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Computational Neuroscience Commons

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340 Full-Text Articles 649 Authors 81,263 Downloads 56 Institutions

All Articles in Computational Neuroscience

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340 full-text articles. Page 1 of 14.

Mixed Mode Oscillations In Three-Timescale Coupled Morris-Lecar Neurons, NgocAnh Phan, Yangyang Wang 2022 University of Iowa

Mixed Mode Oscillations In Three-Timescale Coupled Morris-Lecar Neurons, Ngocanh Phan, Yangyang Wang

Biology and Medicine Through Mathematics Conference

No abstract provided.


Universality And Synchronization In Complex Quadratic Networks (Cqns), Anca R. Radulescu, Danae Evans 2022 State University of New York at New Paltz

Universality And Synchronization In Complex Quadratic Networks (Cqns), Anca R. Radulescu, Danae Evans

Biology and Medicine Through Mathematics Conference

No abstract provided.


Estimating Glutamate Transporter Surface Density In Mouse Hippocampal Astrocytes, Anca R. Radulescu, Annalisa Scimemi 2022 State University of New York at New Paltz

Estimating Glutamate Transporter Surface Density In Mouse Hippocampal Astrocytes, Anca R. Radulescu, Annalisa Scimemi

Biology and Medicine Through Mathematics Conference

No abstract provided.


Automated Fitting Of Allosteric Parameters In Receptor Oligomer Models, Spenser Wood 2022 William & Mary

Automated Fitting Of Allosteric Parameters In Receptor Oligomer Models, Spenser Wood

Biology and Medicine Through Mathematics Conference

No abstract provided.


Olfactory Bulb Processing Of Ortho Versus Retronasal Odors, Michelle F. Craft, Andrea Barreiro, Shree Gautam, Woodrow Shew, Cheng Ly 2022 Virginia Commonwealth University

Olfactory Bulb Processing Of Ortho Versus Retronasal Odors, Michelle F. Craft, Andrea Barreiro, Shree Gautam, Woodrow Shew, Cheng Ly

Biology and Medicine Through Mathematics Conference

No abstract provided.


Closed-Loop Brain-Computer Interfaces For Memory Restoration Using Deep Brain Stimulation, David Xiaoliang Wang 2022 Southern Methodist University

Closed-Loop Brain-Computer Interfaces For Memory Restoration Using Deep Brain Stimulation, David Xiaoliang Wang

Electrical Engineering Theses and Dissertations

The past two decades have witnessed the rapid growth of therapeutic brain-computer interfaces (BCI) targeting a diversity of brain dysfunctions. Among many neurosurgical procedures, deep brain stimulation (DBS) with neuromodulation technique has emerged as a fruitful treatment for neurodegenerative disorders such as epilepsy, Parkinson's disease, post-traumatic amnesia, and Alzheimer's disease, as well as neuropsychiatric disorders such as depression, obsessive-compulsive disorder, and schizophrenia. In parallel to the open-loop neuromodulation strategies for neuromotor disorders, recent investigations have demonstrated the superior performance of closed-loop neuromodulation systems for memory-relevant disorders due to the more sophisticated underlying brain circuitry during cognitive processes. Our ...


Validity Of Neural Distance Measures In Representational Similarity Analysis, Fabian A. Soto, Emily R. Martin, Hyeonjeong Lee, Nafiz Ahmed, Juan Estepa, Kianoosh Hosseini, Olivia A. Stibolt, Valentina Roldan, Alycia Winters, Mohammadreza Bayat 2022 Florida International University

Validity Of Neural Distance Measures In Representational Similarity Analysis, Fabian A. Soto, Emily R. Martin, Hyeonjeong Lee, Nafiz Ahmed, Juan Estepa, Kianoosh Hosseini, Olivia A. Stibolt, Valentina Roldan, Alycia Winters, Mohammadreza Bayat

MODVIS Workshop

No abstract provided.


Visual Expertise In An Anatomically-Inspired Model Of The Visual System, Garrison W. Cottrell, Martha Gahl, Shubham Kulkarni 2022 University of California, San Diego

Visual Expertise In An Anatomically-Inspired Model Of The Visual System, Garrison W. Cottrell, Martha Gahl, Shubham Kulkarni

MODVIS Workshop

We report on preliminary results of an anatomically-inspired deep learning model of the visual system and its role in explaining the face inversion effect. Contrary to the generally accepted wisdom, our hypothesis is that the face inversion effect can be accounted for by the representation in V1 combined with the reliance on the configuration of features due to face expertise. We take two features of the primate visual system into account: 1) The foveated retina; and 2) The log-polar mapping from retina to V1. We simulate acquisition of faces, etc., by gradually increasing the number of identities the network learns ...


Characterization Of Local And Global Statistics In Three Kinds Of Medical Images, And An Example Of Their Role In A Clinical Judgment, Jonathan Victor, Amanda Simon, Craig K. Abbey 2022 Weill Cornell Medical College

Characterization Of Local And Global Statistics In Three Kinds Of Medical Images, And An Example Of Their Role In A Clinical Judgment, Jonathan Victor, Amanda Simon, Craig K. Abbey

MODVIS Workshop

No abstract provided.


A Two-Layer Model Explains Higher-Order Feature Selectivity Of V2 Neurons, Timothy D. Oleskiw, Justin D. Lieber, J. Anthony Movshon, Eero P. Simoncelli 2022 New York University

A Two-Layer Model Explains Higher-Order Feature Selectivity Of V2 Neurons, Timothy D. Oleskiw, Justin D. Lieber, J. Anthony Movshon, Eero P. Simoncelli

MODVIS Workshop

Neurons in cortical area V2 respond selectively to higher-order visual features, such as the quasi-periodic structure of natural texture. However, a functional account of how V2 neurons build selectivity for complex natural image features from their inputs – V1 neurons locally tuned for orientation and spatial frequency – remains elusive.

We made single-unit recordings in area V2 in two fixating rhesus macaques. We presented stimuli composed of multiple superimposed grating patches that localize contrast energy in space, orientation, and scale. V2 activity is modeled via a two-layer linear-nonlinear network, optimized to use a sparse combination of V1-like outputs to account for observed ...


A Bayesian Account Of Depth From Shadow, James Elder, Patrick Cavanagh, Roberto Casati 2022 York University

A Bayesian Account Of Depth From Shadow, James Elder, Patrick Cavanagh, Roberto Casati

MODVIS Workshop

When an object casts a shadow on a background surface, the offset of the shadow can be a compelling cue to the relative depth between the object and the background (e.g., Kersten et al 1996, Fig. 1). Cavanagh et al (2021) found that, at least for small shadow offsets, perceived depth scales almost linearly with shadow offset. Here we ask whether this finding can be understood quantitatively in terms of Bayesian decision theory.

Estimating relative depth from shadow offset is complicated by the fact that the shadow offset is co-determined by the slant of the light source relative to ...


Fixational Eye Movements, Perceptual Filling-In, And Perceptual Fading Of Grayscale Images, Michael E. Rudd 2022 University of Nevada, Reno

Fixational Eye Movements, Perceptual Filling-In, And Perceptual Fading Of Grayscale Images, Michael E. Rudd

MODVIS Workshop

No abstract provided.


Constraining Computational Models Of Brightness Perception: What’S The Right Psychophysical Data?, Guillermo Aguilar, Joris Vincent, Marianne Maertens 2022 Technische Universitat Berlin

Constraining Computational Models Of Brightness Perception: What’S The Right Psychophysical Data?, Guillermo Aguilar, Joris Vincent, Marianne Maertens

MODVIS Workshop

No abstract provided.


Identifying And Localizing Multiple Objects Using Artificial Ventral And Dorsal Visual Cortical Pathways, Zhixian Han, Anne Sereno 2022 Purdue University

Identifying And Localizing Multiple Objects Using Artificial Ventral And Dorsal Visual Cortical Pathways, Zhixian Han, Anne Sereno

MODVIS Workshop

We concluded in our previous study that model cortical visual pathways actively retained information differently according to the different goals of the training tasks. One limitation of our study was that there was only one object in each input image whereas in reality there may be multiple objects in a scene. In our current study, we try to find a brain-like algorithm that can recognize and localize multiple objects.


Model Of Visual Contrast Gain Control And Pattern And Noise Masking, Joshua A. Solomon 2022 City, University of London

Model Of Visual Contrast Gain Control And Pattern And Noise Masking, Joshua A. Solomon

MODVIS Workshop

The first stage of the model can be subdivided into a global contrast sensitivity function (a 2-D log-parabolic filter of spatial frequency), followed by an array of sensors having Gabor-pattern receptive fields. The second stage is contrast gain control. At this stage, sensor outputs are subjected to an expansive transformation. Then the outputs are pooled and used to inhibit (or “normalize”) each other. Inhibition is strongest between sensors with similar preferences for orientation, spatial frequency and spatial location. In the final stage of the model, the nomalized sensor outputs for each image are subjected to Minkowski pooling. Two-alternative, forced-choice detection ...


Scale-Free Behavioral Dynamics Directly Linked With Scale-Free Cortical Dynamics, Sabrina Jones 2022 University of Arkansas, Fayetteville

Scale-Free Behavioral Dynamics Directly Linked With Scale-Free Cortical Dynamics, Sabrina Jones

Physics Undergraduate Honors Theses

In organisms, an interesting phenomenon occurs in both behavior and neuronal activity: organization with fractal, scale-free fluctuations over multiple spatiotemporal orders of magnitude (1,2). In regard to behavior, this sort of complex structure-- which manifests itself from small scale fidgeting to purposeful, full body movements-- may support goals such as foraging (3-6), visual search (4), and decision making (7,8). Likewise, the presence of this sort of structure in the cerebral cortex in the form of spatiotemporal cascades, coined “neuronal avalanches,” may offer optimal information transfer (9). Thus, when considering the functional relationship between the cerebral cortex and movements ...


Ongoing Calculus In The Cerebral Cortex, Luke Long 2022 University of Arkansas, Fayetteville

Ongoing Calculus In The Cerebral Cortex, Luke Long

Physics Undergraduate Honors Theses

Various modes of neuronal computations have long been theorized to be possible based on the structure and geometry of the brain. These computations also seem necessary for many of the integral functions of the brain, like information processing and regulatory processes in the body. However, experimental data directly supporting these claims have been rare.

In this study, data collected in mice from a large number of neurons over a long period of time provided the opportunity to search for some of these computations, specifically change detection and squaring calculations. Using Matlab, the goal of this analysis was to find statistically ...


Modeling And Analyses Of Mechanisms Underlying Network Synaptic Dynamics In Two Neural Circuits, Linda Ma 2022 William & Mary

Modeling And Analyses Of Mechanisms Underlying Network Synaptic Dynamics In Two Neural Circuits, Linda Ma

Undergraduate Honors Theses

In systems neuroscience, circuit models of cortical structures can be used to deconstruct mechanisms responsible for spike patterns that generate a variety of behaviors observed in the brain. In particular, mathematical simulations of these circuits can replicate complex dynamical behaviors that mirror not only macroscopically patterns observed in the brain, but also a significant amount of experimentally characterized minutiae. These models are capable of analyzing neural mechanisms by explicitly deconstructing connectivities between populations of neurons in ways that tend to be empirically inaccessible. This work presents two such models; one in the rat somatosensory barrel cortex, responsible for processing sensory ...


Seizure Prediction In Epilepsy Patients, Gary Dean Cravens 2022 Nova Southeastern University

Seizure Prediction In Epilepsy Patients, Gary Dean Cravens

NSU REACH and IPE Day

Purpose/Objective: Characterize rigorously the preictal period in epilepsy patients to improve the development of seizure prediction techniques. Background/Rationale: 30% of epilepsy patients are not well-controlled on medications and would benefit immensely from reliable seizure prediction. Methods/Methodology: Computational model consisting of in-silico Hodgkin-Huxley neurons arranged in a small-world topology using the Watts-Strogatz algorithm is used to generate synthetic electrocorticographic (ECoG) signals. ECoG data from 18 epilepsy patients is used to validate the model. Unsupervised machine learning is used with both patient and synthetic data to identify potential electrophysiologic biomarkers of the preictal period. Results/Findings: The model has ...


Nonhematopoietic Erythropoietin: A Study Of Signaling, Structure, And Behavior, Nicholas John Pekas 2022 University of South Dakota

Nonhematopoietic Erythropoietin: A Study Of Signaling, Structure, And Behavior, Nicholas John Pekas

Dissertations and Theses

Erythropoietin (EPO) is a cytokine hormone known for initiating red blood cell proliferation by binding to its homodimer receptor (EPOR)2 in the bone marrow. Recent progress in neurobiology has shown that EPO also exerts robust neurotrophic and neuroprotective activity in the CNS. It is widely thought that EPO’s neurotrophic activity is centrally involved in its antidepressant and cognitive enhancing effects. However, EPO’s potent erythropoietic effects prevent it from being used in the clinic to treat psychiatric disorders. A chemically engineered non-erythropoietic derivative of EPO, carbamoylated EPO (CEPO), produces psychoactive effects without activating hematopoiesis. However, CEPO is expensive ...


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