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Neural connectivity

Vincent Prevot, Bénédicte Dehouck, Ariane Sharif, Philippe Ciofi, Paolo Giacobini, Jerome Clasadonte
The fertility and survival of an individual rely on the ability of the periphery to promptly, effectively and reproducibly communicate with brain neural networks that control reproduction, food intake and energy homeostasis. Tanycytes, a specialized glial cell type lining the wall of the third ventricle in the median eminence of the hypothalamus, appear to act as the linchpin of these processes by dynamically controlling the secretion of neuropeptides into the portal vasculature by hypothalamic neurons and regulating blood-brain and blood-cerebrospinal fluid exchanges, both processes that depend on the ability of these cells to adapt their morphology to the physiological state of the individual...
January 17, 2018: Endocrine Reviews
Grace E Rice, Helen Caswell, Perry Moore, Paul Hoffman, Matthew A Lambon Ralph
The presence and degree of specialization between the anterior temporal lobes (ATLs) is a key issue in debates about the neural architecture of semantic memory. Here, we comprehensively assessed multiple aspects of semantic cognition in a large group of postsurgical temporal lobe epilepsy (TLE) patients with left versus right anterior temporal lobectomy (n = 40). Both subgroups showed deficits in expressive and receptive verbal semantic tasks, word and object recognition, naming and recognition of famous faces and perception of faces and emotions...
January 17, 2018: Cerebral Cortex
Zabit Hameed, Saqib Saleem, Jawad Mirza, Muhammad Salman Mustafa, Qamar-Ul-Islam
Epilepsy is a brain disorder characterised by the recurrent and unpredictable interruptions of normal brain function, called epileptic seizures. The present study attempts to derive new diagnostic indices which may delineate between ictal and interictal states of epilepsy. To achieve this, the nonlinear modeling approach of global principal dynamic modes (PDMs) is adopted to examine the functional connectivity of the temporal and frontal lobes with the occipital brain segment using an ensemble of paediatric EEGs having the presence of epileptic seizure...
2018: PloS One
Frigyes Samuel Racz, Peter Mukli, Zoltan Nagy, Andras Eke
Brain function is organized as a network of functional connections between different neuronal populations with connection strengths dynamically changing in time and space. Studies investigating functional connectivity (FC) usually follow a static approach when describing FC by considering the connectivity strengths constant, however a dynamic approach seems more reasonable, as this way the spatio-temporal dynamics of the underlying system can also be captured. Objective: The scale-free, i.e. fractal nature of neural dynamics is an inherent property of the nervous system...
January 19, 2018: Physiological Measurement
Philip Lindner, Pär Flodin, Peter Larm, Meenal Budhiraja, Ivanka Savic-Berglund, Jussi Jokinen, Jari Tiihonen, Sheilagh Hodgins
Conduct disorder (CD) and anxiety disorders (ADs) are often comorbid and both are characterized by hyper-sensitivity to threat, and reduced structural and functional connectivity between the amygdala and orbitofrontal cortex (OFC). Previous studies of CD have not taken account of ADs nor directly compared connectivity in the two disorders. We examined three groups of young women: 23 presenting CD and lifetime AD; 30 presenting lifetime AD and not CD; and 17 with neither disorder (ND). Participants completed clinical assessments and diffusion-weighted and resting-state functional MRI scans...
January 18, 2018: Scientific Reports
Jose M Esnaola-Acebes, Alex Roxin, Daniele Avitabile, Ernest Montbrió
We investigate the modes of oscillation of heterogeneous ring networks of quadratic integrate-and-fire (QIF) neurons with nonlocal, space-dependent coupling. Perturbations of the equilibrium state with a particular wave number produce transient standing waves with a specific temporal frequency, analogously to those in a tense string. In the neuronal network, the equilibrium corresponds to a spatially homogeneous, asynchronous state. Perturbations of this state excite the network's oscillatory modes, which reflect the interplay of episodes of synchronous spiking with the excitatory-inhibitory spatial interactions...
November 2017: Physical Review. E
Sergey Makovkin, Anil Kumar, Alexey Zaikin, Sarika Jalan, Mikhail Ivanchenko
Inspired by the recent interest in collective dynamics of biological neural networks immersed in the glial cell medium, we investigate the frequency and phase order, i.e., Kuramoto type of synchronization in a multiplex two-layer network of phase oscillators of different time scales and topologies. One of them has a long-range connectivity, exemplified by the Erdős-Rényi random network, and supports both kinds of synchrony. The other is a locally coupled two-dimensional lattice that can reach frequency synchronization but lacks phase order...
November 2017: Physical Review. E
M Kähne, I M Sokolov, S Rüdiger
We develop a statistical framework for studying recurrent networks with broad distributions of the number of synaptic links per neuron. We treat each group of neurons with equal input degree as one population and derive a system of equations determining the population-averaged firing rates. The derivation rests on an assumption of a large number of neurons and, additionally, an assumption of a large number of synapses per neuron. For the case of binary neurons, analytical solutions can be constructed, which correspond to steps in the activity versus degree space...
November 2017: Physical Review. E
Zhuocheng Xiao, Jiwei Zhang, Andrew T Sornborger, Louis Tao
Line attractors in neuronal networks have been suggested to be the basis of many brain functions, such as working memory, oculomotor control, head movement, locomotion, and sensory processing. In this paper, we make the connection between line attractors and pulse gating in feed-forward neuronal networks. In this context, because of their neutral stability along a one-dimensional manifold, line attractors are associated with a time-translational invariance that allows graded information to be propagated from one neuronal population to the next...
November 2017: Physical Review. E
Neta Ravid Tannenbaum, Yoram Burak
We expand the theory of Hawkes processes to the nonstationary case, in which the mutually exciting point processes receive time-dependent inputs. We derive an analytical expression for the time-dependent correlations, which can be applied to networks with arbitrary connectivity, and inputs with arbitrary statistics. The expression shows how the network correlations are determined by the interplay between the network topology, the transfer functions relating units within the network, and the pattern and statistics of the external inputs...
December 2017: Physical Review. E
R C Budzinski, B R R Boaretto, T L Prado, S R Lopes
We study the stability of asymptotic states displayed by a complex neural network. We focus on the loss of stability of a stationary state of networks using recurrence quantifiers as tools to diagnose local and global stabilities as well as the multistability of a coupled neural network. Numerical simulations of a neural network composed of 1024 neurons in a small-world connection scheme are performed using the model of Braun et al. [Int. J. Bifurcation Chaos 08, 881 (1998)IJBEE40218-127410.1142/S0218127498000681], which is a modified model from the Hodgkin-Huxley model [J...
July 2017: Physical Review. E
Natasha C Gabay, P A Robinson
Perturbation analysis of neural field theory is used to derive eigenmodes of neural activity on a cortical hemisphere, which have previously been calculated numerically and found to be close analogs of spherical harmonics, despite heavy cortical folding. The present perturbation method treats cortical folding as a first-order perturbation from a spherical geometry. The first nine spatial eigenmodes on a population-averaged cortical hemisphere are derived and compared with previous numerical solutions. These eigenmodes contribute most to brain activity patterns such as those seen in electroencephalography and functional magnetic resonance imaging...
September 2017: Physical Review. E
Jan Clemens, Cyrille C Girardin, Philip Coen, Xiao-Juan Guan, Barry J Dickson, Mala Murthy
No abstract text is available yet for this article.
January 17, 2018: Neuron
Andrew C Murphy, Sarah F Muldoon, David Baker, Adam Lastowka, Brittany Bennett, Muzhi Yang, Danielle S Bassett
The human body is a complex organism, the gross mechanical properties of which are enabled by an interconnected musculoskeletal network controlled by the nervous system. The nature of musculoskeletal interconnection facilitates stability, voluntary movement, and robustness to injury. However, a fundamental understanding of this network and its control by neural systems has remained elusive. Here we address this gap in knowledge by utilizing medical databases and mathematical modeling to reveal the organizational structure, predicted function, and neural control of the musculoskeletal system...
January 2018: PLoS Biology
Yuefeng Huang, Anusha Mohan, Dirk De Ridder, Stefan Sunaert, Sven Vanneste
Alcohol addiction is accompanied by aberrant neural activity. Previously, task-based fMRI and resting-state EEG studies have revealed that craving, a critical component of addiction, is linked to abnormal activity in cortical regions including the dorsal anterior cingulate cortex (dACC), nucleus accumbens (NAcc), posterior cingulate cortex (PCC) and pregenual anterior cingulate cortex (pgACC), etc. In this study, we combine these two imaging techniques to investigate a group of alcohol-addicted patients and provide convergent evidence for the neural correlates of craving not only in alcohol but substance abuse in general...
January 17, 2018: Scientific Reports
Johannes Leugering, Gordon Pipa
A neuronal population is a computational unit that receives a multivariate, time-varying input signal and creates a related multivariate output. These neural signals are modeled as stochastic processes that transmit information in real time, subject to stochastic noise. In a stationary environment, where the input signals can be characterized by constant statistical properties, the systematic relationship between its input and output processes determines the computation carried out by a population. When these statistical characteristics unexpectedly change, the population needs to adapt to its new environment if it is to maintain stable operation...
January 17, 2018: Neural Computation
Joseph Snider
Neurons integrate information from many neighbors when they process information. Inputs to a given neuron are thus indistinguishable from one another. Under the assumption that neurons maximize their information storage, indistinguishability is shown to place a strong constraint on the distribution of strengths between neurons. The distribution of individual synapse strengths is found to follow a modified Boltzmann distribution with strength proportional to [Formula: see text]. The model is shown to be consistent with experimental data from Caenorhabditis elegans connectivity and in vivo synaptic strength measurements...
January 17, 2018: Neural Computation
Roger E Beaty, Yoed N Kenett, Alexander P Christensen, Monica D Rosenberg, Mathias Benedek, Qunlin Chen, Andreas Fink, Jiang Qiu, Thomas R Kwapil, Michael J Kane, Paul J Silvia
People's ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis-connectome-based predictive modeling-to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences (r = 0...
January 16, 2018: Proceedings of the National Academy of Sciences of the United States of America
Jonas Hornung, Lydia Kogler, Michael Erb, Jessica Freiherr, Birgit Derntl
The androgen derivative androstadienone (AND) is a substance found in human sweat and thus may act as human chemosignal. With the current experiment, we aimed to explore in which way AND affects interference processing during an emotional Stroop task which used human faces as target and emotional words as distractor stimuli. This was complemented by functional magnetic resonance imaging (fMRI) to unravel the neural mechanism of AND-action. Based on previous accounts we expected AND to increase neural activation in areas commonly implicated in evaluation of emotional face processing and to change neural activation in brain regions linked to interference processing...
January 12, 2018: NeuroImage
Yun-An Huang, Jan Jastorff, Jan Van den Stock, Laura Van de Vliet, Patrick Dupont, Mathieu Vandenbulcke
Psychological construction models of emotion state that emotions are variable concepts constructed by fundamental psychological processes, whereas according to basic emotion theory, emotions cannot be divided into more fundamental units and each basic emotion is represented by a unique and innate neural circuitry. In a previous study, we found evidence for the psychological construction account by showing that several brain regions were commonly activated when perceiving different emotions (i.e. a general emotion network)...
January 12, 2018: NeuroImage
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