Patterns of neural response to emotive stimuli distinguish the different symptom dimensions of obsessive-compulsive disorder.

PubMed

Phillips, Mary L; Mataix-Cols, David

2004-04-01

Despite its heterogeneous symptomatology, obsessive-compulsive disorder (OCD) is currently conceptualized as a unitary diagnostic entity. Recent factor-analytic studies have identified several OCD symptom dimensions that are associated with different demographic variables, comorbidity, patterns of genetic transmission, and treatment response. Functional abnormalities in neural systems important for emotion perception, including the orbitofrontal cortex, lateral prefrontal cortex, anterior cingulate gyrus, and limbic regions, have been reported in OCD. In this review, we discuss the extent to which neurobiological markers may distinguish these different symptom dimensions and whether specific symptom dimensions, such as contamination/washing, are associated with abnormalities in emotion and, in particular, disgust, perception in OCD. Also discussed are findings that indicate that anxiety can be induced in healthy volunteers in response to OCD symptom-related material, and that associated increases in activity within neural systems important for emotion perception occur to washing- and hoarding-related material in particular in these subjects. Further examination of neural responses during provocation of different symptom dimensions in OCD patients will help determine the extent to which specific abnormalities in neural systems underlying emotion perception are associated with different symptom dimensions and predict treatment response in OCD.

Spatially Pooled Contrast Responses Predict Neural and Perceptual Similarity of Naturalistic Image Categories

PubMed Central

Groen, Iris I. A.; Ghebreab, Sennay; Lamme, Victor A. F.; Scholte, H. Steven

2012-01-01

The visual world is complex and continuously changing. Yet, our brain transforms patterns of light falling on our retina into a coherent percept within a few hundred milliseconds. Possibly, low-level neural responses already carry substantial information to facilitate rapid characterization of the visual input. Here, we computationally estimated low-level contrast responses to computer-generated naturalistic images, and tested whether spatial pooling of these responses could predict image similarity at the neural and behavioral level. Using EEG, we show that statistics derived from pooled responses explain a large amount of variance between single-image evoked potentials (ERPs) in individual subjects. Dissimilarity analysis on multi-electrode ERPs demonstrated that large differences between images in pooled response statistics are predictive of more dissimilar patterns of evoked activity, whereas images with little difference in statistics give rise to highly similar evoked activity patterns. In a separate behavioral experiment, images with large differences in statistics were judged as different categories, whereas images with little differences were confused. These findings suggest that statistics derived from low-level contrast responses can be extracted in early visual processing and can be relevant for rapid judgment of visual similarity. We compared our results with two other, well- known contrast statistics: Fourier power spectra and higher-order properties of contrast distributions (skewness and kurtosis). Interestingly, whereas these statistics allow for accurate image categorization, they do not predict ERP response patterns or behavioral categorization confusions. These converging computational, neural and behavioral results suggest that statistics of pooled contrast responses contain information that corresponds with perceived visual similarity in a rapid, low-level categorization task. PMID:23093921

Inactivity-induced phrenic and hypoglossal motor facilitation are differentially expressed following intermittent vs. sustained neural apnea

PubMed Central

Baertsch, N. A.

2013-01-01

Reduced respiratory neural activity elicits a rebound increase in phrenic and hypoglossal motor output known as inactivity-induced phrenic and hypoglossal motor facilitation (iPMF and iHMF, respectively). We hypothesized that, similar to other forms of respiratory plasticity, iPMF and iHMF are pattern sensitive. Central respiratory neural activity was reversibly reduced in ventilated rats by hyperventilating below the CO2 apneic threshold to create brief intermittent neural apneas (5, ∼1.5 min each, separated by 5 min), a single brief massed neural apnea (7.5 min), or a single prolonged neural apnea (30 min). Upon restoration of respiratory neural activity, long-lasting (>60 min) iPMF was apparent following brief intermittent and prolonged, but not brief massed, neural apnea. Further, brief intermittent and prolonged neural apnea elicited an increase in the maximum phrenic response to high CO2, suggesting that iPMF is associated with an increase in phrenic dynamic range. By contrast, only prolonged neural apnea elicited iHMF, which was transient in duration (<15 min). Intermittent, massed, and prolonged neural apnea all elicited a modest transient facilitation of respiratory frequency. These results indicate that iPMF, but not iHMF, is pattern sensitive, and that the response to respiratory neural inactivity is motor pool specific. PMID:23493368

Dynamic Modulation of Sensory Cortex by Top-Down Spatial Attention

DTIC Science & Technology

2015-04-15

yet only in recent decades has the neural basis for these benefits begun to be studied. The studies presented here use EEG and MEG to identify patterns...presented here use EEG and MEG to identify patterns of neural activity related to the deployment of attention in extrapersonal space, and examine the...we use simultaneously recorded EEG/ MEG to examine the interaction of these top-down signals with neural responses evoked by attended and unattended

Relationship between neural response and adaptation selectivity to form and color: an ERP study.

PubMed

Rentzeperis, Ilias; Nikolaev, Andrey R; Kiper, Daniel C; van Leeuwen, Cees

2012-01-01

Adaptation is widely used as a tool for studying selectivity to visual features. In these studies it is usually assumed that the loci of feature selective neural responses and adaptation coincide. We used an adaptation paradigm to investigate the relationship between response and adaptation selectivity in event-related potentials (ERPs). ERPs were evoked by the presentation of colored Glass patterns in a form discrimination task. Response selectivities to form and, to some extent, color of the patterns were reflected in the C1 and N1 ERP components. Adaptation selectivity to color was reflected in N1 and was followed by a late (300-500 ms after stimulus onset) effect of form adaptation. Thus for form, response and adaptation selectivity were manifested in non-overlapping intervals. These results indicate that adaptation and response selectivity can be associated with different processes. Therefore, inferring selectivity from an adaptation paradigm requires analysis of both adaptation and neural response data.

Cortical activity patterns predict robust speech discrimination ability in noise

PubMed Central

Shetake, Jai A.; Wolf, Jordan T.; Cheung, Ryan J.; Engineer, Crystal T.; Ram, Satyananda K.; Kilgard, Michael P.

2012-01-01

The neural mechanisms that support speech discrimination in noisy conditions are poorly understood. In quiet conditions, spike timing information appears to be used in the discrimination of speech sounds. In this study, we evaluated the hypothesis that spike timing is also used to distinguish between speech sounds in noisy conditions that significantly degrade neural responses to speech sounds. We tested speech sound discrimination in rats and recorded primary auditory cortex (A1) responses to speech sounds in background noise of different intensities and spectral compositions. Our behavioral results indicate that rats, like humans, are able to accurately discriminate consonant sounds even in the presence of background noise that is as loud as the speech signal. Our neural recordings confirm that speech sounds evoke degraded but detectable responses in noise. Finally, we developed a novel neural classifier that mimics behavioral discrimination. The classifier discriminates between speech sounds by comparing the A1 spatiotemporal activity patterns evoked on single trials with the average spatiotemporal patterns evoked by known sounds. Unlike classifiers in most previous studies, this classifier is not provided with the stimulus onset time. Neural activity analyzed with the use of relative spike timing was well correlated with behavioral speech discrimination in quiet and in noise. Spike timing information integrated over longer intervals was required to accurately predict rat behavioral speech discrimination in noisy conditions. The similarity of neural and behavioral discrimination of speech in noise suggests that humans and rats may employ similar brain mechanisms to solve this problem. PMID:22098331

Context-dependent plasticity in the subcortical encoding of linguistic pitch patterns

PubMed Central

Lau, Joseph C. Y.; Wong, Patrick C. M.

2016-01-01

We examined the mechanics of online experience-dependent auditory plasticity by assessing the influence of prior context on the frequency-following responses (FFRs), which reflect phase-locked responses from neural ensembles within the subcortical auditory system. FFRs were elicited to a Cantonese falling lexical pitch pattern from 24 native speakers of Cantonese in a variable context, wherein the falling pitch pattern randomly occurred in the context of two other linguistic pitch patterns; in a patterned context, wherein, the falling pitch pattern was presented in a predictable sequence along with two other pitch patterns, and in a repetitive context, wherein the falling pitch pattern was presented with 100% probability. We found that neural tracking of the stimulus pitch contour was most faithful and accurate when listening context was patterned and least faithful when the listening context was variable. The patterned context elicited more robust pitch tracking relative to the repetitive context, suggesting that context-dependent plasticity is most robust when the context is predictable but not repetitive. Our study demonstrates a robust influence of prior listening context that works to enhance online neural encoding of linguistic pitch patterns. We interpret these results as indicative of an interplay between contextual processes that are responsive to predictability as well as novelty in the presentation context. NEW & NOTEWORTHY Human auditory perception in dynamic listening environments requires fine-tuning of sensory signal based on behaviorally relevant regularities in listening context, i.e., online experience-dependent plasticity. Our finding suggests what partly underlie online experience-dependent plasticity are interplaying contextual processes in the subcortical auditory system that are responsive to predictability as well as novelty in listening context. These findings add to the literature that looks to establish the neurophysiological bases of auditory system plasticity, a central issue in auditory neuroscience. PMID:27832606

Context-dependent plasticity in the subcortical encoding of linguistic pitch patterns.

PubMed

Lau, Joseph C Y; Wong, Patrick C M; Chandrasekaran, Bharath

2017-02-01

We examined the mechanics of online experience-dependent auditory plasticity by assessing the influence of prior context on the frequency-following responses (FFRs), which reflect phase-locked responses from neural ensembles within the subcortical auditory system. FFRs were elicited to a Cantonese falling lexical pitch pattern from 24 native speakers of Cantonese in a variable context, wherein the falling pitch pattern randomly occurred in the context of two other linguistic pitch patterns; in a patterned context, wherein, the falling pitch pattern was presented in a predictable sequence along with two other pitch patterns, and in a repetitive context, wherein the falling pitch pattern was presented with 100% probability. We found that neural tracking of the stimulus pitch contour was most faithful and accurate when listening context was patterned and least faithful when the listening context was variable. The patterned context elicited more robust pitch tracking relative to the repetitive context, suggesting that context-dependent plasticity is most robust when the context is predictable but not repetitive. Our study demonstrates a robust influence of prior listening context that works to enhance online neural encoding of linguistic pitch patterns. We interpret these results as indicative of an interplay between contextual processes that are responsive to predictability as well as novelty in the presentation context. Human auditory perception in dynamic listening environments requires fine-tuning of sensory signal based on behaviorally relevant regularities in listening context, i.e., online experience-dependent plasticity. Our finding suggests what partly underlie online experience-dependent plasticity are interplaying contextual processes in the subcortical auditory system that are responsive to predictability as well as novelty in listening context. These findings add to the literature that looks to establish the neurophysiological bases of auditory system plasticity, a central issue in auditory neuroscience. Copyright © 2017 the American Physiological Society.

Differential spatial activity patterns of acupuncture by a machine learning based analysis

NASA Astrophysics Data System (ADS)

You, Youbo; Bai, Lijun; Xue, Ting; Zhong, Chongguang; Liu, Zhenyu; Tian, Jie

2011-03-01

Acupoint specificity, lying at the core of the Traditional Chinese Medicine, underlies the theoretical basis of acupuncture application. However, recent studies have reported that acupuncture stimulation at nonacupoint and acupoint can both evoke similar signal intensity decreases in multiple regions. And these regions were spatially overlapped. We used a machine learning based Support Vector Machine (SVM) approach to elucidate the specific neural response pattern induced by acupuncture stimulation. Group analysis demonstrated that stimulation at two different acupoints (belong to the same nerve segment but different meridians) could elicit distinct neural response patterns. Our findings may provide evidence for acupoint specificity.

Neural correlates of emotional responses to music: an EEG study.

PubMed

Daly, Ian; Malik, Asad; Hwang, Faustina; Roesch, Etienne; Weaver, James; Kirke, Alexis; Williams, Duncan; Miranda, Eduardo; Nasuto, Slawomir J

2014-06-24

This paper presents an EEG study into the neural correlates of music-induced emotions. We presented participants with a large dataset containing musical pieces in different styles, and asked them to report on their induced emotional responses. We found neural correlates of music-induced emotion in a number of frequencies over the pre-frontal cortex. Additionally, we found a set of patterns of functional connectivity, defined by inter-channel coherence measures, to be significantly different between groups of music-induced emotional responses. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Self-regulation via neural simulation

PubMed Central

Gilead, Michael; Boccagno, Chelsea; Silverman, Melanie; Hassin, Ran R.; Weber, Jochen; Ochsner, Kevin N.

2016-01-01

Can taking the perspective of other people modify our own affective responses to stimuli? To address this question, we examined the neurobiological mechanisms supporting the ability to take another person’s perspective and thereby emotionally experience the world as they would. We measured participants’ neural activity as they attempted to predict the emotional responses of two individuals that differed in terms of their proneness to experience negative affect. Results showed that behavioral and neural signatures of negative affect (amygdala activity and a distributed multivoxel pattern reflecting affective negativity) simulated the presumed affective state of the target person. Furthermore, the anterior medial prefrontal cortex (mPFC)—a region implicated in mental state inference—exhibited a perspective-dependent pattern of connectivity with the amygdala, and the multivoxel pattern of activity within the mPFC differentiated between the two targets. We discuss the implications of these findings for research on perspective-taking and self-regulation. PMID:27551094

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

PubMed

Ma, Ying; Shaik, Mohammed A; Kozberg, Mariel G; Kim, Sharon H; Portes, Jacob P; Timerman, Dmitriy; Hillman, Elizabeth M C

2016-12-27

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 (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that 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.

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

PubMed Central

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 (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that 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

Temporally diverse firing patterns in olfactory receptor neurons underlie spatiotemporal neural codes for odors

PubMed Central

Raman, Baranidharan; Joseph, Joby; Tang, Jeff; Stopfer, Mark

2010-01-01

Odorants are represented as spatiotemporal patterns of spikes in neurons of the antennal lobe (AL, insects) and olfactory bulb (OB, vertebrates). These response patterns have been thought to arise primarily from interactions within the AL/OB, an idea supported, in part, by the assumption that olfactory receptor neurons (ORNs) respond to odorants with simple firing patterns. However, activating the AL directly with simple pulses of current evoked responses in AL neurons that were much less diverse, complex, and enduring than responses elicited by odorants. Similarly, models of the AL driven by simplistic inputs generated relatively simple output. How then are dynamic neural codes for odors generated? Consistent with recent results from several other species, our recordings from locust ORNs showed a great diversity of temporal structure. Further, we found that, viewed as a population, many response features of ORNs were remarkably similar to those observed within the AL. Using a set of computational models constrained by our electrophysiological recordings, we found that the temporal heterogeneity of responses of ORNs critically underlies the generation of spatiotemporal odor codes in the AL. A test then performed in vivo confirmed that, given temporally homogeneous input, the AL cannot create diverse spatiotemporal patterns on its own; however, given temporally heterogeneous input, the AL generated realistic firing patterns. Finally, given the temporally structured input provided by ORNs, we clarified several separate, additional contributions of the AL to olfactory information processing. Thus, our results demonstrate the origin and subsequent reformatting of spatiotemporal neural codes for odors. PMID:20147528

Attention Alters Neural Responses to Evocative Faces in Behaviorally Inhibited Adolescents

PubMed Central

Pérez-Edgar, Koraly; Roberson-Nay, Roxann; Hardin, Michael G.; Poeth, Kaitlin; Guyer, Amanda E.; Nelson, Eric E.; McClure, Erin B.; Henderson, Heather A.; Fox, Nathan A.; Pine, Daniel S.; Ernst, Monique

2007-01-01

Behavioral inhibition (BI) is a risk factor for anxiety disorders. While the two constructs bear behavioral similarities, previous work has not extended these parallels to the neural level. This study examined amygdala reactivity during a task previously used with clinically anxious adolescents. Adolescents were selected for enduring patterns of BI or non-inhibition (BN). We examined amygdala response to evocative emotion faces in BI (N=10, mean 12.8 years) and BN (N=17, mean 12.5 years) adolescents while systematically manipulating attention. Analyses focused on amygdala response during subjective ratings of internal fear (constrained attention) and passive viewing (unconstrained attention) during the presentation of emotion faces (Happy, Angry, Fearful, and Neutral). BI adolescents, relative to BN adolescents, showed exaggerated amygdala response during subjective fear ratings and deactivation during passive viewing, across all emotion faces. In addition, the BI group showed an abnormally high amygdala response to a task condition marked by novelty and uncertainty (i.e., rating fear state to a Happy face). Perturbations in amygdala function are evident in adolescents temperamentally at risk for anxiety. Attention state alters the underlying pattern of neural processing, potentially mediating the observed behavioral patterns across development. BI adolescents also show a heightened sensitivity to novelty and uncertainty, which has been linked to anxiety. These patterns of reactivity may help sustain early temperamental biases over time and contribute to the observed relation between BI and anxiety. PMID:17376704

Computational advances towards linking BOLD and behavior.

PubMed

Serences, John T; Saproo, Sameer

2012-03-01

Traditionally, fMRI studies have focused on analyzing the mean response amplitude within a cortical area. However, the mean response is blind to many important patterns of cortical modulation, which severely limits the formulation and evaluation of linking hypotheses between neural activity, BOLD responses, and behavior. More recently, multivariate pattern classification analysis (MVPA) has been applied to fMRI data to evaluate the information content of spatially distributed activation patterns. This approach has been remarkably successful at detecting the presence of specific information in targeted brain regions, and provides an extremely flexible means of extracting that information without a precise generative model for the underlying neural activity. However, this flexibility comes at a cost: since MVPA relies on pooling information across voxels that are selective for many different stimulus attributes, it is difficult to infer how specific sub-sets of tuned neurons are modulated by an experimental manipulation. In contrast, recently developed encoding models can produce more precise estimates of feature-selective tuning functions, and can support the creation of explicit linking hypotheses between neural activity and behavior. Although these encoding models depend on strong - and often untested - assumptions about the response properties of underlying neural generators, they also provide a unique opportunity to evaluate population-level computational theories of perception and cognition that have previously been difficult to assess using either single-unit recording or conventional neuroimaging techniques. Copyright © 2011. Published by Elsevier Ltd.

A Decline in Response Variability Improves Neural Signal Detection during Auditory Task Performance.

PubMed

von Trapp, Gardiner; Buran, Bradley N; Sen, Kamal; Semple, Malcolm N; Sanes, Dan H

2016-10-26

The detection of a sensory stimulus arises from a significant change in neural activity, but a sensory neuron's response is rarely identical to successive presentations of the same stimulus. Large trial-to-trial variability would limit the central nervous system's ability to reliably detect a stimulus, presumably affecting perceptual performance. However, if response variability were to decrease while firing rate remained constant, then neural sensitivity could improve. Here, we asked whether engagement in an auditory detection task can modulate response variability, thereby increasing neural sensitivity. We recorded telemetrically from the core auditory cortex of gerbils, both while they engaged in an amplitude-modulation detection task and while they sat quietly listening to the identical stimuli. Using a signal detection theory framework, we found that neural sensitivity was improved during task performance, and this improvement was closely associated with a decrease in response variability. Moreover, units with the greatest change in response variability had absolute neural thresholds most closely aligned with simultaneously measured perceptual thresholds. Our findings suggest that the limitations imposed by response variability diminish during task performance, thereby improving the sensitivity of neural encoding and potentially leading to better perceptual sensitivity. The detection of a sensory stimulus arises from a significant change in neural activity. However, trial-to-trial variability of the neural response may limit perceptual performance. If the neural response to a stimulus is quite variable, then the response on a given trial could be confused with the pattern of neural activity generated when the stimulus is absent. Therefore, a neural mechanism that served to reduce response variability would allow for better stimulus detection. By recording from the cortex of freely moving animals engaged in an auditory detection task, we found that variability of the neural response becomes smaller during task performance, thereby improving neural detection thresholds. Copyright © 2016 the authors 0270-6474/16/3611097-10$15.00/0.

A Decline in Response Variability Improves Neural Signal Detection during Auditory Task Performance

PubMed Central

Buran, Bradley N.; Sen, Kamal; Semple, Malcolm N.; Sanes, Dan H.

2016-01-01

The detection of a sensory stimulus arises from a significant change in neural activity, but a sensory neuron's response is rarely identical to successive presentations of the same stimulus. Large trial-to-trial variability would limit the central nervous system's ability to reliably detect a stimulus, presumably affecting perceptual performance. However, if response variability were to decrease while firing rate remained constant, then neural sensitivity could improve. Here, we asked whether engagement in an auditory detection task can modulate response variability, thereby increasing neural sensitivity. We recorded telemetrically from the core auditory cortex of gerbils, both while they engaged in an amplitude-modulation detection task and while they sat quietly listening to the identical stimuli. Using a signal detection theory framework, we found that neural sensitivity was improved during task performance, and this improvement was closely associated with a decrease in response variability. Moreover, units with the greatest change in response variability had absolute neural thresholds most closely aligned with simultaneously measured perceptual thresholds. Our findings suggest that the limitations imposed by response variability diminish during task performance, thereby improving the sensitivity of neural encoding and potentially leading to better perceptual sensitivity. SIGNIFICANCE STATEMENT The detection of a sensory stimulus arises from a significant change in neural activity. However, trial-to-trial variability of the neural response may limit perceptual performance. If the neural response to a stimulus is quite variable, then the response on a given trial could be confused with the pattern of neural activity generated when the stimulus is absent. Therefore, a neural mechanism that served to reduce response variability would allow for better stimulus detection. By recording from the cortex of freely moving animals engaged in an auditory detection task, we found that variability of the neural response becomes smaller during task performance, thereby improving neural detection thresholds. PMID:27798189

Cortical encoding and neurophysiological tracking of intensity and pitch cues signaling English stress patterns in native and nonnative speakers.

PubMed

Chung, Wei-Lun; Bidelman, Gavin M

2016-01-01

We examined cross-language differences in neural encoding and tracking of intensity and pitch cues signaling English stress patterns. Auditory mismatch negativities (MMNs) were recorded in English and Mandarin listeners in response to contrastive English pseudowords whose primary stress occurred either on the first or second syllable (i.e., "nocTICity" vs. "NOCticity"). The contrastive syllable stress elicited two consecutive MMNs in both language groups, but English speakers demonstrated larger responses to stress patterns than Mandarin speakers. Correlations between the amplitude of ERPs and continuous changes in the running intensity and pitch of speech assessed how well each language group's brain activity tracked these salient acoustic features of lexical stress. We found that English speakers' neural responses tracked intensity changes in speech more closely than Mandarin speakers (higher brain-acoustic correlation). Findings demonstrate more robust and precise processing of English stress (intensity) patterns in early auditory cortical responses of native relative to nonnative speakers. Copyright © 2016 Elsevier Inc. All rights reserved.

Reconstructing the spectrotemporal modulations of real-life sounds from fMRI response patterns

PubMed Central

Santoro, Roberta; Moerel, Michelle; De Martino, Federico; Valente, Giancarlo; Ugurbil, Kamil; Yacoub, Essa; Formisano, Elia

2017-01-01

Ethological views of brain functioning suggest that sound representations and computations in the auditory neural system are optimized finely to process and discriminate behaviorally relevant acoustic features and sounds (e.g., spectrotemporal modulations in the songs of zebra finches). Here, we show that modeling of neural sound representations in terms of frequency-specific spectrotemporal modulations enables accurate and specific reconstruction of real-life sounds from high-resolution functional magnetic resonance imaging (fMRI) response patterns in the human auditory cortex. Region-based analyses indicated that response patterns in separate portions of the auditory cortex are informative of distinctive sets of spectrotemporal modulations. Most relevantly, results revealed that in early auditory regions, and progressively more in surrounding regions, temporal modulations in a range relevant for speech analysis (∼2–4 Hz) were reconstructed more faithfully than other temporal modulations. In early auditory regions, this effect was frequency-dependent and only present for lower frequencies (<∼2 kHz), whereas for higher frequencies, reconstruction accuracy was higher for faster temporal modulations. Further analyses suggested that auditory cortical processing optimized for the fine-grained discrimination of speech and vocal sounds underlies this enhanced reconstruction accuracy. In sum, the present study introduces an approach to embed models of neural sound representations in the analysis of fMRI response patterns. Furthermore, it reveals that, in the human brain, even general purpose and fundamental neural processing mechanisms are shaped by the physical features of real-world stimuli that are most relevant for behavior (i.e., speech, voice). PMID:28420788

Neural feedback for instantaneous spatiotemporal modulation of afferent pathways in bi-directional brain-machine interfaces.

PubMed

Liu, Jianbo; Khalil, Hassan K; Oweiss, Karim G

2011-10-01

In bi-directional brain-machine interfaces (BMIs), precisely controlling the delivery of microstimulation, both in space and in time, is critical to continuously modulate the neural activity patterns that carry information about the state of the brain-actuated device to sensory areas in the brain. In this paper, we investigate the use of neural feedback to control the spatiotemporal firing patterns of neural ensembles in a model of the thalamocortical pathway. Control of pyramidal (PY) cells in the primary somatosensory cortex (S1) is achieved based on microstimulation of thalamic relay cells through multiple-input multiple-output (MIMO) feedback controllers. This closed loop feedback control mechanism is achieved by simultaneously varying the stimulation parameters across multiple stimulation electrodes in the thalamic circuit based on continuous monitoring of the difference between reference patterns and the evoked responses of the cortical PY cells. We demonstrate that it is feasible to achieve a desired level of performance by controlling the firing activity pattern of a few "key" neural elements in the network. Our results suggest that neural feedback could be an effective method to facilitate the delivery of information to the cortex to substitute lost sensory inputs in cortically controlled BMIs.

Neural Mechanisms of Emotion.

ERIC Educational Resources Information Center

Derryberry, Douglas; Tucker, Don M.

1992-01-01

Views neural mechanisms of emotion from an evolutionary perspective, seeing them distributed across the brainstem, limbic, paralimbic, and neocortical regions. Discusses descending and ascending connections among these levels in relation to three types of emotional processes: peripheral effects on patterned bodily responses, central effects on…

The Cluster Variation Method: A Primer for Neuroscientists.

PubMed

Maren, Alianna J

2016-09-30

Effective Brain-Computer Interfaces (BCIs) require that the time-varying activation patterns of 2-D neural ensembles be modelled. The cluster variation method (CVM) offers a means for the characterization of 2-D local pattern distributions. This paper provides neuroscientists and BCI researchers with a CVM tutorial that will help them to understand how the CVM statistical thermodynamics formulation can model 2-D pattern distributions expressing structural and functional dynamics in the brain. The premise is that local-in-time free energy minimization works alongside neural connectivity adaptation, supporting the development and stabilization of consistent stimulus-specific responsive activation patterns. The equilibrium distribution of local patterns, or configuration variables , is defined in terms of a single interaction enthalpy parameter ( h ) for the case of an equiprobable distribution of bistate (neural/neural ensemble) units. Thus, either one enthalpy parameter (or two, for the case of non-equiprobable distribution) yields equilibrium configuration variable values. Modeling 2-D neural activation distribution patterns with the representational layer of a computational engine, we can thus correlate variational free energy minimization with specific configuration variable distributions. The CVM triplet configuration variables also map well to the notion of a M = 3 functional motif. This paper addresses the special case of an equiprobable unit distribution, for which an analytic solution can be found.

The Cluster Variation Method: A Primer for Neuroscientists

PubMed Central

Maren, Alianna J.

2016-01-01

Effective Brain–Computer Interfaces (BCIs) require that the time-varying activation patterns of 2-D neural ensembles be modelled. The cluster variation method (CVM) offers a means for the characterization of 2-D local pattern distributions. This paper provides neuroscientists and BCI researchers with a CVM tutorial that will help them to understand how the CVM statistical thermodynamics formulation can model 2-D pattern distributions expressing structural and functional dynamics in the brain. The premise is that local-in-time free energy minimization works alongside neural connectivity adaptation, supporting the development and stabilization of consistent stimulus-specific responsive activation patterns. The equilibrium distribution of local patterns, or configuration variables, is defined in terms of a single interaction enthalpy parameter (h) for the case of an equiprobable distribution of bistate (neural/neural ensemble) units. Thus, either one enthalpy parameter (or two, for the case of non-equiprobable distribution) yields equilibrium configuration variable values. Modeling 2-D neural activation distribution patterns with the representational layer of a computational engine, we can thus correlate variational free energy minimization with specific configuration variable distributions. The CVM triplet configuration variables also map well to the notion of a M = 3 functional motif. This paper addresses the special case of an equiprobable unit distribution, for which an analytic solution can be found. PMID:27706022

The neural signature of emotional memories in serial crimes.

PubMed

Chassy, Philippe

2017-10-01

Neural plasticity is the process whereby semantic information and emotional responses are stored in neural networks. It is hypothesized that the neural networks built over time to encode the sexual fantasies that motivate serial killers to act should display a unique, detectable activation pattern. The pathological neural watermark hypothesis posits that such networks comprise activation of brain sites that reflect four cognitive components: autobiographical memory, sexual arousal, aggression, and control over aggression. The neural sites performing these cognitive functions have been successfully identified by previous research. The key findings are reviewed to hypothesise the typical pattern of activity that serial killers should display. Through the integration of biological findings into one framework, the neural approach proposed in this paper is in stark contrast with the many theories accounting for serial killers that offer non-medical taxonomies. The pathological neural watermark hypothesis offers a new framework to understand and detect deviant individuals. The technical and legal issues are briefly discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Attenuated Auditory Event-Related Potentials and Associations with Atypical Sensory Response Patterns in Children with Autism

ERIC Educational Resources Information Center

Donkers, Franc C. L.; Schipul, Sarah E.; Baranek, Grace T.; Cleary, Katherine M.; Willoughby, Michael T.; Evans, Anna M.; Bulluck, John C.; Lovmo, Jeanne E.; Belger, Aysenil

2015-01-01

Neurobiological underpinnings of unusual sensory features in individuals with autism are unknown. Event-related potentials elicited by task-irrelevant sounds were used to elucidate neural correlates of auditory processing and associations with three common sensory response patterns (hyperresponsiveness; hyporesponsiveness; sensory seeking).…

UniEnt: uniform entropy model for the dynamics of a neuronal population

NASA Astrophysics Data System (ADS)

Hernandez Lahme, Damian; Nemenman, Ilya

Sensory information and motor responses are encoded in the brain in a collective spiking activity of a large number of neurons. Understanding the neural code requires inferring statistical properties of such collective dynamics from multicellular neurophysiological recordings. Questions of whether synchronous activity or silence of multiple neurons carries information about the stimuli or the motor responses are especially interesting. Unfortunately, detection of such high order statistical interactions from data is especially challenging due to the exponentially large dimensionality of the state space of neural collectives. Here we present UniEnt, a method for the inference of strengths of multivariate neural interaction patterns. The method is based on the Bayesian prior that makes no assumptions (uniform a priori expectations) about the value of the entropy of the observed multivariate neural activity, in contrast to popular approaches that maximize this entropy. We then study previously published multi-electrode recordings data from salamander retina, exposing the relevance of higher order neural interaction patterns for information encoding in this system. This work was supported in part by Grants JSMF/220020321 and NSF/IOS/1208126.

An experimental vestibular neural prosthesis: design and preliminary results with rhesus monkeys stimulated with modulated pulses.

PubMed

Nie, Kaibao; Ling, Leo; Bierer, Steven M; Kaneko, Chris R S; Fuchs, Albert F; Oxford, Trey; Rubinstein, Jay T; Phillips, James O

2013-06-01

A vestibular neural prosthesis was designed on the basis of a cochlear implant for treatment of Meniere's disease and other vestibular disorders. Computer control software was developed to generate patterned pulse stimuli for exploring optimal parameters to activate the vestibular nerve. Two rhesus monkeys were implanted with the prototype vestibular prosthesis and they were behaviorally evaluated post implantation surgery. Horizontal and vertical eye movement responses to patterned electrical pulse stimulations were collected on both monkeys. Pulse amplitude modulated (PAM) and pulse rate modulated (PRM) trains were applied to the lateral canal of each implanted animal. Robust slow-phase nystagmus responses following the PAM or PRM modulation pattern were observed in both implanted monkeys in the direction consistent with the activation of the implanted canal. Both PAM and PRM pulse trains can elicit a significant amount of in-phase modulated eye velocity changes and they could potentially be used for efficiently coding head rotational signals in future vestibular neural prostheses.

Predicting neural network firing pattern from phase resetting curve

NASA Astrophysics Data System (ADS)

Oprisan, Sorinel; Oprisan, Ana

2007-04-01

Autonomous neural networks called central pattern generators (CPG) are composed of endogenously bursting neurons and produce rhythmic activities, such as flying, swimming, walking, chewing, etc. Simplified CPGs for quadrupedal locomotion and swimming are modeled by a ring of neural oscillators such that the output of one oscillator constitutes the input for the subsequent neural oscillator. The phase response curve (PRC) theory discards the detailed conductance-based description of the component neurons of a network and reduces them to ``black boxes'' characterized by a transfer function, which tabulates the transient change in the intrinsic period of a neural oscillator subject to external stimuli. Based on open-loop PRC, we were able to successfully predict the phase-locked period and relative phase between neurons in a half-center network. We derived existence and stability criteria for heterogeneous ring neural networks that are in good agreement with experimental data.

Convergence of inhibitory neural inputs regulate motor activity in the murine and monkey stomach

PubMed Central

Shaylor, Lara A.; Hwang, Sung Jin; Sanders, Kenton M.

2016-01-01

Inhibitory motor neurons regulate several gastric motility patterns including receptive relaxation, gastric peristaltic motor patterns, and pyloric sphincter opening. Nitric oxide (NO) and purines have been identified as likely candidates that mediate inhibitory neural responses. However, the contribution from each neurotransmitter has received little attention in the distal stomach. The aims of this study were to identify the roles played by NO and purines in inhibitory motor responses in the antrums of mice and monkeys. By using wild-type mice and mutants with genetically deleted neural nitric oxide synthase (Nos1−/−) and P2Y1 receptors (P2ry1−/−) we examined the roles of NO and purines in postjunctional inhibitory responses in the distal stomach and compared these responses to those in primate stomach. Activation of inhibitory motor nerves using electrical field stimulation (EFS) produced frequency-dependent inhibitory junction potentials (IJPs) that produced muscle relaxations in both species. Stimulation of inhibitory nerves during slow waves terminated pacemaker events and associated contractions. In Nos1−/− mice IJPs and relaxations persisted whereas in P2ry1−/− mice IJPs were absent but relaxations persisted. In the gastric antrum of the non-human primate model Macaca fascicularis, similar NO and purine neural components contributed to inhibition of gastric motor activity. These data support a role of convergent inhibitory neural responses in the regulation of gastric motor activity across diverse species. PMID:27634009

Convergence of inhibitory neural inputs regulate motor activity in the murine and monkey stomach.

PubMed

Shaylor, Lara A; Hwang, Sung Jin; Sanders, Kenton M; Ward, Sean M

2016-11-01

Inhibitory motor neurons regulate several gastric motility patterns including receptive relaxation, gastric peristaltic motor patterns, and pyloric sphincter opening. Nitric oxide (NO) and purines have been identified as likely candidates that mediate inhibitory neural responses. However, the contribution from each neurotransmitter has received little attention in the distal stomach. The aims of this study were to identify the roles played by NO and purines in inhibitory motor responses in the antrums of mice and monkeys. By using wild-type mice and mutants with genetically deleted neural nitric oxide synthase (Nos1 -/- ) and P2Y1 receptors (P2ry1 -/- ) we examined the roles of NO and purines in postjunctional inhibitory responses in the distal stomach and compared these responses to those in primate stomach. Activation of inhibitory motor nerves using electrical field stimulation (EFS) produced frequency-dependent inhibitory junction potentials (IJPs) that produced muscle relaxations in both species. Stimulation of inhibitory nerves during slow waves terminated pacemaker events and associated contractions. In Nos1 -/- mice IJPs and relaxations persisted whereas in P2ry1 -/- mice IJPs were absent but relaxations persisted. In the gastric antrum of the non-human primate model Macaca fascicularis, similar NO and purine neural components contributed to inhibition of gastric motor activity. These data support a role of convergent inhibitory neural responses in the regulation of gastric motor activity across diverse species. Copyright © 2016 the American Physiological Society.

THE TASTE OF SUGARS

PubMed Central

McCaughey, Stuart A.

2008-01-01

Sugars evoke a distinctive perceptual quality (“sweetness” in humans) and are generally highly preferred. The neural basis for these phenomena is reviewed for rodents, in which detailed electrophysiological measurements have been made. A receptor has been identified that binds sweeteners and activates G-protein-mediated signaling in taste receptor cells, which leads to changes in neural firing rates in the brain, where perceptions of taste quality, intensity, and palatability are generated. Most cells in gustatory nuclei are broadly-tuned, so quality perception presumably arises from patterns of activity across neural populations. However, some manipulations affect only the most sugar-oriented cells, making it useful to consider them as a distinct neural subtype. Quality perception may also arise partly due to temporal patterns of activity to sugars, especially within sugar-oriented cells that give large but delayed responses. Non-specific gustatory neurons that are excited by both sugars and unpalatable stimuli project to ventral forebrain areas, where neural responses provide a closer match with behavioral preferences. This transition likely involves opposing excitatory and inhibitory influences by different subgroups of gustatory cells. Sweeteners are generally preferred over water, but the strength of this preference can vary across time or between individuals, and higher preferences for sugars are often associated with larger taste-evoked responses. PMID:18499254

Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks.

PubMed

Khan, Taimoor; De, Asok

2014-01-01

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results.

Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks

PubMed Central

De, Asok

2014-01-01

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results. PMID:27382616

The role of sensorimotor learning in the perception of letter-like forms: tracking the causes of neural specialization for letters.

PubMed

James, Karin H; Atwood, Thea P

2009-02-01

Functional specialization in the brain is considered a hallmark of efficient processing. It is therefore not surprising that there are brain areas specialized for processing letters. To better understand the causes of functional specialization for letters, we explore the emergence of this pattern of response in the ventral processing stream through a training paradigm. Previously, we hypothesized that the specialized response pattern seen during letter perception may be due in part to our experience in writing letters. The work presented here investigates whether or not this aspect of letter processing-the integration of sensorimotor systems through writing-leads to functional specialization in the visual system. To test this idea, we investigated whether or not different types of experiences with letter-like stimuli ("pseudoletters") led to functional specialization similar to that which exists for letters. Neural activation patterns were measured using functional magnetic resonance imaging (fMRI) before and after three different types of training sessions. Participants were trained to recognize pseudoletters by writing, typing, or purely visual practice. Results suggested that only after writing practice did neural activation patterns to pseudoletters resemble patterns seen for letters. That is, neural activation in the left fusiform and dorsal precentral gyrus was greater when participants viewed pseudoletters than other, similar stimuli but only after writing experience. Neural activation also increased after typing practice in the right fusiform and left precentral gyrus, suggesting that in some areas, any motor experience may change visual processing. The results of this experiment suggest an intimate interaction among perceptual and motor systems during pseudoletter perception that may be extended to everyday letter perception.

Notochord-derived Shh concentrates in close association with the apically positioned basal body in neural target cells and forms a dynamic gradient during neural patterning.

PubMed

Chamberlain, Chester E; Jeong, Juhee; Guo, Chaoshe; Allen, Benjamin L; McMahon, Andrew P

2008-03-01

Sonic hedgehog (Shh) ligand secreted by the notochord induces distinct ventral cell identities in the adjacent neural tube by a concentration-dependent mechanism. To study this process, we genetically engineered mice that produce bioactive, fluorescently labeled Shh from the endogenous locus. We show that Shh ligand concentrates in close association with the apically positioned basal body of neural target cells, forming a dynamic, punctate gradient in the ventral neural tube. Both ligand lipidation and target field response influence the gradient profile, but not the ability of Shh to concentrate around the basal body. Further, subcellular analysis suggests that Shh from the notochord might traffic into the neural target field by means of an apical-to-basal-oriented microtubule scaffold. This study, in which we directly observe, measure, localize and modify notochord-derived Shh ligand in the context of neural patterning, provides several new insights into mechanisms of Shh morphogen action.

Predictive Feedback Can Account for Biphasic Responses in the Lateral Geniculate Nucleus

PubMed Central

Jehee, Janneke F. M.; Ballard, Dana H.

2009-01-01

Biphasic neural response properties, where the optimal stimulus for driving a neural response changes from one stimulus pattern to the opposite stimulus pattern over short periods of time, have been described in several visual areas, including lateral geniculate nucleus (LGN), primary visual cortex (V1), and middle temporal area (MT). We describe a hierarchical model of predictive coding and simulations that capture these temporal variations in neuronal response properties. We focus on the LGN-V1 circuit and find that after training on natural images the model exhibits the brain's LGN-V1 connectivity structure, in which the structure of V1 receptive fields is linked to the spatial alignment and properties of center-surround cells in the LGN. In addition, the spatio-temporal response profile of LGN model neurons is biphasic in structure, resembling the biphasic response structure of neurons in cat LGN. Moreover, the model displays a specific pattern of influence of feedback, where LGN receptive fields that are aligned over a simple cell receptive field zone of the same polarity decrease their responses while neurons of opposite polarity increase their responses with feedback. This phase-reversed pattern of influence was recently observed in neurophysiology. These results corroborate the idea that predictive feedback is a general coding strategy in the brain. PMID:19412529

In-vivo determination of chewing patterns using FBG and artificial neural networks

NASA Astrophysics Data System (ADS)

Pegorini, Vinicius; Zen Karam, Leandro; Rocha Pitta, Christiano S.; Ribeiro, Richardson; Simioni Assmann, Tangriani; Cardozo da Silva, Jean Carlos; Bertotti, Fábio L.; Kalinowski, Hypolito J.; Cardoso, Rafael

2015-09-01

This paper reports the process of pattern classification of the chewing process of ruminants. We propose a simplified signal processing scheme for optical fiber Bragg grating (FBG) sensors based on machine learning techniques. The FBG sensors measure the biomechanical forces during jaw movements and an artificial neural network is responsible for the classification of the associated chewing pattern. In this study, three patterns associated to dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior studies were monitored, rumination and idle period. Experimental results show that the proposed approach for pattern classification has been capable of differentiating the materials involved in the chewing process with a small classification error.

Neural activity in the hippocampus during conflict resolution.

PubMed

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.

Comparing success levels of different neural network structures in extracting discriminative information from the response patterns of a temperature-modulated resistive gas sensor

NASA Astrophysics Data System (ADS)

Hosseini-Golgoo, S. M.; Bozorgi, H.; Saberkari, A.

2015-06-01

Performances of three neural networks, consisting of a multi-layer perceptron, a radial basis function, and a neuro-fuzzy network with local linear model tree training algorithm, in modeling and extracting discriminative features from the response patterns of a temperature-modulated resistive gas sensor are quantitatively compared. For response pattern recording, a voltage staircase containing five steps each with a 20 s plateau is applied to the micro-heater of the sensor, when 12 different target gases, each at 11 concentration levels, are present. In each test, the hidden layer neuron weights are taken as the discriminatory feature vector of the target gas. These vectors are then mapped to a 3D feature space using linear discriminant analysis. The discriminative information content of the feature vectors are determined by the calculation of the Fisher’s discriminant ratio, affording quantitative comparison among the success rates achieved by the different neural network structures. The results demonstrate a superior discrimination ratio for features extracted from local linear neuro-fuzzy and radial-basis-function networks with recognition rates of 96.27% and 90.74%, respectively.

Differences in neural responses to ipsilateral stimuli in wide-view fields between face- and house-selective areas

PubMed Central

Li, Ting; Niu, Yan; Xiang, Jie; Cheng, Junjie; Liu, Bo; Zhang, Hui; Yan, Tianyi; Kanazawa, Susumu; Wu, Jinglong

2018-01-01

Category-selective brain areas exhibit varying levels of neural activity to ipsilaterally presented stimuli. However, in face- and house-selective areas, the neural responses evoked by ipsilateral stimuli in the peripheral visual field remain unclear. In this study, we displayed face and house images using a wide-view visual presentation system while performing functional magnetic resonance imaging (fMRI). The face-selective areas (fusiform face area (FFA) and occipital face area (OFA)) exhibited intense neural responses to ipsilaterally presented images, whereas the house-selective areas (parahippocampal place area (PPA) and transverse occipital sulcus (TOS)) exhibited substantially smaller and even negative neural responses to the ipsilaterally presented images. We also found that the category preferences of the contralateral and ipsilateral neural responses were similar. Interestingly, the face- and house-selective areas exhibited neural responses to ipsilateral images that were smaller than the responses to the contralateral images. Multi-voxel pattern analysis (MVPA) was implemented to evaluate the difference between the contralateral and ipsilateral responses. The classification accuracies were much greater than those expected by chance. The classification accuracies in the FFA were smaller than those in the PPA and TOS. The closer eccentricities elicited greater classification accuracies in the PPA and TOS. We propose that these ipsilateral neural responses might be interpreted by interhemispheric communication through intrahemispheric connectivity of white matter connection and interhemispheric connectivity via the corpus callosum and occipital white matter connection. Furthermore, the PPA and TOS likely have weaker interhemispheric communication than the FFA and OFA, particularly in the peripheral visual field. PMID:29451872

Regulation of Facial Morphogenesis by Endothelin Signaling: Insights from Mice and Fish

PubMed Central

Clouthier, David E.; Garcia, Elvin; Schilling, Thomas F.

2010-01-01

Craniofacial morphogenesis is accomplished through a complex set of developmental events, most of which are initiated in neural crest cells within the pharyngeal arches. Local patterning cues from the surrounding environment induce gene expression within neural crest cells, leading to formation of a diverse set of skeletal elements. Endothelin-1 (Edn1) is one of the primary signals that establish the identities of neural crest cells within the mandibular portion of the first pharyngeal arch. Signaling through its cognate receptor, the endothelin-A receptor, is critical for patterning the ventral/distal portion of the arch (lower jaw) and also participates with Hox genes in patterning more posterior arches. Edn1/Ednra signaling is highly conserved between mouse and zebrafish, and genetic analyses in these two species have provided complementary insights into the patterning cues responsible for establishing the craniofacial complex as well as the genetic basis of facial birth defect syndromes. PMID:20684004

Increasing Spontaneous Retinal Activity before Eye Opening Accelerates the Development of Geniculate Receptive Fields

PubMed Central

Davis, Zachary W.; Chapman, Barbara

2015-01-01

Visually evoked activity is necessary for the normal development of the visual system. However, little is known about the capacity for patterned spontaneous activity to drive the maturation of receptive fields before visual experience. Retinal waves provide instructive retinotopic information for the anatomical organization of the visual thalamus. To determine whether retinal waves also drive the maturation of functional responses, we increased the frequency of retinal waves pharmacologically in the ferret (Mustela putorius furo) during a period of retinogeniculate development before eye opening. The development of geniculate receptive fields after receiving these increased neural activities was measured using single-unit electrophysiology. We found that increased retinal waves accelerate the developmental reduction of geniculate receptive field sizes. This reduction is due to a decrease in receptive field center size rather than an increase in inhibitory surround strength. This work reveals an instructive role for patterned spontaneous activity in guiding the functional development of neural circuits. SIGNIFICANCE STATEMENT Patterned spontaneous neural activity that occurs during development is known to be necessary for the proper formation of neural circuits. However, it is unknown whether the spontaneous activity alone is sufficient to drive the maturation of the functional properties of neurons. Our work demonstrates for the first time an acceleration in the maturation of neural function as a consequence of driving patterned spontaneous activity during development. This work has implications for our understanding of how neural circuits can be modified actively to improve function prematurely or to recover from injury with guided interventions of patterned neural activity. PMID:26511250

Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling

PubMed Central

Dick, Thomas E.; Molkov, Yaroslav I.; Nieman, Gary; Hsieh, Yee-Hsee; Jacono, Frank J.; Doyle, John; Scheff, Jeremy D.; Calvano, Steve E.; Androulakis, Ioannis P.; An, Gary; Vodovotz, Yoram

2012-01-01

Acute inflammation leads to organ failure by engaging catastrophic feedback loops in which stressed tissue evokes an inflammatory response and, in turn, inflammation damages tissue. Manifestations of this maladaptive inflammatory response include cardio-respiratory dysfunction that may be reflected in reduced heart rate and ventilatory pattern variabilities. We have developed signal-processing algorithms that quantify non-linear deterministic characteristics of variability in biologic signals. Now, coalescing under the aegis of the NIH Computational Biology Program and the Society for Complexity in Acute Illness, two research teams performed iterative experiments and computational modeling on inflammation and cardio-pulmonary dysfunction in sepsis as well as on neural control of respiration and ventilatory pattern variability. These teams, with additional collaborators, have recently formed a multi-institutional, interdisciplinary consortium, whose goal is to delineate the fundamental interrelationship between the inflammatory response and physiologic variability. Multi-scale mathematical modeling and complementary physiological experiments will provide insight into autonomic neural mechanisms that may modulate the inflammatory response to sepsis and simultaneously reduce heart rate and ventilatory pattern variabilities associated with sepsis. This approach integrates computational models of neural control of breathing and cardio-respiratory coupling with models that combine inflammation, cardiovascular function, and heart rate variability. The resulting integrated model will provide mechanistic explanations for the phenomena of respiratory sinus-arrhythmia and cardio-ventilatory coupling observed under normal conditions, and the loss of these properties during sepsis. This approach holds the potential of modeling cross-scale physiological interactions to improve both basic knowledge and clinical management of acute inflammatory diseases such as sepsis and trauma. PMID:22783197

Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling.

PubMed

Dick, Thomas E; Molkov, Yaroslav I; Nieman, Gary; Hsieh, Yee-Hsee; Jacono, Frank J; Doyle, John; Scheff, Jeremy D; Calvano, Steve E; Androulakis, Ioannis P; An, Gary; Vodovotz, Yoram

2012-01-01

Acute inflammation leads to organ failure by engaging catastrophic feedback loops in which stressed tissue evokes an inflammatory response and, in turn, inflammation damages tissue. Manifestations of this maladaptive inflammatory response include cardio-respiratory dysfunction that may be reflected in reduced heart rate and ventilatory pattern variabilities. We have developed signal-processing algorithms that quantify non-linear deterministic characteristics of variability in biologic signals. Now, coalescing under the aegis of the NIH Computational Biology Program and the Society for Complexity in Acute Illness, two research teams performed iterative experiments and computational modeling on inflammation and cardio-pulmonary dysfunction in sepsis as well as on neural control of respiration and ventilatory pattern variability. These teams, with additional collaborators, have recently formed a multi-institutional, interdisciplinary consortium, whose goal is to delineate the fundamental interrelationship between the inflammatory response and physiologic variability. Multi-scale mathematical modeling and complementary physiological experiments will provide insight into autonomic neural mechanisms that may modulate the inflammatory response to sepsis and simultaneously reduce heart rate and ventilatory pattern variabilities associated with sepsis. This approach integrates computational models of neural control of breathing and cardio-respiratory coupling with models that combine inflammation, cardiovascular function, and heart rate variability. The resulting integrated model will provide mechanistic explanations for the phenomena of respiratory sinus-arrhythmia and cardio-ventilatory coupling observed under normal conditions, and the loss of these properties during sepsis. This approach holds the potential of modeling cross-scale physiological interactions to improve both basic knowledge and clinical management of acute inflammatory diseases such as sepsis and trauma.

Optical Calibration Process Developed for Neural-Network-Based Optical Nondestructive Evaluation Method

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

2004-01-01

A completely optical calibration process has been developed at Glenn for calibrating a neural-network-based nondestructive evaluation (NDE) method. The NDE method itself detects very small changes in the characteristic patterns or vibration mode shapes of vibrating structures as discussed in many references. The mode shapes or characteristic patterns are recorded using television or electronic holography and change when a structure experiences, for example, cracking, debonds, or variations in fastener properties. An artificial neural network can be trained to be very sensitive to changes in the mode shapes, but quantifying or calibrating that sensitivity in a consistent, meaningful, and deliverable manner has been challenging. The standard calibration approach has been difficult to implement, where the response to damage of the trained neural network is compared with the responses of vibration-measurement sensors. In particular, the vibration-measurement sensors are intrusive, insufficiently sensitive, and not numerous enough. In response to these difficulties, a completely optical alternative to the standard calibration approach was proposed and tested successfully. Specifically, the vibration mode to be monitored for structural damage was intentionally contaminated with known amounts of another mode, and the response of the trained neural network was measured as a function of the peak-to-peak amplitude of the contaminating mode. The neural network calibration technique essentially uses the vibration mode shapes of the undamaged structure as standards against which the changed mode shapes are compared. The published response of the network can be made nearly independent of the contaminating mode, if enough vibration modes are used to train the net. The sensitivity of the neural network can be adjusted for the environment in which the test is to be conducted. The response of a neural network trained with measured vibration patterns for use on a vibration isolation table in the presence of various sources of laboratory noise is shown. The output of the neural network is called the degradable classification index. The curve was generated by a simultaneous comparison of means, and it shows a peak-to-peak sensitivity of about 100 nm. The following graph uses model generated data from a compressor blade to show that much higher sensitivities are possible when the environment can be controlled better. The peak-to-peak sensitivity here is about 20 nm. The training procedure was modified for the second graph, and the data were subjected to an intensity-dependent transformation called folding. All the measurements for this approach to calibration were optical. The peak-to-peak amplitudes of the vibration modes were measured using heterodyne interferometry, and the modes themselves were recorded using television (electronic) holography.

Distinguishing Adolescents With ADHD From Their Unaffected Siblings and Healthy Comparison Subjects by Neural Activation Patterns During Response Inhibition.

PubMed

van Rooij, Daan; Hoekstra, Pieter J; Mennes, Maarten; von Rhein, Daniel; Thissen, Andrieke J A M; Heslenfeld, Dirk; Zwiers, Marcel P; Faraone, Stephen V; Oosterlaan, Jaap; Franke, Barbara; Rommelse, Nanda; Buitelaar, Jan K; Hartman, Catharina A

2015-07-01

Dysfunctional response inhibition is a key executive function impairment in attention deficit hyperactivity disorder (ADHD). Still, behavioral response inhibition measures do not consistently differentiate affected from unaffected individuals. The authors therefore investigated neural correlates of response inhibition and the familial nature of these neural correlates. Functional MRI measurements of neural activation during the stop-signal task and behavioral measures of response inhibition were obtained in adolescents and young adults with ADHD (N=185), their unaffected siblings (N=111), and healthy comparison subjects (N=124). Stop-signal task reaction times were longer and error rates were higher in participants with ADHD, but not in their unaffected siblings, while reaction time variability was higher in both groups than in comparison subjects. Relative to comparison subjects, participants with ADHD and unaffected siblings had neural hypoactivation in frontal-striatal and frontal-parietal networks, whereby activation in inferior frontal and temporal/parietal nodes in unaffected siblings was intermediate between levels of participants with ADHD and comparison subjects. Furthermore, neural activation in inferior frontal nodes correlated with stop-signal reaction times, and activation in both inferior frontal and temporal/parietal nodes correlated with ADHD severity. Neural activation alterations in ADHD are more robust than behavioral response inhibition deficits and explain variance in response inhibition and ADHD severity. Although only affected participants with ADHD have deficient response inhibition, hypoactivation in inferior frontal and temporal-parietal nodes in unaffected siblings supports the familial nature of the underlying neural process. Activation deficits in these nodes may be useful as endophenotypes that extend beyond the affected individuals in the family.

A deep convolutional neural network to analyze position averaged convergent beam electron diffraction patterns.

PubMed

Xu, W; LeBeau, J M

2018-05-01

We establish a series of deep convolutional neural networks to automatically analyze position averaged convergent beam electron diffraction patterns. The networks first calibrate the zero-order disk size, center position, and rotation without the need for pretreating the data. With the aligned data, additional networks then measure the sample thickness and tilt. The performance of the network is explored as a function of a variety of variables including thickness, tilt, and dose. A methodology to explore the response of the neural network to various pattern features is also presented. Processing patterns at a rate of  ∼ 0.1 s/pattern, the network is shown to be orders of magnitude faster than a brute force method while maintaining accuracy. The approach is thus suitable for automatically processing big, 4D STEM data. We also discuss the generality of the method to other materials/orientations as well as a hybrid approach that combines the features of the neural network with least squares fitting for even more robust analysis. The source code is available at https://github.com/subangstrom/DeepDiffraction. Copyright © 2018 Elsevier B.V. All rights reserved.

Neural priming in human frontal cortex: multiple forms of learning reduce demands on the prefrontal executive system.

PubMed

Race, Elizabeth A; Shanker, Shanti; Wagner, Anthony D

2009-09-01

Past experience is hypothesized to reduce computational demands in PFC by providing bottom-up predictive information that informs subsequent stimulus-action mapping. The present fMRI study measured cortical activity reductions ("neural priming"/"repetition suppression") during repeated stimulus classification to investigate the mechanisms through which learning from the past decreases demands on the prefrontal executive system. Manipulation of learning at three levels of representation-stimulus, decision, and response-revealed dissociable neural priming effects in distinct frontotemporal regions, supporting a multiprocess model of neural priming. Critically, three distinct patterns of neural priming were identified in lateral frontal cortex, indicating that frontal computational demands are reduced by three forms of learning: (a) cortical tuning of stimulus-specific representations, (b) retrieval of learned stimulus-decision mappings, and (c) retrieval of learned stimulus-response mappings. The topographic distribution of these neural priming effects suggests a rostrocaudal organization of executive function in lateral frontal cortex.

Axial mesendoderm refines rostrocaudal pattern in the chick nervous system.

PubMed

Rowan, A M; Stern, C D; Storey, K G

1999-07-01

There has long been controversy concerning the role of the axial mesoderm in the induction and rostrocaudal patterning of the vertebrate nervous system. Here we investigate the neural inducing and regionalising properties of defined rostrocaudal regions of head process/prospective notochord in the chick embryo by juxtaposing these tissues with extraembryonic epiblast or neural plate explants. We localise neural inducing signals to the emerging head process and using a large panel of region-specific neural markers, show that different rostrocaudal levels of the head process derived from headfold stage embryos can induce discrete regions of the central nervous system. However, we also find that rostral and caudal head process do not induce expression of any of these molecular markers in explants of the neural plate. During normal development the head process emerges beneath previously induced neural plate, which we show has already acquired some rostrocaudal character. Our findings therefore indicate that discrete regions of axial mesendoderm at headfold stages are not normally responsible for the establishment of rostrocaudal pattern in the neural plate. Strikingly however, we do find that caudal head process inhibits expression of rostral genes in neural plate explants. These findings indicate that despite the ability to induce specific rostrocaudal regions of the CNS de novo, signals provided by the discrete regions of axial mesendoderm do not appear to establish regional differences, but rather refine the rostrocaudal character of overlying neuroepithelium.

Evolution of behavior and neural control of the fast-start escape response.

PubMed

Hale, Melina E; Long, John H; McHenry, Matthew J; Westneat, Mark W

2002-05-01

The fast-start startle behavior is the primary mechanism of rapid escape in fishes and is a model system for examining neural circuit design and musculoskeletal function. To develop a dataset for evolutionary analysis of the startle response, the kinematics and muscle activity patterns of the fast-start were analyzed for four fish species at key branches in the phylogeny of vertebrates. Three of these species (Polypterus palmas, Lepisosteus osseus, and Amia calva) represent the base of the actinopterygian radiation. A fourth species (Oncorhynchus mykiss) provided data for a species in the central region of the teleost phylogeny. Using these data, we explored the evolution of this behavior within the phylogeny of vertebrates. To test the hypothesis that startle features are evolutionarily conservative, the variability of motor patterns and kinematics in fast-starts was described. Results show that the evolution of the startle behavior in fishes, and more broadly among vertebrates, is not conservative. The fast-start has undergone substantial change in suites of kinematics and electromyogram features, including the presence of either a one- or a two-stage kinematic response and change in the extent of bilateral muscle activity. Comparative methods were used to test the evolutionary hypothesis that changes in motor control are correlated with key differences in the kinematics and behavior of the fast-start. Significant evolutionary correlations were found between several motor pattern and behavioral characters. These results suggest that the startle neural circuit itself is not conservative. By tracing the evolution of motor pattern and kinematics on a phylogeny, it is shown that major changes in the neural circuit of the startle behavior occur at several levels in the phylogeny of vertebrates.

Dissociable Patterns of Neural Activity during Response Inhibition in Depressed Adolescents with and without Suicidal Behavior

ERIC Educational Resources Information Center

Pan, Lisa A.; Batezati-Alves, Silvia C.; Almeida, Jorge R. C.; Segreti, AnnaMaria; Akkal, Dalila; Hassel, Stefanie; Lakdawala, Sara; Brent, David A.; Phillips, Mary L.

2011-01-01

Objectives: Impaired attentional control and behavioral control are implicated in adult suicidal behavior. Little is known about the functional integrity of neural circuitry supporting these processes in suicidal behavior in adolescence. Method: Functional magnetic resonance imaging was used in 15 adolescent suicide attempters with a history of…

Challenges to the Use of Artificial Neural Networks for Diagnostic Classifications with Student Test Data

ERIC Educational Resources Information Center

Briggs, Derek C.; Circi, Ruhan

2017-01-01

Artificial Neural Networks (ANNs) have been proposed as a promising approach for the classification of students into different levels of a psychological attribute hierarchy. Unfortunately, because such classifications typically rely upon internally produced item response patterns that have not been externally validated, the instability of ANN…

Comparison of Computational-Model and Experimental-Example Trained Neural Networks for Processing Speckled Fringe Patterns

NASA Technical Reports Server (NTRS)

Decker, A. J.; Fite, E. B.; Thorp, S. A.; Mehmed, O.

1998-01-01

The responses of artificial neural networks to experimental and model-generated inputs are compared for detection of damage in twisted fan blades using electronic holography. The training-set inputs, for this work, are experimentally generated characteristic patterns of the vibrating blades. The outputs are damage-flag indicators or second derivatives of the sensitivity-vector-projected displacement vectors from a finite element model. Artificial neural networks have been trained in the past with computational-model-generated training sets. This approach avoids the difficult inverse calculations traditionally used to compare interference fringes with the models. But the high modeling standards are hard to achieve, even with fan-blade finite-element models.

Comparison of Computational, Model and Experimental, Example Trained Neural Networks for Processing Speckled Fringe Patterns

NASA Technical Reports Server (NTRS)

Decker, A. J.; Fite, E. B.; Thorp, S. A.; Mehmed, O.

1998-01-01

The responses of artificial neural networks to experimental and model-generated inputs are compared for detection of damage in twisted fan blades using electronic holography. The training-set inputs, for this work, are experimentally generated characteristic patterns of the vibrating blades. The outputs are damage-flag indicators or second derivatives of the sensitivity-vector-projected displacement vectors from a finite element model. Artificial neural networks have been trained in the past with computational-model- generated training sets. This approach avoids the difficult inverse calculations traditionally used to compare interference fringes with the models. But the high modeling standards are hard to achieve, even with fan-blade finite-element models.

Surface modification of polydimethylsiloxane (PDMS) induced proliferation and neural-like cells differentiation of umbilical cord blood-derived mesenchymal stem cells.

PubMed

Kim, Sun-Jung; Lee, Jae Kyoo; Kim, Jin Won; Jung, Ji-Won; Seo, Kwangwon; Park, Sang-Bum; Roh, Kyung-Hwan; Lee, Sae-Rom; Hong, Yun Hwa; Kim, Sang Jeong; Lee, Yong-Soon; Kim, Sung June; Kang, Kyung-Sun

2008-08-01

Stem cell-based therapy has recently emerged for use in novel therapeutics for incurable diseases. For successful recovery from neurologic diseases, the most pivotal factor is differentiation and directed neuronal cell growth. In this study, we fabricated three different widths of a micro-pattern on polydimethylsiloxane (PDMS; 1, 2, and 4 microm). Surface modification of the PDMS was investigated for its capacity to manage proliferation and differentiation of neural-like cells from umbilical cord blood-derived mesenchymal stem cells (UCB-MSCs). Among the micro-patterned PDMS fabrications, the 1 microm-patterned PDMS significantly increased cell proliferation and most of the cells differentiated into neuronal cells. In addition, the 1 microm-patterned PDMS induced an increase in cytosolic calcium, while the differentiated cells on the flat and 4 microm-patterned PDMS had no response. PDMS with a 1 microm pattern was also aligned to direct orientation within 10 degrees angles. Taken together, micro-patterned PDMS supported UCB-MSC proliferation and induced neural like-cell differentiation. Our data suggest that micro-patterned PDMS might be a guiding method for stem cell therapy that would improve its therapeutic action in neurological diseases.

Body mass is positively associated with neural response to sweet taste, but not alcohol, among drinkers.

PubMed

Gardiner, Casey K; YorkWilliams, Sophie L; Bryan, Angela D; Hutchison, Kent E

2017-07-28

Obesity is a large and growing public health concern, presenting enormous economic and health costs to individuals and society. A burgeoning literature demonstrates that overweight and obese individuals display different neural processing of rewarding stimuli, including caloric substances, as compared to healthy weight individuals. However, much extant research on the neurobiology of obesity has focused on addiction models, without highlighting potentially separable neural underpinnings of caloric intake versus substance use. The present research explores these differences by examining neural response to alcoholic beverages and a sweet non-alcoholic beverage, among a sample of individuals with varying weight status and patterns of alcohol use and misuse. Participants received tastes of a sweet beverage (litchi juice) and alcoholic beverages during fMRI scanning. When controlling for alcohol use, elevated weight status was associated with increased activation in response to sweet taste in regions including the cingulate cortex, hippocampus, precuneus, and fusiform gyrus. However, weight status was not associated with neural response to alcoholic beverages. Copyright © 2017 Elsevier B.V. All rights reserved.

Selective attention to temporal features on nested time scales.

PubMed

Henry, Molly J; Herrmann, Björn; Obleser, Jonas

2015-02-01

Meaningful auditory stimuli such as speech and music often vary simultaneously along multiple time scales. Thus, listeners must selectively attend to, and selectively ignore, separate but intertwined temporal features. The current study aimed to identify and characterize the neural network specifically involved in this feature-selective attention to time. We used a novel paradigm where listeners judged either the duration or modulation rate of auditory stimuli, and in which the stimulation, working memory demands, response requirements, and task difficulty were held constant. A first analysis identified all brain regions where individual brain activation patterns were correlated with individual behavioral performance patterns, which thus supported temporal judgments generically. A second analysis then isolated those brain regions that specifically regulated selective attention to temporal features: Neural responses in a bilateral fronto-parietal network including insular cortex and basal ganglia decreased with degree of change of the attended temporal feature. Critically, response patterns in these regions were inverted when the task required selectively ignoring this feature. The results demonstrate how the neural analysis of complex acoustic stimuli with multiple temporal features depends on a fronto-parietal network that simultaneously regulates the selective gain for attended and ignored temporal features. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

VEP Responses to Op-Art Stimuli

PubMed Central

O’Hare, Louise; Clarke, Alasdair D. F.; Pollux, Petra M. J.

2015-01-01

Several types of striped patterns have been reported to cause adverse sensations described as visual discomfort. Previous research using op-art-based stimuli has demonstrated that spurious eye movement signals can cause the experience of illusory motion, or shimmering effects, which might be perceived as uncomfortable. Whilst the shimmering effects are one cause of discomfort, another possible contributor to discomfort is excessive neural responses: As striped patterns do not have the statistical redundancy typical of natural images, they are perhaps unable to be encoded efficiently. If this is the case, then this should be seen in the amplitude of the EEG response. This study found that stimuli that were judged to be most comfortable were also those with the lowest EEG amplitude. This provides some support for the idea that excessive neural responses might also contribute to discomfort judgements in normal populations, in stimuli controlled for perceived contrast. PMID:26422207

VEP Responses to Op-Art Stimuli.

PubMed

O'Hare, Louise; Clarke, Alasdair D F; Pollux, Petra M J

2015-01-01

Several types of striped patterns have been reported to cause adverse sensations described as visual discomfort. Previous research using op-art-based stimuli has demonstrated that spurious eye movement signals can cause the experience of illusory motion, or shimmering effects, which might be perceived as uncomfortable. Whilst the shimmering effects are one cause of discomfort, another possible contributor to discomfort is excessive neural responses: As striped patterns do not have the statistical redundancy typical of natural images, they are perhaps unable to be encoded efficiently. If this is the case, then this should be seen in the amplitude of the EEG response. This study found that stimuli that were judged to be most comfortable were also those with the lowest EEG amplitude. This provides some support for the idea that excessive neural responses might also contribute to discomfort judgements in normal populations, in stimuli controlled for perceived contrast.

Attenuated Auditory Event-Related Potentials and Associations with Atypical Sensory Response Patterns in Children with Autism

PubMed Central

Donkers, Franc C.L.; Schipul, Sarah E.; Baranek, Grace T.; Cleary, Katherine M.; Willoughby, Michael T.; Evans, Anna M.; Bulluck, John C.; Lovmo, Jeanne E.; Belger, Aysenil

2015-01-01

Neurobiological underpinnings of unusual sensory features in individuals with autism are unknown. Event-related potentials (ERPs) elicited by task-irrelevant sounds were used to elucidate neural correlates of auditory processing and associations with three common sensory response patterns (hyperresponsiveness; hyporesponsiveness; sensory seeking). Twenty-eight children with autism and 39 typically developing children (4–12 year-olds) completed an auditory oddball paradigm. Results revealed marginally attenuated P1 and N2 to standard tones and attenuated P3a to novel sounds in autism versus controls. Exploratory analyses suggested that within the autism group, attenuated N2 and P3a amplitudes were associated with greater sensory seeking behaviors for specific ranges of P1 responses. Findings suggest that attenuated early sensory as well as later attention-orienting neural responses to stimuli may underlie selective sensory features via complex mechanisms. PMID:24072639

Neural activation patterns during response inhibition distinguish adolescents with ADHD, their unaffected siblings, and healthy controls

PubMed Central

van Rooij, Daan; Hoekstra, Pieter J.; Mennes, Maarten; von Rhein, Daniel; Thissen, Andrieke J.A.M.; Heslenfeld, Dirk; Zwiers, Marcel P.; Faraone, Stephen V.; Oosterlaan, Jaap; Franke, Barbara; Rommelse, Nanda; Buitelaar, Jan K.; Hartman, Catharina A.

2015-01-01

Objective Impaired response inhibition is a key executive function deficit of attention-deficit/hyperactivity disorder (ADHD). Still, behavioral response inhibition measures do not consistently differentiate individuals with ADHD from unaffected individuals. We therefore investigated the neural correlates of response inhibition as well as the familial nature of these neural correlates. Methods fMRI measurements of neural activation during the stop-signal task along with behavioral measures of response inhibition were obtained in adolescents and young adults with ADHD (N=185), their unaffected siblings (N=111), and healthy controls (N=124). Results Stop-signal reaction times were longer in participants with ADHD, but not in their unaffected siblings, while reaction time variability and error rates were higher in both groups than in controls. Neural hypoactivation was observed in frontal-striatal and frontal-parietal networks of participants with ADHD and unaffected siblings compared to controls, whereby activation in inferior frontal and temporal/parietal nodes in unaffected siblings was intermediate between that of participants with ADHD and controls. Furthermore, neural activation in inferior frontal nodes correlated with stop-signal reaction times, and activation in both inferior frontal and temporal/parietal nodes correlated with ADHD severity. Conclusions Neural activation alterations in ADHD are more robust than behavioral response inhibition deficits and explain variance in response inhibition and ADHD severity. Although only affected participants with ADHD have deficient response inhibition, hypoactivation in inferior frontal and temporal-parietal nodes in unaffected siblings support the familial nature of the underlying neural process. Hypoactivation in these nodes may be useful as endophenotypes that extend beyond the affected individuals in the family. PMID:25615565

Cross-Level Effects Between Neurophysiology and Communication During Team Training.

PubMed

Gorman, Jamie C; Martin, Melanie J; Dunbar, Terri A; Stevens, Ronald H; Galloway, Trysha L; Amazeen, Polemnia G; Likens, Aaron D

2016-02-01

We investigated cross-level effects, which are concurrent changes across neural and cognitive-behavioral levels of analysis as teams interact, between neurophysiology and team communication variables under variations in team training. When people work together as a team, they develop neural, cognitive, and behavioral patterns that they would not develop individually. It is currently unknown whether these patterns are associated with each other in the form of cross-level effects. Team-level neurophysiology and latent semantic analysis communication data were collected from submarine teams in a training simulation. We analyzed whether (a) both neural and communication variables change together in response to changes in training segments (briefing, scenario, or debriefing), (b) neural and communication variables mutually discriminate teams of different experience levels, and (c) peak cross-correlations between neural and communication variables identify how the levels are linked. Changes in training segment led to changes in both neural and communication variables, neural and communication variables mutually discriminated between teams of different experience levels, and peak cross-correlations indicated that changes in communication precede changes in neural patterns in more experienced teams. Cross-level effects suggest that teamwork is not reducible to a fundamental level of analysis and that training effects are spread out across neural and cognitive-behavioral levels of analysis. Cross-level effects are important to consider for theories of team performance and practical aspects of team training. Cross-level effects suggest that measurements could be taken at one level (e.g., neural) to assess team experience (or skill) on another level (e.g., cognitive-behavioral). © 2015, Human Factors and Ergonomics Society.

Eliciting naturalistic cortical responses with a sensory prosthesis via optimized microstimulation

NASA Astrophysics Data System (ADS)

Choi, John S.; Brockmeier, Austin J.; McNiel, David B.; von Kraus, Lee M.; Príncipe, José C.; Francis, Joseph T.

2016-10-01

Objective. Lost sensations, such as touch, could one day be restored by electrical stimulation along the sensory neural pathways. Such stimulation, when informed by electronic sensors, could provide naturalistic cutaneous and proprioceptive feedback to the user. Perceptually, microstimulation of somatosensory brain regions produces localized, modality-specific sensations, and several spatiotemporal parameters have been studied for their discernibility. However, systematic methods for encoding a wide array of naturally occurring stimuli into biomimetic percepts via multi-channel microstimulation are lacking. More specifically, generating spatiotemporal patterns for explicitly evoking naturalistic neural activation has not yet been explored. Approach. We address this problem by first modeling the dynamical input-output relationship between multichannel microstimulation and downstream neural responses, and then optimizing the input pattern to reproduce naturally occurring touch responses as closely as possible. Main results. Here we show that such optimization produces responses in the S1 cortex of the anesthetized rat that are highly similar to natural, tactile-stimulus-evoked counterparts. Furthermore, information on both pressure and location of the touch stimulus was found to be highly preserved. Significance. Our results suggest that the currently presented stimulus optimization approach holds great promise for restoring naturalistic levels of sensation.

Neural coordination can be enhanced by occasional interruption of normal firing patterns: a self-optimizing spiking neural network model.

PubMed

Woodward, Alexander; Froese, Tom; Ikegami, Takashi

2015-02-01

The state space of a conventional Hopfield network typically exhibits many different attractors of which only a small subset satisfies constraints between neurons in a globally optimal fashion. It has recently been demonstrated that combining Hebbian learning with occasional alterations of normal neural states avoids this problem by means of self-organized enlargement of the best basins of attraction. However, so far it is not clear to what extent this process of self-optimization is also operative in real brains. Here we demonstrate that it can be transferred to more biologically plausible neural networks by implementing a self-optimizing spiking neural network model. In addition, by using this spiking neural network to emulate a Hopfield network with Hebbian learning, we attempt to make a connection between rate-based and temporal coding based neural systems. Although further work is required to make this model more realistic, it already suggests that the efficacy of the self-optimizing process is independent from the simplifying assumptions of a conventional Hopfield network. We also discuss natural and cultural processes that could be responsible for occasional alteration of neural firing patterns in actual brains. Copyright © 2014 Elsevier Ltd. All rights reserved.

Neural Architecture of Selective Stopping Strategies: Distinct Brain Activity Patterns Are Associated with Attentional Capture But Not with Outright Stopping.

PubMed

Sebastian, Alexandra; Rössler, Kora; Wibral, Michael; Mobascher, Arian; Lieb, Klaus; Jung, Patrick; Tüscher, Oliver

2017-10-04

In stimulus-selective stop-signal tasks, the salient stop signal needs attentional processing before genuine response inhibition is completed. Differential prefrontal involvement in attentional capture and response inhibition has been linked to the right inferior frontal junction (IFJ) and ventrolateral prefrontal cortex (VLPFC), respectively. Recently, it has been suggested that stimulus-selective stopping may be accomplished by the following different strategies: individuals may selectively inhibit their response only upon detecting a stop signal (independent discriminate then stop strategy) or unselectively whenever detecting a stop or attentional capture signal (stop then discriminate strategy). Alternatively, the discrimination process of the critical signal (stop vs attentional capture signal) may interact with the go process (dependent discriminate then stop strategy). Those different strategies might differentially involve attention- and stopping-related processes that might be implemented by divergent neural networks. This should lead to divergent activation patterns and, if disregarded, interfere with analyses in neuroimaging studies. To clarify this crucial issue, we studied 87 human participants of both sexes during a stimulus-selective stop-signal task and performed strategy-dependent functional magnetic resonance imaging analyses. We found that, regardless of the strategy applied, outright stopping displayed indistinguishable brain activation patterns. However, during attentional capture different strategies resulted in divergent neural activation patterns with variable activation of right IFJ and bilateral VLPFC. In conclusion, the neural network involved in outright stopping is ubiquitous and independent of strategy, while different strategies impact on attention-related processes and underlying neural network usage. Strategic differences should therefore be taken into account particularly when studying attention-related processes in stimulus-selective stopping. SIGNIFICANCE STATEMENT Dissociating inhibition from attention has been a major challenge for the cognitive neuroscience of executive functions. Selective stopping tasks have been instrumental in addressing this question. However, recent theoretical, cognitive and behavioral research suggests that different strategies are applied in successful execution of the task. The underlying strategy-dependent neural networks might differ substantially. Here, we show evidence that, regardless of the strategy used, the neural network involved in outright stopping is ubiquitous. However, significant differences can only be found in the attention-related processes underlying those different strategies. Thus, when studying attentional processing of salient stop signals, strategic differences should be considered. In contrast, the neural networks implementing outright stopping seem less or not at all affected by strategic differences. Copyright © 2017 the authors 0270-6474/17/379786-10$15.00/0.

Where the Brain Appreciates the Final State of an Event: The Neural Correlates of Telicity

ERIC Educational Resources Information Center

Romagno, Domenica; Rota, Giuseppina; Ricciardi, Emiliano; Pietrini, Pietro

2012-01-01

In this study we investigated whether the human brain distinguishes between telic events that necessarily entail a specified endpoint (e.g., "reaching"), and atelic events with no delimitation or final state (e.g., "chasing"). We used functional magnetic resonance imaging to explore the patterns of neural response associated with verbs denoting…

Neural substrates of treatment response to cognitive-behavioral therapy in panic disorder with agoraphobia.

PubMed

Lueken, Ulrike; Straube, Benjamin; Konrad, Carsten; Wittchen, Hans-Ulrich; Ströhle, Andreas; Wittmann, André; Pfleiderer, Bettina; Uhlmann, Christina; Arolt, Volker; Jansen, Andreas; Kircher, Tilo

2013-11-01

Although exposure-based cognitive-behavioral therapy (CBT) is an effective treatment option for panic disorder with agoraphobia, the neural substrates of treatment response remain unknown. Evidence suggests that panic disorder with agoraphobia is characterized by dysfunctional safety signal processing. Using fear conditioning as a neurofunctional probe, the authors investigated neural baseline characteristics and neuroplastic changes after CBT that were associated with treatment outcome in patients with panic disorder with agoraphobia. Neural correlates of fear conditioning and extinction were measured using functional MRI before and after a manualized CBT program focusing on behavioral exposure in 49 medication-free patients with a primary diagnosis of panic disorder with agoraphobia. Treatment response was defined as a reduction exceeding 50% in Hamilton Anxiety Rating Scale scores. At baseline, nonresponders exhibited enhanced activation in the right pregenual anterior cingulate cortex, the hippocampus, and the amygdala in response to a safety signal. While this activation pattern partly resolved in nonresponders after CBT, successful treatment was characterized by increased right hippocampal activation when processing stimulus contingencies. Treatment response was associated with an inhibitory functional coupling between the anterior cingulate cortex and the amygdala that did not change over time. This study identified brain activation patterns associated with treatment response in patients with panic disorder with agoraphobia. Altered safety signal processing and anterior cingulate cortex-amygdala coupling may indicate individual differences among these patients that determine the effectiveness of exposure-based CBT and associated neuroplastic changes. Findings point to brain networks by which successful CBT in this patient population is mediated.

Transcriptional response of Hoxb genes to retinoid signalling is regionally restricted along the neural tube rostrocaudal axis.

PubMed

Carucci, Nicoletta; Cacci, Emanuele; Nisi, Paola S; Licursi, Valerio; Paul, Yu-Lee; Biagioni, Stefano; Negri, Rodolfo; Rugg-Gunn, Peter J; Lupo, Giuseppe

2017-04-01

During vertebrate neural development, positional information is largely specified by extracellular morphogens. Their distribution, however, is very dynamic due to the multiple roles played by the same signals in the developing and adult neural tissue. This suggests that neural progenitors are able to modify their competence to respond to morphogen signalling and autonomously maintain positional identities after their initial specification. In this work, we take advantage of in vitro culture systems of mouse neural stem/progenitor cells (NSPCs) to show that NSPCs isolated from rostral or caudal regions of the mouse neural tube are differentially responsive to retinoic acid (RA), a pivotal morphogen for the specification of posterior neural fates. Hoxb genes are among the best known RA direct targets in the neural tissue, yet we found that RA could promote their transcription only in caudal but not in rostral NSPCs. Correlating with these effects, key RA-responsive regulatory regions in the Hoxb cluster displayed opposite enrichment of activating or repressing histone marks in rostral and caudal NSPCs. Finally, RA was able to strengthen Hoxb chromatin activation in caudal NSPCs, but was ineffective on the repressed Hoxb chromatin of rostral NSPCs. These results suggest that the response of NSPCs to morphogen signalling across the rostrocaudal axis of the neural tube may be gated by the epigenetic configuration of target patterning genes, allowing long-term maintenance of intrinsic positional values in spite of continuously changing extrinsic signals.

Developmental trajectory of neural specialization for letter and number visual processing.

PubMed

Park, Joonkoo; van den Berg, Berry; Chiang, Crystal; Woldorff, Marty G; Brannon, Elizabeth M

2018-05-01

Adult neuroimaging studies have demonstrated dissociable neural activation patterns in the visual cortex in response to letters (Latin alphabet) and numbers (Arabic numerals), which suggest a strong experiential influence of reading and mathematics on the human visual system. Here, developmental trajectories in the event-related potential (ERP) patterns evoked by visual processing of letters, numbers, and false fonts were examined in four different age groups (7-, 10-, 15-year-olds, and young adults). The 15-year-olds and adults showed greater neural sensitivity to letters over numbers in the left visual cortex and the reverse pattern in the right visual cortex, extending previous findings in adults to teenagers. In marked contrast, 7- and 10-year-olds did not show this dissociable neural pattern. Furthermore, the contrast of familiar stimuli (letters or numbers) versus unfamiliar ones (false fonts) showed stark ERP differences between the younger (7- and 10-year-olds) and the older (15-year-olds and adults) participants. These results suggest that both coarse (familiar versus unfamiliar) and fine (letters versus numbers) tuning for letters and numbers continue throughout childhood and early adolescence, demonstrating a profound impact of uniquely human cultural inventions on visual cognition and its development. © 2017 John Wiley & Sons Ltd.

Common and Distinct Neural Mechanisms of Attentional Switching and Response Conflict

PubMed Central

Kim, Chobok; Johnson, Nathan F.; Gold, Brian T.

2012-01-01

The human capacities for overcoming prepotent actions and flexibly switching between tasks represent cornerstones of cognitive control. Functional neuroimaging has implicated a diverse set of brain regions contributing to each of these cognitive control processes. However, the extent to which attentional switching and response conflict draw on shared or distinct neural mechanisms remains unclear. The current study examined the neural correlates of response conflict and attentional switching using event-related functional magnetic resonance imaging (fMRI) and a fully randomized 2×2 design. We manipulated an arrow-word version of the Stroop task to measure conflict and switching in the context of a single task decision, in response to a common set of stimuli. Under these common conditions, both behavioral and imaging data showed significant main effects of conflict and switching but no interaction. However, conjunction analyses identified frontal regions involved in both switching and response conflict, including the dorsal anterior cingulate cortex (dACC) and left inferior frontal junction. In addition, connectivity analyses demonstrated task-dependent functional connectivity patterns between dACC and inferior temporal cortex for attentional switching and between dACC and posterior parietal cortex for response conflict. These results suggest that the brain makes use of shared frontal regions, but can dynamically modulate the connectivity patterns of some of those regions, to deal with attentional switching and response conflict. PMID:22750124

Common and distinct neural mechanisms of attentional switching and response conflict.

PubMed

Kim, Chobok; Johnson, Nathan F; Gold, Brian T

2012-08-21

The human capacities for overcoming prepotent actions and flexibly switching between tasks represent cornerstones of cognitive control. Functional neuroimaging has implicated a diverse set of brain regions contributing to each of these cognitive control processes. However, the extent to which attentional switching and response conflict draw on shared or distinct neural mechanisms remains unclear. The current study examined the neural correlates of response conflict and attentional switching using event-related functional magnetic resonance imaging (fMRI) and a fully randomized 2×2 design. We manipulated an arrow-word version of the Stroop task to measure conflict and switching in the context of a single task decision, in response to a common set of stimuli. Under these common conditions, both behavioral and imaging data showed significant main effects of conflict and switching but no interaction. However, conjunction analyses identified frontal regions involved in both switching and response conflict, including the dorsal anterior cingulate cortex (dACC) and left inferior frontal junction. In addition, connectivity analyses demonstrated task-dependent functional connectivity patterns between dACC and inferior temporal cortex for attentional switching and between dACC and posterior parietal cortex for response conflict. These results suggest that the brain makes use of shared frontal regions, but can dynamically modulate the connectivity patterns of some of those regions, to deal with attentional switching and response conflict. Copyright © 2012 Elsevier B.V. All rights reserved.

Neural Response during the Activation of the Attachment System in Patients with Borderline Personality Disorder: An fMRI Study

PubMed Central

Buchheim, Anna; Erk, Susanne; George, Carol; Kächele, Horst; Martius, Philipp; Pokorny, Dan; Spitzer, Manfred; Walter, Henrik

2016-01-01

Individuals with borderline personality disorder (BPD) are characterized by emotional instability, impaired emotion regulation and unresolved attachment patterns associated with abusive childhood experiences. We investigated the neural response during the activation of the attachment system in BPD patients compared to healthy controls using functional magnetic resonance imaging (fMRI). Eleven female patients with BPD without posttraumatic stress disorder (PTSD) and 17 healthy female controls matched for age and education were telling stories in the scanner in response to the Adult Attachment Projective Picture System (AAP), an eight-picture set assessment of adult attachment. The picture set includes theoretically-derived attachment scenes, such as separation, death, threat and potential abuse. The picture presentation order is designed to gradually increase the activation of the attachment system. Each picture stimulus was presented for 2 min. Analyses examine group differences in attachment classifications and neural activation patterns over the course of the task. Unresolved attachment was associated with increasing amygdala activation over the course of the attachment task in patients as well as controls. Unresolved controls, but not patients, showed activation in the right dorsolateral prefrontal cortex (DLPFC) and the rostral cingulate zone (RCZ). We interpret this as a neural signature of BPD patients’ inability to exert top-down control under conditions of attachment distress. These findings point to possible neural mechanisms for underlying affective dysregulation in BPD in the context of attachment trauma and fear. PMID:27531977

Collaborative Brain-Computer Interface for Aiding Decision-Making

PubMed Central

Poli, Riccardo; Valeriani, Davide; Cinel, Caterina

2014-01-01

We look at the possibility of integrating the percepts from multiple non-communicating observers as a means of achieving better joint perception and better group decisions. Our approach involves the combination of a brain-computer interface with human behavioural responses. To test ideas in controlled conditions, we asked observers to perform a simple matching task involving the rapid sequential presentation of pairs of visual patterns and the subsequent decision as whether the two patterns in a pair were the same or different. We recorded the response times of observers as well as a neural feature which predicts incorrect decisions and, thus, indirectly indicates the confidence of the decisions made by the observers. We then built a composite neuro-behavioural feature which optimally combines the two measures. For group decisions, we uses a majority rule and three rules which weigh the decisions of each observer based on response times and our neural and neuro-behavioural features. Results indicate that the integration of behavioural responses and neural features can significantly improve accuracy when compared with the majority rule. An analysis of event-related potentials indicates that substantial differences are present in the proximity of the response for correct and incorrect trials, further corroborating the idea of using hybrids of brain-computer interfaces and traditional strategies for improving decision making. PMID:25072739

Linking dynamic patterns of neural activity in orbitofrontal cortex with decision making.

PubMed

Rich, Erin L; Stoll, Frederic M; Rudebeck, Peter H

2018-04-01

Humans and animals demonstrate extraordinary flexibility in choice behavior, particularly when deciding based on subjective preferences. We evaluate options on different scales, deliberate, and often change our minds. Little is known about the neural mechanisms that underlie these dynamic aspects of decision-making, although neural activity in orbitofrontal cortex (OFC) likely plays a central role. Recent evidence from studies in macaques shows that attention modulates value responses in OFC, and that ensembles of OFC neurons dynamically signal different options during choices. When contexts change, these ensembles flexibly remap to encode the new task. Determining how these dynamic patterns emerge and relate to choices will inform models of decision-making and OFC function. Copyright © 2017 Elsevier Ltd. All rights reserved.

Utilising reinforcement learning to develop strategies for driving auditory neural implants.

PubMed

Lee, Geoffrey W; Zambetta, Fabio; Li, Xiaodong; Paolini, Antonio G

2016-08-01

In this paper we propose a novel application of reinforcement learning to the area of auditory neural stimulation. We aim to develop a simulation environment which is based off real neurological responses to auditory and electrical stimulation in the cochlear nucleus (CN) and inferior colliculus (IC) of an animal model. Using this simulator we implement closed loop reinforcement learning algorithms to determine which methods are most effective at learning effective acoustic neural stimulation strategies. By recording a comprehensive set of acoustic frequency presentations and neural responses from a set of animals we created a large database of neural responses to acoustic stimulation. Extensive electrical stimulation in the CN and the recording of neural responses in the IC provides a mapping of how the auditory system responds to electrical stimuli. The combined dataset is used as the foundation for the simulator, which is used to implement and test learning algorithms. Reinforcement learning, utilising a modified n-Armed Bandit solution, is implemented to demonstrate the model's function. We show the ability to effectively learn stimulation patterns which mimic the cochlea's ability to covert acoustic frequencies to neural activity. Time taken to learn effective replication using neural stimulation takes less than 20 min under continuous testing. These results show the utility of reinforcement learning in the field of neural stimulation. These results can be coupled with existing sound processing technologies to develop new auditory prosthetics that are adaptable to the recipients current auditory pathway. The same process can theoretically be abstracted to other sensory and motor systems to develop similar electrical replication of neural signals.

Motor Cortical Visuomotor Feedback Activity Is Initially Isolated from Downstream Targets in Output-Null Neural State Space Dimensions.

PubMed

Stavisky, Sergey D; Kao, Jonathan C; Ryu, Stephen I; Shenoy, Krishna V

2017-07-05

Neural circuits must transform new inputs into outputs without prematurely affecting downstream circuits while still maintaining other ongoing communication with these targets. We investigated how this isolation is achieved in the motor cortex when macaques received visual feedback signaling a movement perturbation. To overcome limitations in estimating the mapping from cortex to arm movements, we also conducted brain-machine interface (BMI) experiments where we could definitively identify neural firing patterns as output-null or output-potent. This revealed that perturbation-evoked responses were initially restricted to output-null patterns that cancelled out at the neural population code readout and only later entered output-potent neural dimensions. This mechanism was facilitated by the circuit's large null space and its ability to strongly modulate output-potent dimensions when generating corrective movements. These results show that the nervous system can temporarily isolate portions of a circuit's activity from its downstream targets by restricting this activity to the circuit's output-null neural dimensions. Copyright © 2017 Elsevier Inc. All rights reserved.

Mapping of Courtship Behavior-Induced Neural Activity in the Thoracic Ganglia of Silkmoth Bombyx mori by an Immediate Early Gene, Hr38.

PubMed

Morishita, Koudai; Iwami, Masafumi; Kiya, Taketoshi

2018-06-01

In the central nervous system of insects, motor patterns are generated in the thoracic ganglia under the control of brain, where sensory information is integrated and behavioral decisions are made. Previously, we established neural activity-mapping methods using an immediate early gene, BmHr38, as a neural activity marker in the brain of male silkmoth Bombyx mori. In the present study, to gain insights into neural mechanisms of motor-pattern generation in the thoracic ganglia, we investigated expression of BmHr38 in response to sex pheromone-induced courtship behavior. Levels of BmHr38 expression were strongly correlated between the brain and thoracic ganglia, suggesting that neural activity in the thoracic ganglia is tightly controlled by the brain. In situ hybridization of BmHr38 revealed that 20-30% of thoracic neurons are activated by courtship behavior. Using serial sections, we constructed a comprehensive map of courtship behaviorinduced activity in the thoracic ganglia. These results provide important clues into how complex courtship behavior is generated in the neural circuits of thoracic ganglia.

Controlling selective stimulations below a spinal cord hemisection using brain recordings with a neural interface system approach

NASA Astrophysics Data System (ADS)

Panetsos, Fivos; Sanchez-Jimenez, Abel; Torets, Carlos; Largo, Carla; Micera, Silvestro

2011-08-01

In this work we address the use of realtime cortical recordings for the generation of coherent, reliable and robust motor activity in spinal-lesioned animals through selective intraspinal microstimulation (ISMS). The spinal cord of adult rats was hemisectioned and groups of multielectrodes were implanted in both the central nervous system (CNS) and the spinal cord below the lesion level to establish a neural system interface (NSI). To test the reliability of this new NSI connection, highly repeatable neural responses recorded from the CNS were used as a pattern generator of an open-loop control strategy for selective ISMS of the spinal motoneurons. Our experimental procedure avoided the spontaneous non-controlled and non-repeatable neural activity that could have generated spurious ISMS and the consequent undesired muscle contractions. Combinations of complex CNS patterns generated precisely coordinated, reliable and robust motor actions.

A Common Neural Code for Perceived and Inferred Emotion

PubMed Central

Saxe, Rebecca

2014-01-01

Although the emotions of other people can often be perceived from overt reactions (e.g., facial or vocal expressions), they can also be inferred from situational information in the absence of observable expressions. How does the human brain make use of these diverse forms of evidence to generate a common representation of a target's emotional state? In the present research, we identify neural patterns that correspond to emotions inferred from contextual information and find that these patterns generalize across different cues from which an emotion can be attributed. Specifically, we use functional neuroimaging to measure neural responses to dynamic facial expressions with positive and negative valence and to short animations in which the valence of a character's emotion could be identified only from the situation. Using multivoxel pattern analysis, we test for regions that contain information about the target's emotional state, identifying representations specific to a single stimulus type and representations that generalize across stimulus types. In regions of medial prefrontal cortex (MPFC), a classifier trained to discriminate emotional valence for one stimulus (e.g., animated situations) could successfully discriminate valence for the remaining stimulus (e.g., facial expressions), indicating a representation of valence that abstracts away from perceptual features and generalizes across different forms of evidence. Moreover, in a subregion of MPFC, this neural representation generalized to trials involving subjectively experienced emotional events, suggesting partial overlap in neural responses to attributed and experienced emotions. These data provide a step toward understanding how the brain transforms stimulus-bound inputs into abstract representations of emotion. PMID:25429141

A common neural code for perceived and inferred emotion.

PubMed

Skerry, Amy E; Saxe, Rebecca

2014-11-26

Although the emotions of other people can often be perceived from overt reactions (e.g., facial or vocal expressions), they can also be inferred from situational information in the absence of observable expressions. How does the human brain make use of these diverse forms of evidence to generate a common representation of a target's emotional state? In the present research, we identify neural patterns that correspond to emotions inferred from contextual information and find that these patterns generalize across different cues from which an emotion can be attributed. Specifically, we use functional neuroimaging to measure neural responses to dynamic facial expressions with positive and negative valence and to short animations in which the valence of a character's emotion could be identified only from the situation. Using multivoxel pattern analysis, we test for regions that contain information about the target's emotional state, identifying representations specific to a single stimulus type and representations that generalize across stimulus types. In regions of medial prefrontal cortex (MPFC), a classifier trained to discriminate emotional valence for one stimulus (e.g., animated situations) could successfully discriminate valence for the remaining stimulus (e.g., facial expressions), indicating a representation of valence that abstracts away from perceptual features and generalizes across different forms of evidence. Moreover, in a subregion of MPFC, this neural representation generalized to trials involving subjectively experienced emotional events, suggesting partial overlap in neural responses to attributed and experienced emotions. These data provide a step toward understanding how the brain transforms stimulus-bound inputs into abstract representations of emotion. Copyright © 2014 the authors 0270-6474/14/3315997-12$15.00/0.

Dynamic Encoding of Acoustic Features in Neural Responses to Continuous Speech.

PubMed

Khalighinejad, Bahar; Cruzatto da Silva, Guilherme; Mesgarani, Nima

2017-02-22

Humans are unique in their ability to communicate using spoken language. However, it remains unclear how the speech signal is transformed and represented in the brain at different stages of the auditory pathway. In this study, we characterized electroencephalography responses to continuous speech by obtaining the time-locked responses to phoneme instances (phoneme-related potential). We showed that responses to different phoneme categories are organized by phonetic features. We found that each instance of a phoneme in continuous speech produces multiple distinguishable neural responses occurring as early as 50 ms and as late as 400 ms after the phoneme onset. Comparing the patterns of phoneme similarity in the neural responses and the acoustic signals confirms a repetitive appearance of acoustic distinctions of phonemes in the neural data. Analysis of the phonetic and speaker information in neural activations revealed that different time intervals jointly encode the acoustic similarity of both phonetic and speaker categories. These findings provide evidence for a dynamic neural transformation of low-level speech features as they propagate along the auditory pathway, and form an empirical framework to study the representational changes in learning, attention, and speech disorders. SIGNIFICANCE STATEMENT We characterized the properties of evoked neural responses to phoneme instances in continuous speech. We show that each instance of a phoneme in continuous speech produces several observable neural responses at different times occurring as early as 50 ms and as late as 400 ms after the phoneme onset. Each temporal event explicitly encodes the acoustic similarity of phonemes, and linguistic and nonlinguistic information are best represented at different time intervals. Finally, we show a joint encoding of phonetic and speaker information, where the neural representation of speakers is dependent on phoneme category. These findings provide compelling new evidence for dynamic processing of speech sounds in the auditory pathway. Copyright © 2017 Khalighinejad et al.

Decoding the neural signatures of emotions expressed through sound.

PubMed

Sachs, Matthew E; Habibi, Assal; Damasio, Antonio; Kaplan, Jonas T

2018-07-01

Effective social functioning relies in part on the ability to identify emotions from auditory stimuli and respond appropriately. Previous studies have uncovered brain regions engaged by the affective information conveyed by sound. But some of the acoustical properties of sounds that express certain emotions vary remarkably with the instrument used to produce them, for example the human voice or a violin. Do these brain regions respond in the same way to different emotions regardless of the sound source? To address this question, we had participants (N = 38, 20 females) listen to brief audio excerpts produced by the violin, clarinet, and human voice, each conveying one of three target emotions-happiness, sadness, and fear-while brain activity was measured with fMRI. We used multivoxel pattern analysis to test whether emotion-specific neural responses to the voice could predict emotion-specific neural responses to musical instruments and vice-versa. A whole-brain searchlight analysis revealed that patterns of activity within the primary and secondary auditory cortex, posterior insula, and parietal operculum were predictive of the affective content of sound both within and across instruments. Furthermore, classification accuracy within the anterior insula was correlated with behavioral measures of empathy. The findings suggest that these brain regions carry emotion-specific patterns that generalize across sounds with different acoustical properties. Also, individuals with greater empathic ability have more distinct neural patterns related to perceiving emotions. These results extend previous knowledge regarding how the human brain extracts emotional meaning from auditory stimuli and enables us to understand and connect with others effectively. Copyright © 2018 Elsevier Inc. All rights reserved.

Neural Language Processing in Adolescent First-Language Learners: Longitudinal Case Studies in American Sign Language

PubMed Central

Ferjan Ramirez, Naja; Leonard, Matthew K.; Davenport, Tristan S.; Torres, Christina; Halgren, Eric; Mayberry, Rachel I.

2016-01-01

One key question in neurolinguistics is the extent to which the neural processing system for language requires linguistic experience during early life to develop fully. We conducted a longitudinal anatomically constrained magnetoencephalography (aMEG) analysis of lexico-semantic processing in 2 deaf adolescents who had no sustained language input until 14 years of age, when they became fully immersed in American Sign Language. After 2 to 3 years of language, the adolescents' neural responses to signed words were highly atypical, localizing mainly to right dorsal frontoparietal regions and often responding more strongly to semantically primed words (Ferjan Ramirez N, Leonard MK, Torres C, Hatrak M, Halgren E, Mayberry RI. 2014. Neural language processing in adolescent first-language learners. Cereb Cortex. 24 (10): 2772–2783). Here, we show that after an additional 15 months of language experience, the adolescents' neural responses remained atypical in terms of polarity. While their responses to less familiar signed words still showed atypical localization patterns, the localization of responses to highly familiar signed words became more concentrated in the left perisylvian language network. Our findings suggest that the timing of language experience affects the organization of neural language processing; however, even in adolescence, language representation in the human brain continues to evolve with experience. PMID:25410427

Development of infant mismatch responses to auditory pattern changes between 2 and 4 months old.

PubMed

He, Chao; Hotson, Lisa; Trainor, Laurel J

2009-02-01

In order to process speech and music, the auditory cortex must learn to process patterns of sounds. Our previous studies showed that with a stream consisting of a repeating (standard) sound, younger infants show an increase in the amplitude of a positive slow wave in response to occasional changes (deviants) in pitch or duration, whereas older infants show a faster negative response that resembles mismatch negativity (MMN) in adults (Trainor et al., 2001, 2003; He et al., 2007). MMN reflects an automatic change-detection process that does not require attention, conscious awareness or behavioural response for its elicitation (Picton et al., 2000; Näätänen et al., 2007). It is an important tool for understanding auditory perception because MMN reflects a change-detection mechanism, and not simply that repetition of a stimulus results in a refractory state of sensory neural circuits while occasional changes to a new sound activate new non-refractory neural circuits (Näätänen et al., 2005). For example, MMN is elicited by a change in the pattern of a repeating note sequence, even when no new notes are introduced that could activate new sensory circuits (Alain et al., 1994, 1999;Schröger et al., 1996). In the present study, we show that in response to a change in the pattern of two repeating tones, MMN in 4-month-olds remains robust whereas the 2-month-old response does not. This indicates that the MMN response to a change in pattern at 4 months reflects the activation of a change-detection mechanism similarly as in adults.

Responses of Cells in the Midbrain Near-Response Area in Monkeys with Strabismus

PubMed Central

Das, Vallabh E.

2012-01-01

Purpose. To investigate whether neuronal activity within the supraoculomotor area (SOA—monosynaptically connected to medial rectus motoneurons and encode vergence angle) of strabismic monkeys was correlated with the angle of horizontal misalignment and therefore helps to define the state of strabismus. Methods. Single-cell neural activity was recorded from SOA neurons in two monkeys with exotropia as they performed eye movement tasks during monocular viewing. Results. Horizontal strabismus angle varied depending on eye of fixation (dissociated horizontal deviation) and the activity of SOA cells (n = 35) varied in correlation with the angle of strabismus. Both near-response (cells that showed larger firing rates for smaller angles of exotropia) and far-response (cells that showed lower firing rates for smaller angles of exotropia) cells were identified. SOA cells showed no modulation of activity with changes in conjugate eye position as tested during smooth-pursuit, thereby verifying that the responses were related to binocular misalignment. SOA cell activity was also not correlated with change in horizontal misalignment due to A-patterns of strabismus. Comparison of SOA population activity in strabismic animals and normal monkeys (described in the literature) show that both neural thresholds and neural sensitivities are altered in the strabismic animals compared with the normal animals. Conclusions. SOA cell activity is important in determining the state of horizontal strabismus, possibly by altering vergence tone in extraocular muscle. The lack of correlated SOA activity with changes in misalignment due to A/V patterns suggest that circuits mediating horizontal strabismus angle and those that mediate A/V patterns are different. PMID:22562519

Decoding Task and Stimulus Representations in Face-responsive Cortex

PubMed Central

Kliemann, Dorit; Jacoby, Nir; Anzellotti, Stefano; Saxe, Rebecca R.

2017-01-01

Faces provide rich social information about others’ stable traits (e.g., age) and fleeting states of mind (e.g., emotional expression). While some of these facial aspects may be processed automatically, observers can also deliberately attend to some features while ignoring others. It remains unclear how internal goals (e.g., task context) influence the representational geometry of variable and stable facial aspects in face-responsive cortex. We investigated neural response patterns related to decoding i) the intention to attend to a facial aspect before its perception, ii) the attended aspect of a face and iii) stimulus properties. We measured neural responses while subjects watched videos of dynamic positive and negative expressions, and judged the age or the expression’s valence. Split-half multivoxel pattern analyses (MVPA) showed that (i) the intention to attend to a specific aspect of a face can be decoded from left fronto-lateral, but not face-responsive regions; (ii) during face perception, the attend aspect (age vs emotion) could be robustly decoded from almost all face-responsive regions; and (iii) a stimulus property (valence), was represented in right posterior superior temporal sulcus and medial prefrontal cortices. The effect of deliberately shifting the focus of attention on representations suggest a powerful influence of top-down signals on cortical representation of social information, varying across cortical regions, likely reflecting neural flexibility to optimally integrate internal goals and dynamic perceptual input. PMID:27978778

Psychophysiology of neural, cognitive and affective integration: fMRI and autonomic indicants

PubMed Central

Critchley, Hugo D.

2009-01-01

Behaviour is shaped by environmental challenge in the context of homoeostatic need. Emotional and cognitive processes evoke patterned changes in bodily state that may signal emotional state to others. This dynamic modulation of visceral state is neurally mediated by sympathetic and parasympathetic divisions of the autonomic nervous system. Moreover neural afferents convey representations of the internal state of the body back to the brain to further influence emotion and cognition. Neuroimaging and lesion studies implicate specific regions of limbic forebrain in the behavioural generation of autonomic arousal states. Activity within these regions may predict emotion-specific autonomic response patterns within and between bodily organs, with implications for psychosomatic medicine. Feedback from the viscera is mapped hierarchically in the brain to influence efferent signals, and ultimately at the cortical level to engender and reinforce affective responses and subjective feeling states. Again neuroimaging and patient studies suggest discrete neural substrates for these representations, notably regions of insula and orbitofrontal cortex. Individual differences in conscious access to these interoceptive representations predict differences in emotional experience, but equally the misperception of heightened arousal level may evoke changes in emotional behaviour through engagement of the same neural centres. Perturbation of feedback may impair emotional reactivity and, in the context of inflammatory states give rise to cognitive, affective and psychomotor expressions of illness. Changes in visceral state during emotion may be mirrored in the responses of others, permitting a corresponding representation in the observer. The degree to which individuals are susceptible to this ‘contagion’ predicts individual differences in questionnaire ratings of empathy. Together these neuroimaging and clinical studies highlight the dynamic relationship between mind and body and help identify neural substrates that may translate thoughts into autonomic arousal and bodily states into feelings that can be shared. PMID:19414044

Response of neural reward regions to food cues in autism spectrum disorders

PubMed Central

2012-01-01

Background One hypothesis for the social deficits that characterize autism spectrum disorders (ASD) is diminished neural reward response to social interaction and attachment. Prior research using established monetary reward paradigms as a test of non-social reward to compare with social reward may involve confounds in the ability of individuals with ASD to utilize symbolic representation of money and the abstraction required to interpret monetary gains. Thus, a useful addition to our understanding of neural reward circuitry in ASD includes a characterization of the neural response to primary rewards. Method We asked 17 children with ASD and 18 children without ASD to abstain from eating for at least four hours before an MRI scan in which they viewed images of high-calorie foods. We assessed the neural reward network for increases in the blood oxygenation level dependent (BOLD) signal in response to the food images Results We found very similar patterns of increased BOLD signal to these images in the two groups; both groups showed increased BOLD signal in the bilateral amygdala, as well as in the nucleus accumbens, orbitofrontal cortex, and insula. Direct group comparisons revealed that the ASD group showed a stronger response to food cues in bilateral insula along the anterior-posterior gradient and in the anterior cingulate cortex than the control group, whereas there were no neural reward regions that showed higher activation for controls than for ASD. Conclusion These results suggest that neural response to primary rewards is not diminished but in fact shows an aberrant enhancement in children with ASD. PMID:22958533

Postpartum depressive symptoms moderate the link between mothers’ neural response to positive faces in reward and social regions and observed caregiving

PubMed Central

Guo, Chaohui; Moses-Kolko, Eydie L; Phillips, Mary L; Stepp, Stephanie D; Hipwell, Alison E

2017-01-01

Abstract Postpartum depression may disrupt socio-affective neural circuitry and compromise provision of positive parenting. Although work has evaluated how parental response to negative stimuli is related to caregiving, research is needed to examine how depressive symptoms during the postpartum period may be related to neural response to positive stimuli, especially positive faces, given depression’s association with biased processing of positive faces. The current study examined the association between neural response to adult happy faces and observations of maternal caregiving and the moderating role of postpartum depression, in a sample of 18- to 22-year old mothers (n = 70) assessed at 17 weeks (s.d. = 4.7 weeks) postpartum. Positive caregiving was associated with greater precuneus and occipital response to positive faces among mothers with lower depressive symptoms, but not for those with higher symptoms. For mothers with higher depressive symptoms, greater ventral and dorsal striatal response to positive faces was associated with more positive caregiving, whereas the opposite pattern emerged for mothers with lower symptoms. There was no association between negative caregiving and neural response to positive faces or negative faces. Processing of positive stimuli may be an important prognostic target in mothers with depressive symptoms, given its link with healthy caregiving behaviors. PMID:29048603

Improved discriminability of spatiotemporal neural patterns in rat motor cortical areas as directional choice learning progresses

PubMed Central

Mao, Hongwei; Yuan, Yuan; Si, Jennie

2015-01-01

Animals learn to choose a proper action among alternatives to improve their odds of success in food foraging and other activities critical for survival. Through trial-and-error, they learn correct associations between their choices and external stimuli. While a neural network that underlies such learning process has been identified at a high level, it is still unclear how individual neurons and a neural ensemble adapt as learning progresses. In this study, we monitored the activity of single units in the rat medial and lateral agranular (AGm and AGl, respectively) areas as rats learned to make a left or right side lever press in response to a left or right side light cue. We noticed that rat movement parameters during the performance of the directional choice task quickly became stereotyped during the first 2–3 days or sessions. But learning the directional choice problem took weeks to occur. Accompanying rats' behavioral performance adaptation, we observed neural modulation by directional choice in recorded single units. Our analysis shows that ensemble mean firing rates in the cue-on period did not change significantly as learning progressed, and the ensemble mean rate difference between left and right side choices did not show a clear trend of change either. However, the spatiotemporal firing patterns of the neural ensemble exhibited improved discriminability between the two directional choices through learning. These results suggest a spatiotemporal neural coding scheme in a motor cortical neural ensemble that may be responsible for and contributing to learning the directional choice task. PMID:25798093

Optimal Design for Hetero-Associative Memory: Hippocampal CA1 Phase Response Curve and Spike-Timing-Dependent Plasticity

PubMed Central

Miyata, Ryota; Ota, Keisuke; Aonishi, Toru

2013-01-01

Recently reported experimental findings suggest that the hippocampal CA1 network stores spatio-temporal spike patterns and retrieves temporally reversed and spread-out patterns. In this paper, we explore the idea that the properties of the neural interactions and the synaptic plasticity rule in the CA1 network enable it to function as a hetero-associative memory recalling such reversed and spread-out spike patterns. In line with Lengyel’s speculation (Lengyel et al., 2005), we firstly derive optimally designed spike-timing-dependent plasticity (STDP) rules that are matched to neural interactions formalized in terms of phase response curves (PRCs) for performing the hetero-associative memory function. By maximizing object functions formulated in terms of mutual information for evaluating memory retrieval performance, we search for STDP window functions that are optimal for retrieval of normal and doubly spread-out patterns under the constraint that the PRCs are those of CA1 pyramidal neurons. The system, which can retrieve normal and doubly spread-out patterns, can also retrieve reversed patterns with the same quality. Finally, we demonstrate that purposely designed STDP window functions qualitatively conform to typical ones found in CA1 pyramidal neurons. PMID:24204822

SoxB1-driven transcriptional network underlies neural-specific interpretation of morphogen signals.

PubMed

Oosterveen, Tony; Kurdija, Sanja; Ensterö, Mats; Uhde, Christopher W; Bergsland, Maria; Sandberg, Magnus; Sandberg, Rickard; Muhr, Jonas; Ericson, Johan

2013-04-30

The reiterative deployment of a small cadre of morphogen signals underlies patterning and growth of most tissues during embyogenesis, but how such inductive events result in tissue-specific responses remains poorly understood. By characterizing cis-regulatory modules (CRMs) associated with genes regulated by Sonic hedgehog (Shh), retinoids, or bone morphogenetic proteins in the CNS, we provide evidence that the neural-specific interpretation of morphogen signaling reflects a direct integration of these pathways with SoxB1 proteins at the CRM level. Moreover, expression of SoxB1 proteins in the limb bud confers on mesodermal cells the potential to activate neural-specific target genes upon Shh, retinoid, or bone morphogenetic protein signaling, and the collocation of binding sites for SoxB1 and morphogen-mediatory transcription factors in CRMs faithfully predicts neural-specific gene activity. Thus, an unexpectedly simple transcriptional paradigm appears to conceptually explain the neural-specific interpretation of pleiotropic signaling during vertebrate development. Importantly, genes induced in a SoxB1-dependent manner appear to constitute repressive gene regulatory networks that are directly interlinked at the CRM level to constrain the regional expression of patterning genes. Accordingly, not only does the topology of SoxB1-driven gene regulatory networks provide a tissue-specific mode of gene activation, but it also determines the spatial expression pattern of target genes within the developing neural tube.

Visual pattern recognition based on spatio-temporal patterns of retinal ganglion cells’ activities

PubMed Central

Jing, Wei; Liu, Wen-Zhong; Gong, Xin-Wei; Gong, Hai-Qing

2010-01-01

Neural information is processed based on integrated activities of relevant neurons. Concerted population activity is one of the important ways for retinal ganglion cells to efficiently organize and process visual information. In the present study, the spike activities of bullfrog retinal ganglion cells in response to three different visual patterns (checker-board, vertical gratings and horizontal gratings) were recorded using multi-electrode arrays. A measurement of subsequence distribution discrepancy (MSDD) was applied to identify the spatio-temporal patterns of retinal ganglion cells’ activities in response to different stimulation patterns. The results show that the population activity patterns were different in response to different stimulation patterns, such difference in activity pattern was consistently detectable even when visual adaptation occurred during repeated experimental trials. Therefore, the stimulus pattern can be reliably discriminated according to the spatio-temporal pattern of the neuronal activities calculated using the MSDD algorithm. PMID:21886670

Affective neural response to restricted interests in Autism Spectrum Disorders

PubMed Central

Cascio, Carissa J.; Foss-Feig, Jennifer H.; Heacock, Jessica; Schauder, Kimberly B.; Loring, Whitney A.; Rogers, Baxter P.; Pryweller, Jennifer R.; Newsom, Cassandra R.; Cockhren, Jurnell; Cao, Aize; Bolton, Scott

2013-01-01

Background Restricted interests are a class of repetitive behavior in autism spectrum disorders (ASD) whose intensity and narrow focus often contribute to significant interference with daily functioning. While numerous neuroimaging studies have investigated executive circuits as putative neural substrates of repetitive behavior, recent work implicates affective neural circuits in restricted interests. We sought to explore the role of affective neural circuits and determine how restricted interests are distinguished from hobbies or interests in typical development. Methods We compared a group of children with ASD to a typically developing (TD) group of children with strong interests or hobbies, employing parent report, an operant behavioral task, and functional imaging with personalized stimuli based on individual interests. Results While performance on the operant task was similar between the two groups, parent report of intensity and interference of interests was significantly higher in the ASD group. Both the ASD and TD groups showed increased BOLD response in widespread affective neural regions to pictures of their own interest. When viewing pictures of other children's interests, the TD group showed a similar pattern, whereas BOLD response in the ASD group was much more limited. Increased BOLD response in the insula and anterior cingulate cortex distinguished the ASD from the TD group, and parent report of the intensity and interference with daily life of the child's restricted interest predicted insula response. Conclusions While affective neural network response and operant behavior are comparable in typical and restricted interests, the narrowness of focus that clinically distinguishes restricted interests in ASD is reflected in more interference in daily life and aberrantly enhanced insula and anterior cingulate response to individuals’ own interests in the ASD group. These results further support the involvement of affective neural networks in repetitive behaviors in ASD. PMID:24117668

Strategies for memory-based decision making: Modeling behavioral and neural signatures within a cognitive architecture.

PubMed

Fechner, Hanna B; Pachur, Thorsten; Schooler, Lael J; Mehlhorn, Katja; Battal, Ceren; Volz, Kirsten G; Borst, Jelmer P

2016-12-01

How do people use memories to make inferences about real-world objects? We tested three strategies based on predicted patterns of response times and blood-oxygen-level-dependent (BOLD) responses: one strategy that relies solely on recognition memory, a second that retrieves additional knowledge, and a third, lexicographic (i.e., sequential) strategy, that considers knowledge conditionally on the evidence obtained from recognition memory. We implemented the strategies as computational models within the Adaptive Control of Thought-Rational (ACT-R) cognitive architecture, which allowed us to derive behavioral and neural predictions that we then compared to the results of a functional magnetic resonance imaging (fMRI) study in which participants inferred which of two cities is larger. Overall, versions of the lexicographic strategy, according to which knowledge about many but not all alternatives is searched, provided the best account of the joint patterns of response times and BOLD responses. These results provide insights into the interplay between recognition and additional knowledge in memory, hinting at an adaptive use of these two sources of information in decision making. The results highlight the usefulness of implementing models of decision making within a cognitive architecture to derive predictions on the behavioral and neural level. Copyright © 2016 Elsevier B.V. All rights reserved.

Peripheral neuropathies associated with antibodies directed to intracellular neural antigens.

PubMed

Antoine, J-C

2014-10-01

Antibodies directed to intracellular neural antigens have been mainly described in paraneoplastic peripheral neuropathies and mostly includes anti-Hu and anti-CV2/CRMP5 antibodies. These antibodies occur with different patterns of neuropathy. With anti-Hu antibody, the most frequent manifestation is sensory neuronopathy with frequent autonomic involvement. With anti-CV2/CRMP5 the neuropathy is more frequently sensory and motor with an axonal or mixed demyelinating and axonal electrophysiological pattern. The clinical pattern of these neuropathies is in keeping with the cellular distribution of HuD and CRMP5 in the peripheral nervous system. Although present in high titer, these antibodies are probably not directly responsible for the neuropathy. Pathological and experimental studies indicate that cytotoxic T-cells are probably the main effectors of the immune response. These disorders contrast with those in which antibodies recognize a cell surface antigen and are probably responsible for the disease. The neuronal cell death and axonal degeneration which result from T-cell mediated immunity explains why treating these disorders remains challenging. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Neural Activity in the Ventral Pallidum Encodes Variation in the Incentive Value of a Reward Cue

PubMed Central

Meyer, Paul J.; Ferguson, Lindsay M.; Robinson, Terry E.; Aldridge, J. Wayne

2016-01-01

There is considerable individual variation in the extent to which reward cues are attributed with incentive salience. For example, a food-predictive conditioned stimulus (CS; an illuminated lever) becomes attractive, eliciting approach toward it only in some rats (“sign trackers,” STs), whereas others (“goal trackers,” GTs) approach the food cup during the CS period. The purpose of this study was to determine how individual differences in Pavlovian approach responses are represented in neural firing patterns in the major output structure of the mesolimbic system, the ventral pallidum (VP). Single-unit in vivo electrophysiology was used to record neural activity in the caudal VP during the performance of ST and GT conditioned responses. All rats showed neural responses to both cue onset and reward delivery but, during the CS period, STs showed greater neural activity than GTs both in terms of the percentage of responsive neurons and the magnitude of the change in neural activity. Furthermore, neural activity was positively correlated with the degree of attraction to the cue. Given that the CS had equal predictive value in STs and GTs, we conclude that neural activity in the VP largely reflects the degree to which the CS was attributed with incentive salience. SIGNIFICANCE STATEMENT Cues associated with reward can acquire motivational properties (i.e., incentive salience) that cause them to have a powerful influence on desire and motivated behavior. There are individual differences in sensitivity to reward-paired cues, with some individuals attaching greater motivational value to cues than others. Here, we investigated the neural activity associated with these individual differences in incentive salience. We found that cue-evoked neural firing in the ventral pallidum (VP) reflected the strength of incentive motivation, with the greatest neural responses occurring in individuals that demonstrated the strongest attraction to the cue. This suggests that the VP plays an important role in the process by which cues gain control over motivation and behavior. PMID:27466340

Distributed patterns of activity in sensory cortex reflect the precision of multiple items maintained in visual short-term memory.

PubMed

Emrich, Stephen M; Riggall, Adam C; Larocque, Joshua J; Postle, Bradley R

2013-04-10

Traditionally, load sensitivity of sustained, elevated activity has been taken as an index of storage for a limited number of items in visual short-term memory (VSTM). Recently, studies have demonstrated that the contents of a single item held in VSTM can be decoded from early visual cortex, despite the fact that these areas do not exhibit elevated, sustained activity. It is unknown, however, whether the patterns of neural activity decoded from sensory cortex change as a function of load, as one would expect from a region storing multiple representations. Here, we use multivoxel pattern analysis to examine the neural representations of VSTM in humans across multiple memory loads. In an important extension of previous findings, our results demonstrate that the contents of VSTM can be decoded from areas that exhibit a transient response to visual stimuli, but not from regions that exhibit elevated, sustained load-sensitive delay-period activity. Moreover, the neural information present in these transiently activated areas decreases significantly with increasing load, indicating load sensitivity of the patterns of activity that support VSTM maintenance. Importantly, the decrease in classification performance as a function of load is correlated with within-subject changes in mnemonic resolution. These findings indicate that distributed patterns of neural activity in putatively sensory visual cortex support the representation and precision of information in VSTM.

The auditory representation of speech sounds in human motor cortex

PubMed Central

Cheung, Connie; Hamilton, Liberty S; Johnson, Keith; Chang, Edward F

2016-01-01

In humans, listening to speech evokes neural responses in the motor cortex. This has been controversially interpreted as evidence that speech sounds are processed as articulatory gestures. However, it is unclear what information is actually encoded by such neural activity. We used high-density direct human cortical recordings while participants spoke and listened to speech sounds. Motor cortex neural patterns during listening were substantially different than during articulation of the same sounds. During listening, we observed neural activity in the superior and inferior regions of ventral motor cortex. During speaking, responses were distributed throughout somatotopic representations of speech articulators in motor cortex. The structure of responses in motor cortex during listening was organized along acoustic features similar to auditory cortex, rather than along articulatory features as during speaking. Motor cortex does not contain articulatory representations of perceived actions in speech, but rather, represents auditory vocal information. DOI: http://dx.doi.org/10.7554/eLife.12577.001 PMID:26943778

Category-Specific Neural Oscillations Predict Recall Organization During Memory Search

PubMed Central

Morton, Neal W.; Kahana, Michael J.; Rosenberg, Emily A.; Baltuch, Gordon H.; Litt, Brian; Sharan, Ashwini D.; Sperling, Michael R.; Polyn, Sean M.

2013-01-01

Retrieved-context models of human memory propose that as material is studied, retrieval cues are constructed that allow one to target particular aspects of past experience. We examined the neural predictions of these models by using electrocorticographic/depth recordings and scalp electroencephalography (EEG) to characterize category-specific oscillatory activity, while participants studied and recalled items from distinct, neurally discriminable categories. During study, these category-specific patterns predict whether a studied item will be recalled. In the scalp EEG experiment, category-specific activity during study also predicts whether a given item will be recalled adjacent to other same-category items, consistent with the proposal that a category-specific retrieval cue is used to guide memory search. Retrieved-context models suggest that integrative neural circuitry is involved in the construction and maintenance of the retrieval cue. Consistent with this hypothesis, we observe category-specific patterns that rise in strength as multiple same-category items are studied sequentially, and find that individual differences in this category-specific neural integration during study predict the degree to which a participant will use category information to organize memory search. Finally, we track the deployment of this retrieval cue during memory search: Category-specific patterns are stronger when participants organize their responses according to the category of the studied material. PMID:22875859

Neural mechanism of optimal limb coordination in crustacean swimming

PubMed Central

Zhang, Calvin; Guy, Robert D.; Mulloney, Brian; Zhang, Qinghai; Lewis, Timothy J.

2014-01-01

A fundamental challenge in neuroscience is to understand how biologically salient motor behaviors emerge from properties of the underlying neural circuits. Crayfish, krill, prawns, lobsters, and other long-tailed crustaceans swim by rhythmically moving limbs called swimmerets. Over the entire biological range of animal size and paddling frequency, movements of adjacent swimmerets maintain an approximate quarter-period phase difference with the more posterior limbs leading the cycle. We use a computational fluid dynamics model to show that this frequency-invariant stroke pattern is the most effective and mechanically efficient paddling rhythm across the full range of biologically relevant Reynolds numbers in crustacean swimming. We then show that the organization of the neural circuit underlying swimmeret coordination provides a robust mechanism for generating this stroke pattern. Specifically, the wave-like limb coordination emerges robustly from a combination of the half-center structure of the local central pattern generating circuits (CPGs) that drive the movements of each limb, the asymmetric network topology of the connections between local CPGs, and the phase response properties of the local CPGs, which we measure experimentally. Thus, the crustacean swimmeret system serves as a concrete example in which the architecture of a neural circuit leads to optimal behavior in a robust manner. Furthermore, we consider all possible connection topologies between local CPGs and show that the natural connectivity pattern generates the biomechanically optimal stroke pattern most robustly. Given the high metabolic cost of crustacean swimming, our results suggest that natural selection has pushed the swimmeret neural circuit toward a connection topology that produces optimal behavior. PMID:25201976

Modelling the perceptual similarity of facial expressions from image statistics and neural responses.

PubMed

Sormaz, Mladen; Watson, David M; Smith, William A P; Young, Andrew W; Andrews, Timothy J

2016-04-01

The ability to perceive facial expressions of emotion is essential for effective social communication. We investigated how the perception of facial expression emerges from the image properties that convey this important social signal, and how neural responses in face-selective brain regions might track these properties. To do this, we measured the perceptual similarity between expressions of basic emotions, and investigated how this is reflected in image measures and in the neural response of different face-selective regions. We show that the perceptual similarity of different facial expressions (fear, anger, disgust, sadness, happiness) can be predicted by both surface and feature shape information in the image. Using block design fMRI, we found that the perceptual similarity of expressions could also be predicted from the patterns of neural response in the face-selective posterior superior temporal sulcus (STS), but not in the fusiform face area (FFA). These results show that the perception of facial expression is dependent on the shape and surface properties of the image and on the activity of specific face-selective regions. Copyright © 2016 Elsevier Inc. All rights reserved.

The Shift from a Response Strategy to Object-in-Place Strategy during Learning Is Accompanied by a Matching Shift in Neural Firing Correlates in the Hippocampus

ERIC Educational Resources Information Center

Lee, Inah; Kim, Jangjin

2010-01-01

Hippocampal-dependent tasks often involve specific associations among stimuli (including egocentric information), and such tasks are therefore prone to interference from irrelevant task strategies before a correct strategy is found. Using an object-place paired-associate task, we investigated changes in neural firing patterns in the hippocampus in…

Monkey Prefrontal Neurons Reflect Logical Operations for Cognitive Control in a Variant of the AX Continuous Performance Task (AX-CPT)

PubMed Central

Blackman, Rachael K.; Crowe, David A.; DeNicola, Adele L.; Sakellaridi, Sofia; MacDonald, Angus W.

2016-01-01

Cognitive control is the ability to modify the behavioral response to a stimulus based on internal representations of goals or rules. We sought to characterize neural mechanisms in prefrontal cortex associated with cognitive control in a context that would maximize the potential for future translational relevance to human neuropsychiatric disease. To that end, we trained monkeys to perform a dot-pattern variant of the AX continuous performance task that is used to measure cognitive control impairment in patients with schizophrenia (MacDonald, 2008; Jones et al., 2010). Here we describe how information processing for cognitive control in this task is related to neural activity patterns in prefrontal cortex of monkeys, to advance our understanding of how behavioral flexibility is implemented by prefrontal neurons in general, and to model neural signals in the healthy brain that may be disrupted to produce cognitive control deficits in schizophrenia. We found that the neural representation of stimuli in prefrontal cortex is strongly biased toward stimuli that inhibit prepotent or automatic responses. We also found that population signals encoding different stimuli were modulated to overlap in time specifically in the case that information from multiple stimuli had to be integrated to select a conditional response. Finally, population signals relating to the motor response were biased toward less frequent and therefore less automatic actions. These data relate neuronal activity patterns in prefrontal cortex to logical information processing operations required for cognitive control, and they characterize neural events that may be disrupted in schizophrenia. SIGNIFICANCE STATEMENT Functional imaging studies have demonstrated that cognitive control deficits in schizophrenia are associated with reduced activation of the dorsolateral prefrontal cortex (MacDonald et al., 2005). However, these data do not reveal how the disease has disrupted the function of prefrontal neurons to produce the observed deficits in cognitive control. Relating cognitive control to neurophysiological signals at a cellular level in prefrontal cortex is a necessary first step toward understanding how disruption of these signals could lead to cognitive control failure in neuropsychiatric disease. To that end, we translated a task that measures cognitive control deficits in patients with schizophrenia to monkeys and describe here how neural signals in prefrontal cortex relate to performance. PMID:27053213

Associative memory model with spontaneous neural activity

NASA Astrophysics Data System (ADS)

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.

Neuronal integration in visual cortex elevates face category tuning to conscious face perception

PubMed Central

Fahrenfort, Johannes J.; Snijders, Tineke M.; Heinen, Klaartje; van Gaal, Simon; Scholte, H. Steven; Lamme, Victor A. F.

2012-01-01

The human brain has the extraordinary capability to transform cluttered sensory input into distinct object representations. For example, it is able to rapidly and seemingly without effort detect object categories in complex natural scenes. Surprisingly, category tuning is not sufficient to achieve conscious recognition of objects. What neural process beyond category extraction might elevate neural representations to the level where objects are consciously perceived? Here we show that visible and invisible faces produce similar category-selective responses in the ventral visual cortex. The pattern of neural activity evoked by visible faces could be used to decode the presence of invisible faces and vice versa. However, only visible faces caused extensive response enhancements and changes in neural oscillatory synchronization, as well as increased functional connectivity between higher and lower visual areas. We conclude that conscious face perception is more tightly linked to neural processes of sustained information integration and binding than to processes accommodating face category tuning. PMID:23236162

Pattern Analyses Reveal Separate Experience-Based Fear Memories in the Human Right Amygdala.

PubMed

Braem, Senne; De Houwer, Jan; Demanet, Jelle; Yuen, Kenneth S L; Kalisch, Raffael; Brass, Marcel

2017-08-23

Learning fear via the experience of contingencies between a conditioned stimulus (CS) and an aversive unconditioned stimulus (US) is often assumed to be fundamentally different from learning fear via instructions. An open question is whether fear-related brain areas respond differently to experienced CS-US contingencies than to merely instructed CS-US contingencies. Here, we contrasted two experimental conditions where subjects were instructed to expect the same CS-US contingencies while only one condition was characterized by prior experience with the CS-US contingency. Using multivoxel pattern analysis of fMRI data, we found CS-related neural activation patterns in the right amygdala (but not in other fear-related regions) that dissociated between whether a CS-US contingency had been instructed and experienced versus merely instructed. A second experiment further corroborated this finding by showing a category-independent neural response to instructed and experienced, but not merely instructed, CS presentations in the human right amygdala. Together, these findings are in line with previous studies showing that verbal fear instructions have a strong impact on both brain and behavior. However, even in the face of fear instructions, the human right amygdala still shows a separable neural pattern response to experience-based fear contingencies. SIGNIFICANCE STATEMENT In our study, we addressed a fundamental problem of the science of human fear learning and memory, namely whether fear learning via experience in humans relies on a neural pathway that can be separated from fear learning via verbal information. Using two new procedures and recent advances in the analysis of brain imaging data, we localized purely experience-based fear processing and memory in the right amygdala, thereby making a direct link between human and animal research. Copyright © 2017 the authors 0270-6474/17/378116-15$15.00/0.

Neural Language Processing in Adolescent First-Language Learners: Longitudinal Case Studies in American Sign Language.

PubMed

Ferjan Ramirez, Naja; Leonard, Matthew K; Davenport, Tristan S; Torres, Christina; Halgren, Eric; Mayberry, Rachel I

2016-03-01

One key question in neurolinguistics is the extent to which the neural processing system for language requires linguistic experience during early life to develop fully. We conducted a longitudinal anatomically constrained magnetoencephalography (aMEG) analysis of lexico-semantic processing in 2 deaf adolescents who had no sustained language input until 14 years of age, when they became fully immersed in American Sign Language. After 2 to 3 years of language, the adolescents' neural responses to signed words were highly atypical, localizing mainly to right dorsal frontoparietal regions and often responding more strongly to semantically primed words (Ferjan Ramirez N, Leonard MK, Torres C, Hatrak M, Halgren E, Mayberry RI. 2014. Neural language processing in adolescent first-language learners. Cereb Cortex. 24 (10): 2772-2783). Here, we show that after an additional 15 months of language experience, the adolescents' neural responses remained atypical in terms of polarity. While their responses to less familiar signed words still showed atypical localization patterns, the localization of responses to highly familiar signed words became more concentrated in the left perisylvian language network. Our findings suggest that the timing of language experience affects the organization of neural language processing; however, even in adolescence, language representation in the human brain continues to evolve with experience. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

PubMed Central

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

Cortical Development and Neuroplasticity in Auditory Neuropathy Spectrum Disorder

PubMed Central

Sharma, Anu; Cardon, Garrett

2015-01-01

Cortical development is dependent to a large extent on stimulus-driven input. Auditory Neuropathy Spectrum Disorder (ANSD) is a recently described form of hearing impairment where neural dys-synchrony is the predominant characteristic. Children with ANSD provide a unique platform to examine the effects of asynchronous and degraded afferent stimulation on cortical auditory neuroplasticity and behavioral processing of sound. In this review, we describe patterns of auditory cortical maturation in children with ANSD. The disruption of cortical maturation that leads to these various patterns includes high levels of intra-individual cortical variability and deficits in cortical phase synchronization of oscillatory neural responses. These neurodevelopmental changes, which are constrained by sensitive periods for central auditory maturation, are correlated with behavioral outcomes for children with ANSD. Overall, we hypothesize that patterns of cortical development in children with ANSD appear to be markers of the severity of the underlying neural dys-synchrony, providing prognostic indicators of success of clinical intervention with amplification and/or electrical stimulation. PMID:26070426

Emergence of an abstract categorical code enabling the discrimination of temporally structured tactile stimuli

PubMed Central

Rossi-Pool, Román; Salinas, Emilio; Zainos, Antonio; Alvarez, Manuel; Vergara, José; Parga, Néstor; Romo, Ranulfo

2016-01-01

The problem of neural coding in perceptual decision making revolves around two fundamental questions: (i) How are the neural representations of sensory stimuli related to perception, and (ii) what attributes of these neural responses are relevant for downstream networks, and how do they influence decision making? We studied these two questions by recording neurons in primary somatosensory (S1) and dorsal premotor (DPC) cortex while trained monkeys reported whether the temporal pattern structure of two sequential vibrotactile stimuli (of equal mean frequency) was the same or different. We found that S1 neurons coded the temporal patterns in a literal way and only during the stimulation periods and did not reflect the monkeys’ decisions. In contrast, DPC neurons coded the stimulus patterns as broader categories and signaled them during the working memory, comparison, and decision periods. These results show that the initial sensory representation is transformed into an intermediate, more abstract categorical code that combines past and present information to ultimately generate a perceptually informed choice. PMID:27872293

The Neural Representation of Consonant-Vowel Transitions in Adults Who Wear Hearing Aids

PubMed Central

Tremblay, Kelly L.; Kalstein, Laura; Billings, Cuttis J.; Souza, Pamela E.

2006-01-01

Hearing aids help compensate for disorders of the ear by amplifying sound; however, their effectiveness also depends on the central auditory system's ability to represent and integrate spectral and temporal information delivered by the hearing aid. The authors report that the neural detection of time-varying acoustic cues contained in speech can be recorded in adult hearing aid users using the acoustic change complex (ACC). Seven adults (50–76 years) with mild to severe sensorineural hearing participated in the study. When presented with 2 identifiable consonant-vowel (CV) syllables (“shee” and “see”), the neural detection of CV transitions (as indicated by the presence of a P1-N1-P2 response) was different for each speech sound. More specifically, the latency of the evoked neural response coincided in time with the onset of the vowel, similar to the latency patterns the authors previously reported in normal-hearing listeners. PMID:16959736

Appearance Matters: Neural Correlates of Food Choice and Packaging Aesthetics

PubMed Central

Van der Laan, Laura N.; De Ridder, Denise T. D.; Viergever, Max A.; Smeets, Paul A. M.

2012-01-01

Neuro-imaging holds great potential for predicting choice behavior from brain responses. In this study we used both traditional mass-univariate and state-of-the-art multivariate pattern analysis to establish which brain regions respond to preferred packages and to what extent neural activation patterns can predict realistic low-involvement consumer choices. More specifically, this was assessed in the context of package-induced binary food choices. Mass-univariate analyses showed that several regions, among which the bilateral striatum, were more strongly activated in response to preferred food packages. Food choices could be predicted with an accuracy of up to 61.2% by activation patterns in brain regions previously found to be involved in healthy food choices (superior frontal gyrus) and visual processing (middle occipital gyrus). In conclusion, this study shows that mass-univariate analysis can detect small package-induced differences in product preference and that MVPA can successfully predict realistic low-involvement consumer choices from functional MRI data. PMID:22848586

Auditory Brainstem Responses from Children Three Months to Three Years of Age: Normal Patterns of Response II.

ERIC Educational Resources Information Center

Gorga, Michael P.; And Others

1989-01-01

Auditory brainstem responses (ABR) were measured in 535 children from 3 months to 3 years of age. Results suggested that changes in wave V latency with age are due to central (neural) factors and that age-appropriate norms should be used in evaluations of ABR latencies in children. (Author/DB)

Patterns of brain reorganization subsequent to left fusiform damage: fMRI evidence from visual processing of words and pseudowords, faces and objects.

PubMed

Tsapkini, Kyrana; Vindiola, Manuel; Rapp, Brenda

2011-04-01

Little is known about the neural reorganization that takes place subsequent to lesions that affect orthographic processing (reading and/or spelling). We report on an fMRI investigation of an individual with a left mid-fusiform resection that affected both reading and spelling (Tsapkini & Rapp, 2010). To investigate possible patterns of functional reorganization, we compared the behavioral and neural activation patterns of this individual with those of a group of control participants for the tasks of silent reading of words and pseudowords and the passive viewing of faces and objects, all tasks that typically recruit the inferior temporal lobes. This comparison was carried out with methods that included a novel application of Mahalanobis distance statistics, and revealed: (1) normal behavioral and neural responses for face and object processing, (2) evidence of neural reorganization bilaterally in the posterior fusiform that supported normal performance in pseudoword reading and which contributed to word reading (3) evidence of abnormal recruitment of the bilateral anterior temporal lobes indicating compensatory (albeit insufficient) recruitment of mechanisms for circumventing the word reading deficit. Copyright © 2010 Elsevier Inc. All rights reserved.

Neural Response to Reward as a Predictor of Rise in Depressive Symptoms in Adolescence

PubMed Central

Morgan, Judith K.; Olino, Thomas M.; McMakin, Dana L.; Ryan, Neal D.; Forbes, Erika E.

2012-01-01

Adolescence is a developmental period characterized by significant increases in the onset of depression, but also by increases in depressive symptoms, even among psychiatrically healthy youth. Disrupted reward function has been postulated as a critical factor in the development of depression, but it is still unclear which adolescents are particularly at risk for rising depressive symptoms. We provide a conceptual stance on gender, pubertal development, and reward type as potential moderators of the association between neural response to reward and rises in depressive symptoms. In addition, we describe preliminary findings that support claims of this conceptual stance. We propose that (1) status-related rewards may be particularly salient for eliciting neural response relevant to depressive symptoms in boys, whereas social rewards may be more salient for eliciting neural response relevant to depressive symptoms in girls and (2) the pattern of reduced striatal response and enhanced medial prefrontal response to reward may be particularly predictive of depressive symptoms in pubertal adolescents. We found that greater vmPFC activation when winning rewards predicted greater increases in depressive symptoms over two years, for boys only, and less striatal activation when anticipating rewards predicted greater increases in depressive symptoms over two years, for adolescents in mid to late pubertal stages but not those in pre to early puberty. We also propose directions for future studies, including the investigation of social vs. monetary reward directly and the longitudinal assessment of parallel changes in pubertal development, neural response to reward, and depressive symptoms. PMID:22521464

The neural response in short-term visual recognition memory for perceptual conjunctions.

PubMed

Elliott, R; Dolan, R J

1998-01-01

Short-term visual memory has been widely studied in humans and animals using delayed matching paradigms. The present study used positron emission tomography (PET) to determine the neural substrates of delayed matching to sample for complex abstract patterns over a 5-s delay. More specifically, the study assessed any differential neural response associated with remembering individual perceptual properties (color only and shape only) compared to conjunction between these properties. Significant activations associated with short-term visual memory (all memory conditions compared to perceptuomotor control) were observed in extrastriate cortex, medial and lateral parietal cortex, anterior cingulate, inferior frontal gyrus, and the thalamus. Significant deactivations were observed throughout the temporal cortex. Although the requirement to remember color compared to shape was associated with subtly different patterns of blood flow, the requirement to remember perceptual conjunctions between these features was not associated with additional specific activations. These data suggest that visual memory over a delay of the order of 5 s is mainly dependent on posterior perceptual regions of the cortex, with the exact regions depending on the perceptual aspect of the stimuli to be remembered.

Cognon Neural Model Software Verification and Hardware Implementation Design

NASA Astrophysics Data System (ADS)

Haro Negre, Pau

Little is known yet about how the brain can recognize arbitrary sensory patterns within milliseconds using neural spikes to communicate information between neurons. In a typical brain there are several layers of neurons, with each neuron axon connecting to ˜104 synapses of neurons in an adjacent layer. The information necessary for cognition is contained in theses synapses, which strengthen during the learning phase in response to newly presented spike patterns. Continuing on the model proposed in "Models for Neural Spike Computation and Cognition" by David H. Staelin and Carl H. Staelin, this study seeks to understand cognition from an information theoretic perspective and develop potential models for artificial implementation of cognition based on neuronal models. To do so we focus on the mathematical properties and limitations of spike-based cognition consistent with existing neurological observations. We validate the cognon model through software simulation and develop concepts for an optical hardware implementation of a network of artificial neural cognons.

Enhanced visual processing contributes to matrix reasoning in autism

PubMed Central

Soulières, Isabelle; Dawson, Michelle; Samson, Fabienne; Barbeau, Elise B.; Sahyoun, Cherif; Strangman, Gary E.; Zeffiro, Thomas A.; Mottron, Laurent

2009-01-01

Recent behavioral investigations have revealed that autistics perform more proficiently on Raven's Standard Progressive Matrices (RSPM) than would be predicted by their Wechsler intelligence scores. A widely-used test of fluid reasoning and intelligence, the RSPM assays abilities to flexibly infer rules, manage goal hierarchies, and perform high-level abstractions. The neural substrates for these abilities are known to encompass a large frontoparietal network, with different processing models placing variable emphasis on the specific roles of the prefrontal or posterior regions. We used functional magnetic resonance imaging to explore the neural bases of autistics' RSPM problem solving. Fifteen autistic and eighteen non-autistic participants, matched on age, sex, manual preference and Wechsler IQ, completed 60 self-paced randomly-ordered RSPM items along with a visually similar 60-item pattern matching comparison task. Accuracy and response times did not differ between groups in the pattern matching task. In the RSPM task, autistics performed with similar accuracy, but with shorter response times, compared to their non-autistic controls. In both the entire sample and a subsample of participants additionally matched on RSPM performance to control for potential response time confounds, neural activity was similar in both groups for the pattern matching task. However, for the RSPM task, autistics displayed relatively increased task-related activity in extrastriate areas (BA18), and decreased activity in the lateral prefrontal cortex (BA9) and the medial posterior parietal cortex (BA7). Visual processing mechanisms may therefore play a more prominent role in reasoning in autistics. PMID:19530215

Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains.

PubMed

Onken, Arno; Liu, Jian K; Karunasekara, P P Chamanthi R; Delis, Ioannis; Gollisch, Tim; Panzeri, Stefano

2016-11-01

Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations), in their temporal dimension (temporal neural response variations), or in their combination (temporally coordinated neural population firing). Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together), temporal firing patterns (temporal activation of these groups of neurons) and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial). We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine-scale image features, and supplied almost as much information about coarse natural image features as firing rates. Together, these results highlight the importance of spike timing, and particularly of first-spike latencies, in retinal coding.

Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains

PubMed Central

Onken, Arno; Liu, Jian K.; Karunasekara, P. P. Chamanthi R.; Delis, Ioannis; Gollisch, Tim; Panzeri, Stefano

2016-01-01

Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations), in their temporal dimension (temporal neural response variations), or in their combination (temporally coordinated neural population firing). Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together), temporal firing patterns (temporal activation of these groups of neurons) and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial). We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine-scale image features, and supplied almost as much information about coarse natural image features as firing rates. Together, these results highlight the importance of spike timing, and particularly of first-spike latencies, in retinal coding. PMID:27814363

The shift from a response strategy to object-in-place strategy during learning is accompanied by a matching shift in neural firing correlates in the hippocampus.

PubMed

Lee, Inah; Kim, Jangjin

2010-08-01

Hippocampal-dependent tasks often involve specific associations among stimuli (including egocentric information), and such tasks are therefore prone to interference from irrelevant task strategies before a correct strategy is found. Using an object-place paired-associate task, we investigated changes in neural firing patterns in the hippocampus in association with a shift in strategy during learning. We used an object-place paired-associate task in which a pair of objects was presented in two different arms of a radial maze. Each object was associated with reward only in one of the arms, thus requiring the rats to consider both object identity and its location in the maze. Hippocampal neurons recorded in CA1 displayed a dynamic transition in their firing patterns during the acquisition of the task across days, and this corresponded to a shift in strategy manifested in behavioral data. Specifically, before the rats learned the task, they chose an object that maintained a particular egocentric relationship with their body (response strategy) irrespective of the object identity. However, as the animal acquired the task, it chose an object according to both its identity and the associated location in the maze (object-in-place strategy). We report that CA1 neurons in the hippocampus changed their prospective firing correlates according to the dominant strategy (i.e., response versus object-in-place strategy) employed at a given stage of learning. The results suggest that neural firing pattern in the hippocampus is heavily influenced by the task demand hypothesized by the animal and the firing pattern changes flexibly as the perceived task demand changes.

The neural dynamics of task context in free recall.

PubMed

Polyn, Sean M; Kragel, James E; Morton, Neal W; McCluey, Joshua D; Cohen, Zachary D

2012-03-01

Multivariate pattern analysis (MVPA) is a powerful tool for relating theories of cognitive function to the neural dynamics observed while people engage in cognitive tasks. Here, we use the Context Maintenance and Retrieval model of free recall (CMR; Polyn et al., 2009a) to interpret variability in the strength of task-specific patterns of distributed neural activity as participants study and recall lists of words. The CMR model describes how temporal and source-related (here, encoding task) information combine in a contextual representation that is responsible for guiding memory search. Each studied word in the free-recall paradigm is associated with one of two encoding tasks (size and animacy) that have distinct neural representations during encoding. We find evidence for the context retrieval hypothesis central to the CMR model: Task-specific patterns of neural activity are reactivated during memory search, as the participant recalls an item previously associated with a particular task. Furthermore, we find that the fidelity of these task representations during study is related to task-shifting, the serial position of the studied item, and variability in the magnitude of the recency effect across participants. The CMR model suggests that these effects may be related to a central parameter of the model that controls the rate that an internal contextual representation integrates information from the surrounding environment. Copyright © 2011 Elsevier Ltd. All rights reserved.

Underlying neural alpha frequency patterns associated with intra-hemispheric inhibition during an interhemispheric transfer task.

PubMed

Simon-Dack, Stephanie L; Kraus, Brian; Walter, Zachary; Smith, Shelby; Cadle, Chelsea

2018-05-18

Interhemispheric transfer measured via differences in right- or left-handed motoric responses to lateralized visual stimuli, known as the crossed-uncrossed difference (CUD), is one way of identifying patterns of processing that are vital for understanding the transfer of neural signals. Examination of interhemispheric transfer by means of the CUD is not entirely explained by simple measures of response time. Multiple processes contribute to wide variability observed in CUD reaction times. Prior research has suggested that intra-hemispheric inhibitory processes may be involved in regulation of speed of transfer. Our study examined electroencephalography recordings and time-locked alpha frequency activity while 18 participants responded to lateralized targets during performance of the Poffenberger Paradigm. Our results suggest that there are alpha frequency differences at fronto-central lateral electrodes based on target, hand-of-response, and receiving hemisphere. These findings suggest that early motoric inhibitory mechanisms may help explain the wide range of variability typically seen with the CUD. Copyright © 2018 Elsevier B.V. All rights reserved.

4-dimensional functional profiling in the convulsant-treated larval zebrafish brain.

PubMed

Winter, Matthew J; Windell, Dylan; Metz, Jeremy; Matthews, Peter; Pinion, Joe; Brown, Jonathan T; Hetheridge, Malcolm J; Ball, Jonathan S; Owen, Stewart F; Redfern, Will S; Moger, Julian; Randall, Andrew D; Tyler, Charles R

2017-07-26

Functional neuroimaging, using genetically-encoded Ca 2+ sensors in larval zebrafish, offers a powerful combination of high spatiotemporal resolution and higher vertebrate relevance for quantitative neuropharmacological profiling. Here we use zebrafish larvae with pan-neuronal expression of GCaMP6s, combined with light sheet microscopy and a novel image processing pipeline, for the 4D profiling of chemoconvulsant action in multiple brain regions. In untreated larvae, regions associated with autonomic functionality, sensory processing and stress-responsiveness, consistently exhibited elevated spontaneous activity. The application of drugs targeting different convulsant mechanisms (4-Aminopyridine, Pentylenetetrazole, Pilocarpine and Strychnine) resulted in distinct spatiotemporal patterns of activity. These activity patterns showed some interesting parallels with what is known of the distribution of their respective molecular targets, but crucially also revealed system-wide neural circuit responses to stimulation or suppression. Drug concentration-response curves of neural activity were identified in a number of anatomically-defined zebrafish brain regions, and in vivo larval electrophysiology, also conducted in 4dpf larvae, provided additional measures of neural activity. Our quantification of network-wide chemoconvulsant drug activity in the whole zebrafish brain illustrates the power of this approach for neuropharmacological profiling in applications ranging from accelerating studies of drug safety and efficacy, to identifying pharmacologically-altered networks in zebrafish models of human neurological disorders.

The functional neuroanatomy of maternal love: mother's response to infant's attachment behaviors.

PubMed

Noriuchi, Madoka; Kikuchi, Yoshiaki; Senoo, Atsushi

2008-02-15

Maternal love, which may be the core of maternal behavior, is essential for the mother-infant attachment relationship and is important for the infant's development and mental health. However, little has been known about these neural mechanisms in human mothers. We examined patterns of maternal brain activation in response to infant cues using video clips. We performed functional magnetic resonance imaging (fMRI) measurements while 13 mothers viewed video clips, with no sound, of their own infant and other infants of approximately 16 months of age who demonstrated two different attachment behaviors (smiling at the infant's mother and crying for her). We found that a limited number of the mother's brain areas were specifically involved in recognition of the mother's own infant, namely orbitofrontal cortex (OFC), periaqueductal gray, anterior insula, and dorsal and ventrolateral parts of putamen. Additionally, we found the strong and specific mother's brain response for the mother's own infant's distress. The differential neural activation pattern was found in the dorsal region of OFC, caudate nucleus, right inferior frontal gyrus, dorsomedial prefrontal cortex (PFC), anterior cingulate, posterior cingulate, thalamus, substantia nigra, posterior superior temporal sulcus, and PFC. Our results showed the highly elaborate neural mechanism mediating maternal love and diverse and complex maternal behaviors for vigilant protectiveness.

Predicting variations of perceptual performance across individuals from neural activity using pattern classifiers.

PubMed

Das, Koel; Giesbrecht, Barry; Eckstein, Miguel P

2010-07-15

Within the past decade computational approaches adopted from the field of machine learning have provided neuroscientists with powerful new tools for analyzing neural data. For instance, previous studies have applied pattern classification algorithms to electroencephalography data to predict the category of presented visual stimuli, human observer decision choices and task difficulty. Here, we quantitatively compare the ability of pattern classifiers and three ERP metrics (peak amplitude, mean amplitude, and onset latency of the face-selective N170) to predict variations across individuals' behavioral performance in a difficult perceptual task identifying images of faces and cars embedded in noise. We investigate three different pattern classifiers (Classwise Principal Component Analysis, CPCA; Linear Discriminant Analysis, LDA; and Support Vector Machine, SVM), five training methods differing in the selection of training data sets and three analyses procedures for the ERP measures. We show that all three pattern classifier algorithms surpass traditional ERP measurements in their ability to predict individual differences in performance. Although the differences across pattern classifiers were not large, the CPCA method with training data sets restricted to EEG activity for trials in which observers expressed high confidence about their decisions performed the highest at predicting perceptual performance of observers. We also show that the neural activity predicting the performance across individuals was distributed through time starting at 120ms, and unlike the face-selective ERP response, sustained for more than 400ms after stimulus presentation, indicating that both early and late components contain information correlated with observers' behavioral performance. Together, our results further demonstrate the potential of pattern classifiers compared to more traditional ERP techniques as an analysis tool for modeling spatiotemporal dynamics of the human brain and relating neural activity to behavior. Copyright 2010 Elsevier Inc. All rights reserved.

Dynamic Trial-by-Trial Recoding of Task-Set Representations in the Frontoparietal Cortex Mediates Behavioral Flexibility

PubMed Central

Qiao, Lei; Zhang, Lijie

2017-01-01

Cognitive flexibility forms the core of the extraordinary ability of humans to adapt, but the precise neural mechanisms underlying our ability to nimbly shift between task sets remain poorly understood. Recent functional magnetic resonance imaging (fMRI) studies employing multivoxel pattern analysis (MVPA) have shown that a currently relevant task set can be decoded from activity patterns in the frontoparietal cortex, but whether these regions support the dynamic transformation of task sets from trial to trial is not clear. Here, we combined a cued task-switching protocol with human (both sexes) fMRI, and harnessed representational similarity analysis (RSA) to facilitate a novel assessment of trial-by-trial changes in neural task-set representations. We first used MVPA to define task-sensitive frontoparietal and visual regions and found that neural task-set representations on switch trials are less stably encoded than on repeat trials. We then exploited RSA to show that the neural representational pattern dissimilarity across consecutive trials is greater for switch trials than for repeat trials, and that the degree of this pattern dissimilarity predicts behavior. Moreover, the overall neural pattern of representational dissimilarities followed from the assumption that repeating sets, compared with switching sets, results in stronger neural task representations. Finally, when moving from cue to target phase within a trial, pattern dissimilarities tracked the transformation from previous-trial task representations to the currently relevant set. These results provide neural evidence for the longstanding assumptions of an effortful task-set reconfiguration process hampered by task-set inertia, and they demonstrate that frontoparietal and stimulus processing regions support “dynamic adaptive coding,” flexibly representing changing task sets in a trial-by-trial fashion. SIGNIFICANCE STATEMENT Humans can fluently switch between different tasks, reflecting an ability to dynamically configure “task sets,” rule representations that link stimuli to appropriate responses. Recent studies show that neural signals in frontal and parietal brain regions can tell us which of two tasks a person is currently performing. However, it is not known whether these regions are also involved in dynamically reconfiguring task-set representations when switching between tasks. Here we measured human brain activity during task switching and tracked the similarity of neural task-set representations from trial to trial. We show that frontal and parietal brain regions flexibly recode changing task sets in a trial-by-trial fashion, and that task-set similarity over consecutive trials predicts behavior. PMID:28972126

Maximum entropy models as a tool for building precise neural controls.

PubMed

Savin, Cristina; Tkačik, Gašper

2017-10-01

Neural responses are highly structured, with population activity restricted to a small subset of the astronomical range of possible activity patterns. Characterizing these statistical regularities is important for understanding circuit computation, but challenging in practice. Here we review recent approaches based on the maximum entropy principle used for quantifying collective behavior in neural activity. We highlight recent models that capture population-level statistics of neural data, yielding insights into the organization of the neural code and its biological substrate. Furthermore, the MaxEnt framework provides a general recipe for constructing surrogate ensembles that preserve aspects of the data, but are otherwise maximally unstructured. This idea can be used to generate a hierarchy of controls against which rigorous statistical tests are possible. Copyright © 2017 Elsevier Ltd. All rights reserved.

Engaged listeners: shared neural processing of powerful political speeches

PubMed Central

Häcker, Frank E. K.; Honey, Christopher J.; Hasson, Uri

2015-01-01

Powerful speeches can captivate audiences, whereas weaker speeches fail to engage their listeners. What is happening in the brains of a captivated audience? Here, we assess audience-wide functional brain dynamics during listening to speeches of varying rhetorical quality. The speeches were given by German politicians and evaluated as rhetorically powerful or weak. Listening to each of the speeches induced similar neural response time courses, as measured by inter-subject correlation analysis, in widespread brain regions involved in spoken language processing. Crucially, alignment of the time course across listeners was stronger for rhetorically powerful speeches, especially for bilateral regions of the superior temporal gyri and medial prefrontal cortex. Thus, during powerful speeches, listeners as a group are more coupled to each other, suggesting that powerful speeches are more potent in taking control of the listeners’ brain responses. Weaker speeches were processed more heterogeneously, although they still prompted substantially correlated responses. These patterns of coupled neural responses bear resemblance to metaphors of resonance, which are often invoked in discussions of speech impact, and contribute to the literature on auditory attention under natural circumstances. Overall, this approach opens up possibilities for research on the neural mechanisms mediating the reception of entertaining or persuasive messages. PMID:25653012

The Emerging Role of Epigenetics in Stroke

PubMed Central

Qureshi, Irfan A.; Mehler, Mark F.

2013-01-01

The transplantation of exogenous stem cells and the activation of endogenous neural stem and progenitor cells (NSPCs) are promising treatments for stroke. These cells can modulate intrinsic responses to ischemic injury and may even integrate directly into damaged neural networks. However, the neuroprotective and neural regenerative effects that can be mediated by these cells are limited and may even be deleterious. Epigenetic reprogramming represents a novel strategy for enhancing the intrinsic potential of the brain to protect and repair itself by modulating pathologic neural gene expression and promoting the recapitulation of seminal neural developmental processes. In fact, recent evidence suggests that emerging epigenetic mechanisms are critical for orchestrating nearly every aspect of neural development and homeostasis, including brain patterning, neural stem cell maintenance, neurogenesis and gliogenesis, neural subtype specification, and synaptic and neural network connectivity and plasticity. In this review, we survey the therapeutic potential of exogenous stem cells and endogenous NSPCs and highlight innovative technological approaches for designing, developing, and delivering epigenetic therapies for targeted reprogramming of endogenous pools of NSPCs, neural cells at risk, and dysfunctional neural networks to rescue and restore neurologic function in the ischemic brain. PMID:21403016

Neural Activity in the Ventral Pallidum Encodes Variation in the Incentive Value of a Reward Cue.

PubMed

Ahrens, Allison M; Meyer, Paul J; Ferguson, Lindsay M; Robinson, Terry E; Aldridge, J Wayne

2016-07-27

There is considerable individual variation in the extent to which reward cues are attributed with incentive salience. For example, a food-predictive conditioned stimulus (CS; an illuminated lever) becomes attractive, eliciting approach toward it only in some rats ("sign trackers," STs), whereas others ("goal trackers," GTs) approach the food cup during the CS period. The purpose of this study was to determine how individual differences in Pavlovian approach responses are represented in neural firing patterns in the major output structure of the mesolimbic system, the ventral pallidum (VP). Single-unit in vivo electrophysiology was used to record neural activity in the caudal VP during the performance of ST and GT conditioned responses. All rats showed neural responses to both cue onset and reward delivery but, during the CS period, STs showed greater neural activity than GTs both in terms of the percentage of responsive neurons and the magnitude of the change in neural activity. Furthermore, neural activity was positively correlated with the degree of attraction to the cue. Given that the CS had equal predictive value in STs and GTs, we conclude that neural activity in the VP largely reflects the degree to which the CS was attributed with incentive salience. Cues associated with reward can acquire motivational properties (i.e., incentive salience) that cause them to have a powerful influence on desire and motivated behavior. There are individual differences in sensitivity to reward-paired cues, with some individuals attaching greater motivational value to cues than others. Here, we investigated the neural activity associated with these individual differences in incentive salience. We found that cue-evoked neural firing in the ventral pallidum (VP) reflected the strength of incentive motivation, with the greatest neural responses occurring in individuals that demonstrated the strongest attraction to the cue. This suggests that the VP plays an important role in the process by which cues gain control over motivation and behavior. Copyright © 2016 the authors 0270-6474/16/367957-14$15.00/0.

Brain machine interfaces combining microelectrode arrays with nanostructured optical biochemical sensors

NASA Astrophysics Data System (ADS)

Hajj-Hassan, Mohamad; Gonzalez, Timothy; Ghafer-Zadeh, Ebrahim; Chodavarapu, Vamsy; Musallam, Sam; Andrews, Mark

2009-02-01

Neural microelectrodes are an important component of neural prosthetic systems which assist paralyzed patients by allowing them to operate computers or robots using their neural activity. These microelectrodes are also used in clinical settings to localize the locus of seizure initiation in epilepsy or to stimulate sub-cortical structures in patients with Parkinson's disease. In neural prosthetic systems, implanted microelectrodes record the electrical potential generated by specific thoughts and relay the signals to algorithms trained to interpret these thoughts. In this paper, we describe novel elongated multi-site neural electrodes that can record electrical signals and specific neural biomarkers and that can reach depths greater than 8mm in the sulcus of non-human primates (monkeys). We hypothesize that additional signals recorded by the multimodal probes will increase the information yield when compared to standard probes that record just electropotentials. We describe integration of optical biochemical sensors with neural microelectrodes. The sensors are made using sol-gel derived xerogel thin films that encapsulate specific biomarker responsive luminophores in their nanostructured pores. The desired neural biomarkers are O2, pH, K+, and Na+ ions. As a prototype, we demonstrate direct-write patterning to create oxygen-responsive xerogel waveguide structures on the neural microelectrodes. The recording of neural biomarkers along with electrical activity could help the development of intelligent and more userfriendly neural prosthesis/brain machine interfaces as well as aid in providing answers to complex brain diseases and disorders.

A Double Dissociation between Anterior and Posterior Superior Temporal Gyrus for Processing Audiovisual Speech Demonstrated by Electrocorticography.

PubMed

Ozker, Muge; Schepers, Inga M; Magnotti, John F; Yoshor, Daniel; Beauchamp, Michael S

2017-06-01

Human speech can be comprehended using only auditory information from the talker's voice. However, comprehension is improved if the talker's face is visible, especially if the auditory information is degraded as occurs in noisy environments or with hearing loss. We explored the neural substrates of audiovisual speech perception using electrocorticography, direct recording of neural activity using electrodes implanted on the cortical surface. We observed a double dissociation in the responses to audiovisual speech with clear and noisy auditory component within the superior temporal gyrus (STG), a region long known to be important for speech perception. Anterior STG showed greater neural activity to audiovisual speech with clear auditory component, whereas posterior STG showed similar or greater neural activity to audiovisual speech in which the speech was replaced with speech-like noise. A distinct border between the two response patterns was observed, demarcated by a landmark corresponding to the posterior margin of Heschl's gyrus. To further investigate the computational roles of both regions, we considered Bayesian models of multisensory integration, which predict that combining the independent sources of information available from different modalities should reduce variability in the neural responses. We tested this prediction by measuring the variability of the neural responses to single audiovisual words. Posterior STG showed smaller variability than anterior STG during presentation of audiovisual speech with noisy auditory component. Taken together, these results suggest that posterior STG but not anterior STG is important for multisensory integration of noisy auditory and visual speech.

Low-intensity focused ultrasound alters the latency and spatial patterns of sensory-evoked cortical responses in vivo

NASA Astrophysics Data System (ADS)

Fisher, Jonathan A. N.; Gumenchuk, Iryna

2018-06-01

Objective. The use of transcranial, low intensity focused ultrasound (FUS) is an emerging neuromodulation technology that shows promise for both therapeutic and research applications. Among many, one of the most exciting applications is the use of FUS to rehabilitate or augment human sensory capabilities. While there is compelling empirical evidence demonstrating this capability, basic questions regarding the spatiotemporal extent of the modulatory effects remain. Our objective was to assess the basic, yet often overlooked hypothesis that FUS in fact alters sensory-evoked neural activity within the region of the cerebral cortex at the beam’s focus. Approach. To address this knowledge gap, we developed an approach to optically interrogate patterns of neural activity in the cortex directly at the acoustic focus, in vivo. Implementing simultaneous wide-field optical imaging and FUS stimulation in mice, our experiments probed somatosensory-evoked electrical activity through the use of voltage sensitive dyes (VSDs) and, in transgenic mice expressing GCaMP6f, monitored associated Ca2+ responses. Main results. Our results demonstrate that low-intensity FUS alters both the kinetics and spatial patterns of neural activity in primary somatosensory cortex at the acoustic focus. When preceded by 1 s of pulsed ultrasound at intensities below 1 W cm‑2 (I sppa), the onset of sensory-evoked cortical responses occurred 3.0  ±  0.7 ms earlier and altered the surface spatial morphology of Ca2+ responses. Significance. These findings support the heretofore unconfirmed assumption that FUS-induced sensory modulation reflects, at least in part, altered reactivity in primary sensory cortex at the site of sonication. The findings are significant given the interest in using FUS to target and alter spatial aspects of sensory receptive fields on the cerebral cortex.

Modality-specific spectral dynamics in response to visual and tactile sequential shape information processing tasks: An MEG study using multivariate pattern classification analysis.

PubMed

Gohel, Bakul; Lee, Peter; Jeong, Yong

2016-08-01

Brain regions that respond to more than one sensory modality are characterized as multisensory regions. Studies on the processing of shape or object information have revealed recruitment of the lateral occipital cortex, posterior parietal cortex, and other regions regardless of input sensory modalities. However, it remains unknown whether such regions show similar (modality-invariant) or different (modality-specific) neural oscillatory dynamics, as recorded using magnetoencephalography (MEG), in response to identical shape information processing tasks delivered to different sensory modalities. Modality-invariant or modality-specific neural oscillatory dynamics indirectly suggest modality-independent or modality-dependent participation of particular brain regions, respectively. Therefore, this study investigated the modality-specificity of neural oscillatory dynamics in the form of spectral power modulation patterns in response to visual and tactile sequential shape-processing tasks that are well-matched in terms of speed and content between the sensory modalities. Task-related changes in spectral power modulation and differences in spectral power modulation between sensory modalities were investigated at source-space (voxel) level, using a multivariate pattern classification (MVPC) approach. Additionally, whole analyses were extended from the voxel level to the independent-component level to take account of signal leakage effects caused by inverse solution. The modality-specific spectral dynamics in multisensory and higher-order brain regions, such as the lateral occipital cortex, posterior parietal cortex, inferior temporal cortex, and other brain regions, showed task-related modulation in response to both sensory modalities. This suggests modality-dependency of such brain regions on the input sensory modality for sequential shape-information processing. Copyright © 2016 Elsevier B.V. All rights reserved.

Low-intensity focused ultrasound alters the latency and spatial patterns of sensory-evoked cortical responses in vivo.

PubMed

Fisher, Jonathan A N; Gumenchuk, Iryna

2018-06-01

The use of transcranial, low intensity focused ultrasound (FUS) is an emerging neuromodulation technology that shows promise for both therapeutic and research applications. Among many, one of the most exciting applications is the use of FUS to rehabilitate or augment human sensory capabilities. While there is compelling empirical evidence demonstrating this capability, basic questions regarding the spatiotemporal extent of the modulatory effects remain. Our objective was to assess the basic, yet often overlooked hypothesis that FUS in fact alters sensory-evoked neural activity within the region of the cerebral cortex at the beam's focus. To address this knowledge gap, we developed an approach to optically interrogate patterns of neural activity in the cortex directly at the acoustic focus, in vivo. Implementing simultaneous wide-field optical imaging and FUS stimulation in mice, our experiments probed somatosensory-evoked electrical activity through the use of voltage sensitive dyes (VSDs) and, in transgenic mice expressing GCaMP6f, monitored associated Ca 2+ responses. Our results demonstrate that low-intensity FUS alters both the kinetics and spatial patterns of neural activity in primary somatosensory cortex at the acoustic focus. When preceded by 1 s of pulsed ultrasound at intensities below 1 W cm -2 (I sppa ), the onset of sensory-evoked cortical responses occurred 3.0  ±  0.7 ms earlier and altered the surface spatial morphology of Ca 2+ responses. These findings support the heretofore unconfirmed assumption that FUS-induced sensory modulation reflects, at least in part, altered reactivity in primary sensory cortex at the site of sonication. The findings are significant given the interest in using FUS to target and alter spatial aspects of sensory receptive fields on the cerebral cortex.

Affective neural response to restricted interests in autism spectrum disorders.

PubMed

Cascio, Carissa J; Foss-Feig, Jennifer H; Heacock, Jessica; Schauder, Kimberly B; Loring, Whitney A; Rogers, Baxter P; Pryweller, Jennifer R; Newsom, Cassandra R; Cockhren, Jurnell; Cao, Aize; Bolton, Scott

2014-01-01

Restricted interests are a class of repetitive behavior in autism spectrum disorders (ASD) whose intensity and narrow focus often contribute to significant interference with daily functioning. While numerous neuroimaging studies have investigated executive circuits as putative neural substrates of repetitive behavior, recent work implicates affective neural circuits in restricted interests. We sought to explore the role of affective neural circuits and determine how restricted interests are distinguished from hobbies or interests in typical development. We compared a group of children with ASD to a typically developing (TD) group of children with strong interests or hobbies, employing parent report, an operant behavioral task, and functional imaging with personalized stimuli based on individual interests. While performance on the operant task was similar between the two groups, parent report of intensity and interference of interests was significantly higher in the ASD group. Both the ASD and TD groups showed increased BOLD response in widespread affective neural regions to the pictures of their own interest. When viewing pictures of other children's interests, the TD group showed a similar pattern, whereas BOLD response in the ASD group was much more limited. Increased BOLD response in the insula and anterior cingulate cortex distinguished the ASD from the TD group, and parent report of the intensity and interference with daily life of the child's restricted interest predicted insula response. While affective neural network response and operant behavior are comparable in typical and restricted interests, the narrowness of focus that clinically distinguishes restricted interests in ASD is reflected in more interference in daily life and aberrantly enhanced insula and anterior cingulate response to individuals' own interests in the ASD group. These results further support the involvement of affective neural networks in repetitive behaviors in ASD. © 2013 The Authors. Journal of Child Psychology and Psychiatry © 2013 Association for Child and Adolescent Mental Health.

Concurrent encoding of frequency and amplitude modulation in human auditory cortex: encoding transition.

PubMed

Luo, Huan; Wang, Yadong; Poeppel, David; Simon, Jonathan Z

2007-12-01

Complex natural sounds (e.g., animal vocalizations or speech) can be characterized by specific spectrotemporal patterns the components of which change in both frequency (FM) and amplitude (AM). The neural coding of AM and FM has been widely studied in humans and animals but typically with either pure AM or pure FM stimuli. The neural mechanisms employed to perceptually unify AM and FM acoustic features remain unclear. Using stimuli with simultaneous sinusoidal AM (at rate f(AM) = 37 Hz) and FM (with varying rates f(FM)), magnetoencephalography (MEG) is used to investigate the elicited auditory steady-state response (aSSR) at relevant frequencies (f(AM), f(FM), f(AM) + f(FM)). Previous work demonstrated that for sounds with slower FM dynamics (f(FM) < 5 Hz), the phase of the aSSR at f(AM) tracked the FM; in other words, AM and FM features were co-tracked and co-represented by "phase modulation" encoding. This study explores the neural coding mechanism for stimuli with faster FM dynamics (< or =30 Hz), demonstrating that at faster rates (f(FM) > 5 Hz), there is a transition from pure phase modulation encoding to a single-upper-sideband (SSB) response (at frequency f(AM) + f(FM)) pattern. We propose that this unexpected SSB response can be explained by the additional involvement of subsidiary AM encoding responses simultaneously to, and in quadrature with, the ongoing phase modulation. These results, using MEG to reveal a possible neural encoding of specific acoustic properties, demonstrate more generally that physiological tests of encoding hypotheses can be performed noninvasively on human subjects, complementing invasive, single-unit recordings in animals.

Time of Day Differences in Neural Reward Functioning in Healthy Young Men.

PubMed

Byrne, Jamie E M; Hughes, Matthew E; Rossell, Susan L; Johnson, Sheri L; Murray, Greg

2017-09-13

Reward function appears to be modulated by the circadian system, but little is known about the neural basis of this interaction. Previous research suggests that the neural reward response may be different in the afternoon; however, the direction of this effect is contentious. Reward response may follow the diurnal rhythm in self-reported positive affect, peaking in the early afternoon. An alternative is that daily reward response represents a type of prediction error, with neural reward activation relatively high at times of day when rewards are unexpected (i.e., early and late in the day). The present study measured neural reward activation in the context of a validated reward task at 10.00 h, 14.00 h, and 19.00 h in healthy human males. A region of interest BOLD fMRI protocol was used to investigate the diurnal waveform of activation in reward-related brain regions. Multilevel modeling found, as expected, a highly significant quadratic time-of-day effect focusing on the left putamen ( p < 0.001). Consistent with the "prediction error" hypothesis, activation was significantly higher at 10.00 h and 19.00 h compared with 14.00 h. It is provisionally concluded that the putamen may be particularly important in endogenous priming of reward motivation at different times of day, with the pattern of activation consistent with circadian-modulated reward expectancies in neural pathways (i.e., greater activation to reward stimuli at unexpected times of day). This study encourages further research into circadian modulation of reward and underscores the methodological importance of accounting for time of day in fMRI protocols. SIGNIFICANCE STATEMENT This is one of the first studies to use a repeated-measures imaging procedure to explore the diurnal rhythm of reward activation. Although self-reported reward (most often operationalized as positive affect) peaks in the afternoon, the present findings indicate that neural activation is lowest at this time. We conclude that the diurnal neural activation pattern may reflect a prediction error of the brain, where rewards at unexpected times (10.00 h and 19.00 h) elicit higher activation in reward brain regions than at expected (14.00 h) times. These data also have methodological significance, suggesting that there may be a time of day influence, which should be accounted for in neural reward studies. Copyright © 2017 the authors 0270-6474/17/378895-06$15.00/0.

Distinct but Overlapping Patterns of Response to Words and Faces in the Fusiform Gyrus.

PubMed

Harris, Richard J; Rice, Grace E; Young, Andrew W; Andrews, Timothy J

2016-07-01

Converging evidence suggests that the fusiform gyrus is involved in the processing of both faces and words. We used fMRI to investigate the extent to which the representation of words and faces in this region of the brain is based on a common neural representation. In Experiment 1, a univariate analysis revealed regions in the fusiform gyrus that were only selective for faces and other regions that were only selective for words. However, we also found regions that showed both word-selective and face-selective responses, particularly in the left hemisphere. We then used a multivariate analysis to measure the pattern of response to faces and words. Despite the overlap in regional responses, we found distinct patterns of response to both faces and words in the left and right fusiform gyrus. In Experiment 2, fMR adaptation was used to determine whether information about familiar faces and names is integrated in the fusiform gyrus. Distinct regions of the fusiform gyrus showed adaptation to either familiar faces or familiar names. However, there was no adaptation to sequences of faces and names with the same identity. Taken together, these results provide evidence for distinct, but overlapping, neural representations for words and faces in the fusiform gyrus. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Coding of sounds in the auditory system and its relevance to signal processing and coding in cochlear implants.

PubMed

Moore, Brian C J

2003-03-01

To review how the properties of sounds are "coded" in the normal auditory system and to discuss the extent to which cochlear implants can and do represent these codes. Data are taken from published studies of the response of the cochlea and auditory nerve to simple and complex stimuli, in both the normal and the electrically stimulated ear. REVIEW CONTENT: The review describes: 1) the coding in the normal auditory system of overall level (which partly determines perceived loudness), spectral shape (which partly determines perceived timbre and the identity of speech sounds), periodicity (which partly determines pitch), and sound location; 2) the role of the active mechanism in the cochlea, and particularly the fast-acting compression associated with that mechanism; 3) the neural response patterns evoked by cochlear implants; and 4) how the response patterns evoked by implants differ from those observed in the normal auditory system in response to sound. A series of specific issues is then discussed, including: 1) how to compensate for the loss of cochlear compression; 2) the effective number of independent channels in a normal ear and in cochlear implantees; 3) the importance of independence of responses across neurons; 4) the stochastic nature of normal neural responses; 5) the possible role of across-channel coincidence detection; and 6) potential benefits of binaural implantation. Current cochlear implants do not adequately reproduce several aspects of the neural coding of sound in the normal auditory system. Improved electrode arrays and coding systems may lead to improved coding and, it is hoped, to better performance.

Neural constraints on learning.

PubMed

Sadtler, Patrick T; Quick, Kristin M; Golub, Matthew D; Chase, Steven M; Ryu, Stephen I; Tyler-Kabara, Elizabeth C; Yu, Byron M; Batista, Aaron P

2014-08-28

Learning, whether motor, sensory or cognitive, requires networks of neurons to generate new activity patterns. As some behaviours are easier to learn than others, we asked if some neural activity patterns are easier to generate than others. Here we investigate whether an existing network constrains the patterns that a subset of its neurons is capable of exhibiting, and if so, what principles define this constraint. We employed a closed-loop intracortical brain-computer interface learning paradigm in which Rhesus macaques (Macaca mulatta) controlled a computer cursor by modulating neural activity patterns in the primary motor cortex. Using the brain-computer interface paradigm, we could specify and alter how neural activity mapped to cursor velocity. At the start of each session, we observed the characteristic activity patterns of the recorded neural population. The activity of a neural population can be represented in a high-dimensional space (termed the neural space), wherein each dimension corresponds to the activity of one neuron. These characteristic activity patterns comprise a low-dimensional subspace (termed the intrinsic manifold) within the neural space. The intrinsic manifold presumably reflects constraints imposed by the underlying neural circuitry. Here we show that the animals could readily learn to proficiently control the cursor using neural activity patterns that were within the intrinsic manifold. However, animals were less able to learn to proficiently control the cursor using activity patterns that were outside of the intrinsic manifold. These results suggest that the existing structure of a network can shape learning. On a timescale of hours, it seems to be difficult to learn to generate neural activity patterns that are not consistent with the existing network structure. These findings offer a network-level explanation for the observation that we are more readily able to learn new skills when they are related to the skills that we already possess.

Stimulus-dependent Maximum Entropy Models of Neural Population Codes

PubMed Central

Segev, Ronen; Schneidman, Elad

2013-01-01

Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. For large populations, direct sampling of these distributions is impossible, and so we must rely on constructing appropriate models. We show here that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. We introduce the stimulus-dependent maximum entropy (SDME) model—a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. We find that the SDME model gives a more accurate account of single cell responses and in particular significantly outperforms uncoupled models in reproducing the distributions of population codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like average surprise and information transmission in a neural population. PMID:23516339

Method and system for pattern analysis using a coarse-coded neural network

NASA Technical Reports Server (NTRS)

Spirkovska, Liljana (Inventor); Reid, Max B. (Inventor)

1994-01-01

A method and system for performing pattern analysis with a neural network coarse-coding a pattern to be analyzed so as to form a plurality of sub-patterns collectively defined by data. Each of the sub-patterns comprises sets of pattern data. The neural network includes a plurality fields, each field being associated with one of the sub-patterns so as to receive the sub-pattern data therefrom. Training and testing by the neural network then proceeds in the usual way, with one modification: the transfer function thresholds the value obtained from summing the weighted products of each field over all sub-patterns associated with each pattern being analyzed by the system.

Neural correlations enable invariant coding and perception of natural stimuli in weakly electric fish

PubMed Central

Metzen, Michael G; Hofmann, Volker; Chacron, Maurice J

2016-01-01

Neural representations of behaviorally relevant stimulus features displaying invariance with respect to different contexts are essential for perception. However, the mechanisms mediating their emergence and subsequent refinement remain poorly understood in general. Here, we demonstrate that correlated neural activity allows for the emergence of an invariant representation of natural communication stimuli that is further refined across successive stages of processing in the weakly electric fish Apteronotus leptorhynchus. Importantly, different patterns of input resulting from the same natural communication stimulus occurring in different contexts all gave rise to similar behavioral responses. Our results thus reveal how a generic neural circuit performs an elegant computation that mediates the emergence and refinement of an invariant neural representation of natural stimuli that most likely constitutes a neural correlate of perception. DOI: http://dx.doi.org/10.7554/eLife.12993.001 PMID:27128376

Prediction of Welded Joint Strength in Plasma Arc Welding: A Comparative Study Using Back-Propagation and Radial Basis Neural Networks

NASA Astrophysics Data System (ADS)

Srinivas, Kadivendi; Vundavilli, Pandu R.; Manzoor Hussain, M.; Saiteja, M.

2016-09-01

Welding input parameters such as current, gas flow rate and torch angle play a significant role in determination of qualitative mechanical properties of weld joint. Traditionally, it is necessary to determine the weld input parameters for every new welded product to obtain a quality weld joint which is time consuming. In the present work, the effect of plasma arc welding parameters on mild steel was studied using a neural network approach. To obtain a response equation that governs the input-output relationships, conventional regression analysis was also performed. The experimental data was constructed based on Taguchi design and the training data required for neural networks were randomly generated, by varying the input variables within their respective ranges. The responses were calculated for each combination of input variables by using the response equations obtained through the conventional regression analysis. The performances in Levenberg-Marquardt back propagation neural network and radial basis neural network (RBNN) were compared on various randomly generated test cases, which are different from the training cases. From the results, it is interesting to note that for the above said test cases RBNN analysis gave improved training results compared to that of feed forward back propagation neural network analysis. Also, RBNN analysis proved a pattern of increasing performance as the data points moved away from the initial input values.

Dissociation of neural mechanisms underlying orientation processing in humans

PubMed Central

Ling, Sam; Pearson, Joel; Blake, Randolph

2009-01-01

Summary Orientation selectivity is a fundamental, emergent property of neurons in early visual cortex, and discovery of that property [1, 2] dramatically shaped how we conceptualize visual processing [3–6]. However, much remains unknown about the neural substrates of these basic building blocks of perception, and what is known primarily stems from animal physiology studies. To probe the neural concomitants of orientation processing in humans, we employed repetitive transcranial magnetic stimulation (rTMS) to attenuate neural responses evoked by stimuli presented within a local region of the visual field. Previous physiological studies have shown that rTMS can significantly suppress the neuronal spiking activity, hemodynamic responses, and local field potentials within a focused cortical region [7, 8]. By suppressing neural activity with rTMS, we were able to dissociate components of the neural circuitry underlying two distinct aspects of orientation processing: selectivity and contextual effects. Orientation selectivity gauged by masking was unchanged by rTMS, whereas an otherwise robust orientation repulsion illusion was weakened following rTMS. This dissociation implies that orientation processing relies on distinct mechanisms, only one of which was impacted by rTMS. These results are consistent with models positing that orientation selectivity is largely governed by the patterns of convergence of thalamic afferents onto cortical neurons, with intracortical activity then shaping population responses contained within those orientation-selective cortical neurons. PMID:19682905

Exact computation of the maximum-entropy potential of spiking neural-network models.

PubMed

Cofré, R; Cessac, B

2014-05-01

Understanding how stimuli and synaptic connectivity influence the statistics of spike patterns in neural networks is a central question in computational neuroscience. The maximum-entropy approach has been successfully used to characterize the statistical response of simultaneously recorded spiking neurons responding to stimuli. However, in spite of good performance in terms of prediction, the fitting parameters do not explain the underlying mechanistic causes of the observed correlations. On the other hand, mathematical models of spiking neurons (neuromimetic models) provide a probabilistic mapping between the stimulus, network architecture, and spike patterns in terms of conditional probabilities. In this paper we build an exact analytical mapping between neuromimetic and maximum-entropy models.

Task-level feedback can explain temporal recruitment of spatially fixed muscle synergies throughout postural perturbations

PubMed Central

Safavynia, Seyed A.

2012-01-01

Recent evidence suggests that complex spatiotemporal patterns of muscle activity can be explained with a low-dimensional set of muscle synergies or M-modes. While it is clear that both spatial and temporal aspects of muscle coordination may be low dimensional, constraints on spatial versus temporal features of muscle coordination likely involve different neural control mechanisms. We hypothesized that the low-dimensional spatial and temporal features of muscle coordination are independent of each other. We further hypothesized that in reactive feedback tasks, spatially fixed muscle coordination patterns—or muscle synergies—are hierarchically recruited via time-varying neural commands based on delayed task-level feedback. We explicitly compared the ability of spatially fixed (SF) versus temporally fixed (TF) muscle synergies to reconstruct the entire time course of muscle activity during postural responses to anterior-posterior support-surface translations. While both SF and TF muscle synergies could account for EMG variability in a postural task, SF muscle synergies produced more consistent and physiologically interpretable results than TF muscle synergies during postural responses to perturbations. Moreover, a majority of SF muscle synergies were consistent in structure when extracted from epochs throughout postural responses. Temporal patterns of SF muscle synergy recruitment were well-reconstructed by delayed feedback of center of mass (CoM) kinematics and reproduced EMG activity of multiple muscles. Consistent with the idea that independent and hierarchical low-dimensional neural control structures define spatial and temporal patterns of muscle activity, our results suggest that CoM kinematics are a task variable used to recruit SF muscle synergies for feedback control of balance. PMID:21957219

Auditory stream segregation in monkey auditory cortex: effects of frequency separation, presentation rate, and tone duration

NASA Astrophysics Data System (ADS)

Fishman, Yonatan I.; Arezzo, Joseph C.; Steinschneider, Mitchell

2004-09-01

Auditory stream segregation refers to the organization of sequential sounds into ``perceptual streams'' reflecting individual environmental sound sources. In the present study, sequences of alternating high and low tones, ``...ABAB...,'' similar to those used in psychoacoustic experiments on stream segregation, were presented to awake monkeys while neural activity was recorded in primary auditory cortex (A1). Tone frequency separation (ΔF), tone presentation rate (PR), and tone duration (TD) were systematically varied to examine whether neural responses correlate with effects of these variables on perceptual stream segregation. ``A'' tones were fixed at the best frequency of the recording site, while ``B'' tones were displaced in frequency from ``A'' tones by an amount=ΔF. As PR increased, ``B'' tone responses decreased in amplitude to a greater extent than ``A'' tone responses, yielding neural response patterns dominated by ``A'' tone responses occurring at half the alternation rate. Increasing TD facilitated the differential attenuation of ``B'' tone responses. These findings parallel psychoacoustic data and suggest a physiological model of stream segregation whereby increasing ΔF, PR, or TD enhances spatial differentiation of ``A'' tone and ``B'' tone responses along the tonotopic map in A1.

Disgust, Fear, and the Anxiety Disorders: A Critical Review

PubMed Central

Cisler, Josh M.; Olatunji, Bunmi O.; Lohr, Jeffrey M.

2010-01-01

Anxiety disorders have traditionally been conceptualized as reflecting the emotions of fear and anxiety. A developing program of research demonstrates a relation between disgust and three specific anxiety disorders: blood-injection-injury (BII) phobia, spider phobia, and contamination-related obsessive-compulsive disorder (OCD). This review serves three purposes. First, the authors review the response patterns predicted to be observed if the emotional response in these disorders involved disgust versus fear. The review suggests specific response patterns that characterize disgust and fear in the domains of heart rate, facial expression, neural activity, and cognitive processes. Second, the authors review extant research employing measures of these domains in spider phobia, BII phobia, and contamination-related OCD. The evidence suggests that both fear and disgust characterize each of these disorders, but the magnitude at which the emotions characterize the disorders may depend on the response domain measured. For example, disgust may be more involved in spider phobia in appraisals and facial expression, but less involved in neural correlates or heart rate domains. Third, the authors suggest guidelines for future research, including concurrent use of specific measures as well as examining whether the different emotions in different response domains respond to similar interventions (e.g., exposure). PMID:18977061

Neural Decoding of Bistable Sounds Reveals an Effect of Intention on Perceptual Organization

PubMed Central

2018-01-01

Auditory signals arrive at the ear as a mixture that the brain must decompose into distinct sources based to a large extent on acoustic properties of the sounds. An important question concerns whether listeners have voluntary control over how many sources they perceive. This has been studied using pure high (H) and low (L) tones presented in the repeating pattern HLH-HLH-, which can form a bistable percept heard either as an integrated whole (HLH-) or as segregated into high (H-H-) and low (-L-) sequences. Although instructing listeners to try to integrate or segregate sounds affects reports of what they hear, this could reflect a response bias rather than a perceptual effect. We had human listeners (15 males, 12 females) continuously report their perception of such sequences and recorded neural activity using MEG. During neutral listening, a classifier trained on patterns of neural activity distinguished between periods of integrated and segregated perception. In other conditions, participants tried to influence their perception by allocating attention either to the whole sequence or to a subset of the sounds. They reported hearing the desired percept for a greater proportion of time than when listening neutrally. Critically, neural activity supported these reports; stimulus-locked brain responses in auditory cortex were more likely to resemble the signature of segregation when participants tried to hear segregation than when attempting to perceive integration. These results indicate that listeners can influence how many sound sources they perceive, as reflected in neural responses that track both the input and its perceptual organization. SIGNIFICANCE STATEMENT Can we consciously influence our perception of the external world? We address this question using sound sequences that can be heard either as coming from a single source or as two distinct auditory streams. Listeners reported spontaneous changes in their perception between these two interpretations while we recorded neural activity to identify signatures of such integration and segregation. They also indicated that they could, to some extent, choose between these alternatives. This claim was supported by corresponding changes in responses in auditory cortex. By linking neural and behavioral correlates of perception, we demonstrate that the number of objects that we perceive can depend not only on the physical attributes of our environment, but also on how we intend to experience it. PMID:29440556

Developmental dyscalculia: compensatory mechanisms in left intraparietal regions in response to nonsymbolic magnitudes.

PubMed

Kaufmann, Liane; Vogel, Stephan E; Starke, Marc; Kremser, Christian; Schocke, Michael; Wood, Guilherme

2009-08-05

Functional magnetic resonance imaging (fMRI) studies investigating the neural mechanisms underlying developmental dyscalculia are scarce and results are thus far inconclusive. Main aim of the present study is to investigate the neural correlates of nonsymbolic number magnitude processing in children with and without dyscalculia. 18 children (9 with dyscalculia) were asked to solve a non-symbolic number magnitude comparison task (finger patterns) during brain scanning. For the spatial control task identical stimuli were employed, instructions varying only (judgment of palm rotation). This design enabled us to present identical stimuli with identical visual processing requirements in the experimental and the control task. Moreover, because numerical and spatial processing relies on parietal brain regions, task-specific contrasts are expected to reveal true number-specific activations. Behavioral results during scanning reveal that despite comparable (almost at ceiling) performance levels, task-specific activations were stronger in dyscalculic children in inferior parietal cortices bilaterally (intraparietal sulcus, supramarginal gyrus, extending to left angular gyrus). Interestingly, fMRI signal strengths reflected a group x task interaction: relative to baseline, controls produced significant deactivations in (intra)parietal regions bilaterally in response to number but not spatial processing, while the opposite pattern emerged in dyscalculics. Moreover, beta weights in response to number processing differed significantly between groups in left - but not right - (intra)parietal regions (becoming even positive in dyscalculic children). Overall, findings are suggestive of (a) less consistent neural activity in right (intra)parietal regions upon processing nonsymbolic number magnitudes; and (b) compensatory neural activity in left (intra)parietal regions in developmental dyscalculia.

Developmental dyscalculia: compensatory mechanisms in left intraparietal regions in response to nonsymbolic magnitudes

PubMed Central

Kaufmann, Liane; Vogel, Stephan E; Starke, Marc; Kremser, Christian; Schocke, Michael; Wood, Guilherme

2009-01-01

Background Functional magnetic resonance imaging (fMRI) studies investigating the neural mechanisms underlying developmental dyscalculia are scarce and results are thus far inconclusive. Main aim of the present study is to investigate the neural correlates of nonsymbolic number magnitude processing in children with and without dyscalculia. Methods 18 children (9 with dyscalculia) were asked to solve a non-symbolic number magnitude comparison task (finger patterns) during brain scanning. For the spatial control task identical stimuli were employed, instructions varying only (judgment of palm rotation). This design enabled us to present identical stimuli with identical visual processing requirements in the experimental and the control task. Moreover, because numerical and spatial processing relies on parietal brain regions, task-specific contrasts are expected to reveal true number-specific activations. Results Behavioral results during scanning reveal that despite comparable (almost at ceiling) performance levels, task-specific activations were stronger in dyscalculic children in inferior parietal cortices bilaterally (intraparietal sulcus, supramarginal gyrus, extending to left angular gyrus). Interestingly, fMRI signal strengths reflected a group × task interaction: relative to baseline, controls produced significant deactivations in (intra)parietal regions bilaterally in response to number but not spatial processing, while the opposite pattern emerged in dyscalculics. Moreover, beta weights in response to number processing differed significantly between groups in left – but not right – (intra)parietal regions (becoming even positive in dyscalculic children). Conclusion Overall, findings are suggestive of (a) less consistent neural activity in right (intra)parietal regions upon processing nonsymbolic number magnitudes; and (b) compensatory neural activity in left (intra)parietal regions in developmental dyscalculia. PMID:19653919

Goal-Directed Modulation of Neural Memory Patterns: Implications for fMRI-Based Memory Detection.

PubMed

Uncapher, Melina R; Boyd-Meredith, J Tyler; Chow, Tiffany E; Rissman, Jesse; Wagner, Anthony D

2015-06-03

Remembering a past event elicits distributed neural patterns that can be distinguished from patterns elicited when encountering novel information. These differing patterns can be decoded with relatively high diagnostic accuracy for individual memories using multivoxel pattern analysis (MVPA) of fMRI data. Brain-based memory detection--if valid and reliable--would have clear utility beyond the domain of cognitive neuroscience, in the realm of law, marketing, and beyond. However, a significant boundary condition on memory decoding validity may be the deployment of "countermeasures": strategies used to mask memory signals. Here we tested the vulnerability of fMRI-based memory detection to countermeasures, using a paradigm that bears resemblance to eyewitness identification. Participants were scanned while performing two tasks on previously studied and novel faces: (1) a standard recognition memory task; and (2) a task wherein they attempted to conceal their true memory state. Univariate analyses revealed that participants were able to strategically modulate neural responses, averaged across trials, in regions implicated in memory retrieval, including the hippocampus and angular gyrus. Moreover, regions associated with goal-directed shifts of attention and thought substitution supported memory concealment, and those associated with memory generation supported novelty concealment. Critically, whereas MVPA enabled reliable classification of memory states when participants reported memory truthfully, the ability to decode memory on individual trials was compromised, even reversing, during attempts to conceal memory. Together, these findings demonstrate that strategic goal states can be deployed to mask memory-related neural patterns and foil memory decoding technology, placing a significant boundary condition on their real-world utility. Copyright © 2015 the authors 0270-6474/15/358531-15$15.00/0.

Multi-voxel Patterns Reveal Functionally Differentiated Networks Underlying Auditory Feedback Processing of Speech

PubMed Central

Zheng, Zane Z.; Vicente-Grabovetsky, Alejandro; MacDonald, Ewen N.; Munhall, Kevin G.; Cusack, Rhodri; Johnsrude, Ingrid S.

2013-01-01

The everyday act of speaking involves the complex processes of speech motor control. An important component of control is monitoring, detection and processing of errors when auditory feedback does not correspond to the intended motor gesture. Here we show, using fMRI and converging operations within a multi-voxel pattern analysis framework, that this sensorimotor process is supported by functionally differentiated brain networks. During scanning, a real-time speech-tracking system was employed to deliver two acoustically different types of distorted auditory feedback or unaltered feedback while human participants were vocalizing monosyllabic words, and to present the same auditory stimuli while participants were passively listening. Whole-brain analysis of neural-pattern similarity revealed three functional networks that were differentially sensitive to distorted auditory feedback during vocalization, compared to during passive listening. One network of regions appears to encode an ‘error signal’ irrespective of acoustic features of the error: this network, including right angular gyrus, right supplementary motor area, and bilateral cerebellum, yielded consistent neural patterns across acoustically different, distorted feedback types, only during articulation (not during passive listening). In contrast, a fronto-temporal network appears sensitive to the speech features of auditory stimuli during passive listening; this preference for speech features was diminished when the same stimuli were presented as auditory concomitants of vocalization. A third network, showing a distinct functional pattern from the other two, appears to capture aspects of both neural response profiles. Taken together, our findings suggest that auditory feedback processing during speech motor control may rely on multiple, interactive, functionally differentiated neural systems. PMID:23467350

The problem with value

PubMed Central

O’Doherty, John P.

2015-01-01

Neural correlates of value have been extensively reported in a diverse set of brain regions. However, in many cases it is difficult to determine whether a particular neural response pattern corresponds to a value-signal per se as opposed to an array of alternative non-value related processes, such as outcome-identity coding, informational coding, encoding of autonomic and skeletomotor consequences, alongside previously described “salience” or “attentional” effects. Here, I review a number of experimental manipulations that can be used to test for value, and I identify the challenges in ascertaining whether a particular neural response is or is not a value signal. Finally, I emphasize that some non-value related signals may be especially informative as a means of providing insight into the nature of the decision-making related computations that are being implemented in a particular brain region. PMID:24726573

Specific contributions of basal ganglia and cerebellum to the neural tracking of rhythm.

PubMed

Nozaradan, Sylvie; Schwartze, Michael; Obermeier, Christian; Kotz, Sonja A

2017-10-01

How specific brain networks track rhythmic sensory input over time remains a challenge in neuroimaging work. Here we show that subcortical areas, namely the basal ganglia and the cerebellum, specifically contribute to the neural tracking of rhythm. We tested patients with focal lesions in either of these areas and healthy controls by means of electroencephalography (EEG) while they listened to rhythmic sequences known to induce selective neural tracking at a frequency corresponding to the most-often perceived pulse-like beat. Both patients and controls displayed neural responses to the rhythmic sequences. However, these response patterns were different across groups, with patients showing reduced tracking at beat frequency, especially for the more challenging rhythms. In the cerebellar patients, this effect was specific to the rhythm played at a fast tempo, which places high demands on the temporally precise encoding of events. In contrast, basal ganglia patients showed more heterogeneous responses at beat frequency specifically for the most complex rhythm, which requires more internal generation of the beat. These findings provide electrophysiological evidence that these subcortical structures selectively shape the neural representation of rhythm. Moreover, they suggest that the processing of rhythmic auditory input relies on an extended cortico-subcortico-cortical functional network providing specific timing and entrainment sensitivities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Artificial neural network implementation of a near-ideal error prediction controller

NASA Technical Reports Server (NTRS)

Mcvey, Eugene S.; Taylor, Lynore Denise

1992-01-01

A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error responses be known for a particular input and modeled plant. These responses are used in the error prediction controller. An analysis was done on the general dynamic behavior that results from including a digital error predictor in a control loop and these were compared to those including the near-ideal Neural Network error predictor. This analysis was done for a second and third order system.

Implantable Neural Interfaces for Sharks

DTIC Science & Technology

2007-05-01

technology for recording and stimulating from the auditory and olfactory sensory nervous systems of the awake , swimming nurse shark, G. cirratum (Figures...and awake animals. Finally, evidence exists that microstimulation of the olfactory system could lead to patterned behavioral responses in the...auditory-evoked local field potentials (multi- modal sensory responses) from both anesthetized and awake animals. Figure 1: Pre-operative MR

Young Adult Smokers' Neural Response to Graphic Cigarette Warning Labels.

PubMed

Green, Adam E; Mays, Darren; Falk, Emily B; Vallone, Donna; Gallagher, Natalie; Richardson, Amanda; Tercyak, Kenneth P; Abrams, David B; Niaura, Raymond S

2016-06-01

The study examined young adult smokers' neural response to graphic warning labels (GWLs) on cigarette packs using functional magnetic resonance imaging (fMRI). Nineteen young adult smokers ( M age 22.9, 52.6% male, 68.4% non-white, M 4.3 cigarettes/day) completed pre-scan, self-report measures of demographics, cigarette smoking behavior, and nicotine dependence, and an fMRI scanning session. During the scanning session participants viewed cigarette pack images (total 64 stimuli, viewed 4 seconds each) that varied based on the warning label (graphic or visually occluded control) and pack branding (branded or plain packaging) in an event-related experimental design. Participants reported motivation to quit (MTQ) in response to each image using a push-button control. Whole-brain blood oxygenation level-dependent (BOLD) functional images were acquired during the task. GWLs produced significantly greater self-reported MTQ than control warnings ( p < .001). Imaging data indicate stronger neural activation in response to GWLs than the control warnings at a cluster-corrected threshold p <.001 in medial prefrontal cortex, amygdala, medial temporal lobe, and occipital cortex. There were no significant differences in response to warnings on branded versus plain cigarette packages. In this sample of young adult smokers, GWLs promoted neural activation in brain regions involved in cognitive and affective decision-making and memory formation and the effects of GWLs did not differ on branded or plain cigarette packaging. These findings complement other recent neuroimaging GWL studies conducted with older adult smokers and with adolescents by demonstrating similar patterns of neural activation in response to GWLs among young adult smokers.

BDNFval66met affects neural activation pattern during fear conditioning and 24 h delayed fear recall.

PubMed

Lonsdorf, Tina B; Golkar, Armita; Lindström, Kara M; Haaker, Jan; Öhman, Arne; Schalling, Martin; Ingvar, Martin

2015-05-01

Brain-derived neurotrophic factor (BDNF), the most abundant neutrophin in the mammalian central nervous system, is critically involved in synaptic plasticity. In both rodents and humans, BDNF has been implicated in hippocampus- and amygdala-dependent learning and memory and has more recently been linked to fear extinction processes. Fifty-nine healthy participants, genotyped for the functional BDNFval66met polymorphism, underwent a fear conditioning and 24h-delayed extinction protocol while skin conductance and blood oxygenation level dependent (BOLD) responses (functional magnetic resonance imaging) were acquired. We present the first report of neural activation pattern during fear acquisition 'and' extinction for the BDNFval66met polymorphism using a differential conditioned stimulus (CS)+ > CS- comparison. During conditioning, we observed heightened allele dose-dependent responses in the amygdala and reduced responses in the subgenual anterior cingulate cortex in BDNFval66met met-carriers. During early extinction, 24h later, we again observed heightened responses in several regions ascribed to the fear network in met-carriers as opposed to val-carriers (insula, amygdala, hippocampus), which likely reflects fear memory recall. No differences were observed during late extinction, which likely reflects learned extinction. Our data thus support previous associations of the BDNFval66met polymorphism with neural activation in the fear and extinction network, but speak against a specific association with fear extinction processes. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Spatiotemporal activity patterns detected from single cell measurements from behaving animals

NASA Astrophysics Data System (ADS)

Villa, Alessandro E. P.; Tetko, Igor V.

1999-03-01

Precise temporal patterning of activity within and between neurons has been predicted on theoretical grounds, and found in the spike trains of neurons recorded from anesthetized and conscious animals, in association with sensor stimuli and particular phases of task performance. However, the functional significance of such patterning in the generation of behavior has not been confirmed. We recorded from multiple single neurons in regions of rat auditory cortex during the waiting period of a Go/NoGo task. During this time the animal waited for an auditory signal with high cognitive load. Of note is the fact that neural activity during the period analyzed was essentially stationary, with no event related variability in firing. Detected patterns therefore provide a measure of brain state that could not be addressed by standard methods relying on analysis of changes in mean discharge rate. The possibility is discussed that some patterns might reflect a preset bias to a particular response, formed in the waiting period. Others patterns might reflect a state of prior preparation of appropriate neural assemblies for analyzing a signal that is expected but of unknown behavioral valence.

Neural Bases Of Food Perception: Coordinate-Based Meta-Analyses Of Neuroimaging Studies In Multiple Modalities

PubMed Central

Huerta, Claudia I; Sarkar, Pooja R; Duong, Timothy Q.; Laird, Angela R; Fox, Peter T

2013-01-01

Objective The purpose of this study was to compare the results of the three food-cue paradigms most commonly used for functional neuroimaging studies to determine: i) commonalities and differences in the neural response patterns by paradigm; and, ii) the relative robustness and reliability of responses to each paradigm. Design and Methods functional magnetic resonance imaging (fMRI) studies using standardized stereotactic coordinates to report brain responses to food cues were identified using on-line databases. Studies were grouped by food-cue modality as: i) tastes (8 studies); ii) odors (8 studies); and, iii) images (11 studies). Activation likelihood estimation (ALE) was used to identify statistically reliable regional responses within each stimulation paradigm. Results Brain response distributions were distinctly different for the three stimulation modalities, corresponding to known differences in location of the respective primary and associative cortices. Visual stimulation induced the most robust and extensive responses. The left anterior insula was the only brain region reliably responding to all three stimulus categories. Conclusions These findings suggest visual food-cue paradigm as promising candidate for imaging studies addressing the neural substrate of therapeutic interventions. PMID:24174404

Locating the cortical bottleneck for slow reading in peripheral vision

PubMed Central

Yu, Deyue; Jiang, Yi; Legge, Gordon E.; He, Sheng

2015-01-01

Yu, Legge, Park, Gage, and Chung (2010) suggested that the neural bottleneck for slow peripheral reading is located in nonretinotopic areas. We investigated the potential rate-limiting neural site for peripheral reading using fMRI, and contrasted peripheral reading with recognition of peripherally presented line drawings of common objects. We measured the BOLD responses to both text (three-letter words/nonwords) and line-drawing objects presented either in foveal or peripheral vision (10° lower right visual field) at three presentation rates (2, 4, and 8/second). The statistically significant interaction effect of visual field × presentation rate on the BOLD response for text but not for line drawings provides evidence for distinctive processing of peripheral text. This pattern of results was obtained in all five regions of interest (ROIs). At the early retinotopic cortical areas, the BOLD signal slightly increased with increasing presentation rate for foveal text, and remained fairly constant for peripheral text. In the Occipital Word-Responsive Area (OWRA), Visual Word Form Area (VWFA), and object sensitive areas (LO and PHA), the BOLD responses to text decreased with increasing presentation rate for peripheral but not foveal presentation. In contrast, there was no rate-dependent reduction in BOLD response for line-drawing objects in all the ROIs for either foveal or peripheral presentation. Only peripherally presented text showed a distinctive rate-dependence pattern. Although it is possible that the differentiation starts to emerge at the early retinotopic cortical representation, the neural bottleneck for slower reading of peripherally presented text may be a special property of peripheral text processing in object category selective cortex. PMID:26237299

Categorical clustering of the neural representation of color.

PubMed

Brouwer, Gijs Joost; Heeger, David J

2013-09-25

Cortical activity was measured with functional magnetic resonance imaging (fMRI) while human subjects viewed 12 stimulus colors and performed either a color-naming or diverted attention task. A forward model was used to extract lower dimensional neural color spaces from the high-dimensional fMRI responses. The neural color spaces in two visual areas, human ventral V4 (V4v) and VO1, exhibited clustering (greater similarity between activity patterns evoked by stimulus colors within a perceptual category, compared to between-category colors) for the color-naming task, but not for the diverted attention task. Response amplitudes and signal-to-noise ratios were higher in most visual cortical areas for color naming compared to diverted attention. But only in V4v and VO1 did the cortical representation of color change to a categorical color space. A model is presented that induces such a categorical representation by changing the response gains of subpopulations of color-selective neurons.

Reciprocal neural response within lateral and ventral medial prefrontal cortex during hot and cold reasoning.

PubMed

Goel, Vinod; Dolan, Raymond J

2003-12-01

Logic is widely considered the basis of rationality. Logical choices, however, are often influenced by emotional responses, sometimes to our detriment, sometimes to our advantage. To understand the neural basis of emotionally neutral ("cold") and emotionally salient ("hot") reasoning we studied 19 volunteers using event-related fMRI, as they made logical judgments about arguments that varied in emotional saliency. Despite identical logical form and content categories across "hot" and "cold" reasoning conditions, lateral and ventral medial prefrontal cortex showed reciprocal response patterns as a function of emotional saliency of content. "Cold" reasoning trials resulted in enhanced activity in lateral/dorsal lateral prefrontal cortex (L/DLPFC) and suppression of activity in ventral medial prefrontal cortex (VMPFC). By contrast, "hot" reasoning trials resulted in enhanced activation in VMPFC and suppression of activation in L/DLPFC. This reciprocal engagement of L/DLPFC and VMPFC provides evidence for a dynamic neural system for reasoning, the configuration of which is strongly influenced by emotional saliency.

Categorical Clustering of the Neural Representation of Color

PubMed Central

Heeger, David J.

2013-01-01

Cortical activity was measured with functional magnetic resonance imaging (fMRI) while human subjects viewed 12 stimulus colors and performed either a color-naming or diverted attention task. A forward model was used to extract lower dimensional neural color spaces from the high-dimensional fMRI responses. The neural color spaces in two visual areas, human ventral V4 (V4v) and VO1, exhibited clustering (greater similarity between activity patterns evoked by stimulus colors within a perceptual category, compared to between-category colors) for the color-naming task, but not for the diverted attention task. Response amplitudes and signal-to-noise ratios were higher in most visual cortical areas for color naming compared to diverted attention. But only in V4v and VO1 did the cortical representation of color change to a categorical color space. A model is presented that induces such a categorical representation by changing the response gains of subpopulations of color-selective neurons. PMID:24068814

An oxytocin-induced facilitation of neural and emotional responses to social touch correlates inversely with autism traits.

PubMed

Scheele, Dirk; Kendrick, Keith M; Khouri, Christoph; Kretzer, Elisa; Schläpfer, Thomas E; Stoffel-Wagner, Birgit; Güntürkün, Onur; Maier, Wolfgang; Hurlemann, René

2014-08-01

Social communication through touch and mutual grooming can convey highly salient socio-emotional signals and has been shown to involve the neuropeptide oxytocin (OXT) in several species. Less is known about the modulatory influence of OXT on the neural and emotional responses to human interpersonal touch. The present randomized placebo (PLC)-controlled within-subject pharmaco-functional magnetic resonance imaging (fMRI) study was designed to test the hypothesis that a single intranasal dose of synthetic OXT (24 IU) would facilitate both neural and emotional responses to interpersonal touch in a context- (female vs male touch) and trait- (autistic trait load) specific manner. Specifically, the experimental rationale was to manipulate the reward value of interpersonal touch independent of the intensity and type of actual cutaneous stimulation administered. Thus, 40 heterosexual males believed that they were touched by either a man or a woman, although in fact an identical pattern of touch was always given by the same female experimenter blind to condition type. Our results show that OXT increased the perceived pleasantness of female, but not male touch, and associated neural responses in insula, precuneus, orbitofrontal, and pregenual anterior cingulate cortex. Moreover, the behavioral and neural effects of OXT were negatively correlated with autistic-like traits. Taken together, this is the first study to show that the perceived hedonic value of human heterosexual interpersonal touch is facilitated by OXT in men, but that its behavioral and neural effects in this context are blunted in individuals with autistic traits.

A Double Dissociation between Anterior and Posterior Superior Temporal Gyrus for Processing Audiovisual Speech Demonstrated by Electrocorticography

PubMed Central

Ozker, Muge; Schepers, Inga M.; Magnotti, John F.; Yoshor, Daniel; Beauchamp, Michael S.

2017-01-01

Human speech can be comprehended using only auditory information from the talker’s voice. However, comprehension is improved if the talker’s face is visible, especially if the auditory information is degraded as occurs in noisy environments or with hearing loss. We explored the neural substrates of audiovisual speech perception using electrocorticography, direct recording of neural activity using electrodes implanted on the cortical surface. We observed a double dissociation in the responses to audiovisual speech with clear and noisy auditory component within the superior temporal gyrus (STG), a region long known to be important for speech perception. Anterior STG showed greater neural activity to audiovisual speech with clear auditory component, whereas posterior STG showed similar or greater neural activity to audiovisual speech in which the speech was replaced with speech-like noise. A distinct border between the two response patterns was observed, demarcated by a landmark corresponding to the posterior margin of Heschl’s gyrus. To further investigate the computational roles of both regions, we considered Bayesian models of multisensory integration, which predict that combining the independent sources of information available from different modalities should reduce variability in the neural responses. We tested this prediction by measuring the variability of the neural responses to single audiovisual words. Posterior STG showed smaller variability than anterior STG during presentation of audiovisual speech with noisy auditory component. Taken together, these results suggest that posterior STG but not anterior STG is important for multisensory integration of noisy auditory and visual speech. PMID:28253074

Vibrational Analysis of Engine Components Using Neural-Net Processing and Electronic Holography

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Fite, E. Brian; Mehmed, Oral; Thorp, Scott A.

1997-01-01

The use of computational-model trained artificial neural networks to acquire damage specific information from electronic holograms is discussed. A neural network is trained to transform two time-average holograms into a pattern related to the bending-induced-strain distribution of the vibrating component. The bending distribution is very sensitive to component damage unlike the characteristic fringe pattern or the displacement amplitude distribution. The neural network processor is fast for real-time visualization of damage. The two-hologram limit makes the processor more robust to speckle pattern decorrelation. Undamaged and cracked cantilever plates serve as effective objects for testing the combination of electronic holography and neural-net processing. The requirements are discussed for using finite-element-model trained neural networks for field inspections of engine components. The paper specifically discusses neural-network fringe pattern analysis in the presence of the laser speckle effect and the performances of two limiting cases of the neural-net architecture.

Vibrational Analysis of Engine Components Using Neural-Net Processing and Electronic Holography

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Fite, E. Brian; Mehmed, Oral; Thorp, Scott A.

1998-01-01

The use of computational-model trained artificial neural networks to acquire damage specific information from electronic holograms is discussed. A neural network is trained to transform two time-average holograms into a pattern related to the bending-induced-strain distribution of the vibrating component. The bending distribution is very sensitive to component damage unlike the characteristic fringe pattern or the displacement amplitude distribution. The neural network processor is fast for real-time visualization of damage. The two-hologram limit makes the processor more robust to speckle pattern decorrelation. Undamaged and cracked cantilever plates serve as effective objects for testing the combination of electronic holography and neural-net processing. The requirements are discussed for using finite-element-model trained neural networks for field inspections of engine components. The paper specifically discusses neural-network fringe pattern analysis in the presence of the laser speckle effect and the performances of two limiting cases of the neural-net architecture.

Engaged listeners: shared neural processing of powerful political speeches.

PubMed

Schmälzle, Ralf; Häcker, Frank E K; Honey, Christopher J; Hasson, Uri

2015-08-01

Powerful speeches can captivate audiences, whereas weaker speeches fail to engage their listeners. What is happening in the brains of a captivated audience? Here, we assess audience-wide functional brain dynamics during listening to speeches of varying rhetorical quality. The speeches were given by German politicians and evaluated as rhetorically powerful or weak. Listening to each of the speeches induced similar neural response time courses, as measured by inter-subject correlation analysis, in widespread brain regions involved in spoken language processing. Crucially, alignment of the time course across listeners was stronger for rhetorically powerful speeches, especially for bilateral regions of the superior temporal gyri and medial prefrontal cortex. Thus, during powerful speeches, listeners as a group are more coupled to each other, suggesting that powerful speeches are more potent in taking control of the listeners' brain responses. Weaker speeches were processed more heterogeneously, although they still prompted substantially correlated responses. These patterns of coupled neural responses bear resemblance to metaphors of resonance, which are often invoked in discussions of speech impact, and contribute to the literature on auditory attention under natural circumstances. Overall, this approach opens up possibilities for research on the neural mechanisms mediating the reception of entertaining or persuasive messages. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Ingroup favoritism or the black sheep effect: Perceived intentions modulate subjective responses to aggressive interactions.

PubMed

Wang, Lei; Zheng, Jiehui; Meng, Liang; Lu, Qiang; Ma, Qingguo

2016-07-01

Social categorization plays an important role in provoking the victim's responses to aggressive interactions. Pioneering studies suggested that uncertainty in the perpetrator's hostile intention influences whether ingroup favoritism or the black sheep effect (ingroup strictness) will be manifested to a greater extent. However, when the hostile intention is ambiguous, subjective perception of the perpetrator's intention may still be quite different due to the inherent information gap between participants, and this discrepancy in perceived intentions may further modulate subjective responses to social aggression. In the present study, subjects played as responders of the Ultimatum Game, and received varied offers proposed by either ingroup or outgroup members. Electrophysiological results showed that, when proposers were perceived to be intentional, unfair offers from ingroups elicited significantly larger Feedback-related Negativity (FRN) than those from outgroups, potentially providing neural evidence for the black sheep effect. The opposite FRN pattern was observed when proposers were perceived to be unintentional, which might suggest ingroup favoritism. Interestingly, despite contrary neural patterns, perceived intentions did not modulate behavioral response to aggressive interactions. Thus, converging results suggested that, when the perpetrator's hostile intention remained ambiguous, perceived intentions modulated the victim's electrophysiological response while not the rational behavioral response to aggressive interactions. Copyright © 2016 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.

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

PubMed Central

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, 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. Results 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. 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. PMID:25009771

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

PubMed

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.

Detecting agency from the biological motion of veridical vs animated agents

PubMed Central

Kelley, William M.; Heatherton, Todd F.; Macrae, C. Neil

2007-01-01

The ability to detect agency is fundamental for understanding the social world. Underlying this capacity are neural circuits that respond to patterns of intentional biological motion in the superior temporal sulcus and temporoparietal junction. Here we show that the brain's blood oxygenation level dependent (BOLD) response to such motion is modulated by the representation of the actor. Dynamic social interactions were portrayed by either live-action agents or computer-animated agents, enacting the exact same patterns of biological motion. Using an event-related design, we found that the BOLD response associated with the perception and interpretation of agency was greater when identical physical movements were performed by real rather than animated agents. This finding has important implications for previous work on biological motion that has relied upon computer-animated stimuli and demonstrates that the neural substrates of social perception are finely tuned toward real-world agents. In addition, the response in lateral temporal areas was observed in the absence of instructions to make mental inferences, thus demonstrating the spontaneous implementation of the intentional stance. PMID:18985141

Investigation of the neurological correlates of information reception

NASA Technical Reports Server (NTRS)

1971-01-01

Animals trained to respond to a given pattern of electrical stimuli applied to pathways or centers of the auditory nervous system respond also to certain patterns of acoustic stimuli without additional training. Likewise, only certain electrical stimuli elicit responses after training to a given acoustic signal. In most instances, if a response has been learned to a given electrical stimulus applied to one center of the auditory nervous system, the same stimulus applied to another auditory center at either a higher or lower level will also elicit the response. This kind of transfer of response does not take place when a stimulus is applied through electrodes implanted in neural tissue outside of the auditory system.

Understanding the dynamical control of animal movement

NASA Astrophysics Data System (ADS)

Edwards, Donald

2008-03-01

Over the last 50 years, neurophysiologists have described many neural circuits that transform sensory input into motor commands, while biomechanicians and behavioral biologists have described many patterns of animal movement that occur in response to sensory input. Attempts to link these two have been frustrated by our technical inability to record from the necessary neurons in a freely behaving animal. As a result, we don't know how these neural circuits function in the closed loop context of free behavior, where the sensory and motor context changes on a millisecond time-scale. To address this problem, we have developed a software package, AnimatLab (www.AnimatLab.com), that enables users to reconstruct an animal's body and its relevant neural circuits, to link them at the sensory and motor ends, and through simulation, to test their ability to reproduce appropriate patterns of the animal's movements in a simulated Newtonian world. A Windows-based program, AnimatLab consists of a neural editor, a body editor, a world editor, stimulus and recording facilities, neural and physics engines, and an interactive 3-D graphical display. We have used AnimatLab to study three patterns of behavior: the grasshopper jump, crayfish escape, and crayfish leg movements used in postural control, walking, reaching and grasping. In each instance, the simulation helped identify constraints on both nervous function and biomechanical performance that have provided the basis for new experiments. Colleagues elsewhere have begun to use AnimatLab to study control of paw movements in cats and postural control in humans. We have also used AnimatLab simulations to guide the development of an autonomous hexapod robot in which the neural control circuitry is downloaded to the robot from the test computer.

Differences in neural activation as a function of risk-taking task parameters.

PubMed

Congdon, Eliza; Bato, Angelica A; Schonberg, Tom; Mumford, Jeanette A; Karlsgodt, Katherine H; Sabb, Fred W; London, Edythe D; Cannon, Tyrone D; Bilder, Robert M; Poldrack, Russell A

2013-01-01

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 Analog 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 (DI) 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 toward characterizing a behavioral measure of risky decision-making that may support a better understanding of naturalistic risk-taking.

A thesaurus for a neural population code

PubMed Central

Ganmor, Elad; Segev, Ronen; Schneidman, Elad

2015-01-01

Information is carried in the brain by the joint spiking patterns of large groups of noisy, unreliable neurons. This noise limits the capacity of the neural code and determines how information can be transmitted and read-out. To accurately decode, the brain must overcome this noise and identify which patterns are semantically similar. We use models of network encoding noise to learn a thesaurus for populations of neurons in the vertebrate retina responding to artificial and natural videos, measuring the similarity between population responses to visual stimuli based on the information they carry. This thesaurus reveals that the code is organized in clusters of synonymous activity patterns that are similar in meaning but may differ considerably in their structure. This organization is highly reminiscent of the design of engineered codes. We suggest that the brain may use this structure and show how it allows accurate decoding of novel stimuli from novel spiking patterns. DOI: http://dx.doi.org/10.7554/eLife.06134.001 PMID:26347983

Neural-Net Processing of Characteristic Patterns From Electronic Holograms of Vibrating Blades

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

1999-01-01

Finite-element-model-trained artificial neural networks can be used to process efficiently the characteristic patterns or mode shapes from electronic holograms of vibrating blades. The models used for routine design may not yet be sufficiently accurate for this application. This document discusses the creation of characteristic patterns; compares model generated and experimental characteristic patterns; and discusses the neural networks that transform the characteristic patterns into strain or damage information. The current potential to adapt electronic holography to spin rigs, wind tunnels and engines provides an incentive to have accurate finite element models lor training neural networks.

Parametric fMRI of paced motor responses uncovers novel whole-brain imaging biomarkers in spinocerebellar ataxia type 3.

PubMed

Duarte, João Valente; Faustino, Ricardo; Lobo, Mercês; Cunha, Gil; Nunes, César; Ferreira, Carlos; Januário, Cristina; Castelo-Branco, Miguel

2016-10-01

Machado-Joseph Disease, inherited type 3 spinocerebellar ataxia (SCA3), is the most common form worldwide. Neuroimaging and neuropathology have consistently demonstrated cerebellar alterations. Here we aimed to discover whole-brain functional biomarkers, based on parametric performance-level-dependent signals. We assessed 13 patients with early SCA3 and 14 healthy participants. We used a combined parametric behavioral/functional neuroimaging design to investigate disease fingerprints, as a function of performance levels, coupled with structural MRI and voxel-based morphometry. Functional magnetic resonance imaging (fMRI) was designed to parametrically analyze behavior and neural responses to audio-paced bilateral thumb movements at temporal frequencies of 1, 3, and 5 Hz. Our performance-level-based design probing neuronal correlates of motor coordination enabled the discovery that neural activation and behavior show critical loss of parametric modulation specifically in SCA3, associated with frequency-dependent cortico/subcortical activation/deactivation patterns. Cerebellar/cortical rate-dependent dissociation patterns could clearly differentiate between groups irrespective of grey matter loss. Our findings suggest functional reorganization of the motor network and indicate a possible role of fMRI as a tool to monitor disease progression in SCA3. Accordingly, fMRI patterns proved to be potential biomarkers in early SCA3, as tested by receiver operating characteristic analysis of both behavior and neural activation at different frequencies. Discrimination analysis based on BOLD signal in response to the applied parametric finger-tapping task significantly often reached >80% sensitivity and specificity in single regions-of-interest.Functional fingerprints based on cerebellar and cortical BOLD performance dependent signal modulation can thus be combined as diagnostic and/or therapeutic targets in hereditary ataxia. Hum Brain Mapp 37:3656-3668, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Convolutional neural networks for event-related potential detection: impact of the architecture.

PubMed

Cecotti, H

2017-07-01

The detection of brain responses at the single-trial level in the electroencephalogram (EEG) such as event-related potentials (ERPs) is a difficult problem that requires different processing steps to extract relevant discriminant features. While most of the signal and classification techniques for the detection of brain responses are based on linear algebra, different pattern recognition techniques such as convolutional neural network (CNN), as a type of deep learning technique, have shown some interests as they are able to process the signal after limited pre-processing. In this study, we propose to investigate the performance of CNNs in relation of their architecture and in relation to how they are evaluated: a single system for each subject, or a system for all the subjects. More particularly, we want to address the change of performance that can be observed between specifying a neural network to a subject, or by considering a neural network for a group of subjects, taking advantage of a larger number of trials from different subjects. The results support the conclusion that a convolutional neural network trained on different subjects can lead to an AUC above 0.9 by using an appropriate architecture using spatial filtering and shift invariant layers.

Cognitive control in children with learning disabilities: neuromarker for deficient executive functions.

PubMed

Alahmadi, Nsreen A

2017-08-02

The neural underpinnings of learning disabilities (LD) are still not known. Recent discussions focus over whether domain-specific and/or domain-unspecific reasons might be responsible for LD either alone or in combination with each other. This study applied standard nonverbal Go-NoGo tasks (visual continuous performance test) to LD and healthy control children to examine whether they show deficient executive functions. During this Go-NoGo task, electroencephalogram was measured in addition to reaction times, hits, omissions, and commissions to the Go and NoGo stimuli. It was shown that children with LD reacted slower with variable responses to Go stimuli and made more omission errors in comparison with the healthy control children. The analysis of the event-related potential indicated that the deficient behavior in this task is associated with smaller - and in part nonexistent - P3d amplitudes. This neural activation indicates a different neural activation pattern during action inhibition in LD children. The neural networks involved in controlling action inhibition are mostly located in frontal brain areas, for which it has been shown that children with LD show neural activation deficiencies. This is possibly a consequence of a maturational delay of the frontal cortex.

Estimating the functional dimensionality of neural representations.

PubMed

Ahlheim, Christiane; Love, Bradley C

2018-06-07

Recent advances in multivariate fMRI analysis stress the importance of information inherent to voxel patterns. Key to interpreting these patterns is estimating the underlying dimensionality of neural representations. Dimensions may correspond to psychological dimensions, such as length and orientation, or involve other coding schemes. Unfortunately, the noise structure of fMRI data inflates dimensionality estimates and thus makes it difficult to assess the true underlying dimensionality of a pattern. To address this challenge, we developed a novel approach to identify brain regions that carry reliable task-modulated signal and to derive an estimate of the signal's functional dimensionality. We combined singular value decomposition with cross-validation to find the best low-dimensional projection of a pattern of voxel-responses at a single-subject level. Goodness of the low-dimensional reconstruction is measured as Pearson correlation with a test set, which allows to test for significance of the low-dimensional reconstruction across participants. Using hierarchical Bayesian modeling, we derive the best estimate and associated uncertainty of underlying dimensionality across participants. We validated our method on simulated data of varying underlying dimensionality, showing that recovered dimensionalities match closely true dimensionalities. We then applied our method to three published fMRI data sets all involving processing of visual stimuli. The results highlight three possible applications of estimating the functional dimensionality of neural data. Firstly, it can aid evaluation of model-based analyses by revealing which areas express reliable, task-modulated signal that could be missed by specific models. Secondly, it can reveal functional differences across brain regions. Thirdly, knowing the functional dimensionality allows assessing task-related differences in the complexity of neural patterns. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Directional constraint of endpoint force emerges from hindlimb anatomy.

PubMed

Bunderson, Nathan E; McKay, J Lucas; Ting, Lena H; Burkholder, Thomas J

2010-06-15

Postural control requires the coordination of force production at the limb endpoints to apply an appropriate force to the body. Subjected to horizontal plane perturbations, quadruped limbs stereotypically produce force constrained along a line that passes near the center of mass. This phenomenon, referred to as the force constraint strategy, may reflect mechanical constraints on the limb or body, a specific neural control strategy or an interaction among neural controls and mechanical constraints. We used a neuromuscular model of the cat hindlimb to test the hypothesis that the anatomical constraints restrict the mechanical action of individual muscles during stance and constrain the response to perturbations to a line independent of perturbation direction. In a linearized neuromuscular model of the cat hindlimb, muscle lengthening directions were highly conserved across 10,000 different muscle activation patterns, each of which produced an identical, stance-like endpoint force. These lengthening directions were closely aligned with the sagittal plane and reveal an anatomical structure for directionally constrained force responses. Each of the 10,000 activation patterns was predicted to produce stable stance based on Lyapunov stability analysis. In forward simulations of the nonlinear, seven degree of freedom model under the action of 200 random muscle activation patterns, displacement of the endpoint from its equilibrium position produced restoring forces, which were also biased toward the sagittal plane. The single exception was an activation pattern based on minimum muscle stress optimization, which produced destabilizing force responses in some perturbation directions. The sagittal force constraint increased during simulations as the system shifted from an inertial response during the acceleration phase to a viscoelastic response as peak velocity was obtained. These results qualitatively match similar experimental observations and suggest that the force constraint phenomenon may result from the anatomical arrangement of the limb.

Directional constraint of endpoint force emerges from hindlimb anatomy

PubMed Central

Bunderson, Nathan E.; McKay, J. Lucas; Ting, Lena H.; Burkholder, Thomas J.

2010-01-01

Postural control requires the coordination of force production at the limb endpoints to apply an appropriate force to the body. Subjected to horizontal plane perturbations, quadruped limbs stereotypically produce force constrained along a line that passes near the center of mass. This phenomenon, referred to as the force constraint strategy, may reflect mechanical constraints on the limb or body, a specific neural control strategy or an interaction among neural controls and mechanical constraints. We used a neuromuscular model of the cat hindlimb to test the hypothesis that the anatomical constraints restrict the mechanical action of individual muscles during stance and constrain the response to perturbations to a line independent of perturbation direction. In a linearized neuromuscular model of the cat hindlimb, muscle lengthening directions were highly conserved across 10,000 different muscle activation patterns, each of which produced an identical, stance-like endpoint force. These lengthening directions were closely aligned with the sagittal plane and reveal an anatomical structure for directionally constrained force responses. Each of the 10,000 activation patterns was predicted to produce stable stance based on Lyapunov stability analysis. In forward simulations of the nonlinear, seven degree of freedom model under the action of 200 random muscle activation patterns, displacement of the endpoint from its equilibrium position produced restoring forces, which were also biased toward the sagittal plane. The single exception was an activation pattern based on minimum muscle stress optimization, which produced destabilizing force responses in some perturbation directions. The sagittal force constraint increased during simulations as the system shifted from an inertial response during the acceleration phase to a viscoelastic response as peak velocity was obtained. These results qualitatively match similar experimental observations and suggest that the force constraint phenomenon may result from the anatomical arrangement of the limb. PMID:20511528

Neural signatures of the response to emotional distraction: a review of evidence from brain imaging investigations

PubMed Central

Iordan, A. D.; Dolcos, S.; Dolcos, F.

2013-01-01

Prompt responses to emotional, potentially threatening, stimuli are supported by neural mechanisms that allow for privileged access of emotional information to processing resources. The existence of these mechanisms can also make emotional stimuli potent distracters, particularly when task-irrelevant. The ability to deploy cognitive control in order to cope with emotional distraction is essential for adaptive behavior, while reduced control may lead to enhanced emotional distractibility, which is often a hallmark of affective disorders. Evidence suggests that increased susceptibility to emotional distraction is linked to changes in the processing of emotional information that affect both the basic response to and coping with emotional distraction, but the neural correlates of these phenomena are not clear. The present review discusses emerging evidence from brain imaging studies addressing these issues, and highlights the following three aspects. First, the response to emotional distraction is associated with opposing patterns of activity in a ventral “hot” affective system (HotEmo, showing increased activity) and a dorsal “cold” executive system (ColdEx, showing decreased activity). Second, coping with emotional distraction involves top–down control in order to counteract the bottom-up influence of emotional distraction, and involves interactions between the amygdala and the prefrontal cortex. Third, both the response to and coping with emotional distraction are influenced by individual differences affecting emotional sensitivity and distractibility, which are linked to alterations of both HotEmo and ColdEx neural systems. Collectively, the available evidence identifies specific neural signatures of the response to emotional challenge, which are fundamental to understanding the mechanisms of emotion-cognition interactions in healthy functioning, and the changes linked to individual variation in emotional distractibility and susceptibility to affective disorders. PMID:23761741

The Influence of Gravito-Inertial Force on Sensorimotor Integration and Reflexive Responses

NASA Technical Reports Server (NTRS)

Curthoys, Ian S.; Guedry, Fred E.; Merfeld, Daniel M.; Watt, Doug G. D.; Tomko, David L.; Wade, Charles E. (Technical Monitor)

1994-01-01

Sensorimotor responses (e.g.. eye movements, spinal reflexes, etc depend upon the interpretation of the neural signals from the sensory systems. Since neural signals from the otoliths may represent either tilt (gravity) or translation (linear inertial force), sensory signals from the otolith organs are necessarily somewhat ambiguous. Therefore. the neural responses to changing otolith signals depend upon the context of the stimulation (e.g- active vs. passive, relative orientation of gravity, etc.) as well as upon other sensory signals (e.g., vision. canals, etc.). This session will focus upon the -role -played by the sensory signals from the otolith organs in producing efficient sensorimotor and behavioral responses. Curthoys will show the influence of the peripheral anatomy and physiology. Tomko will discuss the influence of tilt and translational otolith signals on eye movements. Merfeld will demonstrate the rate otolith organs play during the interaction of sensory signals from the canals and otoliths. Watt will show the influence of the otoliths on spinal/postural responses. Guedry will discuss the contribution of vestibular information to "path of movement"' perception and to the development of a stable vertical reference. Sensorimotor responses to the ambiguous inertial force stimulation provide an important tool to investigate how the nervous system processes patterns of sensory information and yields functional sensorimotor responses.

Self-organized adaptation of a simple neural circuit enables complex robot behaviour

NASA Astrophysics Data System (ADS)

Steingrube, Silke; Timme, Marc; Wörgötter, Florentin; Manoonpong, Poramate

2010-03-01

Controlling sensori-motor systems in higher animals or complex robots is a challenging combinatorial problem, because many sensory signals need to be simultaneously coordinated into a broad behavioural spectrum. To rapidly interact with the environment, this control needs to be fast and adaptive. Present robotic solutions operate with limited autonomy and are mostly restricted to few behavioural patterns. Here we introduce chaos control as a new strategy to generate complex behaviour of an autonomous robot. In the presented system, 18 sensors drive 18 motors by means of a simple neural control circuit, thereby generating 11 basic behavioural patterns (for example, orienting, taxis, self-protection and various gaits) and their combinations. The control signal quickly and reversibly adapts to new situations and also enables learning and synaptic long-term storage of behaviourally useful motor responses. Thus, such neural control provides a powerful yet simple way to self-organize versatile behaviours in autonomous agents with many degrees of freedom.

Creative-Dynamics Approach To Neural Intelligence

NASA Technical Reports Server (NTRS)

Zak, Michail A.

1992-01-01

Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

Repeated Ferret Odor Exposure Induces Different Temporal Patterns of Same-Stressor Habituation and Novel-Stressor Sensitization in Both Hypothalamic-Pituitary-Adrenal Axis Activity and Forebrain c-fos Expression in the Rat

PubMed Central

Weinberg, Marc S.; Bhatt, Aadra P.; Girotti, Milena; Masini, Cher V.; Day, Heidi E. W.; Campeau, Serge; Spencer, Robert L.

2009-01-01

Repeated exposure to a moderately intense stressor typically produces attenuation of the hypothalamic-pituitary-adrenal (HPA) axis response (habituation) on re-presentation of the same stressor; however, if a novel stressor is presented to the same animals, the HPA axis response may be augmented (sensitization). The extent to which this adaptation is also evident within neural activity patterns is unknown. This study tested whether repeated ferret odor (FO) exposure, a moderately intense psychological stressor for rats, leads to both same-stressor habituation and novel-stressor sensitization of the HPA axis response and neuronal activity as determined by immediate early gene induction (c-fos mRNA). Rats were presented with FO in their home cages for 30 min a day for up to 2 wk and subsequently challenged with FO or restraint. Rats displayed HPA axis activity habituation and widespread habituation of c-fos mRNA expression (in situ hybridization) throughout the brain in as few as three repeated presentations of FO. However, repeated FO exposure led to a more gradual development of sensitized HPA-axis and c-fos mRNA responses to restraint that were not fully evident until after 14 d of prior FO exposure. The sensitized response was evident in many of the same brain regions that displayed habituation, including primary sensory cortices and the prefrontal cortex. The shared spatial expression but distinct temporal development of habituation and sensitization neural response patterns suggests two independent processes with opposing influences across overlapping brain systems. PMID:18845631

Neural processing of musical meter in musicians and non-musicians.

PubMed

Zhao, T Christina; Lam, H T Gloria; Sohi, Harkirat; Kuhl, Patricia K

2017-11-01

Musical sounds, along with speech, are the most prominent sounds in our daily lives. They are highly dynamic, yet well structured in the temporal domain in a hierarchical manner. The temporal structures enhance the predictability of musical sounds. Western music provides an excellent example: while time intervals between musical notes are highly variable, underlying beats can be realized. The beat-level temporal structure provides a sense of regular pulses. Beats can be further organized into units, giving the percept of alternating strong and weak beats (i.e. metrical structure or meter). Examining neural processing at the meter level offers a unique opportunity to understand how the human brain extracts temporal patterns, predicts future stimuli and optimizes neural resources for processing. The present study addresses two important questions regarding meter processing, using the mismatch negativity (MMN) obtained with electroencephalography (EEG): 1) how tempo (fast vs. slow) and type of metrical structure (duple: two beats per unit vs. triple: three beats per unit) affect the neural processing of metrical structure in non-musically trained individuals, and 2) how early music training modulates the neural processing of metrical structure. Metrical structures were established by patterns of consecutive strong and weak tones (Standard) with occasional violations that disrupted and reset the structure (Deviant). Twenty non-musicians listened passively to these tones while their neural activities were recorded. MMN indexed the neural sensitivity to the meter violations. Results suggested that MMNs were larger for fast tempo and for triple meter conditions. Further, 20 musically trained individuals were tested using the same methods and the results were compared to the non-musicians. While tempo and meter type similarly influenced MMNs in both groups, musicians overall exhibited significantly reduced MMNs, compared to their non-musician counterparts. Further analyses indicated that the reduction was driven by responses to sounds that defined the structure (Standard), not by responses to Deviants. We argue that musicians maintain a more accurate and efficient mental model for metrical structures, which incorporates occasional disruptions using significantly fewer neural resources. Copyright © 2017 Elsevier Ltd. All rights reserved.

Tracking Deceased-Related Thinking with Neural Pattern Decoding of a Cortical-Basal Ganglia Circuit.

PubMed

Schneck, Noam; Haufe, Stefan; Tu, Tao; Bonanno, George A; Ochsner, Kevin; Sajda, Paul; Mann, J John

2017-07-01

Deceased-related thinking is central to grieving and potentially critical to processing of the loss. Self-report measurements might fail to capture important elements of deceased-related thinking and processing. Here, we used a machine learning approach applied to fMRI - known as neural decoding - to develop a measure of ongoing deceased-related processing. 23 subjects grieving the loss of a first-degree relative, spouse or partner within 14 months underwent two fMRI tasks. They first viewed pictures and stories related to the deceased, a living control and a demographic control figure while providing ongoing valence and arousal ratings. Second, they performed a 10-minute Sustained Attention to Response Task (SART) with thought probes every 25-35 seconds to identify deceased, living and self-related thoughts. A conjunction analysis, controlling for valence/arousal, identified neural clusters in basal ganglia, orbital prefrontal cortex and insula associated with both types of deceased-related stimuli vs. the two control conditions in the first task. This pattern was applied to fMRI data collected during the SART, and discriminated deceased-related but not living or self-related thoughts, independently of grief-severity and time since loss. Deceased-related thoughts on the SART correlated with self-reported avoidance. The neural model predicted avoidance over and above deceased-related thoughts. A neural pattern trained to identify mental representations of the deceased tracked deceased-related thinking during a sustained attention task and also predicted subject-level avoidance. This approach provides a new imaging tool to be used as an index of processing the deceased for future studies of complicated grief.

The challenges of neural mind-reading paradigms.

PubMed

Vilarroya, Oscar

2013-01-01

Neural mind-reading studies, based on multivariate pattern analysis (MVPA) methods, are providing exciting new studies. Some of the results obtained with these paradigms have raised high expectations, such as the possibility of creating brain reading devices. However, such hopes are based on the assumptions that: (a) the BOLD signal is a marker of neural activity; (b) the BOLD pattern identified by a MVPA is a neurally sound pattern; (c) the MVPA's feature space is a good mapping of the neural representation of a stimulus, and (d) the pattern identified by a MVPA corresponds to a representation. I examine here the challenges that still have to be met before fully accepting such assumptions.

Different Neural Processes Accompany Self-Recognition in Photographs Across the Lifespan: An ERP Study Using Dizygotic Twins

PubMed Central

Butler, David L.; Mattingley, Jason B.; Cunnington, Ross; Suddendorf, Thomas

2013-01-01

Our appearance changes over time, yet we can recognize ourselves in photographs from across the lifespan. Researchers have extensively studied self-recognition in photographs and have proposed that specific neural correlates are involved, but few studies have examined self-recognition using images from different periods of life. Here we compared ERP responses to photographs of participants when they were 5–15, 16–25, and 26–45 years old. We found marked differences between the responses to photographs from these time periods in terms of the neural markers generally assumed to reflect (i) the configural processing of faces (i.e., the N170), (ii) the matching of the currently perceived face to a representation already stored in memory (i.e., the P250), and (iii) the retrieval of information about the person being recognized (i.e., the N400). There was no uniform neural signature of visual self-recognition. To test whether there was anything specific to self-recognition in these brain responses, we also asked participants to identify photographs of their dizygotic twins taken from the same time periods. Critically, this allowed us to minimize the confounding effects of exposure, for it is likely that participants have been similarly exposed to each other's faces over the lifespan. The same pattern of neural response emerged with only one exception: the neural marker reflecting the retrieval of mnemonic information (N400) differed across the lifespan for self but not for twin. These results, as well as our novel approach using twins and photographs from across the lifespan, have wide-ranging consequences for the study of self-recognition and the nature of our personal identity through time. PMID:24069151

Different neural processes accompany self-recognition in photographs across the lifespan: an ERP study using dizygotic twins.

PubMed

Butler, David L; Mattingley, Jason B; Cunnington, Ross; Suddendorf, Thomas

2013-01-01

Our appearance changes over time, yet we can recognize ourselves in photographs from across the lifespan. Researchers have extensively studied self-recognition in photographs and have proposed that specific neural correlates are involved, but few studies have examined self-recognition using images from different periods of life. Here we compared ERP responses to photographs of participants when they were 5-15, 16-25, and 26-45 years old. We found marked differences between the responses to photographs from these time periods in terms of the neural markers generally assumed to reflect (i) the configural processing of faces (i.e., the N170), (ii) the matching of the currently perceived face to a representation already stored in memory (i.e., the P250), and (iii) the retrieval of information about the person being recognized (i.e., the N400). There was no uniform neural signature of visual self-recognition. To test whether there was anything specific to self-recognition in these brain responses, we also asked participants to identify photographs of their dizygotic twins taken from the same time periods. Critically, this allowed us to minimize the confounding effects of exposure, for it is likely that participants have been similarly exposed to each other's faces over the lifespan. The same pattern of neural response emerged with only one exception: the neural marker reflecting the retrieval of mnemonic information (N400) differed across the lifespan for self but not for twin. These results, as well as our novel approach using twins and photographs from across the lifespan, have wide-ranging consequences for the study of self-recognition and the nature of our personal identity through time.

Enhanced neural responses to rule violation in children with autism: a comparison to social exclusion.

PubMed

Bolling, Danielle Z; Pitskel, Naomi B; Deen, Ben; Crowley, Michael J; McPartland, James C; Kaiser, Martha D; Wyk, Brent C Vander; Wu, Jia; Mayes, Linda C; Pelphrey, Kevin A

2011-07-01

The present study aimed to explore the neural correlates of two characteristic deficits in autism spectrum disorders (ASD); social impairment and restricted, repetitive behavior patterns. To this end, we used comparable experiences of social exclusion and rule violation to probe potentially atypical neural networks in ASD. In children and adolescents with and without ASD, we used the interactive ball-toss game (Cyberball) to elicit social exclusion and a comparable game (Cybershape) to elicit a non-exclusive rule violation. Using functional magnetic resonance imaging (fMRI), we identified group differences in brain responses to social exclusion and rule violation. Though both groups reported equal distress following exclusion, the right insula and ventral anterior cingulate cortex were hypoactive during exclusion in children with ASD. In rule violation, right insula and dorsal prefrontal cortex were hyperactive in ASD. Right insula showed a dissociation in activation; it was hypoactive to social exclusion and hyperactive to rule violation in the ASD group. Further probed, different regions of right insula were modulated in each game, highlighting differences in regional specificity for which subsequent analyses revealed differences in patterns of functional connectivity. These results demonstrate neurobiological differences in processing social exclusion and rule violation in children with ASD.

A Method for Generating Natural and User-Defined Sniffing Patterns in Anesthetized or Reduced Preparations

PubMed Central

Carey, Ryan M.; Wachowiak, Matt

2009-01-01

Sniffing has long been thought to play a critical role in shaping neural responses to odorants at multiple levels of the nervous system. However, it has been difficult to systematically examine how particular parameters of sniffing behavior shape odorant-evoked activity, in large part because of the complexity of sniffing behavior and the difficulty in reproducing this behavior in an anesthetized or reduced preparation. Here we present a method for generating naturalistic sniffing patterns in such preparations. The method involves a nasal ventilator whose movement is controlled by an analog command voltage. The command signal may consist of intranasal pressure transients recorded from awake rats and mice or user-defined waveforms. This “sniff playback” device generates intranasal pressure and airflow transients in anesthetized animals that approximate those recorded from the awake animal and are reproducible across trials and across preparations. The device accurately reproduces command waveforms over an amplitude range of approximately 1 log unit and up to frequencies of approximately 12 Hz. Further, odorant-evoked neural activity imaged during sniff playback appears similar to that seen in awake animals. This method should prove useful in investigating how the parameters of odorant sampling shape neural responses in a variety of experimental settings. PMID:18791186

Neural Categorization of Vibrotactile Frequency in Flutter and Vibration Stimulations: An fMRI Study.

PubMed

Kim, Junsuk; Chung, Yoon Gi; Chung, Soon-Cheol; Bulthoff, Heinrich H; Kim, Sung-Phil

2016-01-01

As the use of wearable haptic devices with vibrating alert features is commonplace, an understanding of the perceptual categorization of vibrotactile frequencies has become important. This understanding can be substantially enhanced by unveiling how neural activity represents vibrotactile frequency information. Using functional magnetic resonance imaging (fMRI), this study investigated categorical clustering patterns of the frequency-dependent neural activity evoked by vibrotactile stimuli with gradually changing frequencies from 20 to 200 Hz. First, a searchlight multi-voxel pattern analysis (MVPA) was used to find brain regions exhibiting neural activities associated with frequency information. We found that the contralateral postcentral gyrus (S1) and the supramarginal gyrus (SMG) carried frequency-dependent information. Next, we applied multidimensional scaling (MDS) to find low-dimensional neural representations of different frequencies obtained from the multi-voxel activity patterns within these regions. The clustering analysis on the MDS results showed that neural activity patterns of 20-100 Hz and 120-200 Hz were divided into two distinct groups. Interestingly, this neural grouping conformed to the perceptual frequency categories found in the previous behavioral studies. Our findings therefore suggest that neural activity patterns in the somatosensory cortical regions may provide a neural basis for the perceptual categorization of vibrotactile frequency.

Neural Correlates of the Lombard Effect in Primate Auditory Cortex

PubMed Central

Eliades, Steven J.

2012-01-01

Speaking is a sensory-motor process that involves constant self-monitoring to ensure accurate vocal production. Self-monitoring of vocal feedback allows rapid adjustment to correct perceived differences between intended and produced vocalizations. One important behavior in vocal feedback control is a compensatory increase in vocal intensity in response to noise masking during vocal production, commonly referred to as the Lombard effect. This behavior requires mechanisms for continuously monitoring auditory feedback during speaking. However, the underlying neural mechanisms are poorly understood. Here we show that when marmoset monkeys vocalize in the presence of masking noise that disrupts vocal feedback, the compensatory increase in vocal intensity is accompanied by a shift in auditory cortex activity toward neural response patterns seen during vocalizations under normal feedback condition. Furthermore, we show that neural activity in auditory cortex during a vocalization phrase predicts vocal intensity compensation in subsequent phrases. These observations demonstrate that the auditory cortex participates in self-monitoring during the Lombard effect, and may play a role in the compensation of noise masking during feedback-mediated vocal control. PMID:22855821

Dissociated emergent-response system and fine-processing system in human neural network and a heuristic neural architecture for autonomous humanoid robots.

PubMed

Yan, Xiaodan

2010-01-01

The current study investigated the functional connectivity of the primary sensory system with resting state fMRI and applied such knowledge into the design of the neural architecture of autonomous humanoid robots. Correlation and Granger causality analyses were utilized to reveal the functional connectivity patterns. Dissociation was within the primary sensory system, in that the olfactory cortex and the somatosensory cortex were strongly connected to the amygdala whereas the visual cortex and the auditory cortex were strongly connected with the frontal cortex. The posterior cingulate cortex (PCC) and the anterior cingulate cortex (ACC) were found to maintain constant communication with the primary sensory system, the frontal cortex, and the amygdala. Such neural architecture inspired the design of dissociated emergent-response system and fine-processing system in autonomous humanoid robots, with separate processing units and another consolidation center to coordinate the two systems. Such design can help autonomous robots to detect and respond quickly to danger, so as to maintain their sustainability and independence.

Neural basis for recognition confidence in younger and older adults.

PubMed

Chua, Elizabeth F; Schacter, Daniel L; Sperling, Reisa A

2009-03-01

Although several studies have examined the neural basis for age-related changes in objective memory performance, less is known about how the process of memory monitoring changes with aging. The authors used functional magnetic resonance imaging to examine retrospective confidence in memory performance in aging. During low confidence, both younger and older adults showed behavioral evidence that they were guessing during recognition and that they were aware they were guessing when making confidence judgments. Similarly, both younger and older adults showed increased neural activity during low- compared to high-confidence responses in the lateral prefrontal cortex, anterior cingulate cortex, and left intraparietal sulcus. In contrast, older adults showed more high-confidence errors than younger adults. Younger adults showed greater activity for high compared to low confidence in medial temporal lobe structures, but older adults did not show this pattern. Taken together, these findings may suggest that impairments in the confidence-accuracy relationship for memory in older adults, which are often driven by high-confidence errors, may be primarily related to altered neural signals associated with greater activity for high-confidence responses.

Neural basis for recognition confidence in younger and older adults

PubMed Central

Chua, Elizabeth F.; Schacter, Daniel L.; Sperling, Reisa A.

2008-01-01

Although several studies have examined the neural basis for age-related changes in objective memory performance, less is known about how the process of memory monitoring changes with aging. We used fMRI to examine retrospective confidence in memory performance in aging. During low confidence, both younger and older adults showed behavioral evidence that they were guessing during recognition, and that they were aware they were guessing when making confidence judgments. Similarly, both younger and older adults showed increased neural activity during low compared to high confidence responses in lateral prefrontal cortex, anterior cingulate cortex, and left intraparietal sulcus. In contrast, older adults showed more high confidence errors than younger adults. Younger adults showed greater activity for high compared to low confidence in medial temporal lobe structures, but older adults did not show this pattern. Taken together, these findings may suggest that impairments in the confidence-accuracy relationship for memory in older adults, which are often driven by high confidence errors, may be primarily related to altered neural signals associated with greater activity for high confidence responses. PMID:19290745

Angle of Arrival Detection Through Artificial Neural Network Analysis of Optical Fiber Intensity Patterns

DTIC Science & Technology

1990-12-01

ARTIFICIAL NEURAL NETWORK ANALYSIS OF OPTICAL FIBER INTENSITY PATTERNS THESIS Scott Thomas Captain, USAF AFIT/GE/ENG/90D-62 DTIC...ELECTE ao • JAN08 1991 Approved for public release; distribution unlimited. AFIT/GE/ENG/90D-62 ANGLE OF ARRIVAL DETECTION THROUGH ARTIFICIAL NEURAL NETWORK ANALYSIS... ARTIFICIAL NEURAL NETWORK ANALYSIS OF OPTICAL FIBER INTENSITY PATTERNS L Introduction The optical sensors of United States Air Force reconnaissance

An Electrophysiological Index of Perceptual Goodness

PubMed Central

Makin, Alexis D.J.; Wright, Damien; Rampone, Giulia; Palumbo, Letizia; Guest, Martin; Sheehan, Rhiannon; Cleaver, Helen; Bertamini, Marco

2016-01-01

A traditional line of work starting with the Gestalt school has shown that patterns vary in strength and salience; a difference in “Perceptual goodness.” The Holographic weight of evidence model quantifies goodness of visual regularities. The key formula states that W = E/N, where E is number of holographic identities in a pattern and N is number of elements. We tested whether W predicts the amplitude of the neural response to regularity in an extrastriate symmetry-sensitive network. We recorded an Event Related Potential (ERP) generated by symmetry called the Sustained Posterior Negativity (SPN). First, we reanalyzed the published work and found that W explained most variance in SPN amplitude. Then in four new studies, we confirmed specific predictions of the holographic model regarding 1) the differential effects of numerosity on reflection and repetition, 2) the similarity between reflection and Glass patterns, 3) multiple symmetries, and 4) symmetry and anti-symmetry. In all cases, the holographic approach predicted SPN amplitude remarkably well; particularly in an early window around 300–400 ms post stimulus onset. Although the holographic model was not conceived as a model of neural processing, it captures many details of the brain response to symmetry. PMID:27702812

A neuroanatomically grounded Hebbian-learning model of attention–language interactions in the human brain

PubMed Central

Garagnani, Max; Wennekers, Thomas; Pulvermüller, Friedemann

2008-01-01

Meaningful familiar stimuli and senseless unknown materials lead to different patterns of brain activation. A late major neurophysiological response indexing ‘sense’ is the negative component of event-related potential peaking at around 400 ms (N400), an event-related potential that emerges in attention-demanding tasks and is larger for senseless materials (e.g. meaningless pseudowords) than for matched meaningful stimuli (words). However, the mismatch negativity (latency 100–250 ms), an early automatic brain response elicited under distraction, is larger to words than to pseudowords, thus exhibiting the opposite pattern to that seen for the N400. So far, no theoretical account has been able to reconcile and explain these findings by means of a single, mechanistic neural model. We implemented a neuroanatomically grounded neural network model of the left perisylvian language cortex and simulated: (i) brain processes of early language acquisition and (ii) cortical responses to familiar word and senseless pseudoword stimuli. We found that variation of the area-specific inhibition (the model correlate of attention) modulated the simulated brain response to words and pseudowords, producing either an N400- or a mismatch negativity-like response depending on the amount of inhibition (i.e. available attentional resources). Our model: (i) provides a unifying explanatory account, at cortical level, of experimental observations that, so far, had not been given a coherent interpretation within a single framework; (ii) demonstrates the viability of purely Hebbian, associative learning in a multilayered neural network architecture; and (iii) makes clear predictions on the effects of attention on latency and magnitude of event-related potentials to lexical items. Such predictions have been confirmed by recent experimental evidence. PMID:18215243

Chronic stress and neural function: accounting for sex and age.

PubMed

Luine, V N; Beck, K D; Bowman, R E; Frankfurt, M; Maclusky, N J

2007-10-01

Cognitive responses to stress follow the temporally dependent pattern originally established by Selye (1) wherein short-term stressors elicit adaptive responses whereas continued stress (chronic) results in maladaptive changes--deleterious effects on physiological systems and impaired cognition. However, this pattern for cognitive effects appears to apply to only half the population (males) and, more specifically, to young, adult males. Females show different cognitive responses to stress. In contrast to impaired cognition in males after chronic stress, female rodents show enhanced performance on the same memory tasks after the same stress. Not only cognition, but anxiety, shows sex-dependent changes following chronic stress--stress is anxiolytic in males and anxiogenic in females. Moreover, behavioral responses to chronic stress are different in developing as well as aging subjects (both sexes) as compared to adults. In aged rats, chronic stress enhances recognition memory in both sexes, does not alter spatial memory, and anxiety effects are opposite to young adults. When pregnant dams are exposed to chronic stress, at adulthood the offspring display yet different consequences of stress on anxiety and cognition, and, in contrast to adulthood when the behavioral effects of stress are reversible, prenatal stress effects appear enduring. Changing levels of estradiol in the sexes over the lifespan appear to contribute to the differences in response to stress. Thus, theories of stress dependent modulations in CNS function--developed solely in male models, focused on peripheral physiological processes and tested in adults--may require revision when applied to a more diverse population (age- and sex-wise) at least in relation to the neural functions of cognition and anxiety. Moreover, these results suggest that other stressors and neural functions should be investigated to determine whether age, sex and gonadal hormones also have an impact.

Changes in pitch height elicit both language universal and language dependent changes in neural representation of pitch in the brainstem and auditory cortex

PubMed Central

Krishnan, Ananthanarayan; Suresh, Chandan H.; Gandour, Jackson T.

2017-01-01

Language experience shapes encoding of pitch-relevant information at both brainstem and cortical levels of processing. Pitch height is a salient dimension that orders pitch from low to high. Herein we investigate the effects of language experience (Chinese, English) in the brainstem and cortex on i) neural responses to variations in pitch height, ii) presence of asymmetry in cortical pitch representation, and iii) patterns of relative changes in magnitude of pitch height between these two levels of brain structure. Stimuli were three nonspeech homologs of Mandarin Tone 2 varying in pitch height only. The frequency-following response (FFR) and the cortical pitch-specific response (CPR) were recorded concurrently. At the Fz-linked T7/T8 site, peak latency of Na, Pb, and Nb decreased with increasing pitch height for both groups. Peak-to-peak amplitude of Na–Pb and Pb–Nb increased with increasing pitch height across groups. A language-dependent effect was restricted to Na-Pb; the Chinese had larger amplitude than the English group. At temporal sites (T7/T8), the Chinese group had larger amplitude, as compared to English, across stimuli, but also limited to the Na-Pb component and right temporal site. In the brainstem, F0 magnitude decreased with increasing pitch height; Chinese had larger magnitude across stimuli. A comparison of CPR and FFR responses revealed distinct patterns of relative changes in magnitude common to both groups. CPR amplitude increased and FFR amplitude decreased with increasing pitch height. Experience-dependent effects on CPR components vary as a function of neural sensitivity to pitch height within a particular temporal window (Na–Pb). Differences between the auditory brainstem and cortex imply distinct neural mechanisms for pitch extraction at both levels of brain structure. PMID:28108254

Changes in pitch height elicit both language-universal and language-dependent changes in neural representation of pitch in the brainstem and auditory cortex.

PubMed

Krishnan, Ananthanarayan; Suresh, Chandan H; Gandour, Jackson T

2017-03-27

Language experience shapes encoding of pitch-relevant information at both brainstem and cortical levels of processing. Pitch height is a salient dimension that orders pitch from low to high. Herein we investigate the effects of language experience (Chinese, English) in the brainstem and cortex on (i) neural responses to variations in pitch height, (ii) presence of asymmetry in cortical pitch representation, and (iii) patterns of relative changes in magnitude of pitch height between these two levels of brain structure. Stimuli were three nonspeech homologs of Mandarin Tone 2 varying in pitch height only. The frequency-following response (FFR) and the cortical pitch-specific response (CPR) were recorded concurrently. At the Fz-linked T7/T8 site, peak latency of Na, Pb, and Nb decreased with increasing pitch height for both groups. Peak-to-peak amplitude of Na-Pb and Pb-Nb increased with increasing pitch height across groups. A language-dependent effect was restricted to Na-Pb; the Chinese had larger amplitude than the English group. At temporal sites (T7/T8), the Chinese group had larger amplitude, as compared to English, across stimuli, but also limited to the Na-Pb component and right temporal site. In the brainstem, F0 magnitude decreased with increasing pitch height; Chinese had larger magnitude across stimuli. A comparison of CPR and FFR responses revealed distinct patterns of relative changes in magnitude common to both groups. CPR amplitude increased and FFR amplitude decreased with increasing pitch height. Experience-dependent effects on CPR components vary as a function of neural sensitivity to pitch height within a particular temporal window (Na-Pb). Differences between the auditory brainstem and cortex imply distinct neural mechanisms for pitch extraction at both levels of brain structure. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Neural Tuning to Numerosity Relates to Perceptual Tuning in 3-6-Year-Old Children.

PubMed

Kersey, Alyssa J; Cantlon, Jessica F

2017-01-18

Neural representations of approximate numerical value, or numerosity, have been observed in the intraparietal sulcus (IPS) in monkeys and humans, including children. Using functional magnetic resonance imaging, we show that children as young as 3-4 years old exhibit neural tuning to cardinal numerosities in the IPS and that their neural responses are accounted for by a model of numerosity coding that has been used to explain neural responses in the adult IPS. We also found that the sensitivity of children's neural tuning to number in the right IPS was comparable to their numerical discrimination sensitivity observed behaviorally, outside of the scanner. Children's neural tuning curves in the right IPS were significantly sharper than in the left IPS, indicating that numerical representations are more precise and mature more rapidly in the right hemisphere than in the left. Further, we show that children's perceptual sensitivity to numerosity can be predicted by the development of their neural sensitivity to numerosity. This research provides novel evidence of developmental continuity in the neural code underlying numerical representation and demonstrates that children's neural sensitivity to numerosity is related to their cognitive development. Here we test for the existence of neural tuning to numerosity in the developing brain in the youngest sample of children tested with fMRI to date. Although previous research shows evidence of numerical distance effects in the intraparietal sulcus of the developing brain, those effects could be explained by patterns of neural activity that do not represent neural tuning to numerosity. These data provide the first robust evidence that from as early as 3-4 years of age there is developmental continuity in how the intraparietal sulcus represents the values of numerosities. Moreover, the study goes beyond previous research by examining the relation between neural tuning and perceptual tuning in children. Copyright © 2017 the authors 0270-6474/17/370512-11$15.00/0.

What Neural Substrates Trigger the Adept Scientific Pattern Discovery by Biologists?

ERIC Educational Resources Information Center

Lee, Jun-Ki; Kwon, Yong-Ju

2011-01-01

This study investigated the neural correlates of experts and novices during biological object pattern detection using an fMRI approach in order to reveal the neural correlates of a biologist's superior pattern discovery ability. Sixteen healthy male participants (8 biologists and 8 non-biologists) volunteered for the study. Participants were shown…

Feedback Enhances Feedforward Figure-Ground Segmentation by Changing Firing Mode

PubMed Central

Supèr, Hans; Romeo, August

2011-01-01

In the visual cortex, feedback projections are conjectured to be crucial in figure-ground segregation. However, the precise function of feedback herein is unclear. Here we tested a hypothetical model of reentrant feedback. We used a previous developed 2-layered feedforwardspiking network that is able to segregate figure from ground and included feedback connections. Our computer model data show that without feedback, neurons respond with regular low-frequency (∼9 Hz) bursting to a figure-ground stimulus. After including feedback the firing pattern changed into a regular (tonic) spiking pattern. In this state, we found an extra enhancement of figure responses and a further suppression of background responses resulting in a stronger figure-ground signal. Such push-pull effect was confirmed by comparing the figure-ground responses withthe responses to a homogenous texture. We propose that feedback controlsfigure-ground segregation by influencing the neural firing patterns of feedforward projecting neurons. PMID:21738747

Feedback enhances feedforward figure-ground segmentation by changing firing mode.

PubMed

Supèr, Hans; Romeo, August

2011-01-01

In the visual cortex, feedback projections are conjectured to be crucial in figure-ground segregation. However, the precise function of feedback herein is unclear. Here we tested a hypothetical model of reentrant feedback. We used a previous developed 2-layered feedforward spiking network that is able to segregate figure from ground and included feedback connections. Our computer model data show that without feedback, neurons respond with regular low-frequency (∼9 Hz) bursting to a figure-ground stimulus. After including feedback the firing pattern changed into a regular (tonic) spiking pattern. In this state, we found an extra enhancement of figure responses and a further suppression of background responses resulting in a stronger figure-ground signal. Such push-pull effect was confirmed by comparing the figure-ground responses with the responses to a homogenous texture. We propose that feedback controls figure-ground segregation by influencing the neural firing patterns of feedforward projecting neurons.

Neural Processing of Facial Identity and Emotion in Infants at High-Risk for Autism Spectrum Disorders

PubMed Central

Fox, Sharon E.; Wagner, Jennifer B.; Shrock, Christine L.; Tager-Flusberg, Helen; Nelson, Charles A.

2013-01-01

Deficits in face processing and social impairment are core characteristics of autism spectrum disorder. The present work examined 7-month-old infants at high-risk for developing autism and typically developing controls at low-risk, using a face perception task designed to differentiate between the effects of face identity and facial emotions on neural response using functional Near-Infrared Spectroscopy. In addition, we employed independent component analysis, as well as a novel method of condition-related component selection and classification to identify group differences in hemodynamic waveforms and response distributions associated with face and emotion processing. The results indicate similarities of waveforms, but differences in the magnitude, spatial distribution, and timing of responses between groups. These early differences in local cortical regions and the hemodynamic response may, in turn, contribute to differences in patterns of functional connectivity. PMID:23576966

A Neural Mechanism of Social Categorization.

PubMed

Stolier, Ryan M; Freeman, Jonathan B

2017-06-07

Humans readily sort one another into multiple social categories from mere facial features. However, the facial features used to do so are not always clear-cut because they can be associated with opponent categories (e.g., feminine male face). Recently, computational models and behavioral studies have provided indirect evidence that categorizing such faces is accomplished through dynamic competition between parallel, coactivated social categories that resolve into a stable categorical percept. Using a novel paradigm combining fMRI with real-time hand tracking, the present study examined how the brain translates diverse social cues into categorical percepts. Participants (male and female) categorized faces varying in gender and racial typicality. When categorizing atypical faces, participants' hand movements were simultaneously attracted toward the unselected category response, indexing the degree to which such faces activated the opposite category in parallel. Multivoxel pattern analyses (MVPAs) provided evidence that such social category coactivation manifested in neural patterns of the right fusiform cortex. The extent to which the hand was simultaneously attracted to the opposite gender or race category response option corresponded to increased neural pattern similarity with the average pattern associated with that category, which in turn associated with stronger engagement of the dorsal anterior cingulate cortex. The findings point to a model of social categorization in which occasionally conflicting facial features are resolved through competition between coactivated ventral-temporal cortical representations with the assistance of conflict-monitoring regions. More broadly, the results offer a promising multimodal paradigm to investigate the neural basis of "hidden", temporarily active representations in the service of a broad range of cognitive processes. SIGNIFICANCE STATEMENT Individuals readily sort one another into social categories (e.g., sex, race), which have important consequences for a variety of interpersonal behaviors. However, individuals routinely encounter faces that contain diverse features associated with multiple categories (e.g., feminine male face). Using a novel paradigm combining neuroimaging with hand tracking, the present research sought to address how the brain comes to arrive at stable social categorizations from multiple social cues. The results provide evidence that opponent social categories coactivate in face-processing regions, which compete and may resolve into an eventual stable categorization with the assistance of conflict-monitoring regions. Therefore, the findings provide a neural mechanism through which the brain may translate inherently diverse social cues into coherent categorizations of other people. Copyright © 2017 the authors 0270-6474/17/375711-11$15.00/0.

Neural Decoding Reveals Impaired Face Configural Processing in the Right Fusiform Face Area of Individuals with Developmental Prosopagnosia

PubMed Central

Zhang, Jiedong; Liu, Jia

2015-01-01

Most of human daily social interactions rely on the ability to successfully recognize faces. Yet ∼2% of the human population suffers from face blindness without any acquired brain damage [this is also known as developmental prosopagnosia (DP) or congenital prosopagnosia]). Despite the presence of severe behavioral face recognition deficits, surprisingly, a majority of DP individuals exhibit normal face selectivity in the right fusiform face area (FFA), a key brain region involved in face configural processing. This finding, together with evidence showing impairments downstream from the right FFA in DP individuals, has led some to argue that perhaps the right FFA is largely intact in DP individuals. Using fMRI multivoxel pattern analysis, here we report the discovery of a neural impairment in the right FFA of DP individuals that may play a critical role in mediating their face-processing deficits. In seven individuals with DP, we discovered that, despite the right FFA's preference for faces and it showing decoding for the different face parts, it exhibited impaired face configural decoding and did not contain distinct neural response patterns for the intact and the scrambled face configurations. This abnormality was not present throughout the ventral visual cortex, as normal neural decoding was found in an adjacent object-processing region. To our knowledge, this is the first direct neural evidence showing impaired face configural processing in the right FFA in individuals with DP. The discovery of this neural impairment provides a new clue to our understanding of the neural basis of DP. PMID:25632131

Optimization of Training Sets For Neural-Net Processing of Characteristic Patterns From Vibrating Solids

NASA Technical Reports Server (NTRS)

Decker, Arthur J. (Inventor)

2006-01-01

An artificial neural network is disclosed that processes holography generated characteristic pattern of vibrating structures along with finite-element models. The present invention provides for a folding operation for conditioning training sets for optimally training forward-neural networks to process characteristic fringe pattern. The folding pattern increases the sensitivity of the feed-forward network for detecting changes in the characteristic pattern The folding routine manipulates input pixels so as to be scaled according to the location in an intensity range rather than the position in the characteristic pattern.

Frequency tagging to track the neural processing of contrast in fast, continuous sound sequences.

PubMed

Nozaradan, Sylvie; Mouraux, André; Cousineau, Marion

2017-07-01

The human auditory system presents a remarkable ability to detect rapid changes in fast, continuous acoustic sequences, as best illustrated in speech and music. However, the neural processing of rapid auditory contrast remains largely unclear, probably due to the lack of methods to objectively dissociate the response components specifically related to the contrast from the other components in response to the sequence of fast continuous sounds. To overcome this issue, we tested a novel use of the frequency-tagging approach allowing contrast-specific neural responses to be tracked based on their expected frequencies. The EEG was recorded while participants listened to 40-s sequences of sounds presented at 8Hz. A tone or interaural time contrast was embedded every fifth sound (AAAAB), such that a response observed in the EEG at exactly 8 Hz/5 (1.6 Hz) or harmonics should be the signature of contrast processing by neural populations. Contrast-related responses were successfully identified, even in the case of very fine contrasts. Moreover, analysis of the time course of the responses revealed a stable amplitude over repetitions of the AAAAB patterns in the sequence, except for the response to perceptually salient contrasts that showed a buildup and decay across repetitions of the sounds. Overall, this new combination of frequency-tagging with an oddball design provides a valuable complement to the classic, transient, evoked potentials approach, especially in the context of rapid auditory information. Specifically, we provide objective evidence on the neural processing of contrast embedded in fast, continuous sound sequences. NEW & NOTEWORTHY Recent theories suggest that the basis of neurodevelopmental auditory disorders such as dyslexia might be an impaired processing of fast auditory changes, highlighting how the encoding of rapid acoustic information is critical for auditory communication. Here, we present a novel electrophysiological approach to capture in humans neural markers of contrasts in fast continuous tone sequences. Contrast-specific responses were successfully identified, even for very fine contrasts, providing direct insight on the encoding of rapid auditory information. Copyright © 2017 the American Physiological Society.

Dlx proteins position the neural plate border and determine adjacent cell fates.

PubMed

Woda, Juliana M; Pastagia, Julie; Mercola, Mark; Artinger, Kristin Bruk

2003-01-01

The lateral border of the neural plate is a major source of signals that induce primary neurons, neural crest cells and cranial placodes as well as provide patterning cues to mesodermal structures such as somites and heart. Whereas secreted BMP, FGF and Wnt proteins influence the differentiation of neural and non-neural ectoderm, we show here that members of the Dlx family of transcription factors position the border between neural and non-neural ectoderm and are required for the specification of adjacent cell fates. Inhibition of endogenous Dlx activity in Xenopus embryos with an EnR-Dlx homeodomain fusion protein expands the neural plate into non-neural ectoderm tissue whereas ectopic activation of Dlx target genes inhibits neural plate differentiation. Importantly, the stereotypic pattern of border cell fates in the adjacent ectoderm is re-established only under conditions where the expanded neural plate abuts Dlx-positive non-neural ectoderm. Experiments in which presumptive neural plate was grafted to ventral ectoderm reiterate induction of neural crest and placodal lineages and also demonstrate that Dlx activity is required in non-neural ectoderm for the production of signals needed for induction of these cells. We propose that Dlx proteins regulate intercellular signaling across the interface between neural and non-neural ectoderm that is critical for inducing and patterning adjacent cell fates.

Beyond sensory images: Object-based representation in the human ventral pathway

PubMed Central

Pietrini, Pietro; Furey, Maura L.; Ricciardi, Emiliano; Gobbini, M. Ida; Wu, W.-H. Carolyn; Cohen, Leonardo; Guazzelli, Mario; Haxby, James V.

2004-01-01

We investigated whether the topographically organized, category-related patterns of neural response in the ventral visual pathway are a representation of sensory images or a more abstract representation of object form that is not dependent on sensory modality. We used functional MRI to measure patterns of response evoked during visual and tactile recognition of faces and manmade objects in sighted subjects and during tactile recognition in blind subjects. Results showed that visual and tactile recognition evoked category-related patterns of response in a ventral extrastriate visual area in the inferior temporal gyrus that were correlated across modality for manmade objects. Blind subjects also demonstrated category-related patterns of response in this “visual” area, and in more ventral cortical regions in the fusiform gyrus, indicating that these patterns are not due to visual imagery and, furthermore, that visual experience is not necessary for category-related representations to develop in these cortices. These results demonstrate that the representation of objects in the ventral visual pathway is not simply a representation of visual images but, rather, is a representation of more abstract features of object form. PMID:15064396

Glomerular Activity Patterns Evoked by Natural Odor Objects in the Rat Olfactory Bulb Are Related to Patterns Evoked by Major Odorant Components

PubMed Central

Johnson, Brett A.; Ong, Joan; Leon, Michael

2014-01-01

To determine how responses evoked by natural odorant mixtures compare to responses evoked by individual odorant chemicals, we mapped 2-deoxyglucose uptake during exposures to vapors arising from a variety of odor objects that may be important to rodents in the wild. We studied 21 distinct natural odor stimuli ranging from possible food sources such as fruits, vegetables, and meats to environmental odor objects such as grass, herbs, and tree leaves. The natural odor objects evoked robust and surprisingly focal patterns of 2-deoxyglucose uptake involving clusters of neighboring glomeruli, thereby resembling patterns evoked by pure chemicals. Overall, the patterns were significantly related to patterns evoked by monomolecular odorant components that had been studied previously. Object patterns also were significantly related to the molecular features present in the mixture components. Despite these overall relationships, there were individual examples of object patterns that were simpler than might have been predicted given the multiplicity of components present in the vapors. In these cases, the object patterns lacked certain responses evoked by their major odorant mixture components. These data suggest the possibility of mixture response interactions and provide a foundation for understanding the neural coding of natural odor stimuli. PMID:20187145

Insights into the mechanisms underlying colonic motor patterns

PubMed Central

Dinning, Phil G.; Brookes, Simon J.; Costa, Marcello

2016-01-01

Abstract In recent years there have been significant technical and methodological advances in our ability to record the movements of the gastrointestinal tract. This has led to significant changes in our understanding of the different types of motor patterns that exist in the gastrointestinal tract (particularly the large intestine) and in our understanding of the mechanisms underlying their generation. Compared with other tubular smooth muscle organs, a rich variety of motor patterns occurs in the large intestine. This reflects a relatively autonomous nervous system in the gut wall, which has its own unique population of sensory neurons. Although the enteric nervous system can function independently of central neural inputs, under physiological conditions bowel motility is influenced by the CNS: if spinal pathways are disrupted, deficits in motility occur. The combination of high resolution manometry and video imaging has improved our knowledge of the range of motor patterns and provided some insight into the neural and mechanical factors underlying propulsion of contents. The neural circuits responsible for the generation of peristalsis and colonic migrating motor complexes have now been identified to lie within the myenteric plexus and do not require inputs from the mucosa or submucosal ganglia for their generation, but can be modified by their activity. This review will discuss the recent advances in our understanding of the different patterns of propagating motor activity in the large intestine of mammals and how latest technologies have led to major changes in our understanding of the mechanisms underlying their generation. PMID:26990133

Responses of single cells in cat visual cortex to prolonged stimulus movement: neural correlates of visual aftereffects.

PubMed

Vautin, R G; Berkley, M A

1977-09-01

1. The activity of single cortical cells in area 17 of anesthetized and unanesthetized cats was recorded in response to prolonged stimulation with moving stimuli. 2. Under the appropriate conditions, all cells observed showed a progressive response decrement during the stimulation period, regardless of cell classification, i.e., simple, complex, or hypercomplex. 3. The observed response decrement was shown to be largely cortical in origin and could be adequately described with an exponential function of the form R = Rf +(R1-Rf)e-t/T. Time constants derived from such calculations yielded values ranging from 1.92 to 12.45 s under conditions of optimal-stimulation. 4. Most cells showed poststimulation effects, usually a brief period of reduced responsiveness that recovered exponentially. Recovery was essentially complete in about 5-35 s. 5. The degree to which stimuli were effective at inducing response was shown to have significant effects on the magnitude of the response decrement. 6. Several cells showed neural patterns of response and recovery that suggested the operation of intracortical inhibitory mechanisms. 7. A simple two-process model that adequately describes the behavior of all the studied cells is presented. 8. Because the properties of the cells studied correlate well with human psychophysical measures of contour and movement adaptation and recovery, a causal relationship to similar neural mechanisms in humans is suggested.

Neural evidence of motivational conflict between social values.

PubMed

Leszkowicz, Emilia; Linden, David E J; Maio, Gregory R; Ihssen, Niklas

2017-10-01

Motivational interdependence is an organizing principle in Schwartz's circumplex model of social values, which has received abundant cross-cultural support. We used fMRI to test whether motivational relations between social values predict different brain responses in a situation of choice between values. We hypothesized that differences in brain responses would become evident when the more important value had to be selected in pairs of congruent (e.g., wealth and success) as opposed to incongruent (e.g., curiosity and stability) values as they are described in Schwartz's model, because the former serve mutually facilitating motives, whereas the latter serve mutually inhibiting motives. Consistent with the model, choosing between congruent values led to longer response times and more activation in conflict-related brain regions (e.g., the supplementary motor area, dorsolateral prefrontal cortex) than selecting between incongruent values. These results provide novel neural evidence supporting the circumplex model's predictions about motivational interdependence between social values. In particular, our results show that the neural networks underlying social values are organized in a way that allows activation patterns related to motivational similarity between congruent values to be dissociated from those related to incongruent values.

Modeling Anterior Development in Mice: Diet as Modulator of Risk for Neural Tube Defects

PubMed Central

Kappen, Claudia

2014-01-01

Head morphogenesis is a complex process that is controlled by multiple signaling centers. The most common defects of cranial development are craniofacial defects, such as cleft lip and cleft palate, and neural tube defects, such as anencephaly and encephalocoele in humans. More than 400 genes that contribute to proper neural tube closure have been identified in experimental animals, but only very few causative gene mutations have been identified in humans, supporting the notion that environmental influences are critical. The intrauterine environment is influenced by maternal nutrition, and hence, maternal diet can modulate the risk for cranial and neural tube defects. This article reviews recent progress toward a better understanding of nutrients during pregnancy, with particular focus on mouse models for defective neural tube closure. At least four major patterns of nutrient responses are apparent, suggesting that multiple pathways are involved in the response, and likely in the underlying pathogenesis of the defects. Folic acid has been the most widely studied nutrient, and the diverse responses of the mouse models to folic acid supplementation indicate that folic acid is not universally beneficial, but that the effect is dependent on genetic configuration. If this is the case for other nutrients as well, efforts to prevent neural tube defects with nutritional supplementation may need to become more specifically targeted than previously appreciated. Mouse models are indispensable for a better understanding of nutrient–gene interactions in normal pregnancies, as well as in those affected by metabolic diseases, such as diabetes and obesity. PMID:24124024

External motivation to avoid prejudice alters neural responses to targets varying in race and status

PubMed Central

Mattan, Bradley D; Kubota, Jennifer T; Dang, Tzipporah P

2018-01-01

Abstract Those who are high in external motivation to respond without prejudice (EMS) tend to focus on non-racial attributes when describing others. This fMRI study examined the neural processing of race and an alternative yet stereotypically relevant attribute (viz., socioeconomic status: SES) as a function of the perceiver’s EMS. Sixty-one White participants privately formed impressions of Black and White faces ascribed with high or low SES. Analyses focused on regions supporting race- and status-based reward/salience (NAcc), evaluation (VMPFC) and threat/relevance (amygdala). Consistent with previous findings from the literature on status-based evaluation, we observed greater neural responses to high-status (vs low-status) targets in all regions of interest when participants were relatively low in EMS. In contrast, we observed the opposite pattern when participants were relatively high in EMS. Notably, all effects were independent of target race. In summary, White perceivers’ race-related motivations similarly altered their neural responses to the SES of Black and White targets. Specifically, the findings suggest that EMS may attenuate the positive value and/or salience of high status in a mixed-race context. Findings are discussed in the context of the stereotypic relationship between race and SES. PMID:29077925

Spiking Neurons for Analysis of Patterns

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance

2008-01-01

Artificial neural networks comprising spiking neurons of a novel type have been conceived as improved pattern-analysis and pattern-recognition computational systems. These neurons are represented by a mathematical model denoted the state-variable model (SVM), which among other things, exploits a computational parallelism inherent in spiking-neuron geometry. Networks of SVM neurons offer advantages of speed and computational efficiency, relative to traditional artificial neural networks. The SVM also overcomes some of the limitations of prior spiking-neuron models. There are numerous potential pattern-recognition, tracking, and data-reduction (data preprocessing) applications for these SVM neural networks on Earth and in exploration of remote planets. Spiking neurons imitate biological neurons more closely than do the neurons of traditional artificial neural networks. A spiking neuron includes a central cell body (soma) surrounded by a tree-like interconnection network (dendrites). Spiking neurons are so named because they generate trains of output pulses (spikes) in response to inputs received from sensors or from other neurons. They gain their speed advantage over traditional neural networks by using the timing of individual spikes for computation, whereas traditional artificial neurons use averages of activity levels over time. Moreover, spiking neurons use the delays inherent in dendritic processing in order to efficiently encode the information content of incoming signals. Because traditional artificial neurons fail to capture this encoding, they have less processing capability, and so it is necessary to use more gates when implementing traditional artificial neurons in electronic circuitry. Such higher-order functions as dynamic tasking are effected by use of pools (collections) of spiking neurons interconnected by spike-transmitting fibers. The SVM includes adaptive thresholds and submodels of transport of ions (in imitation of such transport in biological neurons). These features enable the neurons to adapt their responses to high-rate inputs from sensors, and to adapt their firing thresholds to mitigate noise or effects of potential sensor failure. The mathematical derivation of the SVM starts from a prior model, known in the art as the point soma model, which captures all of the salient properties of neuronal response while keeping the computational cost low. The point-soma latency time is modified to be an exponentially decaying function of the strength of the applied potential. Choosing computational efficiency over biological fidelity, the dendrites surrounding a neuron are represented by simplified compartmental submodels and there are no dendritic spines. Updates to the dendritic potential, calcium-ion concentrations and conductances, and potassium-ion conductances are done by use of equations similar to those of the point soma. Diffusion processes in dendrites are modeled by averaging among nearest-neighbor compartments. Inputs to each of the dendritic compartments come from sensors. Alternatively or in addition, when an affected neuron is part of a pool, inputs can come from other spiking neurons. At present, SVM neural networks are implemented by computational simulation, using algorithms that encode the SVM and its submodels. However, it should be possible to implement these neural networks in hardware: The differential equations for the dendritic and cellular processes in the SVM model of spiking neurons map to equivalent circuits that can be implemented directly in analog very-large-scale integrated (VLSI) circuits.

Abnormal neural hierarchy in processing of verbal information in patients with schizophrenia.

PubMed

Lerner, Yulia; Bleich-Cohen, Maya; Solnik-Knirsh, Shimrit; Yogev-Seligmann, Galit; Eisenstein, Tamir; Madah, Waheed; Shamir, Alon; Hendler, Talma; Kremer, Ilana

2018-01-01

Previous research indicates abnormal comprehension of verbal information in patients with schizophrenia. Yet the neural mechanism underlying the breakdown of verbal information processing in schizophrenia is poorly understood. Imaging studies in healthy populations have shown a network of brain areas involved in hierarchical processing of verbal information over time. Here, we identified critical aspects of this hierarchy, examining patients with schizophrenia. Using functional magnetic resonance imaging, we examined various levels of information comprehension elicited by naturally presented verbal stimuli; from a set of randomly shuffled words to an intact story. Specifically, patients with first episode schizophrenia ( N  = 15), their non-manifesting siblings ( N  = 14) and healthy controls ( N  = 15) listened to a narrated story and randomly scrambled versions of it. To quantify the degree of dissimilarity between the groups, we adopted an inter-subject correlation (inter-SC) approach, which estimates differences in synchronization of neural responses within and between groups. The temporal topography found in healthy and siblings groups were consistent with our previous findings - high synchronization in responses from early sensory toward high order perceptual and cognitive areas. In patients with schizophrenia, stimuli with short and intermediate temporal scales evoked a typical pattern of reliable responses, whereas story condition (long temporal scale) revealed robust and widespread disruption of the inter-SCs. In addition, the more similar the neural activity of patients with schizophrenia was to the average response in the healthy group, the less severe the positive symptoms of the patients. Our findings suggest that system-level neural indication of abnormal verbal information processing in schizophrenia reflects disease manifestations.

Dynamic neural activity during stress signals resilient coping

PubMed Central

Sinha, Rajita; Lacadie, Cheryl M.; Constable, R. Todd; Seo, Dongju

2016-01-01

Active coping underlies a healthy stress response, but neural processes supporting such resilient coping are not well-known. Using a brief, sustained exposure paradigm contrasting highly stressful, threatening, and violent stimuli versus nonaversive neutral visual stimuli in a functional magnetic resonance imaging (fMRI) study, we show significant subjective, physiologic, and endocrine increases and temporally related dynamically distinct patterns of neural activation in brain circuits underlying the stress response. First, stress-specific sustained increases in the amygdala, striatum, hypothalamus, midbrain, right insula, and right dorsolateral prefrontal cortex (DLPFC) regions supported the stress processing and reactivity circuit. Second, dynamic neural activation during stress versus neutral runs, showing early increases followed by later reduced activation in the ventrolateral prefrontal cortex (VLPFC), dorsal anterior cingulate cortex (dACC), left DLPFC, hippocampus, and left insula, suggested a stress adaptation response network. Finally, dynamic stress-specific mobilization of the ventromedial prefrontal cortex (VmPFC), marked by initial hypoactivity followed by increased VmPFC activation, pointed to the VmPFC as a key locus of the emotional and behavioral control network. Consistent with this finding, greater neural flexibility signals in the VmPFC during stress correlated with active coping ratings whereas lower dynamic activity in the VmPFC also predicted a higher level of maladaptive coping behaviors in real life, including binge alcohol intake, emotional eating, and frequency of arguments and fights. These findings demonstrate acute functional neuroplasticity during stress, with distinct and separable brain networks that underlie critical components of the stress response, and a specific role for VmPFC neuroflexibility in stress-resilient coping. PMID:27432990

Muscle synergies evoked by microstimulation are preferentially encoded during behavior

PubMed Central

Overduin, Simon A.; d'Avella, Andrea; Carmena, Jose M.; Bizzi, Emilio

2014-01-01

Electrical microstimulation studies provide some of the most direct evidence for the neural representation of muscle synergies. These synergies, i.e., coordinated activations of groups of muscles, have been proposed as building blocks for the construction of motor behaviors by the nervous system. Intraspinal or intracortical microstimulation (ICMS) has been shown to evoke muscle patterns that can be resolved into a small set of synergies similar to those seen in natural behavior. However, questions remain about the validity of microstimulation as a probe of neural function, particularly given the relatively long trains of supratheshold stimuli used in these studies. Here, we examined whether muscle synergies evoked during ICMS in two rhesus macaques were similarly encoded by nearby motor cortical units during a purely voluntary behavior involving object reach, grasp, and carry movements. At each microstimulation site we identified the synergy most strongly evoked among those extracted from muscle patterns evoked over all microstimulation sites. For each cortical unit recorded at the same microstimulation site, we then identified the synergy most strongly encoded among those extracted from muscle patterns recorded during the voluntary behavior. We found that the synergy most strongly evoked at an ICMS site matched the synergy most strongly encoded by proximal units more often than expected by chance. These results suggest a common neural substrate for microstimulation-evoked motor responses and for the generation of muscle patterns during natural behaviors. PMID:24634652

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

PubMed

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

2012-01-01

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

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

PubMed Central

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

2011-01-01

Many sounds of ecological importance, such as communication calls, are characterized by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamo-cortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP), which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectro-temporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step toward the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems. PMID:22347163

Reconstitution of a Patterned Neural Tube from Single Mouse Embryonic Stem Cells.

PubMed

Ishihara, Keisuke; Ranga, Adrian; Lutolf, Matthias P; Tanaka, Elly M; Meinhardt, Andrea

2017-01-01

The recapitulation of tissue development and patterning in three-dimensional (3D) culture is an important dimension of stem cell research. Here, we describe a 3D culture protocol in which single mouse ES cells embedded in Matrigel under neural induction conditions clonally form a lumen containing, oval-shaped epithelial structure within 3 days. By Day 7 an apicobasally polarized neuroepithelium with uniformly dorsal cell identity forms. Treatment with retinoic acid at Day 2 results in posteriorization and self-organization of dorsal-ventral neural tube patterning. Neural tube organoid growth is also supported by pure laminin gels as well as poly(ethylene glycol) (PEG)-based artificial extracellular matrix hydrogels, which can be fine-tuned for key microenvironment characteristics. The rapid generation of a simple, patterned tissue in well-defined culture conditions makes the neural tube organoid a tractable model for studying neural stem cell self-organization.

Antagonism between the transcription factors NANOG and OTX2 specifies rostral or caudal cell fate during neural patterning transition.

PubMed

Su, Zhenghui; Zhang, Yanqi; Liao, Baojian; Zhong, Xiaofen; Chen, Xin; Wang, Haitao; Guo, Yiping; Shan, Yongli; Wang, Lihui; Pan, Guangjin

2018-03-23

During neurogenesis, neural patterning is a critical step during which neural progenitor cells differentiate into neurons with distinct functions. However, the molecular determinants that regulate neural patterning remain poorly understood. Here we optimized the "dual SMAD inhibition" method to specifically promote differentiation of human pluripotent stem cells (hPSCs) into forebrain and hindbrain neural progenitor cells along the rostral-caudal axis. We report that neural patterning determination occurs at the very early stage in this differentiation. Undifferentiated hPSCs expressed basal levels of the transcription factor orthodenticle homeobox 2 (OTX2) that dominantly drove hPSCs into the "default" rostral fate at the beginning of differentiation. Inhibition of glycogen synthase kinase 3β (GSK3β) through CHIR99021 application sustained transient expression of the transcription factor NANOG at early differentiation stages through Wnt signaling. Wnt signaling and NANOG antagonized OTX2 and, in the later stages of differentiation, switched the default rostral cell fate to the caudal one. Our findings have uncovered a mutual antagonism between NANOG and OTX2 underlying cell fate decisions during neural patterning, critical for the regulation of early neural development in humans. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Optical imaging of the ventral medullary surface of developing kittens during ventilatory challenges.

PubMed

Gozal, D; Dong, X W; Rector, D M; Harper, R K; Harper, R M

1996-01-01

We used large-array optical recording procedures to examine maturation of regional neural activity within the ventral medullary surface (VMS) of anaesthetized kittens during graded hypercapnic and hypoxic challenges. The VMS was exposed through a ventral surgical approach in 10, 20, 30, and 45-day-old kittens and in adult cats under sodium pentobarbital anaesthesia. Arterial pressure, costal diaphragmatic EMG, and ECG were continuously monitored. A coherent image conduit with 12 mu fibre resolution was attached to a charge-coupled-device camera and positioned over the VMS. Reflected 660 nm light was digitized continuously at 2-s intervals during a baseline period, hyperoxic hypercapnia, (3, 5, and 10% CO2 in O2), and poikylocapnic hypoxia (6%, 9%, and 12% O2 in N2), and recovery. Sixty to seventy-five images within each epoch were averaged, and subtracted from baseline. Regional differences within the image were determined by ANOVA procedures (alpha = 0.05). During hypercapnia, an overall decrease in neural activity (increase in scattered light) occurred, which was marginally age-dependent. By 30 days, regional bidirectional reflectance changes in response to CO2 emerged in a small proportion of animals, and were similar to adult responses. Hypoxia induced a dose- and age-dependent decrease in overall scattered light. Transient "on" and "off" responses were common under both ventilatory stimuli. In 20-30-day kittens, marked rebound responses in reflectance accompanied cessation of hypoxic stimuli; such patterns were absent at other ages. At 30 days, a caudal-rostral bidirectionality in response to mild hypoxia (12% O2) began to emerge in a subset of animals. We conclude that dose-dependent response to ventilatory stimuli occur in the VMS at all post-natal ages of the kitten; however, in hypoxia, the magnitude of the overall reflectance changes is diminished relative to adult patterns. Rebound responses to hypoxia are present at particular ages, and older kittens begin to show a topographical organization of neural activation.

Self-organizing neural network models for visual pattern recognition.

PubMed

Fukushima, K

1987-01-01

Two neural network models for visual pattern recognition are discussed. The first model, called a "neocognitron", is a hierarchical multilayered network which has only afferent synaptic connections. It can acquire the ability to recognize patterns by "learning-without-a-teacher": the repeated presentation of a set of training patterns is sufficient, and no information about the categories of the patterns is necessary. The cells of the highest stage eventually become "gnostic cells", whose response shows the final result of the pattern-recognition of the network. Pattern recognition is performed on the basis of similarity in shape between patterns, and is not affected by deformation, nor by changes in size, nor by shifts in the position of the stimulus pattern. The second model has not only afferent but also efferent synaptic connections, and is endowed with the function of selective attention. The afferent and the efferent signals interact with each other in the hierarchical network: the efferent signals, that is, the signals for selective attention, have a facilitating effect on the afferent signals, and at the same time, the afferent signals gate efferent signal flow. When a complex figure, consisting of two patterns or more, is presented to the model, it is segmented into individual patterns, and each pattern is recognized separately. Even if one of the patterns to which the models is paying selective attention is affected by noise or defects, the model can "recall" the complete pattern from which the noise has been eliminated and the defects corrected.

Neural Responses to Visual Food Cues According to Weight Status: A Systematic Review of Functional Magnetic Resonance Imaging Studies

PubMed Central

Pursey, Kirrilly M.; Stanwell, Peter; Callister, Robert J.; Brain, Katherine; Collins, Clare E.; Burrows, Tracy L.

2014-01-01

Emerging evidence from recent neuroimaging studies suggests that specific food-related behaviors contribute to the development of obesity. The aim of this review was to report the neural responses to visual food cues, as assessed by functional magnetic resonance imaging (fMRI), in humans of differing weight status. Published studies to 2014 were retrieved and included if they used visual food cues, studied humans >18 years old, reported weight status, and included fMRI outcomes. Sixty studies were identified that investigated the neural responses of healthy weight participants (n = 26), healthy weight compared to obese participants (n = 17), and weight-loss interventions (n = 12). High-calorie food images were used in the majority of studies (n = 36), however, image selection justification was only provided in 19 studies. Obese individuals had increased activation of reward-related brain areas including the insula and orbitofrontal cortex in response to visual food cues compared to healthy weight individuals, and this was particularly evident in response to energy dense cues. Additionally, obese individuals were more responsive to food images when satiated. Meta-analysis of changes in neural activation post-weight loss revealed small areas of convergence across studies in brain areas related to emotion, memory, and learning, including the cingulate gyrus, lentiform nucleus, and precuneus. Differential activation patterns to visual food cues were observed between obese, healthy weight, and weight-loss populations. Future studies require standardization of nutrition variables and fMRI outcomes to enable more direct comparisons between studies. PMID:25988110

Neural responses to visual food cues according to weight status: a systematic review of functional magnetic resonance imaging studies.

PubMed

Pursey, Kirrilly M; Stanwell, Peter; Callister, Robert J; Brain, Katherine; Collins, Clare E; Burrows, Tracy L

2014-01-01

Emerging evidence from recent neuroimaging studies suggests that specific food-related behaviors contribute to the development of obesity. The aim of this review was to report the neural responses to visual food cues, as assessed by functional magnetic resonance imaging (fMRI), in humans of differing weight status. Published studies to 2014 were retrieved and included if they used visual food cues, studied humans >18 years old, reported weight status, and included fMRI outcomes. Sixty studies were identified that investigated the neural responses of healthy weight participants (n = 26), healthy weight compared to obese participants (n = 17), and weight-loss interventions (n = 12). High-calorie food images were used in the majority of studies (n = 36), however, image selection justification was only provided in 19 studies. Obese individuals had increased activation of reward-related brain areas including the insula and orbitofrontal cortex in response to visual food cues compared to healthy weight individuals, and this was particularly evident in response to energy dense cues. Additionally, obese individuals were more responsive to food images when satiated. Meta-analysis of changes in neural activation post-weight loss revealed small areas of convergence across studies in brain areas related to emotion, memory, and learning, including the cingulate gyrus, lentiform nucleus, and precuneus. Differential activation patterns to visual food cues were observed between obese, healthy weight, and weight-loss populations. Future studies require standardization of nutrition variables and fMRI outcomes to enable more direct comparisons between studies.

Noise-invariant Neurons in the Avian Auditory Cortex: Hearing the Song in Noise

PubMed Central

Moore, R. Channing; Lee, Tyler; Theunissen, Frédéric E.

2013-01-01

Given the extraordinary ability of humans and animals to recognize communication signals over a background of noise, describing noise invariant neural responses is critical not only to pinpoint the brain regions that are mediating our robust perceptions but also to understand the neural computations that are performing these tasks and the underlying circuitry. Although invariant neural responses, such as rotation-invariant face cells, are well described in the visual system, high-level auditory neurons that can represent the same behaviorally relevant signal in a range of listening conditions have yet to be discovered. Here we found neurons in a secondary area of the avian auditory cortex that exhibit noise-invariant responses in the sense that they responded with similar spike patterns to song stimuli presented in silence and over a background of naturalistic noise. By characterizing the neurons' tuning in terms of their responses to modulations in the temporal and spectral envelope of the sound, we then show that noise invariance is partly achieved by selectively responding to long sounds with sharp spectral structure. Finally, to demonstrate that such computations could explain noise invariance, we designed a biologically inspired noise-filtering algorithm that can be used to separate song or speech from noise. This novel noise-filtering method performs as well as other state-of-the-art de-noising algorithms and could be used in clinical or consumer oriented applications. Our biologically inspired model also shows how high-level noise-invariant responses could be created from neural responses typically found in primary auditory cortex. PMID:23505354

Noise-invariant neurons in the avian auditory cortex: hearing the song in noise.

PubMed

Moore, R Channing; Lee, Tyler; Theunissen, Frédéric E

2013-01-01

Given the extraordinary ability of humans and animals to recognize communication signals over a background of noise, describing noise invariant neural responses is critical not only to pinpoint the brain regions that are mediating our robust perceptions but also to understand the neural computations that are performing these tasks and the underlying circuitry. Although invariant neural responses, such as rotation-invariant face cells, are well described in the visual system, high-level auditory neurons that can represent the same behaviorally relevant signal in a range of listening conditions have yet to be discovered. Here we found neurons in a secondary area of the avian auditory cortex that exhibit noise-invariant responses in the sense that they responded with similar spike patterns to song stimuli presented in silence and over a background of naturalistic noise. By characterizing the neurons' tuning in terms of their responses to modulations in the temporal and spectral envelope of the sound, we then show that noise invariance is partly achieved by selectively responding to long sounds with sharp spectral structure. Finally, to demonstrate that such computations could explain noise invariance, we designed a biologically inspired noise-filtering algorithm that can be used to separate song or speech from noise. This novel noise-filtering method performs as well as other state-of-the-art de-noising algorithms and could be used in clinical or consumer oriented applications. Our biologically inspired model also shows how high-level noise-invariant responses could be created from neural responses typically found in primary auditory cortex.

A Novel Method of Combining Blood Oxygenation and Blood Flow Sensitive Magnetic Resonance Imaging Techniques to Measure the Cerebral Blood Flow and Oxygen Metabolism Responses to an Unknown Neural Stimulus

PubMed Central

Simon, Aaron B.; Griffeth, Valerie E. M.; Wong, Eric C.; Buxton, Richard B.

2013-01-01

Simultaneous implementation of magnetic resonance imaging methods for Arterial Spin Labeling (ASL) and Blood Oxygenation Level Dependent (BOLD) imaging makes it possible to quantitatively measure the changes in cerebral blood flow (CBF) and cerebral oxygen metabolism (CMRO2) that occur in response to neural stimuli. To date, however, the range of neural stimuli amenable to quantitative analysis is limited to those that may be presented in a simple block or event related design such that measurements may be repeated and averaged to improve precision. Here we examined the feasibility of using the relationship between cerebral blood flow and the BOLD signal to improve dynamic estimates of blood flow fluctuations as well as to estimate metabolic-hemodynamic coupling under conditions where a stimulus pattern is unknown. We found that by combining the information contained in simultaneously acquired BOLD and ASL signals through a method we term BOLD Constrained Perfusion (BCP) estimation, we could significantly improve the precision of our estimates of the hemodynamic response to a visual stimulus and, under the conditions of a calibrated BOLD experiment, accurately determine the ratio of the oxygen metabolic response to the hemodynamic response. Importantly we were able to accomplish this without utilizing a priori knowledge of the temporal nature of the neural stimulus, suggesting that BOLD Constrained Perfusion estimation may make it feasible to quantitatively study the cerebral metabolic and hemodynamic responses to more natural stimuli that cannot be easily repeated or averaged. PMID:23382977

The Role of Visual and Semantic Properties in the Emergence of Category-Specific Patterns of Neural Response in the Human Brain.

PubMed

Coggan, David D; Baker, Daniel H; Andrews, Timothy J

2016-01-01

Brain-imaging studies have found distinct spatial and temporal patterns of response to different object categories across the brain. However, the extent to which these categorical patterns of response reflect higher-level semantic or lower-level visual properties of the stimulus remains unclear. To address this question, we measured patterns of EEG response to intact and scrambled images in the human brain. Our rationale for using scrambled images is that they have many of the visual properties found in intact images, but do not convey any semantic information. Images from different object categories (bottle, face, house) were briefly presented (400 ms) in an event-related design. A multivariate pattern analysis revealed categorical patterns of response to intact images emerged ∼80-100 ms after stimulus onset and were still evident when the stimulus was no longer present (∼800 ms). Next, we measured the patterns of response to scrambled images. Categorical patterns of response to scrambled images also emerged ∼80-100 ms after stimulus onset. However, in contrast to the intact images, distinct patterns of response to scrambled images were mostly evident while the stimulus was present (∼400 ms). Moreover, scrambled images were able to account only for all the variance in the intact images at early stages of processing. This direct manipulation of visual and semantic content provides new insights into the temporal dynamics of object perception and the extent to which different stages of processing are dependent on lower-level or higher-level properties of the image.

Information Compression, Multiple Alignment, and the Representation and Processing of Knowledge in the Brain.

PubMed

Wolff, J Gerard

2016-01-01

The SP theory of intelligence , with its realization in the SP computer model , aims to simplify and integrate observations and concepts across artificial intelligence, mainstream computing, mathematics, and human perception and cognition, with information compression as a unifying theme. This paper describes how abstract structures and processes in the theory may be realized in terms of neurons, their interconnections, and the transmission of signals between neurons. This part of the SP theory- SP-neural -is a tentative and partial model for the representation and processing of knowledge in the brain. Empirical support for the SP theory-outlined in the paper-provides indirect support for SP-neural. In the abstract part of the SP theory (SP-abstract), all kinds of knowledge are represented with patterns , where a pattern is an array of atomic symbols in one or two dimensions. In SP-neural, the concept of a "pattern" is realized as an array of neurons called a pattern assembly , similar to Hebb's concept of a "cell assembly" but with important differences. Central to the processing of information in SP-abstract is information compression via the matching and unification of patterns (ICMUP) and, more specifically, information compression via the powerful concept of multiple alignment , borrowed and adapted from bioinformatics. Processes such as pattern recognition, reasoning and problem solving are achieved via the building of multiple alignments, while unsupervised learning is achieved by creating patterns from sensory information and also by creating patterns from multiple alignments in which there is a partial match between one pattern and another. It is envisaged that, in SP-neural, short-lived neural structures equivalent to multiple alignments will be created via an inter-play of excitatory and inhibitory neural signals. It is also envisaged that unsupervised learning will be achieved by the creation of pattern assemblies from sensory information and from the neural equivalents of multiple alignments, much as in the non-neural SP theory-and significantly different from the "Hebbian" kinds of learning which are widely used in the kinds of artificial neural network that are popular in computer science. The paper discusses several associated issues, with relevant empirical evidence.

Spatiotemporal canards in neural field equations

NASA Astrophysics Data System (ADS)

Avitabile, D.; Desroches, M.; Knobloch, E.

2017-04-01

Canards are special solutions to ordinary differential equations that follow invariant repelling slow manifolds for long time intervals. In realistic biophysical single-cell models, canards are responsible for several complex neural rhythms observed experimentally, but their existence and role in spatially extended systems is largely unexplored. We identify and describe a type of coherent structure in which a spatial pattern displays temporal canard behavior. Using interfacial dynamics and geometric singular perturbation theory, we classify spatiotemporal canards and give conditions for the existence of folded-saddle and folded-node canards. We find that spatiotemporal canards are robust to changes in the synaptic connectivity and firing rate. The theory correctly predicts the existence of spatiotemporal canards with octahedral symmetry in a neural field model posed on the unit sphere.

Biologically inspired adaptive walking of a quadruped robot.

PubMed

Kimura, Hiroshi; Fukuoka, Yasuhiro; Cohen, Avis H

2007-01-15

We describe here the efforts to induce a quadruped robot to walk with medium-walking speed on irregular terrain based on biological concepts. We propose the necessary conditions for stable dynamic walking on irregular terrain in general, and we design the mechanical and the neural systems by comparing biological concepts with those necessary conditions described in physical terms. PD-controller at joints constructs the virtual spring-damper system as the viscoelasticity model of a muscle. The neural system model consists of a central pattern generator (CPG), reflexes and responses. We validate the effectiveness of the proposed neural system model control using the quadruped robots called 'Tekken1&2'. MPEG footage of experiments can be seen at http://www.kimura.is.uec.ac.jp.

Probabilistic models for neural populations that naturally capture global coupling and criticality

PubMed Central

2017-01-01

Advances in multi-unit recordings pave the way for statistical modeling of activity patterns in large neural populations. Recent studies have shown that the summed activity of all neurons strongly shapes the population response. A separate recent finding has been that neural populations also exhibit criticality, an anomalously large dynamic range for the probabilities of different population activity patterns. Motivated by these two observations, we introduce a class of probabilistic models which takes into account the prior knowledge that the neural population could be globally coupled and close to critical. These models consist of an energy function which parametrizes interactions between small groups of neurons, and an arbitrary positive, strictly increasing, and twice differentiable function which maps the energy of a population pattern to its probability. We show that: 1) augmenting a pairwise Ising model with a nonlinearity yields an accurate description of the activity of retinal ganglion cells which outperforms previous models based on the summed activity of neurons; 2) prior knowledge that the population is critical translates to prior expectations about the shape of the nonlinearity; 3) the nonlinearity admits an interpretation in terms of a continuous latent variable globally coupling the system whose distribution we can infer from data. Our method is independent of the underlying system’s state space; hence, it can be applied to other systems such as natural scenes or amino acid sequences of proteins which are also known to exhibit criticality. PMID:28926564

Neural Markers in Pediatric Bipolar Disorder and Familial Risk for Bipolar Disorder.

PubMed

Wiggins, Jillian Lee; Brotman, Melissa A; Adleman, Nancy E; Kim, Pilyoung; Wambach, Caroline G; Reynolds, Richard C; Chen, Gang; Towbin, Kenneth; Pine, Daniel S; Leibenluft, Ellen

2017-01-01

Bipolar disorder (BD) is highly heritable. Neuroimaging studies comparing unaffected youth at high familial risk for BD (i.e., those with a first-degree relative with the disorder; termed "high-risk" [HR]) to "low-risk" (LR) youth (i.e., those without a first-degree relative with BD) and to patients with BD may help identify potential brain-based markers associated with risk (i.e., regions where HR+BD≠LR), resilience (HR≠BD+LR), or illness (BD≠HR+LR). During functional magnetic resonance imaging (fMRI), 99 youths (i.e., adolescents and young adults) aged 9.8 to 24.8 years (36 BD, 22 HR, 41 LR) performed a task probing face emotion labeling, previously shown to be impaired behaviorally in youth with BD and HR youth. We found three patterns of results. Candidate risk endophenotypes (i.e., where BD and HR shared deficits) included dysfunction in higher-order face processing regions (e.g., middle temporal gyrus, dorsolateral prefrontal cortex). Candidate resilience markers and disorder sequelae (where HR and BD, respectively, show unique alterations relative to the other two groups) included different patterns of neural responses across other regions mediating face processing (e.g., fusiform), executive function (e.g., inferior frontal gyrus), and social cognition (e.g., default network, superior temporal sulcus, temporo-parietal junction). If replicated in longitudinal studies and with additional populations, neural patterns suggesting risk endophenotypes could be used to identify individuals at risk for BD who may benefit from prevention measures. Moreover, information about risk and resilience markers could be used to develop novel treatments that recruit neural markers of resilience and attenuate neural patterns associated with risk. Clinical trial registration information-Studies of Brain Function and Course of Illness in Pediatric Bipolar Disorder and Child and Adolescent Bipolar Disorder Brain Imaging and Treatment Study; http://clinicaltrials.gov/; NCT00025935 and NCT00006177. Published by Elsevier Inc.

Isolating Age-Group Differences in Working Memory Load-Related Neural Activity: Assessing the Contribution of Working Memory Capacity Using a Partial-Trial fMRI Method

PubMed Central

Bennett, Ilana J.; Rivera, Hannah G.; Rypma, Bart

2013-01-01

Previous studies examining age-group differences in working memory load-related neural activity have yielded mixed results. When present, age-group differences in working memory capacity are frequently proposed to underlie these neural effects. However, direct relationships between working memory capacity and working memory load-related activity have only been observed in younger adults. These relationships remain untested in healthy aging. Therefore, the present study examined patterns of working memory load-related activity in 22 younger and 20 older adults and assessed the contribution of working memory capacity to these load-related effects. Participants performed a partial-trial delayed response item recognition task during functional magnetic resonance imaging. In this task, participants encoded either 2 or 6 letters, maintained them during a delay, and then indicated whether a probe was present in the memory set. Behavioral results revealed faster and more accurate responses to load 2 versus 6, with age-group differences in this load condition effect for the accuracy measure. Neuroimaging results revealed one region (medial superior frontal gyrus) that showed age-group differences in load-related activity during the retrieval period, with less (greater) neural activity for the low versus high load condition in younger (older) adults. Furthermore, for older adults, load-related activity did not vary as a function of working memory capacity. Thus, working memory-related activity varies with healthy aging, but these patterns are not due solely to working memory capacity. Neurocognitive aging theories that feature capacity will need to account for these results. PMID:23357076

Induced and evoked neural correlates of orientation selectivity in human visual cortex.

PubMed

Koelewijn, Loes; Dumont, Julie R; Muthukumaraswamy, Suresh D; Rich, Anina N; Singh, Krish D

2011-02-14

Orientation discrimination is much better for patterns oriented along the horizontal or vertical (cardinal) axes than for patterns oriented obliquely, but the neural basis for this is not known. Previous animal neurophysiology and human neuroimaging studies have demonstrated only a moderate bias for cardinal versus oblique orientations, with fMRI showing a larger response to cardinals in primary visual cortex (V1) and EEG demonstrating both increased magnitudes and reduced latencies of transient evoked responses. Here, using MEG, we localised and characterised induced gamma and transient evoked responses to stationary circular grating patches of three orientations (0, 45, and 90° from vertical). Surprisingly, we found that the sustained gamma response was larger for oblique, compared to cardinal, stimuli. This "inverse oblique effect" was also observed in the earliest (80 ms) evoked response, whereas later responses (120 ms) showed a trend towards the reverse, "classic", oblique response. Source localisation demonstrated that the sustained gamma and early evoked responses were localised to medial visual cortex, whilst the later evoked responses came from both this early visual area and a source in a more inferolateral extrastriate region. These results suggest that (1) the early evoked and sustained gamma responses manifest the initial tuning of V1 neurons, with the stronger response to oblique stimuli possibly reflecting increased tuning widths for these orientations, and (2) the classic behavioural oblique effect is mediated by an extrastriate cortical area and may also implicate feedback from extrastriate to primary visual cortex. Copyright © 2010 Elsevier Inc. All rights reserved.

Automation of Some Operations of a Wind Tunnel Using Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Buggele, Alvin E.

1996-01-01

Artificial neural networks were used successfully to sequence operations in a small, recently modernized, supersonic wind tunnel at NASA-Lewis Research Center. The neural nets generated correct estimates of shadowgraph patterns, pressure sensor readings and mach numbers for conditions occurring shortly after startup and extending to fully developed flow. Artificial neural networks were trained and tested for estimating: sensor readings from shadowgraph patterns, shadowgraph patterns from shadowgraph patterns and sensor readings from sensor readings. The 3.81 by 10 in. (0.0968 by 0.254 m) tunnel was operated with its mach 2.0 nozzle, and shadowgraph was recorded near the nozzle exit. These results support the thesis that artificial neural networks can be combined with current workstation technology to automate wind tunnel operations.

Speech training alters consonant and vowel responses in multiple auditory cortex fields

PubMed Central

Engineer, Crystal T.; Rahebi, Kimiya C.; Buell, Elizabeth P.; Fink, Melyssa K.; Kilgard, Michael P.

2015-01-01

Speech sounds evoke unique neural activity patterns in primary auditory cortex (A1). Extensive speech sound discrimination training alters A1 responses. While the neighboring auditory cortical fields each contain information about speech sound identity, each field processes speech sounds differently. We hypothesized that while all fields would exhibit training-induced plasticity following speech training, there would be unique differences in how each field changes. In this study, rats were trained to discriminate speech sounds by consonant or vowel in quiet and in varying levels of background speech-shaped noise. Local field potential and multiunit responses were recorded from four auditory cortex fields in rats that had received 10 weeks of speech discrimination training. Our results reveal that training alters speech evoked responses in each of the auditory fields tested. The neural response to consonants was significantly stronger in anterior auditory field (AAF) and A1 following speech training. The neural response to vowels following speech training was significantly weaker in ventral auditory field (VAF) and posterior auditory field (PAF). This differential plasticity of consonant and vowel sound responses may result from the greater paired pulse depression, expanded low frequency tuning, reduced frequency selectivity, and lower tone thresholds, which occurred across the four auditory fields. These findings suggest that alterations in the distributed processing of behaviorally relevant sounds may contribute to robust speech discrimination. PMID:25827927

Abnormal fronto-limbic engagement in incarcerated stimulant users during moral processing.

PubMed

Fede, Samantha J; Harenski, Carla L; Schaich Borg, Jana; Sinnott-Armstrong, Walter; Rao, Vikram; Caldwell, Brendan M; Nyalakanti, Prashanth K; Koenigs, Michael R; Decety, Jean; Calhoun, Vince D; Kiehl, Kent A

2016-09-01

Stimulant use is a significant and prevalent problem, particularly in criminal populations. Previous studies found that cocaine and methamphetamine use is related to impairment in identifying emotions and empathy. Stimulant users also have abnormal neural structure and function of the ventromedial prefrontal cortex (vmPFC), amygdala, and anterior (ACC) and posterior cingulate (PCC), regions implicated in moral decision-making. However, no research has studied the neural correlates of stimulant use and explicit moral processing in an incarcerated population. Here, we examine how stimulant use affects sociomoral processing that might contribute to antisocial behavior. We predicted that vmPFC, amygdala, PCC, and ACC would show abnormal neural response during a moral processing task in incarcerated methamphetamine and cocaine users. Incarcerated adult males (N = 211) were scanned with a mobile MRI system while completing a moral decision-making task. Lifetime drug use was assessed. Neural responses during moral processing were compared between users and non-users. The relationship between duration of use and neural function was also examined. Incarcerated stimulant users showed less amygdala engagement than non-users during moral processing. Duration of stimulant use was negatively associated with activity in ACC and positively associated with vmPFC response during moral processing. These results suggest a dynamic pattern of fronto-limbic moral processing related to stimulant use with deficits in both central motive and cognitive integration elements of biological moral processes theory. This increases our understanding of how drug use relates to moral processing in the brain in an ultra-high-risk population.

Optimization of Training Sets for Neural-Net Processing of Characteristic Patterns from Vibrating Solids

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

2001-01-01

Artificial neural networks have been used for a number of years to process holography-generated characteristic patterns of vibrating structures. This technology depends critically on the selection and the conditioning of the training sets. A scaling operation called folding is discussed for conditioning training sets optimally for training feed-forward neural networks to process characteristic fringe patterns. Folding allows feed-forward nets to be trained easily to detect damage-induced vibration-displacement-distribution changes as small as 10 nm. A specific application to aerospace of neural-net processing of characteristic patterns is presented to motivate the conditioning and optimization effort.

Neural correlates of inhibitory control in adult ADHD: Evidence from the Milwaukee longitudinal sample

PubMed Central

Mulligan, Richard C.; Knopik, Valerie S.; Sweet, Lawrence H.; Fischer, Mariellen; Seidenberg, Michael; Rao, Stephen M.

2011-01-01

Only a few studies have investigated the neural substrate of response inhibition in adult ADHD using Stop-Signal and Go/No-Go tasks. Inconsistencies and methodological limitations in the existing literature have resulted in limited conclusions regarding underlying pathophysiology. We examined the neural basis of response inhibition in a group of adults diagnosed with ADHD in childhood and who continue to meet criteria for ADHD while addressing limitations present in earlier studies. Adults with ADHD (n=12) and controls (n=12) were recruited from an ongoing longitudinal study and were matched for age, IQ, and education. Individuals with comorbid conditions were excluded. Functional MRI was used to identify and compare the brain activation patterns during correct trials of a response inhibition task (Go/No-Go). Our results showed that the control group recruited a more extensive network of brain regions than the ADHD group during correct inhibition trials. Adults with ADHD showed reduced brain activation in the right frontal eye field, pre-supplementary motor area, left precentral gyrus, and the inferior parietal lobe bilaterally. During successful inhibition of an inappropriate response, adults with ADHD display reduced activation in fronto-parietal networks previously implicated in working memory, goal-oriented attention, and response selection. This profile of brain activation may be specifically associated with ADHD in adulthood. PMID:21937201

A Neural Network Approach to fMRI Binocular Visual Rivalry Task Analysis

PubMed Central

Bertolino, Nicola; Ferraro, Stefania; Nigri, Anna; Bruzzone, Maria Grazia; Ghielmetti, Francesco; Leonardi, Matilde; Agostino Parati, Eugenio; Grazia Bruzzone, Maria; Franceschetti, Silvana; Caldiroli, Dario; Sattin, Davide; Giovannetti, Ambra; Pagani, Marco; Covelli, Venusia; Ciaraffa, Francesca; Vela Gomez, Jesus; Reggiori, Barbara; Ferraro, Stefania; Nigri, Anna; D'Incerti, Ludovico; Minati, Ludovico; Andronache, Adrian; Rosazza, Cristina; Fazio, Patrik; Rossi, Davide; Varotto, Giulia; Panzica, Ferruccio; Benti, Riccardo; Marotta, Giorgio; Molteni, Franco

2014-01-01

The purpose of this study was to investigate whether artificial neural networks (ANN) are able to decode participants’ conscious experience perception from brain activity alone, using complex and ecological stimuli. To reach the aim we conducted pattern recognition data analysis on fMRI data acquired during the execution of a binocular visual rivalry paradigm (BR). Twelve healthy participants were submitted to fMRI during the execution of a binocular non-rivalry (BNR) and a BR paradigm in which two classes of stimuli (faces and houses) were presented. During the binocular rivalry paradigm, behavioral responses related to the switching between consciously perceived stimuli were also collected. First, we used the BNR paradigm as a functional localizer to identify the brain areas involved the processing of the stimuli. Second, we trained the ANN on the BNR fMRI data restricted to these regions of interest. Third, we applied the trained ANN to the BR data as a ‘brain reading’ tool to discriminate the pattern of neural activity between the two stimuli. Fourth, we verified the consistency of the ANN outputs with the collected behavioral indicators of which stimulus was consciously perceived by the participants. Our main results showed that the trained ANN was able to generalize across the two different tasks (i.e. BNR and BR) and to identify with high accuracy the cognitive state of the participants (i.e. which stimulus was consciously perceived) during the BR condition. The behavioral response, employed as control parameter, was compared with the network output and a statistically significant percentage of correspondences (p-value <0.05) were obtained for all subjects. In conclusion the present study provides a method based on multivariate pattern analysis to investigate the neural basis of visual consciousness during the BR phenomenon when behavioral indicators lack or are inconsistent, like in disorders of consciousness or sedated patients. PMID:25121595

Dlx proteins position the neural plate border and determine adjacent cell fates

PubMed Central

Woda, Juliana M.; Pastagia, Julie; Mercola, Mark; Artinger, Kristin Bruk

2014-01-01

Summary The lateral border of the neural plate is a major source of signals that induce primary neurons, neural crest cells and cranial placodes as well as provide patterning cues to mesodermal structures such as somites and heart. Whereas secreted BMP, FGF and Wnt proteins influence the differentiation of neural and non-neural ectoderm, we show here that members of the Dlx family of transcription factors position the border between neural and non-neural ectoderm and are required for the specification of adjacent cell fates. Inhibition of endogenous Dlx activity in Xenopus embryos with an EnR-Dlx homeodomain fusion protein expands the neural plate into non-neural ectoderm tissue whereas ectopic activation of Dlx target genes inhibits neural plate differentiation. Importantly, the stereotypic pattern of border cell fates in the adjacent ectoderm is re-established only under conditions where the expanded neural plate abuts Dlx-positive non-neural ectoderm. Experiments in which presumptive neural plate was grafted to ventral ectoderm reiterate induction of neural crest and placodal lineages and also demonstrate that Dlx activity is required in non-neural ectoderm for the production of signals needed for induction of these cells. We propose that Dlx proteins regulate intercellular signaling across the interface between neural and non-neural ectoderm that is critical for inducing and patterning adjacent cell fates. PMID:12466200

Continuous monitoring of the lunar or Martian subsurface using on-board pattern recognition and neural processing of Rover geophysical data

NASA Technical Reports Server (NTRS)

Glass, Charles E.; Boyd, Richard V.; Sternberg, Ben K.

1991-01-01

The overall aim is to provide base technology for an automated vision system for on-board interpretation of geophysical data. During the first year's work, it was demonstrated that geophysical data can be treated as patterns and interpreted using single neural networks. Current research is developing an integrated vision system comprising neural networks, algorithmic preprocessing, and expert knowledge. This system is to be tested incrementally using synthetic geophysical patterns, laboratory generated geophysical patterns, and field geophysical patterns.

Novel transformation-based response prediction of shear building using interval neural network

NASA Astrophysics Data System (ADS)

Chakraverty, S.; Sahoo, Deepti Moyi

2017-04-01

Present paper uses powerful technique of interval neural network (INN) to simulate and estimate structural response of multi-storey shear buildings subject to earthquake motion. The INN is first trained for a real earthquake data, viz., the ground acceleration as input and the numerically generated responses of different floors of multi-storey buildings as output. Till date, no model exists to handle positive and negative data in the INN. As such here, the bipolar data in [ -1, 1] are converted first to unipolar form, i.e., to [0, 1] by means of a novel transformation for the first time to handle the above training patterns in normalized form. Once the training is done, again the unipolar data are converted back to its bipolar form by using the inverse transformation. The trained INN architecture is then used to simulate and test the structural response of different floors for various intensity earthquake data and it is found that the predicted responses given by INN model are good for practical purposes.

Human inferior colliculus activity relates to individual differences in spoken language learning.

PubMed

Chandrasekaran, Bharath; Kraus, Nina; Wong, Patrick C M

2012-03-01

A challenge to learning words of a foreign language is encoding nonnative phonemes, a process typically attributed to cortical circuitry. Using multimodal imaging methods [functional magnetic resonance imaging-adaptation (fMRI-A) and auditory brain stem responses (ABR)], we examined the extent to which pretraining pitch encoding in the inferior colliculus (IC), a primary midbrain structure, related to individual variability in learning to successfully use nonnative pitch patterns to distinguish words in American English-speaking adults. fMRI-A indexed the efficiency of pitch representation localized to the IC, whereas ABR quantified midbrain pitch-related activity with millisecond precision. In line with neural "sharpening" models, we found that efficient IC pitch pattern representation (indexed by fMRI) related to superior neural representation of pitch patterns (indexed by ABR), and consequently more successful word learning following sound-to-meaning training. Our results establish a critical role for the IC in speech-sound representation, consistent with the established role for the IC in the representation of communication signals in other animal models.

Unity and diversity of executive functions: Individual differences as a window on cognitive structure.

PubMed

Friedman, Naomi P; Miyake, Akira

2017-01-01

Executive functions (EFs) are high-level cognitive processes, often associated with the frontal lobes, that control lower level processes in the service of goal-directed behavior. They include abilities such as response inhibition, interference control, working memory updating, and set shifting. EFs show a general pattern of shared but distinct functions, a pattern described as "unity and diversity". We review studies of EF unity and diversity at the behavioral and genetic levels, focusing on studies of normal individual differences and what they reveal about the functional organization of these cognitive abilities. In particular, we review evidence that across multiple ages and populations, commonly studied EFs (a) are robustly correlated but separable when measured with latent variables; (b) are not the same as general intelligence or g; (c) are highly heritable at the latent level and seemingly also highly polygenic; and (d) activate both common and specific neural areas and can be linked to individual differences in neural activation, volume, and connectivity. We highlight how considering individual differences at the behavioral and neural levels can add considerable insight to the investigation of the functional organization of the brain, and conclude with some key points about individual differences to consider when interpreting neuropsychological patterns of dissociation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modelling the firing pattern of bullfrog vestibular neurons responding to naturalistic stimuli

NASA Technical Reports Server (NTRS)

Paulin, M. G.; Hoffman, L. F.

1999-01-01

We have developed a neural system identification method for fitting models to stimulus-response data, where the response is a spike train. The method involves using a general nonlinear optimisation procedure to fit models in the time domain. We have applied the method to model bullfrog semicircular canal afferent neuron responses during naturalistic, broad-band head rotations. These neurons respond in diverse ways, but a simple four parameter class of models elegantly accounts for the various types of responses observed. c1999 Elsevier Science B.V. All rights reserved.

Patterns of synchrony for feed-forward and auto-regulation feed-forward neural networks.

PubMed

Aguiar, Manuela A D; Dias, Ana Paula S; Ferreira, Flora

2017-01-01

We consider feed-forward and auto-regulation feed-forward neural (weighted) coupled cell networks. In feed-forward neural networks, cells are arranged in layers such that the cells of the first layer have empty input set and cells of each other layer receive only inputs from cells of the previous layer. An auto-regulation feed-forward neural coupled cell network is a feed-forward neural network where additionally some cells of the first layer have auto-regulation, that is, they have a self-loop. Given a network structure, a robust pattern of synchrony is a space defined in terms of equalities of cell coordinates that is flow-invariant for any coupled cell system (with additive input structure) associated with the network. In this paper, we describe the robust patterns of synchrony for feed-forward and auto-regulation feed-forward neural networks. Regarding feed-forward neural networks, we show that only cells in the same layer can synchronize. On the other hand, in the presence of auto-regulation, we prove that cells in different layers can synchronize in a robust way and we give a characterization of the possible patterns of synchrony that can occur for auto-regulation feed-forward neural networks.

Deinterlacing using modular neural network

NASA Astrophysics Data System (ADS)

Woo, Dong H.; Eom, Il K.; Kim, Yoo S.

2004-05-01

Deinterlacing is the conversion process from the interlaced scan to progressive one. While many previous algorithms that are based on weighted-sum cause blurring in edge region, deinterlacing using neural network can reduce the blurring through recovering of high frequency component by learning process, and is found robust to noise. In proposed algorithm, input image is divided into edge and smooth region, and then, to each region, one neural network is assigned. Through this process, each neural network learns only patterns that are similar, therefore it makes learning more effective and estimation more accurate. But even within each region, there are various patterns such as long edge and texture in edge region. To solve this problem, modular neural network is proposed. In proposed modular neural network, two modules are combined in output node. One is for low frequency feature of local area of input image, and the other is for high frequency feature. With this structure, each modular neural network can learn different patterns with compensating for drawback of counterpart. Therefore it can adapt to various patterns within each region effectively. In simulation, the proposed algorithm shows better performance compared with conventional deinterlacing methods and single neural network method.

Differences in neural activation as a function of risk-taking task parameters

PubMed Central

Congdon, Eliza; Bato, Angelica A.; Schonberg, Tom; Mumford, Jeanette A.; Karlsgodt, Katherine H.; Sabb, Fred W.; London, Edythe D.; Cannon, Tyrone D.; Bilder, Robert M.; Poldrack, Russell A.

2013-01-01

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 Analog 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 (DI) 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 toward characterizing a behavioral measure of risky decision-making that may support a better understanding of naturalistic risk-taking. PMID:24137106

Neural Network Model For Fast Learning And Retrieval

NASA Astrophysics Data System (ADS)

Arsenault, Henri H.; Macukow, Bohdan

1989-05-01

An approach to learning in a multilayer neural network is presented. The proposed network learns by creating interconnections between the input layer and the intermediate layer. In one of the new storage prescriptions proposed, interconnections are excitatory (positive) only and the weights depend on the stored patterns. In the intermediate layer each mother cell is responsible for one stored pattern. Mutually interconnected neurons in the intermediate layer perform a winner-take-all operation, taking into account correlations between stored vectors. The performance of networks using this interconnection prescription is compared with two previously proposed schemes, one using inhibitory connections at the output and one using all-or-nothing interconnections. The network can be used as a content-addressable memory or as a symbolic substitution system that yields an arbitrarily defined output for any input. The training of a model to perform Boolean logical operations is also described. Computer simulations using the network as an autoassociative content-addressable memory show the model to be efficient. Content-addressable associative memories and neural logic modules can be combined to perform logic operations on highly corrupted data.

Unsupervised Extraction of Stable Expression Signatures from Public Compendia with an Ensemble of Neural Networks.

PubMed

Tan, Jie; Doing, Georgia; Lewis, Kimberley A; Price, Courtney E; Chen, Kathleen M; Cady, Kyle C; Perchuk, Barret; Laub, Michael T; Hogan, Deborah A; Greene, Casey S

2017-07-26

Cross-experiment comparisons in public data compendia are challenged by unmatched conditions and technical noise. The ADAGE method, which performs unsupervised integration with denoising autoencoder neural networks, can identify biological patterns, but because ADAGE models, like many neural networks, are over-parameterized, different ADAGE models perform equally well. To enhance model robustness and better build signatures consistent with biological pathways, we developed an ensemble ADAGE (eADAGE) that integrated stable signatures across models. We applied eADAGE to a compendium of Pseudomonas aeruginosa gene expression profiling experiments performed in 78 media. eADAGE revealed a phosphate starvation response controlled by PhoB in media with moderate phosphate and predicted that a second stimulus provided by the sensor kinase, KinB, is required for this PhoB activation. We validated this relationship using both targeted and unbiased genetic approaches. eADAGE, which captures stable biological patterns, enables cross-experiment comparisons that can highlight measured but undiscovered relationships. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Stable and Dynamic Coding for Working Memory in Primate Prefrontal Cortex

PubMed Central

Watanabe, Kei; Funahashi, Shintaro; Stokes, Mark G.

2017-01-01

Working memory (WM) provides the stability necessary for high-level cognition. Influential theories typically assume that WM depends on the persistence of stable neural representations, yet increasing evidence suggests that neural states are highly dynamic. Here we apply multivariate pattern analysis to explore the population dynamics in primate lateral prefrontal cortex (PFC) during three variants of the classic memory-guided saccade task (recorded in four animals). We observed the hallmark of dynamic population coding across key phases of a working memory task: sensory processing, memory encoding, and response execution. Throughout both these dynamic epochs and the memory delay period, however, the neural representational geometry remained stable. We identified two characteristics that jointly explain these dynamics: (1) time-varying changes in the subpopulation of neurons coding for task variables (i.e., dynamic subpopulations); and (2) time-varying selectivity within neurons (i.e., dynamic selectivity). These results indicate that even in a very simple memory-guided saccade task, PFC neurons display complex dynamics to support stable representations for WM. SIGNIFICANCE STATEMENT Flexible, intelligent behavior requires the maintenance and manipulation of incoming information over various time spans. For short time spans, this faculty is labeled “working memory” (WM). Dominant models propose that WM is maintained by stable, persistent patterns of neural activity in prefrontal cortex (PFC). However, recent evidence suggests that neural activity in PFC is dynamic, even while the contents of WM remain stably represented. Here, we explored the neural dynamics in PFC during a memory-guided saccade task. We found evidence for dynamic population coding in various task epochs, despite striking stability in the neural representational geometry of WM. Furthermore, we identified two distinct cellular mechanisms that contribute to dynamic population coding. PMID:28559375

Coordinated within-trial dynamics of low-frequency neural rhythms controls evidence accumulation.

PubMed

Werkle-Bergner, Markus; Grandy, Thomas H; Chicherio, Christian; Schmiedek, Florian; Lövdén, Martin; Lindenberger, Ulman

2014-06-18

Higher cognitive functions, such as human perceptual decision making, require information processing and transmission across wide-spread cortical networks. Temporally synchronized neural firing patterns are advantageous for efficiently representing and transmitting information within and between assemblies. Computational, empirical, and conceptual considerations all lead to the expectation that the informational redundancy of neural firing rates is positively related to their synchronization. Recent theorizing and initial evidence also suggest that the coding of stimulus characteristics and their integration with behavioral goal states require neural interactions across a hierarchy of timescales. However, most studies thus have focused on neural activity in a single frequency range or on a restricted set of brain regions. Here we provide evidence for cooperative spatiotemporal dynamics of slow and fast EEG signals during perceptual decision making at the single-trial level. Participants performed three masked two-choice decision tasks, one each with numerical, verbal, or figural content. Decrements in posterior α power (8-14 Hz) were paralleled by increments in high-frequency (>30 Hz) signal entropy in trials demanding active sensory processing. Simultaneously, frontocentral θ power (4-7 Hz) increased, indicating evidence integration. The coordinated α/θ dynamics were tightly linked to decision speed and remarkably similar across tasks, suggesting a domain-general mechanism. In sum, we demonstrate an inverse association between decision-related changes in widespread low-frequency power and local high-frequency entropy. The cooperation among mechanisms captured by these changes enhances the informational density of neural response patterns and qualifies as a neural coding system in the service of perceptual decision making. Copyright © 2014 the authors 0270-6474/14/348519-10$15.00/0.

Higher-Order Neural Networks Recognize Patterns

NASA Technical Reports Server (NTRS)

Reid, Max B.; Spirkovska, Lilly; Ochoa, Ellen

1996-01-01

Networks of higher order have enhanced capabilities to distinguish between different two-dimensional patterns and to recognize those patterns. Also enhanced capabilities to "learn" patterns to be recognized: "trained" with far fewer examples and, therefore, in less time than necessary to train comparable first-order neural networks.

Visualizing the spinal neuronal dynamics of locomotion

NASA Astrophysics Data System (ADS)

Subramanian, Kalpathi R.; Bashor, D. P.; Miller, M. T.; Foster, J. A.

2004-06-01

Modern imaging and simulation techniques have enhanced system-level understanding of neural function. In this article, we present an application of interactive visualization to understanding neuronal dynamics causing locomotion of a single hip joint, based on pattern generator output of the spinal cord. Our earlier work visualized cell-level responses of multiple neuronal populations. However, the spatial relationships were abstract, making communication with colleagues difficult. We propose two approaches to overcome this: (1) building a 3D anatomical model of the spinal cord with neurons distributed inside, animated by the simulation and (2) adding limb movements predicted by neuronal activity. The new system was tested using a cat walking central pattern generator driving a pair of opposed spinal motoneuron pools. Output of opposing motoneuron pools was combined into a single metric, called "Net Neural Drive", which generated angular limb movement in proportion to its magnitude. Net neural drive constitutes a new description of limb movement control. The combination of spatial and temporal information in the visualizations elegantly conveys the neural activity of the output elements (motoneurons), as well as the resulting movement. The new system encompasses five biological levels of organization from ion channels to observed behavior. The system is easily scalable, and provides an efficient interactive platform for rapid hypothesis testing.

Antenna analysis using neural networks

NASA Technical Reports Server (NTRS)

Smith, William T.

1992-01-01

Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern shaping. The interesting thing about D-C synthesis is that the side lobes have the same amplitude. Five-element arrays were used. Again, 41 pattern samples were used for the input. Nine actual D-C patterns ranging from -10 dB to -30 dB side lobe levels were used to train the network. A comparison between simulated and actual D-C techniques for a pattern with -22 dB side lobe level is shown. The goal for this research was to evaluate the performance of neural network computing with antennas. Future applications will employ the backpropagation training algorithm to drastically reduce the computational complexity involved in performing EM compensation for surface errors in large space reflector antennas.

Antenna analysis using neural networks

NASA Astrophysics Data System (ADS)

Smith, William T.

1992-09-01

Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary).

Biological sources of inflexibility in brain and behavior with aging and neurodegenerative diseases

PubMed Central

Hong, S. Lee; Rebec, George V.

2012-01-01

Almost unequivocally, aging and neurodegeneration lead to deficits in neural information processing. These declines are marked by increased neural noise that is associated with increased variability or inconsistency in behavioral patterns. While it is often viewed that these problems arise from dysregulation of dopamine (DA), a monoamine modulator, glutamate (GLU), an excitatory amino acid that interacts with DA, also plays a role in determining the level of neural noise. We review literature demonstrating that neural noise is highest at both high and low levels of DA and GLU, allowing their interaction to form a many-to-one solution map for neural noise modulation. With aging and neurodegeneration, the range over which DA and GLU can be modulated is decreased leading to inflexibility in brain activity and behavior. As the capacity to modulate neural noise is restricted, the ability to shift noise from one brain region to another is reduced, leading to greater uniformity in signal-to-noise ratios across the entire brain. A negative consequence at the level of behavior is inflexibility that reduces the ability to: (1) switch from one behavior to another; and (2) stabilize a behavioral pattern against external perturbations. In this paper, we develop a theoretical framework where inflexibility across brain and behavior, rather than inconsistency and variability is the more important problem in aging and neurodegeneration. This theoretical framework of inflexibility in aging and neurodegeneration leads to the hypotheses that: (1) dysfunction in either or both of the DA and GLU systems restricts the ability to modulate neural noise; and (2) levels of neural noise and variability in brain activation will be dedifferentiated and more evenly distributed across the brain; and (3) changes in neural noise and behavioral variability in response to different task demands and changes in the environment will be reduced. PMID:23226117

Convergent and Divergent fMRI Responses in Children and Adults to Increasing Language Production Demands

PubMed Central

Krishnan, Saloni; Leech, Robert; Mercure, Evelyne; Lloyd-Fox, Sarah; Dick, Frederic

2015-01-01

In adults, patterns of neural activation associated with perhaps the most basic language skill—overt object naming—are extensively modulated by the psycholinguistic and visual complexity of the stimuli. Do children's brains react similarly when confronted with increasing processing demands, or they solve this problem in a different way? Here we scanned 37 children aged 7–13 and 19 young adults who performed a well-normed picture-naming task with 3 levels of difficulty. While neural organization for naming was largely similar in childhood and adulthood, adults had greater activation in all naming conditions over inferior temporal gyri and superior temporal gyri/supramarginal gyri. Manipulating naming complexity affected adults and children quite differently: neural activation, especially over the dorsolateral prefrontal cortex, showed complexity-dependent increases in adults, but complexity-dependent decreases in children. These represent fundamentally different responses to the linguistic and conceptual challenges of a simple naming task that makes no demands on literacy or metalinguistics. We discuss how these neural differences might result from different cognitive strategies used by adults and children during lexical retrieval/production as well as developmental changes in brain structure and functional connectivity. PMID:24907249

Population responses in V1 encode different figures by response amplitude.

PubMed

Gilad, Ariel; Slovin, Hamutal

2015-04-22

The visual system simultaneously segregates between several objects presented in a visual scene. The neural code for encoding different objects or figures is not well understood. To study this question, we trained two monkeys to discriminate whether two elongated bars are either separate, thus generating two different figures, or connected, thus generating a single figure. Using voltage-sensitive dyes, we imaged at high spatial and temporal resolution V1 population responses evoked by the two bars, while keeping their local attributes similar among the two conditions. In the separate condition, unlike the connected condition, the population response to one bar is enhanced, whereas the response to the other is simultaneously suppressed. The response to the background remained unchanged between the two conditions. This divergent pattern developed ∼200 ms poststimulus onset and could discriminate well between the separate and connected single trials. The stimulus separation saliency and behavioral report were highly correlated with the differential response to the bars. In addition, the proximity and/or the specific location of the connectors seemed to have only a weak effect on this late activity pattern, further supporting the involvement of top-down influences. Additional neural codes were less informative about the separate and connected conditions, with much less consistency and discriminability compared with a response amplitude code. We suggest that V1 is involved in the encoding of each figure by different neuronal response amplitude, which can mediate their segregation and perception. Copyright © 2015 the authors 0270-6474/15/356335-15$15.00/0.

Real-time biomimetic Central Pattern Generators in an FPGA for hybrid experiments

PubMed Central

Ambroise, Matthieu; Levi, Timothée; Joucla, Sébastien; Yvert, Blaise; Saïghi, Sylvain

2013-01-01

This investigation of the leech heartbeat neural network system led to the development of a low resources, real-time, biomimetic digital hardware for use in hybrid experiments. The leech heartbeat neural network is one of the simplest central pattern generators (CPG). In biology, CPG provide the rhythmic bursts of spikes that form the basis for all muscle contraction orders (heartbeat) and locomotion (walking, running, etc.). The leech neural network system was previously investigated and this CPG formalized in the Hodgkin–Huxley neural model (HH), the most complex devised to date. However, the resources required for a neural model are proportional to its complexity. In response to this issue, this article describes a biomimetic implementation of a network of 240 CPGs in an FPGA (Field Programmable Gate Array), using a simple model (Izhikevich) and proposes a new synapse model: activity-dependent depression synapse. The network implementation architecture operates on a single computation core. This digital system works in real-time, requires few resources, and has the same bursting activity behavior as the complex model. The implementation of this CPG was initially validated by comparing it with a simulation of the complex model. Its activity was then matched with pharmacological data from the rat spinal cord activity. This digital system opens the way for future hybrid experiments and represents an important step toward hybridization of biological tissue and artificial neural networks. This CPG network is also likely to be useful for mimicking the locomotion activity of various animals and developing hybrid experiments for neuroprosthesis development. PMID:24319408

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

PubMed

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.

Language-experience plasticity in neural representation of changes in pitch salience

PubMed Central

Krishnan, Ananthanarayan; Gandour, Jackson T.; Suresh, Chandan H.

2016-01-01

Neural representation of pitch-relevant information at the brainstem and cortical levels of processing is influenced by language experience. A well-known attribute of pitch is its salience. Brainstem frequency following responses and cortical pitch specific responses, recorded concurrently, were elicited by a pitch salience continuum spanning weak to strong pitch of a dynamic, iterated rippled noise pitch contour—homolog of a Mandarin tone. Our aims were to assess how language experience (Chinese, English) affects i) enhancement of neural activity associated with pitch salience at brainstem and cortical levels, ii) the presence of asymmetry in cortical pitch representation, and iii) patterns of relative changes in magnitude along the pitch salience continuum. Peak latency (Fz: Na, Pb, Nb) was shorter in the Chinese than the English group across the continuum. Peak-to-peak amplitude (Fz: Na-Pb, Pb-Nb) of the Chinese group grew larger with increasing pitch salience, but an experience-dependent advantage was limited to the Na-Pb component. At temporal sites (T7/T8), the larger amplitude of the Chinese group across the continuum was both limited to the Na-Pb component and the right temporal site. At the brainstem level, F0 magnitude gets larger as you increase pitch salience, and it too reveals Chinese superiority. A direct comparison of cortical and brainstem responses for the Chinese group reveals different patterns of relative changes in magnitude along the pitch salience continuum. Such differences may point to a transformation in pitch processing at the cortical level presumably mediated by local sensory and/or extrasensory influence overlaid on the brainstem output. PMID:26903418

Orthogonal Patterns In A Binary Neural Network

NASA Technical Reports Server (NTRS)

Baram, Yoram

1991-01-01

Report presents some recent developments in theory of binary neural networks. Subject matter relevant to associate (content-addressable) memories and to recognition of patterns - both of considerable importance in advancement of robotics and artificial intelligence. When probed by any pattern, network converges to one of stored patterns.

Subjective and clinical assessment criteria suggestive for five clinical patterns discernible in nonspecific neck pain patients. A Delphi-survey of clinical experts.

PubMed

Dewitte, Vincent; Peersman, Wim; Danneels, Lieven; Bouche, Katie; Roets, Arne; Cagnie, Barbara

2016-12-01

Nonspecific neck pain patients form a heterogeneous group with different musculoskeletal impairments. Classifying nonspecific neck pain patients into subgroups based on clinical characteristics might lead to more comprehensive diagnoses and can guide effective management. To establish consensus among a group of experts regarding the clinical criteria suggestive of a clinical dominance of 'articular', 'myofascial', 'neural', 'central' and 'sensorimotor control' dysfunction patterns distinguishable in patients with nonspecific neck pain. Delphi study. A focus group with 10 academic experts was organized to elaborate on the different dysfunction patterns discernible in neck pain patients. Consecutively, a 3-round online Delphi-survey was designed to obtain consensual symptoms and physical examination findings for the 5 distinct dysfunction patterns resulting from the focus group. A total of 21 musculoskeletal physical therapists from Belgium and the Netherlands experienced in assessing and treating neck pain patients completed the 3-round Delphi-survey. Respectively, 33 (response rate, 100.0%), 27 (81.8%) and 21 (63.6%) respondents replied to rounds 1, 2 and 3. Eighteen 'articular', 16 'myofascial', 20 'neural', 18 'central' and 10 'sensorimotor control' clinical indicators reached a predefined ≥80% consensus level. These indicators suggestive of a clinical dominance of 'articular', 'myofascial', 'neural', 'central', and 'sensorimotor control' dysfunction patterns may help clinicians to assess and diagnose patients with nonspecific neck pain. Future validity testing is needed to determine how these criteria may help to improve the outcome of physical therapy interventions in nonspecific neck pain patients. Copyright © 2016 Elsevier Ltd. All rights reserved.

The neural mechanisms of semantic and response conflicts: an fMRI study of practice-related effects in the Stroop task.

PubMed

Chen, Zhencai; Lei, Xu; Ding, Cody; Li, Hong; Chen, Antao

2013-02-01

Previous studies have demonstrated that there are separate neural mechanisms underlying semantic and response conflicts in the Stroop task. However, the practice effects of these conflicts need to be elucidated and the possible involvements of common neural mechanisms are yet to be established. We employed functional magnetic resonance imaging (fMRI) in a 4-2 mapping practice-related Stroop task to determine the neural substrates under these conflicts. Results showed that different patterns of brain activations are associated with practice in the attentional networks (e.g., dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), and posterior parietal cortex (PPC)) for both conflicts, response control regions (e.g., inferior frontal junction (IFJ), inferior frontal gyrus (IFG)/insula, and pre-supplementary motor areas (pre-SMA)) for semantic conflict, and posterior cortex for response conflict. We also found areas of common activation in the left hemisphere within the attentional networks, for the early practice stage in semantic conflict and the late stage in "pure" response conflict using conjunction analysis. The different practice effects indicate that there are distinct mechanisms underlying these two conflict types: semantic conflict practice effects are attributable to the automation of stimulus processing, conflict and response control; response conflict practice effects are attributable to the proportional increase of conflict-related cognitive resources. In addition, the areas of common activation suggest that the semantic conflict effect may contain a partial response conflict effect, particularly at the beginning of the task. These findings indicate that there are two kinds of response conflicts contained in the key-pressing Stroop task: the vocal-level (mainly in the early stage) and key-pressing (mainly in the late stage) response conflicts; thus, the use of the subtraction method for the exploration of semantic and response conflicts may need to be further examined. Copyright © 2012 Elsevier Inc. All rights reserved.

Complex auditory behaviour emerges from simple reactive steering

NASA Astrophysics Data System (ADS)

Hedwig, Berthold; Poulet, James F. A.

2004-08-01

The recognition and localization of sound signals is fundamental to acoustic communication. Complex neural mechanisms are thought to underlie the processing of species-specific sound patterns even in animals with simple auditory pathways. In female crickets, which orient towards the male's calling song, current models propose pattern recognition mechanisms based on the temporal structure of the song. Furthermore, it is thought that localization is achieved by comparing the output of the left and right recognition networks, which then directs the female to the pattern that most closely resembles the species-specific song. Here we show, using a highly sensitive method for measuring the movements of female crickets, that when walking and flying each sound pulse of the communication signal releases a rapid steering response. Thus auditory orientation emerges from reactive motor responses to individual sound pulses. Although the reactive motor responses are not based on the song structure, a pattern recognition process may modulate the gain of the responses on a longer timescale. These findings are relevant to concepts of insect auditory behaviour and to the development of biologically inspired robots performing cricket-like auditory orientation.

Computing with Neural Synchrony

PubMed Central

Brette, Romain

2012-01-01

Neurons communicate primarily with spikes, but most theories of neural computation are based on firing rates. Yet, many experimental observations suggest that the temporal coordination of spikes plays a role in sensory processing. Among potential spike-based codes, synchrony appears as a good candidate because neural firing and plasticity are sensitive to fine input correlations. However, it is unclear what role synchrony may play in neural computation, and what functional advantage it may provide. With a theoretical approach, I show that the computational interest of neural synchrony appears when neurons have heterogeneous properties. In this context, the relationship between stimuli and neural synchrony is captured by the concept of synchrony receptive field, the set of stimuli which induce synchronous responses in a group of neurons. In a heterogeneous neural population, it appears that synchrony patterns represent structure or sensory invariants in stimuli, which can then be detected by postsynaptic neurons. The required neural circuitry can spontaneously emerge with spike-timing-dependent plasticity. Using examples in different sensory modalities, I show that this allows simple neural circuits to extract relevant information from realistic sensory stimuli, for example to identify a fluctuating odor in the presence of distractors. This theory of synchrony-based computation shows that relative spike timing may indeed have computational relevance, and suggests new types of neural network models for sensory processing with appealing computational properties. PMID:22719243

Pattern recognition neural-net by spatial mapping of biology visual field

NASA Astrophysics Data System (ADS)

Lin, Xin; Mori, Masahiko

2000-05-01

The method of spatial mapping in biology vision field is applied to artificial neural networks for pattern recognition. By the coordinate transform that is called the complex-logarithm mapping and Fourier transform, the input images are transformed into scale- rotation- and shift- invariant patterns, and then fed into a multilayer neural network for learning and recognition. The results of computer simulation and an optical experimental system are described.

Single-exposure visual memory judgments are reflected in inferotemporal cortex

PubMed Central

Meyer, Travis

2018-01-01

Our visual memory percepts of whether we have encountered specific objects or scenes before are hypothesized to manifest as decrements in neural responses in inferotemporal cortex (IT) with stimulus repetition. To evaluate this proposal, we recorded IT neural responses as two monkeys performed a single-exposure visual memory task designed to measure the rates of forgetting with time. We found that a weighted linear read-out of IT was a better predictor of the monkeys’ forgetting rates and reaction time patterns than a strict instantiation of the repetition suppression hypothesis, expressed as a total spike count scheme. Behavioral predictions could be attributed to visual memory signals that were reflected as repetition suppression and were intermingled with visual selectivity, but only when combined across the most sensitive neurons. PMID:29517485

Distinctive and common neural underpinnings of major depression, social anxiety, and their comorbidity

PubMed Central

Chen, Michael C.; Waugh, Christian E.; Joormann, Jutta; Gotlib, Ian H.

2015-01-01

Assessing neural commonalities and differences among depression, anxiety and their comorbidity is critical in developing a more integrative clinical neuroscience and in evaluating currently debated categorical vs dimensional approaches to psychiatric classification. Therefore, in this study, we sought to identify patterns of anomalous neural responding to criticism and praise that are specific to and common among major depressive disorder (MDD), social anxiety disorder (SAD) and comorbid MDD-SAD. Adult females who met formal diagnostic criteria for MDD, SAD or MDD-SAD and psychiatrically healthy participants underwent functional magnetic resonance imaging as they listened to statements directing praise or criticism at them or at another person. MDD groups showed reduced responding to praise across a distributed cortical network, an effect potentially mediated by thalamic nuclei undergirding arousal-mediated attention. SAD groups showed heightened anterior insula and decreased default-mode network response to criticism. The MDD-SAD group uniquely showed reduced responding to praise in the dorsal anterior cingulate cortex. Finally, all groups with psychopathology showed heightened response to criticism in a region of the superior frontal gyrus implicated in attentional gating. The present results suggest novel neural models of anhedonia in MDD, vigilance-withdrawal behaviors in SAD, and poorer outcome in MDD-SAD. Importantly, in identifying unique and common neural substrates of MDD and SAD, these results support a formulation in which common neural components represent general risk factors for psychopathology that, due to factors that are present at illness onset, lead to distinct forms of psychopathology with unique neural signatures. PMID:25038225

An improved genetic algorithm for designing optimal temporal patterns of neural stimulation

NASA Astrophysics Data System (ADS)

Cassar, Isaac R.; Titus, Nathan D.; Grill, Warren M.

2017-12-01

Objective. Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach. We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main results. The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance. The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.

Computational Psychiatry of ADHD: Neural Gain Impairments across Marrian Levels of Analysis

PubMed Central

Hauser, Tobias U.; Fiore, Vincenzo G.; Moutoussis, Michael; Dolan, Raymond J.

2016-01-01

Attention-deficit hyperactivity disorder (ADHD), one of the most common psychiatric disorders, is characterised by unstable response patterns across multiple cognitive domains. However, the neural mechanisms that explain these characteristic features remain unclear. Using a computational multilevel approach, we propose that ADHD is caused by impaired gain modulation in systems that generate this phenotypic increased behavioural variability. Using Marr's three levels of analysis as a heuristic framework, we focus on this variable behaviour, detail how it can be explained algorithmically, and how it might be implemented at a neural level through catecholamine influences on corticostriatal loops. This computational, multilevel, approach to ADHD provides a framework for bridging gaps between descriptions of neuronal activity and behaviour, and provides testable predictions about impaired mechanisms. PMID:26787097

Patterning of somatosympathetic reflexes

NASA Technical Reports Server (NTRS)

Kerman, I. A.; Yates, B. J.

1999-01-01

In a previous study, we reported that vestibular nerve stimulation in the cat elicits a specific pattern of sympathetic nerve activation, such that responses are particularly large in the renal nerve. This patterning of vestibulosympathetic reflexes was the same in anesthetized and decerebrate preparations. In the present study, we report that inputs from skin and muscle also elicit a specific patterning of sympathetic outflow, which is distinct from that produced by vestibular stimulation. Renal, superior mesenteric, and lumbar colonic nerves respond most strongly to forelimb and hindlimb nerve stimulation (approximately 60% of maximal nerve activation), whereas external carotid and hypogastric nerves were least sensitive to these inputs (approximately 20% of maximal nerve activation). In contrast to vestibulosympathetic reflexes, the expression of responses to skin and muscle afferent activation differs in decerebrate and anesthetized animals. In baroreceptor-intact animals, somatosympathetic responses were strongly attenuated (to <20% of control in every nerve) by increasing blood pressure levels to >150 mmHg. These findings demonstrate that different types of somatic inputs elicit specific patterns of sympathetic nerve activation, presumably generated through distinct neural circuits.

Dynamic neural network models of the premotoneuronal circuitry controlling wrist movements in primates.

PubMed

Maier, M A; Shupe, L E; Fetz, E E

2005-10-01

Dynamic recurrent neural networks were derived to simulate neuronal populations generating bidirectional wrist movements in the monkey. The models incorporate anatomical connections of cortical and rubral neurons, muscle afferents, segmental interneurons and motoneurons; they also incorporate the response profiles of four populations of neurons observed in behaving monkeys. The networks were derived by gradient descent algorithms to generate the eight characteristic patterns of motor unit activations observed during alternating flexion-extension wrist movements. The resulting model generated the appropriate input-output transforms and developed connection strengths resembling those in physiological pathways. We found that this network could be further trained to simulate additional tasks, such as experimentally observed reflex responses to limb perturbations that stretched or shortened the active muscles, and scaling of response amplitudes in proportion to inputs. In the final comprehensive network, motor units are driven by the combined activity of cortical, rubral, spinal and afferent units during step tracking and perturbations. The model displayed many emergent properties corresponding to physiological characteristics. The resulting neural network provides a working model of premotoneuronal circuitry and elucidates the neural mechanisms controlling motoneuron activity. It also predicts several features to be experimentally tested, for example the consequences of eliminating inhibitory connections in cortex and red nucleus. It also reveals that co-contraction can be achieved by simultaneous activation of the flexor and extensor circuits without invoking features specific to co-contraction.

Detection of deception based on fMRI activation patterns underlying the production of a deceptive response and receiving feedback about the success of the deception after a mock murder crime

PubMed Central

Cui, Qian; Vanman, Eric J.; Wei, Dongtao; Yang, Wenjing; Jia, Lei

2014-01-01

The ability of a deceiver to track a victim’s ongoing judgments about the truthfulness of the deceit can be critical for successful deception. However, no study has yet investigated the neural circuits underlying receiving a judgment about one’s lie. To explore this issue, we used a modified Guilty Knowledge Test in a mock murder situation to simultaneously record the neural responses involved in producing deception and later when judgments of that deception were made. Producing deception recruited the bilateral inferior parietal lobules (IPLs), right ventral lateral prefrontal (VLPF) areas and right striatum, among which the activation of the right VLPF contributed mostly to diagnosing the identities of the participants, correctly diagnosing 81.25% of ‘murderers’ and 81.25% of ‘innocents’. Moreover, the participant’s response when their deception was successful uniquely recruited the right middle frontal gyrus, bilateral IPLs, bilateral orbitofrontal cortices, bilateral middle temporal gyrus and left cerebellum, among which the right IPL contributed mostly to diagnosing participants’ identities, correctly diagnosing 93.75% of murderers and 87.5% of innocents. This study shows that neural activity associated with being a successful liar (or not) is a feasible indicator for detecting lies and may be more valid than neural activity associated with producing deception. PMID:23946002

The Impact of Anxiety-Inducing Distraction on Cognitive Performance: A Combined Brain Imaging and Personality Investigation

PubMed Central

Denkova, Ekaterina; Wong, Gloria; Dolcos, Sanda; Sung, Keen; Wang, Lihong; Coupland, Nicholas; Dolcos, Florin

2010-01-01

Background Previous investigations revealed that the impact of task-irrelevant emotional distraction on ongoing goal-oriented cognitive processing is linked to opposite patterns of activation in emotional and perceptual vs. cognitive control/executive brain regions. However, little is known about the role of individual variations in these responses. The present study investigated the effect of trait anxiety on the neural responses mediating the impact of transient anxiety-inducing task-irrelevant distraction on cognitive performance, and on the neural correlates of coping with such distraction. We investigated whether activity in the brain regions sensitive to emotional distraction would show dissociable patterns of co-variation with measures indexing individual variations in trait anxiety and cognitive performance. Methodology/Principal Findings Event-related fMRI data, recorded while healthy female participants performed a delayed-response working memory (WM) task with distraction, were investigated in conjunction with behavioural measures that assessed individual variations in both trait anxiety and WM performance. Consistent with increased sensitivity to emotional cues in high anxiety, specific perceptual areas (fusiform gyrus - FG) exhibited increased activity that was positively correlated with trait anxiety and negatively correlated with WM performance, whereas specific executive regions (right lateral prefrontal cortex - PFC) exhibited decreased activity that was negatively correlated with trait anxiety. The study also identified a role of the medial and left lateral PFC in coping with distraction, as opposed to reflecting a detrimental impact of emotional distraction. Conclusions These findings provide initial evidence concerning the neural mechanisms sensitive to individual variations in trait anxiety and WM performance, which dissociate the detrimental impact of emotion distraction and the engagement of mechanisms to cope with distracting emotions. Our study sheds light on the neural correlates of emotion-cognition interactions in normal behaviour, which has implications for understanding factors that may influence susceptibility to affective disorders, in general, and to anxiety disorders, in particular. PMID:21152391

Spike-train communities: finding groups of similar spike trains.

PubMed

Humphries, Mark D

2011-02-09

Identifying similar spike-train patterns is a key element in understanding neural coding and computation. For single neurons, similar spike patterns evoked by stimuli are evidence of common coding. Across multiple neurons, similar spike trains indicate potential cell assemblies. As recording technology advances, so does the urgent need for grouping methods to make sense of large-scale datasets of spike trains. Existing methods require specifying the number of groups in advance, limiting their use in exploratory analyses. I derive a new method from network theory that solves this key difficulty: it self-determines the maximum number of groups in any set of spike trains, and groups them to maximize intragroup similarity. This method brings us revealing new insights into the encoding of aversive stimuli by dopaminergic neurons, and the organization of spontaneous neural activity in cortex. I show that the characteristic pause response of a rat's dopaminergic neuron depends on the state of the superior colliculus: when it is inactive, aversive stimuli invoke a single pattern of dopaminergic neuron spiking; when active, multiple patterns occur, yet the spike timing in each is reliable. In spontaneous multineuron activity from the cortex of anesthetized cat, I show the existence of neural ensembles that evolve in membership and characteristic timescale of organization during global slow oscillations. I validate these findings by showing that the method both is remarkably reliable at detecting known groups and can detect large-scale organization of dynamics in a model of the striatum.

Patterns recognition of electric brain activity using artificial neural networks

NASA Astrophysics Data System (ADS)

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.

Electronic system with memristive synapses for pattern recognition

PubMed Central

Park, Sangsu; Chu, Myonglae; Kim, Jongin; Noh, Jinwoo; Jeon, Moongu; Hun Lee, Byoung; Hwang, Hyunsang; Lee, Boreom; Lee, Byung-geun

2015-01-01

Memristive synapses, the most promising passive devices for synaptic interconnections in artificial neural networks, are the driving force behind recent research on hardware neural networks. Despite significant efforts to utilize memristive synapses, progress to date has only shown the possibility of building a neural network system that can classify simple image patterns. In this article, we report a high-density cross-point memristive synapse array with improved synaptic characteristics. The proposed PCMO-based memristive synapse exhibits the necessary gradual and symmetrical conductance changes, and has been successfully adapted to a neural network system. The system learns, and later recognizes, the human thought pattern corresponding to three vowels, i.e. /a /, /i /, and /u/, using electroencephalography signals generated while a subject imagines speaking vowels. Our successful demonstration of a neural network system for EEG pattern recognition is likely to intrigue many researchers and stimulate a new research direction. PMID:25941950

Experiential, Autonomic, and Neural Responses During Threat Anticipation Vary as a Function of Threat Intensity and Neuroticism

PubMed Central

Drabant, Emily M; Kuo, Janice R; Ramel, Wiveka; Blechert, Jens; Edge, Michael D; Cooper, Jeff R; Goldin, Philippe R; Hariri, Ahmad R; Gross, James J

2011-01-01

Anticipatory emotional responses play a crucial role in preparing individuals for impending challenges. They do this by triggering a coordinated set of changes in behavioral, autonomic, and neural response systems. In the present study, we examined the biobehavioral impact of varying levels of anticipatory anxiety, using a shock anticipation task in which unpredictable electric shocks were threatened and delivered to the wrist at variable intervals and intensities (safe, medium, strong). This permitted investigation of a dynamic range of anticipatory anxiety responses. In two studies, 95 and 51 healthy female participants, respectively, underwent this shock anticipation task while providing continuous ratings of anxiety experience and electrodermal responding (Study 1) and during fMRI BOLD neuroimaging (Study 2). Results indicated a step-wise pattern of responding in anxiety experience and electrodermal responses. Several brain regions showed robust responses to shock anticipation relative to safe trials, including the hypothalamus, periaqueductal gray, caudate, precentral gyrus, thalamus, insula, ventrolateral PFC, dorsomedial PFC, and ACC. A subset of these regions demonstrated a linear pattern of increased responding from safe to medium to strong trials, including the bilateral insula, ACC, and inferior frontal gyrus. These responses were modulated by individual differences in neuroticism, such that those high in neuroticism showed exaggerated anxiety experience across the entire task, and reduced brain activation from medium to strong trials in a subset of brain regions. These findings suggest that individual differences in neuroticism may influence sensitivity to anticipatory threat and provide new insights into the mechanism through which neuroticism may confer risk for developing anxiety disorders via dysregulated anticipatory responses. PMID:21093595

GABAergic Local Interneurons Shape Female Fruit Fly Response to Mating Songs.

PubMed

Yamada, Daichi; Ishimoto, Hiroshi; Li, Xiaodong; Kohashi, Tsunehiko; Ishikawa, Yuki; Kamikouchi, Azusa

2018-05-02

Many animals use acoustic signals to attract a potential mating partner. In fruit flies ( Drosophila melanogaster ), the courtship pulse song has a species-specific interpulse interval (IPI) that activates mating. Although a series of auditory neurons in the fly brain exhibit different tuning patterns to IPIs, it is unclear how the response of each neuron is tuned. Here, we studied the neural circuitry regulating the activity of antennal mechanosensory and motor center (AMMC)-B1 neurons, key secondary auditory neurons in the excitatory neural pathway that relay song information. By performing Ca 2+ imaging in female flies, we found that the IPI selectivity observed in AMMC-B1 neurons differs from that of upstream auditory sensory neurons [Johnston's organ (JO)-B]. Selective knock-down of a GABA A receptor subunit in AMMC-B1 neurons increased their response to short IPIs, suggesting that GABA suppresses AMMC-B1 activity at these IPIs. Connection mapping identified two GABAergic local interneurons that synapse with AMMC-B1 and JO-B. Ca 2+ imaging combined with neuronal silencing revealed that these local interneurons, AMMC-LN and AMMC-B2, shape the response pattern of AMMC-B1 neurons at a 15 ms IPI. Neuronal silencing studies further suggested that both GABAergic local interneurons suppress the behavioral response to artificial pulse songs in flies, particularly those with a 15 ms IPI. Altogether, we identified a circuit containing two GABAergic local interneurons that affects the temporal tuning of AMMC-B1 neurons in the song relay pathway and the behavioral response to the courtship song. Our findings suggest that feedforward inhibitory pathways adjust the behavioral response to courtship pulse songs in female flies. SIGNIFICANCE STATEMENT To understand how the brain detects time intervals between sound elements, we studied the neural pathway that relays species-specific courtship song information in female Drosophila melanogaster We demonstrate that the signal transmission from auditory sensory neurons to key secondary auditory neurons antennal mechanosensory and motor center (AMMC)-B1 is the first-step to generate time interval selectivity of neurons in the song relay pathway. Two GABAergic local interneurons are suggested to shape the interval selectivity of AMMC-B1 neurons by receiving auditory inputs and in turn providing feedforward inhibition onto AMMC-B1 neurons. Furthermore, these GABAergic local interneurons suppress the song response behavior in an interval-dependent manner. Our results provide new insights into the neural circuit basis to adjust neuronal and behavioral responses to a species-specific communication sound. Copyright © 2018 the authors 0270-6474/18/384329-19$15.00/0.

Optical responses evoked by white matter stimulation in rat visual cortical slices and their relation to neural activities.

PubMed

Tanifuji, M; Yamanaka, A; Sunaba, R; Terakawa, S; Toyama, K

1996-10-28

To characterize optical responses (ORs) evoked by white matter (WM) stimulation in slices of rat visual cortex (VC) stained with voltage sensitive dyes, time course of ORs in each layer was investigated by recording ORs with a linearly aligned photodiode array, and the spatial patterns of the ORs at specified time after stimulation were investigated by a CCD camera in combination with stroboscopic illumination. The ORs recorded by the photodiode array were an increase in absorption at 700 nm and a decrease in the wavelength below 650 nm, suggesting that the ORs were dye related. The ORs were compared with field potentials (FPs) to clarify that neural events were represented by the ORs, and in support of this view, we found that the first order spatial differentials of ORs and that of FPs were in good agreement. We further compared ORs with intracellular responses, and found that the ORs mainly represent postsynaptic potentials (PSPs) of VC neurons except for the deeper part of layer VI, where a component representing action potentials in fibers stimulated directly was observed. The time-lapse imaging of ORs showed that excitation first propagated vertically up to layer I and subsequently in the horizontal direction along layers II-III and V-VI as in previous investigations. Spatio-temporal patterns of ORs under blockade of synaptic transmission were also investigated to reveal activity of fibers evoked by WM stimulation which produced such patterns of propagation.

Neuronal pattern separation of motion-relevant input in LIP activity

PubMed Central

Berberian, Nareg; MacPherson, Amanda; Giraud, Eloïse; Richardson, Lydia

2016-01-01

In various regions of the brain, neurons discriminate sensory stimuli by decreasing the similarity between ambiguous input patterns. Here, we examine whether this process of pattern separation may drive the rapid discrimination of visual motion stimuli in the lateral intraparietal area (LIP). Starting with a simple mean-rate population model that captures neuronal activity in LIP, we show that overlapping input patterns can be reformatted dynamically to give rise to separated patterns of neuronal activity. The population model predicts that a key ingredient of pattern separation is the presence of heterogeneity in the response of individual units. Furthermore, the model proposes that pattern separation relies on heterogeneity in the temporal dynamics of neural activity and not merely in the mean firing rates of individual neurons over time. We confirm these predictions in recordings of macaque LIP neurons and show that the accuracy of pattern separation is a strong predictor of behavioral performance. Overall, results propose that LIP relies on neuronal pattern separation to facilitate decision-relevant discrimination of sensory stimuli. NEW & NOTEWORTHY A new hypothesis is proposed on the role of the lateral intraparietal (LIP) region of cortex during rapid decision making. This hypothesis suggests that LIP alters the representation of ambiguous inputs to reduce their overlap, thus improving sensory discrimination. A combination of computational modeling, theoretical analysis, and electrophysiological data shows that the pattern separation hypothesis links neural activity to behavior and offers novel predictions on the role of LIP during sensory discrimination. PMID:27881719

Architecture of enteric neural circuits involved in intestinal motility.

PubMed

Costa, M; Brookes, S H

2008-08-01

This short review describes the conceptual development in the search for the enteric neural circuits with the initial identifications of the classes of enteric neurons on the bases of their morphology, neurochemistry, biophysical properties, projections and connectivity. The discovery of the presence of multiple neurochemicals in the same nerve cells in specific combinations led to the concept of "chemical coding" and of "plurichemical transmission". The proposal that enteric reflexes are largely responsible for the propulsion of contents led to investigations of polarised reflex pathways and how these may be activated to generate the coordinated propulsive behaviour of the intestine. The research over the past decades attempted to integrate information of chemical neuroanatomy with functional studies, with the development of methods combining anatomical, functional and pharmacological techniques. This multidisciplinary strategy led to a full accounting of all functional classes of enteric neurons in the guinea-pig, and advanced wiring diagrams of the enteric neural circuits have been proposed. In parallel, investigations of the actual behaviour of the intestine during physiological motor activity have advanced with the development of spatio-temporal analysis from video recordings. The relation between neural pathways, their activities and the generation of patterns of motor activity remain largely unexplained. The enteric neural circuits appear not set in rigid programs but respond to different physico-chemical contents in an adaptable way (neuromechanical hypothesis). The generation of the complex repertoire of motor patterns results from the interplay of myogenic and neuromechanical mechanisms with spontaneous generation of migratory motor activity by enteric circuits.

Photopolymerized materials and patterning for improved performance of neural prosthetics

NASA Astrophysics Data System (ADS)

Tuft, Bradley William

Neural prosthetics are used to replace or substantially augment remaining motor and sensory functions of neural pathways that were lost or damaged due to physical trauma, disease, or genetics. However, due to poor spatial signal resolution, neural prostheses fail to recapitulate the intimate, precise interactions inherent to neural networks. Designing materials and interfaces that direct de novo nerve growth to spatially specific stimulating elements is, therefore, a promising method to enhance signal specificity and performance of prostheses such as the successful cochlear implant (CI) and the developing retinal implant. In this work, the spatial and temporal reaction control inherent to photopolymerization was used to develop methods to generate micro and nanopatterned materials that direct neurite growth from prosthesis relevant neurons. In particular, neurite growth and directionality has been investigated in response to physical, mechanical, and chemical cues on photopolymerized surfaces. Spiral ganglion neurons (SGNs) serve as the primary neuronal model as they are the principal target for CI stimulation. The objective of the research is to rationally design materials that spatially direct neurite growth and to translate fundamental understanding of nerve cell-material interactions into methods of nerve regeneration that improve neural prosthetic performance. A rapid, single-step photopolymerization method was developed to fabricate micro and nanopatterned physical cues on methacrylate surfaces by selectively blocking light with photomasks. Feature height is readily tuned by modulating parameters of the photopolymerizaiton including initiator concentration and species, light intensity, separation distance from the photomask, and radiation exposure time. Alignment of neural elements increases significantly with increasing feature amplitude and constant periodicity, as well as with decreasing periodicity and constant amplitude. SGN neurite alignment strongly correlates with the maximum feature slope. Neurite alignment is compared on unpatterned, unidirectional, and multidirectional photopolymerized micropatterns. The effect of substrate rigidity on neurite alignment to physical cues was determined by maintaining equivalent pattern microfeatures, afforded by the reaction control of photopolymerization, while concomitantly altering the composition of several copolymer platforms to tune matrix stiffness. For each platform, neurite alignment to unidirectional patterns increases with increasing substrate rigidity. Interestingly, SGN neurites respond to material stiffness cues that are orders of magnitude higher (GPa) than what is typically ascribed to neural environments (kPa). Finally, neurite behavior at bioactive borders of various adhesion modulating molecules was evaluated on micropatterned materials to determine which cues took precedence in establishing neurite directionality. At low microfeatures aspect ratios, neurites align to the pattern direction but are then caused to turn and repel from or turn and align to bioactive borders. Conversely, physical cues dominate neurite path-finding as pattern feature slope increases, i.e. aspect ratio of sloping photopolymerized features increases, causing neurites to readily cross bioactive borders. The photopolymerization method developed in this work to generate micro and nanopatterned materials serves as an additional surface engineering tool that enables investigation of cell-material interactions including directed de novo neurite growth. The results of this interdisciplinary effort contribute substantially to polymer neural regeneration technology and will lead to development of advanced biomaterials that improve neural prosthetic tissue integration and performance by spatially directing nerve growth.

Reward-related neural responses are dependent on the beneficiary

PubMed Central

Güroğlu, Berna; de Water, Erik; Meuwese, Rosa; Koolschijn, P. Cédric; Peper, Jiska S.; Crone, Eveline A.

2014-01-01

Prior studies have suggested that positive social interactions are experienced as rewarding. Yet, it is not well understood how social relationships influence neural responses to other persons’ gains. In this study, we investigated neural responses during a gambling task in which healthy participants (N = 31; 18 females) could win or lose money for themselves, their best friend or a disliked other (antagonist). At the moment of receiving outcome, person-related activity was observed in the dorsal medial prefrontal cortex (dmPFC), precuneus and temporal parietal junction (TPJ), showing higher activity for friends and antagonists than for self, and this activity was independent of outcome. The only region showing an interaction between the person-participants played for and outcome was the ventral striatum. Specifically, the striatum was more active following gains than losses for self and friends, whereas for the antagonist this pattern was reversed. Together, these results show that, in a context with social and reward information, social aspects are processed in brain regions associated with social cognition (mPFC, TPJ), and reward aspects are processed in primary reward areas (striatum). Furthermore, there is an interaction of social and reward information in the striatum, such that reward-related activity was dependent on social relationship. PMID:23720575

Processing of Communication Sounds: Contributions of Learning, Memory, and Experience

PubMed Central

Bigelow, James; Rossi, Breein

2013-01-01

Abundant evidence from both field and lab studies has established that conspecific vocalizations (CVs) are of critical ecological significance for a wide variety of species, including humans, nonhuman primates, rodents, and other mammals and birds. Correspondingly, a number of experiments have demonstrated behavioral processing advantages for CVs, such as in discrimination and memory tasks. Further, a wide range of experiments have described brain regions in many species that appear to be specialized for processing CVs. For example, several neural regions have been described in both mammals and birds wherein greater neural responses are elicited by CVs than by comparison stimuli such as heterospecific vocalizations, nonvocal complex sounds, and artificial stimuli. These observations raise the question of whether these regions reflect domain-specific neural mechanisms dedicated to processing CVs, or alternatively, if these regions reflect domain-general neural mechanisms for representing complex sounds of learned significance. Inasmuch as CVs can be viewed as complex combinations of basic spectrotemporal features, the plausibility of the latter position is supported by a large body of literature describing modulated cortical and subcortical representation of a variety of acoustic features that have been experimentally associated with stimuli of natural behavioral significance (such as food rewards). Herein, we review a relatively small body of existing literature describing the roles of experience, learning, and memory in the emergence of species-typical neural representations of CVs and auditory system plasticity. In both songbirds and mammals, manipulations of auditory experience as well as specific learning paradigms are shown to modulate neural responses evoked by CVs, either in terms of overall firing rate or temporal firing patterns. In some cases, CV-sensitive neural regions gradually acquire representation of non-CV stimuli with which subjects have training and experience. These results parallel literature in humans describing modulation of responses in face-sensitive neural regions through learning and experience. Thus, although many questions remain, the available evidence is consistent with the notion that CVs may acquire distinct neural representation through domain-general mechanisms for representing complex auditory objects that are of learned importance to the animal. PMID:23792078

Isolating age-group differences in working memory load-related neural activity: assessing the contribution of working memory capacity using a partial-trial fMRI method.

PubMed

Bennett, Ilana J; Rivera, Hannah G; Rypma, Bart

2013-05-15

Previous studies examining age-group differences in working memory load-related neural activity have yielded mixed results. When present, age-group differences in working memory capacity are frequently proposed to underlie these neural effects. However, direct relationships between working memory capacity and working memory load-related activity have only been observed in younger adults. These relationships remain untested in healthy aging. Therefore, the present study examined patterns of working memory load-related activity in 22 younger and 20 older adults and assessed the contribution of working memory capacity to these load-related effects. Participants performed a partial-trial delayed response item recognition task during functional magnetic resonance imaging. In this task, participants encoded either 2 or 6 letters, maintained them during a delay, and then indicated whether a probe was present in the memory set. Behavioral results revealed faster and more accurate responses to load 2 versus 6, with age-group differences in this load condition effect for the accuracy measure. Neuroimaging results revealed one region (medial superior frontal gyrus) that showed age-group differences in load-related activity during the retrieval period, with less (greater) neural activity for the low versus high load condition in younger (older) adults. Furthermore, for older adults, load-related activity did not vary as a function of working memory capacity. Thus, working memory-related activity varies with healthy aging, but these patterns are not due solely to working memory capacity. Neurocognitive aging theories that feature capacity will need to account for these results. Copyright © 2013 Elsevier Inc. All rights reserved.

Wnt/Yes-Associated Protein Interactions During Neural Tissue Patterning of Human Induced Pluripotent Stem Cells.

PubMed

Bejoy, Julie; Song, Liqing; Zhou, Yi; Li, Yan

2018-04-01

Human induced pluripotent stem cells (hiPSCs) have special ability to self-assemble into neural spheroids or mini-brain-like structures. During the self-assembly process, Wnt signaling plays an important role in regional patterning and establishing positional identity of hiPSC-derived neural progenitors. Recently, the role of Wnt signaling in regulating Yes-associated protein (YAP) expression (nuclear or cytoplasmic), the pivotal regulator during organ growth and tissue generation, has attracted increasing interests. However, the interactions between Wnt and YAP expression for neural lineage commitment of hiPSCs remain poorly explored. The objective of this study is to investigate the effects of Wnt signaling and YAP expression on the cellular population in three-dimensional (3D) neural spheroids derived from hiPSCs. In this study, Wnt signaling was activated using CHIR99021 for 3D neural spheroids derived from human iPSK3 cells through embryoid body formation. Our results indicate that Wnt activation induces nuclear localization of YAP and upregulates the expression of HOXB4, the marker for hindbrain/spinal cord. By contrast, the cells exhibit more rostral forebrain neural identity (expression of TBR1) without Wnt activation. Cytochalasin D was then used to induce cytoplasmic YAP and the results showed the decreased HOXB4 expression. In addition, the incorporation of microparticles in the neural spheroids was investigated for the perturbation of neural patterning. This study may indicate the bidirectional interactions of Wnt signaling and YAP expression during neural tissue patterning, which have the significance in neurological disease modeling, drug screening, and neural tissue regeneration.

Characterization of the Trunk Neural Crest in the bamboo shark, Chiloscyllium punctatum

PubMed Central

Juarez, Marilyn; Reyes, Michelle; Coleman, Tiffany; Rotenstein, Lisa; Sao, Sothy; Martinez, Darwin; Jones, Matthew; Mackelprang, Rachel; de Bellard, Maria Elena

2013-01-01

The neural crest is a population of mesenchymal cells that after migrating from the neural tube give rise to a structures and cell-types: jaw, part of the peripheral ganglia and melanocytes. Although much is known about neural crest development in jawed vertebrates, a clear picture of trunk neural crest development for elasmobranchs is yet to be developed. Here we present a detailed study of trunk neural crest development in the bamboo shark, Chiloscyllium punctatum. Vital labeling with DiI and in situ hybridization using cloned Sox8 and Sox9 probes demonstrated that trunk neural crest cells follow a pattern similar to the migratory paths already described in zebrafish and amphibians. We found shark trunk neural crest along the rostral side of the somites, the ventromedial pathway, branchial arches, gut, sensory ganglia and nerves. Interestingly, Chiloscyllium punctatum Sox8 and Sox9 sequences aligned with vertebrate SoxE genes, but appeared to be more ancient than the corresponding vertebrate paralogs. The expression of these two SoxE genes in trunk neural crest cells, especially Sox9, matched the Sox10 migratory patterns observed in teleosts. Interestingly, we observed DiI cells and Sox9 labeling along the lateral line, suggesting that in C. punctatum, glial cells in the lateral line are likely of neural crest origin. Though this has been observed in other vertebrates, we are the first to show that the pattern is present in cartilaginous fishes. These findings demonstrate that trunk neural crest cell development in Chiloscyllium punctatum follows the same highly conserved migratory pattern observed in jawed vertebrates PMID:23640803

Introduction to Neural Networks.

DTIC Science & Technology

1992-03-01

parallel processing of information that can greatly reduce the time required to perform operations which are needed in pattern recognition. Neural network, Artificial neural network , Neural net, ANN.

The neuronal response to electrical constant-amplitude pulse train stimulation: additive Gaussian noise.

PubMed

Matsuoka, A J; Abbas, P J; Rubinstein, J T; Miller, C A

2000-11-01

Experimental results from humans and animals show that electrically evoked compound action potential (EAP) responses to constant-amplitude pulse train stimulation can demonstrate an alternating pattern, due to the combined effects of highly synchronized responses to electrical stimulation and refractory effects (Wilson et al., 1994). One way to improve signal representation is to reduce the level of across-fiber synchrony and hence, the level of the amplitude alternation. To accomplish this goal, we have examined EAP responses in the presence of Gaussian noise added to the pulse train stimulus. Addition of Gaussian noise at a level approximately -30 dB relative to EAP threshold to the pulse trains decreased the amount of alternation, indicating that stochastic resonance may be induced in the auditory nerve. The use of some type of conditioning stimulus such as Gaussian noise may provide a more 'normal' neural response pattern.

Information Compression, Multiple Alignment, and the Representation and Processing of Knowledge in the Brain

PubMed Central

Wolff, J. Gerard

2016-01-01

The SP theory of intelligence, with its realization in the SP computer model, aims to simplify and integrate observations and concepts across artificial intelligence, mainstream computing, mathematics, and human perception and cognition, with information compression as a unifying theme. This paper describes how abstract structures and processes in the theory may be realized in terms of neurons, their interconnections, and the transmission of signals between neurons. This part of the SP theory—SP-neural—is a tentative and partial model for the representation and processing of knowledge in the brain. Empirical support for the SP theory—outlined in the paper—provides indirect support for SP-neural. In the abstract part of the SP theory (SP-abstract), all kinds of knowledge are represented with patterns, where a pattern is an array of atomic symbols in one or two dimensions. In SP-neural, the concept of a “pattern” is realized as an array of neurons called a pattern assembly, similar to Hebb's concept of a “cell assembly” but with important differences. Central to the processing of information in SP-abstract is information compression via the matching and unification of patterns (ICMUP) and, more specifically, information compression via the powerful concept of multiple alignment, borrowed and adapted from bioinformatics. Processes such as pattern recognition, reasoning and problem solving are achieved via the building of multiple alignments, while unsupervised learning is achieved by creating patterns from sensory information and also by creating patterns from multiple alignments in which there is a partial match between one pattern and another. It is envisaged that, in SP-neural, short-lived neural structures equivalent to multiple alignments will be created via an inter-play of excitatory and inhibitory neural signals. It is also envisaged that unsupervised learning will be achieved by the creation of pattern assemblies from sensory information and from the neural equivalents of multiple alignments, much as in the non-neural SP theory—and significantly different from the “Hebbian” kinds of learning which are widely used in the kinds of artificial neural network that are popular in computer science. The paper discusses several associated issues, with relevant empirical evidence. PMID:27857695

Advances in memory research: single-neuron recordings from the human medial temporal lobe aid our understanding of declarative memory.

PubMed

Viskontas, Indre V

2008-12-01

To gain a complete understanding of how the brain functions, both in illness and good health, data from multiple levels of analysis must be integrated. Technical advances have made direct recordings of neuronal activity deep inside the human brain tractable, providing a rare glimpse into cellular processes during long-term memory formation. Recent findings using intracranial recordings in the medial temporal lobe inform current neural network models of memory, and may lead to a more comprehensive understanding of the neural basis of memory-related processes. These recordings have shown that cells in the hippocampus appear to support declarative learning by distinguishing novel and familiar stimuli via changes in firing patterns. Some cells with highly selective and invariant responses have also been described, and these responses seem to represent abstract concepts such as identity, rather than superficial perceptual features of items. Importantly, however, both selective and globally responsive cells are capable of changing their preferred stimulus depending on the conscious demands of the task. Firing patterns of human medial temporal lobe neurons indicate that cells can be both plastic and stable in terms of the information that they code; although some cells show highly selective and reproducible excitatory responses when presented with a familiar object, other cells change their receptive fields in line with changes in experience and the cognitive environment.

An fMRI Investigation of Preparatory Set in the Human Cerebral Cortex and Superior Colliculus for Pro- and Anti-Saccades

PubMed Central

Furlan, Michele; Smith, Andrew T.; Walker, Robin

2016-01-01

Previous studies have identified several cortical regions that show larger BOLD responses during preparation and execution of anti-saccades than pro-saccades. We confirmed this finding with a greater BOLD response for anti-saccades than pro-saccades during the preparation phase in the FEF, IPS and DLPFC and in the FEF and IPS in the execution phase. We then applied multi-voxel pattern analysis (MVPA) to establish whether different neural populations are involved in the two types of saccade. Pro-saccades and anti-saccades were reliably decoded during saccade execution in all three cortical regions (FEF, DLPFC and IPS) and in IPS during saccade preparation. This indicates neural specialization, for programming the desired response depending on the task rule, in these regions. In a further study tailored for imaging the superior colliculus in the midbrain a similar magnitude BOLD response was observed for pro-saccades and anti-saccades and the two saccade types could not be decoded with MVPA. This was the case both for activity related to the preparation phase and also for that elicited during the execution phase. We conclude that separate cortical neural populations are involved in the task-specific programming of a saccade while in contrast, the SC has a role in response preparation but may be less involved in high-level, task-specific aspects of the control of saccades. PMID:27391390

Temperament and Parenting Styles in Early Childhood Differentially Influence Neural Response to Peer Evaluation in Adolescence.

PubMed

Guyer, Amanda E; Jarcho, Johanna M; Pérez-Edgar, Koraly; Degnan, Kathryn A; Pine, Daniel S; Fox, Nathan A; Nelson, Eric E

2015-07-01

Behavioral inhibition (BI) is a temperament characterized by social reticence and withdrawal from unfamiliar or novel contexts and conveys risk for social anxiety disorder. Developmental outcomes associated with this temperament can be influenced by children's caregiving context. The convergence of a child's temperamental disposition and rearing environment is ultimately expressed at both the behavioral and neural levels in emotional and cognitive response patterns to social challenges. The present study used functional neuroimaging to assess the moderating effects of different parenting styles on neural response to peer rejection in two groups of adolescents characterized by their early childhood temperament (M(age) = 17.89 years, N = 39, 17 males, 22 females; 18 with BI; 21 without BI). The moderating effects of authoritarian and authoritative parenting styles were examined in three brain regions linked with social anxiety: ventrolateral prefrontal cortex (vlPFC), striatum, and amygdala. In youth characterized with BI in childhood, but not in those without BI, diminished responses to peer rejection in vlPFC were associated with higher levels of authoritarian parenting. In contrast, all youth showed decreased caudate response to peer rejection at higher levels of authoritative parenting. These findings indicate that BI in early life relates to greater neurobiological sensitivity to variance in parenting styles, particularly harsh parenting, in late adolescence. These results are discussed in relation to biopsychosocial models of development.

Temperament and Parenting Styles in Early Childhood Differentially Influence Neural Response to Peer Evaluation in Adolescence

PubMed Central

Guyer, Amanda E.; Jarcho, Johanna M.; Pérez-Edgar, Koraly; Degnan, Kathryn A.; Pine, Daniel S.; Fox, Nathan A.; Nelson, Eric E.

2015-01-01

Behavioral inhibition (BI) is a temperament characterized by social reticence and withdrawal from unfamiliar or novel contexts and conveys risk for social anxiety disorder. Developmental outcomes associated with this temperament can be influenced by children’s caregiving context. The convergence of a child’s temperamental disposition and rearing environment is ultimately expressed at both the behavioral and neural levels in emotional and cognitive response patterns to social challenges. The present study used functional neuroimaging to assess the moderating effects of different parenting styles on neural response to peer rejection in two groups of adolescents characterized by their early childhood temperament (Mage = 17.89 years, N= 39, 17 males, 22 females; 18 with BI; 21 without BI). The moderating effects of authoritarian and authoritative parenting styles were examined in three brain regions linked with social anxiety: ventrolateral prefrontal cortex (vlPFC), striatum, and amygdala. In youth characterized with BI in childhood, but not in those without BI, diminished responses to peer rejection in vlPFC were associated with higher levels of authoritarian parenting. In contrast, all youth showed decreased caudate response to peer rejection at higher levels of authoritative parenting. These findings indicate that BI in early life relates to greater neurobiological sensitivity to variance in parenting styles, particularly harsh parenting, in late adolescence. These results are discussed in relation to biopsychosocial models of development. PMID:25588884

Oscillatory phase dynamics in neural entrainment underpin illusory percepts of time.

PubMed

Herrmann, Björn; Henry, Molly J; Grigutsch, Maren; Obleser, Jonas

2013-10-02

Neural oscillatory dynamics are a candidate mechanism to steer perception of time and temporal rate change. While oscillator models of time perception are strongly supported by behavioral evidence, a direct link to neural oscillations and oscillatory entrainment has not yet been provided. In addition, it has thus far remained unaddressed how context-induced illusory percepts of time are coded for in oscillator models of time perception. To investigate these questions, we used magnetoencephalography and examined the neural oscillatory dynamics that underpin pitch-induced illusory percepts of temporal rate change. Human participants listened to frequency-modulated sounds that varied over time in both modulation rate and pitch, and judged the direction of rate change (decrease vs increase). Our results demonstrate distinct neural mechanisms of rate perception: Modulation rate changes directly affected listeners' rate percept as well as the exact frequency of the neural oscillation. However, pitch-induced illusory rate changes were unrelated to the exact frequency of the neural responses. The rate change illusion was instead linked to changes in neural phase patterns, which allowed for single-trial decoding of percepts. That is, illusory underestimations or overestimations of perceived rate change were tightly coupled to increased intertrial phase coherence and changes in cerebro-acoustic phase lag. The results provide insight on how illusory percepts of time are coded for by neural oscillatory dynamics.

Modelling Peri-Perceptual Brain Processes in a Deep Learning Spiking Neural Network Architecture.

PubMed

Gholami Doborjeh, Zohreh; Kasabov, Nikola; Gholami Doborjeh, Maryam; Sumich, Alexander

2018-06-11

Familiarity of marketing stimuli may affect consumer behaviour at a peri-perceptual processing level. The current study introduces a method for deep learning of electroencephalogram (EEG) data using a spiking neural network (SNN) approach that reveals the complexity of peri-perceptual processes of familiarity. The method is applied to data from 20 participants viewing familiar and unfamiliar logos. The results support the potential of SNN models as novel tools in the exploration of peri-perceptual mechanisms that respond differentially to familiar and unfamiliar stimuli. Specifically, the activation pattern of the time-locked response identified by the proposed SNN model at approximately 200 milliseconds post-stimulus suggests greater connectivity and more widespread dynamic spatio-temporal patterns for familiar than unfamiliar logos. The proposed SNN approach can be applied to study other peri-perceptual or perceptual brain processes in cognitive and computational neuroscience.

Learning and retrieval behavior in recurrent neural networks with pre-synaptic dependent homeostatic plasticity

NASA Astrophysics Data System (ADS)

Mizusaki, Beatriz E. P.; Agnes, Everton J.; Erichsen, Rubem; Brunnet, Leonardo G.

2017-08-01

The plastic character of brain synapses is considered to be one of the foundations for the formation of memories. There are numerous kinds of such phenomenon currently described in the literature, but their role in the development of information pathways in neural networks with recurrent architectures is still not completely clear. In this paper we study the role of an activity-based process, called pre-synaptic dependent homeostatic scaling, in the organization of networks that yield precise-timed spiking patterns. It encodes spatio-temporal information in the synaptic weights as it associates a learned input with a specific response. We introduce a correlation measure to evaluate the precision of the spiking patterns and explore the effects of different inhibitory interactions and learning parameters. We find that large learning periods are important in order to improve the network learning capacity and discuss this ability in the presence of distinct inhibitory currents.

Fractal Patterns of Neural Activity Exist within the Suprachiasmatic Nucleus and Require Extrinsic Network Interactions

PubMed Central

Hu, Kun; Meijer, Johanna H.; Shea, Steven A.; vanderLeest, Henk Tjebbe; Pittman-Polletta, Benjamin; Houben, Thijs; van Oosterhout, Floor; Deboer, Tom; Scheer, Frank A. J. L.

2012-01-01

The mammalian central circadian pacemaker (the suprachiasmatic nucleus, SCN) contains thousands of neurons that are coupled through a complex network of interactions. In addition to the established role of the SCN in generating rhythms of ∼24 hours in many physiological functions, the SCN was recently shown to be necessary for normal self-similar/fractal organization of motor activity and heart rate over a wide range of time scales—from minutes to 24 hours. To test whether the neural network within the SCN is sufficient to generate such fractal patterns, we studied multi-unit neural activity of in vivo and in vitro SCNs in rodents. In vivo SCN-neural activity exhibited fractal patterns that are virtually identical in mice and rats and are similar to those in motor activity at time scales from minutes up to 10 hours. In addition, these patterns remained unchanged when the main afferent signal to the SCN, namely light, was removed. However, the fractal patterns of SCN-neural activity are not autonomous within the SCN as these patterns completely broke down in the isolated in vitro SCN despite persistence of circadian rhythmicity. Thus, SCN-neural activity is fractal in the intact organism and these fractal patterns require network interactions between the SCN and extra-SCN nodes. Such a fractal control network could underlie the fractal regulation observed in many physiological functions that involve the SCN, including motor control and heart rate regulation. PMID:23185285

How Do Stress Exposure and Stress Regulation Relate to Borderline Personality Disorder?

PubMed Central

Bourvis, Nadège; Aouidad, Aveline; Cabelguen, Clémence; Cohen, David; Xavier, Jean

2017-01-01

Borderline personality disorder (BPD) is a severe and frequent disorder characterized by a pervasive pattern of instability affecting impulse control, emotional regulation, cognitive processing, self-image and interpersonal relationships. Patients’ personal histories are often marked by stressful or traumatic experiences, either unique or repeated. Moreover, while clinical signs of the disorder include both chronic and acute features, acute features are mostly triggered by acute stressful situations. Such features include transient cognitive distortion, intense anger, uncontrollable impulsivity, and self-harm behavior – including suicide – and contribute to the burden of the disease. In this paper, we review the various aspects (epidemiological, clinical, and physiological) contributing to the relationship between BDP and stress. In particular, we explore the statistical association between stress exposure and the emergence of BPD while taking into account other psychopathologies, such as post-traumatic stress disorder. Then, the different aspects of stress responses (namely, the phenomenological, behavioral, hormonal, neuro-vegetative and neural responses) are reviewed in BPD patients. Pathophysiological hypotheses are formulated to explain the differences in responses between BPD patients and healthy subjects and their relation to BPD symptoms. Although the pathogenesis remains uncertain, our conclusions seem to reflect a specific biological and neural pattern of altered stress perception and regulation in BPD. PMID:29250007

How Do Stress Exposure and Stress Regulation Relate to Borderline Personality Disorder?

PubMed

Bourvis, Nadège; Aouidad, Aveline; Cabelguen, Clémence; Cohen, David; Xavier, Jean

2017-01-01

Borderline personality disorder (BPD) is a severe and frequent disorder characterized by a pervasive pattern of instability affecting impulse control, emotional regulation, cognitive processing, self-image and interpersonal relationships. Patients' personal histories are often marked by stressful or traumatic experiences, either unique or repeated. Moreover, while clinical signs of the disorder include both chronic and acute features, acute features are mostly triggered by acute stressful situations. Such features include transient cognitive distortion, intense anger, uncontrollable impulsivity, and self-harm behavior - including suicide - and contribute to the burden of the disease. In this paper, we review the various aspects (epidemiological, clinical, and physiological) contributing to the relationship between BDP and stress. In particular, we explore the statistical association between stress exposure and the emergence of BPD while taking into account other psychopathologies, such as post-traumatic stress disorder. Then, the different aspects of stress responses (namely, the phenomenological, behavioral, hormonal, neuro-vegetative and neural responses) are reviewed in BPD patients. Pathophysiological hypotheses are formulated to explain the differences in responses between BPD patients and healthy subjects and their relation to BPD symptoms. Although the pathogenesis remains uncertain, our conclusions seem to reflect a specific biological and neural pattern of altered stress perception and regulation in BPD.

Representation of tactile curvature in macaque somatosensory area 2

PubMed Central

Connor, Charles E.; Hsiao, Steven S.

2013-01-01

Tactile shape information is elaborated in a cortical hierarchy spanning primary (SI) and secondary somatosensory cortex (SII). Indeed, SI neurons in areas 3b and 1 encode simple contour features such as small oriented bars and edges, whereas higher order SII neurons represent large curved contour features such as angles and arcs. However, neural coding of these contour features has not been systematically characterized in area 2, the most caudal SI subdivision in the postcentral gyrus. In the present study, we analyzed area 2 neural responses to embossed oriented bars and curved contour fragments to establish whether curvature representations are generated in the postcentral gyrus. We found that many area 2 neurons (26 of 112) exhibit clear curvature tuning, preferring contours pointing in a particular direction. Fewer area 2 neurons (15 of 112) show preferences for oriented bars. Because area 2 response patterns closely resembled SII patterns, we also compared area 2 and SII response time courses to characterize the temporal dynamics of curvature synthesis in the somatosensory system. We found that curvature representations develop and peak concurrently in area 2 and SII. These results reveal that transitions from orientation tuning to curvature selectivity in the somatosensory cortical hierarchy occur within SI rather than between SI and SII. PMID:23536717

Improvement of the Hopfield Neural Network by MC-Adaptation Rule

NASA Astrophysics Data System (ADS)

Zhou, Zhen; Zhao, Hong

2006-06-01

We show that the performance of the Hopfield neural networks, especially the quality of the recall and the capacity of the effective storing, can be greatly improved by making use of a recently presented neural network designing method without altering the whole structure of the network. In the improved neural network, a memory pattern is recalled exactly from initial states having a given degree of similarity with the memory pattern, and thus one can avoids to apply the overlap criterion as carried out in the Hopfield neural networks.

Neural Networks for the Beginner.

ERIC Educational Resources Information Center

Snyder, Robin M.

Motivated by the brain, neural networks are a right-brained approach to artificial intelligence that is used to recognize patterns based on previous training. In practice, one would not program an expert system to recognize a pattern and one would not train a neural network to make decisions from rules; but one could combine the best features of…

Development of a computational model on the neural activity patterns of a visual working memory in a hierarchical feedforward Network

NASA Astrophysics Data System (ADS)

An, Soyoung; Choi, Woochul; Paik, Se-Bum

2015-11-01

Understanding the mechanism of information processing in the human brain remains a unique challenge because the nonlinear interactions between the neurons in the network are extremely complex and because controlling every relevant parameter during an experiment is difficult. Therefore, a simulation using simplified computational models may be an effective approach. In the present study, we developed a general model of neural networks that can simulate nonlinear activity patterns in the hierarchical structure of a neural network system. To test our model, we first examined whether our simulation could match the previously-observed nonlinear features of neural activity patterns. Next, we performed a psychophysics experiment for a simple visual working memory task to evaluate whether the model could predict the performance of human subjects. Our studies show that the model is capable of reproducing the relationship between memory load and performance and may contribute, in part, to our understanding of how the structure of neural circuits can determine the nonlinear neural activity patterns in the human brain.

A neural model of the temporal dynamics of figure-ground segregation in motion perception.

PubMed

Raudies, Florian; Neumann, Heiko

2010-03-01

How does the visual system manage to segment a visual scene into surfaces and objects and manage to attend to a target object? Based on psychological and physiological investigations, it has been proposed that the perceptual organization and segmentation of a scene is achieved by the processing at different levels of the visual cortical hierarchy. According to this, motion onset detection, motion-defined shape segregation, and target selection are accomplished by processes which bind together simple features into fragments of increasingly complex configurations at different levels in the processing hierarchy. As an alternative to this hierarchical processing hypothesis, it has been proposed that the processing stages for feature detection and segregation are reflected in different temporal episodes in the response patterns of individual neurons. Such temporal epochs have been observed in the activation pattern of neurons as low as in area V1. Here, we present a neural network model of motion detection, figure-ground segregation and attentive selection which explains these response patterns in an unifying framework. Based on known principles of functional architecture of the visual cortex, we propose that initial motion and motion boundaries are detected at different and hierarchically organized stages in the dorsal pathway. Visual shapes that are defined by boundaries, which were generated from juxtaposed opponent motions, are represented at different stages in the ventral pathway. Model areas in the different pathways interact through feedforward and modulating feedback, while mutual interactions enable the communication between motion and form representations. Selective attention is devoted to shape representations by sending modulating feedback signals from higher levels (working memory) to intermediate levels to enhance their responses. Areas in the motion and form pathway are coupled through top-down feedback with V1 cells at the bottom end of the hierarchy. We propose that the different temporal episodes in the response pattern of V1 cells, as recorded in recent experiments, reflect the strength of modulating feedback signals. This feedback results from the consolidated shape representations from coherent motion patterns and the attentive modulation of responses along the cortical hierarchy. The model makes testable predictions concerning the duration and delay of the temporal episodes of V1 cell responses as well as their response variations that were caused by modulating feedback signals. Copyright 2009 Elsevier Ltd. All rights reserved.

Decoding the dynamic representation of musical pitch from human brain activity.

PubMed

Sankaran, N; Thompson, W F; Carlile, S; Carlson, T A

2018-01-16

In music, the perception of pitch is governed largely by its tonal function given the preceding harmonic structure of the music. While behavioral research has advanced our understanding of the perceptual representation of musical pitch, relatively little is known about its representational structure in the brain. Using Magnetoencephalography (MEG), we recorded evoked neural responses to different tones presented within a tonal context. Multivariate Pattern Analysis (MVPA) was applied to "decode" the stimulus that listeners heard based on the underlying neural activity. We then characterized the structure of the brain's representation using decoding accuracy as a proxy for representational distance, and compared this structure to several well established perceptual and acoustic models. The observed neural representation was best accounted for by a model based on the Standard Tonal Hierarchy, whereby differences in the neural encoding of musical pitches correspond to their differences in perceived stability. By confirming that perceptual differences honor those in the underlying neuronal population coding, our results provide a crucial link in understanding the cognitive foundations of musical pitch across psychological and neural domains.

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

PubMed Central

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

Brain response to empathy-eliciting scenarios involving pain in incarcerated psychopaths

PubMed Central

Decety, Jean; Skelly, Laurie R.; Kiehl, Kent A.

2013-01-01

Context A marked lack of empathy is a hallmark characteristic of individuals with psychopathy. However, neural response associated to empathic processing has not yet been directly examined in psychopathy especially in response to the perception of other people in pain and distress. Objective To identify potential differences in patterns of neural activity in incarcerated psychopaths and incarcerated controls during the perception of empathy-eliciting stimuli depicting other people in pain. Design In a case-control study, brain activation patterns elicited by dynamic stimuli depicting individuals being harmed and facial expression of pain were compared between incarcerated psychopaths and incarcerated controls. Setting Participants were scanned in on the grounds of a correctional facility using the Mind Research Network's mobile 1.5 T MRI system. Participants Eighty incarcerated males were classified according to scores on the Hare Psychopathy Checklist-Revised (PCL-R) as high (n = 27; PCL-R =30), intermediate (n = 28; PCL-R between 21–29), or low (n = 25; PCL-R ≤20) on psychopathy. Main Outcome Measure Neuro-hemodynamic response to empathy-eliciting dynamic scenarios revealed by functional magnetic resonance imaging. Results Psychopaths exhibited significantly less activation in the ventromedial prefrontal cortex, lateral orbitofrontal cortex, and periaqueductal gray relative to controls, but showed greater activation in the insula. Conclusion In response to pain cues expressed by others, psychopaths exhibit deficits in vmPFC and OFC regardless of stimulus type, but display selective impairment in processing facial cues of distress in regions associated with cognitive mentalizing. PMID:23615636

The Neural Border: Induction, Specification and Maturation of the territory that generates Neural Crest cells.

PubMed

Pla, Patrick; Monsoro-Burq, Anne H

2018-05-28

The neural crest is induced at the edge between the neural plate and the nonneural ectoderm, in an area called the neural (plate) border, during gastrulation and neurulation. In recent years, many studies have explored how this domain is patterned, and how the neural crest is induced within this territory, that also participates to the prospective dorsal neural tube, the dorsalmost nonneural ectoderm, as well as placode derivatives in the anterior area. This review highlights the tissue interactions, the cell-cell signaling and the molecular mechanisms involved in this dynamic spatiotemporal patterning, resulting in the induction of the premigratory neural crest. Collectively, these studies allow building a complex neural border and early neural crest gene regulatory network, mostly composed by transcriptional regulations but also, more recently, including novel signaling interactions. Copyright © 2018. Published by Elsevier Inc.

Digital micromirror based near-infrared illumination system for plasmonic photothermal neuromodulation.

PubMed

Jung, Hyunjun; Kang, Hongki; Nam, Yoonkey

2017-06-01

Light-mediated neuromodulation techniques provide great advantages to investigate neuroscience due to its high spatial and temporal resolution. To generate a spatial pattern of neural activity, it is necessary to develop a system for patterned-light illumination to a specific area. Digital micromirror device (DMD) based patterned illumination system have been used for neuromodulation due to its simple configuration and design flexibility. In this paper, we developed a patterned near-infrared (NIR) illumination system for region specific photothermal manipulation of neural activity using NIR-sensitive plasmonic gold nanorods (GNRs). The proposed system had high power transmission efficiency for delivering power density up to 19 W/mm 2 . We used a GNR-coated microelectrode array (MEA) to perform biological experiments using E18 rat hippocampal neurons and showed that it was possible to inhibit neural spiking activity of specific area in neural circuits with the patterned NIR illumination. This patterned NIR illumination system can serve as a promising neuromodulation tool to investigate neuroscience in a wide range of physiological and clinical applications.

Optical computing and neural networks; Proceedings of the Meeting, National Chiao Tung Univ., Hsinchu, Taiwan, Dec. 16, 17, 1992

NASA Technical Reports Server (NTRS)

Hsu, Ken-Yuh (Editor); Liu, Hua-Kuang (Editor)

1992-01-01

The present conference discusses optical neural networks, photorefractive nonlinear optics, optical pattern recognition, digital and analog processors, and holography and its applications. Attention is given to bifurcating optical information processing, neural structures in digital halftoning, an exemplar-based optical neural net classifier for color pattern recognition, volume storage in photorefractive disks, and microlaser-based compact optical neuroprocessors. Also treated are the optical implementation of a feature-enhanced optical interpattern-associative neural network model and its optical implementation, an optical pattern binary dual-rail logic gate module, a theoretical analysis for holographic associative memories, joint transform correlators, image addition and subtraction via the Talbot effect, and optical wavelet-matched filters. (No individual items are abstracted in this volume)

Optical computing and neural networks; Proceedings of the Meeting, National Chiao Tung Univ., Hsinchu, Taiwan, Dec. 16, 17, 1992

NASA Astrophysics Data System (ADS)

Hsu, Ken-Yuh; Liu, Hua-Kuang

The present conference discusses optical neural networks, photorefractive nonlinear optics, optical pattern recognition, digital and analog processors, and holography and its applications. Attention is given to bifurcating optical information processing, neural structures in digital halftoning, an exemplar-based optical neural net classifier for color pattern recognition, volume storage in photorefractive disks, and microlaser-based compact optical neuroprocessors. Also treated are the optical implementation of a feature-enhanced optical interpattern-associative neural network model and its optical implementation, an optical pattern binary dual-rail logic gate module, a theoretical analysis for holographic associative memories, joint transform correlators, image addition and subtraction via the Talbot effect, and optical wavelet-matched filters. (No individual items are abstracted in this volume)

Neural mechanisms of rhythm perception: current findings and future perspectives.

PubMed

Grahn, Jessica A

2012-10-01

Perception of temporal patterns is fundamental to normal hearing, speech, motor control, and music. Certain types of pattern understanding are unique to humans, such as musical rhythm. Although human responses to musical rhythm are universal, there is much we do not understand about how rhythm is processed in the brain. Here, I consider findings from research into basic timing mechanisms and models through to the neuroscience of rhythm and meter. A network of neural areas, including motor regions, is regularly implicated in basic timing as well as processing of musical rhythm. However, fractionating the specific roles of individual areas in this network has remained a challenge. Distinctions in activity patterns appear between "automatic" and "cognitively controlled" timing processes, but the perception of musical rhythm requires features of both automatic and controlled processes. In addition, many experimental manipulations rely on participants directing their attention toward or away from certain stimulus features, and measuring corresponding differences in neural activity. Many temporal features, however, are implicitly processed whether attended to or not, making it difficult to create controlled baseline conditions for experimental comparisons. The variety of stimuli, paradigms, and definitions can further complicate comparisons across domains or methodologies. Despite these challenges, the high level of interest and multitude of methodological approaches from different cognitive domains (including music, language, and motor learning) have yielded new insights and hold promise for future progress. Copyright © 2012 Cognitive Science Society, Inc.

Temporal pattern processing in songbirds.

PubMed

Comins, Jordan A; Gentner, Timothy Q

2014-10-01

Understanding how the brain perceives, organizes and uses patterned information is directly related to the neurobiology of language. Given the present limitations, such knowledge at the scale of neurons, neural circuits and neural populations can only come from non-human models, focusing on shared capacities that are relevant to language processing. Here we review recent advances in the behavioral and neural basis of temporal pattern processing of natural auditory communication signals in songbirds, focusing on European starlings. We suggest a general inhibitory circuit for contextual modulation that can act to control sensory representations based on patterning rules. Copyright © 2014. Published by Elsevier Ltd.

Bioprinting for Neural Tissue Engineering.

PubMed

Knowlton, Stephanie; Anand, Shivesh; Shah, Twisha; Tasoglu, Savas

2018-01-01

Bioprinting is a method by which a cell-encapsulating bioink is patterned to create complex tissue architectures. Given the potential impact of this technology on neural research, we review the current state-of-the-art approaches for bioprinting neural tissues. While 2D neural cultures are ubiquitous for studying neural cells, 3D cultures can more accurately replicate the microenvironment of neural tissues. By bioprinting neuronal constructs, one can precisely control the microenvironment by specifically formulating the bioink for neural tissues, and by spatially patterning cell types and scaffold properties in three dimensions. We review a range of bioprinted neural tissue models and discuss how they can be used to observe how neurons behave, understand disease processes, develop new therapies and, ultimately, design replacement tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

Is race erased? Decoding race from patterns of neural activity when skin color is not diagnostic of group boundaries.

PubMed

Ratner, Kyle G; Kaul, Christian; Van Bavel, Jay J

2013-10-01

Several theories suggest that people do not represent race when it does not signify group boundaries. However, race is often associated with visually salient differences in skin tone and facial features. In this study, we investigated whether race could be decoded from distributed patterns of neural activity in the fusiform gyri and early visual cortex when visual features that often covary with race were orthogonal to group membership. To this end, we used multivariate pattern analysis to examine an fMRI dataset that was collected while participants assigned to mixed-race groups categorized own-race and other-race faces as belonging to their newly assigned group. Whereas conventional univariate analyses provided no evidence of race-based responses in the fusiform gyri or early visual cortex, multivariate pattern analysis suggested that race was represented within these regions. Moreover, race was represented in the fusiform gyri to a greater extent than early visual cortex, suggesting that the fusiform gyri results do not merely reflect low-level perceptual information (e.g. color, contrast) from early visual cortex. These findings indicate that patterns of activation within specific regions of the visual cortex may represent race even when overall activation in these regions is not driven by racial information.

Guiding the study of brain dynamics by using first-person data: Synchrony patterns correlate with ongoing conscious states during a simple visual task

PubMed Central

Lutz, Antoine; Lachaux, Jean-Philippe; Martinerie, Jacques; Varela, Francisco J.

2002-01-01

Even during well-calibrated cognitive tasks, successive brain responses to repeated identical stimulations are highly variable. The source of this variability is believed to reside mainly in fluctuations of the subject's cognitive “context” defined by his/her attentive state, spontaneous thought process, strategy to carry out the task, and so on … As these factors are hard to manipulate precisely, they are usually not controlled, and the variability is discarded by averaging techniques. We combined first-person data and the analysis of neural processes to reduce such noise. We presented the subjects with a three-dimensional illusion and recorded their electrical brain activity and their own report about their cognitive context. Trials were clustered according to these first-person data, and separate dynamical analyses were conducted for each cluster. We found that (i) characteristic patterns of endogenous synchrony appeared in frontal electrodes before stimulation. These patterns depended on the degree of preparation and the immediacy of perception as verbally reported. (ii) These patterns were stable for several recordings. (iii) Preparatory states modulate both the behavioral performance and the evoked and induced synchronous patterns that follow. (iv) These results indicated that first-person data can be used to detect and interpret neural processes. PMID:11805299

Resting-state brain activity in the motor cortex reflects task-induced activity: A multi-voxel pattern analysis.

PubMed

Kusano, Toshiki; Kurashige, Hiroki; Nambu, Isao; Moriguchi, Yoshiya; Hanakawa, Takashi; Wada, Yasuhiro; Osu, Rieko

2015-08-01

It has been suggested that resting-state brain activity reflects task-induced brain activity patterns. In this study, we examined whether neural representations of specific movements can be observed in the resting-state brain activity patterns of motor areas. First, we defined two regions of interest (ROIs) to examine brain activity associated with two different behavioral tasks. Using multi-voxel pattern analysis with regularized logistic regression, we designed a decoder to detect voxel-level neural representations corresponding to the tasks in each ROI. Next, we applied the decoder to resting-state brain activity. We found that the decoder discriminated resting-state neural activity with accuracy comparable to that associated with task-induced neural activity. The distribution of learned weighted parameters for each ROI was similar for resting-state and task-induced activities. Large weighted parameters were mainly located on conjunctive areas. Moreover, the accuracy of detection was higher than that for a decoder whose weights were randomly shuffled, indicating that the resting-state brain activity includes multi-voxel patterns similar to the neural representation for the tasks. Therefore, these results suggest that the neural representation of resting-state brain activity is more finely organized and more complex than conventionally considered.

Cross-Modal Decoding of Neural Patterns Associated with Working Memory: Evidence for Attention-Based Accounts of Working Memory

PubMed Central

Majerus, Steve; Cowan, Nelson; Péters, Frédéric; Van Calster, Laurens; Phillips, Christophe; Schrouff, Jessica

2016-01-01

Recent studies suggest common neural substrates involved in verbal and visual working memory (WM), interpreted as reflecting shared attention-based, short-term retention mechanisms. We used a machine-learning approach to determine more directly the extent to which common neural patterns characterize retention in verbal WM and visual WM. Verbal WM was assessed via a standard delayed probe recognition task for letter sequences of variable length. Visual WM was assessed via a visual array WM task involving the maintenance of variable amounts of visual information in the focus of attention. We trained a classifier to distinguish neural activation patterns associated with high- and low-visual WM load and tested the ability of this classifier to predict verbal WM load (high–low) from their associated neural activation patterns, and vice versa. We observed significant between-task prediction of load effects during WM maintenance, in posterior parietal and superior frontal regions of the dorsal attention network; in contrast, between-task prediction in sensory processing cortices was restricted to the encoding stage. Furthermore, between-task prediction of load effects was strongest in those participants presenting the highest capacity for the visual WM task. This study provides novel evidence for common, attention-based neural patterns supporting verbal and visual WM. PMID:25146374

Inhalation Frequency Controls Reformatting of Mitral/Tufted Cell Odor Representations in the Olfactory Bulb.

PubMed

Díaz-Quesada, Marta; Youngstrom, Isaac A; Tsuno, Yusuke; Hansen, Kyle R; Economo, Michael N; Wachowiak, Matt

2018-02-28

In mammals, olfactory sensation depends on inhalation, which controls activation of sensory neurons and temporal patterning of central activity. Odor representations by mitral and tufted (MT) cells, the main output from the olfactory bulb (OB), reflect sensory input as well as excitation and inhibition from OB circuits, which may change as sniff frequency increases. To test the impact of sampling frequency on MT cell odor responses, we obtained whole-cell recordings from MT cells in anesthetized male and female mice while varying inhalation frequency via tracheotomy, allowing comparison of inhalation-linked responses across cells. We characterized frequency effects on MT cell responses during inhalation of air and odorants using inhalation pulses and also "playback" of sniffing recorded from awake mice. Inhalation-linked changes in membrane potential were well predicted across frequency from linear convolution of 1 Hz responses; and, as frequency increased, near-identical temporal responses could emerge from depolarizing, hyperpolarizing, or multiphasic MT responses. However, net excitation was not well predicted from 1 Hz responses and varied substantially across MT cells, with some cells increasing and others decreasing in spike rate. As a result, sustained odorant sampling at higher frequencies led to increasing decorrelation of the MT cell population response pattern over time. Bulk activation of sensory inputs by optogenetic stimulation affected MT cells more uniformly across frequency, suggesting that frequency-dependent decorrelation emerges from odor-specific patterns of activity in the OB network. These results suggest that sampling behavior alone can reformat early sensory representations, possibly to optimize sensory perception during repeated sampling. SIGNIFICANCE STATEMENT Olfactory sensation in mammals depends on inhalation, which increases in frequency during active sampling of olfactory stimuli. We asked how inhalation frequency can shape the neural coding of odor information by recording from projection neurons of the olfactory bulb while artificially varying odor sampling frequency in the anesthetized mouse. We found that sampling an odor at higher frequencies led to diverse changes in net responsiveness, as measured by action potential output, that were not predicted from low-frequency responses. These changes led to a reorganization of the pattern of neural activity evoked by a given odorant that occurred preferentially during sustained, high-frequency inhalation. These results point to a novel mechanism for modulating early sensory representations solely as a function of sampling behavior. Copyright © 2018 the authors 0270-6474/18/382189-18$15.00/0.

Spatiotemporal dynamics of similarity-based neural representations of facial identity.

PubMed

Vida, Mark D; Nestor, Adrian; Plaut, David C; Behrmann, Marlene

2017-01-10

Humans' remarkable ability to quickly and accurately discriminate among thousands of highly similar complex objects demands rapid and precise neural computations. To elucidate the process by which this is achieved, we used magnetoencephalography to measure spatiotemporal patterns of neural activity with high temporal resolution during visual discrimination among a large and carefully controlled set of faces. We also compared these neural data to lower level "image-based" and higher level "identity-based" model-based representations of our stimuli and to behavioral similarity judgments of our stimuli. Between ∼50 and 400 ms after stimulus onset, face-selective sources in right lateral occipital cortex and right fusiform gyrus and sources in a control region (left V1) yielded successful classification of facial identity. In all regions, early responses were more similar to the image-based representation than to the identity-based representation. In the face-selective regions only, responses were more similar to the identity-based representation at several time points after 200 ms. Behavioral responses were more similar to the identity-based representation than to the image-based representation, and their structure was predicted by responses in the face-selective regions. These results provide a temporally precise description of the transformation from low- to high-level representations of facial identity in human face-selective cortex and demonstrate that face-selective cortical regions represent multiple distinct types of information about face identity at different times over the first 500 ms after stimulus onset. These results have important implications for understanding the rapid emergence of fine-grained, high-level representations of object identity, a computation essential to human visual expertise.

Age-related Neural Differences in Affiliation and Isolation

PubMed Central

Beadle, Janelle N.; Yoon, Carolyn; Gutchess, Angela H.

2012-01-01

While previous aging studies have focused on particular components of social perception (e.g., theory of mind, self-referencing), little is known about age-related differences specifically for the neural basis of perception of affiliation and isolation. This study investigates age-related similarities and differences in the neural basis of affiliation and isolation. Participants viewed images of affiliation (groups engaged in social interaction), and isolation (lone individuals), as well as non-social stimuli (e.g., landscapes) while making pleasantness judgments and undergoing functional neuroimaging (BOLD fMRI). Results indicated age-related similarities in response to affiliation and isolation in recruitment of regions involved in theory of mind and self-referencing (e.g. temporal pole, medial prefrontal cortex). Yet, age-related differences also emerged in response to affiliation and isolation in regions implicated in theory of mind as well as self-referencing. Specifically, in response to isolation versus affiliation images, older adults showed greater recruitment than younger adults of the temporal pole, a region that is important for retrieval of personally-relevant memories utilized to understand others’ mental states. Furthermore, in response to images of affiliation versus isolation, older adults showed greater recruitment than younger adults of the precuneus, a region implicated in self-referencing. We suggest that age-related divergence in neural activation patterns underlying judgments of scenes depicting isolation versus affiliation may indicate that older adults’ theory of mind processes are driven by retrieval of isolation-relevant information. Moreover, older adults’ greater recruitment of the precuneus for affiliation versus isolation suggests that the positivity bias for emotional information may extend to social information involving affiliation. PMID:22371086

Pattern classification and recognition of invertebrate functional groups using self-organizing neural networks.

PubMed

Zhang, WenJun

2007-07-01

Self-organizing neural networks can be used to mimic non-linear systems. The main objective of this study is to make pattern classification and recognition on sampling information using two self-organizing neural network models. Invertebrate functional groups sampled in the irrigated rice field were classified and recognized using one-dimensional self-organizing map and self-organizing competitive learning neural networks. Comparisons between neural network models, distance (similarity) measures, and number of neurons were conducted. The results showed that self-organizing map and self-organizing competitive learning neural network models were effective in pattern classification and recognition of sampling information. Overall the performance of one-dimensional self-organizing map neural network was better than self-organizing competitive learning neural network. The number of neurons could determine the number of classes in the classification. Different neural network models with various distance (similarity) measures yielded similar classifications. Some differences, dependent upon the specific network structure, would be found. The pattern of an unrecognized functional group was recognized with the self-organizing neural network. A relative consistent classification indicated that the following invertebrate functional groups, terrestrial blood sucker; terrestrial flyer; tourist (nonpredatory species with no known functional role other than as prey in ecosystem); gall former; collector (gather, deposit feeder); predator and parasitoid; leaf miner; idiobiont (acarine ectoparasitoid), were classified into the same group, and the following invertebrate functional groups, external plant feeder; terrestrial crawler, walker, jumper or hunter; neustonic (water surface) swimmer (semi-aquatic), were classified into another group. It was concluded that reliable conclusions could be drawn from comparisons of different neural network models that use different distance (similarity) measures. Results with the larger consistency will be more reliable.

Weaving and neural complexity in symmetric quantum states

NASA Astrophysics Data System (ADS)

Susa, Cristian E.; Girolami, Davide

2018-04-01

We study the behaviour of two different measures of the complexity of multipartite correlation patterns, weaving and neural complexity, for symmetric quantum states. Weaving is the weighted sum of genuine multipartite correlations of any order, where the weights are proportional to the correlation order. The neural complexity, originally introduced to characterize correlation patterns in classical neural networks, is here extended to the quantum scenario. We derive closed formulas of the two quantities for GHZ states mixed with white noise.

Spatio-Temporal Neural Networks for Vision, Reasoning and Rapid Decision Making

DTIC Science & Technology

1994-08-31

something that is obviously not pattern for long-term knowledge base (LTKB) facts. As a matter possiblc in common neural networks (as units in a...Conferences on Neural Davis, P. (19W0) Application of op~tical chaos to temporal pattern search in a Networks . Piscataway, NJ. [SC] nonlinear optical...Science Institute PROJECT TITLE: Spatio-temporal Neural Networks for Vision, Reasoning and Rapid Decision Making (N00014-93-1-1149) Number of ONR

Win for your kin: Neural responses to personal and vicarious rewards when mothers win for their adolescent children.

PubMed

Spaans, Jochem P; Burke, Sarah M; Altikulaç, Sibel; Braams, Barbara R; Op de Macks, Zdeňa A; Crone, Eveline A

2018-01-01

Mother-child relationships change considerably in adolescence, but it is not yet understood how mothers experience vicarious rewards for their adolescent children. In the current study, we investigated neural responses of twenty mothers winning and losing money for their best friend and for their adolescent child in a gambling task. During the task, functional neuroimaging data were acquired. We examined the activation patterns when playing for or winning for self, adolescent children and friends in four a-priori selected ROIs (nucleus accumbens, dorsomedial prefrontal cortex, precuneus and temporo-parietal junction). Behaviorally, mothers indicated that they experienced most enjoyment when they gained money for their children and that their children deserved to win more, relative to friends and self. At the neural level, nucleus accumbens activity was stronger when winning versus losing. This pattern was not only found when playing for self, but also for friends and children, possibly reflecting the rewarding value of vicarious prosocial gains. In addition, dorsomedial prefrontal cortex, precuneus, and temporo-parietal junction were more active when receiving outcomes for children and friends compared to self, possibly reflecting increased recruitment of mentalizing processes. Interestingly, activity in this network was stronger for mothers who indicated that their children and friends deserved to win more. These findings provide initial evidence that vicarious rewards for one's children are processed similarly as rewards for self, and that activation in social brain regions are related to social closeness.

Biosonar navigation above water I: estimating flight height.

PubMed

Hoffmann, Susanne; Genzel, Daria; Prosch, Selina; Baier, Leonie; Weser, Sabrina; Wiegrebe, Lutz; Firzlaff, Uwe

2015-02-15

Locomotion and foraging on the wing require precise navigation in more than just the horizontal plane. Navigation in three dimensions and, specifically, precise adjustment of flight height are essential for flying animals. Echolocating bats drink from water surfaces in flight, which requires an exceptionally precise vertical navigation. Here, we exploit this behavior in the bat, Phyllostomus discolor, to understand the biophysical and neural mechanisms that allow for sonar-guided navigation in the vertical plane. In a set of behavioral experiments, we show that for echolocating bats, adjustment of flight height depends on the tragus in their outer ears. Specifically, the tragus imposes elevation-specific spectral interference patterns on the echoes of the bats' sonar emissions. Head-related transfer functions of our bats show that these interference patterns are most conspicuous in the frequency range ∼55 kHz. This conspicuousness is faithfully preserved in the frequency tuning and spatial receptive fields of cortical single and multiunits recorded from anesthetized animals. In addition, we recorded vertical spatiotemporal response maps that describe neural tuning in elevation over time. One class of units that were very sharply tuned to frequencies ∼55 kHz showed unusual spatiotemporal response characteristics with a preference for paired echoes where especially the first echo originates from very low elevations. These behavioral and neural data provide the first insight into biosonar-based processing and perception of acoustic elevation cues that are essential for bats to navigate in three-dimensional space. Copyright © 2015 the American Physiological Society.

The Neural Crest in Cardiac Congenital Anomalies

PubMed Central

Keyte, Anna; Hutson, Mary Redmond

2012-01-01

This review discusses the function of neural crest as they relate to cardiovascular defects. The cardiac neural crest cells are a subpopulation of cranial neural crest discovered nearly 30 years ago by ablation of premigratory neural crest. The cardiac neural crest cells are necessary for normal cardiovascular development. We begin with a description of the crest cells in normal development, including their function in remodeling the pharyngeal arch arteries, outflow tract septation, valvulogenesis, and development of the cardiac conduction system. The cells are also responsible for modulating signaling in the caudal pharynx, including the second heart field. Many of the molecular pathways that are known to influence specification, migration, patterning and final targeting of the cardiac neural crest cells are reviewed. The cardiac neural crest cells play a critical role in the pathogenesis of various human cardiocraniofacial syndromes such as DiGeorge, Velocardiofacial, CHARGE, Fetal Alcohol, Alagille, LEOPARD, and Noonan syndromes, as well as Retinoic Acid Embryopathy. The loss of neural crest cells or their dysfunction may not always directly cause abnormal cardiovascular development, but are involved secondarily because crest cells represent a major component in the complex tissue interactions in the head, pharynx and outflow tract. Thus many of the human syndromes linking defects in the heart, face and brain can be better understood when considered within the context of a single cardiocraniofacial developmental module with the neural crest being a key cell type that interconnects the regions. PMID:22595346

Neural responses to gains and losses in children of suicide attempters.

PubMed

Tsypes, Aliona; Owens, Max; Hajcak, Greg; Gibb, Brandon E

2017-02-01

[Correction Notice: An Erratum for this article was reported in Vol 126(2) of Journal of Abnormal Psychology (see record 2016-56318-001). In the article, Figure 1 had incorrect axis labels. There was also an error in the abstract, which did not state that ΔFN was calculated as FN to losses minus FN to gains. All versions of this article have been corrected.] Suicidal behavior aggregates within families, yet the specific mechanisms of suicide-risk transmission are poorly understood. Despite some evidence that abnormal patterns of reward responsiveness might constitute one such potential mechanism, empirical evidence is lacking. The goal of this study was to examine neural responses to gains and losses in children of suicide attempters with no personal history of suicide attempt (SA) themselves. To objectively assess these neural responses, we used feedback negativity (FN), a psychophysiological marker of responsiveness to reward and loss. Participants were 66 parents and their 7-11-year-old children (22 with parental history of SA and 44 demographically and clinically matched children of parents with no SA history). Diagnostic interviews were used to gather information about psychiatric diagnoses, symptoms, and histories of suicidal thoughts and behaviors. Children also completed a guessing task, during which continuous electroencephalography (EEG) was recorded. The FN was scored as the mean amplitude, 275-375 ms, following gain or loss feedback at frontocentral sites (Fz and FCz). Children of suicide attempters exhibited significantly more negative ΔFN (i.e., FN to losses minus FN to gains) than children of parents with no SA history. We found that this difference in ΔFN was due specifically to children of parents with a history of SA exhibiting a stronger response to loss, and no group differences were observed for responses to gains. The results suggest that an increased neural response to loss might represent one of the potential pathways of the familial transmission of suicide risk. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Pattern learning with deep neural networks in EMG-based speech recognition.

PubMed

Wand, Michael; Schultz, Tanja

2014-01-01

We report on classification of phones and phonetic features from facial electromyographic (EMG) data, within the context of our EMG-based Silent Speech interface. In this paper we show that a Deep Neural Network can be used to perform this classification task, yielding a significant improvement over conventional Gaussian Mixture models. Our central contribution is the visualization of patterns which are learned by the neural network. With increasing network depth, these patterns represent more and more intricate electromyographic activity.

Nested neural networks

NASA Technical Reports Server (NTRS)

Baram, Yoram

1988-01-01

Nested neural networks, consisting of small interconnected subnetworks, allow for the storage and retrieval of neural state patterns of different sizes. The subnetworks are naturally categorized by layers of corresponding to spatial frequencies in the pattern field. The storage capacity and the error correction capability of the subnetworks generally increase with the degree of connectivity between layers (the nesting degree). Storage of only few subpatterns in each subnetworks results in a vast storage capacity of patterns and subpatterns in the nested network, maintaining high stability and error correction capability.

Advances in Cochlear Implant Telemetry: Evoked Neural Responses, Electrical Field Imaging, and Technical Integrity

PubMed Central

Mens, Lucas H. M.

2007-01-01

During the last decade, cochlear implantation has evolved into a well-established treatment of deafness, predominantly because of many improvements in speech processing and the controlled excitation of the auditory nerve. Cochlear implants now also feature telemetry, which is highly useful to monitor the proper functioning of the implanted electronics and electrode contacts. Telemetry can also support the clinical management in young children and difficult cases where neural unresponsiveness is suspected. This article will review recent advances in the telemetry of the electrically evoked compound action potential that have made these measurements simple and routine procedures in most cases. The distribution of the electrical stimulus itself sampled by “electrical field imaging” reveals general patterns of current flow in the normal cochlea and gross abnormalities in individual patients; models have been developed to derive more subtle insights from an individual electrical field imaging. Finally, some thoughts are given to the extended application of telemetry, for example, in monitoring the neural responses or in combination with other treatments of the deaf ear. PMID:17709572

Neural response to reward anticipation under risk is nonlinear in probabilities.

PubMed

Hsu, Ming; Krajbich, Ian; Zhao, Chen; Camerer, Colin F

2009-02-18

A widely observed phenomenon in decision making under risk is the apparent overweighting of unlikely events and the underweighting of nearly certain events. This violates standard assumptions in expected utility theory, which requires that expected utility be linear (objective) in probabilities. Models such as prospect theory have relaxed this assumption and introduced the notion of a "probability weighting function," which captures the key properties found in experimental data. This study reports functional magnetic resonance imaging (fMRI) data that neural response to expected reward is nonlinear in probabilities. Specifically, we found that activity in the striatum during valuation of monetary gambles are nonlinear in probabilities in the pattern predicted by prospect theory, suggesting that probability distortion is reflected at the level of the reward encoding process. The degree of nonlinearity reflected in individual subjects' decisions is also correlated with striatal activity across subjects. Our results shed light on the neural mechanisms of reward processing, and have implications for future neuroscientific studies of decision making involving extreme tails of the distribution, where probability weighting provides an explanation for commonly observed behavioral anomalies.

Applications of artificial neural network in AIDS research and therapy.

PubMed

Sardari, S; Sardari, D

2002-01-01

In recent years considerable effort has been devoted to applying pattern recognition techniques to the complex task of data analysis in drug research. Artificial neural networks (ANN) methodology is a modeling method with great ability to adapt to a new situation, or control an unknown system, using data acquired in previous experiments. In this paper, a brief history of ANN and the basic concepts behind the computing, the mathematical and algorithmic formulation of each of the techniques, and their developmental background is presented. Based on the abilities of ANNs in pattern recognition and estimation of system outputs from the known inputs, the neural network can be considered as a tool for molecular data analysis and interpretation. Analysis by neural networks improves the classification accuracy, data quantification and reduces the number of analogues necessary for correct classification of biologically active compounds. Conformational analysis and quantifying the components in mixtures using NMR spectra, aqueous solubility prediction and structure-activity correlation are among the reported applications of ANN as a new modeling method. Ranging from drug design and discovery to structure and dosage form design, the potential pharmaceutical applications of the ANN methodology are significant. In the areas of clinical monitoring, utilization of molecular simulation and design of bioactive structures, ANN would make the study of the status of the health and disease possible and brings their predicted chemotherapeutic response closer to reality.

Model-based functional neuroimaging using dynamic neural fields: An integrative cognitive neuroscience approach

PubMed Central

Wijeakumar, Sobanawartiny; Ambrose, Joseph P.; Spencer, John P.; Curtu, Rodica

2017-01-01

A fundamental challenge in cognitive neuroscience is to develop theoretical frameworks that effectively span the gap between brain and behavior, between neuroscience and psychology. Here, we attempt to bridge this divide by formalizing an integrative cognitive neuroscience approach using dynamic field theory (DFT). We begin by providing an overview of how DFT seeks to understand the neural population dynamics that underlie cognitive processes through previous applications and comparisons to other modeling approaches. We then use previously published behavioral and neural data from a response selection Go/Nogo task as a case study for model simulations. Results from this study served as the ‘standard’ for comparisons with a model-based fMRI approach using dynamic neural fields (DNF). The tutorial explains the rationale and hypotheses involved in the process of creating the DNF architecture and fitting model parameters. Two DNF models, with similar structure and parameter sets, are then compared. Both models effectively simulated reaction times from the task as we varied the number of stimulus-response mappings and the proportion of Go trials. Next, we directly simulated hemodynamic predictions from the neural activation patterns from each model. These predictions were tested using general linear models (GLMs). Results showed that the DNF model that was created by tuning parameters to capture simultaneously trends in neural activation and behavioral data quantitatively outperformed a Standard GLM analysis of the same dataset. Further, by using the GLM results to assign functional roles to particular clusters in the brain, we illustrate how DNF models shed new light on the neural populations’ dynamics within particular brain regions. Thus, the present study illustrates how an interactive cognitive neuroscience model can be used in practice to bridge the gap between brain and behavior. PMID:29118459

Distinctive and common neural underpinnings of major depression, social anxiety, and their comorbidity.

PubMed

Hamilton, J Paul; Chen, Michael C; Waugh, Christian E; Joormann, Jutta; Gotlib, Ian H

2015-04-01

Assessing neural commonalities and differences among depression, anxiety and their comorbidity is critical in developing a more integrative clinical neuroscience and in evaluating currently debated categorical vs dimensional approaches to psychiatric classification. Therefore, in this study, we sought to identify patterns of anomalous neural responding to criticism and praise that are specific to and common among major depressive disorder (MDD), social anxiety disorder (SAD) and comorbid MDD-SAD. Adult females who met formal diagnostic criteria for MDD, SAD or MDD-SAD and psychiatrically healthy participants underwent functional magnetic resonance imaging as they listened to statements directing praise or criticism at them or at another person. MDD groups showed reduced responding to praise across a distributed cortical network, an effect potentially mediated by thalamic nuclei undergirding arousal-mediated attention. SAD groups showed heightened anterior insula and decreased default-mode network response to criticism. The MDD-SAD group uniquely showed reduced responding to praise in the dorsal anterior cingulate cortex. Finally, all groups with psychopathology showed heightened response to criticism in a region of the superior frontal gyrus implicated in attentional gating. The present results suggest novel neural models of anhedonia in MDD, vigilance-withdrawal behaviors in SAD, and poorer outcome in MDD-SAD. Importantly, in identifying unique and common neural substrates of MDD and SAD, these results support a formulation in which common neural components represent general risk factors for psychopathology that, due to factors that are present at illness onset, lead to distinct forms of psychopathology with unique neural signatures. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Computational modeling of direct neuronal recruitment during intracortical microstimulation in somatosensory cortex.

PubMed

Overstreet, C K; Klein, J D; Helms Tillery, S I

2013-12-01

Electrical stimulation of cortical tissue could be used to deliver sensory information as part of a neuroprosthetic device, but current control of the location, resolution, quality, and intensity of sensations elicited by intracortical microstimulation (ICMS) remains inadequate for this purpose. One major obstacle to resolving this problem is the poor understanding of the neural activity induced by ICMS. Even with new imaging methods, quantifying the activity of many individual neurons within cortex is difficult. We used computational modeling to examine the response of somatosensory cortex to ICMS. We modeled the axonal arbors of eight distinct morphologies of interneurons and seven types of pyramidal neurons found in somatosensory cortex and identified their responses to extracellular stimulation. We then combined these axonal elements to form a multi-layered slab of simulated cortex and investigated the patterns of neural activity directly induced by ICMS. Specifically we estimated the number, location, and variety of neurons directly recruited by stimulation on a single penetrating microelectrode. The population of neurons activated by ICMS was dependent on both stimulation strength and the depth of the electrode within cortex. Strikingly, stimulation recruited interneurons and pyramidal neurons in very different patterns. Interneurons are primarily recruited within a dense, continuous region around the electrode, while pyramidal neurons were recruited in a sparse fashion both near the electrode and up to several millimeters away. Thus ICMS can lead to an unexpectedly complex spatial distribution of firing neurons. These results lend new insights to the complexity and range of neural activity that can be induced by ICMS. This work also suggests mechanisms potentially responsible for the inconsistency and unnatural quality of sensations initiated by ICMS. Understanding these mechanisms will aid in the design of stimulation that can be used to generate effective sensory feedback for neuroprosthetic devices.

Multivariate pattern analysis of fMRI: the early beginnings.

PubMed

Haxby, James V

2012-08-15

In 2001, we published a paper on the representation of faces and objects in ventral temporal cortex that introduced a new method for fMRI analysis, which subsequently came to be called multivariate pattern analysis (MVPA). MVPA now refers to a diverse set of methods that analyze neural responses as patterns of activity that reflect the varying brain states that a cortical field or system can produce. This paper recounts the circumstances and events that led to the original study and later developments and innovations that have greatly expanded this approach to fMRI data analysis, leading to its widespread application. Copyright © 2012 Elsevier Inc. All rights reserved.

Human inferior colliculus activity relates to individual differences in spoken language learning

PubMed Central

Chandrasekaran, Bharath; Kraus, Nina

2012-01-01

A challenge to learning words of a foreign language is encoding nonnative phonemes, a process typically attributed to cortical circuitry. Using multimodal imaging methods [functional magnetic resonance imaging-adaptation (fMRI-A) and auditory brain stem responses (ABR)], we examined the extent to which pretraining pitch encoding in the inferior colliculus (IC), a primary midbrain structure, related to individual variability in learning to successfully use nonnative pitch patterns to distinguish words in American English-speaking adults. fMRI-A indexed the efficiency of pitch representation localized to the IC, whereas ABR quantified midbrain pitch-related activity with millisecond precision. In line with neural “sharpening” models, we found that efficient IC pitch pattern representation (indexed by fMRI) related to superior neural representation of pitch patterns (indexed by ABR), and consequently more successful word learning following sound-to-meaning training. Our results establish a critical role for the IC in speech-sound representation, consistent with the established role for the IC in the representation of communication signals in other animal models. PMID:22131377

DNA topoisomerase IIβ stimulates neurite outgrowth in neural differentiated human mesenchymal stem cells through regulation of Rho-GTPases (RhoA/Rock2 pathway) and Nurr1 expression.

PubMed

Zaim, Merve; Isik, Sevim

2018-04-25

DNA topoisomerase IIβ (topo IIβ) is known to regulate neural differentiation by inducing the neuronal genes responsible for critical neural differentiation events such as neurite outgrowth and axon guidance. However, the pathways of axon growth controlled by topo IIβ have not been clarified yet. Microarray results of our previous study have shown that topo IIβ silencing in neural differentiated primary human mesenchymal stem cells (hMSCs) significantly alters the expression pattern of genes involved in neural polarity, axonal growth, and guidance, including Rho-GTPases. This study aims to further analyze the regulatory role of topo IIβ on the process of axon growth via regulation of Rho-GTPases. For this purpose, topo IIβ was silenced in neurally differentiated hMSCs. Cells lost their morphology because of topo IIβ deficiency, becoming enlarged and flattened. Additionally, a reduction in both neural differentiation efficiency and neurite length, upregulation in RhoA and Rock2, downregulation in Cdc42 gene expression were detected. On the other hand, cells were transfected with topo IIβ gene to elucidate the possible neuroprotective effect of topo IIβ overexpression on neural-induced hMSCs. Topo IIβ overexpression prompted all the cells to exhibit neural cell morphology as characterized by longer neurites. RhoA and Rock2 expressions were downregulated, whereas Cdc42 expression was upregulated. Nurr1 expression level correlated with topo IIβ in both topo IIβ-overexpressed and -silenced cells. Furthermore, differential translocation of Rho-GTPases was detected by immunostaining in response to topo IIβ. Our results suggest that topo IIβ deficiency could give rise to neurodegeneration through dysregulation of Rho-GTPases. However, further in-vivo research is needed to demonstrate if re-regulation of Rho GTPases by topo IIβ overexpression could be a neuroprotective treatment in the case of neurodegenerative diseases.

Neural response to pictorial health warning labels can predict smoking behavioral change

PubMed Central

Riddle, Philip J.; Newman-Norlund, Roger D.; Baer, Jessica; Thrasher, James F.

2016-01-01

In order to improve our understanding of how pictorial health warning labels (HWLs) influence smoking behavior, we examined whether brain activity helps to explain smoking behavior above and beyond self-reported effectiveness of HWLs. We measured the neural response in the ventromedial prefrontal cortex (vmPFC) and the amygdala while adult smokers viewed HWLs. Two weeks later, participants’ self-reported smoking behavior and biomarkers of smoking behavior were reassessed. We compared multiple models predicting change in self-reported smoking behavior (cigarettes per day [CPD]) and change in a biomarkers of smoke exposure (expired carbon monoxide [CO]). Brain activity in the vmPFC and amygdala not only predicted changes in CO, but also accounted for outcome variance above and beyond self-report data. Neural data were most useful in predicting behavioral change as quantified by the objective biomarker (CO). This pattern of activity was significantly modulated by individuals’ intention to quit. The finding that both cognitive (vmPFC) and affective (amygdala) brain areas contributed to these models supports the idea that smokers respond to HWLs in a cognitive-affective manner. Based on our findings, researchers may wish to consider using neural data from both cognitive and affective networks when attempting to predict behavioral change in certain populations (e.g. cigarette smokers). PMID:27405615

Fractionating the neural correlates of individual working memory components underlying arithmetic problem solving skills in children

PubMed Central

Metcalfe, Arron W. S.; Ashkenazi, Sarit; Rosenberg-Lee, Miriam; Menon, Vinod

2013-01-01

Baddeley and Hitch’s multi-component working memory (WM) model has played an enduring and influential role in our understanding of cognitive abilities. Very little is known, however, about the neural basis of this multi-component WM model and the differential role each component plays in mediating arithmetic problem solving abilities in children. Here, we investigate the neural basis of the central executive (CE), phonological (PL) and visuo-spatial (VS) components of WM during a demanding mental arithmetic task in 7–9 year old children (N=74). The VS component was the strongest predictor of math ability in children and was associated with increased arithmetic complexity-related responses in left dorsolateral and right ventrolateral prefrontal cortices as well as bilateral intra-parietal sulcus and supramarginal gyrus in posterior parietal cortex. Critically, VS, CE and PL abilities were associated with largely distinct patterns of brain response. Overlap between VS and CE components was observed in left supramarginal gyrus and no overlap was observed between VS and PL components. Our findings point to a central role of visuo-spatial WM during arithmetic problem-solving in young grade-school children and highlight the usefulness of the multi-component Baddeley and Hitch WM model in fractionating the neural correlates of arithmetic problem solving during development. PMID:24212504

Neural response to pictorial health warning labels can predict smoking behavioral change.

PubMed

Riddle, Philip J; Newman-Norlund, Roger D; Baer, Jessica; Thrasher, James F

2016-11-01

In order to improve our understanding of how pictorial health warning labels (HWLs) influence smoking behavior, we examined whether brain activity helps to explain smoking behavior above and beyond self-reported effectiveness of HWLs. We measured the neural response in the ventromedial prefrontal cortex (vmPFC) and the amygdala while adult smokers viewed HWLs. Two weeks later, participants' self-reported smoking behavior and biomarkers of smoking behavior were reassessed. We compared multiple models predicting change in self-reported smoking behavior (cigarettes per day [CPD]) and change in a biomarkers of smoke exposure (expired carbon monoxide [CO]). Brain activity in the vmPFC and amygdala not only predicted changes in CO, but also accounted for outcome variance above and beyond self-report data. Neural data were most useful in predicting behavioral change as quantified by the objective biomarker (CO). This pattern of activity was significantly modulated by individuals' intention to quit. The finding that both cognitive (vmPFC) and affective (amygdala) brain areas contributed to these models supports the idea that smokers respond to HWLs in a cognitive-affective manner. Based on our findings, researchers may wish to consider using neural data from both cognitive and affective networks when attempting to predict behavioral change in certain populations (e.g. cigarette smokers). © The Author (2016). Published by Oxford University Press.

Arrested development: early prefrontal lesions impair the maturation of moral judgement.

PubMed

Taber-Thomas, Bradley C; Asp, Erik W; Koenigs, Michael; Sutterer, Matthew; Anderson, Steven W; Tranel, Daniel

2014-04-01

Learning to make moral judgements based on considerations beyond self-interest is a fundamental aspect of moral development. A deficit in such learning is associated with poor socialization and criminal behaviour. The neural systems required for the acquisition and maturation of moral competency are not well understood. Here we show in a unique sample of neurological patients that focal lesions involving ventromedial prefrontal cortex, acquired during development, result in an abnormally egocentric pattern of moral judgement. In response to simple hypothetical moral scenarios, the patients were more likely than comparison participants to endorse self-interested actions that involved breaking moral rules or physically harming others in order to benefit themselves. This pattern (which we also found in subjects with psychopathy) differs from that of patients with adult-onset ventromedial prefrontal cortex lesions--the latter group showed normal rejection of egocentric rule violations. This novel contrast of patients with ventromedial prefrontal cortex lesions acquired during development versus during adulthood yields new evidence suggesting that the ventromedial prefrontal cortex is a critical neural substrate for the acquisition and maturation of moral competency that goes beyond self-interest to consider the welfare of others. Disruption to this affective neural system early in life interrupts moral development.

Neural net diagnostics for VLSI test

NASA Technical Reports Server (NTRS)

Lin, T.; Tseng, H.; Wu, A.; Dogan, N.; Meador, J.

1990-01-01

This paper discusses the application of neural network pattern analysis algorithms to the IC fault diagnosis problem. A fault diagnostic is a decision rule combining what is known about an ideal circuit test response with information about how it is distorted by fabrication variations and measurement noise. The rule is used to detect fault existence in fabricated circuits using real test equipment. Traditional statistical techniques may be used to achieve this goal, but they can employ unrealistic a priori assumptions about measurement data. Our approach to this problem employs an adaptive pattern analysis technique based on feedforward neural networks. During training, a feedforward network automatically captures unknown sample distributions. This is important because distributions arising from the nonlinear effects of process variation can be more complex than is typically assumed. A feedforward network is also able to extract measurement features which contribute significantly to making a correct decision. Traditional feature extraction techniques employ matrix manipulations which can be particularly costly for large measurement vectors. In this paper we discuss a software system which we are developing that uses this approach. We also provide a simple example illustrating the use of the technique for fault detection in an operational amplifier.

Neural representation of emotion regulation goals.

PubMed

Morawetz, Carmen; Bode, Stefan; Baudewig, Juergen; Jacobs, Arthur M; Heekeren, Hauke R

2016-02-01

The use of top-down cognitive control mechanisms to regulate emotional responses as circumstances change is critical for mental and physical health. Several theoretical models of emotion regulation have been postulated; it remains unclear, however, in which brain regions emotion regulation goals (e.g., the downregulation of fear) are represented. Here, we examined the neural mechanisms of regulating emotion using fMRI and identified brain regions representing reappraisal goals. Using a multimethodological analysis approach, combining standard activation-based and pattern-information analyses, we identified a distributed network of lateral frontal, temporal, and parietal regions implicated in reappraisal and within it, a core system that represents reappraisal goals in an abstract, stimulus-independent fashion. Within this core system, the neural pattern-separability in a subset of regions including the left inferior frontal gyrus, middle temporal gyrus, and inferior parietal lobe was related to the success in emotion regulation. Those brain regions might link the prefrontal control regions with the subcortical affective regions. Given the strong association of this subsystem with inner speech functions and semantic memory, we conclude that those cognitive mechanisms may be used for orchestrating emotion regulation. Hum Brain Mapp 37:600-620, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Functional localization of the human color center by decreased water displacement using diffusion-weighted fMRI.

PubMed

Williams, Rebecca J; Reutens, David C; Hocking, Julia

2015-11-01

Decreased water displacement following increased neural activity has been observed using diffusion-weighted functional MRI (DfMRI) at high b-values. The physiological mechanisms underlying the diffusion signal change may be unique from the standard blood oxygenation level-dependent (BOLD) contrast and closer to the source of neural activity. Whether DfMRI reflects neural activity more directly than BOLD outside the primary cerebral regions remains unclear. Colored and achromatic Mondrian visual stimuli were statistically contrasted to functionally localize the human color center Area V4 in neurologically intact adults. Spatial and temporal properties of DfMRI and BOLD activation were examined across regions of the visual cortex. At the individual level, DfMRI activation patterns showed greater spatial specificity to V4 than BOLD. The BOLD activation patterns were more prominent in the primary visual cortex than DfMRI, where activation was localized to the ventral temporal lobe. Temporally, the diffusion signal change in V4 and V1 both preceded the corresponding hemodynamic response, however the early diffusion signal change was more evident in V1. DfMRI may be of use in imaging applications implementing cognitive subtraction paradigms, and where highly precise individual functional localization is required.

A functional magnetic resonance imaging study of working memory abnormalities in schizophrenia.

PubMed

Johnson, Matthew R; Morris, Nicholas A; Astur, Robert S; Calhoun, Vince D; Mathalon, Daniel H; Kiehl, Kent A; Pearlson, Godfrey D

2006-07-01

Previous neuroimaging studies of working memory (WM) in schizophrenia, typically focusing on dorsolateral prefrontal cortex, yield conflicting results, possibly because of varied choice of tasks and analysis techniques. We examined neural function changes at several WM loads to derive a more complete picture of WM dysfunction in schizophrenia. We used a version of the Sternberg Item Recognition Paradigm to test WM function at five distinct loads. Eighteen schizophrenia patients and 18 matched healthy controls were scanned with functional magnetic resonance imaging at 3 Tesla. Patterns of both overactivation and underactivation in patients were observed depending on WM load. Patients' activation was generally less responsive to load changes than control subjects', and different patterns of between-group differences were observed for memory encoding and retrieval. In the specific case of successful retrieval, patients recruited additional neural circuits unused by control subjects. Behavioral effects were generally consistent with these imaging results. Differential findings of overactivation and underactivation may be attributable to patients' decreased ability to focus and allocate neural resources at task-appropriate levels. Additionally, differences between encoding and retrieval suggest that WM dysfunction may be manifested differently during the distinct phases of encoding, maintenance, and retrieval.

Dynamic analysis of patterns of renal sympathetic nerve activity: implications for renal function.

PubMed

DiBona, Gerald F

2005-03-01

Methods of dynamic analysis are used to provide additional understanding of the renal sympathetic neural control of renal function. The concept of functionally specific subgroups of renal sympathetic nerve fibres conveying information encoded in the frequency domain is presented. Analog pulse modulation and pseudorandom binary sequence stimulation patterns are used for the determination of renal vascular frequency response. Transfer function analysis is used to determine the effects of non-renal vasoconstrictor and vasoconstrictor intensities of renal sympathetic nerve activity on dynamic autoregulation of renal blood flow.

Genetic Influences on the Neural and Physiological Bases of Acute Threat: A Research Domain Criteria (RDoC) Perspective

PubMed Central

Sumner, Jennifer A.; Powers, Abigail; Jovanovic, Tanja; Koenen, Karestan C.

2015-01-01

The NIMH Research Domain Criteria (RDoC) initiative aims to describe key dimensional constructs underlying mental function across multiple units of analysis—from genes to observable behaviors—in order to better understand psychopathology. The acute threat (“fear”) construct of the RDoC Negative Valence System has been studied extensively from a translational perspective, and is highly pertinent to numerous psychiatric conditions, including anxiety and trauma-related disorders. We examined genetic contributions to the construct of acute threat at two units of analysis within the RDoC framework: 1) neural circuits and 2) physiology. Specifically, we focused on genetic influences on activation patterns of frontolimbic neural circuitry and on startle, skin conductance, and heart rate responses. Research on the heritability of activation in threat-related frontolimbic neural circuitry is lacking, but physiological indicators of acute threat have been found to be moderately heritable (35-50%). Genetic studies of the neural circuitry and physiology of acute threat have almost exclusively relied on the candidate gene method and, as in the broader psychiatric genetics literature, most findings have failed to replicate. The most robust support has been demonstrated for associations between variation in the serotonin transporter (SLC6A4) and catechol-O-methyltransferase (COMT) genes with threat-related neural activation and physiological responses. However, unbiased genome-wide approaches using very large samples are needed for gene discovery, and these can be accomplished with collaborative consortium-based research efforts, such as those of the Psychiatric Genomics Consortium (PGC) and Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium. PMID:26377804

Optical-Correlator Neural Network Based On Neocognitron

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Stoner, William W.

1994-01-01

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

Neural-Network Simulator

NASA Technical Reports Server (NTRS)

Mitchell, Paul H.

1991-01-01

F77NNS (FORTRAN 77 Neural Network Simulator) computer program simulates popular back-error-propagation neural network. Designed to take advantage of vectorization when used on computers having this capability, also used on any computer equipped with ANSI-77 FORTRAN Compiler. Problems involving matching of patterns or mathematical modeling of systems fit class of problems F77NNS designed to solve. Program has restart capability so neural network solved in stages suitable to user's resources and desires. Enables user to customize patterns of connections between layers of network. Size of neural network F77NNS applied to limited only by amount of random-access memory available to user.

Monopolar Detection Thresholds Predict Spatial Selectivity of Neural Excitation in Cochlear Implants: Implications for Speech Recognition

PubMed Central

2016-01-01

The objectives of the study were to (1) investigate the potential of using monopolar psychophysical detection thresholds for estimating spatial selectivity of neural excitation with cochlear implants and to (2) examine the effect of site removal on speech recognition based on the threshold measure. Detection thresholds were measured in Cochlear Nucleus® device users using monopolar stimulation for pulse trains that were of (a) low rate and long duration, (b) high rate and short duration, and (c) high rate and long duration. Spatial selectivity of neural excitation was estimated by a forward-masking paradigm, where the probe threshold elevation in the presence of a forward masker was measured as a function of masker-probe separation. The strength of the correlation between the monopolar thresholds and the slopes of the masking patterns systematically reduced as neural response of the threshold stimulus involved interpulse interactions (refractoriness and sub-threshold adaptation), and spike-rate adaptation. Detection threshold for the low-rate stimulus most strongly correlated with the spread of forward masking patterns and the correlation reduced for long and high rate pulse trains. The low-rate thresholds were then measured for all electrodes across the array for each subject. Subsequently, speech recognition was tested with experimental maps that deactivated five stimulation sites with the highest thresholds and five randomly chosen ones. Performance with deactivating the high-threshold sites was better than performance with the subjects’ clinical map used every day with all electrodes active, in both quiet and background noise. Performance with random deactivation was on average poorer than that with the clinical map but the difference was not significant. These results suggested that the monopolar low-rate thresholds are related to the spatial neural excitation patterns in cochlear implant users and can be used to select sites for more optimal speech recognition performance. PMID:27798658

Weaving and neural complexity in symmetric quantum states

DOE PAGES

Susa, Cristian E.; Girolami, Davide

2017-12-27

Here, we study the behaviour of two different measures of the complexity of multipartite correlation patterns, weaving and neural complexity, for symmetric quantum states. Weaving is the weighted sum of genuine multipartite correlations of any order, where the weights are proportional to the correlation order. The neural complexity, originally introduced to characterize correlation patterns in classical neural networks, is here extended to the quantum scenario. We derive closed formulas of the two quantities for GHZ states mixed with white noise.

Weaving and neural complexity in symmetric quantum states

DOE Office of Scientific and Technical Information (OSTI.GOV)

Susa, Cristian E.; Girolami, Davide

Here, we study the behaviour of two different measures of the complexity of multipartite correlation patterns, weaving and neural complexity, for symmetric quantum states. Weaving is the weighted sum of genuine multipartite correlations of any order, where the weights are proportional to the correlation order. The neural complexity, originally introduced to characterize correlation patterns in classical neural networks, is here extended to the quantum scenario. We derive closed formulas of the two quantities for GHZ states mixed with white noise.

Experiential, autonomic, and neural responses during threat anticipation vary as a function of threat intensity and neuroticism.

PubMed

Drabant, Emily M; Kuo, Janice R; Ramel, Wiveka; Blechert, Jens; Edge, Michael D; Cooper, Jeff R; Goldin, Philippe R; Hariri, Ahmad R; Gross, James J

2011-03-01

Anticipatory emotional responses play a crucial role in preparing individuals for impending challenges. They do this by triggering a coordinated set of changes in behavioral, autonomic, and neural response systems. In the present study, we examined the biobehavioral impact of varying levels of anticipatory anxiety, using a shock anticipation task in which unpredictable electric shocks were threatened and delivered to the wrist at variable intervals and intensities (safe, medium, strong). This permitted investigation of a dynamic range of anticipatory anxiety responses. In two studies, 95 and 51 healthy female participants, respectively, underwent this shock anticipation task while providing continuous ratings of anxiety experience and electrodermal responding (Study 1) and during fMRI BOLD neuroimaging (Study 2). Results indicated a step-wise pattern of responding in anxiety experience and electrodermal responses. Several brain regions showed robust responses to shock anticipation relative to safe trials, including the hypothalamus, periaqueductal gray, caudate, precentral gyrus, thalamus, insula, ventrolateral PFC, dorsomedial PFC, and ACC. A subset of these regions demonstrated a linear pattern of increased responding from safe to medium to strong trials, including the bilateral insula, ACC, and inferior frontal gyrus. These responses were modulated by individual differences in neuroticism, such that those high in neuroticism showed exaggerated anxiety experience across the entire task, and reduced brain activation from medium to strong trials in a subset of brain regions. These findings suggest that individual differences in neuroticism may influence sensitivity to anticipatory threat and provide new insights into the mechanism through which neuroticism may confer risk for developing anxiety disorders via dysregulated anticipatory responses. Copyright © 2010 Elsevier Inc. All rights reserved.

Interpretations of Frequency Domain Analyses of Neural Entrainment: Periodicity, Fundamental Frequency, and Harmonics.

PubMed

Zhou, Hong; Melloni, Lucia; Poeppel, David; Ding, Nai

2016-01-01

Brain activity can follow the rhythms of dynamic sensory stimuli, such as speech and music, a phenomenon called neural entrainment. It has been hypothesized that low-frequency neural entrainment in the neural delta and theta bands provides a potential mechanism to represent and integrate temporal information. Low-frequency neural entrainment is often studied using periodically changing stimuli and is analyzed in the frequency domain using the Fourier analysis. The Fourier analysis decomposes a periodic signal into harmonically related sinusoids. However, it is not intuitive how these harmonically related components are related to the response waveform. Here, we explain the interpretation of response harmonics, with a special focus on very low-frequency neural entrainment near 1 Hz. It is illustrated why neural responses repeating at f Hz do not necessarily generate any neural response at f Hz in the Fourier spectrum. A strong neural response at f Hz indicates that the time scales of the neural response waveform within each cycle match the time scales of the stimulus rhythm. Therefore, neural entrainment at very low frequency implies not only that the neural response repeats at f Hz but also that each period of the neural response is a slow wave matching the time scale of a f Hz sinusoid.

Visual Discomfort From Flash Afterimages of Riloid Patterns.

PubMed

O'Hare, Louise

2017-06-01

Op-art-based stimuli have been shown to be uncomfortable, possibly due to a combination of fixational eye movements (microsaccades) and excessive cortical responses. Efforts have been made to measure illusory phenomena arising from these stimuli in the absence of microsaccades, but there has been no attempt thus far to decouple the effects of the cortical response from the effect of fixational eye movements. This study uses flash afterimages to stabilise the image on the retina and thus reduce the systematic effect of eye movements, in order to investigate the role of the brain in discomfort from op-art-based stimuli. There was a relationship between spatial frequency and the magnitude of the P300 response, showing a similar pattern to that of discomfort judgements, which suggests that there might be a role of discomfort and excessive neural responses independently from the effects of microsaccades.

Neural Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Patrick I.

2003-09-23

Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neuralmore » networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing information [2]. Each one of these cells acts as a simple processor. When individual cells interact with one another, the complex abilities of the brain are made possible. In neural networks, the input or data are processed by a propagation function that adds up the values of all the incoming data. The ending value is then compared with a threshold or specific value. The resulting value must exceed the activation function value in order to become output. The activation function is a mathematical function that a neuron uses to produce an output referring to its input value. [8] Figure 1 depicts this process. Neural networks usually have three components an input, a hidden, and an output. These layers create the end result of the neural network. A real world example is a child associating the word dog with a picture. The child says dog and simultaneously looks a picture of a dog. The input is the spoken word ''dog'', the hidden is the brain processing, and the output will be the category of the word dog based on the picture. This illustration describes how a neural network functions.« less

Learning by subtraction: Hippocampal activity and effects of ethanol during the acquisition and performance of response sequences.

PubMed

Ketchum, Myles J; Weyand, Theodore G; Weed, Peter F; Winsauer, Peter J

2016-05-01

Learning is believed to be reflected in the activity of the hippocampus. However, neural correlates of learning have been difficult to characterize because hippocampal activity is integrated with ongoing behavior. To address this issue, male rats (n = 5) implanted with electrodes (n = 14) in the CA1 subfield responded during two tasks within a single test session. In one task, subjects acquired a new 3-response sequence (acquisition), whereas in the other task, subjects completed a well-rehearsed 3-response sequence (performance). Both tasks though could be completed using an identical response topography and used the same sensory stimuli and schedule of reinforcement. More important, comparing neural patterns during sequence acquisition to those during sequence performance allows for a subtractive approach whereby activity associated with learning could potentially be dissociated from the activity associated with ongoing behavior. At sites where CA1 activity was closely associated with behavior, the patterns of activity were differentially modulated by key position and the serial position of a response within the schedule of reinforcement. Temporal shifts between peak activity and responding on particular keys also occurred during sequence acquisition, but not during sequence performance. Ethanol disrupted CA1 activity while producing rate-decreasing effects in both tasks and error-increasing effects that were more selective for sequence acquisition than sequence performance. Ethanol also produced alterations in the magnitude of modulations and temporal pattern of CA1 activity, although these effects were not selective for sequence acquisition. Similar to ethanol, hippocampal micro-stimulation decreased response rate in both tasks and selectively increased the percentage of errors during sequence acquisition, and provided a more direct demonstration of hippocampal involvement during sequence acquisition. Together, these results strongly support the notion that ethanol disrupts sequence acquisition by disrupting hippocampal activity and that the hippocampus is necessary for the conditioned associations required for sequence acquisition. © 2015 Wiley Periodicals, Inc.

Learning by Subtraction: Hippocampal Activity and Effects of Ethanol during the Acquisition and Performance of Response Sequences

PubMed Central

Ketchum, Myles J.; Weyand, Theodore G.; Weed, Peter F.; Winsauer, Peter J.

2015-01-01

Learning is believed to be reflected in the activity of the hippocampus. However, neural correlates of learning have been difficult to characterize because hippocampal activity is integrated with ongoing behavior. To address this issue, male rats (n=5) implanted with electrodes (n=14) in the CA1 subfield responded during two tasks within a single test session. In one task, subjects acquired a new 3-response sequence (acquisition), whereas in the other task, subjects completed a well-rehearsed 3-response sequence (performance). Both tasks though could be completed using an identical response topography and used the same sensory stimuli and schedule of reinforcement. More important, comparing neural patterns during sequence acquisition to those during sequence performance allows for a subtractive approach whereby activity associated with learning could potentially be dissociated from the activity associated with ongoing behavior. At sites where CA1 activity was closely associated with behavior, the patterns of activity were differentially modulated by key position and the serial position of a response within the schedule of reinforcement. Temporal shifts between peak activity and responding on particular keys also occurred during sequence acquisition, but not during sequence performance. Ethanol disrupted CA1 activity while producing rate-decreasing effects in both tasks and error-increasing effects that were more selective for sequence acquisition than sequence performance. Ethanol also produced alterations in the magnitude of modulations and temporal pattern of CA1 activity, although these effects were not selective for sequence acquisition. Similar to ethanol, hippocampal micro-stimulation decreased response rate in both tasks and selectively increased the percentage of errors during sequence acquisition, and provided a more direct demonstration of hippocampal involvement during sequence acquisition. Together, these results strongly support the notion that ethanol disrupts sequence acquisition by disrupting hippocampal activity and that the hippocampus is necessary for the conditioned associations required for sequence acquisition. PMID:26482846

Emergence of order in visual system development.

PubMed Central

Shatz, C J

1996-01-01

Neural connections in the adult central nervous system are highly precise. In the visual system, retinal ganglion cells send their axons to target neurons in the lateral geniculate nucleus (LGN) in such a way that axons originating from the two eyes terminate in adjacent but nonoverlapping eye-specific layers. During development, however, inputs from the two eyes are intermixed, and the adult pattern emerges gradually as axons from the two eyes sort out to form the layers. Experiments indicate that the sorting-out process, even though it occurs in utero in higher mammals and always before vision, requires retinal ganglion cell signaling; blocking retinal ganglion cell action potentials with tetrodotoxin prevents the formation of the layers. These action potentials are endogenously generated by the ganglion cells, which fire spontaneously and synchronously with each other, generating "waves" of activity that travel across the retina. Calcium imaging of the retina shows that the ganglion cells undergo correlated calcium bursting to generate the waves and that amacrine cells also participate in the correlated activity patterns. Physiological recordings from LGN neurons in vitro indicate that the quasiperiodic activity generated by the retinal ganglion cells is transmitted across the synapse between ganglion cells to drive target LGN neurons. These observations suggest that (i) a neural circuit within the immature retina is responsible for generating specific spatiotemporal patterns of neural activity; (ii) spontaneous activity generated in the retina is propagated across central synapses; and (iii) even before the photoreceptors are present, nerve cell function is essential for correct wiring of the visual system during early development. Since spontaneously generated activity is known to be present elsewhere in the developing CNS, this process of activity-dependent wiring could be used throughout the nervous system to help refine early sets of neural connections into their highly precise adult patterns. Images Fig. 1 Fig. 4 PMID:8570602

Retinoic acid regulates size, pattern and alignment of tissues at the head-trunk transition.

PubMed

Lee, Keun; Skromne, Isaac

2014-11-01

At the head-trunk transition, hindbrain and spinal cord alignment to occipital and vertebral bones is crucial for coherent neural and skeletal system organization. Changes in neural or mesodermal tissue configuration arising from defects in the specification, patterning or relative axial placement of territories can severely compromise their integration and function. Here, we show that coordination of neural and mesodermal tissue at the zebrafish head-trunk transition crucially depends on two novel activities of the signaling factor retinoic acid (RA): one specifying the size and the other specifying the axial position relative to mesodermal structures of the hindbrain territory. These activities are each independent but coordinated with the well-established function of RA in hindbrain patterning. Using neural and mesodermal landmarks we demonstrate that the functions of RA in aligning neural and mesodermal tissues temporally precede the specification of hindbrain and spinal cord territories and the activation of hox transcription. Using cell transplantation assays we show that RA activity in the neuroepithelium regulates hindbrain patterning directly and territory size specification indirectly. This indirect function is partially dependent on Wnts but independent of FGFs. Importantly, RA specifies and patterns the hindbrain territory by antagonizing the activity of the spinal cord specification gene cdx4; loss of Cdx4 rescues the defects associated with the loss of RA, including the reduction in hindbrain size and the loss of posterior rhombomeres. We propose that at the head-trunk transition, RA coordinates specification, patterning and alignment of neural and mesodermal tissues that are essential for the organization and function of the neural and skeletal systems. © 2014. Published by The Company of Biologists Ltd.

Evolution of central pattern generators and rhythmic behaviours

PubMed Central

Katz, Paul S.

2016-01-01

Comparisons of rhythmic movements and the central pattern generators (CPGs) that control them uncover principles about the evolution of behaviour and neural circuits. Over the course of evolutionary history, gradual evolution of behaviours and their neural circuitry within any lineage of animals has been a predominant occurrence. Small changes in gene regulation can lead to divergence of circuit organization and corresponding changes in behaviour. However, some behavioural divergence has resulted from large-scale rewiring of the neural network. Divergence of CPG circuits has also occurred without a corresponding change in behaviour. When analogous rhythmic behaviours have evolved independently, it has generally been with different neural mechanisms. Repeated evolution of particular rhythmic behaviours has occurred within some lineages due to parallel evolution or latent CPGs. Particular motor pattern generating mechanisms have also evolved independently in separate lineages. The evolution of CPGs and rhythmic behaviours shows that although most behaviours and neural circuits are highly conserved, the nature of the behaviour does not dictate the neural mechanism and that the presence of homologous neural components does not determine the behaviour. This suggests that although behaviour is generated by neural circuits, natural selection can act separately on these two levels of biological organization. PMID:26598733

Evolution of central pattern generators and rhythmic behaviours.

PubMed

Katz, Paul S

2016-01-05

Comparisons of rhythmic movements and the central pattern generators (CPGs) that control them uncover principles about the evolution of behaviour and neural circuits. Over the course of evolutionary history, gradual evolution of behaviours and their neural circuitry within any lineage of animals has been a predominant occurrence. Small changes in gene regulation can lead to divergence of circuit organization and corresponding changes in behaviour. However, some behavioural divergence has resulted from large-scale rewiring of the neural network. Divergence of CPG circuits has also occurred without a corresponding change in behaviour. When analogous rhythmic behaviours have evolved independently, it has generally been with different neural mechanisms. Repeated evolution of particular rhythmic behaviours has occurred within some lineages due to parallel evolution or latent CPGs. Particular motor pattern generating mechanisms have also evolved independently in separate lineages. The evolution of CPGs and rhythmic behaviours shows that although most behaviours and neural circuits are highly conserved, the nature of the behaviour does not dictate the neural mechanism and that the presence of homologous neural components does not determine the behaviour. This suggests that although behaviour is generated by neural circuits, natural selection can act separately on these two levels of biological organization. © 2015 The Author(s).

Source analysis of auditory steady-state responses in acoustic and electric hearing.

PubMed

Luke, Robert; De Vos, Astrid; Wouters, Jan

2017-02-15

Speech is a complex signal containing a broad variety of acoustic information. For accurate speech reception, the listener must perceive modulations over a range of envelope frequencies. Perception of these modulations is particularly important for cochlear implant (CI) users, as all commercial devices use envelope coding strategies. Prolonged deafness affects the auditory pathway. However, little is known of how cochlear implantation affects the neural processing of modulated stimuli. This study investigates and contrasts the neural processing of envelope rate modulated signals in acoustic and CI listeners. Auditory steady-state responses (ASSRs) are used to study the neural processing of amplitude modulated (AM) signals. A beamforming technique is applied to determine the increase in neural activity relative to a control condition, with particular attention paid to defining the accuracy and precision of this technique relative to other tomographies. In a cohort of 44 acoustic listeners, the location, activity and hemispheric lateralisation of ASSRs is characterised while systematically varying the modulation rate (4, 10, 20, 40 and 80Hz) and stimulation ear (right, left and bilateral). We demonstrate a complex pattern of laterality depending on both modulation rate and stimulation ear that is consistent with, and extends, existing literature. We present a novel extension to the beamforming method which facilitates source analysis of electrically evoked auditory steady-state responses (EASSRs). In a cohort of 5 right implanted unilateral CI users, the neural activity is determined for the 40Hz rate and compared to the acoustic cohort. Results indicate that CI users activate typical thalamic locations for 40Hz stimuli. However, complementary to studies of transient stimuli, the CI population has atypical hemispheric laterality, preferentially activating the contralateral hemisphere. Copyright © 2016. Published by Elsevier Inc.

Neural substrates of reward magnitude, probability, and risk during a wheel of fortune decision-making task.

PubMed

Smith, Bruce W; Mitchell, Derek G V; Hardin, Michael G; Jazbec, Sandra; Fridberg, Daniel; Blair, R James R; Ernst, Monique

2009-01-15

Economic decision-making involves the weighting of magnitude and probability of potential gains/losses. While previous work has examined the neural systems involved in decision-making, there is a need to understand how the parameters associated with decision-making (e.g., magnitude of expected reward, probability of expected reward and risk) modulate activation within these neural systems. In the current fMRI study, we modified the monetary wheel of fortune (WOF) task [Ernst, M., Nelson, E.E., McClure, E.B., Monk, C.S., Munson, S., Eshel, N., et al. (2004). Choice selection and reward anticipation: an fMRI study. Neuropsychologia 42(12), 1585-1597.] to examine in 25 healthy young adults the neural responses to selections of different reward magnitudes, probabilities, or risks. Selection of high, relative to low, reward magnitude increased activity in insula, amygdala, middle and posterior cingulate cortex, and basal ganglia. Selection of low-probability, as opposed to high-probability reward, increased activity in anterior cingulate cortex, as did selection of risky, relative to safe reward. In summary, decision-making that did not involve conflict, as in the magnitude contrast, recruited structures known to support the coding of reward values, and those that integrate motivational and perceptual information for behavioral responses. In contrast, decision-making under conflict, as in the probability and risk contrasts, engaged the dorsal anterior cingulate cortex whose role in conflict monitoring is well established. However, decision-making under conflict failed to activate the structures that track reward values per se. Thus, the presence of conflict in decision-making seemed to significantly alter the pattern of neural responses to simple rewards. In addition, this paradigm further clarifies the functional specialization of the cingulate cortex in processes of decision-making.

Ultradian rhythmicity of plasma cortisol is necessary for normal emotional and cognitive responses in man.

PubMed

Kalafatakis, K; Russell, G M; Harmer, C J; Munafo, M R; Marchant, N; Wilson, A; Brooks, J C; Durant, C; Thakrar, J; Murphy, P; Thai, N J; Lightman, S L

2018-04-24

Glucocorticoids (GCs) are secreted in an ultradian, pulsatile pattern that emerges from delays in the feedforward-feedback interaction between the anterior pituitary and adrenal glands. Dynamic oscillations of GCs are critical for normal cognitive and metabolic function in the rat and have been shown to modulate the pattern of GC-sensitive gene expression, modify synaptic activity, and maintain stress responsiveness. In man, current cortisol replacement therapy does not reproduce physiological hormone pulses and is associated with psychopathological symptoms, especially apathy and attenuated motivation in engaging with daily activities. In this work, we tested the hypothesis that the pattern of GC dynamics in the brain is of crucial importance for regulating cognitive and behavioral processes. We provide evidence that exactly the same dose of cortisol administered in different patterns alters the neural processing underlying the response to emotional stimulation, the accuracy in recognition and attentional bias toward/away from emotional faces, the quality of sleep, and the working memory performance of healthy male volunteers. These data indicate that the pattern of the GC rhythm differentially impacts human cognition and behavior under physiological, nonstressful conditions and has major implications for the improvement of cortisol replacement therapy.

Neural net target-tracking system using structured laser patterns

NASA Astrophysics Data System (ADS)

Cho, Jae-Wan; Lee, Yong-Bum; Lee, Nam-Ho; Park, Soon-Yong; Lee, Jongmin; Choi, Gapchu; Baek, Sunghyun; Park, Dong-Sun

1996-06-01

In this paper, we describe a robot endeffector tracking system using sensory information from recently-announced structured pattern laser diodes, which can generate images with several different types of structured pattern. The neural network approach is employed to recognize the robot endeffector covering the situation of three types of motion: translation, scaling and rotation. Features for the neural network to detect the position of the endeffector are extracted from the preprocessed images. Artificial neural networks are used to store models and to match with unknown input features recognizing the position of the robot endeffector. Since a minimal number of samples are used for different directions of the robot endeffector in the system, an artificial neural network with the generalization capability can be utilized for unknown input features. A feedforward neural network with the generalization capability can be utilized for unknown input features. A feedforward neural network trained with the back propagation learning is used to detect the position of the robot endeffector. Another feedforward neural network module is used to estimate the motion from a sequence of images and to control movements of the robot endeffector. COmbining the tow neural networks for recognizing the robot endeffector and estimating the motion with the preprocessing stage, the whole system keeps tracking of the robot endeffector effectively.

Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks

PubMed Central

2018-01-01

Much of the information the brain processes and stores is temporal in nature—a spoken word or a handwritten signature, for example, is defined by how it unfolds in time. However, it remains unclear how neural circuits encode complex time-varying patterns. We show that by tuning the weights of a recurrent neural network (RNN), it can recognize and then transcribe spoken digits. The model elucidates how neural dynamics in cortical networks may resolve three fundamental challenges: first, encode multiple time-varying sensory and motor patterns as stable neural trajectories; second, generalize across relevant spatial features; third, identify the same stimuli played at different speeds—we show that this temporal invariance emerges because the recurrent dynamics generate neural trajectories with appropriately modulated angular velocities. Together our results generate testable predictions as to how recurrent networks may use different mechanisms to generalize across the relevant spatial and temporal features of complex time-varying stimuli. PMID:29537963

Neural networks: Alternatives to conventional techniques for automatic docking

NASA Technical Reports Server (NTRS)

Vinz, Bradley L.

1994-01-01

Automatic docking of orbiting spacecraft is a crucial operation involving the identification of vehicle orientation as well as complex approach dynamics. The chaser spacecraft must be able to recognize the target spacecraft within a scene and achieve accurate closing maneuvers. In a video-based system, a target scene must be captured and transformed into a pattern of pixels. Successful recognition lies in the interpretation of this pattern. Due to their powerful pattern recognition capabilities, artificial neural networks offer a potential role in interpretation and automatic docking processes. Neural networks can reduce the computational time required by existing image processing and control software. In addition, neural networks are capable of recognizing and adapting to changes in their dynamic environment, enabling enhanced performance, redundancy, and fault tolerance. Most neural networks are robust to failure, capable of continued operation with a slight degradation in performance after minor failures. This paper discusses the particular automatic docking tasks neural networks can perform as viable alternatives to conventional techniques.

Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks.

PubMed

Goudar, Vishwa; Buonomano, Dean V

2018-03-14

Much of the information the brain processes and stores is temporal in nature-a spoken word or a handwritten signature, for example, is defined by how it unfolds in time. However, it remains unclear how neural circuits encode complex time-varying patterns. We show that by tuning the weights of a recurrent neural network (RNN), it can recognize and then transcribe spoken digits. The model elucidates how neural dynamics in cortical networks may resolve three fundamental challenges: first, encode multiple time-varying sensory and motor patterns as stable neural trajectories; second, generalize across relevant spatial features; third, identify the same stimuli played at different speeds-we show that this temporal invariance emerges because the recurrent dynamics generate neural trajectories with appropriately modulated angular velocities. Together our results generate testable predictions as to how recurrent networks may use different mechanisms to generalize across the relevant spatial and temporal features of complex time-varying stimuli. © 2018, Goudar et al.

Aberrant occipital dynamics differentiate HIV-infected patients with and without cognitive impairment.

PubMed

Wiesman, Alex I; O'Neill, Jennifer; Mills, Mackenzie S; Robertson, Kevin R; Fox, Howard S; Swindells, Susan; Wilson, Tony W

2018-06-01

Combination antiretroviral therapies have revolutionized the treatment of HIV infection, and many patients now enjoy a lifespan equal to that of the general population. However, HIV-associated neurocognitive disorders (HAND) remain a major health concern, with between 30% and 70% of all HIV-infected patients developing cognitive impairments during their life time. One important feature of HAND is visuo-perceptual deficits, but the systems-level neural dynamics underlying these impairments are poorly understood. In the current study, we use magnetoencephalography and advanced time series analyses to examine these neural dynamics during a visuospatial processing task in a group of HIV-infected patients without HAND (n = 25), patients with HAND (n = 18), and a group of demographically-matched uninfected controls (n = 24). All participants completed a thorough neuropsychological assessment, and underwent magnetoencephalography and structural MRI protocols. In agreement with previous studies, patients with HAND performed significantly worse than HIV-infected patients without HAND and controls on the cognitive task, in terms of increased reaction time and decreased accuracy. Our magnetoencephalography results demonstrated that both spontaneous and neural oscillatory activity within the occipital cortices were affected by HIV infection, and that these patterns predicted behavioural performance (i.e. accuracy) on the task. Specifically, spontaneous neural activity in the alpha (8-16 Hz) and gamma (52-70 Hz) bands during the prestimulus baseline period, as well as oscillatory theta responses (4-8 Hz) during task performance were aberrant in HIV-infected patients, with both spontaneous alpha and oscillatory theta activity significantly predicting accuracy on the task and neuropsychological performance outside of the magnetoencephalography scanner. Importantly, these rhythmic patterns of population-level neural activity also distinguished patients by HAND status, such that spontaneous alpha activity in patients with HAND was elevated relative to HIV-infected patients without HAND and controls. In contrast, HIV-infected patients with and without HAND had increased spontaneous gamma compared to controls. Finally, there was a stepwise decrease in oscillatory theta activity as a function of disease severity, such that the response diminished from controls to patients without HAND to patients with HAND. Interestingly, the strength of the relationship between this theta response and accuracy also dissociated patient groups in a similar manner (controls > HIV with no HAND > HIV with HAND), indicating a reduced coupling between neurophysiology and behaviour in HIV-infected patients. This study provides the first neuroimaging evidence of a dissociation between HIV-infected patients with and without HAND, and these findings shed new light on the neural bases of cognitive impairment in HIV infection.

Alternative forms of axial startle behaviors in fishes.

PubMed

Liu, Yen-Chyi; Hale, Melina E

2014-02-01

For most aquatic vertebrates, axial movements play key roles in the performance of startle responses. In fishes, these axis-based startle behaviors fall into three distinct categories - the C-start, withdrawal, and S-start - defined by patterns of body bending and underlying motor control. Startle behaviors have been widely studied due to their importance for predator evasion. In addition, the neural circuits that control startles are relatively accessible, compared to other vertebrate circuits, and have provided opportunities to understand basic nervous system function. The C-start neural circuit has long been a model in systems neuroscience and considerable work on neural control of withdrawal response has been conducted in the larval lamprey. The S-start response has only recently been explored from a physiological perspective and we focus here on reviewing S-start motor control and movement in the context of the other two responses. Axial elongation has previously been associated with startle behavior in comparisons of C-starts and withdrawal, with extremely elongate animals performing withdrawals. We suggest that the S-start tends to occur with moderate body elongation, complementing the C-start in animals with this body form. As many larval fishes are moderately elongate, we suggest that the S-start may be common in larvae but may be secondarily lost with body shape change through development. Copyright © 2013 Elsevier GmbH. All rights reserved.

Prior activity of olfactory receptor neurons is required for proper sensory processing and behavior in Drosophila larvae.

PubMed

Utashiro, Nao; Williams, Claire R; Parrish, Jay Z; Emoto, Kazuo

2018-06-05

Animal responses to their environment rely on activation of sensory neurons by external stimuli. In many sensory systems, however, neurons display basal activity prior to the external stimuli. This prior activity is thought to modulate neural functions, yet its impact on animal behavior remains elusive. Here, we reveal a potential role for prior activity in olfactory receptor neurons (ORNs) in shaping larval olfactory behavior. We show that prior activity in larval ORNs is mediated by the olfactory receptor complex (OR complex). Mutations of Orco, an odorant co-receptor required for OR complex function, cause reduced attractive behavior in response to optogenetic activation of ORNs. Calcium imaging reveals that Orco mutant ORNs fully respond to optogenetic stimulation but exhibit altered temporal patterns of neural responses. These findings together suggest a critical role for prior activity in information processing upon ORN activation in Drosophila larvae, which in turn contributes to olfactory behavior control.

Ageing differentially affects neural processing of different conflict types-an fMRI study.

PubMed

Korsch, Margarethe; Frühholz, Sascha; Herrmann, Manfred

2014-01-01

Interference control and conflict resolution is affected by ageing. There is increasing evidence that ageing does not compromise interference control in general but rather shows distinctive effects on different components of interference control. Different conflict types, [e.g., stimulus-stimulus (S-S) or stimulus-response (S-R) conflicts] trigger different cognitive processes and thus activate different neural networks. In the present functional magnetic resonance imaging (fMRI) study, we used a combined Flanker and Stimulus Response Conflict (SRC) task to investigate the effect of ageing on S-S and S-R conflicts. Behavioral data analysis revealed larger SRC effects in elderly. fMRI Results show that both age groups recruited similar regions [caudate nucleus, cingulate gyrus and middle occipital gyrus (MOG)] during Flanker conflict processing. Furthermore, elderly show an additional activation pattern in parietal and frontal areas. In contrast, no common activation of both age groups was found in response to the SRC. These data suggest that ageing has distinctive effects on S-S and S-R conflicts.

Subjective and neural responses to intravenous alcohol in young adults with light and heavy drinking patterns.

PubMed

Gilman, Jodi M; Ramchandani, Vijay A; Crouss, Tess; Hommer, Daniel W

2012-01-01

Heavy alcohol consumption during young adulthood is a risk factor for the development of serious alcohol use disorders. Research has shown that individual differences in subjective responses to alcohol may affect individuals' vulnerability to developing alcoholism. Studies comparing the subjective and objective response to alcohol between light and heavy drinkers (HDs), however, have yielded inconsistent results, and neural responses to alcohol in these groups have not been characterized. We performed a double-blind, placebo-controlled, randomized crossover alcohol challenge study comparing functional magnetic resonance imaging and subjective response to intravenously administered 6% v/v ethanol to a target blood alcohol concentration of 0.08% or placebo between HDs and social drinkers (SDs). During the imaging, we presented emotional cues in order to measure how emotion modulated the effects of alcohol on the brain's reward circuitry. We found that, at equivalent blood alcohol concentrations, HDs reported lower subjective alcohol effects than SDs. Alcohol significantly activated the nucleus accumbens in SDs, but not in HDs. Self-reported ratings of intoxication correlated with striatal activation, suggesting that activation may reflect subjective experience of intoxication. Fearful faces significantly activated the amygdala in the SDs only, and this activation was attenuated by alcohol. This study shows that HDs not only experience reduced subjective effects of alcohol, but also demonstrate a blunted response to alcohol in the brain's reward system. Our findings indicate that reduced subjective and neural response to alcohol in HDs may be suggestive of either the development of tolerance to alcohol, or of pre-existing decreased sensitivity to alcohol's effects.

Classification of 2-dimensional array patterns: assembling many small neural networks is better than using a large one.

PubMed

Chen, Liang; Xue, Wei; Tokuda, Naoyuki

2010-08-01

In many pattern classification/recognition applications of artificial neural networks, an object to be classified is represented by a fixed sized 2-dimensional array of uniform type, which corresponds to the cells of a 2-dimensional grid of the same size. A general neural network structure, called an undistricted neural network, which takes all the elements in the array as inputs could be used for problems such as these. However, a districted neural network can be used to reduce the training complexity. A districted neural network usually consists of two levels of sub-neural networks. Each of the lower level neural networks, called a regional sub-neural network, takes the elements in a region of the array as its inputs and is expected to output a temporary class label, called an individual opinion, based on the partial information of the entire array. The higher level neural network, called an assembling sub-neural network, uses the outputs (opinions) of regional sub-neural networks as inputs, and by consensus derives the label decision for the object. Each of the sub-neural networks can be trained separately and thus the training is less expensive. The regional sub-neural networks can be trained and performed in parallel and independently, therefore a high speed can be achieved. We prove theoretically in this paper, using a simple model, that a districted neural network is actually more stable than an undistricted neural network in noisy environments. We conjecture that the result is valid for all neural networks. This theory is verified by experiments involving gender classification and human face recognition. We conclude that a districted neural network is highly recommended for neural network applications in recognition or classification of 2-dimensional array patterns in highly noisy environments. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Neural breathing patterns in preterm newborns supported with non-invasive neurally adjusted ventilatory assist.

PubMed

García-Muñoz Rodrigo, Fermín; Urquía Martí, Lourdes; Galán Henríquez, Gloria; Rivero Rodríguez, Sonia; Hernández Gómez, Alberto

2018-06-18

To characterize the neural breathing pattern in preterm infants supported with non-invasive neurally adjusted ventilatory assist (NIV-NAVA). Single-center prospective observational study. The electrical activity of the diaphragm (EAdi) was periodically recorded in 30-second series with the Edi catheter and the Servo-n software (Maquet, Solna, Sweden) in preterm infants supported with NIV-NAVA. The EAdi Peak , EAdi Min , EAdi Tonic , EAdi Phasic , neural inspiratory, and expiratory times (nTi and nTe) and the neural respiratory rate (nRR) were calculated. EAdi curves were generated by Excel for visual examination and classified according to the predominant pattern. 291 observations were analyzed in 19 patients with a mean GA of 27.3 weeks (range 24-36 weeks), birth weight 1028 g (510-2945 g), and a median (IQR) postnatal age of 18 days (4-27 days). The distribution of respiratory patterns was phasic without tonic activity 61.9%, phasic with basal tonic activity 18.6, tonic burst 3.8%, central apnea 7.9%, and mixed pattern 7.9%. In addition, 12% of the records showed apneas of >10 seconds, and 50.2% one or more "sighs", defined as breaths with an EAdi Peak and/or nTi greater than twice the average EAdi Peak and/or nTi of the recording. Neural times were measurable in 252 observations. The nTi was, median (IQR): 279 ms (253-285 ms), the nTe 764 ms (642-925 ms), and the nRR 63 bpm (51-70), with a great intra and inter-subjects variability. The neural breathing patterns in preterm infants supported with NIV-NAVA are quite variable and are characterized by the presence of significant tonic activity. Central apneas and sighs are common in this group of patients. The nTi seems to be shorter than the mechanical Ti commonly used in assisted ventilation.

Differences in neural responses to reward and punishment processing between anorexia nervosa subtypes: An fMRI study.

PubMed

Murao, Ema; Sugihara, Genichi; Isobe, Masanori; Noda, Tomomi; Kawabata, Michiko; Matsukawa, Noriko; Takahashi, Hidehiko; Murai, Toshiya; Noma, Shun'ichi

2017-09-01

Anorexia nervosa (AN) includes the restricting (AN-r) and binge-eating/purging (AN-bp) subtypes, which have been reported to differ regarding their underlying pathophysiologies as well as their behavioral patterns. However, the differences in neural mechanisms of reward systems between AN subtypes remain unclear. The aim of the present study was to explore differences in the neural processing of reward and punishment between AN subtypes. Twenty-three female patients with AN (11 AN-r and 12 AN-bp) and 20 healthy women underwent functional magnetic resonance imaging while performing a monetary incentive delay task. Whole-brain one-way analysis of variance was conducted to test between-group differences. There were significant group differences in brain activation in the rostral anterior cingulate cortex and right posterior insula during loss anticipation, with increased brain activation in the AN-bp group relative to the AN-r and healthy women groups. No significant differences were found during gain anticipation. AN-bp patients showed altered neural responses to punishment in brain regions implicated in emotional arousal. Our findings suggest that individuals with AN-bp are more sensitive to potential punishment than individuals with AN-r and healthy individuals at the neural level. The present study provides preliminary evidence that there are neurobiological differences between AN subtypes with regard to the reward system, especially punishment processing. © 2017 The Authors. Psychiatry and Clinical Neurosciences © 2017 Japanese Society of Psychiatry and Neurology.

Effects of Morphology Constraint on Electrophysiological Properties of Cortical Neurons

NASA Astrophysics Data System (ADS)

Zhu, Geng; Du, Liping; Jin, Lei; Offenhäusser, Andreas

2016-04-01

There is growing interest in engineering nerve cells in vitro to control architecture and connectivity of cultured neuronal networks or to build neuronal networks with predictable computational function. Pattern technologies, such as micro-contact printing, have been developed to design ordered neuronal networks. However, electrophysiological characteristics of the single patterned neuron haven’t been reported. Here, micro-contact printing, using polyolefine polymer (POP) stamps with high resolution, was employed to grow cortical neurons in a designed structure. The results demonstrated that the morphology of patterned neurons was well constrained, and the number of dendrites was decreased to be about 2. Our electrophysiological results showed that alterations of dendritic morphology affected firing patterns of neurons and neural excitability. When stimulated by current, though both patterned and un-patterned neurons presented regular spiking, the dynamics and strength of the response were different. The un-patterned neurons exhibited a monotonically increasing firing frequency in response to injected current, while the patterned neurons first exhibited frequency increase and then a slow decrease. Our findings indicate that the decrease in dendritic complexity of cortical neurons will influence their electrophysiological characteristics and alter their information processing activity, which could be considered when designing neuronal circuitries.

Beyond mind-reading: multi-voxel pattern analysis of fMRI data.

PubMed

Norman, Kenneth A; Polyn, Sean M; Detre, Greg J; Haxby, James V

2006-09-01

A key challenge for cognitive neuroscience is determining how mental representations map onto patterns of neural activity. Recently, researchers have started to address this question by applying sophisticated pattern-classification algorithms to distributed (multi-voxel) patterns of functional MRI data, with the goal of decoding the information that is represented in the subject's brain at a particular point in time. This multi-voxel pattern analysis (MVPA) approach has led to several impressive feats of mind reading. More importantly, MVPA methods constitute a useful new tool for advancing our understanding of neural information processing. We review how researchers are using MVPA methods to characterize neural coding and information processing in domains ranging from visual perception to memory search.

Cross-Modal Decoding of Neural Patterns Associated with Working Memory: Evidence for Attention-Based Accounts of Working Memory.

PubMed

Majerus, Steve; Cowan, Nelson; Péters, Frédéric; Van Calster, Laurens; Phillips, Christophe; Schrouff, Jessica

2016-01-01

Recent studies suggest common neural substrates involved in verbal and visual working memory (WM), interpreted as reflecting shared attention-based, short-term retention mechanisms. We used a machine-learning approach to determine more directly the extent to which common neural patterns characterize retention in verbal WM and visual WM. Verbal WM was assessed via a standard delayed probe recognition task for letter sequences of variable length. Visual WM was assessed via a visual array WM task involving the maintenance of variable amounts of visual information in the focus of attention. We trained a classifier to distinguish neural activation patterns associated with high- and low-visual WM load and tested the ability of this classifier to predict verbal WM load (high-low) from their associated neural activation patterns, and vice versa. We observed significant between-task prediction of load effects during WM maintenance, in posterior parietal and superior frontal regions of the dorsal attention network; in contrast, between-task prediction in sensory processing cortices was restricted to the encoding stage. Furthermore, between-task prediction of load effects was strongest in those participants presenting the highest capacity for the visual WM task. This study provides novel evidence for common, attention-based neural patterns supporting verbal and visual WM. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Neural Pattern Similarity in the Left IFG and Fusiform Is Associated with Novel Word Learning

PubMed Central

Qu, Jing; Qian, Liu; Chen, Chuansheng; Xue, Gui; Li, Huiling; Xie, Peng; Mei, Leilei

2017-01-01

Previous studies have revealed that greater neural pattern similarity across repetitions is associated with better subsequent memory. In this study, we used an artificial language training paradigm and representational similarity analysis to examine whether neural pattern similarity across repetitions before training was associated with post-training behavioral performance. Twenty-four native Chinese speakers were trained to learn a logographic artificial language for 12 days and behavioral performance was recorded using the word naming and picture naming tasks. Participants were scanned while performing a passive viewing task before training, after 4-day training and after 12-day training. Results showed that pattern similarity in the left pars opercularis (PO) and fusiform gyrus (FG) before training was negatively associated with reaction time (RT) in both word naming and picture naming tasks after training. These results suggest that neural pattern similarity is an effective neurofunctional predictor of novel word learning in addition to word memory. PMID:28878640

Modality-independent representations of small quantities based on brain activation patterns.

PubMed

Damarla, Saudamini Roy; Cherkassky, Vladimir L; Just, Marcel Adam

2016-04-01

Machine learning or MVPA (Multi Voxel Pattern Analysis) studies have shown that the neural representation of quantities of objects can be decoded from fMRI patterns, in cases where the quantities were visually displayed. Here we apply these techniques to investigate whether neural representations of quantities depicted in one modality (say, visual) can be decoded from brain activation patterns evoked by quantities depicted in the other modality (say, auditory). The main finding demonstrated, for the first time, that quantities of dots were decodable by a classifier that was trained on the neural patterns evoked by quantities of auditory tones, and vice-versa. The representations that were common across modalities were mainly right-lateralized in frontal and parietal regions. A second finding was that the neural patterns in parietal cortex that represent quantities were common across participants. These findings demonstrate a common neuronal foundation for the representation of quantities across sensory modalities and participants and provide insight into the role of parietal cortex in the representation of quantity information. © 2016 Wiley Periodicals, Inc.

Digital micromirror based near-infrared illumination system for plasmonic photothermal neuromodulation

PubMed Central

Jung, Hyunjun; Kang, Hongki; Nam, Yoonkey

2017-01-01

Light-mediated neuromodulation techniques provide great advantages to investigate neuroscience due to its high spatial and temporal resolution. To generate a spatial pattern of neural activity, it is necessary to develop a system for patterned-light illumination to a specific area. Digital micromirror device (DMD) based patterned illumination system have been used for neuromodulation due to its simple configuration and design flexibility. In this paper, we developed a patterned near-infrared (NIR) illumination system for region specific photothermal manipulation of neural activity using NIR-sensitive plasmonic gold nanorods (GNRs). The proposed system had high power transmission efficiency for delivering power density up to 19 W/mm2. We used a GNR-coated microelectrode array (MEA) to perform biological experiments using E18 rat hippocampal neurons and showed that it was possible to inhibit neural spiking activity of specific area in neural circuits with the patterned NIR illumination. This patterned NIR illumination system can serve as a promising neuromodulation tool to investigate neuroscience in a wide range of physiological and clinical applications. PMID:28663912

Reward-related neural responses are dependent on the beneficiary.

PubMed

Braams, Barbara R; Güroğlu, Berna; de Water, Erik; Meuwese, Rosa; Koolschijn, P Cédric; Peper, Jiska S; Crone, Eveline A

2014-07-01

Prior studies have suggested that positive social interactions are experienced as rewarding. Yet, it is not well understood how social relationships influence neural responses to other persons' gains. In this study, we investigated neural responses during a gambling task in which healthy participants (N = 31; 18 females) could win or lose money for themselves, their best friend or a disliked other (antagonist). At the moment of receiving outcome, person-related activity was observed in the dorsal medial prefrontal cortex (dmPFC), precuneus and temporal parietal junction (TPJ), showing higher activity for friends and antagonists than for self, and this activity was independent of outcome. The only region showing an interaction between the person-participants played for and outcome was the ventral striatum. Specifically, the striatum was more active following gains than losses for self and friends, whereas for the antagonist this pattern was reversed. Together, these results show that, in a context with social and reward information, social aspects are processed in brain regions associated with social cognition (mPFC, TPJ), and reward aspects are processed in primary reward areas (striatum). Furthermore, there is an interaction of social and reward information in the striatum, such that reward-related activity was dependent on social relationship. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Analyte species and concentration identification using differentially functionalized microcantilever arrays and artificial neural networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Senesac, Larry R; Datskos, Panos G; Sepaniak, Michael J

2006-01-01

In the present work, we have performed analyte species and concentration identification using an array of ten differentially functionalized microcantilevers coupled with a back-propagation artificial neural network pattern recognition algorithm. The array consists of ten nanostructured silicon microcantilevers functionalized by polymeric and gas chromatography phases and macrocyclic receptors as spatially dense, differentially responding sensing layers for identification and quantitation of individual analyte(s) and their binary mixtures. The array response (i.e. cantilever bending) to analyte vapor was measured by an optical readout scheme and the responses were recorded for a selection of individual analytes as well as several binary mixtures. Anmore » artificial neural network (ANN) was designed and trained to recognize not only the individual analytes and binary mixtures, but also to determine the concentration of individual components in a mixture. To the best of our knowledge, ANNs have not been applied to microcantilever array responses previously to determine concentrations of individual analytes. The trained ANN correctly identified the eleven test analyte(s) as individual components, most with probabilities greater than 97%, whereas it did not misidentify an unknown (untrained) analyte. Demonstrated unique aspects of this work include an ability to measure binary mixtures and provide both qualitative (identification) and quantitative (concentration) information with array-ANN-based sensor methodologies.« less

Neural Correlates and Connectivity underlying Stress-related Impulse Control Difficulties in Alcoholism

PubMed Central

Seo, Dongju; Lacadie, Cheryl M.; Sinha, Rajita

2016-01-01

BACKGROUND Stress triggers impulsive and addictive behaviors, and alcoholism has been frequently associated with increased stress sensitivity and impulse control problems. However, neural correlates underlying the link between alcoholism and impulsivity in the context of stress in patients with alcohol use disorders (AUD) have not been well studied. METHOD The current study investigated neural correlates and connectivity patterns associated with impulse control difficulties in abstinent AUD patients. Using functional magnetic resonance imaging, brain responses of 37 AUD inpatients and 37 demographically-matched healthy controls were examined during brief individualized imagery trials of stress, alcohol-cue and neutral-relaxing conditions. Stress-related impulsivity was measured using a subscale score of impulse control problems from Difficulties in Emotion Regulation Scale (DERS). RESULTS Impulse control difficulties in AUD patients were significantly associated with hypoactive response to stress in the ventromedial prefrontal cortex (VmPFC), right caudate, and left lateral PFC (LPFC) compared to the neutral condition (p<0.01, whole-brain corrected). These regions were used as seed regions to further examine the connectivity patterns with other brain regions. With the VmPFC seed, AUD patients showed reduced connectivity with the anterior cingulate cortex (ACC) compared to controls, which are core regions of emotion regulation, suggesting AUD patients’ decreased ability to modulate emotional response under distressed state. With the right caudate seed, patients showed increased connectivity with the right motor cortex, suggesting increased tendency toward habitually driven behaviors. With the left LPFC seed, decreased connectivity with the dorsomedial PFC (DmPFC), but increased connectivity with sensory and motor cortices were found in AUD patients compared to controls (p<0.05, whole-brain corrected). Reduced connectivity between the left LPFC and DmPFC was further associated with increased stress-induced anxiety in AUD patients (p<0.05, with adjusted Bonferroni correction). CONCLUSION Hypoactive response to stress and altered connectivity in key emotion regulatory regions may account for greater stress-related impulse control problems in alcoholism. PMID:27501356

Neural Correlates and Connectivity Underlying Stress-Related Impulse Control Difficulties in Alcoholism.

PubMed

Seo, Dongju; Lacadie, Cheryl M; Sinha, Rajita

2016-09-01

Stress triggers impulsive and addictive behaviors, and alcoholism has been frequently associated with increased stress sensitivity and impulse control problems. However, neural correlates underlying the link between alcoholism and impulsivity in the context of stress in patients with alcohol use disorders (AUD) have not been well studied. This study investigated neural correlates and connectivity patterns associated with impulse control difficulties in abstinent AUD patients. Using functional magnetic resonance imaging, brain responses of 37 AUD inpatients, and 37 demographically matched healthy controls were examined during brief individualized imagery trials of stress, alcohol cue, and neutral-relaxing conditions. Stress-related impulsivity was measured using a subscale score of impulse control problems from Difficulties in Emotion Regulation Scale. Impulse control difficulties in AUD patients were significantly associated with hypo-active response to stress in the ventromedial prefrontal cortex (VmPFC), right caudate, and left lateral PFC (LPFC) compared to the neutral condition (p < 0.01, whole-brain corrected). These regions were used as seed regions to further examine the connectivity patterns with other brain regions. With the VmPFC seed, AUD patients showed reduced connectivity with the anterior cingulate cortex compared to controls, which are core regions of emotion regulation, suggesting AUD patients' decreased ability to modulate emotional response under distressed state. With the right caudate seed, patients showed increased connectivity with the right motor cortex, suggesting increased tendency toward habitually driven behaviors. With the left LPFC seed, decreased connectivity with the dorsomedial PFC (DmPFC), but increased connectivity with sensory and motor cortices were found in AUD patients compared to controls (p < 0.05, whole-brain corrected). Reduced connectivity between the left LPFC and DmPFC was further associated with increased stress-induced anxiety in AUD patients (p < 0.05, with adjusted Bonferroni correction). Hypo-active response to stress and altered connectivity in key emotion regulatory regions may account for greater stress-related impulse control problems in alcoholism. Copyright © 2016 by the Research Society on Alcoholism.

Abnormal relationships between the neural response to high- and low-calorie foods and endogenous acylated ghrelin in women with active and weight-recovered anorexia nervosa

PubMed Central

Holsen, Laura M.; Lawson, Elizabeth A.; Christensen, Kara; Klibanski, Anne; Goldstein, Jill M.

2014-01-01

Evidence contributing to the understanding of neurobiological mechanisms underlying appetite dysregulation in anorexia nervosa draws heavily on separate lines of research into neuroendocrine and neural circuitry functioning. In particular, studies consistently cite elevated ghrelin and abnormal activation patterns in homeostatic (hypothalamus) and hedonic (striatum, amygdala, insula) regions governing appetite. The current preliminary study examined the interaction of these systems, based on research demonstrating associations between circulating ghrelin levels and activity in these regions in healthy individuals. In a cross-sectional design, we studied 13 women with active anorexia nervosa (AN), 9 women weight-recovered from AN (AN-WR), and 12 healthy-weight control women using a food cue functional magnetic resonance imaging paradigm, with assessment of fasting levels of acylated ghrelin. Healthy-weight control women exhibited significant positive associations between fasting acylated ghrelin and activity in the right amygdala, hippocampus, insula, and orbitofrontal cortex in response to high-calorie foods, associations which were absent in the AN and AN-WR groups. Women with AN-WR demonstrated a negative relationship between ghrelin and activity in the left hippocampus in response to high-calorie foods, while women with AN showed a positive association between ghrelin and activity in the right orbitofrontal cortex in response to low-calorie foods. Findings suggest a breakdown in the interaction between ghrelin signaling and neural activity in relation to reward responsivity in AN, a phenomenon that may be further characterized using pharmacogenetic studies. PMID:24862390

The race to learn: spike timing and STDP can coordinate learning and recall in CA3.

PubMed

Nolan, Christopher R; Wyeth, Gordon; Milford, Michael; Wiles, Janet

2011-06-01

The CA3 region of the hippocampus has long been proposed as an autoassociative network performing pattern completion on known inputs. The dentate gyrus (DG) region is often proposed as a network performing the complementary function of pattern separation. Neural models of pattern completion and separation generally designate explicit learning phases to encode new information and assume an ideal fixed threshold at which to stop learning new patterns and begin recalling known patterns. Memory systems are significantly more complex in practice, with the degree of memory recall depending on context-specific goals. Here, we present our spike-timing separation and completion (STSC) model of the entorhinal cortex (EC), DG, and CA3 network, ascribing to each region a role similar to that in existing models but adding a temporal dimension by using a spiking neural network. Simulation results demonstrate that (a) spike-timing dependent plasticity in the EC-CA3 synapses provides a pattern completion ability without recurrent CA3 connections, (b) the race between activation of CA3 cells via EC-CA3 synapses and activation of the same cells via DG-CA3 synapses distinguishes novel from known inputs, and (c) modulation of the EC-CA3 synapses adjusts the learned versus test input similarity required to evoke a direct CA3 response prior to any DG activity, thereby adjusting the pattern completion threshold. These mechanisms suggest that spike timing can arbitrate between learning and recall based on the novelty of each individual input, ensuring control of the learn-recall decision resides in the same subsystem as the learned memories themselves. The proposed modulatory signal does not override this decision but biases the system toward either learning or recall. The model provides an explanation for empirical observations that a reduction in novelty produces a corresponding reduction in the latency of responses in CA3 and CA1. Copyright © 2010 Wiley-Liss, Inc.

Where’s the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network

PubMed Central

Hartmann, Christoph; Lazar, Andreea; Nessler, Bernhard; Triesch, Jochen

2015-01-01

Even in the absence of sensory stimulation the brain is spontaneously active. This background “noise” seems to be the dominant cause of the notoriously high trial-to-trial variability of neural recordings. Recent experimental observations have extended our knowledge of trial-to-trial variability and spontaneous activity in several directions: 1. Trial-to-trial variability systematically decreases following the onset of a sensory stimulus or the start of a motor act. 2. Spontaneous activity states in sensory cortex outline the region of evoked sensory responses. 3. Across development, spontaneous activity aligns itself with typical evoked activity patterns. 4. The spontaneous brain activity prior to the presentation of an ambiguous stimulus predicts how the stimulus will be interpreted. At present it is unclear how these observations relate to each other and how they arise in cortical circuits. Here we demonstrate that all of these phenomena can be accounted for by a deterministic self-organizing recurrent neural network model (SORN), which learns a predictive model of its sensory environment. The SORN comprises recurrently coupled populations of excitatory and inhibitory threshold units and learns via a combination of spike-timing dependent plasticity (STDP) and homeostatic plasticity mechanisms. Similar to balanced network architectures, units in the network show irregular activity and variable responses to inputs. Additionally, however, the SORN exhibits sequence learning abilities matching recent findings from visual cortex and the network’s spontaneous activity reproduces the experimental findings mentioned above. Intriguingly, the network’s behaviour is reminiscent of sampling-based probabilistic inference, suggesting that correlates of sampling-based inference can develop from the interaction of STDP and homeostasis in deterministic networks. We conclude that key observations on spontaneous brain activity and the variability of neural responses can be accounted for by a simple deterministic recurrent neural network which learns a predictive model of its sensory environment via a combination of generic neural plasticity mechanisms. PMID:26714277

Neural networks for calibration tomography

NASA Technical Reports Server (NTRS)

Decker, Arthur

1993-01-01

Artificial neural networks are suitable for performing pattern-to-pattern calibrations. These calibrations are potentially useful for facilities operations in aeronautics, the control of optical alignment, and the like. Computed tomography is compared with neural net calibration tomography for estimating density from its x-ray transform. X-ray transforms are measured, for example, in diffuse-illumination, holographic interferometry of fluids. Computed tomography and neural net calibration tomography are shown to have comparable performance for a 10 degree viewing cone and 29 interferograms within that cone. The system of tomography discussed is proposed as a relevant test of neural networks and other parallel processors intended for using flow visualization data.

Influence of contingency awareness on neural, electrodermal and evaluative responses during fear conditioning

PubMed Central

Merz, Christian J.; Klucken, Tim; Schweckendiek, Jan; Vaitl, Dieter; Wolf, Oliver T.; Stark, Rudolf

2011-01-01

In an fMRI study, effects of contingency awareness on conditioned responses were assessed in three groups comprising 118 subjects. A differential fear-conditioning paradigm with visual conditioned stimuli, an electrical unconditioned stimulus and two distractors was applied. The instructed aware group was informed about the contingencies, whereas the distractors prevented contingency detection in the unaware group. The third group (learned aware) was not informed about the contingencies, but learned them despite the distractors. Main effects of contingency awareness on conditioned responses emerged in several brain structures. Post hoc tests revealed differential dorsal anterior cingulate, insula and ventral striatum responses in aware conditioning only, whereas the amygdala was activated independent of contingency awareness. Differential responses of the hippocampus were specifically observed in learned aware subjects, indicating a role in the development of contingency awareness. The orbitofrontal cortex showed varying response patterns: lateral structures showed higher responses in instructed aware than unaware subjects, the opposite was true for medial parts. Conditioned subjective and electrodermal responses emerged only in the two aware groups. These results confirm the independence of conditioned amygdala responses from contingency awareness and indicate specific neural circuits for different aspects of fear acquisition in unaware, learned aware and instructed aware subjects. PMID:20693389

Dissociating maternal responses to sad and happy facial expressions of their own child: An fMRI study.

PubMed

Kluczniok, Dorothea; Hindi Attar, Catherine; Stein, Jenny; Poppinga, Sina; Fydrich, Thomas; Jaite, Charlotte; Kappel, Viola; Brunner, Romuald; Herpertz, Sabine C; Boedeker, Katja; Bermpohl, Felix

2017-01-01

Maternal sensitive behavior depends on recognizing one's own child's affective states. The present study investigated distinct and overlapping neural responses of mothers to sad and happy facial expressions of their own child (in comparison to facial expressions of an unfamiliar child). We used functional MRI to measure dissociable and overlapping activation patterns in 27 healthy mothers in response to happy, neutral and sad facial expressions of their own school-aged child and a gender- and age-matched unfamiliar child. To investigate differential activation to sad compared to happy faces of one's own child, we used interaction contrasts. During the scan, mothers had to indicate the affect of the presented face. After scanning, they were asked to rate the perceived emotional arousal and valence levels for each face using a 7-point Likert-scale (adapted SAM version). While viewing their own child's sad faces, mothers showed activation in the amygdala and anterior cingulate cortex whereas happy facial expressions of the own child elicited activation in the hippocampus. Conjoint activation in response to one's own child happy and sad expressions was found in the insula and the superior temporal gyrus. Maternal brain activations differed depending on the child's affective state. Sad faces of the own child activated areas commonly associated with a threat detection network, whereas happy faces activated reward related brain areas. Overlapping activation was found in empathy related networks. These distinct neural activation patterns might facilitate sensitive maternal behavior.

Empirical modeling for intelligent, real-time manufacture control

NASA Technical Reports Server (NTRS)

Xu, Xiaoshu

1994-01-01

Artificial neural systems (ANS), also known as neural networks, are an attempt to develop computer systems that emulate the neural reasoning behavior of biological neural systems (e.g. the human brain). As such, they are loosely based on biological neural networks. The ANS consists of a series of nodes (neurons) and weighted connections (axons) that, when presented with a specific input pattern, can associate specific output patterns. It is essentially a highly complex, nonlinear, mathematical relationship or transform. These constructs have two significant properties that have proven useful to the authors in signal processing and process modeling: noise tolerance and complex pattern recognition. Specifically, the authors have developed a new network learning algorithm that has resulted in the successful application of ANS's to high speed signal processing and to developing models of highly complex processes. Two of the applications, the Weld Bead Geometry Control System and the Welding Penetration Monitoring System, are discussed in the body of this paper.

An FPGA Implementation of a Polychronous Spiking Neural Network with Delay Adaptation.

PubMed

Wang, Runchun; Cohen, Gregory; Stiefel, Klaus M; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, André

2013-01-01

We present an FPGA implementation of a re-configurable, polychronous spiking neural network with a large capacity for spatial-temporal patterns. The proposed neural network generates delay paths de novo, so that only connections that actually appear in the training patterns will be created. This allows the proposed network to use all the axons (variables) to store information. Spike Timing Dependent Delay Plasticity is used to fine-tune and add dynamics to the network. We use a time multiplexing approach allowing us to achieve 4096 (4k) neurons and up to 1.15 million programmable delay axons on a Virtex 6 FPGA. Test results show that the proposed neural network is capable of successfully recalling more than 95% of all spikes for 96% of the stored patterns. The tests also show that the neural network is robust to noise from random input spikes.

Heuristic pattern correction scheme using adaptively trained generalized regression neural networks.

PubMed

Hoya, T; Chambers, J A

2001-01-01

In many pattern classification problems, an intelligent neural system is required which can learn the newly encountered but misclassified patterns incrementally, while keeping a good classification performance over the past patterns stored in the network. In the paper, an heuristic pattern correction scheme is proposed using adaptively trained generalized regression neural networks (GRNNs). The scheme is based upon both network growing and dual-stage shrinking mechanisms. In the network growing phase, a subset of the misclassified patterns in each incoming data set is iteratively added into the network until all the patterns in the incoming data set are classified correctly. Then, the redundancy in the growing phase is removed in the dual-stage network shrinking. Both long- and short-term memory models are considered in the network shrinking, which are motivated from biological study of the brain. The learning capability of the proposed scheme is investigated through extensive simulation studies.

Long-Term Memory Stabilized by Noise-Induced Rehearsal

PubMed Central

Wei, Yi

2014-01-01

Cortical networks can maintain memories for decades despite the short lifetime of synaptic strengths. Can a neural network store long-lasting memories in unstable synapses? Here, we study the effects of ongoing spike-timing-dependent plasticity (STDP) on the stability of memory patterns stored in synapses of an attractor neural network. We show that certain classes of STDP rules can stabilize all stored memory patterns despite a short lifetime of synapses. In our model, unstructured neural noise, after passing through the recurrent network connections, carries the imprint of all memory patterns in temporal correlations. STDP, combined with these correlations, leads to reinforcement of all stored patterns, even those that are never explicitly visited. Our findings may provide the functional reason for irregular spiking displayed by cortical neurons and justify models of system memory consolidation. Therefore, we propose that irregular neural activity is the feature that helps cortical networks maintain stable connections. PMID:25411507

Neural Responses to Electrical Stimulation on Patterned Silk Films

PubMed Central

Hronik-Tupaj, Marie; Raja, Waseem Khan; Tang-Schomer, Min; Omenetto, Fiorenzo G.; Kaplan, David L.

2013-01-01

Peripheral nerve injury is a critical issue for trauma patients. Following injury, incomplete axon regeneration or misguided axon innervation into tissue will result in loss of sensory and motor functions. The objective of this study was to examine axon outgrowth and axon alignment in response to surface patterning and electrical stimulation. To accomplish our objective, metal electrodes with dimensions of 1.5 mm × 4 cm, were sputter coated onto micropatterned silk protein films, with surface grooves 3.5 μm wide × 500 nm deep. P19 neurons were seeded on the patterned electronic silk films and stimulated at 120 mV, 1 kHz, for 45 minutes each day for 7 days. Responses were compared to neurons on flat electronic silk films, patterned silk films without stimulation, and flat silk films without stimulation. Significant alignment was found on the patterned film groups compared to the flat film groups. Axon outgrowth was greater (p < 0.05) on electronic films on day 5 and day 7 compared to the unstimulated groups. In conclusion, electrical stimulation, at 120 mV, 1 kHz, for 45 minutes daily, in addition to surface patterning, of 3.5 μm wide × 500 nm deep grooves, offered control of nerve axon outgrowth and alignment. PMID:23401351

Whole-brain activity maps reveal stereotyped, distributed networks for visuomotor behavior.

PubMed

Portugues, Ruben; Feierstein, Claudia E; Engert, Florian; Orger, Michael B

2014-03-19

Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate but ordered pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments systematically reveal the functional architecture of neural circuits underlying a sensorimotor behavior in a vertebrate brain. Copyright © 2014 Elsevier Inc. All rights reserved.

Whole-brain activity maps reveal stereotyped, distributed networks for visuomotor behavior

PubMed Central

Portugues, Ruben; Feierstein, Claudia E.; Engert, Florian; Orger, Michael B.

2014-01-01

Summary Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate, but ordered, pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments reveal, for the first time in a vertebrate, the comprehensive functional architecture of the neural circuits underlying a sensorimotor behavior. PMID:24656252

The neural basis of episodic memory: evidence from functional neuroimaging.

PubMed Central

Rugg, Michael D; Otten, Leun J; Henson, Richard N A

2002-01-01

We review some of our recent research using functional neuroimaging to investigate neural activity supporting the encoding and retrieval of episodic memories, that is, memories for unique events. Findings from studies of encoding indicate that, at the cortical level, the regions responsible for the effective encoding of a stimulus event as an episodic memory include some of the regions that are also engaged to process the event 'online'. Thus, it appears that there is no single cortical site or circuit responsible for episodic encoding. The results of retrieval studies indicate that successful recollection of episodic information is associated with activation of lateral parietal cortex, along with more variable patterns of activity in dorsolateral and anterior prefrontal cortex. Whereas parietal regions may play a part in the representation of retrieved information, prefrontal areas appear to support processes that act on the products of retrieval to align behaviour with the demands of the retrieval task. PMID:12217177

Persistent neuronal activity in human prefrontal cortex links perception and action

PubMed Central

Haller, Matar; Case, John; Crone, Nathan E.; Chang, Edward F.; King-Stephens, David; Laxer, Kenneth D.; Weber, Peter B.; Parvizi, Josef; Knight, Robert T.; Shestyuk, Avgusta Y.

2017-01-01

How do humans flexibly respond to changing environmental demands on a sub-second temporal scale? Extensive research has highlighted the key role of the prefrontal cortex in flexible decision-making and adaptive behavior, yet the core mechanisms that translate sensory information into behavior remain undefined. Utilizing direct human cortical recordings, we investigated the temporal and spatial evolution of neuronal activity, indexed by the broadband gamma signal, while sixteen participants performed a broad range of self-paced cognitive tasks. Here we describe a robust domain- and modality-independent pattern of persistent stimulus-to-response neural activation that encodes stimulus features and predicts motor output on a trial-by-trial basis with near-perfect accuracy. Observed across a distributed network of brain areas, this persistent neural activation is centered in the prefrontal cortex and is required for successful response implementation, providing a functional substrate for domain-general transformation of perception into action, critical for flexible behavior.

Towards biological plausibility of electronic noses: A spiking neural network based approach for tea odour classification.

PubMed

Sarkar, Sankho Turjo; Bhondekar, Amol P; Macaš, Martin; Kumar, Ritesh; Kaur, Rishemjit; Sharma, Anupma; Gulati, Ashu; Kumar, Amod

2015-11-01

The paper presents a novel encoding scheme for neuronal code generation for odour recognition using an electronic nose (EN). This scheme is based on channel encoding using multiple Gaussian receptive fields superimposed over the temporal EN responses. The encoded data is further applied to a spiking neural network (SNN) for pattern classification. Two forms of SNN, a back-propagation based SpikeProp and a dynamic evolving SNN are used to learn the encoded responses. The effects of information encoding on the performance of SNNs have been investigated. Statistical tests have been performed to determine the contribution of the SNN and the encoding scheme to overall odour discrimination. The approach has been implemented in odour classification of orthodox black tea (Kangra-Himachal Pradesh Region) thereby demonstrating a biomimetic approach for EN data analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition.

PubMed

Wang, Runchun; Thakur, Chetan Singh; Cohen, Gregory; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, Andre

2017-06-01

We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs nonlinear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time-multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing high-speed, neuromorphic, and massively parallel pattern recognition and classification tasks.

A New Local Bipolar Autoassociative Memory Based on External Inputs of Discrete Recurrent Neural Networks With Time Delay.

PubMed

Zhou, Caigen; Zeng, Xiaoqin; Luo, Chaomin; Zhang, Huaguang

In this paper, local bipolar auto-associative memories are presented based on discrete recurrent neural networks with a class of gain type activation function. The weight parameters of neural networks are acquired by a set of inequalities without the learning procedure. The global exponential stability criteria are established to ensure the accuracy of the restored patterns by considering time delays and external inputs. The proposed methodology is capable of effectively overcoming spurious memory patterns and achieving memory capacity. The effectiveness, robustness, and fault-tolerant capability are validated by simulated experiments.In this paper, local bipolar auto-associative memories are presented based on discrete recurrent neural networks with a class of gain type activation function. The weight parameters of neural networks are acquired by a set of inequalities without the learning procedure. The global exponential stability criteria are established to ensure the accuracy of the restored patterns by considering time delays and external inputs. The proposed methodology is capable of effectively overcoming spurious memory patterns and achieving memory capacity. The effectiveness, robustness, and fault-tolerant capability are validated by simulated experiments.

Towards multifocal ultrasonic neural stimulation: pattern generation algorithms

NASA Astrophysics Data System (ADS)

Hertzberg, Yoni; Naor, Omer; Volovick, Alexander; Shoham, Shy

2010-10-01

Focused ultrasound (FUS) waves directed onto neural structures have been shown to dynamically modulate neural activity and excitability, opening up a range of possible systems and applications where the non-invasiveness, safety, mm-range resolution and other characteristics of FUS are advantageous. As in other neuro-stimulation and modulation modalities, the highly distributed and parallel nature of neural systems and neural information processing call for the development of appropriately patterned stimulation strategies which could simultaneously address multiple sites in flexible patterns. Here, we study the generation of sparse multi-focal ultrasonic distributions using phase-only modulation in ultrasonic phased arrays. We analyse the relative performance of an existing algorithm for generating multifocal ultrasonic distributions and new algorithms that we adapt from the field of optical digital holography, and find that generally the weighted Gerchberg-Saxton algorithm leads to overall superior efficiency and uniformity in the focal spots, without significantly increasing the computational burden. By combining phased-array FUS and magnetic-resonance thermometry we experimentally demonstrate the simultaneous generation of tightly focused multifocal distributions in a tissue phantom, a first step towards patterned FUS neuro-modulation systems and devices.

Squids in the Study of Cerebral Magnetic Field

NASA Astrophysics Data System (ADS)

Romani, G. L.; Narici, L.

The following sections are included: * INTRODUCTION * HISTORICAL OVERVIEW * NEUROMAGNETIC FIELDS AND AMBIENT NOISE * DETECTORS * Room temperature sensors * SQUIDs * DETECTION COILS * Magnetometers * Gradiometers * Balancing * Planar gradiometers * Choice of the gradiometer parameters * MODELING * Current pattern due to neural excitations * Action potentials and postsynaptic currents * The current dipole model * Neural population and detected fields * Spherically bounded medium * SPATIAL CONFIGURATION OF THE SENSORS * SOURCE LOCALIZATION * Localization procedure * Experimental accuracy and reproducibility * SIGNAL PROCESSING * Analog Filtering * Bandpass filters * Line rejection filters * DATA ANALYSIS * Analysis of evoked/event-related responses * Simple average * Selected average * Recursive techniques * Similarity analysis * Analysis of spontaneous activity * Mapping and localization * EXAMPLES OF NEUROMAGNETIC STUDIES * Neuromagnetic measurements * Studies on the normal brain * Clinical applications * Epilepsy * Tinnitus * CONCLUSIONS * ACKNOWLEDGEMENTS * REFERENCES

Emotion identification and aging: Behavioral and neural age-related changes.

PubMed

Gonçalves, Ana R; Fernandes, Carina; Pasion, Rita; Ferreira-Santos, Fernando; Barbosa, Fernando; Marques-Teixeira, João

2018-05-01

Aging is known to alter the processing of facial expressions of emotion (FEE), however the impact of this alteration is less clear. Additionally, there is little information about the temporal dynamics of the neural processing of facial affect. We examined behavioral and neural age-related changes in the identification of FEE using event-related potentials. Furthermore, we analyze the relationship between behavioral/neural responses and neuropsychological functioning. To this purpose, 30 younger adults, 29 middle-aged adults and 26 older adults identified FEE. The behavioral results showed a similar performance between groups. The neural results showed no significant differences between groups for the P100 component and an increased N170 amplitude in the older group. Furthermore, a pattern of asymmetric activation was evident in the N170 component. Results also suggest deficits in facial feature decoding abilities, reflected by a reduced N250 amplitude in older adults. Neuropsychological functioning predicts P100 modulation, but does not seem to influence emotion identification ability. The findings suggest the existence of a compensatory function that would explain the age-equivalent performance in emotion identification. The study may help future research addressing behavioral and neural processes involved on processing of FEE in neurodegenerative conditions. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Race modulates neural activity during imitation

PubMed Central

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

Spatiotemporal dynamics of similarity-based neural representations of facial identity

PubMed Central

Vida, Mark D.; Nestor, Adrian; Plaut, David C.; Behrmann, Marlene

2017-01-01

Humans’ remarkable ability to quickly and accurately discriminate among thousands of highly similar complex objects demands rapid and precise neural computations. To elucidate the process by which this is achieved, we used magnetoencephalography to measure spatiotemporal patterns of neural activity with high temporal resolution during visual discrimination among a large and carefully controlled set of faces. We also compared these neural data to lower level “image-based” and higher level “identity-based” model-based representations of our stimuli and to behavioral similarity judgments of our stimuli. Between ∼50 and 400 ms after stimulus onset, face-selective sources in right lateral occipital cortex and right fusiform gyrus and sources in a control region (left V1) yielded successful classification of facial identity. In all regions, early responses were more similar to the image-based representation than to the identity-based representation. In the face-selective regions only, responses were more similar to the identity-based representation at several time points after 200 ms. Behavioral responses were more similar to the identity-based representation than to the image-based representation, and their structure was predicted by responses in the face-selective regions. These results provide a temporally precise description of the transformation from low- to high-level representations of facial identity in human face-selective cortex and demonstrate that face-selective cortical regions represent multiple distinct types of information about face identity at different times over the first 500 ms after stimulus onset. These results have important implications for understanding the rapid emergence of fine-grained, high-level representations of object identity, a computation essential to human visual expertise. PMID:28028220

Risky decisions and their consequences: neural processing by boys with Antisocial Substance Disorder.

PubMed

Crowley, Thomas J; Dalwani, Manish S; Mikulich-Gilbertson, Susan K; Du, Yiping P; Lejuez, Carl W; Raymond, Kristen M; Banich, Marie T

2010-09-22

Adolescents with conduct and substance problems ("Antisocial Substance Disorder" (ASD)) repeatedly engage in risky antisocial and drug-using behaviors. We hypothesized that, during processing of risky decisions and resulting rewards and punishments, brain activation would differ between abstinent ASD boys and comparison boys. We compared 20 abstinent adolescent male patients in treatment for ASD with 20 community controls, examining rapid event-related blood-oxygen-level-dependent (BOLD) responses during functional magnetic resonance imaging. In 90 decision trials participants chose to make either a cautious response that earned one cent, or a risky response that would either gain 5 cents or lose 10 cents; odds of losing increased as the game progressed. We also examined those times when subjects experienced wins, or separately losses, from their risky choices. We contrasted decision trials against very similar comparison trials requiring no decisions, using whole-brain BOLD-response analyses of group differences, corrected for multiple comparisons. During decision-making ASD boys showed hypoactivation in numerous brain regions robustly activated by controls, including orbitofrontal and dorsolateral prefrontal cortices, anterior cingulate, basal ganglia, insula, amygdala, hippocampus, and cerebellum. While experiencing wins, ASD boys had significantly less activity than controls in anterior cingulate, temporal regions, and cerebellum, with more activity nowhere. During losses ASD boys had significantly more activity than controls in orbitofrontal cortex, dorsolateral prefrontal cortex, brain stem, and cerebellum, with less activity nowhere. Adolescent boys with ASD had extensive neural hypoactivity during risky decision-making, coupled with decreased activity during reward and increased activity during loss. These neural patterns may underlie the dangerous, excessive, sustained risk-taking of such boys. The findings suggest that the dysphoria, reward insensitivity, and suppressed neural activity observed among older addicted persons also characterize youths early in the development of substance use disorders.

Organization of Anti-Phase Synchronization Pattern in Neural Networks: What are the Key Factors?

PubMed Central

Li, Dong; Zhou, Changsong

2011-01-01

Anti-phase oscillation has been widely observed in cortical neural network. Elucidating the mechanism underlying the organization of anti-phase pattern is of significance for better understanding more complicated pattern formations in brain networks. In dynamical systems theory, the organization of anti-phase oscillation pattern has usually been considered to relate to time delay in coupling. This is consistent to conduction delays in real neural networks in the brain due to finite propagation velocity of action potentials. However, other structural factors in cortical neural network, such as modular organization (connection density) and the coupling types (excitatory or inhibitory), could also play an important role. In this work, we investigate the anti-phase oscillation pattern organized on a two-module network of either neuronal cell model or neural mass model, and analyze the impact of the conduction delay times, the connection densities, and coupling types. Our results show that delay times and coupling types can play key roles in this organization. The connection densities may have an influence on the stability if an anti-phase pattern exists due to the other factors. Furthermore, we show that anti-phase synchronization of slow oscillations can be achieved with small delay times if there is interaction between slow and fast oscillations. These results are significant for further understanding more realistic spatiotemporal dynamics of cortico-cortical communications. PMID:22232576

Single-unit activity during natural vision: diversity, consistency, and spatial sensitivity among AF face patch neurons.

PubMed

McMahon, David B T; Russ, Brian E; Elnaiem, Heba D; Kurnikova, Anastasia I; Leopold, David A

2015-04-08

Several visual areas within the STS of the macaque brain respond strongly to faces and other biological stimuli. Determining the principles that govern neural responses in this region has proven challenging, due in part to the inherently complex stimulus domain of dynamic biological stimuli that are not captured by an easily parameterized stimulus set. Here we investigated neural responses in one fMRI-defined face patch in the anterior fundus (AF) of the STS while macaques freely view complex videos rich with natural social content. Longitudinal single-unit recordings allowed for the accumulation of each neuron's responses to repeated video presentations across sessions. We found that individual neurons, while diverse in their response patterns, were consistently and deterministically driven by the video content. We used principal component analysis to compute a family of eigenneurons, which summarized 24% of the shared population activity in the first two components. We found that the most prominent component of AF activity reflected an interaction between visible body region and scene layout. Close-up shots of faces elicited the strongest neural responses, whereas far away shots of faces or close-up shots of hindquarters elicited weak or inhibitory responses. Sensitivity to the apparent proximity of faces was also observed in gamma band local field potential. This category-selective sensitivity to spatial scale, together with the known exchange of anatomical projections of this area with regions involved in visuospatial analysis, suggests that the AF face patch may be specialized in aspects of face perception that pertain to the layout of a social scene.

Women with borderline personality disorder do not show altered BOLD responses during response inhibition.

PubMed

van Eijk, Julia; Sebastian, Alexandra; Krause-Utz, Annegret; Cackowski, Sylvia; Demirakca, Traute; Biedermann, Sarah V; Lieb, Klaus; Bohus, Martin; Schmahl, Christian; Ende, Gabriele; Tüscher, Oliver

2015-12-30

Impulsivity is central to borderline personality disorder (BPD). Response inhibition, addressing the ability to suppress or stop actions, is one aspect of behavioral impulse control which is frequently used to assess impulsivity. BPD patients display deficits in response inhibition under stress condition or negative emotions. We assessed whether response inhibition and its neural underpinnings are impaired in BPD when tested in an emotionally neutral setting and when co-morbid attention-deficit/hyperactivity disorder (ADHD) is excluded. To this end, we studied response inhibition in unmedicated BPD patients and healthy controls (HC) in two independent samples using functional magnetic resonance imaging during Simon-, Go/nogo-, and Stopsignal tasks. BPD patients and HC did not differ significantly in their performance in the Go/nogo and the Stopsignal tasks. Response interference in the Simon task was increased in BPD patients in one sample, but this could not be replicated in the second sample. In both samples, no significant differences in brain activation patterns during any of the tasks were present while the neural impulse control network was robustly activated during the inhibition tasks in both groups. Our results provide evidence that under emotionally neutral conditions response inhibition is not impaired in patients with BPD without co-occurring ADHD. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

COMMUNICATION Designing a somatosensory neural prosthesis: percepts evoked by different patterns of thalamic stimulation

NASA Astrophysics Data System (ADS)

Heming, Ethan; Sanden, Andrew; Kiss, Zelma H. T.

2010-12-01

Although major advances have been made in the development of motor prostheses, fine motor control requires intuitive somatosensory feedback. Here we explored whether a thalamic site for a somatosensory neural prosthetic could provide natural somatic sensation to humans. Different patterns of electrical stimulation (obtained from thalamic spike trains) were applied in patients undergoing deep brain stimulation surgery. Changes in pattern produced different sensations, while preserving somatotopic representation. While most percepts were reported as 'unnatural', some stimulations produced more 'natural' sensations than others. However, the additional patterns did not elicit more 'natural' percepts than high-frequency (333 Hz) electrical stimulation. These features suggest that despite some limitations, the thalamus may be a feasible site for a somatosensory neural prosthesis and different stimulation patterns may be useful in its development.

Sex differences in autism: a resting-state fMRI investigation of functional brain connectivity in males and females

PubMed Central

Swinnen, Stephan P.; Wenderoth, Nicole

2016-01-01

Autism spectrum disorders (ASD) are far more prevalent in males than in females. Little is known however about the differential neural expression of ASD in males and females. We used a resting-state fMRI-dataset comprising 42 males/42 females with ASD and 75 male/75 female typical-controls to examine whether autism-related alterations in intrinsic functional connectivity are similar or different in males and females, and particularly whether alterations reflect ‘neural masculinization’, as predicted by the Extreme Male Brain theory. Males and females showed a differential neural expression of ASD, characterized by highly consistent patterns of hypo-connectivity in males with ASD (compared to typical males), and hyper-connectivity in females with ASD (compared to typical females). Interestingly, patterns of hyper-connectivity in females with ASD reflected a shift towards the (high) connectivity levels seen in typical males (neural masculinization), whereas patterns of hypo-connectivity observed in males with ASD reflected a shift towards the (low) typical feminine connectivity patterns (neural feminization). Our data support the notion that ASD is a disorder of sexual differentiation rather than a disorder characterized by masculinization in both genders. Future work is needed to identify underlying factors such as sex hormonal alterations that drive these sex-specific neural expressions of ASD. PMID:26989195

Hippocampal CA1 local field potential oscillations induced by olfactory cue of liked food.

PubMed

Samerphob, Nifareeda; Cheaha, Dania; Chatpun, Surapong; Kumarnsit, Ekkasit

2017-07-01

Eating motivation is induced not only by negative energy balance but also food related cues. However, neural processing for acquisition of learned food preference remains to be established. This study aimed to identify hippocampal neural signaling in response to olfactory cue (chocolate scent) after completion of repetitive chocolate sessions. Male Swiss albino mice implanted with intracranial electrode into the hippocampus were used for local field potential (LFP) recording. Animals were given chocolate sessions (a piece of 2g chocolate per each mouse to eat on day 1, 3, 5 and 7). Hippocampal CA1 LFP signals and exploratory behavior of animals receiving chocolate scent were analyzed before and after chocolate sessions. The experiment was performed in a place preference-like apparatus with the zones of normal food pellet and chocolate (both kept in a small perforated cup for smell dispersion) at the opposite ends. Following chocolate sessions, time spent in a chocolate zone and CA1 LFP patterns were analyzed in comparison to control levels. Two-way ANOVA revealed significant increase in time spent seeking for chocolate. Frequency analysis of LFP power spectra revealed significant increases in delta and theta powers. Phase-amplitude analysis showed significant increase in maximal modulation index and decrease in frequency for phase of theta-high gamma coupling. Taken together, neural signaling in the hippocampus was sensitive to chocolate olfactory cue that might underlie learning process in response to repeated chocolate consumptions that primed intense food approaching behavior. Ultimately, these LFP patterns might reflect motivation to eat and predict feeding probability. Copyright © 2017 Elsevier Inc. All rights reserved.

Behavioral characteristics and neural mechanisms mediating performance in a rodent version of the Balloon Analog Risk Task.

PubMed

Jentsch, James David; Woods, Jason A; Groman, Stephanie M; Seu, Emanuele

2010-07-01

The tendency for some individuals to partake in high-risk behaviors (eg, substance abuse, gambling, risky sexual activities) is a matter of great public health concern, yet the characteristics and neural bases of this vulnerability are largely unknown. Recent work shows that this susceptibility can be partially predicted by laboratory measures of reward seeking under risk, including the Balloon Analog Risk Task. Rats were trained to respond on two levers: one of which (the 'add lever') increased the size of a potential food reward and a second (the 'cash-out lever') that led to delivery of accrued reward. Crucially, each add-lever response was also associated with a risk that the trial would fail and no reward would be delivered. The relative probabilities that each add-lever press would lead to an addition food pellet or to trial failure (risk) were orthogonally varied. Rats exhibited a pattern of responding characteristic of incentive motivation and risk aversion, with a subset of rats showing traits of high-risk taking and/or suboptimal responding. Neural inactivation studies suggest that the orbitofrontal cortex supports greater reward seeking in the presence or absence of risk, whereas the medial prefrontal cortex is required for optimization of patterns of responding. These findings provide new information about the neural circuitry of decision making under risk and reveal new insights into the biological determinants of risk-taking behaviors that may be useful in developing biomarkers of vulnerability.

Neural learning rules for the vestibulo-ocular reflex

NASA Technical Reports Server (NTRS)

Raymond, J. L.; Lisberger, S. G.

1998-01-01

Mechanisms for the induction of motor learning in the vestibulo-ocular reflex (VOR) were evaluated by recording the patterns of neural activity elicited in the cerebellum by a range of stimuli that induce learning. Patterns of climbing-fiber, vestibular, and Purkinje cell simple-spike signals were examined during sinusoidal head movement paired with visual image movement at stimulus frequencies from 0.5 to 10 Hz. A comparison of simple-spike and vestibular signals contained the information required to guide learning only at low stimulus frequencies, and a comparison of climbing-fiber and simple-spike signals contained the information required to guide learning only at high stimulus frequencies. Learning could be guided by comparison of climbing-fiber and vestibular signals at all stimulus frequencies tested, but only if climbing fiber responses were compared with the vestibular signals present 100 msec earlier. Computational analysis demonstrated that this conclusion is valid even if there is a broad range of vestibular signals at the site of plasticity. Simulations also indicated that the comparison of vestibular and climbing-fiber signals across the 100 msec delay must be implemented by a subcellular "eligibility" trace rather than by neural circuits that delay the vestibular inputs to the site of plasticity. The results suggest two alternative accounts of learning in the VOR. Either there are multiple mechanisms of learning that use different combinations of neural signals to drive plasticity, or there is a single mechanism tuned to climbing-fiber activity that follows activity in vestibular pathways by approximately 100 msec.

AmphiPax3/7, an amphioxus paired box gene: insights into chordate myogenesis, neurogenesis, and the possible evolutionary precursor of definitive vertebrate neural crest.

PubMed

Holland, L Z; Schubert, M; Kozmik, Z; Holland, N D

1999-01-01

Amphioxus probably has only a single gene (AmphiPax3/7) in the Pax3/7 subfamily. Like its vertebrate homologs (Pax3 and Pax7), amphioxus AmphiPax3/7 is probably involved in specifying the axial musculature and muscularized notochord. During nervous system development, AmphiPax3/7 is first expressed in bilateral anteroposterior stripes along the edges of the neural plate. This early neural expression may be comparable to the transcription of Pax3 and Pax7 in some of the anterior neural crest cells of vertebrates. Previous studies by others and ourselves have demonstrated that several genes homologous to genetic markers for vertebrate neural crest are expressed along the neural plate-epidermis boundary in embryos of tunicates and amphioxus. Taken together, the early neural expression patterns of AmphiPax3/7 and other neural crest markers of amphioxus and tunicates suggest that cell populations that eventually gave rise to definitive vertebrate neural crest may have been present in ancestral invertebrate chordates. During later neurogenesis in amphioxus, AmphiPax3/7, like its vertebrate homologs, is expressed dorsally and dorsolaterally in the neural tube and may be involved in dorsoventral patterning. However, unlike its vertebrate homologs, AmphiPax3/7 is expressed only at the anterior end of the central nervous system instead of along much of the neuraxis; this amphioxus pattern may represent the loss of a primitive chordate character.

Oscillator Neural Network Retrieving Sparsely Coded Phase Patterns

NASA Astrophysics Data System (ADS)

Aoyagi, Toshio; Nomura, Masaki

1999-08-01

Little is known theoretically about the associative memory capabilities of neural networks in which information is encoded not only in the mean firing rate but also in the timing of firings. Particularly, in the case of sparsely coded patterns, it is biologically important to consider the timings of firings and to study how such consideration influences storage capacities and quality of recalled patterns. For this purpose, we propose a simple extended model of oscillator neural networks to allow for expression of a nonfiring state. Analyzing both equilibrium states and dynamical properties in recalling processes, we find that the system possesses good associative memory.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals.

PubMed

Zhuang, Ning; Zeng, Ying; Yang, Kai; Zhang, Chi; Tong, Li; Yan, Bin

2018-03-12

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals

PubMed Central

Zeng, Ying; Yang, Kai; Tong, Li; Yan, Bin

2018-01-01

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods. PMID:29534515

Motor cortex embeds muscle-like commands in an untangled population response

PubMed Central

Russo, Abigail A.; Bittner, Sean R.; Perkins, Sean M.; Seely, Jeffrey S.; London, Brian M.; Lara, Antonio H.; Miri, Andrew; Marshall, Najja J.; Kohn, Adam; Jessell, Thomas M.; Abbott, Laurence F.; Cunningham, John P.; Churchland, Mark M.

2018-01-01

Summary Primate motor cortex projects to spinal interneurons and motor neurons, suggesting that motor cortex activity may be dominated by muscle-like commands. Extensive observations during reaching lend support to this view, but evidence remains ambiguous and much-debated. To provide a different perspective, we employed a novel behavioral paradigm that affords extensive comparison between time-evolving neural and muscle activity. We found that single motor cortex neurons displayed many muscle-like properties, but the structure of population activity was not muscle-like. Unlike muscle activity, neural activity was structured to avoid ‘tangling’: moments where similar activity patterns led to dissimilar future patterns. Avoidance of tangling was present across tasks and species. Network models revealed a potential reason for this consistent feature: low tangling confers noise robustness. Finally, we were able to predict motor cortex activity from muscle activity alone, by leveraging the hypothesis that muscle-like commands are embedded in additional structure that yields low tangling. PMID:29398358

Outcome dependency alters the neural substrates of impression formation

PubMed Central

Ames, Daniel L.; Fiske, Susan T.

2015-01-01

How do people maintain consistent impressions of other people when other people are often inconsistent? The present research addresses this question by combining recent neuroscientific insights with ecologically meaningful behavioral methods. Participants formed impressions of real people whom they met in a personally involving situation. fMRI and supporting behavioral data revealed that outcome dependency (i.e., depending on another person for a desired outcome) alters previously identified neural dynamics of impression formation. Consistent with past research, a functional localizer identified a region of dorsomedial PFC previously linked to social impression formation. In the main task, this ROI revealed the predicted patterns of activity across outcome dependency conditions: greater BOLD response when information confirmed (vs. violated) social expectations if participants were outcome-independent and the reverse pattern if participants were outcome-dependent. We suggest that, although social perceivers often discount expectancy-disconfirming information as noise, being dependent on another person for a desired outcome focuses impression-formation processing on the most diagnostic information, rather than on the most tractable information. PMID:23850465

Rotation-invariant neural pattern recognition system with application to coin recognition.

PubMed

Fukumi, M; Omatu, S; Takeda, F; Kosaka, T

1992-01-01

In pattern recognition, it is often necessary to deal with problems to classify a transformed pattern. A neural pattern recognition system which is insensitive to rotation of input pattern by various degrees is proposed. The system consists of a fixed invariance network with many slabs and a trainable multilayered network. The system was used in a rotation-invariant coin recognition problem to distinguish between a 500 yen coin and a 500 won coin. The results show that the approach works well for variable rotation pattern recognition.

Neural coding in graphs of bidirectional associative memories.

PubMed

Bouchain, A David; Palm, Günther

2012-01-24

In the last years we have developed large neural network models for the realization of complex cognitive tasks in a neural network architecture that resembles the network of the cerebral cortex. We have used networks of several cortical modules that contain two populations of neurons (one excitatory, one inhibitory). The excitatory populations in these so-called "cortical networks" are organized as a graph of Bidirectional Associative Memories (BAMs), where edges of the graph correspond to BAMs connecting two neural modules and nodes of the graph correspond to excitatory populations with associative feedback connections (and inhibitory interneurons). The neural code in each of these modules consists essentially of the firing pattern of the excitatory population, where mainly it is the subset of active neurons that codes the contents to be represented. The overall activity can be used to distinguish different properties of the patterns that are represented which we need to distinguish and control when performing complex tasks like language understanding with these cortical networks. The most important pattern properties or situations are: exactly fitting or matching input, incomplete information or partially matching pattern, superposition of several patterns, conflicting information, and new information that is to be learned. We show simple simulations of these situations in one area or module and discuss how to distinguish these situations based on the overall internal activation of the module. This article is part of a Special Issue entitled "Neural Coding". Copyright © 2011 Elsevier B.V. All rights reserved.

fMRI activation patterns in an analytic reasoning task: consistency with EEG source localization

NASA Astrophysics Data System (ADS)

Li, Bian; Vasanta, Kalyana C.; O'Boyle, Michael; Baker, Mary C.; Nutter, Brian; Mitra, Sunanda

2010-03-01

Functional magnetic resonance imaging (fMRI) is used to model brain activation patterns associated with various perceptual and cognitive processes as reflected by the hemodynamic (BOLD) response. While many sensory and motor tasks are associated with relatively simple activation patterns in localized regions, higher-order cognitive tasks may produce activity in many different brain areas involving complex neural circuitry. We applied a recently proposed probabilistic independent component analysis technique (PICA) to determine the true dimensionality of the fMRI data and used EEG localization to identify the common activated patterns (mapped as Brodmann areas) associated with a complex cognitive task like analytic reasoning. Our preliminary study suggests that a hybrid GLM/PICA analysis may reveal additional regions of activation (beyond simple GLM) that are consistent with electroencephalography (EEG) source localization patterns.

Higher-order neural network software for distortion invariant object recognition

NASA Technical Reports Server (NTRS)

Reid, Max B.; Spirkovska, Lilly

1991-01-01

The state-of-the-art in pattern recognition for such applications as automatic target recognition and industrial robotic vision relies on digital image processing. We present a higher-order neural network model and software which performs the complete feature extraction-pattern classification paradigm required for automatic pattern recognition. Using a third-order neural network, we demonstrate complete, 100 percent accurate invariance to distortions of scale, position, and in-plate rotation. In a higher-order neural network, feature extraction is built into the network, and does not have to be learned. Only the relatively simple classification step must be learned. This is key to achieving very rapid training. The training set is much smaller than with standard neural network software because the higher-order network only has to be shown one view of each object to be learned, not every possible view. The software and graphical user interface run on any Sun workstation. Results of the use of the neural software in autonomous robotic vision systems are presented. Such a system could have extensive application in robotic manufacturing.

Neural responses to social threat and predictors of cognitive behavioral therapy and acceptance and commitment therapy in social anxiety disorder.

PubMed

Burklund, Lisa J; Torre, Jared B; Lieberman, Matthew D; Taylor, Shelley E; Craske, Michelle G

2017-03-30

Previous research has often highlighted hyperactivity in emotion regions to simple, static social threat cues in social anxiety disorder (SAD). Investigation of the neurobiology of SAD using more naturalistic paradigms can further reveal underlying mechanisms and how these relate to clinical outcomes. We used fMRI to investigate responses to novel dynamic rejection stimuli in individuals with SAD (N=70) and healthy controls (HC; N=17), and whether these responses predicted treatment outcomes following cognitive behavioral therapy (CBT) or acceptance and commitment therapy (ACT). Both HC and SAD groups reported greater distress to rejection compared to neutral social stimuli. At the neural level, HCs exhibited greater activations in social pain/rejection regions, including dorsal anterior cingulate cortex and anterior insula, to rejection stimuli. The SAD group evidenced a different pattern, with no differences in these rejection regions and relatively greater activations in the amygdala and other regions to neutral stimuli. Greater responses in anterior cingulate cortex and the amygdala to rejection vs. neutral stimuli predicted better CBT outcomes. In contrast, enhanced activity in sensory-focused posterior insula predicted ACT responses. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Flow Pattern Identification of Horizontal Two-Phase Refrigerant Flow Using Neural Networks

DTIC Science & Technology

2015-12-31

AFRL-RQ-WP-TP-2016-0079 FLOW PATTERN IDENTIFICATION OF HORIZONTAL TWO-PHASE REFRIGERANT FLOW USING NEURAL NETWORKS (POSTPRINT) Abdeel J...Journal Article Postprint 01 October 2013 – 22 June 2015 4. TITLE AND SUBTITLE FLOW PATTERN IDENTIFICATION OF HORIZONTAL TWO-PHASE REFRIGERANT FLOW USING...networks were used to automatically identify two-phase flow patterns for refrigerant R-134a flowing in a horizontal tube. In laboratory experiments

Neural network-based system for pattern recognition through a fiber optic bundle

NASA Astrophysics Data System (ADS)

Gamo-Aranda, Javier; Rodriguez-Horche, Paloma; Merchan-Palacios, Miguel; Rosales-Herrera, Pablo; Rodriguez, M.

2001-04-01

A neural network based system to identify images transmitted through a Coherent Fiber-optic Bundle (CFB) is presented. Patterns are generated in a computer, displayed on a Spatial Light Modulator, imaged onto the input face of the CFB, and recovered optically by a CCD sensor array for further processing. Input and output optical subsystems were designed and used to that end. The recognition step of the transmitted patterns is made by a powerful, widely-used, neural network simulator running on the control PC. A complete PC-based interface was developed to control the different tasks involved in the system. An optical analysis of the system capabilities was carried out prior to performing the recognition step. Several neural network topologies were tested, and the corresponding numerical results are also presented and discussed.

Perception of social synchrony induces mother–child gamma coupling in the social brain

PubMed Central

Levy, Jonathan; Goldstein, Abraham

2017-01-01

Abstract The recent call to move from focus on one brain’s functioning to two-brain communication initiated a search for mechanisms that enable two humans to coordinate brain response during social interactions. Here, we utilized the mother–child context as a developmentally salient setting to study two-brain coupling. Mothers and their 9-year-old children were videotaped at home in positive and conflictual interactions. Positive interactions were microcoded for social synchrony and conflicts for overall dialogical style. Following, mother and child underwent magnetoencephalography while observing the positive vignettes. Episodes of behavioral synchrony, compared to non-synchrony, increased gamma-band power in the superior temporal sulcus (STS), hub of social cognition, mirroring and mentalizing. This neural pattern was coupled between mother and child. Brain-to-brain coordination was anchored in behavioral synchrony; only during episodes of behavioral synchrony, but not during non-synchronous moments, mother’s and child's STS gamma power was coupled. Importantly, neural synchrony was not found during observation of unfamiliar mother-child interaction Maternal empathic/dialogical conflict style predicted mothers’ STS activations whereas child withdrawal predicted attenuated STS response in both partners. Results define a novel neural marker for brain-to-brain synchrony, highlight the role of rapid bottom-up oscillatory mechanisms for neural coupling and indicate that behavior-based processes may drive synchrony between two brains during social interactions. PMID:28402479

Do resting brain dynamics predict oddball evoked-potential?

PubMed Central

2011-01-01

Background The oddball paradigm is widely applied to the investigation of cognitive function in neuroscience and in neuropsychiatry. Whether cortical oscillation in the resting state can predict the elicited oddball event-related potential (ERP) is still not clear. This study explored the relationship between resting electroencephalography (EEG) and oddball ERPs. The regional powers of 18 electrodes across delta, theta, alpha and beta frequencies were correlated with the amplitude and latency of N1, P2, N2 and P3 components of oddball ERPs. A multivariate analysis based on partial least squares (PLS) was applied to further examine the spatial pattern revealed by multiple correlations. Results Higher synchronization in the resting state, especially at the alpha spectrum, is associated with higher neural responsiveness and faster neural propagation, as indicated by the higher amplitude change of N1/N2 and shorter latency of P2. None of the resting quantitative EEG indices predict P3 latency and amplitude. The PLS analysis confirms that the resting cortical dynamics which explains N1/N2 amplitude and P2 latency does not show regional specificity, indicating a global property of the brain. Conclusions This study differs from previous approaches by relating dynamics in the resting state to neural responsiveness in the activation state. Our analyses suggest that the neural characteristics carried by resting brain dynamics modulate the earlier/automatic stage of target detection. PMID:22114868

Perception of social synchrony induces mother-child gamma coupling in the social brain.

PubMed

Levy, Jonathan; Goldstein, Abraham; Feldman, Ruth

2017-07-01

The recent call to move from focus on one brain's functioning to two-brain communication initiated a search for mechanisms that enable two humans to coordinate brain response during social interactions. Here, we utilized the mother-child context as a developmentally salient setting to study two-brain coupling. Mothers and their 9-year-old children were videotaped at home in positive and conflictual interactions. Positive interactions were microcoded for social synchrony and conflicts for overall dialogical style. Following, mother and child underwent magnetoencephalography while observing the positive vignettes. Episodes of behavioral synchrony, compared to non-synchrony, increased gamma-band power in the superior temporal sulcus (STS), hub of social cognition, mirroring and mentalizing. This neural pattern was coupled between mother and child. Brain-to-brain coordination was anchored in behavioral synchrony; only during episodes of behavioral synchrony, but not during non-synchronous moments, mother's and child's STS gamma power was coupled. Importantly, neural synchrony was not found during observation of unfamiliar mother-child interaction Maternal empathic/dialogical conflict style predicted mothers' STS activations whereas child withdrawal predicted attenuated STS response in both partners. Results define a novel neural marker for brain-to-brain synchrony, highlight the role of rapid bottom-up oscillatory mechanisms for neural coupling and indicate that behavior-based processes may drive synchrony between two brains during social interactions. © The Author (2017). Published by Oxford University Press.

Fractionating the neural correlates of individual working memory components underlying arithmetic problem solving skills in children.

PubMed

Metcalfe, Arron W S; Ashkenazi, Sarit; Rosenberg-Lee, Miriam; Menon, Vinod

2013-10-01

Baddeley and Hitch's multi-component working memory (WM) model has played an enduring and influential role in our understanding of cognitive abilities. Very little is known, however, about the neural basis of this multi-component WM model and the differential role each component plays in mediating arithmetic problem solving abilities in children. Here, we investigate the neural basis of the central executive (CE), phonological (PL) and visuo-spatial (VS) components of WM during a demanding mental arithmetic task in 7-9 year old children (N=74). The VS component was the strongest predictor of math ability in children and was associated with increased arithmetic complexity-related responses in left dorsolateral and right ventrolateral prefrontal cortices as well as bilateral intra-parietal sulcus and supramarginal gyrus in posterior parietal cortex. Critically, VS, CE and PL abilities were associated with largely distinct patterns of brain response. Overlap between VS and CE components was observed in left supramarginal gyrus and no overlap was observed between VS and PL components. Our findings point to a central role of visuo-spatial WM during arithmetic problem-solving in young grade-school children and highlight the usefulness of the multi-component Baddeley and Hitch WM model in fractionating the neural correlates of arithmetic problem solving during development. Copyright © 2013 Elsevier Ltd. All rights reserved.

Intranasal oxytocin modulates neural functional connectivity during human social interaction.

PubMed

Rilling, James K; Chen, Xiangchuan; Chen, Xu; Haroon, Ebrahim

2018-02-10

Oxytocin (OT) modulates social behavior in primates and many other vertebrate species. Studies in non-primate animals have demonstrated that, in addition to influencing activity within individual brain areas, OT influences functional connectivity across networks of areas involved in social behavior. Previously, we used fMRI to image brain function in human subjects during a dyadic social interaction task following administration of either intranasal oxytocin (INOT) or placebo, and analyzed the data with a standard general linear model. Here, we conduct an extensive re-analysis of these data to explore how OT modulates functional connectivity across a neural network that animal studies implicate in social behavior. OT induced widespread increases in functional connectivity in response to positive social interactions among men and widespread decreases in functional connectivity in response to negative social interactions among women. Nucleus basalis of Meynert, an important regulator of selective attention and motivation with a particularly high density of OT receptors, had the largest number of OT-modulated connections. Regions known to receive mesolimbic dopamine projections such as the nucleus accumbens and lateral septum were also hubs for OT effects on functional connectivity. Our results suggest that the neural mechanism by which OT influences primate social cognition may include changes in patterns of activity across neural networks that regulate social behavior in other animals. © 2018 Wiley Periodicals, Inc.

Neural mechanisms underlying cognitive control of men with lifelong antisocial behavior.

PubMed

Schiffer, Boris; Pawliczek, Christina; Mu Ller, Bernhard; Forsting, Michael; Gizewski, Elke; Leygraf, Norbert; Hodgins, Sheilagh

2014-04-30

Results of meta-analyses suggested subtle deficits in cognitive control among antisocial individuals. Because almost all studies focused on children with conduct problems or adult psychopaths, however, little is known about cognitive control mechanisms among the majority of persistent violent offenders who present an antisocial personality disorder (ASPD). The present study aimed to determine whether offenders with ASPD, relative to non-offenders, display dysfunction in the neural mechanisms underlying cognitive control and to assess the extent to which these dysfunctions are associated with psychopathic traits and trait impulsivity. Participants comprised 21 violent offenders and 23 non-offenders who underwent event-related functional magnetic resonance imaging while performing a non-verbal Stroop task. The offenders, relative to the non-offenders, exhibited reduced response time interference and a different pattern of conflict- and error-related activity in brain areas involved in cognitive control, attention, language, and emotion processing, that is, the anterior cingulate, dorsolateral prefrontal, superior temporal and postcentral cortices, putamen, thalamus, and amygdala. Moreover, between-group differences in behavioural and neural responses revealed associations with core features of psychopathy and attentional impulsivity. Thus, the results of the present study confirmed the hypothesis that offenders with ASPD display alterations in the neural mechanisms underlying cognitive control and that those alterations relate, at least in part, to personality characteristics. Copyright © 2014. Published by Elsevier Ireland Ltd.

Individual Differences in Risk Preference Predict Neural Responses during Financial Decision-Making

PubMed Central

Engelmann, Jan B.; Tamir, Diana

2009-01-01

We investigated the neural correlates of subjective valuations during a task involving risky choices about lotteries. Because expected value was held constant across all lotteries, decisions were influenced by subjective preferences, which manifest behaviorally as risk-seeking or risk-averse attitudes. To isolate structures encoding risk preference during choice, we probed for areas showing increased activation as a function of selected risk-level. Such response patterns were obtained in anterior (ACC) and posterior cingulate cortex (PCC), superior frontal gyrus, caudate nucleus, and substantia nigra. Behavioral results revealed the presence of risk-averse and risk-neutral individuals. In parallel, brain signals revealed modulation of activity by risk-attitude during choice. Correlations between risk-seeking attitudes and neural activity during risky choice were obtained in superior and inferior frontal gyri, medial and lateral orbitofrontal cortex, and parahippocampal gyrus, while correlations with risk-averse attitudes were found in the caudate. The dynamics of neural responses relevant to each stage of the task (decision, anticipation, outcome) were investigated via timeseries and conjunction analyses. Though the networks engaged in each of the task stages were mostly distinct, regions of ACC, PCC and caudate were consistently activated during each decision-making phase. These results demonstrate (1) that subjective assessments of risk, as well as individual attitudes toward risk, play a significant role in modulating activity within brain regions recruited during decision-making, and (2) that ACC, PCC and caudate are relevant during each phase of a decision-making task requiring subjective valuations, strengthening the role of these regions in self-referential subjective valuations during choice. PMID:19576868

Firing patterns transition and desynchronization induced by time delay in neural networks

NASA Astrophysics Data System (ADS)

Huang, Shoufang; Zhang, Jiqian; Wang, Maosheng; Hu, Chin-Kun

2018-06-01

We used the Hindmarsh-Rose (HR) model (Hindmarsh and Rose, 1984) to study the effect of time delay on the transition of firing behaviors and desynchronization in neural networks. As time delay is increased, neural networks exhibit diversity of firing behaviors, including regular spiking or bursting and firing patterns transitions (FPTs). Meanwhile, the desynchronization of firing and unstable bursting with decreasing amplitude in neural system, are also increasingly enhanced with the increase of time delay. Furthermore, we also studied the effect of coupling strength and network randomness on these phenomena. Our results imply that time delays can induce transition and desynchronization of firing behaviors in neural networks. These findings provide new insight into the role of time delay in the firing activities of neural networks, and can help to better understand the firing phenomena in complex systems of neural networks. A possible mechanism in brain that can cause the increase of time delay is discussed.

Neural basis of hierarchical visual form processing of Japanese Kanji characters.

PubMed

Higuchi, Hiroki; Moriguchi, Yoshiya; Murakami, Hiroki; Katsunuma, Ruri; Mishima, Kazuo; Uno, Akira

2015-12-01

We investigated the neural processing of reading Japanese Kanji characters, which involves unique hierarchical visual processing, including the recognition of visual components specific to Kanji, such as "radicals." We performed functional MRI to measure brain activity in response to hierarchical visual stimuli containing (1) real Kanji characters (complete structure with semantic information), (2) pseudo Kanji characters (subcomponents without complete character structure), (3) artificial characters (character fragments), and (4) checkerboard (simple photic stimuli). As we expected, the peaks of the activation in response to different stimulus types were aligned within the left occipitotemporal visual region along the posterior-anterior axis in order of the structural complexity of the stimuli, from fragments (3) to complete characters (1). Moreover, only the real Kanji characters produced functional connectivity between the left inferotemporal area and the language area (left inferior frontal triangularis), while pseudo Kanji characters induced connectivity between the left inferotemporal area and the bilateral cerebellum and left putamen. Visual processing of Japanese Kanji takes place in the left occipitotemporal cortex, with a clear hierarchy within the region such that the neural activation differentiates the elements in Kanji characters' fragments, subcomponents, and semantics, with different patterns of connectivity to remote regions among the elements.

Neural mechanisms of single corrective steps evoked in the standing rabbit

PubMed Central

Hsu, L.-J.; Zelenin, P. V.; Lyalka, V. F.; Vemula, M. G.; Orlovsky, G. N.; Deliagina, T. G.

2017-01-01

Single steps in different directions are often used for postural corrections. However, our knowledge about the neural mechanisms underlying their generation is scarce. This study was aimed to characterize the corrective steps generated in response to disturbances of the basic body configuration caused by forward, backward or outward displacement of the hindlimb, as well as to reveal location in the CNS of the corrective step generating mechanisms. Video recording of the motor response to translation of the supporting surface under the hindlimb along with contact forces and activity of back and limb muscles was performed in freely standing intact and in fixed postmammillary rabbits. In intact rabbits, displacement of the hindlimb in any direction caused a lateral trunk movement towards the contralateral hindlimb, and then a corrective step in the direction opposite to the initial displacement. The time difference between onsets of these two events varied considerably. The EMG pattern in the supporting hindlimb was similar for all directions of corrective steps. It caused the increase in the limb stiffness. EMG pattern in the stepping limb differed in steps with different directions. In postmammillary rabbits the corrective stepping movements, as well as EMG patterns in both stepping and standing hindlimbs were similar to those observed in intact rabbits. This study demonstrates that the corrective trunk and limb movements are generated by separate mechanisms activated by sensory signals from the deviated limb. The neuronal networks generating postural corrective steps reside in the brainstem, cerebellum, and spinal cord. PMID:28215990

Distinct dynamical patterns that distinguish willed and forced actions.

PubMed

Garcia Dominguez, Luis; Kostelecki, Wojciech; Wennberg, Richard; Perez Velazquez, Jose L

2011-03-01

The neural pathways for generating willed actions have been increasingly investigated since the famous pioneering work by Benjamin Libet on the nature of free will. To better understand what differentiates the brain states underlying willed and forced behaviours, we performed a study of chosen and forced actions over a binary choice scenario. Magnetoencephalography recordings were obtained from six subjects during a simple task in which the subject presses a button with the left or right finger in response to a cue that either (1) specifies the finger with which the button should be pressed or (2) instructs the subject to press a button with a finger of their own choosing. Three independent analyses were performed to investigate the dynamical patterns of neural activity supporting willed and forced behaviours during the preparatory period preceding a button press. Each analysis offered similar findings in the temporal and spatial domains and in particular, a high accuracy in the classification of single trials was obtained around 200 ms after cue presentation with an overall average of 82%. During this period, the majority of the discriminatory power comes from differential neural processes observed bilaterally in the parietal lobes, as well as some differences in occipital and temporal lobes, suggesting a contribution of these regions to willed and forced behaviours.

Pattern Adaptation and Normalization Reweighting.

PubMed

Westrick, Zachary M; Heeger, David J; Landy, Michael S

2016-09-21

Adaptation to an oriented stimulus changes both the gain and preferred orientation of neural responses in V1. Neurons tuned near the adapted orientation are suppressed, and their preferred orientations shift away from the adapter. We propose a model in which weights of divisive normalization are dynamically adjusted to homeostatically maintain response products between pairs of neurons. We demonstrate that this adjustment can be performed by a very simple learning rule. Simulations of this model closely match existing data from visual adaptation experiments. We consider several alternative models, including variants based on homeostatic maintenance of response correlations or covariance, as well as feedforward gain-control models with multiple layers, and we demonstrate that homeostatic maintenance of response products provides the best account of the physiological data. Adaptation is a phenomenon throughout the nervous system in which neural tuning properties change in response to changes in environmental statistics. We developed a model of adaptation that combines normalization (in which a neuron's gain is reduced by the summed responses of its neighbors) and Hebbian learning (in which synaptic strength, in this case divisive normalization, is increased by correlated firing). The model is shown to account for several properties of adaptation in primary visual cortex in response to changes in the statistics of contour orientation. Copyright © 2016 the authors 0270-6474/16/369805-12$15.00/0.

Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network.

PubMed

Zafar, Raheel; Kamel, Nidal; Naufal, Mohamad; Malik, Aamir Saeed; Dass, Sarat C; Ahmad, Rana Fayyaz; Abdullah, Jafri M; Reza, Faruque

2017-01-01

Decoding of human brain activity has always been a primary goal in neuroscience especially with functional magnetic resonance imaging (fMRI) data. In recent years, Convolutional neural network (CNN) has become a popular method for the extraction of features due to its higher accuracy, however it needs a lot of computation and training data. In this study, an algorithm is developed using Multivariate pattern analysis (MVPA) and modified CNN to decode the behavior of brain for different images with limited data set. Selection of significant features is an important part of fMRI data analysis, since it reduces the computational burden and improves the prediction performance; significant features are selected using t-test. MVPA uses machine learning algorithms to classify different brain states and helps in prediction during the task. General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. The proposed method showed better overall accuracy (68.6%) compared to ROI (61.88%) and estimation values (64.17%).

Inattentional Deafness: Visual Load Leads to Time-Specific Suppression of Auditory Evoked Responses

PubMed Central

Molloy, Katharine; Griffiths, Timothy D.; Lavie, Nilli

2015-01-01

Due to capacity limits on perception, conditions of high perceptual load lead to reduced processing of unattended stimuli (Lavie et al., 2014). Accumulating work demonstrates the effects of visual perceptual load on visual cortex responses, but the effects on auditory processing remain poorly understood. Here we establish the neural mechanisms underlying “inattentional deafness”—the failure to perceive auditory stimuli under high visual perceptual load. Participants performed a visual search task of low (target dissimilar to nontarget items) or high (target similar to nontarget items) load. On a random subset (50%) of trials, irrelevant tones were presented concurrently with the visual stimuli. Brain activity was recorded with magnetoencephalography, and time-locked responses to the visual search array and to the incidental presence of unattended tones were assessed. High, compared to low, perceptual load led to increased early visual evoked responses (within 100 ms from onset). This was accompanied by reduced early (∼100 ms from tone onset) auditory evoked activity in superior temporal sulcus and posterior middle temporal gyrus. A later suppression of the P3 “awareness” response to the tones was also observed under high load. A behavioral experiment revealed reduced tone detection sensitivity under high visual load, indicating that the reduction in neural responses was indeed associated with reduced awareness of the sounds. These findings support a neural account of shared audiovisual resources, which, when depleted under load, leads to failures of sensory perception and awareness. SIGNIFICANCE STATEMENT The present work clarifies the neural underpinning of inattentional deafness under high visual load. The findings of near-simultaneous load effects on both visual and auditory evoked responses suggest shared audiovisual processing capacity. Temporary depletion of shared capacity in perceptually demanding visual tasks leads to a momentary reduction in sensory processing of auditory stimuli, resulting in inattentional deafness. The dynamic “push–pull” pattern of load effects on visual and auditory processing furthers our understanding of both the neural mechanisms of attention and of cross-modal effects across visual and auditory processing. These results also offer an explanation for many previous failures to find cross-modal effects in experiments where the visual load effects may not have coincided directly with auditory sensory processing. PMID:26658858

Inhibition-Induced Forgetting Results from Resource Competition between Response Inhibition and Memory Encoding Processes.

PubMed

Chiu, Yu-Chin; Egner, Tobias

2015-08-26

Response inhibition is a key component of executive control, but its relation to other cognitive processes is not well understood. We recently documented the "inhibition-induced forgetting effect": no-go cues are remembered more poorly than go cues. We attributed this effect to central-resource competition, whereby response inhibition saps attention away from memory encoding. However, this proposal is difficult to test with behavioral means alone. We therefore used fMRI in humans to test two neural predictions of the "common resource hypothesis": (1) brain regions associated with response inhibition should exhibit greater resource demands during encoding of subsequently forgotten than remembered no-go cues; and (2) this higher inhibitory resource demand should lead to memory encoding regions having less resources available during encoding of subsequently forgotten no-go cues. Participants categorized face stimuli by gender in a go/no-go task and, following a delay, performed a surprise recognition memory test for those faces. Replicating previous findings, memory was worse for no-go than for go stimuli. Crucially, forgetting of no-go cues was predicted by high inhibitory resource demand, as quantified by the trial-by-trial ratio of activity in neural "no-go" versus "go" networks. Moreover, this index of inhibitory demand exhibited an inverse trial-by-trial relationship with activity in brain regions responsible for the encoding of no-go cues into memory, notably the ventrolateral prefrontal cortex. This seesaw pattern between the neural resource demand of response inhibition and activity related to memory encoding directly supports the hypothesis that response inhibition temporarily saps attentional resources away from stimulus processing. Recent behavioral experiments showed that inhibiting a motor response to a stimulus (a "no-go cue") impairs subsequent memory for that cue. Here, we used fMRI to test whether this "inhibition-induced forgetting effect" is caused by competition for neural resources between the processes of response inhibition and memory encoding. We found that trial-by-trial variations in neural inhibitory resource demand predicted subsequent forgetting of no-go cues and that higher inhibitory demand was furthermore associated with lower concurrent activation in brain regions responsible for successful memory encoding of no-go cues. Thus, motor inhibition and stimulus encoding appear to compete with each other: when more resources have to be devoted to inhibiting action, less are available for encoding sensory stimuli. Copyright © 2015 the authors 0270-6474/15/3511936-10$15.00/0.

Neural circuit activity in freely behaving zebrafish (Danio rerio).

PubMed

Issa, Fadi A; O'Brien, Georgeann; Kettunen, Petronella; Sagasti, Alvaro; Glanzman, David L; Papazian, Diane M

2011-03-15

Examining neuronal network activity in freely behaving animals is advantageous for probing the function of the vertebrate central nervous system. Here, we describe a simple, robust technique for monitoring the activity of neural circuits in unfettered, freely behaving zebrafish (Danio rerio). Zebrafish respond to unexpected tactile stimuli with short- or long-latency escape behaviors, which are mediated by distinct neural circuits. Using dipole electrodes immersed in the aquarium, we measured electric field potentials generated in muscle during short- and long-latency escapes. We found that activation of the underlying neural circuits produced unique field potential signatures that are easily recognized and can be repeatedly monitored. In conjunction with behavioral analysis, we used this technique to track changes in the pattern of circuit activation during the first week of development in animals whose trigeminal sensory neurons were unilaterally ablated. One day post-ablation, the frequency of short- and long-latency responses was significantly lower on the ablated side than on the intact side. Three days post-ablation, a significant fraction of escapes evoked by stimuli on the ablated side was improperly executed, with the animal turning towards rather than away from the stimulus. However, the overall response rate remained low. Seven days post-ablation, the frequency of escapes increased dramatically and the percentage of improperly executed escapes declined. Our results demonstrate that trigeminal ablation results in rapid reconfiguration of the escape circuitry, with reinnervation by new sensory neurons and adaptive changes in behavior. This technique is valuable for probing the activity, development, plasticity and regeneration of neural circuits under natural conditions.

Neural circuit activity in freely behaving zebrafish (Danio rerio)

PubMed Central

Issa, Fadi A.; O'Brien, Georgeann; Kettunen, Petronella; Sagasti, Alvaro; Glanzman, David L.; Papazian, Diane M.

2011-01-01

Examining neuronal network activity in freely behaving animals is advantageous for probing the function of the vertebrate central nervous system. Here, we describe a simple, robust technique for monitoring the activity of neural circuits in unfettered, freely behaving zebrafish (Danio rerio). Zebrafish respond to unexpected tactile stimuli with short- or long-latency escape behaviors, which are mediated by distinct neural circuits. Using dipole electrodes immersed in the aquarium, we measured electric field potentials generated in muscle during short- and long-latency escapes. We found that activation of the underlying neural circuits produced unique field potential signatures that are easily recognized and can be repeatedly monitored. In conjunction with behavioral analysis, we used this technique to track changes in the pattern of circuit activation during the first week of development in animals whose trigeminal sensory neurons were unilaterally ablated. One day post-ablation, the frequency of short- and long-latency responses was significantly lower on the ablated side than on the intact side. Three days post-ablation, a significant fraction of escapes evoked by stimuli on the ablated side was improperly executed, with the animal turning towards rather than away from the stimulus. However, the overall response rate remained low. Seven days post-ablation, the frequency of escapes increased dramatically and the percentage of improperly executed escapes declined. Our results demonstrate that trigeminal ablation results in rapid reconfiguration of the escape circuitry, with reinnervation by new sensory neurons and adaptive changes in behavior. This technique is valuable for probing the activity, development, plasticity and regeneration of neural circuits under natural conditions. PMID:21346131

Native language shapes automatic neural processing of speech.

PubMed

Intartaglia, Bastien; White-Schwoch, Travis; Meunier, Christine; Roman, Stéphane; Kraus, Nina; Schön, Daniele

2016-08-01

The development of the phoneme inventory is driven by the acoustic-phonetic properties of one's native language. Neural representation of speech is known to be shaped by language experience, as indexed by cortical responses, and recent studies suggest that subcortical processing also exhibits this attunement to native language. However, most work to date has focused on the differences between tonal and non-tonal languages that use pitch variations to convey phonemic categories. The aim of this cross-language study is to determine whether subcortical encoding of speech sounds is sensitive to language experience by comparing native speakers of two non-tonal languages (French and English). We hypothesized that neural representations would be more robust and fine-grained for speech sounds that belong to the native phonemic inventory of the listener, and especially for the dimensions that are phonetically relevant to the listener such as high frequency components. We recorded neural responses of American English and French native speakers, listening to natural syllables of both languages. Results showed that, independently of the stimulus, American participants exhibited greater neural representation of the fundamental frequency compared to French participants, consistent with the importance of the fundamental frequency to convey stress patterns in English. Furthermore, participants showed more robust encoding and more precise spectral representations of the first formant when listening to the syllable of their native language as compared to non-native language. These results align with the hypothesis that language experience shapes sensory processing of speech and that this plasticity occurs as a function of what is meaningful to a listener. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dynamics of Learning in Cultured Neuronal Networks with Antagonists of Glutamate Receptors

PubMed Central

Li, Yanling; Zhou, Wei; Li, Xiangning; Zeng, Shaoqun; Luo, Qingming

2007-01-01

Cognitive dysfunction may result from abnormality of ionotropic glutamate receptors. Although various forms of synaptic plasticity in learning that rely on altering of glutamate receptors have been considered, the evidence is insufficient from an informatics view. Dynamics could reflect neuroinformatics encoding, including temporal pattern encoding, spatial pattern encoding, and energy distribution. Discovering informatics encoding is fundamental and crucial to understanding the working principle of the neural system. In this article, we analyzed the dynamic characteristics of response activities during learning training in cultured hippocampal networks under normal and abnormal conditions of ionotropic glutamate receptors, respectively. The rate, which is one of the temporal configurations, was decreased markedly by inhibition of α-amino-3-hydroxy-5-methylisoxazole-4-proprionic acid (AMPA) receptors. Moreover, the energy distribution in different characteristic frequencies was changed markedly by inhibition of AMPA receptors. Spatial configurations, including regularization, correlation, and synchrony, were changed significantly by inhibition of N-methyl-d-aspartate receptors. These results suggest that temporal pattern encoding and energy distribution of response activities in cultured hippocampal neuronal networks during learning training are modulated by AMPA receptors, whereas spatial pattern encoding of response activities is modulated by N-methyl-d-aspartate receptors. PMID:17766359

Searching for patterns in remote sensing image databases using neural networks

NASA Technical Reports Server (NTRS)

Paola, Justin D.; Schowengerdt, Robert A.

1995-01-01

We have investigated a method, based on a successful neural network multispectral image classification system, of searching for single patterns in remote sensing databases. While defining the pattern to search for and the feature to be used for that search (spectral, spatial, temporal, etc.) is challenging, a more difficult task is selecting competing patterns to train against the desired pattern. Schemes for competing pattern selection, including random selection and human interpreted selection, are discussed in the context of an example detection of dense urban areas in Landsat Thematic Mapper imagery. When applying the search to multiple images, a simple normalization method can alleviate the problem of inconsistent image calibration. Another potential problem, that of highly compressed data, was found to have a minimal effect on the ability to detect the desired pattern. The neural network algorithm has been implemented using the PVM (Parallel Virtual Machine) library and nearly-optimal speedups have been obtained that help alleviate the long process of searching through imagery.

Compact holographic optical neural network system for real-time pattern recognition

NASA Astrophysics Data System (ADS)

Lu, Taiwei; Mintzer, David T.; Kostrzewski, Andrew A.; Lin, Freddie S.

1996-08-01

One of the important characteristics of artificial neural networks is their capability for massive interconnection and parallel processing. Recently, specialized electronic neural network processors and VLSI neural chips have been introduced in the commercial market. The number of parallel channels they can handle is limited because of the limited parallel interconnections that can be implemented with 1D electronic wires. High-resolution pattern recognition problems can require a large number of neurons for parallel processing of an image. This paper describes a holographic optical neural network (HONN) that is based on high- resolution volume holographic materials and is capable of performing massive 3D parallel interconnection of tens of thousands of neurons. A HONN with more than 16,000 neurons packaged in an attache case has been developed. Rotation- shift-scale-invariant pattern recognition operations have been demonstrated with this system. System parameters such as the signal-to-noise ratio, dynamic range, and processing speed are discussed.

Asymmetric Correlation between Experienced Parental Attachment and Event-Related Potentials Evoked in Response to Parental Faces

PubMed Central

Dai, Junqiang; Zhai, Hongchang; Zhou, Anbang; Gong, Yongyuan; Luo, Lin

2013-01-01

This study aims to explore the modulation effects of attachment relationships with parents on the neural correlates that are associated with parental faces. The event-related potentials elicited in 31 college students while viewing facial stimuli of their parents in two single oddball paradigms (father vs. unfamiliar male and mother vs. unfamiliar female) were measured. We found that enhanced P3a and P3b and attenuated N2b were elicited by parental faces; however, the N170 component failed to discriminate parental faces from unfamiliar faces. An experienced attachment relationship with the father was positively correlated to the P3a response associated with the father’s face, whereas no correlation was found in the case of mothers. Further exploration in dipole source localization showed that, within the time window of the P300, distinctive brain regions were involved in the processing of parental faces; the father’s face was located in the medial frontal gyrus, which might be involved in self effect, and the anterior cingulate gyrus was activated in response to the mother’s face. This research is the first to demonstrate that neural mechanisms involved with parents can be modulated differentially by the qualities of the attachments to the parents. In addition, parental faces share a highly similar temporal pattern, but the origins of these neural responses are distinct, which could merit further investigation. PMID:23844240