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Mean field models (MFMs) of cortical tissue incorporate salient features of neural masses to model activity at the population level. One of the common aspects of MFM descriptions is the presence of a high dimensional parameter space…

Dynamical Systems · Mathematics 2015-05-19 Federico Frascoli , Lennaert van Veen , Ingo Bojak , David T J Liley

When the brain receives input from multiple sensory systems, it is faced with the question of whether it is appropriate to process the inputs in combination, as if they originated from the same event, or separately, as if they originated…

Neural and Evolutionary Computing · Computer Science 2018-03-06 Jonathan Tong , German I. Parisi , Stefan Wermter , Brigitte Röder

A major part of membrane function is conducted by proteins, both integral and peripheral. Peripheral membrane proteins temporarily adhere to biological membranes, either to the lipid bilayer or to integral membrane proteins with…

Biomolecules · Quantitative Biology 2014-06-27 Katerina C. Nastou , Georgios N. Tsaousis , Kimon E. Kremizas , Zoi I. Litou , Stavros J. Hamodrakas

Leveraging the perceptual phenomenon of crossmoal correspondence has been shown to facilitate peoples information processing and improves sensorimotor performance. However for goal-oriented interactive tasks, the question of how to enhance…

Human-Computer Interaction · Computer Science 2020-02-18 Feng Feng , Puhong Li , Tony Stockman

Transcranial magnetic stimulation (TMS) is a technique for noninvasively stimulating a brain area for therapeutic, rehabilitation treatments and neuroscience research. Despite our understanding of the physical principles and experimental…

Neurons and Cognition · Quantitative Biology 2020-12-30 Jose Gomez-Tames , Ilkka Laakso , Akimasa Hirata

Classical causal inference assumes treatments meant for a given unit do not have an effect on other units. This assumption is violated in interference problems, where new types of spillover causal effects arise, and causal inference becomes…

Methodology · Statistics 2024-09-30 Ilya Shpitser , Chan Park , Eric Tchetgen Tchetgen , Ryan Andrews

The Expanding Hole Illusion is a compelling visual phenomenon in which a static, concentric pattern evokes a strong perception of continuous forward motion. Despite its simplicity, this illusion challenges our understanding of how the brain…

Neurons and Cognition · Quantitative Biology 2025-01-16 Nasim Nematzadeh , David M. W. Powers

Ischemic stroke is a severe condition caused by the blockage of brain blood vessels, and can lead to the death of brain tissue due to oxygen deprivation. Thrombectomy has become a common treatment choice for ischemic stroke due to its…

Image and Video Processing · Electrical Eng. & Systems 2024-08-05 Caiwen Jiang , Tianyu Wang , Xiaodan Xing , Mianxin Liu , Guang Yang , Zhongxiang Ding , Dinggang Shen

Neuronal heterogeneity, characterized by the presence of a multitude of spiking neuronal patterns, is a widespread phenomenon throughout the nervous system. In particular, the brain exhibits strong variability among inhibitory neurons.…

Neurons and Cognition · Quantitative Biology 2024-12-02 Katiele V. P. Brito , Joana M. G. L. Silva , Claudio R. Mirasso , Fernanda S. Matias

The brain is a complex organ characterized by heterogeneous patterns of structural connections supporting unparalleled feats of cognition and a wide range of behaviors. New noninvasive imaging techniques now allow these patterns to be…

Neurons and Cognition · Quantitative Biology 2020-04-03 Christopher W. Lynn , Danielle S. Bassett

We present a physical interpretation of machine learning functions, opening up the possibility to control properties of statistical systems via the inclusion of these functions in Hamiltonians. In particular, we include the predictive…

High Energy Physics - Lattice · Physics 2021-02-17 Dimitrios Bachtis , Gert Aarts , Biagio Lucini

Animals must integrate sensory cues with their current behavioral context to generate a suitable response. How this integration occurs is poorly understood. Previously we developed high throughput methods to probe neural activity in…

Neurons and Cognition · Quantitative Biology 2023-09-25 Sandeep Kumar , Anuj K Sharma , Andrew Tran , Andrew M Leifer

This paper proposes a new approach to address the problem of unmeasured confounding in spatial designs. Spatial confounding occurs when some confounding variables are unobserved and not included in the model, leading to distorted…

Methodology · Statistics 2025-03-05 Carlo Zaccardi , Pasquale Valentini , Luigi Ippoliti , Alexandra M. Schmidt

We study inhibitory coherence (i.e., collective coherence by synaptic inhibition) in an ensemble of globally-coupled type-I neurons which can fire at arbitrarily low frequencies. No inhibitory coherence is observed in a homogeneous ensemble…

Biological Physics · Physics 2011-11-01 Duk-Geun Hong , Sang-Yoon Kim , Woochang Lim

Balance of excitation and inhibition is a fundamental feature of in vivo network activity and is important for its computations. However, its presence in the neocortex of higher mammals is not well established. We investigated the dynamics…

The functioning of an organ such as the brain emerges from interactions between its constituent parts. Further, this interaction is not immutable in time but rather unfolds in a succession of patterns, thereby allowing the brain to adapt to…

Neurons and Cognition · Quantitative Biology 2021-06-02 Emmanuelle Tognoli , Daniela Benites , J. A. Scott Kelso

Spin-orbit torques offer a promising mechanism for electrically controlling magnetization dynamics in nanoscale heterostructures. While spin-orbit torques occur predominately at interfaces, the physical mechanisms underlying these torques…

Mesoscale and Nanoscale Physics · Physics 2020-12-02 Vivek P. Amin , Paul M. Haney , Mark D. Stiles

Disordered systems form one of the centrestages of research in many body sciences and lead to a plethora of interesting phenomena and applications. A paradigmatic disordered system consists of an one-dimensional array of quantum spin-1/2…

Quantum Physics · Physics 2018-10-23 Utkarsh Mishra , Debraj Rakshit , R. Prabhu , Aditi Sen De , Ujjwal Sen

The ability to predict upcoming events has been hypothesized to comprise a key aspect of natural and machine cognition. This is supported by trends in deep reinforcement learning (RL), where self-supervised auxiliary objectives such as…

Artificial Intelligence · Computer Science 2024-10-31 Ching Fang , Kimberly L Stachenfeld

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…

Neurons and Cognition · Quantitative Biology 2021-04-08 R. Janaki , A. S. Vytheeswaran
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