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Background: We have previously demonstrated that cortical folding across mammalian species follows a universal scaling law that can be derived from a simple theoretical model. The same scaling law has also been shown to hold across brains…

Neurons and Cognition · Quantitative Biology 2020-06-01 Yujiang Wang , Joe Necus , Luis Peraza Rodriguez , Peter Neal Taylor , Bruno Mota

The idealisation of neuronal pulses as $\delta$-spikes is a convenient approach in neuroscience but can sometimes lead to erroneous conclusions. We investigate the effect of a finite pulse-width on the dynamics of balanced neuronal…

Neurons and Cognition · Quantitative Biology 2024-06-19 Afifurrahman , Ekkehard Ullner , Antonio Politi

Neural activity patterns related to behavior occur at many scales in time and space from the atomic and molecular to the whole brain. Here we explore the feasibility of interpreting neurophysiological data in the context of many-body…

Other Quantitative Biology · Quantitative Biology 2009-11-11 Walter J. Freeman , Giuseppe Vitiello

The collective frequency that emerges from synchronized neuronal populations--the network resonance--shows a systematic relationship with brain size: whole-brain's large networks oscillate slowly, whereas finer parcellations of fixed volume…

Neurons and Cognition · Quantitative Biology 2026-03-04 Felipe A. Torres , Alejandro Weinstein , Jesus M. Cortes , Wael El-Deredy

Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions, however it is unclear how this mechanism manifests over time. In this study, we use time-resolved network…

Oscillations are a hallmark of neural population activity in various brain regions with a spectrum covering a wide range of frequencies. Within this spectrum gamma oscillations have received particular attention due to their ubiquitous…

Neurons and Cognition · Quantitative Biology 2020-01-22 Hongjie Bi , Marco Segneri , Matteo di Volo , Alessandro Torcini

Analytical expressions for scaling of brain wave spectra derived from the general nonlinear wave Hamiltonian form show excellent agreement with experimental "neuronal avalanche" data. The theory of the weakly evanescent nonlinear brain wave…

Neurons and Cognition · Quantitative Biology 2021-11-16 Vitaly L. Galinsky , Lawrence R. Frank

We model the elasticity of the cerebral cortex as a layered material with bending energy along the layers and elastic energy between them in both planar and polar geometries. The cortex is also subjected to axons pulling from the underlying…

Soft Condensed Matter · Physics 2016-02-09 O. V. Manyuhina , David Mayett , J. M. Schwarz

Synchronization is an important collective phenomenon in interacting oscillatory agents. Many functional features of the brain are related to synchronization of neurons. The type of synchronization transition that may occur (explosive vs.…

Disordered Systems and Neural Networks · Physics 2020-03-18 Mahsa Khoshkhou , Afshin Montakhab

Brain activity following stimulus presentation and during resting state are often the result of highly coordinated responses of large numbers of neurons both locally and globally. Coordinated activity of neurons can give rise to…

Applications · Statistics 2015-07-20 Carolina Euan , Hernando Ombao , Joaquin Ortega

We applied detrended fluctuation analysis, power spectral density, and eigenanalysis of detrended cross-correlations to investigate fMRI data representing a diurnal variation of working memory in four visual tasks: two verbal and two…

An increasing body of evidence suggests that the trial-to-trial variability of spiking activity in the brain is not mere noise, but rather the reflection of a sampling-based encoding scheme for probabilistic computing. Since the precise…

Population-wide oscillations are ubiquitously observed in mesoscopic signals of cortical activity. In these network states a global oscillatory cycle modulates the propensity of neurons to fire. Synchronous activation of neurons has been…

Neurons and Cognition · Quantitative Biology 2017-07-04 Tobias Kühn , Moritz Helias

Different brain areas, such as the cortex and, more specifically, the prefrontal cortex, show great recurrence in their connections, even in early sensory areas. {Several approaches and methods based on trained networks have been proposed…

Neurons and Cognition · Quantitative Biology 2022-04-25 Cecilia Jarne

The normalization of brain recordings from multiple subjects responding to the natural stimuli is one of the key challenges in auditory neuroscience. The objective of this normalization is to transform the brain data in such a way as to…

Audio and Speech Processing · Electrical Eng. & Systems 2021-03-12 Jaswanth Reddy Katthi , Sriram Ganapathy

Power spectra of awake resting state EEG recordings in humans typically have an Alpha peak at around 10 Hz riding a decreasing background "Xi process". Normal and pathological variations may have more than one peak or none. The single…

Neurons and Cognition · Quantitative Biology 2023-01-02 Roberto D. Pascual-Marqui , Kieko Kochi , Toshihiko Kinoshita

In a series of two papers, we investigate the large deviations and asymptotic behavior of stochastic models of brain neural networks with random interaction coefficients. In this first paper, we take into account the spatial structure of…

Probability · Mathematics 2017-01-05 Tanguy Cabana , Jonathan Touboul

In this paper, we propose a framework to control brain-wide functional connectivity by selectively acting on the brain's structure and parameters. Functional connectivity, which measures the degree of correlation between neural activities…

Systems and Control · Computer Science 2020-03-17 Tommaso Menara , Giacomo Baggio , Danielle S. Bassett , Fabio Pasqualetti

To date, it is still impossible to sample the entire mammalian brain with single-neuron precision. This forces one to either use spikes (focusing on few neurons) or to use coarse-sampled activity (averaging over many neurons, e.g. LFP).…

Neurons and Cognition · Quantitative Biology 2022-12-12 Joao Pinheiro Neto , Franz Paul Spitzner , Viola Priesemann

Motivated by the need to model the dependence between regions of interest in functional neuroconnectivity for efficient inference, we propose a new sampling-based Bayesian clustering approach for covariance structures of high-dimensional…

Methodology · Statistics 2024-01-09 Hyoshin Kim , Sujit K. Ghosh , Adriana Di Martino , Emily C. Hector