Inferring single neuron properties in conductance based balanced networks.

abstract：:The study of sensory signaling in the visual cortex has been greatly advanced by the recording of neural activity simultaneously with the performance of a specific psychophysical task. Individual nerve cells may also increase their firing leading up to the particular choice or decision made on a single psychophysical ...

journal_title：Frontiers in computational neuroscience

authors： Parker AJ

更新日期：2013-08-13 00:00:00

abstract：:Common computational principles underlie processing of various visual features in the cortex. They are considered to create similar patterns of contextual modulations in behavioral studies for different features as orientation and direction of motion. Here, I studied the possibility that a single theoretical framework...

journal_title：Frontiers in computational neuroscience

authors： Tzvetanov T

更新日期：2012-05-22 00:00:00

abstract：:Pitch is a perceptual correlate of periodicity. Sounds with distinct spectra can elicit the same pitch. Despite the importance of pitch perception, understanding the cellular mechanism of pitch perception is still a major challenge and a mechanistic model of pitch is lacking. A multi-stage neuronal network model is de...

journal_title：Frontiers in computational neuroscience

authors： Huang C,Rinzel J

更新日期：2016-06-16 00:00:00

abstract：:Motor system uses muscle synergies as a modular organization to simplify the control of movements. Motor cortical impairments, such as stroke and spinal cord injuries, disrupt the orchestration of the muscle synergies and result in abnormal movements. In this paper, the alterations of muscle synergies in subacute stro...

journal_title：Frontiers in computational neuroscience

authors： Pan B,Sun Y,Xie B,Huang Z,Wu J,Hou J,Liu Y,Huang Z,Zhang Z

更新日期：2018-08-21 00:00:00

abstract：:Background: Convolution neural networks (CNN) is increasingly used in computer science and finds more and more applications in different fields. However, analyzing brain network with CNN is not trivial, due to the non-Euclidean characteristics of brain network built by graph theory. Method: To address this problem, we...

journal_title：Frontiers in computational neuroscience

authors： Meng L,Xiang J

更新日期：2018-12-10 00:00:00

abstract：:Often we need to perform tasks in an environment that changes stochastically. In these situations it is important to learn the statistics of sequences of events in order to predict the future and the outcome of our actions. The statistical description of many of these sequences can be reduced to the set of probabiliti...

journal_title：Frontiers in computational neuroscience

authors： Ostojic S,Fusi S

更新日期：2013-04-12 00:00:00

abstract：:This study proposes a computational model for attentional blink or "blink of the mind," a phenomenon where a human subject misses perception of a later expected visual pattern as two expected visual patterns are presented less than 500 ms apart. A neocortical patch modeled as an attractor network is stimulated with a ...

journal_title：Frontiers in computational neuroscience

authors： Silverstein DN,Lansner A

更新日期：2011-05-03 00:00:00

abstract：:Conscious awareness plays a major role in human cognition and adaptive behavior, though its function in multisensory integration is not yet fully understood, hence, questions remain: How does the brain integrate the incoming multisensory signals with respect to different external environments? How are the roles of the...

journal_title：Frontiers in computational neuroscience

authors： Adeel A

更新日期：2020-05-19 00:00:00

abstract：:We address a question on the effect of common stochastic inputs on the correlation of the spike trains of two neurons when they are coupled through direct connections. We show that the change in the correlation of small amplitude stochastic inputs can be better detected when the neurons are connected by direct excitat...

journal_title：Frontiers in computational neuroscience

authors： Bolhasani E,Azizi Y,Valizadeh A

更新日期：2013-08-14 00:00:00

abstract：:Behavioral studies have shown spatial working memory impairment with aging in several animal species, including humans. Persistent activity of layer 3 pyramidal dorsolateral prefrontal cortex (dlPFC) neurons during delay periods of working memory tasks is important for encoding memory of the stimulus. In vitro studies...

journal_title：Frontiers in computational neuroscience

authors： Ibañez S,Luebke JI,Chang W,Draguljić D,Weaver CM

更新日期：2020-01-17 00:00:00

abstract：:The cerebellum is known to play a critical role in learning relevant patterns of activity for adaptive motor control, but the underlying network mechanisms are only partly understood. The classical long-term synaptic plasticity between parallel fibers (PFs) and Purkinje cells (PCs), which is driven by the inferior oli...

journal_title：Frontiers in computational neuroscience

authors： Luque NR,Garrido JA,Carrillo RR,D'Angelo E,Ros E

更新日期：2014-08-15 00:00:00

abstract：:Two important stimulus features represented within the rodent barrel cortex are velocity and angular direction of whisker deflection. Each cortical barrel receives information from thalamocortical (TC) cells that relay information from a single whisker, and TC input is decoded by barrel regular-spiking (RS) cells thro...

journal_title：Frontiers in computational neuroscience

authors： Patel MJ

更新日期：2018-06-12 00:00:00

abstract：:Proprioceptive afferents from muscle spindles encode information about peripheral joint movements for the central nervous system (CNS). The sensitivity of muscle spindle is nonlinearly dependent on the activation of gamma (γ) motoneurons in the spinal cord that receives inputs from the motor cortex. How fusimotor cont...

journal_title：Frontiers in computational neuroscience

authors： Lan N,He X

更新日期：2012-08-30 00:00:00

abstract：:The process of conditioning via reward learning is highly relevant to the study of food choice and obesity. Learning is itself shaped by environmental exposure, with the potential for such exposures to vary substantially across individuals and across place and time. In this paper, we use computational techniques to ex...

journal_title：Frontiers in computational neuroscience

authors： Hammond RA,Ornstein JT,Fellows LK,Dubé L,Levitan R,Dagher A

更新日期：2012-10-11 00:00:00

abstract：:Persistent activity observed during delayed-response tasks for spatial working memory (Funahashi et al., 1989) has commonly been modeled by recurrent networks whose dynamics is described as a bump attractor (Compte et al., 2000). We examine the effects of interareal architecture on the dynamics of bump attractors in s...

journal_title：Frontiers in computational neuroscience

authors： Kilpatrick ZP

更新日期：2013-07-01 00:00:00

abstract：:What are the functional neuroimaging measurements required for more fully characterizing the events and locations of neocortical activity? A prime assumption has been that modulation of cortical activity will inevitably be reflected in changes in energy utilization (for the most part) changes of glucose and oxygen con...

journal_title：Frontiers in computational neuroscience

authors： Robinson SE,Mandell AJ,Coppola R

更新日期：2013-01-24 00:00:00

abstract：:Calcium concentrations as well as time courses have been used to model the signaling cascades leading to changes in the strength of synaptic connections. Previous models consider the dendritic spines as uniform compartments regarding calcium signaling. However, calcium concentrations can vary drastically on distances ...

journal_title：Frontiers in computational neuroscience

authors： Mihalas S

更新日期：2011-01-13 00:00:00

abstract：:Many brain regions communicate information through synchronized network activity. Electrical coupling among the dendrites of interneurons in the cortex has been implicated in forming and sustaining such activity in the cortex. Evidence for the existence of electrical coupling among cortical pyramidal cells, however, h...

journal_title：Frontiers in computational neuroscience

authors： Crodelle J,Zhou D,Kovačič G,Cai D

更新日期：2019-05-28 00:00:00

abstract：:Stability is an important dynamical property of complex systems and underpins a broad range of coherent self-organized behavior. Based on evidence that some neurological disorders correspond to linear instabilities, we hypothesize that stability constrains the brain's electrical activity and influences its structure a...

journal_title：Frontiers in computational neuroscience

authors： Gray RT,Robinson PA

更新日期：2013-04-12 00:00:00

abstract：:Neuronal networks exhibit a wide diversity of structures, which contributes to the diversity of the dynamics therein. The presented work applies an information theoretic framework to simultaneously analyze structure and dynamics in neuronal networks. Information diversity within the structure and dynamics of a neurona...

journal_title：Frontiers in computational neuroscience

authors： Mäki-Marttunen T,Aćimović J,Nykter M,Kesseli J,Ruohonen K,Yli-Harja O,Linne ML

更新日期：2011-06-01 00:00:00

abstract：:Recently, biologically inspired models are gradually proposed to solve the problem in text analysis. Convolutional neural networks (CNN) are hierarchical artificial neural networks, which include a various of multilayer perceptrons. According to biological research, CNN can be improved by bringing in the attention mod...

journal_title：Frontiers in computational neuroscience

authors： Fu H,Niu Z,Zhang C,Ma J,Chen J

更新日期：2016-07-14 00:00:00

abstract：:The extent to which groups of neurons exhibit higher-order correlations in their spiking activity is a controversial issue in current brain research. A major difficulty is that currently available tools for the analysis of massively parallel spike trains (N >10) for higher-order correlations typically require vast sam...

journal_title：Frontiers in computational neuroscience

authors： Staude B,Grün S,Rotter S

更新日期：2010-07-02 00:00:00

abstract：:Despite the progress in understanding of neural codes, the studies of the cortico-muscular coupling still largely rely on interferential electromyographic (EMG) signal or its rectification for the assessment of motor neuron pool behavior. This assessment is non-trivial and should be used with precaution. Direct analys...

journal_title：Frontiers in computational neuroscience

authors： Mohebian MR,Marateb HR,Karimimehr S,Mañanas MA,Kranjec J,Holobar A

更新日期：2019-04-02 00:00:00

abstract：:Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsong production, whose variables are the average activities of different neural populations within these nuclei of the...

journal_title：Frontiers in computational neuroscience

authors： Alonso RG,Trevisan MA,Amador A,Goller F,Mindlin GB

更新日期：2015-04-07 00:00:00

abstract：:We present a high-capacity model for one-shot association learning (hetero-associative memory) in sparse networks. We assume that basic patterns are pre-learned in networks and associations between two patterns are presented only once and have to be learned immediately. The model is a combination of an Amit-Fusi like ...

journal_title：Frontiers in computational neuroscience

authors： Einarsson H,Lengler J,Steger A

更新日期：2014-11-07 00:00:00

abstract：:This paper presents a new model-based method to define muscle synergies. Unlike the conventional factorization approach, which extracts synergies from electromyographic data, the proposed method employs a biomechanical model and formally defines the synergies as the solution of an optimal control problem. As a result,...

journal_title：Frontiers in computational neuroscience

authors： Sharif Razavian R,Mehrabi N,McPhee J

更新日期：2015-10-06 00:00:00

abstract：:Automatic segmentation of Multiple Sclerosis (MS) lesions from Magnetic Resonance Imaging (MRI) images is essential for clinical assessment and treatment planning of MS. Recent years have seen an increasing use of Convolutional Neural Networks (CNNs) for this task. Although these methods provide accurate segmentation,...

journal_title：Frontiers in computational neuroscience

authors： Ackaouy A,Courty N,Vallée E,Commowick O,Barillot C,Galassi F

更新日期：2020-03-09 00:00:00

abstract：:Learning from limited exemplars (few-shot learning) is a fundamental, unsolved problem that has been laboriously explored in the machine learning community. However, current few-shot learners are mostly supervised and rely heavily on a large amount of labeled examples. Unsupervised learning is a more natural procedure...

journal_title：Frontiers in computational neuroscience

authors： Ji Z,Zou X,Huang T,Wu S

更新日期：2020-10-14 00:00:00

abstract：:This paper investigates how a neural network model of the ventral visual pathway, VisNet, can form separate view invariant representations of a number of objects seen rotating together. In particular, in the current work one of the rotating objects is always partially occluded by the other objects present during train...

journal_title：Frontiers in computational neuroscience

authors： Tromans JM,Higgins I,Stringer SM

更新日期：2012-07-25 00:00:00

abstract：:A promising idea for scaling robot learning to more complex tasks is to use elemental behaviors as building blocks to compose more complex behavior. Ideally, such building blocks are used in combination with a learning algorithm that is able to learn to select, adapt, sequence and co-activate the building blocks. Whil...

journal_title：Frontiers in computational neuroscience

authors： Neumann G,Daniel C,Paraschos A,Kupcsik A,Peters J

更新日期：2014-06-11 00:00:00