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相关论文: Interference of Neural Waves in Distributed Inhibi…

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Inhibition is considered to shape neural activity, and broaden its pattern repertoire. In the sensory organs, where the anatomy of neural circuits is highly structured, lateral inhibition sharpens contrast among stimulus properties. The…

神经元与认知 · 定量生物学 2018-09-18 Netta Haroush , Shimon Marom

The traditional view of neural computation in the cerebral cortex holds that sensory neurons are specialized, i.e., selective for certain dimensions of sensory stimuli. This view was challenged by evidence of contextual interactions between…

神经元与认知 · 定量生物学 2022-04-26 Sergei Gepshtein , Ambarish Pawar , Sunwoo Kwon , Sergey Savel'ev , Thomas D. Albright

We developed a model of cortical computation that implements key features of cortical circuitry and is capable of describing propagation of neural signals between cortical locations in response to spatially distributed stimuli. The model is…

神经元与认知 · 定量生物学 2018-10-23 Sergei Gepshtein , Ambarish S. Pawar , Sergey Saveliev , Thomas D. Albright

Propagation of oscillatory signals through the cortex and coherence is shaped by the connectivity structure of neuronal circuits. This study systematically investigates the network and stimulus properties that shape network responses. The…

神经元与认知 · 定量生物学 2017-04-28 Hannah Bos , Jannis Schücker , Moritz Helias

At the macroscale, the brain operates as a network of interconnected neuronal populations, which display rhythmic dynamics that support interareal communication. Understanding how stimulation of a particular brain area impacts such…

神经元与认知 · 定量生物学 2020-11-12 Lia Papadopoulos , Christopher W. Lynn , Demian Battaglia , Danielle S. Bassett

Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A…

神经元与认知 · 定量生物学 2015-06-19 Sadra Sadeh , Stefan Rotter

Neural network models comprising elements which have exclusively excitatory or inhibitory synapses are capable of a wide range of dynamic behavior, including chaos. In this paper, a simple excitatory-inhibitory neural pair, which forms the…

无序系统与神经网络 · 物理学 2009-10-31 Sitabhra Sinha , Jayanta Basak

Local patterns of excitation and inhibition that can generate neural waves are studied as a computational mechanism underlying the organization of neuronal tunings. Sparse coding algorithms based on networks of excitatory and inhibitory…

神经元与认知 · 定量生物学 2022-05-30 Leon Lufkin , Ashish Puri , Ganlin Song , Xinyi Zhong , John Lafferty

Complexity in the temporal organization of neural systems may be a reflection of the diversity of its neural constituents. These constituents, excitatory and inhibitory neurons, comprise an invariant ratio in vivo and form the substrate for…

神经元与认知 · 定量生物学 2015-05-18 Xin Chen , Rhonda Dzakpasu

Traveling waves of neural activity emerge in cortical networks both spontaneously and in response to stimuli. The spatiotemporal structure of waves can indicate the information they encode and the physiological processes that sustain them.…

神经元与认知 · 定量生物学 2023-12-12 Sage Shaw , Zachary P Kilpatrick

Many neural systems display cascading behavior characterized by uninterrupted sequences of neuronal firing. This gap precludes an understanding of how variations in network structure manifest in neural dynamics and either support or impinge…

神经元与认知 · 定量生物学 2019-11-12 Harang Ju , Jason Z. Kim , Danielle S. Bassett

The human brain exhibits a relatively stable spatiotemporal organization that supports brain function and can be manipulated via local brain stimulation. Such perturbations to local cortical dynamics are globally integrated by distinct…

神经元与认知 · 定量生物学 2018-01-19 Leonardo L. Gollo , James A. Roberts , Luca Cocchi

Networks of model neurons with balanced recurrent excitation and inhibition produce irregular and asynchronous spiking activity. We extend the analysis of balanced networks to include the known dependence of connection probability on the…

神经元与认知 · 定量生物学 2014-06-02 Robert Rosenbaum , Brent Doiron

Neuromorphic networks can be described in terms of coarse-grained variables, where emergent sustained behaviours spontaneously arise if stochasticity is properly taken in account. For example it has been recently found that a directed…

适应与自组织系统 · 物理学 2020-01-23 Ilenia Apicella , Daniel Maria Busiello , Silvia Scarpetta , Samir Suweis

To study information processing in the brain, neuroscientists manipulate experimental stimuli while recording participant brain activity. They can then use encoding models to find out which brain "zone" (e.g. which region of interest,…

神经元与认知 · 定量生物学 2022-02-22 Mariya Toneva , Jennifer Williams , Anand Bollu , Christoph Dann , Leila Wehbe

Rich, spontaneous brain activity has been observed across a range of different temporal and spatial scales. These dynamics are thought to be important t for efficient neural functioning. Experimental evidence suggests that these neural…

神经元与认知 · 定量生物学 2015-01-21 Peter J. Hellyer , Barbara Jachs , Robert Leech , Claudia Clopath

Distributed networks of brain areas interact with one another in a time-varying fashion to enable complex cognitive and sensorimotor functions. Here we use novel network analysis algorithms to test the recruitment and integration of…

神经元与认知 · 定量生物学 2014-03-25 Danielle S. Bassett , Muzhi Yang , Nicholas F. Wymbs , Scott T. Grafton

Correlations in sensory neural networks have both extrinsic and intrinsic origins. Extrinsic or stimulus correlations arise from shared inputs to the network, and thus depend strongly on the stimulus ensemble. Intrinsic or noise…

神经元与认知 · 定量生物学 2018-11-05 Ulisse Ferrari , Stephane Deny , Matthew Chalk , Gasper Tkacik , Olivier Marre , Thierry Mora

Inhibitory neurons play a crucial role in maintaining persistent neuronal activity. Although connected extensively through electrical synapses (gap-junctions), these neurons also exhibit interactions through chemical synapses in certain…

神经元与认知 · 定量生物学 2021-04-08 R. Janaki , A. S. Vytheeswaran

Trial-to-trial variability is an essential feature of neural responses, but its source is a subject of active debate. Response variability (Mast and Victor, 1991; Arieli et al., 1995 & 1996; Anderson et al., 2000 & 2001; Kenet et al., 2003;…

神经元与认知 · 定量生物学 2010-08-04 L F Abbott , Kanaka Rajan , Haim Sompolinsky
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