Neuroscience and Neurobiology Commons^™

Cortical Stimulation Mapping Of Heschl’S Gyrus In The Auditory Cortex For Tinnitus Treatment, Austin Huang

CMC Senior Theses

Tinnitus is the perception of sound in the absence of an actual sound stimulus. Recent developments have shifted the focus to the central nervous system and the neural correlate of tinnitus. Broadly, tinnitus involves cortical map rearrangement, pathological neural synchrony, and increased spontaneous firing rates. Various cortical regions, such as Heschl’s gyrus in the auditory cortex, have been found to be associated with different aspects of tinnitus, such as perception and loudness. I propose a cortical stimulation mapping study of Heschl’s gyrus using a depth and subdural electrode montage to conduct electrocorticography. This study would provide high-resolution data on abnormal …

Differentiation Of Neurons And Glia For Use In Cellular Connectomics, Jacob T. Brettin

Chancellor’s Honors Program Projects

No abstract provided.

Temporal Information Guides Prefrontal Preparatory Activity, Jacqueline R. Janowich

Shared Knowledge Conference

Proactive preparation for an upcoming goal differs from last-minute reactive adaptation, but it is unclear how preparatory mechanisms change based on when in the future a goal needs to be executed. To assess how timing information is integrated into preparatory control, we designed a novel variant of the Dot Pattern Expectancy task, where each cue signaled both task rule and delay duration (known short, known long, or unknown) between cue and probe. We recorded EEG while healthy young adult participants (n=36) performed this task, and found that delay demands elicited distinct prefrontal preparatory activities. Medial prefrontal amplitude was sensitive to …

Learning Expands The Preplanning Horizon In Finger Sequence Tasks, Neda Kordjazi

Electronic Thesis and Dissertation Repository

Many everyday skills involve the production of complex sequences of movements. However, the dynamics of the interplay between action selection and execution processes in sequential movements is poorly understood.Here, we set out to investigate the extent to which information regarding upcoming actions is utilized by the motor system to preplan into the future and furthermore, how this ability is influenced by learning. We designed a finger sequence taskwhere participants were shown only a fixed number of upcoming cues regarding future presses in every trial (viewing window, W). W varied between 1 (next digit revealed with pressing the current digit – …

Decision Making In A Changing Environment, Alan Veliz-Cuba

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Hopfield Networks: Modeling Memory, Maria Gabriela Navas Zuloaga

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Population Codes And Their Correlates In Decision Making, Neda Shahidi

Dissertations & Theses (Open Access)

This dissertation was organized in two parts: in part 1, we discussed Neural Correlates of Perceptual Accuracy” and in part 2 we discussed “Strategy encoding in Prefrontal Cortex”.

Abstract of part 1_The accurate transmission of electrical signals within neocortex is central to sensory perception and cognition. Theoretical studies have long proposed that the temporal coordination of cortical spiking activity controls signal transmission and cognitive function. In reality, whether and how the precise temporal coordination in neuronal populations during wakefulness influences perception remains a mystery. Here, we simultaneously recorded populations of neurons in early and mid-level visual cortex (areas V1 …

Finding Nonlinear Relationships In Functional Magnetic Resonance Imaging Data With Genetic Programming, James Hughes

Electronic Thesis and Dissertation Repository

The human brain is a complex, nonlinear dynamic chaotic system that is poorly understood. When faced with these difficult to understand systems, it is common to observe the system and develop models such that the underlying system might be deciphered. When observing neurological activity within the brain with functional magnetic resonance imaging (fMRI), it is common to develop linear models of functional connectivity; however, these models are incapable of describing the nonlinearities we know to exist within the system.

A genetic programming (GP) system was developed to perform symbolic regression on recorded fMRI data. Symbolic regression makes fewer assumptions than …

Mapping Molecular Datasets Back To The Brain Regions They Are Extracted From: Remembering The Native Countries Of Hypothalamic Expatriates And Refugees, Arshad M. Khan, Alice H. Grant, Anais Martinez, Gully Apc Burns, Brendan S. Thatcher, Vishwanath T. Anekonda, Benjamin W. Thompson, Zachary S. Roberts, Daniel H. Moralejo, James E. Blevins

Arshad M. Khan, Ph.D.

Social Experience Affects Decision Making And Learning: Empirical And Computational Analysis, Sungwoo Ahn

Biology and Medicine Through Mathematics Conference

No abstract provided.

Geometric Analysis Of Synchronization In Neuronal Networks With Global Inhibition And Coupling Delays, Hwayeon Ryu, Sue Ann Campbell

Biology and Medicine Through Mathematics Conference

No abstract provided.

‘Preferred’ Stimulus Of A Whole Model Visual System, Olivier Penacchio, Julie M. Harris

MODVIS Workshop

No abstract provided.

Finding Any Waldo: Zero-Shot Invariant And Efficient Visual Search, Gabriel Kreiman, Mengmi Zhang

MODVIS Workshop

Visual search constitutes a ubiquitous challenge in natural vision, including daily tasks such as finding a friend in a crowd or searching for a car in a parking lot. Visual search must fulfill four key properties: selectivity (to distinguish the target from distractors in a cluttered scene), invariance (to localize the target despite changes in its rotation, scale, illumination, and even searching for generic object categories), speed (to efficiently localize the target without exhaustive sampling), and generalization (to search for any object, even ones that we have had minimal or no experience with). Here we propose a computational model that …

Linking Signal Detection Theory And Encoding Models To Reveal Independent Neural Representations From Neuroimaging Data, Fabian A. Soto

MODVIS Workshop

No abstract provided.

Texture Statistics Are Sufficient For Ensemble Perception, Sasen S. Cain, Matthew S. Cain

MODVIS Workshop

No abstract provided.

Modeling Neural Computations In Lgn And Visual Cortex That Underlie Contextual Modulation Of Lightness And Darkness Magnitudes In Simple And Complex Images, Michael E. Rudd

MODVIS Workshop

No abstract provided.

Brightness Perception Involves Local Adaptation Opposed By Lateral Interaction, Qasim Zaidi, Romain Bachy, Jose-Manuel Alonso

MODVIS Workshop

No abstract provided.

The Road Towards Image-Computable Models Of Human Visual Grasp Planning, Guido Maiello, Lina K. Klein, Vivian C. Paulun, Katherine R. Storrs, Roland W. Fleming

MODVIS Workshop

No abstract provided.

A Feature-Based Model Of Visually Perceiving Deformable Objects, Vivian C. Paulun, Filipp Schmidt, Roland W. Fleming

MODVIS Workshop

No abstract provided.

Effect Of Noise On Mutually Inhibiting Pyramidal Cells In Visual Cortex: Foundation Of Stochasticity In Bi-Stable Perception, Naoki Kogo, Felix Kern, Thomas Nowotny, Raymond Van Ee, Richard Van Wezel, Takeshi Aihara

MODVIS Workshop

Bi-stable perception has been an important tool to investigate how visual input is interpreted and how it reaches consciousness. To explain the mechanisms of this phenomenon, it has been assumed that a mutual inhibition circuit plays a key role. It is possible that this circuit functions to resolve ambiguity of input image by quickly shifting the balance of competing signals in response to conflicting features. Recently we established an in vitro neural recording system combined with computerized connections mediated by model neurons and synapses (“dynamic clamp” system). With this system, mutual inhibition circuit between two pyramidal cells from primary visual …

Visual Category Learning By Means Of Basal Ganglia, Fred H. Hamker, Francesc Villagrasa, Javier Baladron, Henning Schroll, Julien Vitay

MODVIS Workshop

No abstract provided.

Why Latent Representations In Convolutional Neural Networks Fall Outside Visual Space, Katerina Malakhova

MODVIS Workshop

It is common to compare properties of visual information processing by artificial neural networks and the primate visual system.

Some remarkable similarities were observed in the responses of neurons in IT cortex and units in higher layers of CNNs. Here I show that latent representations formed by weights in convolutional layers do not necessarily reflect visual domain. Instead they are strongly dependent on a choice of training set and cost function.

The most striking example is when an individual unit, which is highly selective to some members of a category is, nevertheless, inhibited by visually similar objects of the same …

Appropriate Kernels For Divisive Normalization Explained By Wilson-Cowan Equations, Jesus Malo, Marcelo Bertalmio

MODVIS Workshop

Cascades of standard Linear+NonLinear-Divisive Normalization transforms [Carandini&Heeger12] can be easily fitted using the appropriate formulation introduced in [Martinez17a] to reproduce the perception of image distortion in naturalistic environments. However, consistently with [Rust&Movshon05], training the model in naturalistic environments does not guarantee the prediction of well known phenomena illustrated by artificial stimuli. For example, the cascade of Divisive Normalizations fitted with image quality databases has to be modified to include a variety aspects of masking of simple patterns. Specifically, the standard Gaussian kernels of [Watson&Solomon97] have to be augmented with extra weights [Martinez17b]. These can be introduced ad-hoc using the intuition …

Model Investigation On Contribution Of Feedback In Distortion Induced Motion Adaptation, Siegfried Wahl, Selam Habtegiorgis, Christian Jarvers, Katharina Rifai, Heiko Neumann

MODVIS Workshop

Motion information is processed in a neural circuit formed by synaptic organization of feedforward (FF) and feedback (FB) connections between different cortical areas. However, the contribution of a recurrent FB information to adaptation process is not well explored. Here, a biologically plausible neural model that predicts motion adaptation aftereffect (MAE) induced by exposure to geometrically skewed natural image sequences is suggested. The model constitutes two stage recurrent motion processing within cortical areas V1 and MT [1]. It comprises FF excitatory, FB modulatory and lateral inhibitory connections, and a fast and a slow adaptive synapse in the FF and FB streams, …

A Model Of 1d And 2d Motion Processing In The Primate Brain, Alan Johnston

MODVIS Workshop

Velocity encoding in the primate brain can be modelled by a spatiotemporal gradient approach, with neurons characterized as spatio-temporal derivative operators (Johnston et al. 1999). This strategy works well for moving 1D spatial patterns, but it can produce systematic errors, as it can be overly influenced by the direction of the local spatial gradient of the image brightness. For 2D pattern it is possible to develop a similar spatio-temporal approach, in which the system solves a set of over-determined linear equations directly, to provide an estimate for the 2D image motion. However, in this case the matrix one needs to …

An Active Efficient Coding Model Of The Development Of Amblyopia, Samuel Eckmann, Lukas Klimmasch, Bertram Shi, Jochen Triesch

MODVIS Workshop

No abstract provided.

Molecular Mechanism Of Early Amyloid Self-Assembly Revealed By Computational Modeling, Mohtadin Hashemi

Theses & Dissertations

Protein misfolding followed by the formation of aggregates, is an early step in the cascade of conformational changes in a protein that underlie the development of several neurodegenerative diseases, including Alzheimer’s and Parkinson’s diseases. Efforts aimed at understanding this process have produced little clarity and the mechanism remains elusive.

Here, we demonstrate that the hairpin fold, a structure found in the early folding intermediates of amyloid b, induces morphological and stability changes in the aggregates of Aβ(14-23) peptide. We structurally characterized the interactions of monomer and hairpin using extended molecular dynamics (MD) simulations, which revealed a novel intercalated type complex. …

Efficient Reduced Bias Genetic Algorithm For Generic Community Detection Objectives, Aditya Karnam Gururaj Rao

Theses

The problem of community structure identification has been an extensively investigated area for biology, physics, social sciences, and computer science in recent years for studying the properties of networks representing complex relationships. Most traditional methods, such as K-means and hierarchical clustering, are based on the assumption that communities have spherical configurations. Lately, Genetic Algorithms (GA) are being utilized for efficient community detection without imposing sphericity. GAs are machine learning methods which mimic natural selection and scale with the complexity of the network. However, traditional GA approaches employ a representation method that dramatically increases the solution space to be searched by …

Tinnitus And Dysfunctional Interactions Between Distributed Resting State Networks, Sivayini Kandeepan

Western Research Forum

It is known that peripheral lesions in the cochlea or the auditory nerve produce dysfunctional input to central auditory structures and induce changes in the auditory system causing tinnitus. Recently, it has been proposed that the unified percept of tinnitus could be considered as an emergent property of multiple overlapping dynamic brain networks, each encoding a specific tinnitus characteristic.

The aim of our study was to investigate the neuronal activation patterns associated with specific clinical tinnitus characteristics using fMRI. We hypothesize that tinnitus clinical characteristics could be associated with specific resting-state activity and connectivity patterns and that this could be …

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 …