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Deep learning models have been shown to be vulnerable to adversarial attacks. This perception led to analyzing deep learning models not only from the perspective of their performance measures but also their robustness to certain types of…

Machine Learning · Computer Science 2021-10-13 M. Ben Amor , J. Stier , M. Granitzer

Excitatory synaptic connections in the adult neocortex consist of multiple synaptic contacts, almost exclusively formed on dendritic spines. Changes of dendritic spine shape and volume, a correlate of synaptic strength, can be tracked in…

Neurons and Cognition · Quantitative Biology 2018-03-13 Moritz Deger , Alexander Seeholzer , Wulfram Gerstner

When inhibitory neurons constitute about 40% of neurons they could have an important antinociceptive role, as they would easily regulate the level of activity of other neurons. We consider a simple network of cortical spiking neurons with…

Neurons and Cognition · Quantitative Biology 2014-01-28 Fernando Montani , Emilia B. Deleglise , Osvaldo A. Rosso

Sparse coding algorithms trained on natural images can accurately predict the features that excite visual cortical neurons, but it is not known whether such codes can be learned using biologically realistic plasticity rules. We have…

Neurons and Cognition · Quantitative Biology 2011-11-01 Joel Zylberberg , Jason Timothy Murphy , Michael Robert DeWeese

Cortical neurons whose activity is recorded in behavioral experiments has been classified into several types such as stimulus-related neurons, delay-period neurons, and reward-related neurons. Moreover, the population activity of neurons…

Neurons and Cognition · Quantitative Biology 2018-11-27 Takuma Tanaka

Early brain connectivity development consists of multiple stages: birth of neurons, their migration and the subsequent growth of axons and dendrites. Each stage occurs within a certain period of time depending on types of neurons and…

Neurons and Cognition · Quantitative Biology 2015-03-16 Sol Lim , Marcus Kaiser

The study of dynamical systems defined on complex networks provides a natural framework with which to investigate myriad features of neural dynamics, and has been widely undertaken. Typically, however, networks employed in theoretical…

Neurons and Cognition · Quantitative Biology 2013-02-22 Reuben O'Dea , Jonathan J. Crofts , Marcus Kaiser

Advances in neural recording methods enable sampling from populations of thousands of neurons during the performance of behavioral tasks, raising the question of how recorded activity relates to the theoretical models of computations…

Neurons and Cognition · Quantitative Biology 2020-07-01 Audrey J. Sederberg , Ilya Nemenman

When the human brain manifests the birth of organised communication among local and large-scale neuronal populations activity remains undescribed. We report, in resting-state EEG source-estimates of 100 infants at term age, the existence of…

Neurons and Cognition · Quantitative Biology 2020-09-08 Steve Mehrkanoon

We investigated how the organization of functional brain networks was related to cognitive reserve (CR) during a memory task in healthy aging. We obtained the magnetoencephalographic functional networks of 20 elders with a high or low CR…

Motifs are patterns of subgraphs of complex networks. We studied the impact of such patterns of connectivity on the level of correlated, or synchronized, spiking activity among pairs of cells in a recurrent network model of integrate and…

Neurons and Cognition · Quantitative Biology 2015-06-05 Yu Hu , James Trousdale , Kresimir Josic , Eric Shea-Brown

The activity of a sparse network of leaky integrate-and-fire neurons is carefully revisited with reference to a regime of a bona-fide asynchronous dynamics. The study is preceded by a finite-size scaling analysis, carried out to identify a…

Neurons and Cognition · Quantitative Biology 2020-05-06 Ekkehard Ullner , Antonio Politi , Alessandro Torcini

Coded recurrent neural networks with three levels of sparsity are introduced. The first level is related to the size of messages, much smaller than the number of available neurons. The second one is provided by a particular coding rule,…

Machine Learning · Computer Science 2011-02-22 Vincent Gripon , Claude Berrou

Recent advances in neuroscience have revealed many principles about neural processing. In particular, many biological systems were found to reconfigure/recruit single neurons to generate multiple kinds of decisions. Such findings have the…

Machine Learning · Computer Science 2019-05-30 Yassin Khalifa , Justin Hawks , Ervin Sejdic

Maximum entropy principle (MEP) analysis with few non-zero effective interactions successfully characterizes the distribution of dynamical states of pulse-coupled networks in many experiments, e.g., in neuroscience. To better understand the…

Biological Physics · Physics 2019-01-17 Zhi-Qin John Xu , Douglas Zhou , David Cai

Measured responses from visual cortical neurons show that spike times tend to be correlated rather than exactly Poisson distributed. Fano factors vary and are usually greater than 1 due to the tendency of spikes being clustered into bursts.…

Neurons and Cognition · Quantitative Biology 2007-05-23 Alexander Lerchner , Mandana Ahmadi , John Hertz

Recent evidence in rodent cerebral cortex and olfactory bulb suggests that short-term dynamics of excitatory synaptic transmission is correlated to stereotypical connectivity motifs. It was observed that neurons with short-term facilitating…

Neurons and Cognition · Quantitative Biology 2016-04-08 Eleni Vasilaki , Michele Giugliano

How neurons integrate the myriad synaptic inputs scattered across their dendrites is a fundamental question in neuroscience. Multiple neurophysiological experiments have shown that dendritic non-linearities can have a strong influence on…

Neurons and Cognition · Quantitative Biology 2025-01-13 Clarissa Lauditi , Enrico M. Malatesta , Fabrizio Pittorino , Carlo Baldassi , Nicolas Brunel , Riccardo Zecchina

Collective rhythmic dynamics from neurons is vital for cognitive functions such as memory formation but how neurons self-organize to produce such activity is not well understood. Attractor-based models have been successfully implemented as…

Neurons and Cognition · Quantitative Biology 2013-03-22 Mark Niedringhaus , Xin Chen , Katherine Conant , Rhonda Dzakpasu

Describing the collective activity of neural populations is a daunting task: the number of possible patterns grows exponentially with the number of cells, resulting in practically unlimited complexity. Recent empirical studies, however,…

Neurons and Cognition · Quantitative Biology 2012-02-02 Andrea K. Barreiro , Julijana Gjorgjieva , Fred Rieke , Eric Shea-Brown
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