Memory Consolidation In Binary Inputs,
2016
Georgia State University
Memory Consolidation In Binary Inputs, Shateil C. French Mr., Ricardo J T Toscano
Georgia State Undergraduate Research Conference
No abstract provided.
Multistability And Its Occurrence In Neurons Within The Pre-Bötzinger Complex,
2016
Georgia State University
Multistability And Its Occurrence In Neurons Within The Pre-Bötzinger Complex, Alex Vargas
Georgia State Undergraduate Research Conference
No abstract provided.
“My Logic Is Undeniable”: Replicating The Brain For Ideal Artificial Intelligence,
2016
Liberty University
“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,
2016
Fox Chase Cancer Center
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 …
Neuron Morphology Influences Axon Initial Segment Plasticity,
2016
Dartmouth College
Neuron Morphology Influences Axon Initial Segment Plasticity, Allan T. Gulledge, Jaime J. Bravo
Dartmouth Scholarship
In most vertebrate neurons, action potentials are initiated in the axon initial segment (AIS), a specialized region of the axon containing a high density of voltage-gated sodium and potassium channels. It has recently been proposed that neurons use plasticity of AIS length and/or location to regulate their intrinsic excitability. Here we quantify the impact of neuron morphology on AIS plasticity using computational models of simplified and realistic somatodendritic morphologies. In small neurons (e.g., dentate granule neurons), excitability was highest when the AIS was of intermediate length and located adjacent to the soma. Conversely, neurons having larger dendritic trees (e.g., pyramidal …
Scalar Short-Term Memory,
2016
Wilfrid Laurier University
Scalar Short-Term Memory, Tyler D. Bancroft
Theses and Dissertations (Comprehensive)
The location of the brain’s working and short-term memory (WM/STM) “system” is unclear. The existence of a dedicated WM/STM system is itself under debate. Recently, it has been proposed that WM/STM storage relies not on a dedicated system in prefrontal cortex, but rather that it is an emergent function of interaction between attentional and representational systems (e.g., sensory cortex) in the brain. However, mnemonic representations of very simple stimuli have repeatedly been shown to exist in frontal cortex. In this manuscript, I use computational and behavioural methods to demonstrate similarities between the representations of different types of very simple stimuli …
Analysis Of Neuronal Sequences Using Pairwise Biases,
2015
University of Nebraska-Lincoln
Analysis Of Neuronal Sequences Using Pairwise Biases, Zachary Roth
Department of Mathematics: Dissertations, Theses, and Student Research
Sequences of neuronal activation have long been implicated in a variety of brain functions. In particular, these sequences have been tied to memory formation and spatial navigation in the hippocampus, a region of mammalian brains. Traditionally, neuronal sequences have been interpreted as noisy manifestations of neuronal templates (i.e., orderings), ignoring much richer structure contained in the sequences. This paper introduces a new tool for understanding neuronal sequences: the bias matrix. The bias matrix captures the probabilistic tendency of each neuron to fire before or after each other neuron. Despite considering only pairs of neurons, the bias matrix captures the best …
The New York Head—A Precise Standardized Volume Conductor Model For Eeg Source Localization And Tes Targeting,
2015
CUNY City College
The New York Head—A Precise Standardized Volume Conductor Model For Eeg Source Localization And Tes Targeting, Yu Huang, Lucas C. Parra, Stefan Haufe
Publications and Research
In source localization of electroencephalograpic (EEG) signals, as well as in targeted transcranial electric current stimulation (tES), a volume conductor model is required to describe the flow of electric currents in the head. Boundary element models (BEM) can be readily computed to representmajor tissue compartments, but cannot encode detailed anatomical information within compartments. Finite element models (FEM) can capture more tissue types and intricate anatomical structures, but with the higher precision also comes the need for semiautomated segmentation, and a higher computational cost. In either case, adjusting to the individual human anatomy requires costlymagnetic resonance imaging (MRI), and thus head …
Predicting Phase Resetting Due To Multiple Stimuli,
2015
College of Charleston
Predicting Phase Resetting Due To Multiple Stimuli, Kelsey M. Vollmer, Davy C. Vanderweyen, Derek R. Tuck, Sorinel A. Oprisan
Journal of the South Carolina Academy of Science
We generalized the phase resetting curve (PRC) to a more realistic case of neural oscillators receiving two or more inputs per cycle. The PRC tabulates the transient change in the firing period of a neuron due to an external perturbation, such as a presynaptic stimulus. We used a conductance-based model neuron to estimate experimentally the two-stimulus PRC and compared the results against our mathematical prediction based on the assumption of instantaneous recurrent stimulation. Within the limits of the recurrent stimulation assumptions, we found that the newly introduced prediction for the two-stimulus PRC matched experimental measurements. Our new results open the …
Structure-Function Relationship Of The Brain: A Comparison Between The 2d Classical Ising Model And The Generalized Ising Model,
2015
The University of Western Ontario
Structure-Function Relationship Of The Brain: A Comparison Between The 2d Classical Ising Model And The Generalized Ising Model, Pubuditha M. Abeyasinghe
Electronic Thesis and Dissertation Repository
There is evidence that the functional patterns of the brain observed at rest using fMRI are sustained by a structural architecture of axonal fiber bundles. As neuroimaging techniques advance with time, the relationship between structure and function has become the object of many studies in neuroscience. As recently suggested, the well defined connectivity structure found in the brain can be used to understand the self organization of the brain at rest, as well as to infer the functional connectivity patterns of the brain using different models, such as the Kuramoto model which studies synchronization, and the 2-dimensional classical Ising model, …
Competitive Tuning Of Calmodulin Target Protein Activation Drives E-Ltp Induction In Ca1 Hippocampal Neurons,
2015
Purdue University
Competitive Tuning Of Calmodulin Target Protein Activation Drives E-Ltp Induction In Ca1 Hippocampal Neurons, Daniel R. Romano, Tamara L. Kinzer-Ursem
The Summer Undergraduate Research Fellowship (SURF) Symposium
A number of neurological disorders are caused by disruptions in dynamic neuronal connections called synapses. Normally, electrical activity between neurons activates protein cascades that cause long-lasting, localized changes in the structure and molecular composition of synapses. These changes either increase or decrease the strength of synaptic connections, leading to long-term-potentiation (LTP) or long-term-depression (LTD), respectively. The protein cascades responsible for this synaptic plasticity are initiated in a stimulus-dependent manner by the Ca2+ sensor calmodulin (CaM). Ultimately, it is disruptions within these signaling pathways that cause disease. Traditionally, these protein networks are studied in the laboratory, but limitations in existing …
Characterizing Receptive Field Selectivity In Area V2,
2015
New York University
Characterizing Receptive Field Selectivity In Area V2, Corey M. Ziemba, Robbe Lt Goris, J Anthony Movshon, Eero P. Simoncelli
MODVIS Workshop
The computations performed by neurons in area V1 are reasonably well understood, but computation in subsequent areas such as V2 have been more difficult to characterize. When stimulated with visual stimuli traditionally used to investigate V1, such as sinusoidal gratings, V2 neurons exhibit similar selectivity (but with larger receptive fields, and weaker responses) relative to V1 neurons. However, we find that V2 responses to synthetic stimuli designed to produce naturalistic patterns of joint activity in a model V1 population are more vigorous than responses to control stimuli that lacked this naturalistic structure (Freeman, et. al. 2013). Armed with this signature …
‘Edge’ Integration Explains Contrast And Assimilation In A Gradient Lightness Illusion,
2015
mrudd@u.washington.edu
‘Edge’ Integration Explains Contrast And Assimilation In A Gradient Lightness Illusion, Michael E. Rudd
MODVIS Workshop
In the ‘phantom’ illusion (Galmonte, Soranzo, Rudd, & Agostini, submitted), either an incremental or a decremental target, when surrounded by a luminance gradient, can to be made to appear as an increment or a decrement, depending on the gradient width. For wide gradients, incremental targets appear as increments and decremental targets appear as decrements. For narrow gradients, the reverse is true. Here, I model these phenomena with a two-stage neural lightness theory (Rudd, 2013, 2014) in which local steps in log luminance are first encoded by oriented spatial filters operating on a log-transformed version of the image; then the filter …
Time-Lapse Statistics Of Cone Signals From Natural Scenes,
2015
University of Manchester
Time-Lapse Statistics Of Cone Signals From Natural Scenes, David H. Foster, Kinjiro Amano, Sérgio M C Nascimento
MODVIS Workshop
In the natural world, the spectrum and geometry of the illumination from the sun and sky vary over the day. These geometric changes make it especially difficult to extract from the reflected light invariant signals for surface color perception. The aim of this study was to test the utility of certain combinations of retinal cone excitations, in particular, spatial cone-excitation ratios, known to be approximately invariant under non-geometric changes in illumination. Hyperspectral radiance images were acquired at roughly hourly intervals in four outdoor scenes in the Minho region of Portugal. Spatial resolution of the camera was 1344×1024 pixels. Peak-transmission wavelength …
The Bounded Log-Odds Model Of Frequency And Probability Distortion,
2015
Peking University
The Bounded Log-Odds Model Of Frequency And Probability Distortion, Hang Zhang, Laurence T. Maloney
MODVIS Workshop
No abstract provided.
Putting Saliency In Its Place,
2015
York University
Putting Saliency In Its Place, John K. Tsotsos
MODVIS Workshop
The role of attention and the place within the visual processing stream where the concept of saliency has been situated is critically examined by considering the experimental evidence and performing tests that link experiment to computation.
Towards A Unified Computational Model Of Contextual Interactions Across Visual Modalities,
2015
Brown University
Towards A Unified Computational Model Of Contextual Interactions Across Visual Modalities, David A. Mély, Thomas Serre
MODVIS Workshop
The perception of a stimulus is largely determined by its surrounding. Examples abound from color (Land and McCann, 1971), disparity (Westheimer, 1986) and motion induction (Anstis and Casco, 2006) to orientation tilt effects (O’Toole and Wenderoth, 1976). Some of these phenomena have been studied individually using monkey neurophysiology techniques. In these experiments, a center stimulus is typically used to probe a cell’s classical “center” receptive field (cRF), whose activity is then modulated by an annular “surround” (extra-cRF) stimulus. While this center-surround integration (CSI) has been well characterized, a theoretical framework which unifies these different phenomena across visual modalities is lacking. …
A Conceptual Framework Of Computations In Mid-Level Vision,
2015
University of Leuven
A Conceptual Framework Of Computations In Mid-Level Vision, Jonas Kubilius, Johan Wagemans, Hans P. Op De Beeck
MODVIS Workshop
The goal of visual processing is to extract information necessary for a variety of tasks, such as grasping objects, navigating in scenes, and recognizing them. While ultimately these tasks might be carried out by separate processing pathways, they nonetheless share a common root in the early and intermediate visual areas. What representations should these areas develop in order to facilitate all of these higher-level tasks? Several distinct ideas have received empirical support in the literature so far: (i) boundary feature detection, such as edge, corner, and curved segment extraction; (ii) second-order feature detection, such as the difference in orientation or …
Binocular 3d Motion Perception As Bayesian Inference,
2015
University of Glasgow
Binocular 3d Motion Perception As Bayesian Inference, Martin Lages, Suzanne Heron
MODVIS Workshop
The human visual system encodes monocular motion and binocular disparity input before it is integrated into a single 3D percept. Here we propose a geometric-statistical model of human 3D motion perception that solves the aperture problem in 3D by assuming that (i) velocity constraints arise from inverse projection of local 2D velocity constraints in a binocular viewing geometry, (ii) noise from monocular motion and binocular disparity processing is independent, and (iii) slower motions are more likely to occur than faster ones. In two experiments we found that instantiation of this Bayesian model can explain perceived 3D line motion direction under …
A Binocular Model For Motion Integration In Mt Neurons,
2015
University of Washington - Seattle Campus
A Binocular Model For Motion Integration In Mt Neurons, Pamela M. Baker, Wyeth Bair
MODVIS Workshop
Processing of visual motion by neurons in MT has long been an active area of study, however circuit models detailing the computations underlying binocular integration of motion signals remains elusive. Such models are important for studying the visual perception of motion in depth (MID), which involves both frontoparallel (FP) visual motion and binocular signal integration. Recent studies (Czuba et al. 2014, Sanada and DeAngelis 2014) have shown that many MT neurons are MID sensitive, contrary to the prevailing view (Maunsell and van Essen, 1983). These novel data are ideal for constraining models of binocular motion integration in MT. We have …
