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Articles 1 - 22 of 22
Full-Text Articles in Computational Neuroscience
Temperature Alters The Amplitude Ratios Of Extracellularly Recorded Action Potentials, Marissa Cruz
Temperature Alters The Amplitude Ratios Of Extracellularly Recorded Action Potentials, Marissa Cruz
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Fleshing Out The Details: Towards A Biologically Realistic Learning Algorithm, Douglas Ryan Schuweiler, Paul A. Garris
Fleshing Out The Details: Towards A Biologically Realistic Learning Algorithm, Douglas Ryan Schuweiler, Paul A. Garris
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
A Critical Firing Rate In Synchronous Transitions Of Coupled Neurons, Annabelle Shaffer, Epaminondas Rosa, Rosangela Follmann
A Critical Firing Rate In Synchronous Transitions Of Coupled Neurons, Annabelle Shaffer, Epaminondas Rosa, Rosangela Follmann
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
A Spatial Stochastic Model Of Ampar Trafficking And Subunit Dynamics, Tyler Vandyk, Matthew C. Pharris, Tamara L. Kinzer-Ursem
A Spatial Stochastic Model Of Ampar Trafficking And Subunit Dynamics, Tyler Vandyk, Matthew C. Pharris, Tamara L. Kinzer-Ursem
The Summer Undergraduate Research Fellowship (SURF) Symposium
In excitatory neurons, the ability of a synaptic connection to strengthen or weaken is known as synaptic plasticity and is thought to be the cellular basis for learning and memory. Understanding the mechanism of synaptic plasticity is an important step towards understanding and developing treatment methods for learning and memory disorders. A key molecular process in synaptic plasticity for mammalian glutamatergic neurons is the exocytosis (delivery to the synapse) of AMPA-type glutamate receptors (AMPARs). While the protein signaling pathways responsible for exocytosis have long been investigated with experimental methods, it remains unreasonable to study the system in its full complexity …
Predictive Power And Validity Of Connectome Predictive Modeling: A Replication And Extension, Michael Wang, Joaquin Goni, Enrico Amico
Predictive Power And Validity Of Connectome Predictive Modeling: A Replication And Extension, Michael Wang, Joaquin Goni, Enrico Amico
The Summer Undergraduate Research Fellowship (SURF) Symposium
Neuroimaging, particularly functional magnetic resonance imaging (fMRI), is a rapidly growing research area and has applications ranging from disease classification to understanding neural development. With new advancements in imaging technology, researchers must employ new techniques to accommodate the influx of high resolution data sets. Here, we replicate a new technique: connectome-based predictive modeling (CPM), which constructs a linear predictive model of brain connectivity and behavior. CPM’s advantages over classic machine learning techniques include its relative ease of implementation and transparency compared to “black box” opaqueness and complexity. Is this method efficient, powerful, and reliable in the prediction of behavioral measures …
Balanced Excitation And Inhibition Shapes The Dynamics Of A Neuronal Network For Movement And Reward, Anca R. Radulescu
Balanced Excitation And Inhibition Shapes The Dynamics Of A Neuronal Network For Movement And Reward, Anca R. Radulescu
Biology and Medicine Through Mathematics Conference
No abstract provided.
Central And Peripheral Difference In Perceptual Bias In Ambiguous Perception Using Dichoptic Stimuli --- Implications For The Analysis-By-Synthesis Process In Visual Recognition, Li Zhaoping Prof
MODVIS Workshop
No abstract provided.
Predicting Fixations From Deep And Low-Level Features, Matthias Kümmerer, Thomas S.A. Wallis, Leon A. Gatys, Matthias Bethge
Predicting Fixations From Deep And Low-Level Features, Matthias Kümmerer, Thomas S.A. Wallis, Leon A. Gatys, Matthias Bethge
MODVIS Workshop
Learning what properties of an image are associated with human gaze placement is important both for understanding how biological systems explore the environment and for computer vision applications. Recent advances in deep learning for the first time enable us to explain a significant portion of the information expressed in the spatial fixation structure. Our saliency model DeepGaze II uses the VGG network (trained on object recognition in the ImageNet challenge) to convert an image into a high-dimensional feature space which is then readout by a second very simple network to yield a density prediction. DeepGaze II is right now the …
Applying Fmri Complexity Analyses To The Single-Subject: A Case Study For Proposed Neurodiagnostics, Anca R. Radulescu, Emily R. Hannon
Applying Fmri Complexity Analyses To The Single-Subject: A Case Study For Proposed Neurodiagnostics, Anca R. Radulescu, Emily R. Hannon
Biology and Medicine Through Mathematics Conference
No abstract provided.
An Interdisciplinary Approach To Computational Neurostimulation, Madison Guitard
An Interdisciplinary Approach To Computational Neurostimulation, Madison Guitard
Biology and Medicine Through Mathematics Conference
No abstract provided.
Neural Computation Of Statistical Image Properties In Peripheral Vision, Christoph Zetzsche, Ruth Rosenholtz, Noshaba Cheema, Konrad Gadzicki, Lex Fridman
Neural Computation Of Statistical Image Properties In Peripheral Vision, Christoph Zetzsche, Ruth Rosenholtz, Noshaba Cheema, Konrad Gadzicki, Lex Fridman
MODVIS Workshop
No abstract provided.
Similarity-Based Fusion Of Meg And Fmri Discerns Early Feedforward And Feedback Processing In The Ventral Stream, Yalda Mohsenzadeh Dr., Radoslaw Martin Cichy Dr., Aude Oliva Dr., Dimitrios Pantazis Dr.
Similarity-Based Fusion Of Meg And Fmri Discerns Early Feedforward And Feedback Processing In The Ventral Stream, Yalda Mohsenzadeh Dr., Radoslaw Martin Cichy Dr., Aude Oliva Dr., Dimitrios Pantazis Dr.
MODVIS Workshop
Successful models of vision, such as DNNs and HMAX, are inspired by the human visual system, relying on a hierarchical cascade of feedforward transformations akin to the ventral stream. Despite these advances, the human visual cortex remains unique in complexity, with feedforward and feedback pathways characterized by rapid spatiotemporal dynamics as visual information is transformed into semantic content. Thus, a systematic characterization of the spatiotemporal and representational space of the ventral visual pathway can offer novel insights in the duration and sequencing of cognitive processes, suggesting computational constraints and new architectures for computer vision models.
To discern the feedforward and …
Using Classification Images To Understand Models Of Lightness Perception, Minjung Kim, Jason M. Gold, Richard F. Murray
Using Classification Images To Understand Models Of Lightness Perception, Minjung Kim, Jason M. Gold, Richard F. Murray
MODVIS Workshop
No abstract provided.
Modeling Accommodation Control Of The Human Eye: Chromatic Aberration And Color Opponency, Agostino Gibaldi, Steven A. Cholewiak, Marty S. Banks
Modeling Accommodation Control Of The Human Eye: Chromatic Aberration And Color Opponency, Agostino Gibaldi, Steven A. Cholewiak, Marty S. Banks
MODVIS Workshop
Accommodation is the process by which the eye lens changes optical power to maintain a clear retinal image as the distance to the fixated object varies. Although luminance blur has long been considered the driving feature for accommodation, it is by definition unsigned (i.e., there is no difference between the defocus of an object closer or farther than the focus distance). Nonetheless, the visual system initially accommodates in the correct direction, implying that it exploits a cue with sign information. Here, we present a model of accommodation control based on such a cue: Longitudinal Chromatic Aberration (LCA). The model relies …
Can Cone Signals In The Wild Be Predicted From The Past?, David H. Foster, Iván Marín-Franch
Can Cone Signals In The Wild Be Predicted From The Past?, David H. Foster, Iván Marín-Franch
MODVIS Workshop
In the natural world, the past is usually a good guide to the future. If light from the sun and sky is blue earlier in the day and yellow now, then it is likely to be more yellow later, as the sun's elevation decreases. But is the light reflected from a scene into the eye as predictable as the light incident upon the scene, especially when lighting changes are not just spectral but include changes in local shadows and mutual reflections? The aim of this work was to test the predictability of cone photoreceptor signals in the wild over the …
Role Of The Cost Of Plasticity In Determining The Features Of Fast Vision In Humans., Maria M. Del Viva Phd, Renato Budinich M. Sc, Laura Palmieri M. Sc, Vladimir S Georgiev Phd, Giovanni Punzi Phd
Role Of The Cost Of Plasticity In Determining The Features Of Fast Vision In Humans., Maria M. Del Viva Phd, Renato Budinich M. Sc, Laura Palmieri M. Sc, Vladimir S Georgiev Phd, Giovanni Punzi Phd
MODVIS Workshop
No abstract provided.
Heuristics From Statistics—Modeling The Behavior And Perception Of Non-Rigid Materials, Vivian C. Paulun, Roland W. Fleming
Heuristics From Statistics—Modeling The Behavior And Perception Of Non-Rigid Materials, Vivian C. Paulun, Roland W. Fleming
MODVIS Workshop
No abstract provided.
Modelling Grip Point Selection In Human Precision Grip, Guido Maiello, Lina Klein, Vivian C. Paulun, Roland W. Fleming
Modelling Grip Point Selection In Human Precision Grip, Guido Maiello, Lina Klein, Vivian C. Paulun, Roland W. Fleming
MODVIS Workshop
No abstract provided.
Comparing Diverse V1 Models On The Same Platform: Virtual V1sion, Cheryl Olman
Comparing Diverse V1 Models On The Same Platform: Virtual V1sion, Cheryl Olman
MODVIS Workshop
No abstract provided.
Unifying Binocular, Spatial, And Spatio-Temporal Frequency Integration In Models Of Mt Neurons, Pamela M. Baker, Wyeth Bair
Unifying Binocular, Spatial, And Spatio-Temporal Frequency Integration In Models Of Mt Neurons, Pamela M. Baker, Wyeth Bair
MODVIS Workshop
No abstract provided.
Evaluating And Interpreting A Convolutional Neural Net As A Model Of V4, Dean A. Pospisil, Anitha Pasupathy, Wyeth Bair
Evaluating And Interpreting A Convolutional Neural Net As A Model Of V4, Dean A. Pospisil, Anitha Pasupathy, Wyeth Bair
MODVIS Workshop
Convolutional neural nets (CNNs) are currently the highest performing image recognition computer algorithms. Of interest is whether these CNNs, following extensive supervised training, perform computations similar to those in the ventral visual stream. We investigated whether CNN units’ tuning for shape boundaries was similar to V4’s as described in the angular position and curvature (APC) model of Pasupathy and Connor 2001. From units in all layers of AlexNet (see Figure A), an object recognition CNN, we recorded responses to the original study’s set of shape stimuli (51 simple closed shapes at up to 8 rotations) presented at 51 spatial translations …
Gabor Limits And Hyper-Selectivity In The Tuning Of V1 Neurons, David J. Field, Kedarnath P. Vilankar
Gabor Limits And Hyper-Selectivity In The Tuning Of V1 Neurons, David J. Field, Kedarnath P. Vilankar
MODVIS Workshop
No abstract provided.