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Experiments that study neural encoding of stimuli at the level of individual neurons typically choose a small set of features present in the world --- contrast and luminance for vision, pitch and intensity for sound --- and assemble a…

Machine Learning · Statistics 2016-11-22 Xin , Chen , Jeffrey M Beck , John M Pearson

Magnetoencephalographic (MEG) recordings from a large normative cohort (n = 619) were processed to extract measures of regional neuroelectric activity. The overall objective of the effort was to use these measures to identify normative…

Neurons and Cognition · Quantitative Biology 2018-11-20 Don Krieger , Paul Shepard , David O. Okonkwo

We present a hidden Markov model that describes variation in an animal's position associated with varying levels of activity in action potential spike trains of individual place cell neurons. The model incorporates a coarse-graining of…

Applications · Statistics 2014-12-22 Marc Box , Matt W. Jones , Nick Whiteley

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.…

Neurons and Cognition · Quantitative Biology 2023-12-12 Sage Shaw , Zachary P Kilpatrick

The continuous integration of experimental data into coherent models of the brain is an increasing challenge of modern neuroscience. Such models provide a bridge between structure and activity, and identify the mechanisms giving rise to…

Neurons and Cognition · Quantitative Biology 2017-03-03 Jannis Schuecker , Maximilian Schmidt , Sacha J. van Albada , Markus Diesmann , Moritz Helias

Extracellular electrical potentials (EEP) recorded from the brain are an active manifestation of all cellular processes that propagate within a volume of brain tissue. A standard approach for their quantification are power spectral analyses…

Neurons and Cognition · Quantitative Biology 2020-11-17 Shailaja Akella , Ali Mohebi , Kiersten Riels , Andreas Keil , Karim Oweiss , Jose C. Principe

Effective connectivity analysis provides an understanding of the functional organization of the brain by studying how activated regions influence one other. We propose a nonparametric Bayesian approach to model effective connectivity…

Applications · Statistics 2011-07-22 Sourabh Bhattacharya , Ranjan Maitra

A standard approach in functional neuroimaging explores how a particular cognitive task activates a set of brain regions (one task-to-many regions mapping). Importantly though, the same neural system can be activated by inherently different…

Neurons and Cognition · Quantitative Biology 2016-03-23 Romy Lorenz , Ricardo Pio Monti , Ines R. Violante , Christoforos Anagnostopoulos , Aldo A. Faisal , Giovanni Montana , Robert Leech

Fluctuations in heart rate are intimately tied to changes in the physiological state of the organism. We examine and exploit this relationship by classifying a human subject's wake/sleep status using his instantaneous heart rate (IHR)…

Applications · Statistics 2018-08-02 John Malik , Yu-Lun Lo , Hau-tieng Wu

We report on both analytical and numerical results concerning stochastic Hopfield--like neural automata exhibiting the following (biologically inspired) features: (1) Neurons and synapses evolve in time as in contact with respective baths…

Statistical Mechanics · Physics 2007-05-23 J. J. Torres , J. Marro , P. L. Garrido , J. M. Cortes , F. Ramos , M. A. Munoz

Individual Neurons in the nervous systems exploit various dynamics. To capture these dynamics for single neurons, we tune the parameters of an electrophysiological model of nerve cells, to fit experimental data obtained by calcium imaging.…

Quantitative Methods · Quantitative Biology 2017-11-07 Magdalena Fuchs , Manuel Zimmer , Radu Grosu , Ramin M. Hasani

Background: Recent studies have indicated that functional connectivity is dynamic even during rest. A common approach to modeling the dynamic functional connectivity in whole-brain resting-state fMRI is to compute the correlation between…

Neurons and Cognition · Quantitative Biology 2019-11-05 Shih-Gu Huang , S. Balqis Samdin , Chee-Ming Ting , Hernando Ombao , Moo K. Chung

We study pattern formation in class of a large-dimensional neural networks posed on random graphs and subject to spatio-temporal stochastic forcing. Under generic conditions on coupling and nodal dynamics, we prove that the network admits a…

Probability · Mathematics 2025-08-26 Daniele Avitabile , James MacLaurin

A steadily increasing body of evidence suggests that the brain performs probabilistic inference to interpret and respond to sensory input and that trial-to-trial variability in neural activity plays an important role. The neural sampling…

Neurons and Cognition · Quantitative Biology 2017-07-07 Ilja Bytschok , Dominik Dold , Johannes Schemmel , Karlheinz Meier , Mihai A. Petrovici

We investigate a general class of models for swarming/self-collective behaviour in domains with boundaries. The model is expressed as a stochastic system of interacting particles subject to both reflecting boundary condition and common…

Probability · Mathematics 2025-10-21 Razvan C. Fetecau , Hui Huang , Jinniao Qiu

Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper…

Understanding the neural basis of language comprehension in the brain has been a long-standing goal of various scientific research programs. Recent advances in language modelling and in neuroimaging methodology promise potential…

Computation and Language · Computer Science 2022-03-11 Mostafa Abdou

Here we demonstrate that the activity of neural ensembles can be quantitatively modeled. We first show that an ensemble dynamical model (EDM) accurately approximates the distribution of voltages and average firing rate per neuron of a…

Neurons and Cognition · Quantitative Biology 2015-09-07 Joaquin Rapela , Mark Kostuk , Peter F. Rowat , Tim Mullen , Edward F. Chang , Kristofer Bouchard

Sensory neurons often have variable responses to repeated presentations of the same stimulus, which can significantly degrade the stimulus information contained in those responses. This information can in principle be preserved if…

Neurons and Cognition · Quantitative Biology 2019-04-24 Matthew R Whiteway , Karolina Socha , Vincent Bonin , Daniel A Butts

Mounting experimental evidence suggests that brain-state-specific neural mechanisms, supported by connectomic architectures, play a crucial role in integrating past and contextual knowledge with the current, incoming flow of evidence (e.g.,…