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Computational Neuroscience Commons

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Full-Text Articles in Computational Neuroscience

Virtual Reality (Vr)-Based Environmental Enrichment In Older Adults With Mild Cognitive Impairment (Mci) And Mild Dementia, Waleed Riaz, Zain Yar Khan, Ali Jawaid, Suleman Shahid Aug 2021

Virtual Reality (Vr)-Based Environmental Enrichment In Older Adults With Mild Cognitive Impairment (Mci) And Mild Dementia, Waleed Riaz, Zain Yar Khan, Ali Jawaid, Suleman Shahid

Medical College Documents

Background: Despite an alarming rise in the global prevalence of dementia, the available modalities for improving cognition and mental wellbeing of dementia patients remain limited. Environmental enrichment is an experimental paradigm that has shown promising anti-depressive and memory-enhancing effects in pre-clinical studies. However, its clinical utility has remained limited due to the lack of effective implementation strategies.
Objective: The primary objective of this study was to evaluate the usability (tolerability and interactivity) of a long-term virtual reality (VR)- based environmental enrichment training program in older adults with mild cognitive impairment (MCI) and mild dementia. A secondary objective was to assess …


Axonal Blockage With Microscopic Magnetic Stimulation, Hui Ye Oct 2020

Axonal Blockage With Microscopic Magnetic Stimulation, Hui Ye

Biology: Faculty Publications and Other Works

Numerous neurological dysfunctions are characterized by undesirable nerve activity. By providing reversible nerve blockage, electric stimulation with an implanted electrode holds promise in the treatment of these conditions. However, there are several limitations to its application, including poor bio-compatibility and decreased efficacy during chronic implantation. A magnetic coil of miniature size can mitigate some of these problems, by coating it with biocompatible material for chronic implantation. However, it is unknown if miniature coils could be effective in axonal blockage and, if so, what the underlying mechanisms are. Here we demonstrate that a submillimeter magnetic coil can reversibly block action potentials …


Review: Do The Different Sensory Areas Within The Cat Anterior Ectosylvian Sulcal Cortex Collectively Represent A Network Multisensory Hub?, M. Alex Meredith, Mark T. Wallace, H. Ruth Clemo Jan 2018

Review: Do The Different Sensory Areas Within The Cat Anterior Ectosylvian Sulcal Cortex Collectively Represent A Network Multisensory Hub?, M. Alex Meredith, Mark T. Wallace, H. Ruth Clemo

Anatomy and Neurobiology Publications

Current theory supports that the numerous functional areas of the cerebral cortex are organized and function as a network. Using connectional databases and computational approaches, the cerebral network has been demonstrated to exhibit a hierarchical structure composed of areas, clusters and, ultimately, hubs. Hubs are highly connected, higher-order regions that also facilitate communication between different sensory modalities. One region computationally identified network hub is the visual area of the Anterior Ectosylvian Sulcal cortex (AESc) of the cat. The Anterior Ectosylvian Visual area (AEV) is but one component of the AESc that also includes the auditory (Field of the Anterior Ectosylvian …


The Rhetoric Of Science Education And Technology, Iwasan D. Kejawa Jan 2018

The Rhetoric Of Science Education And Technology, Iwasan D. Kejawa

School of Computing: Faculty Publications

Nearly thousands of science experiments are performed both on humans and animals every year in the United States (Gregory, 1999). Does Science enormously play a role in the well-beings of individual in the society? Research has found that science education is through motivation and satisfying the needs of humans. The scientific world is part of an elongated human development. This can be substantiated with the use and evolution of TECHNOLOGY and SCIENCE (Minton, 2004). Education of the entities that comprise the need to achieve the goal of TECHNOLOGY and SCIENCE which are important issues of today. Research has shown that …


Pattern Discovery In Brain Imaging Genetics Via Scca Modeling With A Generic Non-Convex Penalty, Lei Du, Kefei Liu, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen, Michael W. Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, John Morris, Leslie M. Shaw, Zaven Khachaturian, Greg Sorensen, Maria Carrillo, Lew Kuller, Marc Raichle, Steven Paul, Peter Davies, Howard Fillit, Franz Hefti, David Holtzman, Charles D. Smith, Gregory Jicha, Peter A. Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad Oct 2017

Pattern Discovery In Brain Imaging Genetics Via Scca Modeling With A Generic Non-Convex Penalty, Lei Du, Kefei Liu, Xiaohui Yao, Jingwen Yan, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen, Michael W. Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, John Morris, Leslie M. Shaw, Zaven Khachaturian, Greg Sorensen, Maria Carrillo, Lew Kuller, Marc Raichle, Steven Paul, Peter Davies, Howard Fillit, Franz Hefti, David Holtzman, Charles D. Smith, Gregory Jicha, Peter A. Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad

Neurology Faculty Publications

Brain imaging genetics intends to uncover associations between genetic markers and neuroimaging quantitative traits. Sparse canonical correlation analysis (SCCA) can discover bi-multivariate associations and select relevant features, and is becoming popular in imaging genetic studies. The L1-norm function is not only convex, but also singular at the origin, which is a necessary condition for sparsity. Thus most SCCA methods impose 1-norm onto the individual feature or the structure level of features to pursuit corresponding sparsity. However, the 1-norm penalty over-penalizes large coefficients and may incurs estimation bias. A number of non-convex penalties are proposed to reduce …


The Brain Imaging Data Structure, A Format For Organizing And Describing Outputs Of Neuroimaging Experiments, Krzysztof Gorgolewski, Tibor Auer, Vince Calhoun, R Cameron Craddock, Samir Das, Eugene Duff, Guillaume Flandin, Tristan Glatard, Yaroslav Halchenko Jun 2016

The Brain Imaging Data Structure, A Format For Organizing And Describing Outputs Of Neuroimaging Experiments, Krzysztof Gorgolewski, Tibor Auer, Vince Calhoun, R Cameron Craddock, Samir Das, Eugene Duff, Guillaume Flandin, Tristan Glatard, Yaroslav Halchenko

Dartmouth Scholarship

The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this …


“My Logic Is Undeniable”: Replicating The Brain For Ideal Artificial Intelligence, Samuel C. Adams Apr 2016

“My Logic Is Undeniable”: Replicating The Brain For Ideal Artificial Intelligence, Samuel C. Adams

Senior Honors Theses

Alan Turing asked if machines can think, but intelligence is more than logic and reason. I ask if a machine can feel pain or joy, have visions and dreams, or paint a masterpiece. The human brain sets the bar high, and despite our progress, artificial intelligence has a long way to go. Studying neurology from a software engineer’s perspective reveals numerous uncanny similarities between the functionality of the brain and that of a computer. If the brain is a biological computer, then it is the embodiment of artificial intelligence beyond anything we have yet achieved, and its architecture is advanced …


Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang Feb 2016

Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang

COBRA Preprint Series

Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …


Pathological Effects Of Repeated Concussive Tbi In Mouse Models: Periventricular Damage And Ventriculomegaly, Richard H. Wolferz Jr. May 2015

Pathological Effects Of Repeated Concussive Tbi In Mouse Models: Periventricular Damage And Ventriculomegaly, Richard H. Wolferz Jr.

Honors Scholar Theses

Repeated concussive traumatic brain injury (rcTBI) is the most prominent form of head injury affecting the brain, with an estimated 1.7 million Americans affected each year (Kuhn 2012). Neurologists have been concerned about the danger of repeated head impacts since the 1920’s, but researchers have only begun to understand the long-term effects of rcTBI (McKee 2009). Although symptoms can be as mild as dizziness, current research suggests that multiple concussions can lead to a progressive degenerative brain disease known as chronic traumatic encephalopathy (CTE) (Luo 2008, McKee 2009, Kane 2013). Research on the brain is just beginning to scratch the …


Rescuing Acetylcholinesterase From Nerve Agent Inhibition: Protein Dynamics Driven Drug Discovery, Aiyana M. Emigh, Brian Bennion Jan 2013

Rescuing Acetylcholinesterase From Nerve Agent Inhibition: Protein Dynamics Driven Drug Discovery, Aiyana M. Emigh, Brian Bennion

STAR Program Research Presentations

Severe morbidity and mortality consequences result from irreversible inhibition of human acetylcholinesterase by organophosphates (OPs). Oxime-based reactivators are currently the only available treatments but lack efficacy in the central nervous system (CNS) where the most damage occurs. Computational docking and molecular dynamics (MD) simulations reveal complex structural barriers that may reduce oxime efficacy. These results may guide future drug designs of more effective countermeasures.


A Model Of Intracellular Θ Phase Precession Dependent On Intrinsic Subthreshold Membrane Currents., L Stan Leung Aug 2011

A Model Of Intracellular Θ Phase Precession Dependent On Intrinsic Subthreshold Membrane Currents., L Stan Leung

Physiology and Pharmacology Publications

A hippocampal place cell fires at an increasingly earlier phase in relation to the extracellular theta rhythm as a rodent moves through the place field. The present report presents a compartment model of a CA1 pyramidal cell that explains the increase in amplitude and the phase precession of intracellular theta oscillations, with the assumption that the cell receives an asymmetric ramp depolarization (<10 >mV) in the place field and rhythmic inhibitory and/or excitatory synaptic driving. Intracellular subthreshold membrane potential oscillations (MPOs) increase in amplitude and frequency, and show phase precession within the place field. Theta phase precession and MPO power …


Fuzzy Logic: A “Simple” Solution For Complexities In Neurosciences?, Saniya Siraj Godil, Muhammad Shahzad Shamim, Ather Enam, Uvais Qidwai Feb 2011

Fuzzy Logic: A “Simple” Solution For Complexities In Neurosciences?, Saniya Siraj Godil, Muhammad Shahzad Shamim, Ather Enam, Uvais Qidwai

Medical College Documents

Background: Fuzzy logic is a multi-valued logic which is similar to human thinking and interpretation. It has the potential of combining human heuristics into computer-assisted decision making, which is applicable to individual patients as it takes into account all the factors and complexities of individuals. Fuzzy logic has been applied in all disciplines of medicine in some form and recently its applicability in neurosciences has also gained momentum.
Methods: This review focuses on the use of this concept in various branches of neurosciences including basic neuroscience, neurology, neurosurgery, psychiatry and psychology.
Results: The applicability of fuzzy logic is not limited …


Robust Dynamic Balance Of Ap-1 Transcription Factors In A Neuronal Gene Regulatory Network., Gregory M Miller, Babatunde A Ogunnaike, James S Schwaber, Rajanikanth Vadigepalli Jan 2010

Robust Dynamic Balance Of Ap-1 Transcription Factors In A Neuronal Gene Regulatory Network., Gregory M Miller, Babatunde A Ogunnaike, James S Schwaber, Rajanikanth Vadigepalli

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

BACKGROUND: The octapeptide Angiotensin II is a key hormone that acts via its receptor AT1R in the brainstem to modulate the blood pressure control circuits and thus plays a central role in the cardiac and respiratory homeostasis. This modulation occurs via activation of a complex network of signaling proteins and transcription factors, leading to changes in levels of key genes and proteins. AT1R initiated activity in the nucleus tractus solitarius (NTS), which regulates blood pressure, has been the subject of extensive molecular analysis. But the adaptive network interactions in the NTS response to AT1R, plausibly related to the development of …