors can

Active voltammetric microsensors with neural signal processing

Science.gov (United States)

Vogt, Michael C.; Skubal, Laura R.

1999-02-01

Many industrial and environmental processes, including bioremediation, would benefit from the feedback and control information provided by a local multi-analyte chemical sensor. For most processes, such a sensor would need to be rugged enough to be placed in situ for long-term remote monitoring, and inexpensive enough to be fielded in useful numbers. The multi-analyte capability is difficult to obtain from common passive sensors, but can be provided by an active device that produces a spectrum-type response. Such new active gas microsensor technology has been developed at Argonne National Laboratory. The technology couples an electrocatalytic ceramic-metallic (cermet) microsensor with a voltammetric measurement technique and advanced neural signal processing. It has been demonstrated to be flexible, rugged, and very economical to produce and deploy. Both narrow interest detectors and wide spectrum instruments have been developed around this technology. Much of this technology's strength lies in the active measurement technique employed. The technique involves applying voltammetry to a miniature electrocatalytic cell to produce unique chemical 'signatures' from the analytes. These signatures are processed with neural pattern recognition algorithms to identify and quantify the components in the analyte. The neural signal processing allows for innovative sampling and analysis strategies to be employed with the microsensor. In most situations, the whole response signature from the voltammogram can be used to identify, classify, and quantify an analyte, without dissecting it into component parts. This allows an instrument to be calibrated once for a specific gas or mixture of gases by simple exposure to a multi-component standard rather than by a series of individual gases. The sampled unknown analytes can vary in composition or in concentration; the calibration, sensing, and processing methods of these active voltammetric microsensors can detect, recognize, and

Cognitive-affective neural plasticity following active-controlled mindfulness intervention

DEFF Research Database (Denmark)

Allen, Micah Galen

Mindfulness meditation is a set of attention-based, regulatory and self-inquiry training regimes. Although the impact of mindfulness meditation training (MT) on self-regulation is well established, the neural mechanisms supporting such plasticity are poorly understood. MT is thought to act through...... prefrontal cortex (mPFC), and right anterior insula during negative valence processing. Our findings highlight the importance of active control in MT research, indicate unique neural mechanisms for progressive stages of mindfulness training, and suggest that optimal application of MT may differ depending...

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

OpenAIRE

Francisco Javier Ordóñez; Daniel Roggen

2016-01-01

Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we pro...

High baseline activity in inferior temporal cortex improves neural and behavioral discriminability during visual categorization

Science.gov (United States)

Emadi, Nazli; Rajimehr, Reza; Esteky, Hossein

2014-01-01

Spontaneous firing is a ubiquitous property of neural activity in the brain. Recent literature suggests that this baseline activity plays a key role in perception. However, it is not known how the baseline activity contributes to neural coding and behavior. Here, by recording from the single neurons in the inferior temporal cortex of monkeys performing a visual categorization task, we thoroughly explored the relationship between baseline activity, the evoked response, and behavior. Specifically we found that a low-frequency (baseline activity. This enhancement of the baseline activity was then followed by an increase in the neural selectivity and the response reliability and eventually a higher behavioral performance. PMID:25404900

Differences in Neural Activation as a Function of Risk-taking Task Parameters

Directory of Open Access Journals (Sweden)

Eliza eCongdon

2013-09-01

Full Text Available Despite evidence supporting a relationship between impulsivity and naturalistic risk-taking, the relationship of impulsivity with laboratory-based measures of risky decision-making remains unclear. One factor contributing to this gap in our understanding is the degree to which different risky decision-making tasks vary in their details. We conducted an fMRI investigation of the Angling Risk Task (ART, which is an improved behavioral measure of risky decision-making. In order to examine whether the observed pattern of neural activation was specific to the ART or generalizable, we also examined correlates of the Balloon Analogue Risk Taking (BART task in the same sample of 23 healthy adults. Exploratory analyses were conducted to examine the relationship between neural activation, performance, impulsivity and self-reported risk-taking. While activation in a valuation network was associated with reward tracking during the ART but not the BART, increased fronto-cingulate activation was seen during risky choice trials in the BART as compared to the ART. Thus, neural activation during risky decision-making trials differed between the two tasks, and this observation was likely driven by differences in task parameters, namely the absence vs. presence of ambiguity and/or stationary vs. increasing probability of loss on the ART and BART, respectively. Exploratory association analyses suggest that sensitivity of neural response to the magnitude of potential reward during the ART was associated with a suboptimal performance strategy, higher scores on a scale of dysfunctional impulsivity and a greater likelihood of engaging in risky behaviors, while this pattern was not seen for the BART. Our results suggest that the ART is decomposable and associated with distinct patterns of neural activation; this represents a preliminary step towards characterizing a behavioral measure of risky decision-making that may support a better understanding of naturalistic risk-taking.

Microglia modulate hippocampal neural precursor activity in response to exercise and aging.

Science.gov (United States)

Vukovic, Jana; Colditz, Michael J; Blackmore, Daniel G; Ruitenberg, Marc J; Bartlett, Perry F

2012-05-09

Exercise has been shown to positively augment adult hippocampal neurogenesis; however, the cellular and molecular pathways mediating this effect remain largely unknown. Previous studies have suggested that microglia may have the ability to differentially instruct neurogenesis in the adult brain. Here, we used transgenic Csf1r-GFP mice to investigate whether hippocampal microglia directly influence the activation of neural precursor cells. Our results revealed that an exercise-induced increase in neural precursor cell activity was mediated via endogenous microglia and abolished when these cells were selectively removed from hippocampal cultures. Conversely, microglia from the hippocampi of animals that had exercised were able to activate latent neural precursor cells when added to neurosphere preparations from sedentary mice. We also investigated the role of CX(3)CL1, a chemokine that is known to provide a more neuroprotective microglial phenotype. Intraparenchymal infusion of a blocking antibody against the CX(3)CL1 receptor, CX(3)CR1, but not control IgG, dramatically reduced the neurosphere formation frequency in mice that had exercised. While an increase in soluble CX(3)CL1 was observed following running, reduced levels of this chemokine were found in the aged brain. Lower levels of CX(3)CL1 with advancing age correlated with the natural decline in neural precursor cell activity, a state that could be partially alleviated through removal of microglia. These findings provide the first direct evidence that endogenous microglia can exert a dual and opposing influence on neural precursor cell activity within the hippocampus, and that signaling through the CX(3)CL1-CX(3)CR1 axis critically contributes toward this process.

Oscillatory ripples, evaluation of ancient wave climates and ...

African Journals Online (AJOL)

Oscillatory ripples, evaluation of ancient wave climates and epierogeny in the Anambra ... conditions, epierogenic patterns and paleogeographic history of the basins. ... shallow and marked by low to moderate hydrodynamic energy conditions.

Modeling oscillatory dynamics in brain microcircuits as a way to help uncover neurological disease mechanisms: A proposal

Energy Technology Data Exchange (ETDEWEB)

Skinner, F. K. [Toronto Western Research Institute, University Health Network, Krembil Discovery Tower, Toronto Western Hospital, 60 Leonard Street, 7th floor, 7KD411, Toronto, Ontario M5T 2S8 (Canada); Department of Medicine (Neurology), University of Toronto, 200 Elizabeth Street, Toronto, Ontario M5G 2C4 (Canada); Department of Physiology, University of Toronto Medical Sciences Building, 3rd Floor, 1 King' s College Circle, Toronto, Ontario M5S 1A8 (Canada); Ferguson, K. A. [Toronto Western Research Institute, University Health Network, Krembil Discovery Tower, Toronto Western Hospital, 60 Leonard Street, 7th floor, 7KD411, Toronto, Ontario M5T 2S8 (Canada); Department of Physiology, University of Toronto Medical Sciences Building, 3rd Floor, 1 King' s College Circle, Toronto, Ontario M5S 1A8 (Canada)

2013-12-15

There is an undisputed need and requirement for theoretical and computational studies in Neuroscience today. Furthermore, it is clear that oscillatory dynamical output from brain networks is representative of various behavioural states, and it is becoming clear that one could consider these outputs as measures of normal and pathological brain states. Although mathematical modeling of oscillatory dynamics in the context of neurological disease exists, it is a highly challenging endeavour because of the many levels of organization in the nervous system. This challenge is coupled with the increasing knowledge of cellular specificity and network dysfunction that is associated with disease. Recently, whole hippocampus in vitro preparations from control animals have been shown to spontaneously express oscillatory activities. In addition, when using preparations derived from animal models of disease, these activities show particular alterations. These preparations present an opportunity to address challenges involved with using models to gain insight because of easier access to simultaneous cellular and network measurements, and pharmacological modulations. We propose that by developing and using models with direct links to experiment at multiple levels, which at least include cellular and microcircuit, a cycling can be set up and used to help us determine critical mechanisms underlying neurological disease. We illustrate our proposal using our previously developed inhibitory network models in the context of these whole hippocampus preparations and show the importance of having direct links at multiple levels.

Dynamics of a class of cellular neural networks with time-varying delays

International Nuclear Information System (INIS)

Huang Lihong; Huang Chuangxia; Liu Bingwen

2005-01-01

Employing Brouwer's fixed point theorem, matrix theory, a continuation theorem of the coincidence degree and inequality analysis, the authors make a further investigation of a class of cellular neural networks with delays (DCNNs) in this Letter. A family of sufficient conditions are given for checking global exponential stability and the existence of periodic solutions of DCNNs. These results have important leading significance in the design and applications of globally stable DCNNs and periodic oscillatory DCNNs. Our results extend and improve some earlier publications

Information content of neural networks with self-control and variable activity

International Nuclear Information System (INIS)

Bolle, D.; Amari, S.I.; Dominguez Carreta, D.R.C.; Massolo, G.

2001-01-01

A self-control mechanism for the dynamics of neural networks with variable activity is discussed using a recursive scheme for the time evolution of the local field. It is based upon the introduction of a self-adapting time-dependent threshold as a function of both the neural and pattern activity in the network. This mechanism leads to an improvement of the information content of the network as well as an increase of the storage capacity and the basins of attraction. Different architectures are considered and the results are compared with numerical simulations

Effects from Unsaturated Zone Flow during Oscillatory Hydraulic Testing

Science.gov (United States)

Lim, D.; Zhou, Y.; Cardiff, M. A.; Barrash, W.

2014-12-01

In analyzing pumping tests on unconfined aquifers, the impact of the unsaturated zone is often neglected. Instead, desaturation at the water table is often treated as a free-surface boundary, which is simple and allows for relatively fast computation. Richards' equation models, which account for unsaturated flow, can be compared with saturated flow models to validate the use of Darcy's Law. In this presentation, we examine the appropriateness of using fast linear steady-periodic models based on linearized water table conditions in order to simulate oscillatory pumping tests in phreatic aquifers. We compare oscillatory pumping test models including: 1) a 2-D radially-symmetric phreatic aquifer model with a partially penetrating well, simulated using both Darcy's Law and Richards' Equation in COMSOL; and 2) a linear phase-domain numerical model developed in MATLAB. Both COMSOL and MATLAB models are calibrated to match oscillatory pumping test data collected in the summer of 2013 at the Boise Hydrogeophysical Research Site (BHRS), and we examine the effect of model type on the associated parameter estimates. The results of this research will aid unconfined aquifer characterization efforts and help to constrain the impact of the simplifying physical assumptions often employed during test analysis.

Neural activity in the hippocampus predicts individual visual short-term memory capacity.

Science.gov (United States)

von Allmen, David Yoh; Wurmitzer, Karoline; Martin, Ernst; Klaver, Peter

2013-07-01

Although the hippocampus had been traditionally thought to be exclusively involved in long-term memory, recent studies raised controversial explanations why hippocampal activity emerged during short-term memory tasks. For example, it has been argued that long-term memory processes might contribute to performance within a short-term memory paradigm when memory capacity has been exceeded. It is still unclear, though, whether neural activity in the hippocampus predicts visual short-term memory (VSTM) performance. To investigate this question, we measured BOLD activity in 21 healthy adults (age range 19-27 yr, nine males) while they performed a match-to-sample task requiring processing of object-location associations (delay period  =  900 ms; set size conditions 1, 2, 4, and 6). Based on individual memory capacity (estimated by Cowan's K-formula), two performance groups were formed (high and low performers). Within whole brain analyses, we found a robust main effect of "set size" in the posterior parietal cortex (PPC). In line with a "set size × group" interaction in the hippocampus, a subsequent Finite Impulse Response (FIR) analysis revealed divergent hippocampal activation patterns between performance groups: Low performers (mean capacity  =  3.63) elicited increased neural activity at set size two, followed by a drop in activity at set sizes four and six, whereas high performers (mean capacity  =  5.19) showed an incremental activity increase with larger set size (maximal activation at set size six). Our data demonstrated that performance-related neural activity in the hippocampus emerged below capacity limit. In conclusion, we suggest that hippocampal activity reflected successful processing of object-location associations in VSTM. Neural activity in the PPC might have been involved in attentional updating. Copyright © 2013 Wiley Periodicals, Inc.

Global exponential stability and periodicity of reaction-diffusion recurrent neural networks with distributed delays and Dirichlet boundary conditions

International Nuclear Information System (INIS)

Lu Junguo; Lu Linji

2009-01-01

In this paper, global exponential stability and periodicity of a class of reaction-diffusion recurrent neural networks with distributed delays and Dirichlet boundary conditions are studied by constructing suitable Lyapunov functionals and utilizing some inequality techniques. We first prove global exponential convergence to 0 of the difference between any two solutions of the original neural networks, the existence and uniqueness of equilibrium is the direct results of this procedure. This approach is different from the usually used one where the existence, uniqueness of equilibrium and stability are proved in two separate steps. Secondly, we prove periodicity. Sufficient conditions ensuring the existence, uniqueness, and global exponential stability of the equilibrium and periodic solution are given. These conditions are easy to verify and our results play an important role in the design and application of globally exponentially stable neural circuits and periodic oscillatory neural circuits.

Evidence-Based Systematic Review: Effects of Neuromuscular Electrical Stimulation on Swallowing and Neural Activation

Science.gov (United States)

Clark, Heather; Lazarus, Cathy; Arvedson, Joan; Schooling, Tracy; Frymark, Tobi

2009-01-01

Purpose: To systematically review the literature examining the effects of neuromuscular electrical stimulation (NMES) on swallowing and neural activation. The review was conducted as part of a series examining the effects of oral motor exercises (OMEs) on speech, swallowing, and neural activation. Method: A systematic search was conducted to…

The situated HKB model: how sensorimotor spatial coupling can alter oscillatory brain dynamics

Science.gov (United States)

Aguilera, Miguel; Bedia, Manuel G.; Santos, Bruno A.; Barandiaran, Xabier E.

2013-01-01

Despite the increase of both dynamic and embodied/situated approaches in cognitive science, there is still little research on how coordination dynamics under a closed sensorimotor loop might induce qualitatively different patterns of neural oscillations compared to those found in isolated systems. We take as a departure point the Haken-Kelso-Bunz (HKB) model, a generic model for dynamic coordination between two oscillatory components, which has proven useful for a vast range of applications in cognitive science and whose dynamical properties are well understood. In order to explore the properties of this model under closed sensorimotor conditions we present what we call the situated HKB model: a robotic model that performs a gradient climbing task and whose “brain” is modeled by the HKB equation. We solve the differential equations that define the agent-environment coupling for increasing values of the agent's sensitivity (sensor gain), finding different behavioral strategies. These results are compared with two different models: a decoupled HKB with no sensory input and a passively-coupled HKB that is also decoupled but receives a structured input generated by a situated agent. We can precisely quantify and qualitatively describe how the properties of the system, when studied in coupled conditions, radically change in a manner that cannot be deduced from the decoupled HKB models alone. We also present the notion of neurodynamic signature as the dynamic pattern that correlates with a specific behavior and we show how only a situated agent can display this signature compared to an agent that simply receives the exact same sensory input. To our knowledge, this is the first analytical solution of the HKB equation in a sensorimotor loop and qualitative and quantitative analytic comparison of spatially coupled vs. decoupled oscillatory controllers. Finally, we discuss the limitations and possible generalization of our model to contemporary neuroscience and

The Situated HKB Model: how sensorimotor spatial coupling can alter oscillatory brain dynamics

Directory of Open Access Journals (Sweden)

Miguel eAguilera

2013-08-01

Full Text Available Despite the increase both of dynamic and embodied/situated approaches in cognitive science, there is still little research on how coordination dynamics under a closed sensorimotor loop might induce qualitatively different patterns of neural oscillations compared to those found in isolated systems. We take as a departure point the HKB model, a generic model for dynamic coordination between two oscillatory components, which has proven useful for a vast range of applications in cognitive science and whose dynamical properties are well understood. In order to explore the properties of this model under closed sensorimotor conditions we present what we call the situated HKB model: a robotic model that performs a gradient climbing task and whose "brain" is modelled by the HKB equation. We solve the differential equations that define the agent-environment coupling for increasing values of the agent's sensitivity (sensor gain, finding different behavioural strategies. These results are compared with two different models: a decoupled HKB with no sensory input and a passively-coupled HKB that is also decoupled but receives a structured input generated by a situated agent. We can precisely quantify and qualitatively describe how the properties of the system, when studied in coupled conditions, radically change in a manner that cannot be deduced from the decoupled HKB models alone. We also present the notion of neurodynamic signature as the dynamic pattern that correlates with a specific behaviour and we show how only a situated agent can display this signature compared to an agent that simply receives the exact same sensory input.To our knowledge, this is the first analytical solution of the HKB equation in a sensorimotor loop and qualitative and quantitative analytic comparison of spatially coupled vs. decoupled oscillatory controllers. Finally, we discuss the limitations and possible generalization of our model to contemporary neuroscience and philosophy

Isolating Discriminant Neural Activity in the Presence of Eye Movements and Concurrent Task Demands

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Jon Touryan

2017-07-01

Full Text Available A growing number of studies use the combination of eye-tracking and electroencephalographic (EEG measures to explore the neural processes that underlie visual perception. In these studies, fixation-related potentials (FRPs are commonly used to quantify early and late stages of visual processing that follow the onset of each fixation. However, FRPs reflect a mixture of bottom-up (sensory-driven and top-down (goal-directed processes, in addition to eye movement artifacts and unrelated neural activity. At present there is little consensus on how to separate this evoked response into its constituent elements. In this study we sought to isolate the neural sources of target detection in the presence of eye movements and over a range of concurrent task demands. Here, participants were asked to identify visual targets (Ts amongst a grid of distractor stimuli (Ls, while simultaneously performing an auditory N-back task. To identify the discriminant activity, we used independent components analysis (ICA for the separation of EEG into neural and non-neural sources. We then further separated the neural sources, using a modified measure-projection approach, into six regions of interest (ROIs: occipital, fusiform, temporal, parietal, cingulate, and frontal cortices. Using activity from these ROIs, we identified target from non-target fixations in all participants at a level similar to other state-of-the-art classification techniques. Importantly, we isolated the time course and spectral features of this discriminant activity in each ROI. In addition, we were able to quantify the effect of cognitive load on both fixation-locked potential and classification performance across regions. Together, our results show the utility of a measure-projection approach for separating task-relevant neural activity into meaningful ROIs within more complex contexts that include eye movements.

Oscillatory theta activity during memory formation and its impact on overnight consolidation: a missing link?

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Heib, Dominik P J; Hoedlmoser, Kerstin; Anderer, Peter; Gruber, Georg; Zeitlhofer, Josef; Schabus, Manuel

2015-08-01

Sleep has been shown to promote memory consolidation driven by certain oscillatory patterns, such as sleep spindles. However, sleep does not consolidate all newly encoded information uniformly but rather "selects" certain memories for consolidation. It is assumed that such selection depends on salience tags attached to the new memories before sleep. However, little is known about the underlying neuronal processes reflecting presleep memory tagging. The current study sought to address the question of whether event-related changes in spectral theta power (theta ERSP) during presleep memory formation could reflect memory tagging that influences subsequent consolidation during sleep. Twenty-four participants memorized 160 word pairs before sleep; in a separate laboratory visit, they performed a nonlearning control task. Memory performance was tested twice, directly before and after 8 hr of sleep. Results indicate that participants who improved their memory performance overnight displayed stronger theta ERSP during the memory task in comparison with the control task. They also displayed stronger memory task-related increases in fast sleep spindle activity. Furthermore, presleep theta activity was directly linked to fast sleep spindle activity, indicating that processes during memory formation might indeed reflect memory tagging that influences subsequent consolidation during sleep. Interestingly, our results further indicate that the suggested relation between sleep spindles and overnight performance change is not as direct as once believed. Rather, it appears to be mediated by processes beginning during presleep memory formation. We conclude that theta ERSP during presleep memory formation reflects cortico-hippocampal interactions that lead to a better long-term accessibility by tagging memories for sleep spindle-related reprocessing.

Oscillatory integrals on Hilbert spaces and Schroedinger equation with magnetic fields

International Nuclear Information System (INIS)

Albeverio, S.; Brzezniak, Z.

1994-01-01

We extend the theory of oscillatory integrals on Hilbert spaces (the mathematical version of ''Feynman path integrals'') to cover more general integrable functions, preserving the property of the integrals to have converging finite dimensional approximations. We give an application to the representation of solutions of the time dependent Schroedinger equation with a scalar and a magnetic potential by oscillatory integrals on Hilbert spaces. A relation with Ramer's functional in the corresponding probabilistic setting is found. (orig.)

Neural Activity During The Formation Of A Giant Auditory Synapse

NARCIS (Netherlands)

M.C. Sierksma (Martijn)

2018-01-01

markdownabstractThe formation of synapses is a critical step in the development of the brain. During this developmental stage neural activity propagates across the brain from synapse to synapse. This activity is thought to instruct the precise, topological connectivity found in the sensory central

Cueing vocabulary during sleep increases theta activity during later recognition testing.

Science.gov (United States)

Schreiner, Thomas; Göldi, Maurice; Rasch, Björn

2015-11-01

Neural oscillations in the theta band have repeatedly been implicated in successful memory encoding and retrieval. Several recent studies have shown that memory retrieval can be facilitated by reactivating memories during their consolidation during sleep. However, it is still unknown whether reactivation during sleep also enhances subsequent retrieval-related neural oscillations. We have recently demonstrated that foreign vocabulary cues presented during sleep improve later recall of the associated translations. Here, we examined the effect of cueing foreign vocabulary during sleep on oscillatory activity during subsequent recognition testing after sleep. We show that those words that were replayed during sleep after learning (cued words) elicited stronger centroparietal theta activity during recognition as compared to noncued words. The reactivation-induced increase in theta oscillations during later recognition testing might reflect a strengthening of individual memory traces and the integration of the newly learned words into the mental lexicon by cueing during sleep. © 2015 Society for Psychophysiological Research.

Population-wide distributions of neural activity during perceptual decision-making

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Machens, Christian

2018-01-01

Cortical activity involves large populations of neurons, even when it is limited to functionally coherent areas. Electrophysiological recordings, on the other hand, involve comparatively small neural ensembles, even when modern-day techniques are used. Here we review results which have started to fill the gap between these two scales of inquiry, by shedding light on the statistical distributions of activity in large populations of cells. We put our main focus on data recorded in awake animals that perform simple decision-making tasks and consider statistical distributions of activity throughout cortex, across sensory, associative, and motor areas. We transversally review the complexity of these distributions, from distributions of firing rates and metrics of spike-train structure, through distributions of tuning to stimuli or actions and of choice signals, and finally the dynamical evolution of neural population activity and the distributions of (pairwise) neural interactions. This approach reveals shared patterns of statistical organization across cortex, including: (i) long-tailed distributions of activity, where quasi-silence seems to be the rule for a majority of neurons; that are barely distinguishable between spontaneous and active states; (ii) distributions of tuning parameters for sensory (and motor) variables, which show an extensive extrapolation and fragmentation of their representations in the periphery; and (iii) population-wide dynamics that reveal rotations of internal representations over time, whose traces can be found both in stimulus-driven and internally generated activity. We discuss how these insights are leading us away from the notion of discrete classes of cells, and are acting as powerful constraints on theories and models of cortical organization and population coding. PMID:23123501

Oscillatory regime of avalanche particle detectors

International Nuclear Information System (INIS)

Lukin, K.A.; Cerdeira, H.A.; Colavita, A.A.

1995-06-01

We describe the model of an avalanche high energy particle detector consisting of two pn-junctions, connected through an intrinsic semiconductor with a reverse biased voltage applied. We show that this detector is able to generate the oscillatory response on the single particle passage through the structure. The possibility of oscillations leading to chaotic behaviour is pointed out. (author). 15 refs, 7 figs

On the origin of reproducible sequential activity in neural circuits

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Afraimovich, V. S.; Zhigulin, V. P.; Rabinovich, M. I.

2004-12-01

Robustness and reproducibility of sequential spatio-temporal responses is an essential feature of many neural circuits in sensory and motor systems of animals. The most common mathematical images of dynamical regimes in neural systems are fixed points, limit cycles, chaotic attractors, and continuous attractors (attractive manifolds of neutrally stable fixed points). These are not suitable for the description of reproducible transient sequential neural dynamics. In this paper we present the concept of a stable heteroclinic sequence (SHS), which is not an attractor. SHS opens the way for understanding and modeling of transient sequential activity in neural circuits. We show that this new mathematical object can be used to describe robust and reproducible sequential neural dynamics. Using the framework of a generalized high-dimensional Lotka-Volterra model, that describes the dynamics of firing rates in an inhibitory network, we present analytical results on the existence of the SHS in the phase space of the network. With the help of numerical simulations we confirm its robustness in presence of noise in spite of the transient nature of the corresponding trajectories. Finally, by referring to several recent neurobiological experiments, we discuss possible applications of this new concept to several problems in neuroscience.

GH mediates exercise-dependent activation of SVZ neural precursor cells in aged mice.

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Daniel G Blackmore

Full Text Available Here we demonstrate, both in vivo and in vitro, that growth hormone (GH mediates precursor cell activation in the subventricular zone (SVZ of the aged (12-month-old brain following exercise, and that GH signaling stimulates precursor activation to a similar extent to exercise. Our results reveal that both addition of GH in culture and direct intracerebroventricular infusion of GH stimulate neural precursor cells in the aged brain. In contrast, no increase in neurosphere numbers was observed in GH receptor null animals following exercise. Continuous infusion of a GH antagonist into the lateral ventricle of wild-type animals completely abolished the exercise-induced increase in neural precursor cell number. Given that the aged brain does not recover well after injury, we investigated the direct effect of exercise and GH on neural precursor cell activation following irradiation. This revealed that physical exercise as well as infusion of GH promoted repopulation of neural precursor cells in irradiated aged animals. Conversely, infusion of a GH antagonist during exercise prevented recovery of precursor cells in the SVZ following irradiation.

GH Mediates Exercise-Dependent Activation of SVZ Neural Precursor Cells in Aged Mice

Science.gov (United States)

Blackmore, Daniel G.; Vukovic, Jana; Waters, Michael J.; Bartlett, Perry F.

2012-01-01

Here we demonstrate, both in vivo and in vitro, that growth hormone (GH) mediates precursor cell activation in the subventricular zone (SVZ) of the aged (12-month-old) brain following exercise, and that GH signaling stimulates precursor activation to a similar extent to exercise. Our results reveal that both addition of GH in culture and direct intracerebroventricular infusion of GH stimulate neural precursor cells in the aged brain. In contrast, no increase in neurosphere numbers was observed in GH receptor null animals following exercise. Continuous infusion of a GH antagonist into the lateral ventricle of wild-type animals completely abolished the exercise-induced increase in neural precursor cell number. Given that the aged brain does not recover well after injury, we investigated the direct effect of exercise and GH on neural precursor cell activation following irradiation. This revealed that physical exercise as well as infusion of GH promoted repopulation of neural precursor cells in irradiated aged animals. Conversely, infusion of a GH antagonist during exercise prevented recovery of precursor cells in the SVZ following irradiation. PMID:23209615

Modelling and measurements of sand transport processes over full-scale ripples in oscillatory flow

NARCIS (Netherlands)

van der Werf, Jebbe J.; Ribberink, Jan S.; O'Donoghue, Tom; Doucette, Jeffrey C.

2006-01-01

A new series of laboratory experiments was performed in the Aberdeen Oscillatory Flow Tunnel (AOFT) and the Large Oscillating Water Tunnel (LOWT) to investigate time-averaged suspended sand concentrations and transport rates over rippled beds in regular and irregular oscillatory flow. The

Bias-dependent oscillatory electron transport of monatomic sulfur chains

KAUST Repository

Yu, Jing-Xin; Cheng, Yan; Sanvito, Stefano; Chen, Xiang-Rong

2012-01-01

The bias-dependent oscillatory electron transport of monatomic sulfur chains sandwiched between gold electrodes is investigated with density functional theory and non-equilibrium Green's function method. At zero bias, in contrast to the typical odd-even oscillations observed in most metallic chains, we find that the conductance oscillates with a period of four atoms. However, as the bias voltage is increased the current displays a two-atom periodicity. This emerges gradually, first for the longer chains and then, at voltages larger than 0.7 V, for lengths. The oscillatory behaviors are analyzed by the density of states and the energy-dependent and bias-dependent transmission coefficients. © 2012 American Institute of Physics.

Bias-dependent oscillatory electron transport of monatomic sulfur chains

KAUST Repository

Yu, Jing-Xin

2012-01-01

The bias-dependent oscillatory electron transport of monatomic sulfur chains sandwiched between gold electrodes is investigated with density functional theory and non-equilibrium Green\\'s function method. At zero bias, in contrast to the typical odd-even oscillations observed in most metallic chains, we find that the conductance oscillates with a period of four atoms. However, as the bias voltage is increased the current displays a two-atom periodicity. This emerges gradually, first for the longer chains and then, at voltages larger than 0.7 V, for lengths. The oscillatory behaviors are analyzed by the density of states and the energy-dependent and bias-dependent transmission coefficients. © 2012 American Institute of Physics.

Global exponential stability and periodicity of reaction-diffusion delayed recurrent neural networks with Dirichlet boundary conditions

International Nuclear Information System (INIS)

Lu Junguo

2008-01-01

In this paper, the global exponential stability and periodicity for a class of reaction-diffusion delayed recurrent neural networks with Dirichlet boundary conditions are addressed by constructing suitable Lyapunov functionals and utilizing some inequality techniques. We first prove global exponential converge to 0 of the difference between any two solutions of the original reaction-diffusion delayed recurrent neural networks with Dirichlet boundary conditions, the existence and uniqueness of equilibrium is the direct results of this procedure. This approach is different from the usually used one where the existence, uniqueness of equilibrium and stability are proved in two separate steps. Furthermore, we prove periodicity of the reaction-diffusion delayed recurrent neural networks with Dirichlet boundary conditions. Sufficient conditions ensuring the global exponential stability and the existence of periodic oscillatory solutions for the reaction-diffusion delayed recurrent neural networks with Dirichlet boundary conditions are given. These conditions are easy to check and have important leading significance in the design and application of reaction-diffusion recurrent neural networks with delays. Finally, two numerical examples are given to show the effectiveness of the obtained results

Modulation of alpha and gamma oscillations related to retrospectively orienting attention within working memory.

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Poch, Claudia; Campo, Pablo; Barnes, Gareth R

2014-07-01

Selective attention mechanisms allow us to focus on information that is relevant to the current behavior and, equally important, ignore irrelevant information. An influential model proposes that oscillatory neural activity in the alpha band serves as an active functional inhibitory mechanism. Recent studies have shown that, in the same way that attention can be selectively oriented to bias sensory processing in favor of relevant stimuli in perceptual tasks, it is also possible to retrospectively orient attention to internal representations held in working memory. However, these studies have not explored the associated oscillatory phenomena. In the current study, we analysed the patterns of neural oscillatory activity recorded with magnetoencephalography while participants performed a change detection task, in which a spatial retro-cue was presented during the maintenance period, indicating which item or items were relevant for subsequent retrieval. Participants benefited from retro-cues in terms of accuracy and reaction time. Retro-cues also modulated oscillatory activity in the alpha and gamma frequency bands. We observed greater alpha activity in a ventral visual region ipsilateral to the attended hemifield, thus supporting its suppressive role, i.e., a functional disengagement of task-irrelevant regions. Accompanying this modulation, we found an increase in gamma activity contralateral to the attended hemifield, which could reflect attentional orienting and selective processing. These findings suggest that the oscillatory mechanisms underlying attentional orienting to representations held in working memory are similar to those engaged when attention is oriented in the perceptual space. © 2014 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Effect of short-term escitalopram treatment on neural activation during emotional processing.

Science.gov (United States)

Maron, Eduard; Wall, Matt; Norbury, Ray; Godlewska, Beata; Terbeck, Sylvia; Cowen, Philip; Matthews, Paul; Nutt, David J

2016-01-01

Recent functional magnetic resonance (fMRI) imaging studies have revealed that subchronic medication with escitalopram leads to significant reduction in both amygdala and medial frontal gyrus reactivity during processing of emotional faces, suggesting that escitalopram may have a distinguishable modulatory effect on neural activation as compared with other serotonin-selective antidepressants. In this fMRI study we aimed to explore whether short-term medication with escitalopram in healthy volunteers is associated with reduced neural response to emotional processing, and whether this effect is predicted by drug plasma concentration. The neural response to fearful and happy faces was measured before and on day 7 of treatment with escitalopram (10mg) in 15 healthy volunteers and compared with those in a control unmedicated group (n=14). Significantly reduced activation to fearful, but not to happy facial expressions was observed in the bilateral amygdala, cingulate and right medial frontal gyrus following escitalopram medication. This effect was not correlated with plasma drug concentration. In accordance with previous data, we showed that escitalopram exerts its rapid direct effect on emotional processing via attenuation of neural activation in pathways involving medial frontal gyrus and amygdala, an effect that seems to be distinguishable from that of other SSRIs. © The Author(s) 2015.

Neural Activations of Guided Imagery and Music in Negative Emotional Processing: A Functional MRI Study.

Science.gov (United States)

Lee, Sang Eun; Han, Yeji; Park, HyunWook

2016-01-01

The Bonny Method of Guided Imagery and Music uses music and imagery to access and explore personal emotions associated with episodic memories. Understanding the neural mechanism of guided imagery and music (GIM) as combined stimuli for emotional processing informs clinical application. We performed functional magnetic resonance imaging (fMRI) to demonstrate neural mechanisms of GIM for negative emotional processing when personal episodic memory is recalled and re-experienced through GIM processes. Twenty-four healthy volunteers participated in the study, which used classical music and verbal instruction stimuli to evoke negative emotions. To analyze the neural mechanism, activated regions associated with negative emotional and episodic memory processing were extracted by conducting volume analyses for the contrast between GIM and guided imagery (GI) or music (M). The GIM stimuli showed increased activation over the M-only stimuli in five neural regions associated with negative emotional and episodic memory processing, including the left amygdala, left anterior cingulate gyrus, left insula, bilateral culmen, and left angular gyrus (AG). Compared with GI alone, GIM showed increased activation in three regions associated with episodic memory processing in the emotional context, including the right posterior cingulate gyrus, bilateral parahippocampal gyrus, and AG. No neural regions related to negative emotional and episodic memory processing showed more activation for M and GI than for GIM. As a combined multimodal stimulus, GIM may increase neural activations related to negative emotions and episodic memory processing. Findings suggest a neural basis for GIM with personal episodic memories affecting cortical and subcortical structures and functions. © the American Music Therapy Association 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

[Recent results in research on oscillatory chemical reactions].

Science.gov (United States)

Poros, Eszter; Kurin-Csörgei, Krisztina

2014-01-01

The mechanisms of the complicated periodical phenomenas in the nature (e.g. hearth beat, sleep cycle, circadian rhythms, etc) could be understood with using the laws of nonlinear chemical systems. In this article the newest result in the research of the subfield of nonlinear chemical dynamics aimed at constructing oscillatory chemical reactions, which are novel either in composition or in configuration, are presented. In the introductory part the concept of chemical periodicity is defined, then the forms as it can appear in time and space and the methods of their study are discussed. Detailed description of the experimental work that has resulted in two significant discoveries is provided. A method was developed to design pH-oscillators which are capable of operating under close conditions. The batch pH-oscillators are more convenient to use in some proposed applications than the equivalent CSTR variant. A redox oscillator that is new in composition was found. The permanganate oxidation of some amino acids was shown to take place according to oscillatory kinetics in a narrow range of the experimental parameters. The KMnO4 - glycine - Na2HPO4 system represents the first example in the family of manganese based oscillators where amino acids is involved. In the conclusion formal analogies between the simple chemical and some more complicated biological oscillatory phenomena are mentioned and the possibility of modeling periodic processes with the use of information gained from the studies of chemical oscillations is pointed out.

High baseline activity in inferior temporal cortex improves neural and behavioral discriminability during visual categorization

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Nazli eEmadi

2014-11-01

Full Text Available Spontaneous firing is a ubiquitous property of neural activity in the brain. Recent literature suggests that this baseline activity plays a key role in perception. However, it is not known how the baseline activity contributes to neural coding and behavior. Here, by recording from the single neurons in the inferior temporal cortex of monkeys performing a visual categorization task, we thoroughly explored the relationship between baseline activity, the evoked response, and behavior. Specifically we found that a low-frequency (< 8 Hz oscillation in the spike train, prior and phase-locked to the stimulus onset, was correlated with increased gamma power and neuronal baseline activity. This enhancement of the baseline activity was then followed by an increase in the neural selectivity and the response reliability and eventually a higher behavioral performance.

The Olivo-cerebellar System: A Key to understanding the functional significance of intrinsic oscillatory brain properties

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Rodolfo R Llinas

2014-01-01

Full Text Available The reflexological view of brain function (Sherrington 1906 has played a crucial role in defining both the nature of connectivity and the role of the synaptic interactions among neuronal circuits. One implicit assumption of this view, however, has been that CNS function is fundamentally driven by sensory input. This view was questioned as early as the beginning of the last century when a possible role for intrinsic activity in CNS function was proposed by Thomas Graham Brow (Brown 1911; Brown 1914. However, little progress was made in addressing intrinsic neuronal properties in vertebrates until the discovery of calcium conductances in vertebrate central neurons leading dendritic electroresponsiveness (Llinas and Hess 1976, Llinas and Sugimori 1980a and b and subthreshold neuronal oscillation in mammalian inferior olive (IO neurons (Llinas and Yarom 1981; Llinas and Yarom 1981.This happened in parallel with a similar set of findings concerning invertebrate neuronal system (Marder and Bucher 2001. The generalization into a more global view of intrinsic rhythmicity, at forebrain level, occurred initially with the demonstration that the thalamus has similar oscillatory properties (Llinas and Jahnsen 1982 and the ionic properties responsible for some oscillatory activity were, in fact, similar to those in the IO (Jahnsen and Llinas 1984; Llinas 1988. Thus lending support to the view that not only motricity, but cognitive properties, are organized as coherent oscillatory states (Pare, deCurtis et al. 1992; Singer 1993; Hardcastle 1997; Llinas, Ribary et al. 1998; Varela, Lachaux et al. 2001.

Acute stress evokes sexually dimorphic, stressor-specific patterns of neural activation across multiple limbic brain regions in adult rats.

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Sood, Ankit; Chaudhari, Karina; Vaidya, Vidita A

2018-03-01

Stress enhances the risk for psychiatric disorders such as anxiety and depression. Stress responses vary across sex and may underlie the heightened vulnerability to psychopathology in females. Here, we examined the influence of acute immobilization stress (AIS) and a two-day short-term forced swim stress (FS) on neural activation in multiple cortical and subcortical brain regions, implicated as targets of stress and in the regulation of neuroendocrine stress responses, in male and female rats using Fos as a neural activity marker. AIS evoked a sex-dependent pattern of neural activation within the cingulate and infralimbic subdivisions of the medial prefrontal cortex (mPFC), lateral septum (LS), habenula, and hippocampal subfields. The degree of neural activation in the mPFC, LS, and habenula was higher in males. Female rats exhibited reduced Fos positive cell numbers in the dentate gyrus hippocampal subfield, an effect not observed in males. We addressed whether the sexually dimorphic neural activation pattern noted following AIS was also observed with the short-term stress of FS. In the paraventricular nucleus of the hypothalamus and the amygdala, FS similar to AIS resulted in robust increases in neural activation in both sexes. The pattern of neural activation evoked by FS was distinct across sexes, with a heightened neural activation noted in the prelimbic mPFC subdivision and hippocampal subfields in females and differed from the pattern noted with AIS. This indicates that the sex differences in neural activation patterns observed within stress-responsive brain regions are dependent on the nature of stressor experience.

Oscillatory magnetoconductance of quantum double-well channels

International Nuclear Information System (INIS)

Rojo, A.G.; Kumar, N.; Balseiro, C.A.

1988-07-01

The recently observed flux-periodic interference effect between parallel quantum double-well channels is theoretically studied in a discrete model that takes into account tunneling between channels. We obtain oscillatory magnetoconductance with small modulations which is attributable to the tunneling. Our treatment includes the effect of evanescent modes. (author). 7 refs, 2 figs

Oscillatory behaviors and hierarchical assembly of contractile structures in intercalating cells

International Nuclear Information System (INIS)

Fernandez-Gonzalez, Rodrigo; Zallen, Jennifer A

2011-01-01

Fluctuations in the size of the apical cell surface have been associated with apical constriction and tissue invagination. However, it is currently not known if apical oscillatory behaviors are a unique property of constricting cells or if they constitute a universal feature of the force balance between cells in multicellular tissues. Here, we set out to determine whether oscillatory cell behaviors occur in parallel with cell intercalation during the morphogenetic process of axis elongation in the Drosophila embryo. We applied multi-color, time-lapse imaging of living embryos and SIESTA, an integrated tool for automated and semi-automated cell segmentation, tracking, and analysis of image sequences. Using SIESTA, we identified cycles of contraction and expansion of the apical surface in intercalating cells and characterized them at the molecular, cellular, and tissue scales. We demonstrate that apical oscillations are anisotropic, and this anisotropy depends on the presence of intact cell–cell junctions and spatial cues provided by the anterior–posterior patterning system. Oscillatory cell behaviors during axis elongation are associated with the hierarchical assembly and disassembly of contractile actomyosin structures at the medial cortex of the cell, with actin localization preceding myosin II and with the localization of both proteins preceding changes in cell shape. We discuss models to explain how the architecture of cytoskeletal networks regulates their contractile behavior and the mechanisms that give rise to oscillatory cell behaviors in intercalating cells

Approximate damped oscillatory solutions and error estimates for the perturbed Klein–Gordon equation

International Nuclear Information System (INIS)

Ye, Caier; Zhang, Weiguo

2015-01-01

Highlights: • Analyze the dynamical behavior of the planar dynamical system corresponding to the perturbed Klein–Gordon equation. • Present the relations between the properties of traveling wave solutions and the perturbation coefficient. • Obtain all explicit expressions of approximate damped oscillatory solutions. • Investigate error estimates between exact damped oscillatory solutions and the approximate solutions and give some numerical simulations. - Abstract: The influence of perturbation on traveling wave solutions of the perturbed Klein–Gordon equation is studied by applying the bifurcation method and qualitative theory of dynamical systems. All possible approximate damped oscillatory solutions for this equation are obtained by using undetermined coefficient method. Error estimates indicate that the approximate solutions are meaningful. The results of numerical simulations also establish our analysis

Causal Learning and Explanation of Deep Neural Networks via Autoencoded Activations

OpenAIRE

Harradon, Michael; Druce, Jeff; Ruttenberg, Brian

2018-01-01

Deep neural networks are complex and opaque. As they enter application in a variety of important and safety critical domains, users seek methods to explain their output predictions. We develop an approach to explaining deep neural networks by constructing causal models on salient concepts contained in a CNN. We develop methods to extract salient concepts throughout a target network by using autoencoders trained to extract human-understandable representations of network activations. We then bu...

Enhancing neural activity to drive respiratory plasticity following cervical spinal cord injury

Science.gov (United States)

Hormigo, Kristiina M.; Zholudeva, Lyandysha V.; Spruance, Victoria M.; Marchenko, Vitaliy; Cote, Marie-Pascale; Vinit, Stephane; Giszter, Simon; Bezdudnaya, Tatiana; Lane, Michael A.

2016-01-01

Cervical spinal cord injury (SCI) results in permanent life-altering sensorimotor deficits, among which impaired breathing is one of the most devastating and life-threatening. While clinical and experimental research has revealed that some spontaneous respiratory improvement (functional plasticity) can occur post-SCI, the extent of the recovery is limited and significant deficits persist. Thus, increasing effort is being made to develop therapies that harness and enhance this neuroplastic potential to optimize long-term recovery of breathing in injured individuals. One strategy with demonstrated therapeutic potential is the use of treatments that increase neural and muscular activity (e.g. locomotor training, neural and muscular stimulation) and promote plasticity. With a focus on respiratory function post-SCI, this review will discuss advances in the use of neural interfacing strategies and activity-based treatments, and highlights some recent results from our own research. PMID:27582085

Efficient universal computing architectures for decoding neural activity.

Directory of Open Access Journals (Sweden)

Benjamin I Rapoport

Full Text Available The ability to decode neural activity into meaningful control signals for prosthetic devices is critical to the development of clinically useful brain- machine interfaces (BMIs. Such systems require input from tens to hundreds of brain-implanted recording electrodes in order to deliver robust and accurate performance; in serving that primary function they should also minimize power dissipation in order to avoid damaging neural tissue; and they should transmit data wirelessly in order to minimize the risk of infection associated with chronic, transcutaneous implants. Electronic architectures for brain- machine interfaces must therefore minimize size and power consumption, while maximizing the ability to compress data to be transmitted over limited-bandwidth wireless channels. Here we present a system of extremely low computational complexity, designed for real-time decoding of neural signals, and suited for highly scalable implantable systems. Our programmable architecture is an explicit implementation of a universal computing machine emulating the dynamics of a network of integrate-and-fire neurons; it requires no arithmetic operations except for counting, and decodes neural signals using only computationally inexpensive logic operations. The simplicity of this architecture does not compromise its ability to compress raw neural data by factors greater than [Formula: see text]. We describe a set of decoding algorithms based on this computational architecture, one designed to operate within an implanted system, minimizing its power consumption and data transmission bandwidth; and a complementary set of algorithms for learning, programming the decoder, and postprocessing the decoded output, designed to operate in an external, nonimplanted unit. The implementation of the implantable portion is estimated to require fewer than 5000 operations per second. A proof-of-concept, 32-channel field-programmable gate array (FPGA implementation of this portion

Exponential stability of Cohen-Grossberg neural networks with a general class of activation functions

International Nuclear Information System (INIS)

Wan Anhua; Wang Miansen; Peng Jigen; Qiao Hong

2006-01-01

In this Letter, the dynamics of Cohen-Grossberg neural networks model are investigated. The activation functions are only assumed to be Lipschitz continuous, which provide a much wider application domain for neural networks than the previous results. By means of the extended nonlinear measure approach, new and relaxed sufficient conditions for the existence, uniqueness and global exponential stability of equilibrium of the neural networks are obtained. Moreover, an estimate for the exponential convergence rate of the neural networks is precisely characterized. Our results improve those existing ones

Intermittent reductions in respiratory neural activity elicit spinal TNF-α-independent, atypical PKC-dependent inactivity-induced phrenic motor facilitation.

Science.gov (United States)

Baertsch, Nathan A; Baker-Herman, Tracy L

2015-04-15

In many neural networks, mechanisms of compensatory plasticity respond to prolonged reductions in neural activity by increasing cellular excitability or synaptic strength. In the respiratory control system, a prolonged reduction in synaptic inputs to the phrenic motor pool elicits a TNF-α- and atypical PKC-dependent form of spinal plasticity known as inactivity-induced phrenic motor facilitation (iPMF). Although iPMF may be elicited by a prolonged reduction in respiratory neural activity, iPMF is more efficiently induced when reduced respiratory neural activity (neural apnea) occurs intermittently. Mechanisms giving rise to iPMF following intermittent neural apnea are unknown. The purpose of this study was to test the hypothesis that iPMF following intermittent reductions in respiratory neural activity requires spinal TNF-α and aPKC. Phrenic motor output was recorded in anesthetized and ventilated rats exposed to brief intermittent (5, ∼1.25 min), brief sustained (∼6.25 min), or prolonged sustained (30 min) neural apnea. iPMF was elicited following brief intermittent and prolonged sustained neural apnea, but not following brief sustained neural apnea. Unlike iPMF following prolonged neural apnea, spinal TNF-α was not required to initiate iPMF during intermittent neural apnea; however, aPKC was still required for its stabilization. These results suggest that different patterns of respiratory neural activity induce iPMF through distinct cellular mechanisms but ultimately converge on a similar downstream pathway. Understanding the diverse cellular mechanisms that give rise to inactivity-induced respiratory plasticity may lead to development of novel therapeutic strategies to treat devastating respiratory control disorders when endogenous compensatory mechanisms fail. Copyright © 2015 the American Physiological Society.

Solvent Fermentation From Palm Oil Mill Effluent Using Clostridium acetobutylicum In Oscillatory Flow Bioreactor

International Nuclear Information System (INIS)

Takriff, M.S.; Masngut, N.; Kadhum, A.A.H.; Kalil, M.S.; Mohammad, A.W.

2009-01-01

Acetone-butanol-ethanol (ABE) fermentation from Palm Oil Mill Effluent (POME) by C. acetobutylicum NCIMB 13357 in an oscillatory flow bioreactor was investigated. Experimental works were conducted in a U-shaped stainless steel oscillatory flow bioreactor at oscillation frequency between 0.45-0.78 Hz and a constant amplitude of 12.5 mm. Fermentations were carried out for 72 hr at 35 degree Celsius using palm oil mill effluent and reinforced clostridia medium as a growth medium in batch culture. Result of this investigation showed that POME is a viable media for ABE fermentation and oscillatory flow bioreactor has an excellent potential as an alternative fermentation device. (author)

Capacity of oscillatory associative-memory networks with error-free retrieval

International Nuclear Information System (INIS)

Nishikawa, Takashi; Lai Yingcheng; Hoppensteadt, Frank C.

2004-01-01

Networks of coupled periodic oscillators (similar to the Kuramoto model) have been proposed as models of associative memory. However, error-free retrieval states of such oscillatory networks are typically unstable, resulting in a near zero capacity. This puts the networks at disadvantage as compared with the classical Hopfield network. Here we propose a simple remedy for this undesirable property and show rigorously that the error-free capacity of our oscillatory, associative-memory networks can be made as high as that of the Hopfield network. They can thus not only provide insights into the origin of biological memory, but can also be potentially useful for applications in information science and engineering

Topological probability and connection strength induced activity in complex neural networks

International Nuclear Information System (INIS)

Du-Qu, Wei; Bo, Zhang; Dong-Yuan, Qiu; Xiao-Shu, Luo

2010-01-01

Recent experimental evidence suggests that some brain activities can be assigned to small-world networks. In this work, we investigate how the topological probability p and connection strength C affect the activities of discrete neural networks with small-world (SW) connections. Network elements are described by two-dimensional map neurons (2DMNs) with the values of parameters at which no activity occurs. It is found that when the value of p is smaller or larger, there are no active neurons in the network, no matter what the value of connection strength is; for a given appropriate connection strength, there is an intermediate range of topological probability where the activity of 2DMN network is induced and enhanced. On the other hand, for a given intermediate topological probability level, there exists an optimal value of connection strength such that the frequency of activity reaches its maximum. The possible mechanism behind the action of topological probability and connection strength is addressed based on the bifurcation method. Furthermore, the effects of noise and transmission delay on the activity of neural network are also studied. (general)

Identification of Nonlinear Oscillatory Activity Embedded in Broadband Neural Signals

Czech Academy of Sciences Publication Activity Database

Vejmelka, Martin; Paluš, Milan; Šušmáková, K.

2010-01-01

Roč. 20, č. 2 (2010), s. 117-128 ISSN 0129-0657 R&D Projects: GA MŠk 7E08027 EU Projects: European Commission(XE) 200728 - BRAINSYNC Institutional research plan: CEZ:AV0Z10300504 Keywords : nonlinear dynamical systems * oscillations * random processes * time series analysis * EEG Subject RIV: FH - Neurology Impact factor: 4.237, year: 2010

Social power and approach-related neural activity.

Science.gov (United States)

Boksem, Maarten A S; Smolders, Ruud; De Cremer, David

2012-06-01

It has been argued that power activates a general tendency to approach whereas powerlessness activates a tendency to inhibit. The assumption is that elevated power involves reward-rich environments, freedom and, as a consequence, triggers an approach-related motivational orientation and attention to rewards. In contrast, reduced power is associated with increased threat, punishment and social constraint and thereby activates inhibition-related motivation. Moreover, approach motivation has been found to be associated with increased relative left-sided frontal brain activity, while withdrawal motivation has been associated with increased right sided activations. We measured EEG activity while subjects engaged in a task priming either high or low social power. Results show that high social power is indeed associated with greater left-frontal brain activity compared to low social power, providing the first neural evidence for the theory that high power is associated with approach-related motivation. We propose a framework accounting for differences in both approach motivation and goal-directed behaviour associated with different levels of power.

What are the odds? The neural correlates of active choice during gambling

Directory of Open Access Journals (Sweden)

Bettina eStuder

2012-04-01

Full Text Available Gambling is a widespread recreational activity and requires pitting the values of potential wins and losses against their probability of occurrence. Neuropsychological research showed that betting behavior on laboratory gambling tasks is highly sensitive to focal lesions to the ventromedial prefrontal cortex (vmPFC and insula. In the current study, we assessed the neural basis of betting choices in healthy participants, using functional magnetic resonance imaging of the Roulette Betting Task. In half of the trials participants actively chose their bets; in the other half the computer dictated the bet size. Our results highlight the impact of volitional choice upon the neural substrates of gambling: Neural activity in a distributed network - including key structures of the reward circuitry (midbrain, striatum - was higher during active compared to computer-dictated bet selection. In line with neuropsychological data, the anterior insula and vmPFC were more activated during self-directed bet selection, and responses in these areas were differentially modulated by the odds of winning in the two choice conditions. In addition, responses in the vmPFC and ventral striatum were modulated by the bet size. Convergent with electrophysiological research in macaques, our results further implicate the inferior parietal cortex (IPC in the processing of the likelihood of potential outcomes: Neural responses in the IPC bilaterally reflected the probability of winning during bet selection. Moreover, the IPC was particularly sensitive to the odds of winning in the active choice condition, where this information was used to guide bet selection. Our results indicate a neglected role of the IPC in human decision-making under risk and help to integrate neuropsychological data of risk-taking following vmPFC and insula damage with models of choice derived from human neuroimaging and monkey electrophysiology.

Theories of Person Perception Predict Patterns of Neural Activity During Mentalizing.

Science.gov (United States)

Thornton, Mark A; Mitchell, Jason P

2017-08-22

Social life requires making inferences about other people. What information do perceivers spontaneously draw upon to make such inferences? Here, we test 4 major theories of person perception, and 1 synthetic theory that combines their features, to determine whether the dimensions of such theories can serve as bases for describing patterns of neural activity during mentalizing. While undergoing functional magnetic resonance imaging, participants made social judgments about well-known public figures. Patterns of brain activity were then predicted using feature encoding models that represented target people's positions on theoretical dimensions such as warmth and competence. All 5 theories of person perception proved highly accurate at reconstructing activity patterns, indicating that each could describe the informational basis of mentalizing. Cross-validation indicated that the theories robustly generalized across both targets and participants. The synthetic theory consistently attained the best performance-approximately two-thirds of noise ceiling accuracy--indicating that, in combination, the theories considered here can account for much of the neural representation of other people. Moreover, encoding models trained on the present data could reconstruct patterns of activity associated with mental state representations in independent data, suggesting the use of a common neural code to represent others' traits and states. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Abnormal neural activities of directional brain networks in patients with long-term bilateral hearing loss.

Science.gov (United States)

Xu, Long-Chun; Zhang, Gang; Zou, Yue; Zhang, Min-Feng; Zhang, Dong-Sheng; Ma, Hua; Zhao, Wen-Bo; Zhang, Guang-Yu

2017-10-13

The objective of the study is to provide some implications for rehabilitation of hearing impairment by investigating changes of neural activities of directional brain networks in patients with long-term bilateral hearing loss. Firstly, we implemented neuropsychological tests of 21 subjects (11 patients with long-term bilateral hearing loss, and 10 subjects with normal hearing), and these tests revealed significant differences between the deaf group and the controls. Then we constructed the individual specific virtual brain based on functional magnetic resonance data of participants by utilizing effective connectivity and multivariate regression methods. We exerted the stimulating signal to the primary auditory cortices of the virtual brain and observed the brain region activations. We found that patients with long-term bilateral hearing loss presented weaker brain region activations in the auditory and language networks, but enhanced neural activities in the default mode network as compared with normally hearing subjects. Especially, the right cerebral hemisphere presented more changes than the left. Additionally, weaker neural activities in the primary auditor cortices were also strongly associated with poorer cognitive performance. Finally, causal analysis revealed several interactional circuits among activated brain regions, and these interregional causal interactions implied that abnormal neural activities of the directional brain networks in the deaf patients impacted cognitive function.

Differential proliferation rhythm of neural progenitor and oligodendrocyte precursor cells in the young adult hippocampus.

Directory of Open Access Journals (Sweden)

Yoko Matsumoto

Full Text Available Oligodendrocyte precursor cells (OPCs are a unique type of glial cells that function as oligodendrocyte progenitors while constantly proliferating in the normal condition from rodents to humans. However, the functional roles they play in the adult brain are largely unknown. In this study, we focus on the manner of OPC proliferation in the hippocampus of the young adult mice. Here we report that there are oscillatory dynamics in OPC proliferation that differ from neurogenesis in the subgranular zone (SGZ; the former showed S-phase and M-phase peaks in the resting and active periods, respectively, while the latter only exhibited M-phase peak in the active period. There is coincidence between different modes of proliferation and expression of cyclin proteins that are crucial for cell cycle; cyclin D1 is expressed in OPCs, while cyclin D2 is observed in neural stem cells. Similar to neurogenesis, the proliferation of hippocampal OPCs was enhanced by voluntary exercise that leads to an increase in neuronal activity in the hippocampus. These data suggest an intriguing control of OPC proliferation in the hippocampus.

Large Amplitude Oscillatory Extension of Soft Polymeric Networks

DEFF Research Database (Denmark)

Bejenariu, Anca Gabriela; Rasmussen, Henrik K.; Skov, Anne Ladegaard

2010-01-01

sing a filament stretching rheometer (FSR) surrounded by a thermostatic chamber and equipped with a micrometric laser it is possible to measure large amplitude oscillatory elongation (LAOE) on elastomeric based networks with no base flow as in the LAOE method for polymer melts. Poly(dimethylsilox...

Oscillatory and electrohydrodynamic instabilities in flow over a ...

Indian Academy of Sciences (India)

of fluid flow past flexible surfaces is qualitatively different from the flow over rigid .... work. Oscillatory flows are unsteady, and it is important to precisely define the ..... from 5 to 16, though there is less variation in the critical stress for a steady ...

Implications of the dependence of neuronal activity on neural network states for the design of brain-machine interfaces

Directory of Open Access Journals (Sweden)

Stefano ePanzeri

2016-04-01

Full Text Available Brain-machine interfaces (BMIs can improve the quality of life of patients with sensory and motor disabilities by both decoding motor intentions expressed by neural activity, and by encoding artificially sensed information into patterns of neural activity elicited by causal interventions on the neural tissue. Yet, current BMIs can exchange relatively small amounts of information with the brain. This problem has proved difficult to overcome by simply increasing the number of recording or stimulating electrodes, because trial-to-trial variability of neural activity partly arises from intrinsic factors (collectively known as the network state that include ongoing spontaneous activity and neuromodulation, and so is shared among neurons. Here we review recent progress in characterizing the state dependence of neural responses, and in particular of how neural responses depend on endogenous slow fluctuations of network excitability. We then elaborate on how this knowledge may be used to increase the amount of information that BMIs exchange with brains. Knowledge of network state can be used to fine-tune the stimulation pattern that should reliably elicit a target neural response used to encode information in the brain, and to discount part of the trial-by-trial variability of neural responses, so that they can be decoded more accurately.

Intranasal oxytocin reduces social perception in women: Neural activation and individual variation.

Science.gov (United States)

Hecht, Erin E; Robins, Diana L; Gautam, Pritam; King, Tricia Z

2017-02-15

Most intranasal oxytocin research to date has been carried out in men, but recent studies indicate that females' responses can differ substantially from males'. This randomized, double-blind, placebo-controlled study involved an all-female sample of 28 women not using hormonal contraception. Participants viewed animations of geometric shapes depicting either random movement or social interactions such as playing, chasing, or fighting. Probe questions asked whether any shapes were "friends" or "not friends." Social videos were preceded by cues to attend to either social relationships or physical size changes. All subjects received intranasal placebo spray at scan 1. While the experimenter was not blinded to nasal spray contents at Scan 1, the participants were. Scan 2 followed a randomized, double-blind design. At scan 2, half received a second placebo dose while the other half received 24 IU of intranasal oxytocin. We measured neural responses to these animations at baseline, as well as the change in neural activity induced by oxytocin. Oxytocin reduced activation in early visual cortex and dorsal-stream motion processing regions for the social > size contrast, indicating reduced activity related to social attention. Oxytocin also reduced endorsements that shapes were "friends" or "not friends," and this significantly correlated with reduction in neural activation. Furthermore, participants who perceived fewer social relationships at baseline were more likely to show oxytocin-induced increases in a broad network of regions involved in social perception and social cognition, suggesting that lower social processing at baseline may predict more positive neural responses to oxytocin. Copyright © 2016 Elsevier Inc. All rights reserved.

Distinct Neural Activity Associated with Focused-Attention Meditation and Loving-Kindness Meditation

Science.gov (United States)

Lee, Tatia M. C.; Leung, Mei-Kei; Hou, Wai-Kai; Tang, Joey C. Y.; Yin, Jing; So, Kwok-Fai; Lee, Chack-Fan; Chan, Chetwyn C. H.

2012-01-01

This study examined the dissociable neural effects of ānāpānasati (focused-attention meditation, FAM) and mettā (loving-kindness meditation, LKM) on BOLD signals during cognitive (continuous performance test, CPT) and affective (emotion-processing task, EPT, in which participants viewed affective pictures) processing. Twenty-two male Chinese expert meditators (11 FAM experts, 11 LKM experts) and 22 male Chinese novice meditators (11 FAM novices, 11 LKM novices) had their brain activity monitored by a 3T MRI scanner while performing the cognitive and affective tasks in both meditation and baseline states. We examined the interaction between state (meditation vs. baseline) and expertise (expert vs. novice) separately during LKM and FAM, using a conjunction approach to reveal common regions sensitive to the expert meditative state. Additionally, exclusive masking techniques revealed distinct interactions between state and group during LKM and FAM. Specifically, we demonstrated that the practice of FAM was associated with expertise-related behavioral improvements and neural activation differences in attention task performance. However, the effect of state LKM meditation did not carry over to attention task performance. On the other hand, both FAM and LKM practice appeared to affect the neural responses to affective pictures. For viewing sad faces, the regions activated for FAM practitioners were consistent with attention-related processing; whereas responses of LKM experts to sad pictures were more in line with differentiating emotional contagion from compassion/emotional regulation processes. Our findings provide the first report of distinct neural activity associated with forms of meditation during sustained attention and emotion processing. PMID:22905090

Shear and loading in channels: Oscillatory shearing and edge currents of superconducting vortices

Science.gov (United States)

Wambaugh, J. F.; Marchesoni, F.; Nori, Franco

2003-04-01

Via computer simulations we study the motion of quantized magnetic flux-lines, or vortices, confined to a straight pin-free channel in a strong-pinning superconducting sample. We find that, when a constant current is applied across this system, a very unusual oscillatory shearing appears, in which the vortices moving at the edges of the channel periodically trail behind and then suddenly leapfrog past the vortices moving in the inner rows. For small enough driving forces, this oscillatory shearing dynamic phase is replaced by a continuous shearing phase in which the distance between initially-nearby vortices grows in time, quickly destroying the order of the lattice. An animation of this novel “oscillatory leapfrogging shear” effect of the vortex edge currents appears in http://www-personal.engin.umich.edu/˜nori/channel/

Orphan nuclear receptor TLX activates Wnt/β-catenin signalling to stimulate neural stem cell proliferation and self-renewal

Science.gov (United States)

Qu, Qiuhao; Sun, Guoqiang; Li, Wenwu; Yang, Su; Ye, Peng; Zhao, Chunnian; Yu, Ruth T.; Gage, Fred H.; Evans, Ronald M.; Shi, Yanhong

2010-01-01

The nuclear receptor TLX (also known as NR2E1) is essential for adult neural stem cell self-renewal; however, the molecular mechanisms involved remain elusive. Here we show that TLX activates the canonical Wnt/β-catenin pathway in adult mouse neural stem cells. Furthermore, we demonstrate that Wnt/β-catenin signalling is important in the proliferation and self-renewal of adult neural stem cells in the presence of epidermal growth factor and fibroblast growth factor. Wnt7a and active β-catenin promote neural stem cell self-renewal, whereas the deletion of Wnt7a or the lentiviral transduction of axin, a β-catenin inhibitor, led to decreased cell proliferation in adult neurogenic areas. Lentiviral transduction of active β-catenin led to increased numbers of type B neural stem cells in the subventricular zone of adult brains, whereas deletion of Wnt7a or TLX resulted in decreased numbers of neural stem cells retaining bromodeoxyuridine label in the adult brain. Both Wnt7a and active β-catenin significantly rescued a TLX (also known as Nr2e1) short interfering RNA-induced deficiency in neural stem cell proliferation. Lentiviral transduction of an active β-catenin increased cell proliferation in neurogenic areas of TLX-null adult brains markedly. These results strongly support the hypothesis that TLX acts through the Wnt/β-catenin pathway to regulate neural stem cell proliferation and self-renewal. Moreover, this study suggests that neural stem cells can promote their own self-renewal by secreting signalling molecules that act in an autocrine/paracrine mode. PMID:20010817

Orphan nuclear receptor TLX activates Wnt/beta-catenin signalling to stimulate neural stem cell proliferation and self-renewal.

Science.gov (United States)

Qu, Qiuhao; Sun, Guoqiang; Li, Wenwu; Yang, Su; Ye, Peng; Zhao, Chunnian; Yu, Ruth T; Gage, Fred H; Evans, Ronald M; Shi, Yanhong

2010-01-01

The nuclear receptor TLX (also known as NR2E1) is essential for adult neural stem cell self-renewal; however, the molecular mechanisms involved remain elusive. Here we show that TLX activates the canonical Wnt/beta-catenin pathway in adult mouse neural stem cells. Furthermore, we demonstrate that Wnt/beta-catenin signalling is important in the proliferation and self-renewal of adult neural stem cells in the presence of epidermal growth factor and fibroblast growth factor. Wnt7a and active beta-catenin promote neural stem cell self-renewal, whereas the deletion of Wnt7a or the lentiviral transduction of axin, a beta-catenin inhibitor, led to decreased cell proliferation in adult neurogenic areas. Lentiviral transduction of active beta-catenin led to increased numbers of type B neural stem cells in the subventricular zone of adult brains, whereas deletion of Wnt7a or TLX resulted in decreased numbers of neural stem cells retaining bromodeoxyuridine label in the adult brain. Both Wnt7a and active beta-catenin significantly rescued a TLX (also known as Nr2e1) short interfering RNA-induced deficiency in neural stem cell proliferation. Lentiviral transduction of an active beta-catenin increased cell proliferation in neurogenic areas of TLX-null adult brains markedly. These results strongly support the hypothesis that TLX acts through the Wnt/beta-catenin pathway to regulate neural stem cell proliferation and self-renewal. Moreover, this study suggests that neural stem cells can promote their own self-renewal by secreting signalling molecules that act in an autocrine/paracrine mode.

Adaptive neural networks control for camera stabilization with active suspension system

Directory of Open Access Journals (Sweden)

Feng Zhao

2015-08-01

Full Text Available The camera always suffers from image instability on the moving vehicle due to unintentional vibrations caused by road roughness. This article presents an adaptive neural network approach mixed with linear quadratic regulator control for a quarter-car active suspension system to stabilize the image captured area of the camera. An active suspension system provides extra force through the actuator which allows it to suppress vertical vibration of sprung mass. First, to deal with the road disturbance and the system uncertainties, radial basis function neural network is proposed to construct the map between the state error and the compensation component, which can correct the optimal state-feedback control law. The weights matrix of radial basis function neural network is adaptively tuned online. Then, the closed-loop stability and asymptotic convergence performance is guaranteed by Lyapunov analysis. Finally, the simulation results demonstrate that the proposed controller effectively suppresses the vibration of the camera and enhances the stabilization of the entire camera, where different excitations are considered to validate the system performance.

Oscillatory Dynamics Underlying Perceptual Narrowing of Native Phoneme Mapping from 6 to 12 Months of Age.

Science.gov (United States)

Ortiz-Mantilla, Silvia; Hämäläinen, Jarmo A; Realpe-Bonilla, Teresa; Benasich, April A

2016-11-30

During the first months of life, human infants process phonemic elements from all languages similarly. However, by 12 months of age, as language-specific phonemic maps are established, infants respond preferentially to their native language. This process, known as perceptual narrowing, supports neural representation and thus efficient processing of the distinctive phonemes within the sound environment. Although oscillatory mechanisms underlying processing of native and non-native phonemic contrasts were recently delineated in 6-month-old infants, the maturational trajectory of these mechanisms remained unclear. A group of typically developing infants born into monolingual English families, were followed from 6 to 12 months and presented with English and Spanish syllable contrasts varying in voice-onset time. Brain responses were recorded with high-density electroencephalogram, and sources of event-related potential generators identified at right and left auditory cortices at 6 and 12 months and also at frontal cortex at 6 months. Time-frequency analyses conducted at source level found variations in both θ and γ ranges across age. Compared with 6-month-olds, 12-month-olds' responses to native phonemes showed smaller and faster phase synchronization and less spectral power in the θ range, and increases in left phase synchrony as well as induced high-γ activity in both frontal and left auditory sources. These results demonstrate that infants become more automatized and efficient in processing their native language as they approach 12 months of age via the interplay between θ and γ oscillations. We suggest that, while θ oscillations support syllable processing, γ oscillations underlie phonemic perceptual narrowing, progressively favoring mapping of native over non-native language across the first year of life. During early language acquisition, typically developing infants gradually construct phonemic maps of their native language in auditory cortex. It is well

Novel recurrent neural network for modelling biological networks: oscillatory p53 interaction dynamics.

Science.gov (United States)

Ling, Hong; Samarasinghe, Sandhya; Kulasiri, Don

2013-12-01

Understanding the control of cellular networks consisting of gene and protein interactions and their emergent properties is a central activity of Systems Biology research. For this, continuous, discrete, hybrid, and stochastic methods have been proposed. Currently, the most common approach to modelling accurate temporal dynamics of networks is ordinary differential equations (ODE). However, critical limitations of ODE models are difficulty in kinetic parameter estimation and numerical solution of a large number of equations, making them more suited to smaller systems. In this article, we introduce a novel recurrent artificial neural network (RNN) that addresses above limitations and produces a continuous model that easily estimates parameters from data, can handle a large number of molecular interactions and quantifies temporal dynamics and emergent systems properties. This RNN is based on a system of ODEs representing molecular interactions in a signalling network. Each neuron represents concentration change of one molecule represented by an ODE. Weights of the RNN correspond to kinetic parameters in the system and can be adjusted incrementally during network training. The method is applied to the p53-Mdm2 oscillation system - a crucial component of the DNA damage response pathways activated by a damage signal. Simulation results indicate that the proposed RNN can successfully represent the behaviour of the p53-Mdm2 oscillation system and solve the parameter estimation problem with high accuracy. Furthermore, we presented a modified form of the RNN that estimates parameters and captures systems dynamics from sparse data collected over relatively large time steps. We also investigate the robustness of the p53-Mdm2 system using the trained RNN under various levels of parameter perturbation to gain a greater understanding of the control of the p53-Mdm2 system. Its outcomes on robustness are consistent with the current biological knowledge of this system. As more

Constitutively active Notch1 converts cranial neural crest-derived frontonasal mesenchyme to perivascular cells in vivo

Directory of Open Access Journals (Sweden)

Sophie R. Miller

2017-03-01

Full Text Available Perivascular/mural cells originate from either the mesoderm or the cranial neural crest. Regardless of their origin, Notch signalling is necessary for their formation. Furthermore, in both chicken and mouse, constitutive Notch1 activation (via expression of the Notch1 intracellular domain is sufficient in vivo to convert trunk mesoderm-derived somite cells to perivascular cells, at the expense of skeletal muscle. In experiments originally designed to investigate the effect of premature Notch1 activation on the development of neural crest-derived olfactory ensheathing glial cells (OECs, we used in ovo electroporation to insert a tetracycline-inducible NotchΔE construct (encoding a constitutively active mutant of mouse Notch1 into the genome of chicken cranial neural crest cell precursors, and activated NotchΔE expression by doxycycline injection at embryonic day 4. NotchΔE-targeted cells formed perivascular cells within the frontonasal mesenchyme, and expressed a perivascular marker on the olfactory nerve. Hence, constitutively activating Notch1 is sufficient in vivo to drive not only somite cells, but also neural crest-derived frontonasal mesenchyme and perhaps developing OECs, to a perivascular cell fate. These results also highlight the plasticity of neural crest-derived mesenchyme and glia.

Cognitive emotion regulation in children: Reappraisal of emotional faces modulates neural source activity in a frontoparietal network.

Science.gov (United States)

Wessing, Ida; Rehbein, Maimu A; Romer, Georg; Achtergarde, Sandra; Dobel, Christian; Zwitserlood, Pienie; Fürniss, Tilman; Junghöfer, Markus

2015-06-01

Emotion regulation has an important role in child development and psychopathology. Reappraisal as cognitive regulation technique can be used effectively by children. Moreover, an ERP component known to reflect emotional processing called late positive potential (LPP) can be modulated by children using reappraisal and this modulation is also related to children's emotional adjustment. The present study seeks to elucidate the neural generators of such LPP effects. To this end, children aged 8-14 years reappraised emotional faces, while neural activity in an LPP time window was estimated using magnetoencephalography-based source localization. Additionally, neural activity was correlated with two indexes of emotional adjustment and age. Reappraisal reduced activity in the left dorsolateral prefrontal cortex during down-regulation and enhanced activity in the right parietal cortex during up-regulation. Activity in the visual cortex decreased with increasing age, more adaptive emotion regulation and less anxiety. Results demonstrate that reappraisal changed activity within a frontoparietal network in children. Decreasing activity in the visual cortex with increasing age is suggested to reflect neural maturation. A similar decrease with adaptive emotion regulation and less anxiety implies that better emotional adjustment may be associated with an advance in neural maturation. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Oscillatory flow chemical reactors

Directory of Open Access Journals (Sweden)

Slavnić Danijela S.

2014-01-01

Full Text Available Global market competition, increase in energy and other production costs, demands for high quality products and reduction of waste are forcing pharmaceutical, fine chemicals and biochemical industries, to search for radical solutions. One of the most effective ways to improve the overall production (cost reduction and better control of reactions is a transition from batch to continuous processes. However, the reactions of interests for the mentioned industry sectors are often slow, thus continuous tubular reactors would be impractically long for flow regimes which provide sufficient heat and mass transfer and narrow residence time distribution. The oscillatory flow reactors (OFR are newer type of tube reactors which can offer solution by providing continuous operation with approximately plug flow pattern, low shear stress rates and enhanced mass and heat transfer. These benefits are the result of very good mixing in OFR achieved by vortex generation. OFR consists of cylindrical tube containing equally spaced orifice baffles. Fluid oscillations are superimposed on a net (laminar flow. Eddies are generated when oscillating fluid collides with baffles and passes through orifices. Generation and propagation of vortices create uniform mixing in each reactor cavity (between baffles, providing an overall flow pattern which is close to plug flow. Oscillations can be created by direct action of a piston or a diaphragm on fluid (or alternatively on baffles. This article provides an overview of oscillatory flow reactor technology, its operating principles and basic design and scale - up characteristics. Further, the article reviews the key research findings in heat and mass transfer, shear stress, residence time distribution in OFR, presenting their advantages over the conventional reactors. Finally, relevant process intensification examples from pharmaceutical, polymer and biofuels industries are presented.

Bifurcations of propellant burning rate at oscillatory pressure

Energy Technology Data Exchange (ETDEWEB)

Novozhilov, Boris V. [N. N. Semenov Institute of Chemical Physics, Russian Academy of Science, 4 Kosygina St., Moscow 119991 (Russian Federation)

2006-06-15

A new phenomenon, the disparity between pressure and propellant burning rate frequencies, has revealed in numerical studies of propellant burning rate response to oscillatory pressure. As is clear from the linear approximation, under small pressure amplitudes, h, pressure and propellant burning rate oscillations occur with equal period T (T-solution). In the paper, however, it is shown that at a certain critical value of the parameter h the system in hand undergoes a bifurcation so that the T-solution converts to oscillations with period 2T (2T-solution). When the bifurcation parameter h increases, the subsequent behavior of the system becomes complicated. It is obtained a sequence of period doubling to 4T-solution and 8T-solution. Beyond a certain value of the bifurcation parameter h an apparently fully chaotic solution is found. These effects undoubtedly should be taken into account in studies of oscillatory processes in combustion chambers. (Abstract Copyright [2006], Wiley Periodicals, Inc.)

A continuous time-resolved measure decoded from EEG oscillatory activity predicts working memory task performance.

Science.gov (United States)

Astrand, Elaine

2018-06-01

Working memory (WM), crucial for successful behavioral performance in most of our everyday activities, holds a central role in goal-directed behavior. As task demands increase, inducing higher WM load, maintaining successful behavioral performance requires the brain to work at the higher end of its capacity. Because it is depending on both external and internal factors, individual WM load likely varies in a continuous fashion. The feasibility to extract such a continuous measure in time that correlates to behavioral performance during a working memory task remains unsolved. Multivariate pattern decoding was used to test whether a decoder constructed from two discrete levels of WM load can generalize to produce a continuous measure that predicts task performance. Specifically, a linear regression with L2-regularization was chosen with input features from EEG oscillatory activity recorded from healthy participants while performing the n-back task, [Formula: see text]. The feasibility to extract a continuous time-resolved measure that correlates positively to trial-by-trial working memory task performance is demonstrated (r  =  0.47, p  performance before action (r  =  0.49, p  <  0.05). We show that the extracted continuous measure enables to study the temporal dynamics of the complex activation pattern of WM encoding during the n-back task. Specifically, temporally precise contributions of different spectral features are observed which extends previous findings of traditional univariate approaches. These results constitute an important contribution towards a wide range of applications in the field of cognitive brain-machine interfaces. Monitoring mental processes related to attention and WM load to reduce the risk of committing errors in high-risk environments could potentially prevent many devastating consequences or using the continuous measure as neurofeedback opens up new possibilities to develop novel rehabilitation techniques for

3D LDV Measurements in Oscillatory Boundary Layers

Science.gov (United States)

Mier, J. M.; Garcia, M. H.

2012-12-01

The oscillatory boundary layer represents a particular case of unsteady wall-bounded flows in which fluid particles follow a periodic sinusoidal motion. Unlike steady boundary layer flows, the oscillatory flow regime and bed roughness character change in time along the period for every cycle, a characteristic that introduces a high degree of complexity in the analysis of these flows. Governing equations can be derived from the general Navier-Stokes equations for the motion of fluids, from which the exact solution for the laminar oscillatory boundary layer is obtained (also known as the 2nd Stokes problem). No exact solution exists for the turbulent case, thus, understanding of the main flow characteristics comes from experimental work. Several researchers have reported experimental work in oscillatory boundary layers since the 1960's; however, larger scale facilities and the development of newer measurement techniques with improved temporal and spatial resolution in recent years provides a unique opportunity to achieve a better understanding about this type of flows. Several experiments were performed in the Large Oscillatory Water and Sediment Tunnel (LOWST) facility at the Ven Te Chow Hydrosystems Laboratory, for a range of Reynolds wave numbers between 6x10^4 3D Laser Doppler Velocimetry (LDV) system was used to measure instantaneous flow velocities with a temporal resolution up to ~ 1,000 Hz. It was mounted on a 3-axis traverse with a spatial resolution of 0.01 mm in all three directions. The closest point to the bottom was measured at z = 0.2 mm (z+ ≈ 4), which allowed to capture boundary layer features with great detail. In order to achieve true 3D measurements, 2 probes were used on a perpendicular configuration, such that u and w components were measured from a probe on the side of the flume and v component was measured from a probe pointing down through and access window on top of the flume. The top probe was submerged in a water container, such that the

The neural basis of the bystander effect--the influence of group size on neural activity when witnessing an emergency.

Science.gov (United States)

Hortensius, Ruud; de Gelder, Beatrice

2014-06-01

Naturalistic observation and experimental studies in humans and other primates show that observing an individual in need automatically triggers helping behavior. The aim of the present study is to clarify the neurofunctional basis of social influences on individual helping behavior. We investigate whether when participants witness an emergency, while performing an unrelated color-naming task in an fMRI scanner, the number of bystanders present at the emergency influences neural activity in regions related to action preparation. The results show a decrease in activity with the increase in group size in the left pre- and postcentral gyri and left medial frontal gyrus. In contrast, regions related to visual perception and attention show an increase in activity. These results demonstrate the neural mechanisms of social influence on automatic action preparation that is at the core of helping behavior when witnessing an emergency. Copyright © 2014 Elsevier Inc. All rights reserved.

A Parallel Supercomputer Implementation of a Biological Inspired Neural Network and its use for Pattern Recognition

International Nuclear Information System (INIS)

De Ladurantaye, Vincent; Lavoie, Jean; Bergeron, Jocelyn; Parenteau, Maxime; Lu Huizhong; Pichevar, Ramin; Rouat, Jean

2012-01-01

A parallel implementation of a large spiking neural network is proposed and evaluated. The neural network implements the binding by synchrony process using the Oscillatory Dynamic Link Matcher (ODLM). Scalability, speed and performance are compared for 2 implementations: Message Passing Interface (MPI) and Compute Unified Device Architecture (CUDA) running on clusters of multicore supercomputers and NVIDIA graphical processing units respectively. A global spiking list that represents at each instant the state of the neural network is described. This list indexes each neuron that fires during the current simulation time so that the influence of their spikes are simultaneously processed on all computing units. Our implementation shows a good scalability for very large networks. A complex and large spiking neural network has been implemented in parallel with success, thus paving the road towards real-life applications based on networks of spiking neurons. MPI offers a better scalability than CUDA, while the CUDA implementation on a GeForce GTX 285 gives the best cost to performance ratio. When running the neural network on the GTX 285, the processing speed is comparable to the MPI implementation on RQCHP's Mammouth parallel with 64 notes (128 cores).

Shape perception simultaneously up- and downregulates neural activity in the primary visual cortex.

Science.gov (United States)

Kok, Peter; de Lange, Floris P

2014-07-07

An essential part of visual perception is the grouping of local elements (such as edges and lines) into coherent shapes. Previous studies have shown that this grouping process modulates neural activity in the primary visual cortex (V1) that is signaling the local elements [1-4]. However, the nature of this modulation is controversial. Some studies find that shape perception reduces neural activity in V1 [2, 5, 6], while others report increased V1 activity during shape perception [1, 3, 4, 7-10]. Neurocomputational theories that cast perception as a generative process [11-13] propose that feedback connections carry predictions (i.e., the generative model), while feedforward connections signal the mismatch between top-down predictions and bottom-up inputs. Within this framework, the effect of feedback on early visual cortex may be either enhancing or suppressive, depending on whether the feedback signal is met by congruent bottom-up input. Here, we tested this hypothesis by quantifying the spatial profile of neural activity in V1 during the perception of illusory shapes using population receptive field mapping. We find that shape perception concurrently increases neural activity in regions of V1 that have a receptive field on the shape but do not receive bottom-up input and suppresses activity in regions of V1 that receive bottom-up input that is predicted by the shape. These effects were not modulated by task requirements. Together, these findings suggest that shape perception changes lower-order sensory representations in a highly specific and automatic manner, in line with theories that cast perception in terms of hierarchical generative models. Copyright © 2014 Elsevier Ltd. All rights reserved.

TOUCHING MOMENTS: DESIRE MODULATES THE NEURAL ANTICIPATION OF ACTIVE ROMANTIC CARESS

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Sjoerd J.H. Ebisch

2014-02-01

Full Text Available A romantic caress is a basic expression of affiliative behavior and a primary reinforcer. Given its inherent affective valence, its performance also would imply the prediction of reward values. For example, touching a person for whom one has strong passionate feelings likely is motivated by a strong desire for physical contact and associated with the anticipation of hedonic experiences. The present study aims at investigating how the anticipatory neural processes of active romantic caress are modulated by the intensity of the desire for affective contact as reflected by passionate feelings for the other. Functional magnetic resonance imaging scanning was performed in romantically involved partners using a paradigm that allowed to isolate the specific anticipatory representations of active romantic caress, compared with control caress, while testing for the relationship between neural activity and measures of feelings of passionate love for the other. The results demonstrated that right posterior insula activity in anticipation of romantic caress significantly co-varied with the intensity of desire for union with the other. This effect was independent of the sensory-affective properties of the performed touch, like its pleasantness. Furthermore, functional connectivity analysis showed that the same posterior insula cluster interacted with brain regions related to sensory-motor functions as well as to the processing and anticipation of reward. The findings provide insight on the neural substrate mediating between the desire for and the performance of romantic caress. In particular, we propose that anticipatory activity patterns in posterior insula may modulate subsequent sensory-affective processing of skin-to-skin contact.

Controlling Working Memory Operations by Selective Gating: The Roles of Oscillations and Synchrony

Science.gov (United States)

Dipoppa, Mario; Szwed, Marcin; Gutkin, Boris S.

2016-01-01

Working memory (WM) is a primary cognitive function that corresponds to the ability to update, stably maintain, and manipulate short-term memory (ST M) rapidly to perform ongoing cognitive tasks. A prevalent neural substrate of WM coding is persistent neural activity, the property of neurons to remain active after having been activated by a transient sensory stimulus. This persistent activity allows for online maintenance of memory as well as its active manipulation necessary for task performance. WM is tightly capacity limited. Therefore, selective gating of sensory and internally generated information is crucial for WM function. While the exact neural substrate of selective gating remains unclear, increasing evidence suggests that it might be controlled by modulating ongoing oscillatory brain activity. Here, we review experiments and models that linked selective gating, persistent activity, and brain oscillations, putting them in the more general mechanistic context of WM. We do so by defining several operations necessary for successful WM function and then discussing how such operations may be carried out by mechanisms suggested by computational models. We specifically show how oscillatory mechanisms may provide a rapid and flexible active gating mechanism for WM operations. PMID:28154616

Stuck in default mode: inefficient cross-frequency synchronization may lead to age-related short-term memory decline.

Science.gov (United States)

Pinal, Diego; Zurrón, Montserrat; Díaz, Fernando; Sauseng, Paul

2015-04-01

Aging-related decline in short-term memory capacity seems to be caused by deficient balancing of task-related and resting state brain networks activity; however, the exact neural mechanism underlying this deficit remains elusive. Here, we studied brain oscillatory activity in healthy young and old adults during visual information maintenance in a delayed match-to-sample task. Particular emphasis was on long range phase:amplitude coupling of frontal alpha (8-12 Hz) and posterior fast oscillatory activity (>30 Hz). It is argued that through posterior fast oscillatory activity nesting into the excitatory or the inhibitory phase of frontal alpha wave, long-range networks can be efficiently coupled or decoupled, respectively. On the basis of this mechanism, we show that healthy, elderly participants exhibit a lack of synchronization in task-relevant networks while maintaining synchronized regions of the resting state network. Lacking disconnection of this resting state network is predictive of aging-related short-term memory decline. These results support the idea of inefficient orchestration of competing brain networks in the aging human brain and identify the neural mechanism responsible for this control breakdown. Copyright © 2015 Elsevier Inc. All rights reserved.

Relation of obesity to neural activation in response to food commercials.

Science.gov (United States)

Gearhardt, Ashley N; Yokum, Sonja; Stice, Eric; Harris, Jennifer L; Brownell, Kelly D

2014-07-01

Adolescents view thousands of food commercials annually, but the neural response to food advertising and its association with obesity is largely unknown. This study is the first to examine how neural response to food commercials differs from other stimuli (e.g. non-food commercials and television show) and to explore how this response may differ by weight status. The blood oxygen level-dependent functional magnetic resonance imaging activation was measured in 30 adolescents ranging from lean to obese in response to food and non-food commercials imbedded in a television show. Adolescents exhibited greater activation in regions implicated in visual processing (e.g. occipital gyrus), attention (e.g. parietal lobes), cognition (e.g. temporal gyrus and posterior cerebellar lobe), movement (e.g. anterior cerebellar cortex), somatosensory response (e.g. postcentral gyrus) and reward [e.g. orbitofrontal cortex and anterior cingulate cortex (ACC)] during food commercials. Obese participants exhibited less activation during food relative to non-food commercials in neural regions implicated in visual processing (e.g. cuneus), attention (e.g. posterior cerebellar lobe), reward (e.g. ventromedial prefrontal cortex and ACC) and salience detection (e.g. precuneus). Obese participants did exhibit greater activation in a region implicated in semantic control (e.g. medial temporal gyrus). These findings may inform current policy debates regarding the impact of food advertising to minors. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Encapsulation Efficiency, Oscillatory Rheometry

Directory of Open Access Journals (Sweden)

Z. Mohammad Hassani

2014-01-01

Full Text Available Nanoliposomes are one of the most important polar lipid-based nanocarriers which can be used for encapsulation of both hydrophilic and hydrophobic active compounds. In this research, nanoliposomes based on lecithin-polyethylene glycol-gamma oryzanol were prepared by using a modified thermal method. Only one melting peak in DSC curve of gamma oryzanol bearing liposomes was observed which could be attributed to co-crystallization of both compounds. The addition of gamma oryzanol, caused to reduce the melting point of 5% (w/v lecithin-based liposome from 207°C to 163.2°C. At high level of lecithin, increasing of liposome particle size (storage at 4°C for two months was more obvious and particle size increased from 61 and 113 to 283 and 384 nanometers, respectively. The encapsulation efficiency of gamma oryzanol increased from 60% to 84.3% with increasing lecithin content. The encapsulation stability of oryzanol in liposome was determined at different concentrations of lecithin 3, 5, 10, 20% (w/v and different storage times (1, 7, 30 and 60 days. In all concentrations, the encapsulation stability slightly decreased during 30 days storage. The scanning electron microscopy (SEM images showed relatively spherical to elliptic particles which indicated to low extent of particles coalescence. The oscillatory rheometry showed that the loss modulus of liposomes were higher than storage modulus and more liquid-like behavior than solid-like behavior. The samples storage at 25°C for one month, showed higher viscoelastic parameters than those having been stored at 4°C which were attributed to higher membrane fluidity at 25°C and their final coalescence.Nanoliposomes are one of the most important polar lipid based nanocarriers which can be used for encapsulation of both hydrophilic and hydrophobic active compounds. In this research, nanoliposomes based on lecithin-polyethylene glycol-gamma oryzanol were prepared by using modified thermal method. Only one

The evolution of a horizontal scale for oscillatory magnetoconvection

Energy Technology Data Exchange (ETDEWEB)

Murphy, J O [Monash Univ., Clayton (Australia). Dept. of Mathematics; Lopez, J M [Aeronautical Research Labs., Port Melbourne (Australia). Aerodynamics Div.

1989-01-01

Oscillatory convective motions have been observed in the umbrae of sunspots and, in the past, the linear theory of overstability has been used for sunspot models. Here a non-linear model for oscillatory convection has been used to investigate the possibility of a preferred horizontal cell size for these motions, in the presence of a magnetic field. The integration forward in time, from the conductive state, of the non-linear multimode equations governing magnetoconvection when the magnetic Prandtl number is less than one portrays a complex interaction between the evolving magnetic and vertical velocity horizontal scales. Preferred horizontal scales for the convective cells have been established by identifying the modes that substantially contribute to the overall convective heat transport. All other modes, although initially perturbed, in time essentially decay to zero through self interaction. 8 refs., 5 figs.

Unstable oscillatory Pierce modes of neutralized electron beams

International Nuclear Information System (INIS)

Cary, J.R.; Lemons, D.S.

1982-01-01

Oscillatory modes of the Pierce system have been calculated. These modes are found to have growth rates comparable to the previously investigated purely growing modes. When these modes are included, it is found that the Pierce system is unstable for most values of ω/sub p/ L/V 0 >π

Periodicity and global exponential stability of generalized Cohen-Grossberg neural networks with discontinuous activations and mixed delays.

Science.gov (United States)

Wang, Dongshu; Huang, Lihong

2014-03-01

In this paper, we investigate the periodic dynamical behaviors for a class of general Cohen-Grossberg neural networks with discontinuous right-hand sides, time-varying and distributed delays. By means of retarded differential inclusions theory and the fixed point theorem of multi-valued maps, the existence of periodic solutions for the neural networks is obtained. After that, we derive some sufficient conditions for the global exponential stability and convergence of the neural networks, in terms of nonsmooth analysis theory with generalized Lyapunov approach. Without assuming the boundedness (or the growth condition) and monotonicity of the discontinuous neuron activation functions, our results will also be valid. Moreover, our results extend previous works not only on discrete time-varying and distributed delayed neural networks with continuous or even Lipschitz continuous activations, but also on discrete time-varying and distributed delayed neural networks with discontinuous activations. We give some numerical examples to show the applicability and effectiveness of our main results. Copyright © 2013 Elsevier Ltd. All rights reserved.

Time Multiplexed Active Neural Probe with 1356 Parallel Recording Sites

Directory of Open Access Journals (Sweden)

Bogdan C. Raducanu

2017-10-01

Full Text Available We present a high electrode density and high channel count CMOS (complementary metal-oxide-semiconductor active neural probe containing 1344 neuron sized recording pixels (20 µm × 20 µm and 12 reference pixels (20 µm × 80 µm, densely packed on a 50 µm thick, 100 µm wide, and 8 mm long shank. The active electrodes or pixels consist of dedicated in-situ circuits for signal source amplification, which are directly located under each electrode. The probe supports the simultaneous recording of all 1356 electrodes with sufficient signal to noise ratio for typical neuroscience applications. For enhanced performance, further noise reduction can be achieved while using half of the electrodes (678. Both of these numbers considerably surpass the state-of-the art active neural probes in both electrode count and number of recording channels. The measured input referred noise in the action potential band is 12.4 µVrms, while using 678 electrodes, with just 3 µW power dissipation per pixel and 45 µW per read-out channel (including data transmission.

Neural activation to monetary reward is associated with amphetamine reward sensitivity.

Science.gov (United States)

Crane, Natania A; Gorka, Stephanie M; Weafer, Jessica; Langenecker, Scott A; de Wit, Harriet; Phan, K Luan

2018-03-14

One known risk factor for drug use and abuse is sensitivity to rewarding effects of drugs. It is not known whether this risk factor extends to sensitivity to non-drug rewards. In this study with healthy young adults, we examined the association between sensitivity to the subjective rewarding effects of amphetamine and a neural indicator of anticipation of monetary reward. We hypothesized that greater euphorigenic response to amphetamine would be associated with greater neural activation to anticipation of monetary reward (Win > Loss). Healthy participants (N = 61) completed four laboratory sessions in which they received d-amphetamine (20 mg) and placebo in alternating order, providing self-report measures of euphoria and stimulation at regular intervals. At a separate visit 1-3 weeks later, participants completed the guessing reward task (GRT) during fMRI in a drug-free state. Participants reporting greater euphoria after amphetamine also exhibited greater neural activation during monetary reward anticipation in mesolimbic reward regions, including the bilateral caudate and putamen. This is the first study to show a relationship between neural correlates of monetary reward and sensitivity to the subjective rewarding effects of amphetamine in humans. These findings support growing evidence that sensitivity to reward in general is a risk factor for drug use and abuse, and suggest that sensitivity of drug-induced euphoria may reflect a general sensitivity to rewards. This may be an index of vulnerability for drug use or abuse.

Alternating current electric field effects on neural stem cell viability and differentiation.

Science.gov (United States)

Matos, Marvi A; Cicerone, Marcus T

2010-01-01

Methods utilizing stem cells hold tremendous promise for tissue engineering applications; however, many issues must be worked out before these therapies can be routinely applied. Utilization of external cues for preimplantation expansion and differentiation offers a potentially viable approach to the use of stem cells in tissue engineering. The studies reported here focus on the response of murine neural stem cells encapsulated in alginate hydrogel beads to alternating current electric fields. Cell viability and differentiation was studied as a function of electric field magnitude and frequency. We applied fields of frequency (0.1-10) Hz, and found a marked peak in neural stem cell viability under oscillatory electric fields with a frequency of 1 Hz. We also found an enhanced propensity for astrocyte differentiation over neuronal differentiation in the 1 Hz cultures, as compared to the other field frequencies we studied. Published 2010 American Institute of Chemical Engineers

Increased Neural Activation during Picture Encoding and Retrieval in 60-Year-Olds Compared to 20-Year-Olds

Science.gov (United States)

Burgmans, S.; van Boxtel, M. P. J.; Vuurman, E. F. P. M.; Evers, E. A. T.; Jolles, J.

2010-01-01

Brain aging has been associated with both reduced and increased neural activity during task execution. The purpose of the present study was to investigate whether increased neural activation during memory encoding and retrieval is already present at the age of 60 as well as to obtain more insight into the mechanism behind increased activity.…

Oscillatory signatures of crossmodal congruence effects: An EEG investigation employing a visuotactile pattern matching paradigm.

Science.gov (United States)

Göschl, Florian; Friese, Uwe; Daume, Jonathan; König, Peter; Engel, Andreas K

2015-08-01

Coherent percepts emerge from the accurate combination of inputs from the different sensory systems. There is an ongoing debate about the neurophysiological mechanisms of crossmodal interactions in the brain, and it has been proposed that transient synchronization of neurons might be of central importance. Oscillatory activity in lower frequency ranges (congruence. Analysis of the behavioral data showed benefits for congruent visuotactile stimulus combinations. Differences in oscillatory dynamics related to crossmodal congruence within the two tasks were observed in the beta-band for crossmodal target detection, as well as in the theta-band for congruence evaluation. Contrasting ongoing activity preceding visuotactile stimulation between the two tasks revealed differences in the alpha- and beta-bands. Source reconstruction of between-task differences showed prominent involvement of premotor cortex, supplementary motor area, somatosensory association cortex and the supramarginal gyrus. These areas not only exhibited more involvement in the pre-stimulus interval for target detection compared to congruence evaluation, but were also crucially involved in post-stimulus differences related to crossmodal stimulus congruence within the detection task. These results add to the increasing evidence that low frequency oscillations are functionally relevant for integration in distributed brain networks, as demonstrated for crossmodal interactions in visuotactile pattern matching in the current study. Copyright © 2015 Elsevier Inc. All rights reserved.

Convolutional Neural Networks for Human Activity Recognition Using Body-Worn Sensors

Directory of Open Access Journals (Sweden)

Fernando Moya Rueda

2018-05-01

Full Text Available Human activity recognition (HAR is a classification task for recognizing human movements. Methods of HAR are of great interest as they have become tools for measuring occurrences and durations of human actions, which are the basis of smart assistive technologies and manual processes analysis. Recently, deep neural networks have been deployed for HAR in the context of activities of daily living using multichannel time-series. These time-series are acquired from body-worn devices, which are composed of different types of sensors. The deep architectures process these measurements for finding basic and complex features in human corporal movements, and for classifying them into a set of human actions. As the devices are worn at different parts of the human body, we propose a novel deep neural network for HAR. This network handles sequence measurements from different body-worn devices separately. An evaluation of the architecture is performed on three datasets, the Oportunity, Pamap2, and an industrial dataset, outperforming the state-of-the-art. In addition, different network configurations will also be evaluated. We find that applying convolutions per sensor channel and per body-worn device improves the capabilities of convolutional neural network (CNNs.

Oscillatory behaviour of solutions of linear neutral differential ...

African Journals Online (AJOL)

The paper considers the contribution of space-time noise to the oscillatory behaviour of solutions of a linear neutral stochastic delay differential equation. It was established that under certain conditions on the time lags and their speed of adjustments, the presence of noise generates oscillation in the solution of the equation ...

Non-Steady Oscillatory Flow in Coarse Granular Materials

DEFF Research Database (Denmark)

Andersen, O. H.; Gent, M. R. A. van; Meer, J. W. van der

1992-01-01

Stationary and oscillatory flow through coarse granular materials have been investigated experimentally at Delft Hydraulics in their oscillating water tunnel with the objective of determining the coefficients of the extended Forchheimer equation. Cylinders, spheres and different types of rock have....... Further, for the non-stationary term, the virtual mass coefficient will be derived....

High Frequency Oscillatory Ventilation

Directory of Open Access Journals (Sweden)

AC Bryan

1996-01-01

Full Text Available High frequency oscillatory (HFO ventilation using low tidal volume and peak airway pressures is extremely efficient at eliminating carbon dioxide and raising pH in the newborn infant with acute respiratory failure. Improvement in oxygenation requires a strategy of sustained or repetitive inflations to 25 to 30 cm H2O in order to place the lung on the deflation limb of the pressure-volume curve. This strategy has also been shown to decrease the amount of secondary lung injury in animal models. Experience of the use of HFO ventilation as a rescue therapy as well as several published controlled trials have shown improved outcomes and a decrease in the use of extracorporeal membrane oxygenation when it has been used in newborns.

Performance of Deep and Shallow Neural Networks, the Universal Approximation Theorem, Activity Cliffs, and QSAR.

Science.gov (United States)

Winkler, David A; Le, Tu C

2017-01-01

Neural networks have generated valuable Quantitative Structure-Activity/Property Relationships (QSAR/QSPR) models for a wide variety of small molecules and materials properties. They have grown in sophistication and many of their initial problems have been overcome by modern mathematical techniques. QSAR studies have almost always used so-called "shallow" neural networks in which there is a single hidden layer between the input and output layers. Recently, a new and potentially paradigm-shifting type of neural network based on Deep Learning has appeared. Deep learning methods have generated impressive improvements in image and voice recognition, and are now being applied to QSAR and QSAR modelling. This paper describes the differences in approach between deep and shallow neural networks, compares their abilities to predict the properties of test sets for 15 large drug data sets (the kaggle set), discusses the results in terms of the Universal Approximation theorem for neural networks, and describes how DNN may ameliorate or remove troublesome "activity cliffs" in QSAR data sets. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A direct comparison of appetitive and aversive anticipation: Overlapping and distinct neural activation.

Science.gov (United States)

Sege, Christopher T; Bradley, Margaret M; Weymar, Mathias; Lang, Peter J

2017-05-30

fMRI studies of reward find increased neural activity in ventral striatum and medial prefrontal cortex (mPFC), whereas other regions, including the dorsolateral prefrontal cortex (dlPFC), anterior cingulate cortex (ACC), and anterior insula, are activated when anticipating aversive exposure. Although these data suggest differential activation during anticipation of pleasant or of unpleasant exposure, they also arise in the context of different paradigms (e.g., preparation for reward vs. threat of shock) and participants. To determine overlapping and unique regions active during emotional anticipation, we compared neural activity during anticipation of pleasant or unpleasant exposure in the same participants. Cues signalled the upcoming presentation of erotic/romantic, violent, or everyday pictures while BOLD activity during the 9-s anticipatory period was measured using fMRI. Ventral striatum and a ventral mPFC subregion were activated when anticipating pleasant, but not unpleasant or neutral, pictures, whereas activation in other regions was enhanced when anticipating appetitive or aversive scenes. Copyright © 2017 Elsevier B.V. All rights reserved.

Deep Recurrent Neural Networks for Human Activity Recognition

Directory of Open Access Journals (Sweden)

Abdulmajid Murad

2017-11-01

Full Text Available Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM and k-nearest neighbors (KNN. Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs and CNNs.

Deep Recurrent Neural Networks for Human Activity Recognition.

Science.gov (United States)

Murad, Abdulmajid; Pyun, Jae-Young

2017-11-06

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs.

Parasympathetic neural activity accounts for the lowering of exercise heart rate at high altitude

DEFF Research Database (Denmark)

Boushel, Robert Christopher; Calbet, J A; Rådegran, G

2001-01-01

In chronic hypoxia, both heart rate (HR) and cardiac output (Q) are reduced during exercise. The role of parasympathetic neural activity in lowering HR is unresolved, and its influence on Q and oxygen transport at high altitude has never been studied.......In chronic hypoxia, both heart rate (HR) and cardiac output (Q) are reduced during exercise. The role of parasympathetic neural activity in lowering HR is unresolved, and its influence on Q and oxygen transport at high altitude has never been studied....

Characterization of vertical mixing in oscillatory vegetated flows

Science.gov (United States)

Abdolahpour, M.; Ghisalberti, M.; Lavery, P.; McMahon, K.

2016-02-01

Seagrass meadows are primary producers that provide important ecosystem services, such as improved water quality, sediment stabilisation and trapping and recycling of nutrients. Most of these ecological services are strongly influenced by the vertical exchange of water across the canopy-water interface. That is, vertical mixing is the main hydrodynamic process governing the large-scale ecological and environmental impact of seagrass meadows. The majority of studies into mixing in vegetated flows have focused on steady flow environments whereas many coastal canopies are subjected to oscillatory flows driven by surface waves. It is known that the rate of mass transfer will vary greatly between unidirectional and oscillatory flows, necessitating a specific investigation of mixing in oscillatory canopy flows. In this study, we conducted an extensive laboratory investigation to characterise the rate of vertical mixing through a vertical turbulent diffusivity (Dt,z). This has been done through gauging the evolution of vertical profiles of concentration (C) of a dye sheet injected into a wave-canopy flow. Instantaneous measurement of the variance of the vertical concentration distribution ( allowed the estimation of a vertical turbulent diffusivity (). Two types of model canopies, rigid and flexible, with identical heights and frontal areas, were subjected to a wide and realistic range of wave height and period. The results showed two important mechanisms that dominate vertical mixing under different conditions: a shear layer that forms at the top of the canopy and wake turbulence generated by the stems. By allowing a coupled contribution of wake and shear layer mixing, we present a relationship that can be used to predict the rate of vertical mixing in coastal canopies. The results further showed that the rate of vertical mixing within flexible vegetation was always lower than the corresponding rigid canopy, confirming the impact of plant flexibility on canopy

Dispositional Mindfulness and Depressive Symptomatology: Correlations with Limbic and Self-Referential Neural Activity during Rest

Science.gov (United States)

Way, Baldwin M.; Creswell, J. David; Eisenberger, Naomi I.; Lieberman, Matthew D.

2010-01-01

To better understand the relationship between mindfulness and depression, we studied normal young adults (n=27) who completed measures of dispositional mindfulness and depressive symptomatology, which were then correlated with: a) Rest: resting neural activity during passive viewing of a fixation cross, relative to a simple goal-directed task (shape-matching); and b) Reactivity: neural reactivity during viewing of negative emotional faces, relative to the same shape-matching task. Dispositional mindfulness was negatively correlated with resting activity in self-referential processing areas, while depressive symptomatology was positively correlated with resting activity in similar areas. In addition, dispositional mindfulness was negatively correlated with resting activity in the amygdala, bilaterally, while depressive symptomatology was positively correlated with activity in the right amygdala. Similarly, when viewing emotional faces, amygdala reactivity was positively correlated with depressive symptomatology and negatively correlated with dispositional mindfulness, an effect that was largely attributable to differences in resting activity. These findings indicate that mindfulness is associated with intrinsic neural activity and that changes in resting amygdala activity could be a potential mechanism by which mindfulness-based depression treatments elicit therapeutic improvement. PMID:20141298

Self-reported empathy and neural activity during action imitation and observation in schizophrenia

OpenAIRE

Horan, William P.; Iacoboni, Marco; Cross, Katy A.; Korb, Alex; Lee, Junghee; Nori, Poorang; Quintana, Javier; Wynn, Jonathan K.; Green, Michael F.

2014-01-01

Introduction: Although social cognitive impairments are key determinants of functional outcome in schizophrenia their neural bases are poorly understood. This study investigated neural activity during imitation and observation of finger movements and facial expressions in schizophrenia, and their correlates with self-reported empathy. Methods: 23 schizophrenia outpatients and 23 healthy controls were studied with functional magnetic resonance imaging (fMRI) while they imitated, executed, o...

The Synapse Project: Engagement in mentally challenging activities enhances neural efficiency.

Science.gov (United States)

McDonough, Ian M; Haber, Sara; Bischof, Gérard N; Park, Denise C

2015-01-01

Correlational and limited experimental evidence suggests that an engaged lifestyle is associated with the maintenance of cognitive vitality in old age. However, the mechanisms underlying these engagement effects are poorly understood. We hypothesized that mental effort underlies engagement effects and used fMRI to examine the impact of high-challenge activities (digital photography and quilting) compared with low-challenge activities (socializing or performing low-challenge cognitive tasks) on neural function at pretest, posttest, and one year after the engagement program. In the scanner, participants performed a semantic-classification task with two levels of difficulty to assess the modulation of brain activity in response to task demands. The High-Challenge group, but not the Low-Challenge group, showed increased modulation of brain activity in medial frontal, lateral temporal, and parietal cortex-regions associated with attention and semantic processing-some of which were maintained a year later. This increased modulation stemmed from decreases in brain activity during the easy condition for the High-Challenge group and was associated with time committed to the program, age, and cognition. Sustained engagement in cognitively demanding activities facilitated cognition by increasing neural efficiency. Mentally-challenging activities may be neuroprotective and an important element to maintaining a healthy brain into late adulthood.

Evaluation of the Performance of Feedforward and Recurrent Neural Networks in Active Cancellation of Sound Noise

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Mehrshad Salmasi

2012-07-01

Full Text Available Active noise control is based on the destructive interference between the primary noise and generated noise from the secondary source. An antinoise of equal amplitude and opposite phase is generated and combined with the primary noise. In this paper, performance of the neural networks is evaluated in active cancellation of sound noise. For this reason, feedforward and recurrent neural networks are designed and trained. After training, performance of the feedforwrad and recurrent networks in noise attenuation are compared. We use Elman network as a recurrent neural network. For simulations, noise signals from a SPIB database are used. In order to compare the networks appropriately, equal number of layers and neurons are considered for the networks. Moreover, training and test samples are similar. Simulation results show that feedforward and recurrent neural networks present good performance in noise cancellation. As it is seen, the ability of recurrent neural network in noise attenuation is better than feedforward network.

Stability of Armour Units in Oscillatory Flow

DEFF Research Database (Denmark)

Burcharth, Hans F.; Thompson, A. C.

Despite numerous breakwater model tests very little is known today about the various phenomena and parameters that determine the hydraulic stability characteristics of different types of armour. This is because separation of parameters is extremely difficult in traditional tests.With the object...... of separating some of the factors a deterministic test, in which horizontal beds of armour units were exposed to oscillatory flow, was performed in a pulsating water tunnel....

Dark chocolate’s compositional effects revealed by oscillatory rheology

NARCIS (Netherlands)

van der Vaart, K.; Depypere, F.; De Graef, V.; Schall, P.; Fall, A.; Bonn, D.; Dewettinck, K.

2013-01-01

In this study, two types of oscillatory shear rheology are applied on dark chocolate with varying volume fraction, particle size distribution, and soy lecithin concentration. The first, a conventional strain sweep, allows for the separation of the elastic and viscous properties during the yielding.

Techniques for extracting single-trial activity patterns from large-scale neural recordings

Science.gov (United States)

Churchland, Mark M; Yu, Byron M; Sahani, Maneesh; Shenoy, Krishna V

2008-01-01

Summary Large, chronically-implanted arrays of microelectrodes are an increasingly common tool for recording from primate cortex, and can provide extracellular recordings from many (order of 100) neurons. While the desire for cortically-based motor prostheses has helped drive their development, such arrays also offer great potential to advance basic neuroscience research. Here we discuss the utility of array recording for the study of neural dynamics. Neural activity often has dynamics beyond that driven directly by the stimulus. While governed by those dynamics, neural responses may nevertheless unfold differently for nominally identical trials, rendering many traditional analysis methods ineffective. We review recent studies – some employing simultaneous recording, some not – indicating that such variability is indeed present both during movement generation, and during the preceding premotor computations. In such cases, large-scale simultaneous recordings have the potential to provide an unprecedented view of neural dynamics at the level of single trials. However, this enterprise will depend not only on techniques for simultaneous recording, but also on the use and further development of analysis techniques that can appropriately reduce the dimensionality of the data, and allow visualization of single-trial neural behavior. PMID:18093826

A simple method for estimating the entropy of neural activity

International Nuclear Information System (INIS)

Berry II, Michael J; Tkačik, Gašper; Dubuis, Julien; Marre, Olivier; Da Silveira, Rava Azeredo

2013-01-01

The number of possible activity patterns in a population of neurons grows exponentially with the size of the population. Typical experiments explore only a tiny fraction of the large space of possible activity patterns in the case of populations with more than 10 or 20 neurons. It is thus impossible, in this undersampled regime, to estimate the probabilities with which most of the activity patterns occur. As a result, the corresponding entropy—which is a measure of the computational power of the neural population—cannot be estimated directly. We propose a simple scheme for estimating the entropy in the undersampled regime, which bounds its value from both below and above. The lower bound is the usual ‘naive’ entropy of the experimental frequencies. The upper bound results from a hybrid approximation of the entropy which makes use of the naive estimate, a maximum entropy fit, and a coverage adjustment. We apply our simple scheme to artificial data, in order to check their accuracy; we also compare its performance to those of several previously defined entropy estimators. We then apply it to actual measurements of neural activity in populations with up to 100 cells. Finally, we discuss the similarities and differences between the proposed simple estimation scheme and various earlier methods. (paper)

Effect of sp3-hybridized defects on the oscillatory behavior of carbon nanotube oscillators

International Nuclear Information System (INIS)

Guo, Taiyu; Ding, Tony Weixi; Pei, Qing-Xiang; Zhang, Yong-Wei

2011-01-01

Using molecular dynamics simulations, we investigate the oscillatory behaviors of carbon nanotube oscillators containing sp 3 -hybridized defects formed by hydrogen chemisorption. It is found that the presence of these defects significantly affects the kinetic and potential energies of the nanotube systems, which in turn affects their oscillation periods and frequencies. We have also studied the oscillatory characteristics of the oscillators containing sp 3 -hybridized Stone-Wales defects. Our results show that it is possible to control the motion of the inner nanotube by introducing sp 3 -hybridized defects on the outer nanotube, which provides a potential way to tune the oscillatory behavior of nanotube oscillators. -- Highlights: → sp 3 -hybridized defects increase energy dissipation. → sp 3 -hybridized defects arranged in a row have stronger effect than that in a ring. → sp 3 -hybridized defects reduces the effect of SW defects.

Localized Fluctuant Oscillatory Activity by Working Memory Load: A Simultaneous EEG-fMRI Study

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Xiaojie Zhao

2017-10-01

Full Text Available Working memory (WM is a resource-limited memory system for temporary storage and processing of brain information during the execution of cognitive tasks. Increased WM load will increase the amount and difficulty of memory information. Several studies have used electroencephalography (EEG or functional magnetic resonance imaging (fMRI to explore load-dependent cognition processing according to the time courses of electrophysiological activity or the spatial pattern of blood oxygen metabolic activity. However, the relationships between these two activities and the underlying neural mechanism are still unclear. In this study, using simultaneously collected EEG and fMRI data under an n-back verbal WM task, we modeled the spectral perturbation of EEG oscillation and fMRI activation through joint independent component analysis (JICA. Multi-channel oscillation features were also introduced into the JICA model for further analysis. The results showed that time-locked activity of theta and beta were modulated by memory load in the early stimuli evaluation stage, corresponding to the enhanced activation in the frontal and parietal lobe, which were involved in stimulus discrimination, information encoding and delay-period activity. In the late response selection stage, alpha and gamma activity changes dependent on the load correspond to enhanced activation in the areas of frontal, temporal and parietal lobes, which played important roles in attention, information extraction and memory retention. These findings suggest that the increases in memory load not only affect the intensity and time course of the EEG activities, but also lead to the enhanced activation of brain regions which plays different roles during different time periods of cognitive process of WM.

Localized Fluctuant Oscillatory Activity by Working Memory Load: A Simultaneous EEG-fMRI Study.

Science.gov (United States)

Zhao, Xiaojie; Li, Xiaoyun; Yao, Li

2017-01-01

Working memory (WM) is a resource-limited memory system for temporary storage and processing of brain information during the execution of cognitive tasks. Increased WM load will increase the amount and difficulty of memory information. Several studies have used electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) to explore load-dependent cognition processing according to the time courses of electrophysiological activity or the spatial pattern of blood oxygen metabolic activity. However, the relationships between these two activities and the underlying neural mechanism are still unclear. In this study, using simultaneously collected EEG and fMRI data under an n-back verbal WM task, we modeled the spectral perturbation of EEG oscillation and fMRI activation through joint independent component analysis (JICA). Multi-channel oscillation features were also introduced into the JICA model for further analysis. The results showed that time-locked activity of theta and beta were modulated by memory load in the early stimuli evaluation stage, corresponding to the enhanced activation in the frontal and parietal lobe, which were involved in stimulus discrimination, information encoding and delay-period activity. In the late response selection stage, alpha and gamma activity changes dependent on the load correspond to enhanced activation in the areas of frontal, temporal and parietal lobes, which played important roles in attention, information extraction and memory retention. These findings suggest that the increases in memory load not only affect the intensity and time course of the EEG activities, but also lead to the enhanced activation of brain regions which plays different roles during different time periods of cognitive process of WM.

Neural speech recognition: continuous phoneme decoding using spatiotemporal representations of human cortical activity

Science.gov (United States)

Moses, David A.; Mesgarani, Nima; Leonard, Matthew K.; Chang, Edward F.

2016-10-01

Objective. The superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. In this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography. Approach. The system implements a Viterbi decoder that incorporates phoneme likelihood estimates from a linear discriminant analysis model and transition probabilities from an n-gram phonemic language model. Grid searches were used in an attempt to determine optimal parameterizations of the feature vectors and Viterbi decoder. Main results. The performance of the system was significantly improved by using spatiotemporal representations of the neural activity (as opposed to purely spatial representations) and by including language modeling and Viterbi decoding in the NSR system. Significance. These results emphasize the importance of modeling the temporal dynamics of neural responses when analyzing their variations with respect to varying stimuli and demonstrate that speech recognition techniques can be successfully leveraged when decoding speech from neural signals. Guided by the results detailed in this work, further development of the NSR system could have applications in the fields of automatic speech recognition and neural prosthetics.

Oscillatory regime in the multidimensional homogeneous cosmological models induced by a vector field

International Nuclear Information System (INIS)

Benini, R; Kirillov, A A; Montani, Giovanni

2005-01-01

We show that in multidimensional gravity, vector fields completely determine the structure and properties of singularity. It turns out that in the presence of a vector field the oscillatory regime exists in all spatial dimensions and for all homogeneous models. By analysing the Hamiltonian equations we derive the Poincare return map associated with the Kasner indexes and fix the rules according to which the Kasner vectors rotate. In correspondence to a four-dimensional spacetime, the oscillatory regime here constructed overlaps the usual Belinski-Khalatnikov-Liftshitz one

The Voice of Anger: Oscillatory EEG Responses to Emotional Prosody.

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Renata Del Giudice

Full Text Available Emotionally relevant stimuli and in particular anger are, due to their evolutionary relevance, often processed automatically and able to modulate attention independent of conscious access. Here, we tested whether attention allocation is enhanced when auditory stimuli are uttered by an angry voice. We recorded EEG and presented healthy individuals with a passive condition where unfamiliar names as well as the subject's own name were spoken both with an angry and neutral prosody. The active condition instead, required participants to actively count one of the presented (angry names. Results revealed that in the passive condition the angry prosody only elicited slightly stronger delta synchronization as compared to a neutral voice. In the active condition the attended (angry target was related to enhanced delta/theta synchronization as well as alpha desynchronization suggesting enhanced allocation of attention and utilization of working memory resources. Altogether, the current results are in line with previous findings and highlight that attention orientation can be systematically related to specific oscillatory brain responses. Potential applications include assessment of non-communicative clinical groups such as post-comatose patients.

Rejuvenation of MPTP-induced human neural precursor cell senescence by activating autophagy

Energy Technology Data Exchange (ETDEWEB)

Zhu, Liang [East Hospital, Tongji University School of Medicine, Shanghai (China); Dong, Chuanming [East Hospital, Tongji University School of Medicine, Shanghai (China); Department of Anatomy and Neurobiology, The Jiangsu Key Laboratory of Neuroregeneration, Nantong University, Nantong (China); Sun, Chenxi; Ma, Rongjie; Yang, Danjing [East Hospital, Tongji University School of Medicine, Shanghai (China); Zhu, Hongwen, E-mail: hongwen_zhu@hotmail.com [Tianjin Hospital, Tianjin Academy of Integrative Medicine, Tianjin (China); Xu, Jun, E-mail: xunymc2000@yahoo.com [East Hospital, Tongji University School of Medicine, Shanghai (China)

2015-08-21

Aging of neural stem cell, which can affect brain homeostasis, may be caused by many cellular mechanisms. Autophagy dysfunction was found in aged and neurodegenerative brains. However, little is known about the relationship between autophagy and human neural stem cell (hNSC) aging. The present study used 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP) to treat neural precursor cells (NPCs) derived from human embryonic stem cell (hESC) line H9 and investigate related molecular mechanisms involved in this process. MPTP-treated NPCs were found to undergo premature senescence [determined by increased senescence-associated-β-galactosidase (SA-β-gal) activity, elevated intracellular reactive oxygen species level, and decreased proliferation] and were associated with impaired autophagy. Additionally, the cellular senescence phenotypes were manifested at the molecular level by a significant increase in p21 and p53 expression, a decrease in SOD2 expression, and a decrease in expression of some key autophagy-related genes such as Atg5, Atg7, Atg12, and Beclin 1. Furthermore, we found that the senescence-like phenotype of MPTP-treated hNPCs was rejuvenated through treatment with a well-known autophagy enhancer rapamycin, which was blocked by suppression of essential autophagy gene Beclin 1. Taken together, these findings reveal the critical role of autophagy in the process of hNSC aging, and this process can be reversed by activating autophagy. - Highlights: • We successfully establish hESC-derived neural precursor cells. • MPTP treatment induced senescence-like state in hESC-derived NPCs. • MPTP treatment induced impaired autophagy of hESC-derived NPCs. • MPTP-induced hESC-derived NPC senescence was rejuvenated by activating autophagy.

Synchronization enhancement via an oscillatory bath in a network of ...

Indian Academy of Sciences (India)

2015-02-05

Feb 5, 2015 ... 2Monell Chemical Senses Center, 3500 Market Street, Philadelphia, PA 19104, USA ... The robustness of synchronization strategy is tested using a local and global ..... enhancement effect that the oscillatory bath has in the ...

Oscillatory Critical Amplitudes in Hierarchical Models and the Harris Function of Branching Processes

Science.gov (United States)

Costin, Ovidiu; Giacomin, Giambattista

2013-02-01

Oscillatory critical amplitudes have been repeatedly observed in hierarchical models and, in the cases that have been taken into consideration, these oscillations are so small to be hardly detectable. Hierarchical models are tightly related to iteration of maps and, in fact, very similar phenomena have been repeatedly reported in many fields of mathematics, like combinatorial evaluations and discrete branching processes. It is precisely in the context of branching processes with bounded off-spring that T. Harris, in 1948, first set forth the possibility that the logarithm of the moment generating function of the rescaled population size, in the super-critical regime, does not grow near infinity as a power, but it has an oscillatory prefactor (the Harris function). These oscillations have been observed numerically only much later and, while the origin is clearly tied to the discrete character of the iteration, the amplitude size is not so well understood. The purpose of this note is to reconsider the issue for hierarchical models and in what is arguably the most elementary setting—the pinning model—that actually just boils down to iteration of polynomial maps (and, notably, quadratic maps). In this note we show that the oscillatory critical amplitude for pinning models and the Harris function coincide. Moreover we make explicit the link between these oscillatory functions and the geometry of the Julia set of the map, making thus rigorous and quantitative some ideas set forth in Derrida et al. (Commun. Math. Phys. 94:115-132, 1984).

Neural fate decisions mediated by combinatorial regulation of Hes1 and miR-9.

Science.gov (United States)

Li, Shanshan; Liu, Yanwei; Liu, Zengrong; Wang, Ruiqi

2016-01-01

In the nervous system, Hes1 shows an oscillatory manner in neural progenitors but a persistent one in neurons. Many models involving Hes1 have been provided for the study of neural differentiation but few of them take the role of microRNA into account. It is known that a microRNA, miR-9, plays crucial roles in modulating Hes1 oscillations. However, the roles of miR-9 in controlling Hes1 oscillations and inducing transition between different cell fates still need to be further explored. Here we provide a mathematical model to show the interaction between miR-9 and Hes1, with the aim of understanding how the Hes1 oscillations are produced, how they are controlled, and further, how they are terminated. Based on the experimental findings, the model demonstrates the essential roles of Hes1 and miR-9 in regulating the dynamics of the system. In particular, the model suggests that the balance between miR-9 and Hes1 plays important roles in the choice between progenitor maintenance and neural differentiation. In addition, the synergistic (or antagonistic) effects of several important regulations are investigated so as to elucidate the effects of combinatorial regulation in neural decision-making. Our model provides a qualitative mechanism for understanding the process in neural fate decisions regulated by Hes1 and miR-9.

Neural activity, neural connectivity, and the processing of emotionally valenced information in older adults: links with life satisfaction.

Science.gov (United States)

Waldinger, Robert J; Kensinger, Elizabeth A; Schulz, Marc S

2011-09-01

This study examines whether differences in late-life well-being are linked to how older adults encode emotionally valenced information. Using fMRI with 39 older adults varying in life satisfaction, we examined how viewing positive and negative images would affect activation and connectivity of an emotion-processing network. Participants engaged most regions within this network more robustly for positive than for negative images, but within the PFC this effect was moderated by life satisfaction, with individuals higher in satisfaction showing lower levels of activity during the processing of positive images. Participants high in satisfaction showed stronger correlations among network regions-particularly between the amygdala and other emotion processing regions-when viewing positive, as compared with negative, images. Participants low in satisfaction showed no valence effect. Findings suggest that late-life satisfaction is linked with how emotion-processing regions are engaged and connected during processing of valenced information. This first demonstration of a link between neural recruitment and late-life well-being suggests that differences in neural network activation and connectivity may account for the preferential encoding of positive information seen in some older adults.

A continuous time-resolved measure decoded from EEG oscillatory activity predicts working memory task performance

Science.gov (United States)

Astrand, Elaine

2018-06-01

Objective. Working memory (WM), crucial for successful behavioral performance in most of our everyday activities, holds a central role in goal-directed behavior. As task demands increase, inducing higher WM load, maintaining successful behavioral performance requires the brain to work at the higher end of its capacity. Because it is depending on both external and internal factors, individual WM load likely varies in a continuous fashion. The feasibility to extract such a continuous measure in time that correlates to behavioral performance during a working memory task remains unsolved. Approach. Multivariate pattern decoding was used to test whether a decoder constructed from two discrete levels of WM load can generalize to produce a continuous measure that predicts task performance. Specifically, a linear regression with L2-regularization was chosen with input features from EEG oscillatory activity recorded from healthy participants while performing the n-back task, n\\in [1,2] . Main results. The feasibility to extract a continuous time-resolved measure that correlates positively to trial-by-trial working memory task performance is demonstrated (r  =  0.47, p  <  0.05). It is furthermore shown that this measure allows to predict task performance before action (r  =  0.49, p  <  0.05). We show that the extracted continuous measure enables to study the temporal dynamics of the complex activation pattern of WM encoding during the n-back task. Specifically, temporally precise contributions of different spectral features are observed which extends previous findings of traditional univariate approaches. Significance. These results constitute an important contribution towards a wide range of applications in the field of cognitive brain–machine interfaces. Monitoring mental processes related to attention and WM load to reduce the risk of committing errors in high-risk environments could potentially prevent many devastating consequences or

Event-related theta synchronization predicts deficit in facial affect recognition in schizophrenia.

Science.gov (United States)

Csukly, Gábor; Stefanics, Gábor; Komlósi, Sarolta; Czigler, István; Czobor, Pál

2014-02-01

Growing evidence suggests that abnormalities in the synchronized oscillatory activity of neurons in schizophrenia may lead to impaired neural activation and temporal coding and thus lead to neurocognitive dysfunctions, such as deficits in facial affect recognition. To gain an insight into the neurobiological processes linked to facial affect recognition, we investigated both induced and evoked oscillatory activity by calculating the Event Related Spectral Perturbation (ERSP) and the Inter Trial Coherence (ITC) during facial affect recognition. Fearful and neutral faces as well as nonface patches were presented to 24 patients with schizophrenia and 24 matched healthy controls while EEG was recorded. The participants' task was to recognize facial expressions. Because previous findings with healthy controls showed that facial feature decoding was associated primarily with oscillatory activity in the theta band, we analyzed ERSP and ITC in this frequency band in the time interval of 140-200 ms, which corresponds to the N170 component. Event-related theta activity and phase-locking to facial expressions, but not to nonface patches, predicted emotion recognition performance in both controls and patients. Event-related changes in theta amplitude and phase-locking were found to be significantly weaker in patients compared with healthy controls, which is in line with previous investigations showing decreased neural synchronization in the low frequency bands in patients with schizophrenia. Neural synchrony is thought to underlie distributed information processing. Our results indicate a less effective functioning in the recognition process of facial features, which may contribute to a less effective social cognition in schizophrenia. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Recent developments in structure-preserving algorithms for oscillatory differential equations

CERN Document Server

Wu, Xinyuan

2018-01-01

The main theme of this book is recent progress in structure-preserving algorithms for solving initial value problems of oscillatory differential equations arising in a variety of research areas, such as astronomy, theoretical physics, electronics, quantum mechanics and engineering. It systematically describes the latest advances in the development of structure-preserving integrators for oscillatory differential equations, such as structure-preserving exponential integrators, functionally fitted energy-preserving integrators, exponential Fourier collocation methods, trigonometric collocation methods, and symmetric and arbitrarily high-order time-stepping methods. Most of the material presented here is drawn from the recent literature. Theoretical analysis of the newly developed schemes shows their advantages in the context of structure preservation. All the new methods introduced in this book are proven to be highly effective compared with the well-known codes in the scientific literature. This book also addre...

Comparison Of Power Quality Disturbances Classification Based On Neural Network

Directory of Open Access Journals (Sweden)

Nway Nway Kyaw Win

2015-07-01

Full Text Available Abstract Power quality disturbances PQDs result serious problems in the reliability safety and economy of power system network. In order to improve electric power quality events the detection and classification of PQDs must be made type of transient fault. Software analysis of wavelet transform with multiresolution analysis MRA algorithm and feed forward neural network probabilistic and multilayer feed forward neural network based methodology for automatic classification of eight types of PQ signals flicker harmonics sag swell impulse fluctuation notch and oscillatory will be presented. The wavelet family Db4 is chosen in this system to calculate the values of detailed energy distributions as input features for classification because it can perform well in detecting and localizing various types of PQ disturbances. This technique classifies the types of PQDs problem sevents.The classifiers classify and identify the disturbance type according to the energy distribution. The results show that the PNN can analyze different power disturbance types efficiently. Therefore it can be seen that PNN has better classification accuracy than MLFF.

Neural activity in the hippocampus during conflict resolution.

Science.gov (United States)

Sakimoto, Yuya; Okada, Kana; Hattori, Minoru; Takeda, Kozue; Sakata, Shogo

2013-01-15

This study examined configural association theory and conflict resolution models in relation to hippocampal neural activity during positive patterning tasks. According to configural association theory, the hippocampus is important for responses to compound stimuli in positive patterning tasks. In contrast, according to the conflict resolution model, the hippocampus is important for responses to single stimuli in positive patterning tasks. We hypothesized that if configural association theory is applicable, and not the conflict resolution model, the hippocampal theta power should be increased when compound stimuli are presented. If, on the other hand, the conflict resolution model is applicable, but not configural association theory, then the hippocampal theta power should be increased when single stimuli are presented. If both models are valid and applicable in the positive patterning task, we predict that the hippocampal theta power should be increased by presentation of both compound and single stimuli during the positive patterning task. To examine our hypotheses, we measured hippocampal theta power in rats during a positive patterning task. The results showed that hippocampal theta power increased during the presentation of a single stimulus, but did not increase during the presentation of a compound stimulus. This finding suggests that the conflict resolution model is more applicable than the configural association theory for describing neural activity during positive patterning tasks. Copyright © 2012 Elsevier B.V. All rights reserved.

The effect of a laser beam displacement on parametric oscillatory instabilities for Advanced LIGO

International Nuclear Information System (INIS)

Heinert, D.; Strigin, S.E.

2011-01-01

The arm cavities of real gravitational wave detectors can show small deviations like a tilt or a spatial shift between the cavity mirrors. These deviations lead to a separation of the optical mode centres with respect to the mirror's centre. In this Letter we perform the computation of parametric instable modes considering the described displacement. We further analyse the possibility of parametric oscillatory instability in the Advanced LIGO interferometer for the case of a displaced arm cavity. Our results reveal an additional number of optical and elastic mode combinations due to a displacement that can give rise to the undesirable effect of parametric oscillatory instability. -- Highlights: → We analyse the possibility of parametric oscillatory instability in the Advanced LIGO interferometer. → We perform the computation of parametric instable modes considering the mirror displacement. → Our results reveal an additional number of optical and elastic mode unstable combinations.

Multistability of neural networks with discontinuous non-monotonic piecewise linear activation functions and time-varying delays.

Science.gov (United States)

Nie, Xiaobing; Zheng, Wei Xing

2015-05-01

This paper is concerned with the problem of coexistence and dynamical behaviors of multiple equilibrium points for neural networks with discontinuous non-monotonic piecewise linear activation functions and time-varying delays. The fixed point theorem and other analytical tools are used to develop certain sufficient conditions that ensure that the n-dimensional discontinuous neural networks with time-varying delays can have at least 5(n) equilibrium points, 3(n) of which are locally stable and the others are unstable. The importance of the derived results is that it reveals that the discontinuous neural networks can have greater storage capacity than the continuous ones. Moreover, different from the existing results on multistability of neural networks with discontinuous activation functions, the 3(n) locally stable equilibrium points obtained in this paper are located in not only saturated regions, but also unsaturated regions, due to the non-monotonic structure of discontinuous activation functions. A numerical simulation study is conducted to illustrate and support the derived theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Structural state diagram of concentrated suspensions of jammed soft particles in oscillatory shear flow

Science.gov (United States)

Khabaz, Fardin; Cloitre, Michel; Bonnecaze, Roger T.

2018-03-01

In a recent study [Khabaz et al., Phys. Rev. Fluids 2, 093301 (2017), 10.1103/PhysRevFluids.2.093301], we showed that jammed soft particle glasses (SPGs) crystallize and order in steady shear flow. Here we investigate the rheology and microstructures of these suspensions in oscillatory shear flow using particle-dynamics simulations. The microstructures in both types of flows are similar, but their evolutions are very different. In both cases the monodisperse and polydisperse suspensions form crystalline and layered structures, respectively, at high shear rates. The crystals obtained in the oscillatory shear flow show fewer defects compared to those in the steady shear. SPGs remain glassy for maximum oscillatory strains less than about the yield strain of the material. For maximum strains greater than the yield strain, microstructural and rheological transitions occur for SPGs. Polydisperse SPGs rearrange into a layered structure parallel to the flow-vorticity plane for sufficiently high maximum shear rates and maximum strains about 10 times greater than the yield strain. Monodisperse suspensions form a face-centered cubic (FCC) structure when the maximum shear rate is low and hexagonal close-packed (HCP) structure when the maximum shear rate is high. In steady shear, the transition from a glassy state to a layered one for polydisperse suspensions included a significant induction strain before the transformation. In oscillatory shear, the transformation begins to occur immediately and with different microstructural changes. A state diagram for suspensions in large amplitude oscillatory shear flow is found to be in close but not exact agreement with the state diagram for steady shear flow. For more modest amplitudes of around one to five times the yield strain, there is a transition from a glassy structure to FCC and HCP crystals, at low and high frequencies, respectively, for monodisperse suspensions. At moderate frequencies, the transition is from glassy to HCP via

Wide-field optical mapping of neural activity and brain haemodynamics: considerations and novel approaches

Science.gov (United States)

Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Thibodeaux, David N.; Zhao, Hanzhi T.; Yu, Hang

2016-01-01

Although modern techniques such as two-photon microscopy can now provide cellular-level three-dimensional imaging of the intact living brain, the speed and fields of view of these techniques remain limited. Conversely, two-dimensional wide-field optical mapping (WFOM), a simpler technique that uses a camera to observe large areas of the exposed cortex under visible light, can detect changes in both neural activity and haemodynamics at very high speeds. Although WFOM may not provide single-neuron or capillary-level resolution, it is an attractive and accessible approach to imaging large areas of the brain in awake, behaving mammals at speeds fast enough to observe widespread neural firing events, as well as their dynamic coupling to haemodynamics. Although such wide-field optical imaging techniques have a long history, the advent of genetically encoded fluorophores that can report neural activity with high sensitivity, as well as modern technologies such as light emitting diodes and sensitive and high-speed digital cameras have driven renewed interest in WFOM. To facilitate the wider adoption and standardization of WFOM approaches for neuroscience and neurovascular coupling research, we provide here an overview of the basic principles of WFOM, considerations for implementation of wide-field fluorescence imaging of neural activity, spectroscopic analysis and interpretation of results. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574312

Wide-field optical mapping of neural activity and brain haemodynamics: considerations and novel approaches.

Science.gov (United States)

Ma, Ying; Shaik, Mohammed A; Kim, Sharon H; Kozberg, Mariel G; Thibodeaux, David N; Zhao, Hanzhi T; Yu, Hang; Hillman, Elizabeth M C

2016-10-05

Although modern techniques such as two-photon microscopy can now provide cellular-level three-dimensional imaging of the intact living brain, the speed and fields of view of these techniques remain limited. Conversely, two-dimensional wide-field optical mapping (WFOM), a simpler technique that uses a camera to observe large areas of the exposed cortex under visible light, can detect changes in both neural activity and haemodynamics at very high speeds. Although WFOM may not provide single-neuron or capillary-level resolution, it is an attractive and accessible approach to imaging large areas of the brain in awake, behaving mammals at speeds fast enough to observe widespread neural firing events, as well as their dynamic coupling to haemodynamics. Although such wide-field optical imaging techniques have a long history, the advent of genetically encoded fluorophores that can report neural activity with high sensitivity, as well as modern technologies such as light emitting diodes and sensitive and high-speed digital cameras have driven renewed interest in WFOM. To facilitate the wider adoption and standardization of WFOM approaches for neuroscience and neurovascular coupling research, we provide here an overview of the basic principles of WFOM, considerations for implementation of wide-field fluorescence imaging of neural activity, spectroscopic analysis and interpretation of results.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. © 2016 The Authors.

GABA and Gap Junctions in the Development of Synchronized Activity in Human Pluripotent Stem Cell-Derived Neural Networks

Directory of Open Access Journals (Sweden)

Meeri Eeva-Liisa Mäkinen

2018-03-01

Full Text Available The electrical activity of the brain arises from single neurons communicating with each other. However, how single neurons interact during early development to give rise to neural network activity remains poorly understood. We studied the emergence of synchronous neural activity in human pluripotent stem cell (hPSC-derived neural networks simultaneously on a single-neuron level and network level. The contribution of gamma-aminobutyric acid (GABA and gap junctions to the development of synchronous activity in hPSC-derived neural networks was studied with GABA agonist and antagonist and by blocking gap junctional communication, respectively. We characterized the dynamics of the network-wide synchrony in hPSC-derived neural networks with high spatial resolution (calcium imaging and temporal resolution microelectrode array (MEA. We found that the emergence of synchrony correlates with a decrease in very strong GABA excitation. However, the synchronous network was found to consist of a heterogeneous mixture of synchronously active cells with variable responses to GABA, GABA agonists and gap junction blockers. Furthermore, we show how single-cell distributions give rise to the network effect of GABA, GABA agonists and gap junction blockers. Finally, based on our observations, we suggest that the earliest form of synchronous neuronal activity depends on gap junctions and a decrease in GABA induced depolarization but not on GABAA mediated signaling.

GABA and Gap Junctions in the Development of Synchronized Activity in Human Pluripotent Stem Cell-Derived Neural Networks

Science.gov (United States)

Mäkinen, Meeri Eeva-Liisa; Ylä-Outinen, Laura; Narkilahti, Susanna

2018-01-01

The electrical activity of the brain arises from single neurons communicating with each other. However, how single neurons interact during early development to give rise to neural network activity remains poorly understood. We studied the emergence of synchronous neural activity in human pluripotent stem cell (hPSC)-derived neural networks simultaneously on a single-neuron level and network level. The contribution of gamma-aminobutyric acid (GABA) and gap junctions to the development of synchronous activity in hPSC-derived neural networks was studied with GABA agonist and antagonist and by blocking gap junctional communication, respectively. We characterized the dynamics of the network-wide synchrony in hPSC-derived neural networks with high spatial resolution (calcium imaging) and temporal resolution microelectrode array (MEA). We found that the emergence of synchrony correlates with a decrease in very strong GABA excitation. However, the synchronous network was found to consist of a heterogeneous mixture of synchronously active cells with variable responses to GABA, GABA agonists and gap junction blockers. Furthermore, we show how single-cell distributions give rise to the network effect of GABA, GABA agonists and gap junction blockers. Finally, based on our observations, we suggest that the earliest form of synchronous neuronal activity depends on gap junctions and a decrease in GABA induced depolarization but not on GABAA mediated signaling. PMID:29559893

Theoretical analysis of oscillatory terms in lattice heat-current time correlation functions and their contributions to thermal conductivity

Science.gov (United States)

Pereverzev, Andrey; Sewell, Tommy

2018-03-01

Lattice heat-current time correlation functions for insulators and semiconductors obtained using molecular dynamics (MD) simulations exhibit features of both pure exponential decay and oscillatory-exponential decay. For some materials the oscillatory terms contribute significantly to the lattice heat conductivity calculated from the correlation functions. However, the origin of the oscillatory terms is not well understood, and their contribution to the heat conductivity is accounted for by fitting them to empirical functions. Here, a translationally invariant expression for the heat current in terms of creation and annihilation operators is derived. By using this full phonon-picture definition of the heat current and applying the relaxation-time approximation we explain, at least in part, the origin of the oscillatory terms in the lattice heat-current correlation function. We discuss the relationship between the crystal Hamiltonian and the magnitude of the oscillatory terms. A solvable one-dimensional model is used to illustrate the potential importance of terms that are omitted in the commonly used phonon-picture expression for the heat current. While the derivations are fully quantum mechanical, classical-limit expressions are provided that enable direct contact with classical quantities obtainable from MD.

Measuring alterations in oscillatory brain networks in schizophrenia with resting-state MEG: State-of-the-art and methodological challenges.

Science.gov (United States)

Alamian, Golnoush; Hincapié, Ana-Sofía; Pascarella, Annalisa; Thiery, Thomas; Combrisson, Etienne; Saive, Anne-Lise; Martel, Véronique; Althukov, Dmitrii; Haesebaert, Frédéric; Jerbi, Karim

2017-09-01

Neuroimaging studies provide evidence of disturbed resting-state brain networks in Schizophrenia (SZ). However, untangling the neuronal mechanisms that subserve these baseline alterations requires measurement of their electrophysiological underpinnings. This systematic review specifically investigates the contributions of resting-state Magnetoencephalography (MEG) in elucidating abnormal neural organization in SZ patients. A systematic literature review of resting-state MEG studies in SZ was conducted. This literature is discussed in relation to findings from resting-state fMRI and EEG, as well as to task-based MEG research in SZ population. Importantly, methodological limitations are considered and recommendations to overcome current limitations are proposed. Resting-state MEG literature in SZ points towards altered local and long-range oscillatory network dynamics in various frequency bands. Critical methodological challenges with respect to experiment design, and data collection and analysis need to be taken into consideration. Spontaneous MEG data show that local and global neural organization is altered in SZ patients. MEG is a highly promising tool to fill in knowledge gaps about the neurophysiology of SZ. However, to reach its fullest potential, basic methodological challenges need to be overcome. MEG-based resting-state power and connectivity findings could be great assets to clinical and translational research in psychiatry, and SZ in particular. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Multistability of memristive Cohen-Grossberg neural networks with non-monotonic piecewise linear activation functions and time-varying delays.

Science.gov (United States)

Nie, Xiaobing; Zheng, Wei Xing; Cao, Jinde

2015-11-01

The problem of coexistence and dynamical behaviors of multiple equilibrium points is addressed for a class of memristive Cohen-Grossberg neural networks with non-monotonic piecewise linear activation functions and time-varying delays. By virtue of the fixed point theorem, nonsmooth analysis theory and other analytical tools, some sufficient conditions are established to guarantee that such n-dimensional memristive Cohen-Grossberg neural networks can have 5(n) equilibrium points, among which 3(n) equilibrium points are locally exponentially stable. It is shown that greater storage capacity can be achieved by neural networks with the non-monotonic activation functions introduced herein than the ones with Mexican-hat-type activation function. In addition, unlike most existing multistability results of neural networks with monotonic activation functions, those obtained 3(n) locally stable equilibrium points are located both in saturated regions and unsaturated regions. The theoretical findings are verified by an illustrative example with computer simulations. Copyright © 2015 Elsevier Ltd. All rights reserved.

On the effect of a longitudinal magnetic field on oscillatory ...

Indian Academy of Sciences (India)

. The frequency, ... dinal magnetic field on the oscillatory characteristics of a subnormal region it is proposed to study the variation of ... earth to provide a signal to the oscilloscope (60 MHz digital storage, PM 3350, Phillips). A current meter ...

Global convergence of periodic solution of neural networks with discontinuous activation functions

International Nuclear Information System (INIS)

Huang Lihong; Guo Zhenyuan

2009-01-01

In this paper, without assuming boundedness and monotonicity of the activation functions, we establish some sufficient conditions ensuring the existence and global asymptotic stability of periodic solution of neural networks with discontinuous activation functions by using the Yoshizawa-like theorem and constructing proper Lyapunov function. The obtained results improve and extend previous works.

Reflood modeling under oscillatory flow conditions with Cathare

International Nuclear Information System (INIS)

Kelly, J.M.; Bartak, J.; Janicot, A.

1993-01-01

The problems and the current status in oscillatory reflood modelling with the CATHARE code are presented. The physical models used in CATHARE for reflood modelling predicted globally very well the forced reflood experiments. Significant drawbacks existed in predicting experiments with oscillatory flow (both forced and gravity driven). First, the more simple case of forced flow oscillations was analyzed. Modelling improvements within the reflooding package resolved the problem of quench front blockages and unphysical oscillations. Good agreements with experiment for the ERSEC forced oscillations reflood tests is now obtained. For gravity driven reflood, CATHARE predicted sustained flow oscillations during 100-150 s after the start of the reflood, whereas in the experiment flow oscillations were observed only during 25-30 s. Possible areas of modeling improvements are identified and several new correlations are suggested. The first test calculations of the BETHSY test 6.7A4 have shown that the oscillations are mostly sensitive to heat flux modeling downstream of the quench front. A much better agreement between CATHARE results and the experiment was obtained. However, further effort is necessary to obtain globally satisfactory predictions of gravity driven system reflood tests. (authors) 6 figs., 35 refs

Reflood modeling under oscillatory flow conditions with Cathare

Energy Technology Data Exchange (ETDEWEB)

Kelly, J M; Bartak, J; Janicot, A

1994-12-31

The problems and the current status in oscillatory reflood modelling with the CATHARE code are presented. The physical models used in CATHARE for reflood modelling predicted globally very well the forced reflood experiments. Significant drawbacks existed in predicting experiments with oscillatory flow (both forced and gravity driven). First, the more simple case of forced flow oscillations was analyzed. Modelling improvements within the reflooding package resolved the problem of quench front blockages and unphysical oscillations. Good agreements with experiment for the ERSEC forced oscillations reflood tests is now obtained. For gravity driven reflood, CATHARE predicted sustained flow oscillations during 100-150 s after the start of the reflood, whereas in the experiment flow oscillations were observed only during 25-30 s. Possible areas of modeling improvements are identified and several new correlations are suggested. The first test calculations of the BETHSY test 6.7A4 have shown that the oscillations are mostly sensitive to heat flux modeling downstream of the quench front. A much better agreement between CATHARE results and the experiment was obtained. However, further effort is necessary to obtain globally satisfactory predictions of gravity driven system reflood tests. (authors) 6 figs., 35 refs.

The simplest problem in the collective dynamics of neural networks: is synchrony stable?

International Nuclear Information System (INIS)

Timme, Marc; Wolf, Fred

2008-01-01

For spiking neural networks we consider the stability problem of global synchrony, arguably the simplest non-trivial collective dynamics in such networks. We find that even this simplest dynamical problem—local stability of synchrony—is non-trivial to solve and requires novel methods for its solution. In particular, the discrete mode of pulsed communication together with the complicated connectivity of neural interaction networks requires a non-standard approach. The dynamics in the vicinity of the synchronous state is determined by a multitude of linear operators, in contrast to a single stability matrix in conventional linear stability theory. This unusual property qualitatively depends on network topology and may be neglected for globally coupled homogeneous networks. For generic networks, however, the number of operators increases exponentially with the size of the network. We present methods to treat this multi-operator problem exactly. First, based on the Gershgorin and Perron–Frobenius theorems, we derive bounds on the eigenvalues that provide important information about the synchronization process but are not sufficient to establish the asymptotic stability or instability of the synchronous state. We then present a complete analysis of asymptotic stability for topologically strongly connected networks using simple graph-theoretical considerations. For inhibitory interactions between dissipative (leaky) oscillatory neurons the synchronous state is stable, independent of the parameters and the network connectivity. These results indicate that pulse-like interactions play a profound role in network dynamical systems, and in particular in the dynamics of biological synchronization, unless the coupling is homogeneous and all-to-all. The concepts introduced here are expected to also facilitate the exact analysis of more complicated dynamical network states, for instance the irregular balanced activity in cortical neural networks

Copper is an endogenous modulator of neural circuit spontaneous activity.

Science.gov (United States)

Dodani, Sheel C; Firl, Alana; Chan, Jefferson; Nam, Christine I; Aron, Allegra T; Onak, Carl S; Ramos-Torres, Karla M; Paek, Jaeho; Webster, Corey M; Feller, Marla B; Chang, Christopher J

2014-11-18

For reasons that remain insufficiently understood, the brain requires among the highest levels of metals in the body for normal function. The traditional paradigm for this organ and others is that fluxes of alkali and alkaline earth metals are required for signaling, but transition metals are maintained in static, tightly bound reservoirs for metabolism and protection against oxidative stress. Here we show that copper is an endogenous modulator of spontaneous activity, a property of functional neural circuitry. Using Copper Fluor-3 (CF3), a new fluorescent Cu(+) sensor for one- and two-photon imaging, we show that neurons and neural tissue maintain basal stores of loosely bound copper that can be attenuated by chelation, which define a labile copper pool. Targeted disruption of these labile copper stores by acute chelation or genetic knockdown of the CTR1 (copper transporter 1) copper channel alters the spatiotemporal properties of spontaneous activity in developing hippocampal and retinal circuits. The data identify an essential role for copper neuronal function and suggest broader contributions of this transition metal to cell signaling.

Modulation of Neural Activity during Guided Viewing of Visual Art.

Science.gov (United States)

Herrera-Arcos, Guillermo; Tamez-Duque, Jesús; Acosta-De-Anda, Elsa Y; Kwan-Loo, Kevin; de-Alba, Mayra; Tamez-Duque, Ulises; Contreras-Vidal, Jose L; Soto, Rogelio

2017-01-01

Mobile Brain-Body Imaging (MoBI) technology was deployed to record multi-modal data from 209 participants to examine the brain's response to artistic stimuli at the Museo de Arte Contemporáneo (MARCO) in Monterrey, México. EEG signals were recorded as the subjects walked through the exhibit in guided groups of 6-8 people. Moreover, guided groups were either provided with an explanation of each art piece (Guided-E), or given no explanation (Guided-NE). The study was performed using portable Muse (InteraXon, Inc, Toronto, ON, Canada) headbands with four dry electrodes located at AF7, AF8, TP9, and TP10. Each participant performed a baseline (BL) control condition devoid of artistic stimuli and selected his/her favorite piece of art (FP) during the guided tour. In this study, we report data related to participants' demographic information and aesthetic preference as well as effects of art viewing on neural activity (EEG) in a select subgroup of 18-30 year-old subjects (Nc = 25) that generated high-quality EEG signals, on both BL and FP conditions. Dependencies on gender, sensor placement, and presence or absence of art explanation were also analyzed. After denoising, clustering of spectral EEG models was used to identify neural patterns associated with BL and FP conditions. Results indicate statistically significant suppression of beta band frequencies (15-25 Hz) in the prefrontal electrodes (AF7 and AF8) during appreciation of subjects' favorite painting, compared to the BL condition, which was significantly different from EEG responses to non-favorite paintings (NFP). No significant differences in brain activity in relation to the presence or absence of explanation during exhibit tours were found. Moreover, a frontal to posterior asymmetry in neural activity was observed, for both BL and FP conditions. These findings provide new information about frequency-related effects of preferred art viewing in brain activity, and support the view that art appreciation is

Psychopathic traits linked to alterations in neural activity during personality judgments of self and others.

Science.gov (United States)

Deming, Philip; Philippi, Carissa L; Wolf, Richard C; Dargis, Monika; Kiehl, Kent A; Koenigs, Michael

2018-01-01

Psychopathic individuals are notorious for their grandiose sense of self-worth and disregard for the welfare of others. One potential psychological mechanism underlying these traits is the relative consideration of "self" versus "others". Here we used task-based functional magnetic resonance imaging (fMRI) to identify neural responses during personality trait judgments about oneself and a familiar other in a sample of adult male incarcerated offenders ( n  = 57). Neural activity was regressed on two clusters of psychopathic traits: Factor 1 (e.g., egocentricity and lack of empathy) and Factor 2 (e.g., impulsivity and irresponsibility). Contrary to our hypotheses, Factor 1 scores were not significantly related to neural activity during self- or other-judgments. However, Factor 2 traits were associated with diminished activation to self-judgments, in relation to other-judgments, in bilateral posterior cingulate cortex and right temporoparietal junction. These findings highlight cortical regions associated with a dimension of social-affective cognition that may underlie psychopathic individuals' impulsive traits.

Artificial neural networks in the evaluation of the radioactive waste drums activity

International Nuclear Information System (INIS)

Potiens, J.R.A.J.; Hiromoto, G.

2006-01-01

The mathematical techniques are becoming more important to solve geometry and standard identification problems. The gamma spectrometry of radioactive waste drums would be a complex solution problem. The main difficulty is the detectors calibration for this geometry; the waste is not homogeneously distributed inside the drums, therefore there are many possible combinations between the activity and the position of these radionuclides inside the drums, making the preparation of calibration standards impracticable. This work describes the development of a methodology to estimate the activity of a 200 L radioactive waste drum, as well as a mapping of the waste distribution, using Artificial Neural Network. The neural network data set entry obtaining was based on the possible detection efficiency combination with 10 sources activities varying from 0 to 74 x 10 3 Bq. The set up consists of a 200 L drum divided in 5 layers. Ten detectors were positioned all the way through a parallel line to the drum axis, from 15 cm of its surface. The Cesium -137 radionuclide source was used. The 50 efficiency obtained values (10 detectors and 5 layers), combined with the 10 source intensities resulted in a 100,000 lines for 15 columns matrix, with all the possible combinations of source intensity and the Cs-137 position in the 5 layers of the drum. This archive was divided in 2 parts to compose the set of training: input and target files. The MatLab 7.0 module of neural networks was used for training. The net architecture has 10 neurons in the input layer, 18 in the hidden layer and 5 in the output layer. The training algorithm was the 'traincgb' and after 300 'epoch s' the medium square error was 0.00108172. This methodology allows knowing the detection positions answers in a heterogeneous distribution of radionuclides inside a 200 L waste drum; in consequence it is possible to estimate the total activity of the drum in the training neural network limits. The results accuracy depends

Electronic bypass of spinal lesions: activation of lower motor neurons directly driven by cortical neural signals.

Science.gov (United States)

Li, Yan; Alam, Monzurul; Guo, Shanshan; Ting, K H; He, Jufang

2014-07-03

Lower motor neurons in the spinal cord lose supraspinal inputs after complete spinal cord injury, leading to a loss of volitional control below the injury site. Extensive locomotor training with spinal cord stimulation can restore locomotion function after spinal cord injury in humans and animals. However, this locomotion is non-voluntary, meaning that subjects cannot control stimulation via their natural "intent". A recent study demonstrated an advanced system that triggers a stimulator using forelimb stepping electromyographic patterns to restore quadrupedal walking in rats with spinal cord transection. However, this indirect source of "intent" may mean that other non-stepping forelimb activities may false-trigger the spinal stimulator and thus produce unwanted hindlimb movements. We hypothesized that there are distinguishable neural activities in the primary motor cortex during treadmill walking, even after low-thoracic spinal transection in adult guinea pigs. We developed an electronic spinal bridge, called "Motolink", which detects these neural patterns and triggers a "spinal" stimulator for hindlimb movement. This hardware can be head-mounted or carried in a backpack. Neural data were processed in real-time and transmitted to a computer for analysis by an embedded processor. Off-line neural spike analysis was conducted to calculate and preset the spike threshold for "Motolink" hardware. We identified correlated activities of primary motor cortex neurons during treadmill walking of guinea pigs with spinal cord transection. These neural activities were used to predict the kinematic states of the animals. The appropriate selection of spike threshold value enabled the "Motolink" system to detect the neural "intent" of walking, which triggered electrical stimulation of the spinal cord and induced stepping-like hindlimb movements. We present a direct cortical "intent"-driven electronic spinal bridge to restore hindlimb locomotion after complete spinal cord injury.

On stellar collapse: continual or oscillatory. A short comment

International Nuclear Information System (INIS)

Leung, P.T.

1980-01-01

We comment on a previously published paper on the oscillatory dynamics of stellar collapse and conclude that the Schwarzschild interior solution applied to the 'inflection points' can never give rise to a 'turning back' motion, in spite of the fact that the geodesic equation really does not always describe an attractive gravitational acceleration

New insights into strobe reactions: An intriguing oscillatory combustion phenomenon

NARCIS (Netherlands)

Corbel, J.M.L.

2013-01-01

Strobes are self-sustained oscillatory combustions that have various applications in the fireworks industry and also in the military area (signaling, missile decoys and crowd control). However, most of the strobe compositions were discovered using trial and error methods. The fundamentals mechanisms

Neural oscillatory mechanisms during novel grammar learning underlying language analytical abilities.

Science.gov (United States)

Kepinska, Olga; Pereda, Ernesto; Caspers, Johanneke; Schiller, Niels O

2017-12-01

The goal of the present study was to investigate the initial phases of novel grammar learning on a neural level, concentrating on mechanisms responsible for individual variability between learners. Two groups of participants, one with high and one with average language analytical abilities, performed an Artificial Grammar Learning (AGL) task consisting of learning and test phases. During the task, EEG signals from 32 cap-mounted electrodes were recorded and epochs corresponding to the learning phases were analysed. We investigated spectral power modulations over time, and functional connectivity patterns by means of a bivariate, frequency-specific index of phase synchronization termed Phase Locking Value (PLV). Behavioural data showed learning effects in both groups, with a steeper learning curve and higher ultimate attainment for the highly skilled learners. Moreover, we established that cortical connectivity patterns and profiles of spectral power modulations over time differentiated L2 learners with various levels of language analytical abilities. Over the course of the task, the learning process seemed to be driven by whole-brain functional connectivity between neuronal assemblies achieved by means of communication in the beta band frequency. On a shorter time-scale, increasing proficiency on the AGL task appeared to be supported by stronger local synchronisation within the right hemisphere regions. Finally, we observed that the highly skilled learners might have exerted less mental effort, or reduced attention for the task at hand once the learning was achieved, as evidenced by the higher alpha band power. Copyright © 2017 Elsevier Inc. All rights reserved.

Midfrontal Theta and Posterior Parietal Alpha Band Oscillations Support Conflict Resolution in a Masked Affective Priming Task.

Science.gov (United States)

Jiang, Jun; Bailey, Kira; Xiao, Xiao

2018-01-01

Past attempts to characterize the neural mechanisms of affective priming have conceptualized it in terms of classic cognitive conflict, but have not examined the neural oscillatory mechanisms of subliminal affective priming. Using behavioral and electroencephalogram (EEG) time frequency (TF) analysis, the current study examines the oscillatory dynamics of unconsciously triggered conflict in an emotional facial expressions version of the masked affective priming task. The results demonstrate that the power dynamics of conflict are characterized by increased midfrontal theta activity and suppressed parieto-occipital alpha activity. Across-subject and within-trial correlation analyses further confirmed this pattern. Phase synchrony and Granger causality analyses (GCAs) revealed that the fronto-parietal network was involved in unconscious conflict detection and resolution. Our findings support a response conflict account of affective priming, and reveal the role of the fronto-parietal network in unconscious conflict control.

Midfrontal Theta and Posterior Parietal Alpha Band Oscillations Support Conflict Resolution in a Masked Affective Priming Task

Directory of Open Access Journals (Sweden)

Jun Jiang

2018-05-01

Full Text Available Past attempts to characterize the neural mechanisms of affective priming have conceptualized it in terms of classic cognitive conflict, but have not examined the neural oscillatory mechanisms of subliminal affective priming. Using behavioral and electroencephalogram (EEG time frequency (TF analysis, the current study examines the oscillatory dynamics of unconsciously triggered conflict in an emotional facial expressions version of the masked affective priming task. The results demonstrate that the power dynamics of conflict are characterized by increased midfrontal theta activity and suppressed parieto-occipital alpha activity. Across-subject and within-trial correlation analyses further confirmed this pattern. Phase synchrony and Granger causality analyses (GCAs revealed that the fronto-parietal network was involved in unconscious conflict detection and resolution. Our findings support a response conflict account of affective priming, and reveal the role of the fronto-parietal network in unconscious conflict control.

Decreased somatosensory activity to non-threatening touch in combat veterans with posttraumatic stress disorder.

Science.gov (United States)

Badura-Brack, Amy S; Becker, Katherine M; McDermott, Timothy J; Ryan, Tara J; Becker, Madelyn M; Hearley, Allison R; Heinrichs-Graham, Elizabeth; Wilson, Tony W

2015-08-30

Posttraumatic stress disorder (PTSD) is a severe psychiatric disorder prevalent in combat veterans. Previous neuroimaging studies have demonstrated that patients with PTSD exhibit abnormal responses to non-threatening visual and auditory stimuli, but have not examined somatosensory processing. Thirty male combat veterans, 16 with PTSD and 14 without, completed a tactile stimulation task during a 306-sensor magnetoencephalography (MEG) recording. Significant oscillatory neural responses were imaged using a beamforming approach. Participants also completed clinical assessments of PTSD, combat exposure, and depression. We found that veterans with PTSD exhibited significantly reduced activity during early (0-125 ms) tactile processing compared with combat controls. Specifically, veterans with PTSD had weaker activity in the left postcentral gyrus, left superior parietal area, and right prefrontal cortex in response to nonthreatening tactile stimulation relative to veterans without PTSD. The magnitude of activity in these brain regions was inversely correlated with symptom severity, indicating that those with the most severe PTSD had the most abnormal neural responses. Our findings are consistent with a resource allocation view of perceptual processing in PTSD, which directs attention away from nonthreatening sensory information. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Evaluation of the Performance of Feedforward and Recurrent Neural Networks in Active Cancellation of Sound Noise

OpenAIRE

Mehrshad Salmasi; Homayoun Mahdavi-Nasab

2012-01-01

Active noise control is based on the destructive interference between the primary noise and generated noise from the secondary source. An antinoise of equal amplitude and opposite phase is generated and combined with the primary noise. In this paper, performance of the neural networks is evaluated in active cancellation of sound noise. For this reason, feedforward and recurrent neural networks are designed and trained. After training, performance of the feedforwrad and recurrent networks in n...

Effects of detergent on calcium-activated neutral proteinase (CANP) of neural and non-neural tissues in rat. A comparative study

International Nuclear Information System (INIS)

Banik, N.L.; Chakrabarti, A.K.; Hogan, E.L.

1987-01-01

Homogenates of brain, liver, kidney, heart and skeletal muscle of rat were prepared in 0.32 M-sucrose containing 2 mM EDTA. The CANP activity was assayed using 14 C-azocasein as substrate in 50 mM Tris acetate buffer, pH 7.4, 0.1% Triton X-100 and 5 mM-β-mercaptoethanol, with and without CaCl 2 . Addition to CNS membranes of other non-ionic detergents including sodium deoxycholate, β-D-thiogluco-pyranoside, and cetyltrimethyl-ammonium bromide activated the enzyme to varying extent depending on the detergent concentration. The ionic detergent sodium dodecyl sulfate abolished CANP activity completely in all preparations and this effect could not be reversed by non-ionic detergents. The most interesting feature of the Triton X-100 effect was a ten-fold increase of CNS CANP activity whereas non-neural CANP was not at all induced by Triton. CNS CANP was found mainly in the particulate fraction and only 30% in cytosol. In contrast, non-neural CANP was present mainly in cytosol. These results suggest that the bulk of CANP is membrane bound in CNS and differs from other tissue where it remains cytosolic

Enhancing Rotational Diffusion Using Oscillatory Shear

KAUST Repository

Leahy, Brian D.

2013-05-29

Taylor dispersion - shear-induced enhancement of translational diffusion - is an important phenomenon with applications ranging from pharmacology to geology. Through experiments and simulations, we show that rotational diffusion is also enhanced for anisotropic particles in oscillatory shear. This enhancement arises from variations in the particle\\'s rotation (Jeffery orbit) and depends on the strain amplitude, rate, and particle aspect ratio in a manner that is distinct from the translational diffusion. This separate tunability of translational and rotational diffusion opens the door to new techniques for controlling positions and orientations of suspended anisotropic colloids. © 2013 American Physical Society.

Multistability of delayed complex-valued recurrent neural networks with discontinuous real-imaginary-type activation functions

International Nuclear Information System (INIS)

Huang Yu-Jiao; Hu Hai-Gen

2015-01-01

In this paper, the multistability issue is discussed for delayed complex-valued recurrent neural networks with discontinuous real-imaginary-type activation functions. Based on a fixed theorem and stability definition, sufficient criteria are established for the existence and stability of multiple equilibria of complex-valued recurrent neural networks. The number of stable equilibria is larger than that of real-valued recurrent neural networks, which can be used to achieve high-capacity associative memories. One numerical example is provided to show the effectiveness and superiority of the presented results. (paper)

The Oscillatory Nature of Rotating Convection in Liquid Metal

Science.gov (United States)

Aurnou, J. M.; Bertin, V. L.; Grannan, A. M.

2016-12-01

Earth's magnetic field is assumed to be generated by fluid motions in its liquid metal core. In this fluid, the heat diffuses significantly more than momentum and thus, the ratio of these two diffusivities, the Prandtl number Pr=ν/Κ, is well below unity. The convective flow dynamics of liquid metal is very different from Pr ≈ 1 fluids like water and those used in current dynamo simulations. In order to characterize rapidly rotating thermal convection in low Pr number fluids, we have performed laboratory experiments in a cylinder using liquid gallium (Pr ≈ 0.023) as the working fluid. The Ekman number, which characterizes the effect of rotation, varies from E = 4 10-5 to 4 10-6 and the dimensionless buoyancy forcing (Rayleigh number, Ra) varies from Ra =3 105 to 2 107. Using heat transfer measurements (Nusselt number, Nu) as well as temperature measurements within the fluid, we characterize the different styles of low Pr rotating convective flow. The convection threshold is first overcome in the form of a container scale inertial oscillatory mode. At stronger forcing, wall-localized modes are identified for the first time in liquid metal laboratory experiments. These wall modes coexist with the bulk inertial oscillatory modes. When the strengh of the buoyancy increases, the bulk flow becomes turbulent while the wall modes remain. Our results imply that rotating convective flows in liquid metals do not develop in the form of quasi-steady columns, as in Pr ≈ 1 dynamo models, but in the form of oscillatory motions. Therefore, the flows that drive thermally-driven dynamo action in low Pr geophysical and astrophysical fluids can differ substantively than those occuring in current-day Pr ≈ 1 numerical models. In addition, our results suggest that relatively low wavenumber, wall-attached modes may be dynamically important in rapidly-rotating convection in liquid metals.

Operant conditioning of neural activity in freely behaving monkeys with intracranial reinforcement.

Science.gov (United States)

Eaton, Ryan W; Libey, Tyler; Fetz, Eberhard E

2017-03-01

Operant conditioning of neural activity has typically been performed under controlled behavioral conditions using food reinforcement. This has limited the duration and behavioral context for neural conditioning. To reward cell activity in unconstrained primates, we sought sites in nucleus accumbens (NAc) whose stimulation reinforced operant responding. In three monkeys, NAc stimulation sustained performance of a manual target-tracking task, with response rates that increased monotonically with increasing NAc stimulation. We recorded activity of single motor cortex neurons and documented their modulation with wrist force. We conditioned increased firing rates with the monkey seated in the training booth and during free behavior in the cage using an autonomous head-fixed recording and stimulating system. Spikes occurring above baseline rates triggered single or multiple electrical pulses to the reinforcement site. Such rate-contingent, unit-triggered stimulation was made available for periods of 1-3 min separated by 3-10 min time-out periods. Feedback was presented as event-triggered clicks both in-cage and in-booth, and visual cues were provided in many in-booth sessions. In-booth conditioning produced increases in single neuron firing probability with intracranial reinforcement in 48 of 58 cells. Reinforced cell activity could rise more than five times that of non-reinforced activity. In-cage conditioning produced significant increases in 21 of 33 sessions. In-cage rate changes peaked later and lasted longer than in-booth changes, but were often comparatively smaller, between 13 and 18% above non-reinforced activity. Thus intracranial stimulation reinforced volitional increases in cortical firing rates during both free behavior and a controlled environment, although changes in the latter were more robust. NEW & NOTEWORTHY Closed-loop brain-computer interfaces (BCI) were used to operantly condition increases in muscle and neural activity in monkeys by delivering

Similar patterns of neural activity predict memory function during encoding and retrieval.

Science.gov (United States)

Kragel, James E; Ezzyat, Youssef; Sperling, Michael R; Gorniak, Richard; Worrell, Gregory A; Berry, Brent M; Inman, Cory; Lin, Jui-Jui; Davis, Kathryn A; Das, Sandhitsu R; Stein, Joel M; Jobst, Barbara C; Zaghloul, Kareem A; Sheth, Sameer A; Rizzuto, Daniel S; Kahana, Michael J

2017-07-15

Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. Copyright © 2017 Elsevier Inc. All rights reserved.

Model Integrating Fuzzy Argument with Neural Network Enhancing the Performance of Active Queue Management

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Nguyen Kim Quoc

2015-08-01

Full Text Available The bottleneck control by active queue management mechanisms at network nodes is essential. In recent years, some researchers have used fuzzy argument to improve the active queue management mechanisms to enhance the network performance. However, the projects using the fuzzy controller depend heavily on professionals and their parameters cannot be updated according to changes in the network, so the effectiveness of this mechanism is not high. Therefore, we propose a model combining the fuzzy controller with neural network (FNN to overcome the limitations above. Results of the training of the neural networks will find the optimal parameters for the adaptive fuzzy controller well to changes of the network. This improves the operational efficiency of the active queue management mechanisms at network nodes.

Meditation reduces pain-related neural activity in the anterior cingulate cortex, insula, secondary somatosensory cortex, and thalamus

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Nakata, Hiroki; Sakamoto, Kiwako; Kakigi, Ryusuke

2014-01-01

Recent studies have shown that meditation inhibits or relieves pain perception. To clarify the underlying mechanisms for this phenomenon, neuroimaging methods, such as functional magnetic resonance imaging, and neurophysiological methods, such as magnetoencephalography and electroencephalography, have been used. However, it has been difficult to interpret the results, because there is some paradoxical evidence. For example, some studies reported increased neural responses to pain stimulation during meditation in the anterior cingulate cortex (ACC) and insula, whereas others showed a decrease in these regions. There have been inconsistent findings to date. Moreover, in general, since the activities of the ACC and insula are correlated with pain perception, the increase in neural activities during meditation would be related to the enhancement of pain perception rather than its reduction. These contradictions might directly contribute to the ‘mystery of meditation.’ In this review, we presented previous findings for brain regions during meditation and the anatomical changes that occurred in the brain with long-term meditation training. We then discussed the findings of previous studies that examined pain-related neural activity during meditation. We also described the brain mechanisms responsible for pain relief during meditation, and possible reasons for paradoxical evidence among previous studies. By thoroughly overviewing previous findings, we hypothesized that meditation reduces pain-related neural activity in the ACC, insula, secondary somatosensory cortex, and thalamus. We suggest that the characteristics of the modulation of this activity may depend on the kind of meditation and/or number of years of experience of meditation, which were associated with paradoxical findings among previous studies that investigated pain-related neural activities during meditation. PMID:25566158

Oscillatory device for use with linear tribometer, for tribological evaluation of biomaterials

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Athayde, J. N.; Siqueira, C. J. M.; Kuromoto, N. K.; Cambraia, H. N.

2017-07-01

Orthopedic implants still have limitations regarding their durability, despite being in use for over fifty years. Particles arising from wear due to the relative motion of their surfaces remain responsible for aseptic failure. This paper presents a device to be coupled with a reciprocal linear tribometer to reproduce the ex vivo wear of biomaterials, allowing the measurement of force and coefficient of friction. The device consists of a structure connected to the tribometer that transforms its reciprocal linear motion into one that is oscillatory for the mechanical assembly that contains the samples to test the desired biomaterials. The tribological pair used for testing consisted of Ultra High Molecular Weight Polyethylene (UHMWPE) in conjunction with the austenitic stainless steel AISI 316L in dry lubrication. The results showed that the values of the coefficient of friction in the linear mode and oscillatory mode and the UHMWPE life curve in the oscillatory mode were consistent with those cited in the literature for tests in a dry lubrication environment. Moreover, the UHMWPE sample life curve showed a reduction in the wear rate that can be explained by the preponderance of a wear mechanism over the others. The volumetric wear showed an increase with the number of cycles.

Evaluation of neural networks to identify types of activity using accelerometers

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Vries, S.I. de; Garre, F.G.; Engbers, L.H.; Hildebrandt, V.H.; Buuren, S. van

2011-01-01

Purpose: To develop and evaluate two artificial neural network (ANN) models based on single-sensor accelerometer data and an ANN model based on the data of two accelerometers for the identification of types of physical activity in adults. Methods: Forty-nine subjects (21 men and 28 women; age range

Brain reflections: A circuit-based framework for understanding information processing and cognitive control.

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Gratton, Gabriele

2018-03-01

Here, I propose a view of the architecture of the human information processing system, and of how it can be adapted to changing task demands (which is the hallmark of cognitive control). This view is informed by an interpretation of brain activity as reflecting the excitability level of neural representations, encoding not only stimuli and temporal contexts, but also action plans and task goals. The proposed cognitive architecture includes three types of circuits: open circuits, involved in feed-forward processing such as that connecting stimuli with responses and characterized by brief, transient brain activity; and two types of closed circuits, positive feedback circuits (characterized by sustained, high-frequency oscillatory activity), which help select and maintain representations, and negative feedback circuits (characterized by brief, low-frequency oscillatory bursts), which are instead associated with changes in representations. Feed-forward activity is primarily responsible for the spread of activation along the information processing system. Oscillatory activity, instead, controls this spread. Sustained oscillatory activity due to both local cortical circuits (gamma) and longer corticothalamic circuits (alpha and beta) allows for the selection of individuated representations. Through the interaction of these circuits, it also allows for the preservation of representations across different temporal spans (sensory and working memory) and their spread across the brain. In contrast, brief bursts of oscillatory activity, generated by novel and/or conflicting information, lead to the interruption of sustained oscillatory activity and promote the generation of new representations. I discuss how this framework can account for a number of psychological and behavioral phenomena. © 2017 Society for Psychophysiological Research.

Deep neural nets as a method for quantitative structure-activity relationships.

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Ma, Junshui; Sheridan, Robert P; Liaw, Andy; Dahl, George E; Svetnik, Vladimir

2015-02-23

Neural networks were widely used for quantitative structure-activity relationships (QSAR) in the 1990s. Because of various practical issues (e.g., slow on large problems, difficult to train, prone to overfitting, etc.), they were superseded by more robust methods like support vector machine (SVM) and random forest (RF), which arose in the early 2000s. The last 10 years has witnessed a revival of neural networks in the machine learning community thanks to new methods for preventing overfitting, more efficient training algorithms, and advancements in computer hardware. In particular, deep neural nets (DNNs), i.e. neural nets with more than one hidden layer, have found great successes in many applications, such as computer vision and natural language processing. Here we show that DNNs can routinely make better prospective predictions than RF on a set of large diverse QSAR data sets that are taken from Merck's drug discovery effort. The number of adjustable parameters needed for DNNs is fairly large, but our results show that it is not necessary to optimize them for individual data sets, and a single set of recommended parameters can achieve better performance than RF for most of the data sets we studied. The usefulness of the parameters is demonstrated on additional data sets not used in the calibration. Although training DNNs is still computationally intensive, using graphical processing units (GPUs) can make this issue manageable.

Bistable flapping of flexible flyers in oscillatory flow

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Huang, Yangyang; Kanso, Eva

2016-11-01

Biological and bio-inspired flyers move by shape actuation. The direct control of shape variables for locomotory purposes is well studied. Less is known about indirect shape actuation via the fluid medium. Here, we consider a flexible Λ-flyer in oscillatory flow that is free to flap and rotate around its fixed apex. We study its motion in the context of the inviscid vortex sheet model. We first analyze symmetric flapping about the vertical axis of gravity. We find that there is a finite value of the flexibility that maximizes both the flapping amplitude and elastic energy storage. Our results show that rather than resonance, the flyer relies on fluidic effects to optimize these two quantities. We then perturb the flyer away from the vertical and analyze its stability. Four distinct types of rolling behavior are identified: mono-stable, bistable, bistable oscillatory rotations and chaotic dynamics. We categorize these types of behavior in terms of the flyer's and flow parameters. In particular, the transition from mono-stable to bistable behavior occurs at a constant value of the product of the flow amplitude and acceleration. This product can be interpreted as the ratio of fluidic drag to gravity, confirming the fluid role in this transition.

Psychopathic traits linked to alterations in neural activity during personality judgments of self and others

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Philip Deming

Full Text Available Psychopathic individuals are notorious for their grandiose sense of self-worth and disregard for the welfare of others. One potential psychological mechanism underlying these traits is the relative consideration of “self” versus “others”. Here we used task-based functional magnetic resonance imaging (fMRI to identify neural responses during personality trait judgments about oneself and a familiar other in a sample of adult male incarcerated offenders (n = 57. Neural activity was regressed on two clusters of psychopathic traits: Factor 1 (e.g., egocentricity and lack of empathy and Factor 2 (e.g., impulsivity and irresponsibility. Contrary to our hypotheses, Factor 1 scores were not significantly related to neural activity during self- or other-judgments. However, Factor 2 traits were associated with diminished activation to self-judgments, in relation to other-judgments, in bilateral posterior cingulate cortex and right temporoparietal junction. These findings highlight cortical regions associated with a dimension of social-affective cognition that may underlie psychopathic individuals' impulsive traits. Keywords: Psychopathy, fMRI, Social cognition, Self-referential processing, Emotion, Psychopathology

A new perspective on behavioral inconsistency and neural noise in aging: Compensatory speeding of neural communication

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S. Lee Hong

2012-09-01

Full Text Available This paper seeks to present a new perspective on the aging brain. Here, we make connections between two key phenomena of brain aging: 1 increased neural noise or random background activity; and 2 slowing of brain activity. Our perspective proposes the possibility that the slowing of neural processing due to decreasing nerve conduction velocities leads to a compensatory speeding of neuron firing rates. These increased firing rates lead to a broader distribution of power in the frequency spectrum of neural oscillations, which we propose, can just as easily be interpreted as neural noise. Compensatory speeding of neural activity, as we present, is constrained by the: A availability of metabolic energy sources; and B competition for frequency bandwidth needed for neural communication. We propose that these constraints lead to the eventual inability to compensate for age-related declines in neural function that are manifested clinically as deficits in cognition, affect, and motor behavior.

Vascular Endothelial Growth Factor Receptor 3 Controls Neural Stem Cell Activation in Mice and Humans

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Jinah Han

2015-02-01

Full Text Available Neural stem cells (NSCs continuously produce new neurons within the adult mammalian hippocampus. NSCs are typically quiescent but activated to self-renew or differentiate into neural progenitor cells. The molecular mechanisms of NSC activation remain poorly understood. Here, we show that adult hippocampal NSCs express vascular endothelial growth factor receptor (VEGFR 3 and its ligand VEGF-C, which activates quiescent NSCs to enter the cell cycle and generate progenitor cells. Hippocampal NSC activation and neurogenesis are impaired by conditional deletion of Vegfr3 in NSCs. Functionally, this is associated with compromised NSC activation in response to VEGF-C and physical activity. In NSCs derived from human embryonic stem cells (hESCs, VEGF-C/VEGFR3 mediates intracellular activation of AKT and ERK pathways that control cell fate and proliferation. These findings identify VEGF-C/VEGFR3 signaling as a specific regulator of NSC activation and neurogenesis in mammals.

Methods for parameter identification in oscillatory networks and application to cortical and thalamic 600 Hz activity.

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Leistritz, L; Suesse, T; Haueisen, J; Hilgenfeld, B; Witte, H

2006-01-01

Directed information transfer in the human brain occurs presumably by oscillations. As of yet, most approaches for the analysis of these oscillations are based on time-frequency or coherence analysis. The present work concerns the modeling of cortical 600 Hz oscillations, localized within the Brodmann Areas 3b and 1 after stimulation of the nervus medianus, by means of coupled differential equations. This approach leads to the so-called parameter identification problem, where based on a given data set, a set of unknown parameters of a system of ordinary differential equations is determined by special optimization procedures. Some suitable algorithms for this task are presented in this paper. Finally an oscillatory network model is optimally fitted to the data taken from ten volunteers.

Histamine H3 receptor density is negatively correlated with neural activity related to working memory in humans.

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Ito, Takehito; Kimura, Yasuyuki; Seki, Chie; Ichise, Masanori; Yokokawa, Keita; Kawamura, Kazunori; Takahashi, Hidehiko; Higuchi, Makoto; Zhang, Ming-Rong; Suhara, Tetsuya; Yamada, Makiko

2018-06-14

The histamine H 3 receptor is regarded as a drug target for cognitive impairments in psychiatric disorders. H 3 receptors are expressed in neocortical areas, including the prefrontal cortex, the key region of cognitive functions such as working memory. However, the role of prefrontal H 3 receptors in working memory has not yet been clarified. Therefore, using functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) techniques, we aimed to investigate the association between the neural activity of working memory and the density of H 3 receptors in the prefrontal cortex. Ten healthy volunteers underwent both fMRI and PET scans. The N-back task was used to assess the neural activities related to working memory. H 3 receptor density was measured with the selective PET radioligand [ 11 C] TASP457. The neural activity of the right dorsolateral prefrontal cortex during the performance of the N-back task was negatively correlated with the density of H 3 receptors in this region. Higher neural activity of working memory was associated with lower H 3 receptor density in the right dorsolateral prefrontal cortex. This finding elucidates the role of H 3 receptors in working memory and indicates the potential of H 3 receptors as a therapeutic target for the cognitive impairments associated with neuropsychiatric disorders.

Effect of Temperature on Oscillatory Behaviour of the System Containing Isomers of Hydroxybenzoic Acid in Batch Reactor

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Masood A. Nath

2008-01-01

Full Text Available In the present paper a thorough study of temperature dependence on oscillatory behaviour of the Belousov-Zhabotinsky (BZ system containing the isomers of hydroxybenzoic acids + BrO3-+ Mn(II in aqueous acid medium (1.0 M H2SO4 at a fixed concentration of reacting species has been reported. On varying temperature, the oscillatory parameters like induction time, time period and number of oscillations show marked changes. These changes arise due to the position and number of hydroxyl groups in these isomers which affect the oscillations. Experimental observations have satisfactorily been explained by FKN mechanism and kinetic parameters. The oscillatory characteristics depend on the temperature dependence of the rate constant of the reaction controlling the inhibitory reaction steps (negative feedback

Concurrent OCT imaging of stimulus evoked retinal neural activation and hemodynamic responses

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Son, Taeyoon; Wang, Benquan; Lu, Yiming; Chen, Yanjun; Cao, Dingcai; Yao, Xincheng

2017-02-01

It is well established that major retinal diseases involve distortions of the retinal neural physiology and blood vascular structures. However, the details of distortions in retinal neurovascular coupling associated with major eye diseases are not well understood. In this study, a multi-modal optical coherence tomography (OCT) imaging system was developed to enable concurrent imaging of retinal neural activity and vascular hemodynamics. Flicker light stimulation was applied to mouse retinas to evoke retinal neural responses and hemodynamic changes. The OCT images were acquired continuously during the pre-stimulation, light-stimulation, and post-stimulation phases. Stimulus-evoked intrinsic optical signals (IOSs) and hemodynamic changes were observed over time in blood-free and blood regions, respectively. Rapid IOSs change occurred almost immediately after stimulation. Both positive and negative signals were observed in adjacent retinal areas. The hemodynamic changes showed time delays after stimulation. The signal magnitudes induced by light stimulation were observed in blood regions and did not show significant changes in blood-free regions. These differences may arise from different mechanisms in blood vessels and neural tissues in response to light stimulation. These characteristics agreed well with our previous observations in mouse retinas. Further development of the multimodal OCT may provide a new imaging method for studying how retinal structures and metabolic and neural functions are affected by age-related macular degeneration (AMD), glaucoma, diabetic retinopathy (DR), and other diseases, which promises novel noninvasive biomarkers for early disease detection and reliable treatment evaluations of eye diseases.

Trait approach and avoidance motivation: lateralized neural activity associated with executive function.

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Spielberg, Jeffrey M; Miller, Gregory A; Engels, Anna S; Herrington, John D; Sutton, Bradley P; Banich, Marie T; Heller, Wendy

2011-01-01

Motivation and executive function are both necessary for the completion of goal-directed behavior. Research investigating the manner in which these processes interact is beginning to emerge and has implicated middle frontal gyrus (MFG) as a site of interaction for relevant neural mechanisms. However, this research has focused on state motivation, and it has not examined functional lateralization. The present study examined the impact of trait levels of approach and avoidance motivation on neural processes associated with executive function. Functional magnetic resonance imaging was conducted while participants performed a color-word Stroop task. Analyses identified brain regions in which trait approach and avoidance motivation (measured by questionnaires) moderated activation associated with executive control. Approach was hypothesized to be associated with left-lateralized MFG activation, whereas avoidance was hypothesized to be associated with right-lateralized MFG activation. Results supported both hypotheses. Present findings implicate areas of middle frontal gyrus in top-down control to guide behavior in accordance with motivational goals. Copyright © 2010 Elsevier Inc. All rights reserved.

Model for a flexible motor memory based on a self-active recurrent neural network.

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Boström, Kim Joris; Wagner, Heiko; Prieske, Markus; de Lussanet, Marc

2013-10-01

Using recent recurrent network architecture based on the reservoir computing approach, we propose and numerically simulate a model that is focused on the aspects of a flexible motor memory for the storage of elementary movement patterns into the synaptic weights of a neural network, so that the patterns can be retrieved at any time by simple static commands. The resulting motor memory is flexible in that it is capable to continuously modulate the stored patterns. The modulation consists in an approximately linear inter- and extrapolation, generating a large space of possible movements that have not been learned before. A recurrent network of thousand neurons is trained in a manner that corresponds to a realistic exercising scenario, with experimentally measured muscular activations and with kinetic data representing proprioceptive feedback. The network is "self-active" in that it maintains recurrent flow of activation even in the absence of input, a feature that resembles the "resting-state activity" found in the human and animal brain. The model involves the concept of "neural outsourcing" which amounts to the permanent shifting of computational load from higher to lower-level neural structures, which might help to explain why humans are able to execute learned skills in a fluent and flexible manner without the need for attention to the details of the movement. Copyright © 2013 Elsevier B.V. All rights reserved.

The relative phases of basal ganglia activities dynamically shape effective connectivity in Parkinson's disease.

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Cagnan, Hayriye; Duff, Eugene Paul; Brown, Peter

2015-06-01

Optimal phase alignment between oscillatory neural circuits is hypothesized to optimize information flow and enhance system performance. This theory is known as communication-through-coherence. The basal ganglia motor circuit exhibits exaggerated oscillatory and coherent activity patterns in Parkinson's disease. Such activity patterns are linked to compromised motor system performance as evinced by bradykinesia, rigidity and tremor, suggesting that network function might actually deteriorate once a certain level of net synchrony is exceeded in the motor circuit. Here, we characterize the processes underscoring excessive synchronization and its termination. To this end, we analysed local field potential recordings from the subthalamic nucleus and globus pallidus of five patients with Parkinson's disease (four male and one female, aged 37-64 years). We observed that certain phase alignments between subthalamic nucleus and globus pallidus amplified local neural synchrony in the beta frequency band while others either suppressed it or did not induce any significant change with respect to surrogates. The increase in local beta synchrony directly correlated with how long the two nuclei locked to beta-amplifying phase alignments. Crucially, administration of the dopamine prodrug, levodopa, reduced the frequency and duration of periods during which subthalamic and pallidal populations were phase-locked to beta-amplifying alignments. Conversely ON dopamine, the total duration over which subthalamic and pallidal populations were aligned to phases that left beta-amplitude unchanged with respect to surrogates increased. Thus dopaminergic input shifted circuit dynamics from persistent periods of locking to amplifying phase alignments, associated with compromised motoric function, to more dynamic phase alignment and improved motoric function. This effect of dopamine on local circuit resonance suggests means by which novel electrical interventions might prevent resonance

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

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Francisco Javier Ordóñez

2016-01-01

Full Text Available Human activity recognition (HAR tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: (i is suitable for multimodal wearable sensors; (ii can perform sensor fusion naturally; (iii does not require expert knowledge in designing features; and (iv explicitly models the temporal dynamics of feature activations. We evaluate our framework on two datasets, one of which has been used in a public activity recognition challenge. Our results show that our framework outperforms competing deep non-recurrent networks on the challenge dataset by 4% on average; outperforming some of the previous reported results by up to 9%. Our results show that the framework can be applied to homogeneous sensor modalities, but can also fuse multimodal sensors to improve performance. We characterise key architectural hyperparameters’ influence on performance to provide insights about their optimisation.

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition.

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Ordóñez, Francisco Javier; Roggen, Daniel

2016-01-18

Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: (i) is suitable for multimodal wearable sensors; (ii) can perform sensor fusion naturally; (iii) does not require expert knowledge in designing features; and (iv) explicitly models the temporal dynamics of feature activations. We evaluate our framework on two datasets, one of which has been used in a public activity recognition challenge. Our results show that our framework outperforms competing deep non-recurrent networks on the challenge dataset by 4% on average; outperforming some of the previous reported results by up to 9%. Our results show that the framework can be applied to homogeneous sensor modalities, but can also fuse multimodal sensors to improve performance. We characterise key architectural hyperparameters' influence on performance to provide insights about their optimisation.

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

Science.gov (United States)

Ordóñez, Francisco Javier; Roggen, Daniel

2016-01-01

Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: (i) is suitable for multimodal wearable sensors; (ii) can perform sensor fusion naturally; (iii) does not require expert knowledge in designing features; and (iv) explicitly models the temporal dynamics of feature activations. We evaluate our framework on two datasets, one of which has been used in a public activity recognition challenge. Our results show that our framework outperforms competing deep non-recurrent networks on the challenge dataset by 4% on average; outperforming some of the previous reported results by up to 9%. Our results show that the framework can be applied to homogeneous sensor modalities, but can also fuse multimodal sensors to improve performance. We characterise key architectural hyperparameters’ influence on performance to provide insights about their optimisation. PMID:26797612

Transcranial alternating current stimulation (tACS increases risk taking behavior in the Balloon Analogue Risk Task

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Tal eSela

2012-02-01

Full Text Available The process of evaluating risks and benefits involves a complex neural network that includes the dorsolateral prefrontal cortex (DLPFC. It has been proposed that in conflict and reward situations, theta-band (4–8 Hz oscillatory activity in the frontal cortex may reflect an electrophysiological mechanism for coordinating neural networks monitoring behavior, as well as facilitating task-specific adaptive changes. The goal of the present study was to investigate the hypothesis that theta-band oscillatory balance between right and left frontal and prefrontal regions, with a predominance role to the right hemisphere, is crucial for regulatory control during decision-making under risk. In order to explore this hypothesis, we used transcranial Alternating Current Stimulation (tACS, a novel technique that provides the opportunity to explore the functional role of neuronal oscillatory activities and to establish a causal link between specific oscillations and functional lateralization in risky decision-making situations. For this aim, healthy participants were randomly allocated to one of three stimulation groups (LH stimulation / RH stimulation / Sham stimulation, with active AC stimulation delivered in a frequency-dependent manner (at 6.5 Hz; 1mA peak to-peak. During the AC stimulation, participants performed the Balloon Analog Risk Task. This experiment revealed that participants receiving LH stimulation displayed riskier decision-making style compared to sham and RH stimulation groups. However, there was no difference in decision-making behaviors between sham and RH stimulation groups. The current study extends the notion that DLPFC activity is critical for adaptive decision-making in the context of risk-taking and emphasis the role of theta-band oscillatory activity during risky decision-making situations.

Noise influence on spike activation in a Hindmarsh–Rose small-world neural network

International Nuclear Information System (INIS)

Zhe, Sun; Micheletto, Ruggero

2016-01-01

We studied the role of noise in neural networks, especially focusing on its relation to the propagation of spike activity in a small sized system. We set up a source of information using a single neuron that is constantly spiking. This element called initiator x o feeds spikes to the rest of the network that is initially quiescent and subsequently reacts with vigorous spiking after a transitional period of time. We found that noise quickly suppresses the initiator’s influence and favors spontaneous spike activity and, using a decibel representation of noise intensity, we established a linear relationship between noise amplitude and the interval from the initiator’s first spike and the rest of the network activation. We studied the same process with networks of different sizes (number of neurons) and found that the initiator x o has a measurable influence on small networks, but as the network grows in size, spontaneous spiking emerges disrupting its effects on networks of more than about N = 100 neurons. This suggests that the mechanism of internal noise generation allows information transmission within a small neural neighborhood, but decays for bigger network domains. We also analyzed the Fourier spectrum of the whole network membrane potential and verified that noise provokes the reduction of main θ and α peaks before transitioning into chaotic spiking. However, network size does not reproduce a similar phenomena; instead we recorded a reduction in peaks’ amplitude, a better sharpness and definition of Fourier peaks, but not the evident degeneration to chaos observed with increasing external noise. This work aims to contribute to the understanding of the fundamental mechanisms of propagation of spontaneous spiking in neural networks and gives a quantitative assessment of how noise can be used to control and modulate this phenomenon in Hindmarsh−Rose (H−R) neural networks. (paper)

Noise influence on spike activation in a Hindmarsh-Rose small-world neural network

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Zhe, Sun; Micheletto, Ruggero

2016-07-01

We studied the role of noise in neural networks, especially focusing on its relation to the propagation of spike activity in a small sized system. We set up a source of information using a single neuron that is constantly spiking. This element called initiator x o feeds spikes to the rest of the network that is initially quiescent and subsequently reacts with vigorous spiking after a transitional period of time. We found that noise quickly suppresses the initiator’s influence and favors spontaneous spike activity and, using a decibel representation of noise intensity, we established a linear relationship between noise amplitude and the interval from the initiator’s first spike and the rest of the network activation. We studied the same process with networks of different sizes (number of neurons) and found that the initiator x o has a measurable influence on small networks, but as the network grows in size, spontaneous spiking emerges disrupting its effects on networks of more than about N = 100 neurons. This suggests that the mechanism of internal noise generation allows information transmission within a small neural neighborhood, but decays for bigger network domains. We also analyzed the Fourier spectrum of the whole network membrane potential and verified that noise provokes the reduction of main θ and α peaks before transitioning into chaotic spiking. However, network size does not reproduce a similar phenomena; instead we recorded a reduction in peaks’ amplitude, a better sharpness and definition of Fourier peaks, but not the evident degeneration to chaos observed with increasing external noise. This work aims to contribute to the understanding of the fundamental mechanisms of propagation of spontaneous spiking in neural networks and gives a quantitative assessment of how noise can be used to control and modulate this phenomenon in Hindmarsh-Rose (H-R) neural networks.

Bottom-up driven involuntary auditory evoked field change: constant sound sequencing amplifies but does not sharpen neural activity.

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Okamoto, Hidehiko; Stracke, Henning; Lagemann, Lothar; Pantev, Christo

2010-01-01

The capability of involuntarily tracking certain sound signals during the simultaneous presence of noise is essential in human daily life. Previous studies have demonstrated that top-down auditory focused attention can enhance excitatory and inhibitory neural activity, resulting in sharpening of frequency tuning of auditory neurons. In the present study, we investigated bottom-up driven involuntary neural processing of sound signals in noisy environments by means of magnetoencephalography. We contrasted two sound signal sequencing conditions: "constant sequencing" versus "random sequencing." Based on a pool of 16 different frequencies, either identical (constant sequencing) or pseudorandomly chosen (random sequencing) test frequencies were presented blockwise together with band-eliminated noises to nonattending subjects. The results demonstrated that the auditory evoked fields elicited in the constant sequencing condition were significantly enhanced compared with the random sequencing condition. However, the enhancement was not significantly different between different band-eliminated noise conditions. Thus the present study confirms that by constant sound signal sequencing under nonattentive listening the neural activity in human auditory cortex can be enhanced, but not sharpened. Our results indicate that bottom-up driven involuntary neural processing may mainly amplify excitatory neural networks, but may not effectively enhance inhibitory neural circuits.

Complementary roles of different oscillatory activities in the subthalamic nucleus in coding motor effort in Parkinsonism.

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Tan, Huiling; Pogosyan, Alek; Anzak, Anam; Ashkan, Keyoumars; Bogdanovic, Marko; Green, Alexander L; Aziz, Tipu; Foltynie, Thomas; Limousin, Patricia; Zrinzo, Ludvic; Brown, Peter

2013-10-01

The basal ganglia may play an important role in the control of motor scaling or effort. Recently local field potential (LFP) recordings from patients with deep brain stimulation electrodes in the basal ganglia have suggested that local increases in the synchronisation of neurons in the gamma frequency band may correlate with force or effort. Whether this feature uniquely codes for effort and whether such a coding mechanism holds true over a range of efforts is unclear. Here we investigated the relationship between frequency-specific oscillatory activities in the subthalamic nucleus (STN) and manual grips made with different efforts. The latter were self-rated using the 10 level Borg scale ranging from 0 (no effort) to 10 (maximal effort). STN LFP activities were recorded in patients with Parkinson's Disease (PD) who had undergone functional surgery. Patients were studied while motor performance was improved by dopaminergic medication. In line with previous studies we observed power increase in the theta/alpha band (4-12 Hz), power suppression in the beta band (13-30 Hz) and power increase in the gamma band (55-90 Hz) and high frequency band (101-375 Hz) during voluntary grips. Beta suppression deepened, and then reached a floor level as effort increased. Conversely, gamma and high frequency power increases were enhanced during grips made with greater effort. Multiple regression models incorporating the four different spectral changes confirmed that the modulation of power in the beta band was the only independent predictor of effort during grips made with efforts rated <5. In contrast, increases in gamma band activity were the only independent predictor of effort during grips made with efforts ≥5. Accordingly, the difference between power changes in the gamma and beta bands correlated with effort across all effort levels. These findings suggest complementary roles for changes in beta and gamma band activities in the STN in motor effort coding. The latter function

Dynamic behavior of the bray-liebhafsky oscillatory reaction controlled by sulfuric acid and temperature

Science.gov (United States)

Pejić, N.; Vujković, M.; Maksimović, J.; Ivanović, A.; Anić, S.; Čupić, Ž.; Kolar-Anić, Lj.

2011-12-01

The non-periodic, periodic and chaotic regimes in the Bray-Liebhafsky (BL) oscillatory reaction observed in a continuously fed well stirred tank reactor (CSTR) under isothermal conditions at various inflow concentrations of the sulfuric acid were experimentally studied. In each series (at any fixed temperature), termination of oscillatory behavior via saddle loop infinite period bifurcation (SNIPER) as well as some kind of the Andronov-Hopf bifurcation is presented. In addition, it was found that an increase of temperature, in different series of experiments resulted in the shift of bifurcation point towards higher values of sulfuric acid concentration.

The importance of cutaneous feedback on neural activation during maximal voluntary contraction

NARCIS (Netherlands)

Cruz-Montecinos, Carlos; Maas, Huub; Pellegrin-Friedmann, Carla; Tapia, Claudio

2017-01-01

Purpose: The purpose of this study was to investigate the importance of cutaneous feedback on neural activation during maximal voluntary contraction (MVC) of the ankle plantar flexors. Methods: The effects of cutaneous plantar anaesthesia were assessed in 15 subjects and compared to 15 controls,

Propulsion of a microsubmarine using a thermally oscillatory approach

International Nuclear Information System (INIS)

Qiao, Lei; Luo, Cheng

2013-01-01

In this paper, motivated by the driving mechanism of a putt-putt toy boat, we explore the feasibility to propel a microsubmarine using a thermally oscillatory approach, which only requires a simple design and does not involve any complicated propulsive systems. We investigate the design, fabrication, actuation and horizontal motions of the corresponding microsubmarines. Based on the understanding gained through preliminary tests on two manually fabricated putt-putt boats, we designed and fabricated the prototype of a microsubmarine. Similar to a putt-putt boat, the prototype also uses a thermally oscillatory process for propulsion. In a cyclic period of this process, due to the expansion and shrinkage of a vapor bubble inside the reservoir of the submarine, liquid is first ejected outside and then sucked into the reservoir. Due to the difference in liquid flow directions between ejection and suction stages, a thrust is produced to propel the submarine. At an applied voltage of 16 V and pulse frequency of 100 Hz, the submarine was found to have the highest speed of 1.8 mm s −1 and longest travel distance of 12.6 mm. The corresponding thrust was estimated to be 67.6 nN. (paper)

Neural activity in the prelimbic and infralimbic cortices of freely moving rats during social interaction: Effect of isolation rearing

Science.gov (United States)

Minami, Chihiro; Shimizu, Tomoko

2017-01-01

Sociability promotes a sound daily life for individuals. Reduced sociability is a central symptom of various neuropsychiatric disorders, and yet the neural mechanisms underlying reduced sociability remain unclear. The prelimbic cortex (PL) and infralimbic cortex (IL) have been suggested to play an important role in the neural mechanisms underlying sociability because isolation rearing in rats results in impairment of social behavior and structural changes in the PL and IL. One possible mechanism underlying reduced sociability involves dysfunction of the PL and IL. We made a wireless telemetry system to record multiunit activity in the PL and IL of pairs of freely moving rats during social interaction and examined the influence of isolation rearing on this activity. In group-reared rats, PL neurons increased firing when the rat showed approaching behavior and also contact behavior, especially when the rat attacked the partner. Conversely, IL neurons increased firing when the rat exhibited leaving behavior, especially when the partner left on its own accord. In social interaction, the PL may be involved in active actions toward others, whereas the IL may be involved in passive relief from cautionary subjects. Isolation rearing altered social behavior and neural activity. Isolation-reared rats showed an increased frequency and decreased duration of contact behavior. The increased firing of PL neurons during approaching and contact behavior, observed in group-reared rats, was preserved in isolation-reared rats, whereas the increased firing of IL neurons during leaving behavior, observed in group-reared rats, was suppressed in isolation-reared rats. This result indicates that isolation rearing differentially alters neural activity in the PL and IL during social behavior. The differential influence of isolation rearing on neural activity in the PL and IL may be one of the neural bases of isolation rearing-induced behavior. PMID:28459875

Neural activity in the prelimbic and infralimbic cortices of freely moving rats during social interaction: Effect of isolation rearing.

Science.gov (United States)

Minami, Chihiro; Shimizu, Tomoko; Mitani, Akira

2017-01-01

Sociability promotes a sound daily life for individuals. Reduced sociability is a central symptom of various neuropsychiatric disorders, and yet the neural mechanisms underlying reduced sociability remain unclear. The prelimbic cortex (PL) and infralimbic cortex (IL) have been suggested to play an important role in the neural mechanisms underlying sociability because isolation rearing in rats results in impairment of social behavior and structural changes in the PL and IL. One possible mechanism underlying reduced sociability involves dysfunction of the PL and IL. We made a wireless telemetry system to record multiunit activity in the PL and IL of pairs of freely moving rats during social interaction and examined the influence of isolation rearing on this activity. In group-reared rats, PL neurons increased firing when the rat showed approaching behavior and also contact behavior, especially when the rat attacked the partner. Conversely, IL neurons increased firing when the rat exhibited leaving behavior, especially when the partner left on its own accord. In social interaction, the PL may be involved in active actions toward others, whereas the IL may be involved in passive relief from cautionary subjects. Isolation rearing altered social behavior and neural activity. Isolation-reared rats showed an increased frequency and decreased duration of contact behavior. The increased firing of PL neurons during approaching and contact behavior, observed in group-reared rats, was preserved in isolation-reared rats, whereas the increased firing of IL neurons during leaving behavior, observed in group-reared rats, was suppressed in isolation-reared rats. This result indicates that isolation rearing differentially alters neural activity in the PL and IL during social behavior. The differential influence of isolation rearing on neural activity in the PL and IL may be one of the neural bases of isolation rearing-induced behavior.