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https://www.readbyqxmd.com/read/28445249/study-on-the-mechanisms-of-seizure-like-events-suppression-effect-by-electrical-stimulation-using-a-microelectrode-array
#1
Sora Ahn, Sumin Jo, Sang Beom Jun, Hyang Woon Lee, Seungjun Lee
In this paper, we studied the mechanisms underlying the suppression of seizure-like events (SLEs) by electrical stimulation. We conducted an in-vitro experiment using entorhinal cortex combined hippocampal slices and two convulsant drugs, bicuculline and 4-aminopyridine, to induce spontaneous SLEs. We used a microelectrode array to observe network dynamics over the entire hippocampal area simultaneously, including regions far from the stimulation site. We stimulated the entorhinal cortex region, which has been determined to be a focus of SLEs by Granger causality analysis of multichannel time series data, by an external electrode...
April 25, 2017: Neuroreport
https://www.readbyqxmd.com/read/28444633/distributed-representations-of-action-sequences-in-anterior-cingulate-cortex-a-recurrent-neural-network-approach
#2
Danesh Shahnazian, Clay B Holroyd
Anterior cingulate cortex (ACC) has been the subject of intense debate over the past 2 decades, but its specific computational function remains controversial. Here we present a simple computational model of ACC that incorporates distributed representations across a network of interconnected processing units. Based on the proposal that ACC is concerned with the execution of extended, goal-directed action sequences, we trained a recurrent neural network to predict each successive step of several sequences associated with multiple tasks...
April 25, 2017: Psychonomic Bulletin & Review
https://www.readbyqxmd.com/read/28443696/the-development-and-modelling-of-devices-and-paradigms-for-transcranial-magnetic-stimulation
#3
Stefan M Goetz, Zhi-De Deng
Magnetic stimulation is a non-invasive neurostimulation technique that can evoke action potentials and modulate neural circuits through induced electric fields. Biophysical models of magnetic stimulation have become a major driver for technological developments and the understanding of the mechanisms of magnetic neurostimulation and neuromodulation. Major technological developments involve stimulation coils with different spatial characteristics and pulse sources to control the pulse waveform. While early technological developments were the result of manual design and invention processes, there is a trend in both stimulation coil and pulse source design to mathematically optimize parameters with the help of computational models...
April 26, 2017: International Review of Psychiatry
https://www.readbyqxmd.com/read/28441410/creating-and-parameterizing-patient-specific-deep-brain-stimulation-pathway-activation-models-using-the-hyperdirect-pathway-as-an-example
#4
Kabilar Gunalan, Ashutosh Chaturvedi, Bryan Howell, Yuval Duchin, Scott F Lempka, Remi Patriat, Guillermo Sapiro, Noam Harel, Cameron C McIntyre
BACKGROUND: Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports. OBJECTIVE: Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation...
2017: PloS One
https://www.readbyqxmd.com/read/28441114/neural-circuitry-of-reward-prediction-error
#5
Mitsuko Watabe-Uchida, Neir Eshel, Naoshige Uchida
Dopamine neurons facilitate learning by calculating reward prediction error, or the difference between expected and actual reward. Despite two decades of research, it remains unclear how dopamine neurons make this calculation. Here we review studies that tackle this problem from a diverse set of approaches, from anatomy to electrophysiology to computational modeling and behavior. Several patterns emerge from this synthesis: that dopamine neurons themselves calculate reward prediction error, rather than inherit it passively from upstream regions; that they combine multiple separate and redundant inputs, which are themselves interconnected in a dense recurrent network; and that despite the complexity of inputs, the output from dopamine neurons is remarkably homogeneous and robust...
April 24, 2017: Annual Review of Neuroscience
https://www.readbyqxmd.com/read/28437460/an-aggregation-removal-model-for-the-formation-and-size-determination-of-post-synaptic-scaffold-domains
#6
Jonas Ranft, Leandro G Almeida, Pamela C Rodriguez, Antoine Triller, Vincent Hakim
The formation and stability of synapses are key questions in neuroscience. Post-synaptic domains have been classically conceived as resulting from local insertion and turnover of proteins at the synapse. However, insertion is likely to occur outside the post-synaptic domains and advances in single-molecule imaging have shown that proteins diffuse in the plane of the membrane prior to their accumulation at synapses. We quantitatively investigated this scenario using computer simulations and mathematical analysis, taking for definiteness the specific case of inhibitory synapse components, i...
April 24, 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28437426/representational-models-a-common-framework-for-understanding-encoding-pattern-component-and-representational-similarity-analysis
#7
Jörn Diedrichsen, Nikolaus Kriegeskorte
Representational models specify how activity patterns in populations of neurons (or, more generally, in multivariate brain-activity measurements) relate to sensory stimuli, motor responses, or cognitive processes. In an experimental context, representational models can be defined as hypotheses about the distribution of activity profiles across experimental conditions. Currently, three different methods are being used to test such hypotheses: encoding analysis, pattern component modeling (PCM), and representational similarity analysis (RSA)...
April 24, 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28432786/the-comprehensive-connectome-of-a-neural-substrate-for-on-motion-detection-in-drosophila
#8
Shin-Ya Takemura, Aljoscha Nern, Dmitri B Chklovskii, Louis K Scheffer, Gerald M Rubin, Ian A Meinertzhagen
Analysing computations in neural circuits often uses simplified models because the actual neuronal implementation is not known. For example, a problem in vision, how the eye detects image motion, has long been analysed using Hassenstein-Reichardt (HR) detector or Barlow-Levick (BL) models. These both simulate motion detection well, but the exact neuronal circuits undertaking these tasks remain elusive. We reconstructed a comprehensive connectome of the circuits of Drosophila's motion-sensing T4 cells using a novel EM technique...
April 22, 2017: ELife
https://www.readbyqxmd.com/read/28432423/note-on-the-coefficient-of-variations-of-neuronal-spike-trains
#9
Johannes Lengler, Angelika Steger
It is known that many neurons in the brain show spike trains with a coefficient of variation (CV) of the interspike times of approximately 1, thus resembling the properties of Poisson spike trains. Computational studies have been able to reproduce this phenomenon. However, the underlying models were too complex to be examined analytically. In this paper, we offer a simple model that shows the same effect but is accessible to an analytic treatment. The model is a random walk model with a reflecting barrier; we give explicit formulas for the CV in the regime of excess inhibition...
April 21, 2017: Biological Cybernetics
https://www.readbyqxmd.com/read/28432303/closed-loop-deep-brain-stimulation-by-pulsatile-delayed-feedback-with-increased-gap-between-pulse-phases
#10
Oleksandr V Popovych, Borys Lysyansky, Peter A Tass
Computationally it was shown that desynchronizing delayed feedback stimulation methods are effective closed-loop techniques for the control of synchronization in ensembles of interacting oscillators. We here computationally design stimulation signals for electrical stimulation of neuronal tissue that preserve the desynchronizing delayed feedback characteristics and comply with mandatory charge deposit-related safety requirements. For this, the amplitude of the high-frequency (HF) train of biphasic charge-balanced pulses used by the standard HF deep brain stimulation (DBS) is modulated by the smooth feedback signals...
April 21, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28431219/genetic-analysis-of-%C3%AE-synuclein-3-untranslated-region-and-its-corresponding-micrornas-in-relation-to-parkinson-s-compared-to-dementia-with-lewy-bodies
#11
Lidia Tagliafierro, Omolara-Chinue Glenn, Madison E Zamora, Thomas G Beach, Randy L Woltjer, Michael W Lutz, Ornit Chiba-Falek
INTRODUCTION: The α-synuclein (SNCA) gene has been implicated in the etiology of Parkinson's disease (PD) and dementia with Lewy bodies (DLB). METHODS: A computational analysis of SNCA 3' untranslated region to identify potential microRNA (miRNA) binding sites and quantitative real-time PCR to determine their expression in isogenic induced pluripotent stem cell-derived dopaminergic and cholinergic neurons as a model of PD and DLB, respectively, were performed. In addition, we performed a deep sequencing analysis of the SNCA 3' untranslated region of autopsy-confirmed cases of PD, DLB, and normal controls, followed by genetic association analysis of the identified variants...
April 18, 2017: Alzheimer's & Dementia: the Journal of the Alzheimer's Association
https://www.readbyqxmd.com/read/28427143/activity-induced-spontaneous-spikes-in-gabaergic-neurons-suppress-seizure-discharges-an-implication-of-computational-modeling
#12
Wei Lu, Jing Feng, Bo Wen, Kewei Wang, Jin-Hui Wang
BACKGROUND: Epilepsy, a prevalent neurological disorder, appears self-termination. The endogenous mechanism for seizure self-termination remains to be addressed in order to develop new strategies for epilepsy treatment. We aim to examine the role of activity-induced spontaneous spikes at GABAergic neurons as an endogenous mechanism in the seizure self-termination. METHODS AND RESULTS: Neuronal spikes were induced by depolarization pulses at cortical GABAergic neurons from temporal lobe epilepsy patients and mice, in which some of these neurons fired activity-induced spontaneous spikes...
February 23, 2017: Oncotarget
https://www.readbyqxmd.com/read/28422957/towards-a-theory-of-cortical-columns-from-spiking-neurons-to-interacting-neural-populations-of-finite-size
#13
Tilo Schwalger, Moritz Deger, Wulfram Gerstner
Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50-2000 neurons of the same type but different populations account for different neuron types...
April 19, 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28422669/bioinspired-approach-to-modeling-retinal-ganglion-cells-using-system-identification-techniques
#14
Philip J Vance, Gautham P Das, Dermot Kerr, Sonya A Coleman, T Martin McGinnity, Tim Gollisch, Jian K Liu
The processing capabilities of biological vision systems are still vastly superior to artificial vision, even though this has been an active area of research for over half a century. Current artificial vision techniques integrate many insights from biology yet they remain far-off the capabilities of animals and humans in terms of speed, power, and performance. A key aspect to modeling the human visual system is the ability to accurately model the behavior and computation within the retina. In particular, we focus on modeling the retinal ganglion cells (RGCs) as they convey the accumulated data of real world images as action potentials onto the visual cortex via the optic nerve...
April 12, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28422668/sensitivity-analysis-for-probabilistic-neural-network-structure-reduction
#15
Piotr A Kowalski, Maciej Kusy
In this paper, we propose the use of local sensitivity analysis (LSA) for the structure simplification of the probabilistic neural network (PNN). Three algorithms are introduced. The first algorithm applies LSA to the PNN input layer reduction by selecting significant features of input patterns. The second algorithm utilizes LSA to remove redundant pattern neurons of the network. The third algorithm combines the proposed two and constitutes the solution of how they can work together. PNN with a product kernel estimator is used, where each multiplicand computes a one-dimensional Cauchy function...
April 12, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28422667/modeling-and-analysis-of-beta-oscillations-in-the-basal-ganglia
#16
Chen Liu, Jiang Wang, Huiyan Li, Chris Fietkiewicz, Kenneth A Loparo
Enhanced beta (12-30 Hz) oscillatory activity in the basal ganglia (BG) is a prominent feature of the Parkinsonian state in animal models and in patients with Parkinson's disease. Increased beta oscillations are associated with severe dopaminergic striatal depletion. However, the mechanisms underlying these pathological beta oscillations remain elusive. Inspired by the experimental observation that only subsets of neurons within each nucleus in the BG exhibit oscillatory activities, a computational model of the BG-thalamus neuronal network is proposed, which is characterized by subdivided nuclei within the BG...
April 12, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28422010/synaptic-input-sequence-discrimination-on-behavioral-time-scales-mediated-by-reaction-diffusion-chemistry-in-dendrites
#17
Upinder Singh Bhalla
Sequences of events are ubiquitous in sensory, motor, and cognitive function. Key computational operations, including pattern recognition, event prediction, and plasticity, involve neural discrimination of spatio-temporal sequences. Here we show that synaptically-driven reaction-diffusion pathways on dendrites can perform sequence discrimination on behaviorally relevant time-scales. We used abstract signaling models to show that selectivity arises when inputs at successive locations are aligned with, and amplified by, propagating chemical waves triggered by previous inputs...
April 19, 2017: ELife
https://www.readbyqxmd.com/read/28418693/validating-the-predicted-effect-of-astemizole-and-ketoconazole-using-a-drosophila-model-of-parkinson-s-disease
#18
Katarzyna Styczyńska-Soczka, Luigi Zechini, Lysimachos Zografos
Parkinson's disease is a growing threat to an ever-ageing population. Despite progress in our understanding of the molecular and cellular mechanisms underlying the disease, all therapeutics currently available only act to improve symptoms and do not stop the disease process. It is therefore imperative that more effective drug discovery methods and approaches are developed, validated, and used for the discovery of disease-modifying treatments for Parkinson's. Drug repurposing has been recognized as being equally as promising as de novo drug discovery in the field of neurodegeneration and Parkinson's disease specifically...
April 2017: Assay and Drug Development Technologies
https://www.readbyqxmd.com/read/28417684/toward-a-multiscale-modeling-framework-for-understanding-serotonergic-function
#19
KongFatt Wong-Lin, Da-Hui Wang, Ahmed A Moustafa, Jeremiah Y Cohen, Kae Nakamura
Despite its importance in regulating emotion and mental wellbeing, the complex structure and function of the serotonergic system present formidable challenges toward understanding its mechanisms. In this paper, we review studies investigating the interactions between serotonergic and related brain systems and their behavior at multiple scales, with a focus on biologically-based computational modeling. We first discuss serotonergic intracellular signaling and neuronal excitability, followed by neuronal circuit and systems levels...
April 1, 2017: Journal of Psychopharmacology
https://www.readbyqxmd.com/read/28416630/common-microbehavioral-footprint-of-two-distinct-classes-of-conditioned-aversion
#20
Emmanouil Paisios, Annabell Rjosk, Evren Pamir, Michael Schleyer
Avoiding unfavorable situations is a vital skill and a constant task for any animal. Situations can be unfavorable because they feature something that the animal wants to escape from, or because they do not feature something that it seeks to obtain. We investigate whether the microbehavioral mechanisms by which these two classes of aversion come about are shared or distinct. We find that larval Drosophila avoid odors either previously associated with a punishment, or previously associated with the lack of a reward...
May 2017: Learning & Memory
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