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Neural Oscillations

Seiichiro Amemiya, A David Redish
During decision making, hippocampal activity encodes information sometimes about present and sometimes about potential future plans. The mechanisms underlying this transition remain unknown. Building on the evidence that gamma oscillations at different frequencies (low gamma [LG], 30-55 Hz; high gamma [HG], 60-90 Hz; and epsilon, 100-140 Hz) reflect inputs from different circuits, we identified how changes in those frequencies reflect different information-processing states. Using a unique noradrenergic manipulation by clonidine, which shifted both neural representations and gamma states, we found that future representations depended on gamma components...
March 20, 2018: Cell Reports
N Jmail, M Zaghdoud, A Hadriche, T Frikha, C Ben Amar, C Bénar
To define the neural networks responsible of an epileptic seizure, it is useful to perform advanced signal processing techniques. In this context, electrophysiological signals present three types of waves: oscillations, spikes, and a mixture of both. Recent studies show that spikes and oscillations should be separated properly in order to define the accurate neural connectivity during the pre-ictal, seizure and inter-ictal states. Retrieving oscillatory activity is a sensitive task due to the frequency overlap between oscillations and transient activities...
February 2018: Heliyon
Chia-Hsiung Cheng, Mei-Yin Lin, Shiou-Han Yang
Age-related deficiency in the top-down modulation of cognitive inhibition has been extensively documented, whereas the effects of age on a bottom-up or automatic operation of inhibitory function were less investigated. It is unknown that whether the older adults (OA)' reduced behavioral performance and neural responses are due to the insufficient bottom-up processes. Compared to behavioral assessments which have been widely used to examine the top-down control of response inhibition, electrophysiological recordings are more suitable to probe the early-stage processes of automatic inhibitory function...
2018: Frontiers in Aging Neuroscience
Rodrigo F O Pena, Sebastian Vellmer, Davide Bernardi, Antonio C Roque, Benjamin Lindner
Recurrent networks of spiking neurons can be in an asynchronous state characterized by low or absent cross-correlations and spike statistics which resemble those of cortical neurons. Although spatial correlations are negligible in this state, neurons can show pronounced temporal correlations in their spike trains that can be quantified by the autocorrelation function or the spike-train power spectrum. Depending on cellular and network parameters, correlations display diverse patterns (ranging from simple refractory-period effects and stochastic oscillations to slow fluctuations) and it is generally not well-understood how these dependencies come about...
2018: Frontiers in Computational Neuroscience
Frederic von Wegner, Helmut Laufs, Enzo Tagliazucchi
Long-range memory in time series is often quantified by the Hurst exponent H, a measure of the signal's variance across several time scales. We analyze neurophysiological time series from electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) resting state experiments with two standard Hurst exponent estimators and with the time-lagged mutual information function applied to discretized versions of the signals. A confidence interval for the mutual information function is obtained from surrogate Markov processes with equilibrium distribution and transition matrix identical to the underlying signal...
February 2018: Physical Review. E
Zhenyu Zhu, Rubin Wang, Fengyun Zhu
Based on the Hodgkin-Huxley model, the present study established a fully connected structural neural network to simulate the neural activity and energy consumption of the network by neural energy coding theory. The numerical simulation result showed that the periodicity of the network energy distribution was positively correlated to the number of neurons and coupling strength, but negatively correlated to signal transmitting delay. Moreover, a relationship was established between the energy distribution feature and the synchronous oscillation of the neural network, which showed that when the proportion of negative energy in power consumption curve was high, the synchronous oscillation of the neural network was apparent...
2018: Frontiers in Neuroscience
James P Roach, Aleksandra Pidde, Eitan Katz, Jiaxing Wu, Nicolette Ognjanovski, Sara J Aton, Michal R Zochowski
Network oscillations across and within brain areas are critical for learning and performance of memory tasks. While a large amount of work has focused on the generation of neural oscillations, their effect on neuronal populations' spiking activity and information encoding is less known. Here, we use computational modeling to demonstrate that a shift in resonance responses can interact with oscillating input to ensure that networks of neurons properly encode new information represented in external inputs to the weights of recurrent synaptic connections...
March 15, 2018: Proceedings of the National Academy of Sciences of the United States of America
Irene Navarro-Lobato, Lisa Genzel
Alternations of up and down can be seen across many different levels during sleep. Neural firing-rates, synaptic markers, molecular pathways, and gene expression all show differential up and down regulation across brain areas and sleep stages. And also the hallmarks of sleep - sleep stage specific oscillations - are characterized themselves by up and down as seen within the slow oscillation or theta cycles. In this review, we summarize the up and down of sleep covering molecules to electrophysiology and present different theories how this up and down could be regulated by the up and down of sleep oscillations...
March 12, 2018: Neurobiology of Learning and Memory
Hythem Sidky, Jonathan K Whitmer
Existing adaptive bias techniques, which seek to estimate free energies and physical properties from molecular simulations, are limited by their reliance on fixed kernels or basis sets which hinder their ability to efficiently conform to varied free energy landscapes. Further, user-specified parameters are in general non-intuitive yet significantly affect the convergence rate and accuracy of the free energy estimate. Here we propose a novel method, wherein artificial neural networks (ANNs) are used to develop an adaptive biasing potential which learns free energy landscapes...
March 14, 2018: Journal of Chemical Physics
Michela Balconi, Laura Gatti, Maria Elide Vanutelli
Cooperation behavior is a core question of study on social neuroscience. In the present study, inter-brain functional connectivity and cognitive performance were considered during joint which was failing. The cognitive performance and the EEG (brain oscillations from delta to beta) underlying the execution of joint-actions were recorded when dyads of participants executed synchronicity game and received reinforcing negative feedbacks A pre-feedback condition (cooperation) and a control condition (individual task, T0) were provided as well as a check for possible learning effect (time series analysis)...
March 12, 2018: Consciousness and Cognition
Stefan Elmer, Lutz Jäncke
Numerous studies have documented the behavioral advantages conferred on professional musicians and children undergoing music training in processing speech sounds varying in the spectral and temporal dimensions. These beneficial effects have previously often been associated with local functional and structural changes in the auditory cortex (AC). However, this perspective is oversimplified, in that it does not take into account the intrinsic organization of the human brain, namely, neural networks and oscillatory dynamics...
March 15, 2018: Annals of the New York Academy of Sciences
Timothée Proix, Viktor K Jirsa, Fabrice Bartolomei, Maxime Guye, Wilson Truccolo
Recent studies have shown that seizures can spread and terminate across brain areas via a rich diversity of spatiotemporal patterns. In particular, while the location of the seizure onset area is usually invariant across seizures in an individual patient, the source of traveling (2-3 Hz) spike-and-wave discharges during seizures can either move with the slower propagating ictal wavefront or remain stationary at the seizure onset area. Furthermore, although many focal seizures terminate synchronously across brain areas, some evolve into distinct ictal clusters and terminate asynchronously...
March 14, 2018: Nature Communications
Tianxiao Jiang, Su Liu, Giuseppe Pellizzer, Aydin Aydoseli, Sacit Karamursel, Pulat A Sabanci, Altay Sencer, Candan Gurses, Nuri F Ince
Functional mapping of eloquent cortex before the resection of a tumor is a critical procedure for optimizing survival and quality of life. In order to locate the hand area of the motor cortex in two patients with low-grade gliomas (LGG), we recorded electrocorticogram (ECoG) from a 113 channel hybrid high-density grid (64 large contacts with diameter of 2.7 mm and 49 small contacts with diameter of 1 mm) while they executed hand clenching movements. We investigated the spatio-spectral characteristics of the neural oscillatory activity and observed that, in both patients, the hand movements were consistently associated with a wide spread power decrease in the low frequency band (LFB: 8-32 Hz) and a more localized power increase in the high frequency band (HFB: 60-280 Hz) within the sensorimotor region...
2018: Frontiers in Neuroscience
Anastasia Greenberg, Javad Karimi Abadchi, Clayton T Dickson, Majid H Mohajerani
The signature rhythm of slow-wave forebrain activity is the large amplitude, slow oscillation (SO: ∼1 Hz) made up of alternating synchronous periods of activity and silence at the single cell and network levels. On each wave, the SO originates at a unique location and propagates across the neocortex. Attempts to manipulate SO activity using electrical fields have been shown to entrain cortical networks and enhance memory performance. However, neural activity during this manipulation has remained elusive due to methodological issues in typical electrical recordings...
March 10, 2018: NeuroImage
Nataliya Kraynyukova, Tatjana Tchumatchenko
A hallmark of cortical circuits is their versatility. They can perform multiple fundamental computations such as normalization, memory storage, and rhythm generation. Yet it is far from clear how such versatility can be achieved in a single circuit, given that specialized models are often needed to replicate each computation. Here, we show that the stabilized supralinear network (SSN) model, which was originally proposed for sensory integration phenomena such as contrast invariance, normalization, and surround suppression, can give rise to dynamic cortical features of working memory, persistent activity, and rhythm generation...
March 12, 2018: Proceedings of the National Academy of Sciences of the United States of America
Eline R Kupers, Helena X Wang, Kaoru Amano, Kendrick N Kay, David J Heeger, Jonathan Winawer
Currently, non-invasive methods for studying the human brain do not routinely and reliably measure spike-rate-dependent signals, independent of responses such as hemodynamic coupling (fMRI) and subthreshold neuronal synchrony (oscillations and event-related potentials). In contrast, invasive methods-microelectrode recordings and electrocorticography (ECoG)-have recently measured broadband power elevation in field potentials (~50-200 Hz) as a proxy for locally averaged spike rates. Here, we sought to detect and quantify stimulus-related broadband responses using magnetoencephalography (MEG)...
2018: PloS One
Marcel Heers, Moritz Helias, Tanguy Hedrich, Matthias Dümpelmann, Andreas Schulze-Bonhage, Tonio Ball
The foremost aim of presurgical epilepsy evaluation is the delineation of the seizure onset zone (SOZ). There is increasing evidence that fast epileptic activity (FEA, 14-250 Hz) occurring interictally, i.e. between seizures, is predominantly localized within the SOZ. Currently it is unknown, which frequency band of FEA performs best in identifying the SOZ, although prior studies suggest highest concordance of spectral changes with the SOZ for high frequency changes. We suspected that FEA reflects dampened oscillations in local cortical excitatory-inhibitory neural networks, and that interictal FEA in the SOZ is a consequence of reduced oscillatory damping...
2018: NeuroImage: Clinical
Tanmay Pal, Pranab Kumar Dutta, Srinivasu Maka
Periodic Breathing (PB) is a diseased condition of the cardiorespiratory system, and mathematically it is modelled as an oscillation. Modeling approaches replicate periodic oscillation in the minute ventilation due to a higher than normal gain of the feedback signals from the chemoreceptors coupled with a longer than normal latency in feedback, and do not consider the waxing-waning pattern of the oronasal airflow. In this work, a noted regulation model is extended by integrating respiratory mechanics and respiratory Central Pattern Generator (rCPG) model, using modulation-demodulation1 hypothesis...
March 8, 2018: Respiratory Physiology & Neurobiology
Elizabeth Heinrichs-Graham, Timothy J McDermott, Mackenzie S Mills, Alex I Wiesman, Yu-Ping Wang, Julia M Stephen, Vince D Calhoun, Tony W Wilson
Numerous studies connect beta oscillations in the motor cortices to volitional movement, and beta is known to be aberrant in multiple movement disorders. However, the dynamic interplay between these beta oscillations, motor performance, and spontaneous beta power (e.g., during rest) in the motor cortices remains unknown. This study utilized magnetoencephalography (MEG) to investigate these three parameters and their lifespan trajectory in 57 healthy participants aged 9-75 years old. Movement-related beta activity was imaged using a beamforming approach, and voxel time series data were extracted from the peak voxels in the primary motor cortices...
March 2, 2018: Developmental Cognitive Neuroscience
Matthew J Brookes, Madeleine J Groom, Lucrezia Liuzzi, Ryan M Hill, Helen J F Smith, Paul M Briley, Emma L Hall, Benjamin A E Hunt, Lauren E Gascoyne, Margot J Taylor, Peter F Liddle, Peter G Morris, Mark W Woolrich, Elizabeth B Liddle
Network connectivity is an integral feature of human brain function, and characterising its maturational trajectory is a critical step towards understanding healthy and atypical neurodevelopment. Here, we used magnetoencephalography (MEG) to investigate both stationary (i.e. time averaged) and rapidly modulating (dynamic) electrophysiological connectivity, in participants aged from mid-childhood to early adulthood (youngest participant 9 years old; oldest participant 25 years old). Stationary functional connectivity (measured via inter-regional coordination of neural oscillations) increased with age in the alpha and beta frequency bands, particularly in bilateral parietal and temporo-parietal connections...
March 7, 2018: NeuroImage
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