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neural dynamics

Michael K Yeung, Sophia L Sze, Jean Woo, Timothy Kwok, David H K Shum, Ruby Yu, Agnes S Chan
BACKGROUND: Some functional magnetic resonance imaging studies have reported altered activations in the frontal cortex during working memory (WM) performance in individuals with mild cognitive impairment (MCI), but the findings have been mixed. The objective of the present study was to utilize near-infrared spectroscopy (NIRS), an alternative imaging technique, to examine neural processing during WM performance in individuals with MCI. METHODS: Twenty-six older adults with MCI (7 males; mean age 69...
October 27, 2016: Dementia and Geriatric Cognitive Disorders
André David Kovac, Maximilian Koall, Gordon Pipa, Hazem Toutounji
Delays are ubiquitous in biological systems, ranging from genetic regulatory networks and synaptic conductances, to predator/pray population interactions. The evidence is mounting, not only to the presence of delays as physical constraints in signal propagation speed, but also to their functional role in providing dynamical diversity to the systems that comprise them. The latter observation in biological systems inspired the recent development of a computational architecture that harnesses this dynamical diversity, by delay-coupling a single nonlinear element to itself...
2016: PloS One
Javier Roulet, Gabriel B Mindlin
We develop an extension of the Ott-Antonsen method [E. Ott and T. M. Antonsen, Chaos 18(3), 037113 (2008)] that allows obtaining the mean activity (spiking rate) of a population of excitable units. By means of the Ott-Antonsen method, equations for the dynamics of the order parameters of coupled excitatory and inhibitory populations of excitable units are obtained, and their mean activities are computed. Two different excitable systems are studied: Adler units and theta neurons. The resulting bifurcation diagrams are compared with those obtained from studying the phenomenological Wilson-Cowan model in some regions of the parameter space...
September 2016: Chaos
Christos Koutlis, Dimitris Kugiumtzis
Measures of Granger causality on multivariate time series have been used to form the so-called causality networks. A causality network represents the interdependence structure of the underlying dynamical system or coupled dynamical systems, and its properties are quantified by network indices. In this work, it is investigated whether network indices on networks generated by an appropriate Granger causality measure can discriminate different coupling structures. The information based Granger causality measure of partial mutual information from mixed embedding (PMIME) is used to form causality networks, and a large number of network indices are ranked according to their ability to discriminate the different coupling structures...
September 2016: Chaos
Benjamin W Mooneyham, Michael D Mrazek, Alissa J Mrazek, Kaita L Mrazek, Dawa T Phillips, Jonathan W Schooler
During tasks that require continuous engagement, the mind alternates between mental states of focused attention and mind-wandering. Existing research has assessed the functional connectivity of intrinsic brain networks underlying the experience and training of these mental states using "static" approaches that assess connectivity across an entire task. To disentangle the functional connectivity between brain regions as the mind fluctuates between discrete brain states, we employed a dynamic functional connectivity approach that characterized brain activity using a sliding window...
October 25, 2016: Journal of Cognitive Neuroscience
Alex I Wiesman, Elizabeth Heinrichs-Graham, Nathan M Coolidge, James E Gehringer, Max J Kurz, Tony W Wilson
Sensory gating (SG) is a phenomenon in which neuronal responses to subsequent similar stimuli are weaker, and is thought to be an important mechanism for preventing excessive environmental stimulation from overloading shared neural resources. Although gating has been demonstrated in multiple sensory systems, the neural dynamics and developmental trajectory underlying SG remain poorly understood. Herein, we adopt a data-driven approach to map the spectro-temporal amplitude and functional connectivity (FC) dynamics that support gating in the somatosensory system (somato-SG) in healthy children and adolescents using magnetoencephalography (MEG)...
October 25, 2016: Journal of Physiology
Jannetta S Steyn, Peter Andras
The temporal relationship between the activities of neurons in biological neural systems is critically important for the correct delivery of the functionality of these systems. Fine measurement of temporal relationships of neural activities using micro-electrodes is possible but this approach is very limited due to spatial constraints in the context of physiologically valid settings of neural systems. Optical imaging with voltage-sensitive dyes or calcium dyes can provide data about the activity patterns of many neurons in physiologically valid settings, but the data is relatively noisy...
October 24, 2016: Journal of Computational Neuroscience
Christoph Justen, Cornelia Herbert
So far, neurophysiological studies have investigated implicit and explicit self-related processing particularly for self-related stimuli such as the own face or name. The present study extends previous research to the implicit processing of self-related movement sounds and explores their spatio-temporal dynamics. Event-related potentials (ERPs) were assessed while participants (N = 12 healthy subjects) listened passively to previously recorded self- and other-related finger snapping sounds, presented either as deviants or standards during an oddball paradigm...
2016: Frontiers in Human Neuroscience
Jason S Nomi, Shruti Gopal Vij, Dina R Dajani, Rosa Steimke, Eswar Damaraju, Srinivas Rachakonda, Vince D Calhoun, Lucina Q Uddin
Despite extensive research into executive function (EF), the precise relationship between brain dynamics and flexible cognition remains unknown. Using a large, publicly available dataset (189 participants), we find that functional connections measured throughout 56minutes of resting state fMRI data comprise five distinct connectivity states. Elevated EF performance as measured outside of the scanner was associated with greater episodes of more frequently occurring connectivity states, and fewer episodes of less frequently occurring connectivity states...
October 21, 2016: NeuroImage
Dean R Freestone, Kelvin J Layton, Levin Kuhlmann, Mark J Cook
Data-driven model-based analysis of electrophysiological data is an emerging technique for understanding the mechanisms of seizures. Model-based analysis enables tracking of hidden brain states that are represented by the dynamics of neural mass models. Neural mass models describe the mean firing rates and mean membrane potentials of populations of neurons. Various neural mass models exist with different levels of complexity and realism. An ideal data-driven model-based analysis framework will incorporate the most realistic model possible, enabling accurate imaging of the physiological variables...
June 9, 2016: International Journal of Neural Systems
Byung-Chul Kim, Sung-Min Jun, So Yeon Kim, Yong-Dae Kwon, Sung Chul Choe, Eun-Chul Kim, Jae-Hyung Lee, Jinseok Kim, Jun-Kyo Farancis Suh, Yu-Shik Hwang
The in vitro generation of cell-based three dimensional (3D) nerve tissue is an attractive subject to improve graft survival and integration into host tissue for neural tissue regeneration or to model biological events in stem cell differentiation. Although 3D organotypic culture strategies are well established for 3D nerve tissue formation of pluripotent stem cells to study underlying biology in nerve development, cell-based nerve tissues have not been developed using human postnatal stem cells with therapeutic potential...
October 24, 2016: Biotechnology and Bioengineering
Sun-Hee Kim, Christos Faloutsos, Hyung-Jeong Yang, Seong-Whan Lee
We propose a nonlinear dynamic model for an invasive electroencephalogram analysis that learns the optimal parameters of the neural population model via the Levenberg-Marquardt algorithm. We introduce the crucial windows where the estimated parameters present patterns before seizure onset. The optimal parameters minimizes the error between the observed signal and the generated signal by the model. The proposed approach effectively discriminates between healthy signals and epileptic seizure signals. We evaluate the proposed method using an electroencephalogram dataset with normal and epileptic seizure sequences...
October 24, 2016: Journal of Integrative Neuroscience
Yuanhua Qiao, Xiaojie Liu, Jun Miao, Lijuan Duan
In this paper, a two-layer network is built to simulate the mechanism of visual selection and shifting based on the mapping dynamic model for instantaneous frequency. Unlike the differential equation model using limit cycle to simulate neuron oscillation, we build an instantaneous frequency mapping dynamic model to describe the change of the neuron frequency to avoid the difficulty of generating limit cycle. The activity of the neuron is rebuilt based on the instantaneous frequency and in this work, we use the first layer of neurons to implement image segmentation and the second layer of neurons to act as visual selector...
October 24, 2016: Journal of Integrative Neuroscience
Jennifer L Hoy, Iryna Yavorska, Michael Wehr, Cristopher M Niell
The ability to genetically identify and manipulate neural circuits in the mouse is rapidly advancing our understanding of visual processing in the mammalian brain [1, 2]. However, studies investigating the circuitry that underlies complex ethologically relevant visual behaviors in the mouse have been primarily restricted to fear responses [3-5]. Here, we show that a laboratory strain of mouse (Mus musculus, C57BL/6J) robustly pursues, captures, and consumes live insect prey and that vision is necessary for mice to perform the accurate orienting and approach behaviors leading to capture...
October 8, 2016: Current Biology: CB
Ming-Liang Wang, Wen-Bin Li
Traumatic brain injury (TBI) is closely related to increased incidence of cognitive impairment from the acute phase to chronic phase. At present, the pathological mechanism leading to cognitive impairment after TBI is still not fully understood. We hypothesize that neuron loss, diffuse axonal injury, microbleed, and blood-brain barrier (BBB) disruption altogether contribute to the development of cognitive impairment. Furthermore, the disruption of structural and functional neural network related to the cognitive function might bring about the final step in the occurrence of cognitive impairment after TBI...
November 15, 2016: Journal of the Neurological Sciences
Tianfang Jiang, Qian Sun, Shengdi Chen
Oxidative stress reflects an imbalance between the overproduction and incorporation of free radicals and the dynamic ability of a biosystem to detoxify reactive intermediates. Free radicals produced by oxidative stress are one of the common features in several experimental models of diseases. Free radicals affect both the structure and function of neural cells, and contribute to a wide range of neurodegenerative diseases, including Parkinson's disease and Alzheimer's disease. Although the precise mechanisms that result in the degeneration of neurons and the relevant pathological changes remain unclear, the crucial role of oxidative stress in the pathogenesis of neurodegenerative diseases is associated with several proteins (such as α-synuclein, DJ-1, Amyloid β and tau protein) and some signaling pathways (such as extracellular regulated protein kinases, phosphoinositide 3-kinase/Protein Kinase B pathway and extracellular signal-regulated kinases 1/2) that are tightly associated with the neural damage...
October 18, 2016: Progress in Neurobiology
Tom A Hummer, K Luan Phan, David W Kern, Martha K McClintock
Evidence suggests the putative human pheromone Δ4,16-androstadien-3-one (androstadienone), a natural component of human sweat, increases attention to emotional information when passively inhaled, even in minute amounts. However, the neural mechanisms underlying androstadienone's impact on the perception of emotional stimuli have not been clarified. To characterize how the compound modifies neural circuitry while attending to emotional information, 22 subjects (11 women) underwent two fMRI scanning sessions, one with an androstadienone solution and one with a carrier control solution alone on their upper lip...
September 29, 2016: Psychoneuroendocrinology
Ana Rolo, Sarah Escuin, Nicholas D E Greene, Andrew J Copp
Neural tube closure is an important morphogenetic event that involves dramatic reshaping of both neural and non-neural tissues. Rho GTPases are key cytoskeletal regulators involved in cell motility and in several developmental processes, and are thus expected to play pivotal roles in neurulation. Here, we discuss 2 recent studies that shed light on the roles of distinct Rho GTPases in different tissues during neurulation. RhoA plays an essential role in regulating actomyosin dynamics in the neural epithelium of the elevating neural folds, while Rac1 is required for the formation of cell protrusions in the non-neural surface ectoderm during neural fold fusion...
October 21, 2016: Small GTPases
Gergő Orbán, Pietro Berkes, József Fiser, Máté Lengyel
Neural responses in the visual cortex are variable, and there is now an abundance of data characterizing how the magnitude and structure of this variability depends on the stimulus. Current theories of cortical computation fail to account for these data; they either ignore variability altogether or only model its unstructured Poisson-like aspects. We develop a theory in which the cortex performs probabilistic inference such that population activity patterns represent statistical samples from the inferred probability distribution...
October 19, 2016: Neuron
Haitao Yu, Rishi R Dhingra, Thomas E Dick, Roberto Fernandez Galan
Neural activity generally displays irregular firing patterns even in circuits with apparently regular outputs, such as motor pattern generators, in which the output frequency fluctuates randomly around a mean value. This "circuit noise" is inherited from the random firing of single neurons, which emerges from stochastic ion-channel gating (channel noise), spontaneous neurotransmitter release, and its diffusion and binding to synaptic receptors. Here, we demonstrate how to expand conductance-based network models that are originally deterministic to include realistic, physiological noise, focusing on stochastic ion-channel gating...
October 19, 2016: Journal of Neurophysiology
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