Computational Neuroscience Commons^™

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

MODVIS Workshop

No abstract provided.

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 …

Analytical Modeling Of A Communication Channel Based On Subthreshold Stimulation Of Neurobiological Networks, Alireza Khodaei

School of Computing: Dissertations, Theses, and Student Research

The emergence of wearable and implantable machines manufactured artificially or synthesized biologically opens up a new horizon for patient-centered health services such as medical treatment, health monitoring, and rehabilitation with minimized costs and maximized popularity when provided remotely via the Internet. In particular, a swarm of machines at the scale of a single cell down to the nanoscale can be deployed in the body by the non-invasive or minimally invasive operation (e.g., swallowing and injection respectively) to perform various tasks. However, an individual machine is only able to perform basic tasks so it needs to exchange data with the others …

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 ℓ₁-norm onto the individual feature or the structure level of features to pursuit corresponding sparsity. However, the ℓ₁-norm penalty over-penalizes large coefficients and may incurs estimation bias. A number of non-convex penalties are proposed to reduce …

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 …

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 …

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 …

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

MODVIS Workshop

No abstract provided.

Synchronization Of Coupled Neurons Via Robust Feedback, Hector Puebla, Ricardo Aguilar-Lopez, Priti Kumar Roy

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Machine Learning Methods For Medical And Biological Image Computing, Rongjian Li

Computer Science Theses & Dissertations

Medical and biological imaging technologies provide valuable visualization information of structure and function for an organ from the level of individual molecules to the whole object. Brain is the most complex organ in body, and it increasingly attracts intense research attentions with the rapid development of medical and bio-logical imaging technologies. A massive amount of high-dimensional brain imaging data being generated makes the design of computational methods for efficient analysis on those images highly demanded. The current study of computational methods using hand-crafted features does not scale with the increasing number of brain images, hindering the pace of scientific discoveries …

Modelling Short-Latency Disparity-Vergence Eye Movements Under Dichoptic Unbalanced Stimulation, Agostino Gibaldi, Guido Maiello, Peter J. Bex, Silvio P. Sabatini

MODVIS Workshop

Vergence eye movements align the optical axes of our two eyes onto an object of interest, thus facilitating the binocular summation of the images projected onto the left and the right retinae into a single percept. Both the computational substrate and the functional behaviour of binocular vergence eye movements have been the topic of in depth investigation. Here, we attempt to bring together what is known about computation and function of vergence mechanism. To this aim, we evaluated of a biologically inspired model of horizontal and vertical vergence control, based on a network of V1 simple and complex cells. The …

Experimental And Computational Studies Of Cortical Neural Network Properties Through Signal Processing, Wesley Patrick Clawson

Graduate Theses and Dissertations

Previous studies, both theoretical and experimental, of network level dynamics in the cerebral cortex show evidence for a statistical phenomenon called criticality; a phenomenon originally studied in the context of phase transitions in physical systems and that is associated with favorable information processing in the context of the brain. The focus of this thesis is to expand upon past results with new experimentation and modeling to show a relationship between criticality and the ability to detect and discriminate sensory input. A line of theoretical work predicts maximal sensory discrimination as a functional benefit of criticality, which can then be characterized …

“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 …

Design, Programming, And User-Experience, Kaila G. Manca

Honors Scholar Theses

This thesis is a culmination of my individualized major in Human-Computer Interaction. As such, it showcases my knowledge of design, computer engineering, user-experience research, and puts into practice my background in psychology, com- munications, and neuroscience.

I provided full-service design and development for a web application to be used by the Digital Media and Design Department and their students.This process involved several iterations of user-experience research, testing, concepting, branding and strategy, ideation, and design. It lead to two products.

The first product is full-scale development and optimization of the web appli- cation.The web application adheres to best practices. It was …

Towards Closed-Loop Deep Brain Stimulation: Behavior Recognition From Human Stn, Soroush Niketeghad

Electronic Theses and Dissertations

Deep brain stimulation (DBS) provides significant therapeutic benefit for movement disorders such as Parkinson’s disease (PD). Current DBS devices lack real-time feedback (thus are open loop) and stimulation parameters are adjusted during scheduled visits with a clinician. A closed-loop DBS system may reduce power consumption and side effects by adjusting stimulation parameters based on patient’s behavior. Thus behavior detection is a major step in designing such systems. Various physiological signals can be used to recognize the behaviors. Subthalamic Nucleus (STN) Local field Potential (LFP) is a great candidate signal for the neural feedback, because it can be recorded from the …

The Development Of A Traumatic Brain Injury Bioreactor, Zachery Heller

Graduate Theses and Dissertations

Approximately 1.7 million Americans experience a traumatic brain injury (TBI) each year. Concussive injuries are a subset of TBI in which blows to the head cause the brain to collide against the interior of the skull. Damage to the neurons, supporting cells, and surrounding extra cellular matrix resulting from these collisions can lead to permanent physical, cognitive, and psychological impairment. We believe the prevalence and clinical significance of concussive injures warrants research investment. To study brain injury following TBI, in vivo models have been the gold standard for TBI experiments. Although a valuable research alternative, animals are expensive, raise ethical …

Network Dynamics Of Visual Naming, Christopher R. Conner

Dissertations and Theses (Open Access)

Recognition and naming of objects and actions are fundamental components of language. They involve several different systems working in coordination to accomplish a complex behavior. During visual naming, sensory and semantic processing are carried out by dedicated cortical substrates in the temporal and occipital lobes, while response selection and articulatory planning are handled by prefrontal cortex. Despite decades of research using lesion analysis, functional MRI and electro-encephalography, the precise dynamics involved remain unknown due to the inadequate spatio-temporal resolution of these methodologies. Of particular interest is the organization of semantic knowledge and the degree of serial and parallel organization of …

Low Cost Neurochairs, Frankie Pike

Master's Theses

Electroencephalography (EEG) was formerly confined to clinical and research settings with the necessary hardware costing thousands of dollars. In the last five years a number of companies have produced simple electroencephalograms, priced below $300 and available direct to consumers. These have stirred the imaginations of enthusiasts and brought the prospects of "thought-controlled" devices ever closer to reality. While these new devices were largely targeted at video games and toys, active research on enabling people suffering from debilitating diseases to control wheelchairs was being pursued. A number of neurochairs have come to fruition offering a truly hands-free mobility solution, but whether …

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 …