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Full-Text Articles in Neuroscience and Neurobiology

A Generative-Discriminative Approach To Human Brain Mapping, Deepanshu Wadhwa Aug 2021

A Generative-Discriminative Approach To Human Brain Mapping, Deepanshu Wadhwa

Electronic Thesis and Dissertation Repository

During everyday behaviours, the brain shows complex spatial patterns of activity. These activity maps are very replicable within an individual, but vary significantly across individuals, even though they are evoked by the same behaviour. It is unknown how differences in these spatial patterns relate to differences in behavior or function. More fundamentally, the structural, developmental, and genetic factors that determine the spatial organisation of these brain maps in each individual are unclear. Here we propose a new quantitative approach for uncovering the basic principles by which functional brain maps are organized. We propose to take an generative-discriminative approach to human …


Learning How To Build A Neural Network Model Of The Tactile Periphery, Vicky Chang Aug 2021

Learning How To Build A Neural Network Model Of The Tactile Periphery, Vicky Chang

Undergraduate Student Research Internships Conference

First order neurons in the hairless skin of human hands have spatially complex receptive fields that allow for the detection of spatial details. These spatially complex receptive fields arise from the branching of mechanoreceptors, which converge and connect to first order neurons. This arrangement allows us to process our sensory environment through detecting the edge orientation of a touched object for instance, and do things like read braille.

These spatially complex receptive fields can studied by using a feedforward neural network to model the tactile periphery. By understanding the processing at the level of the tactile periphery, we can better …


Incorporating Action Information Into Computational Models Of The Human Visual System, Justin Zhou Aug 2021

Incorporating Action Information Into Computational Models Of The Human Visual System, Justin Zhou

Undergraduate Student Research Internships Conference

Deep convolutional neural networks (DCNNs) have been used to model the ventral visual stream. However, there have been relatively few computational models of the dorsal visual stream, preventing a wholistic understanding of the human visual system. Additionally, current DCNN models of the ventral stream have shortcomings (such as an over-reliance on texture data) which can be ameliorated by incorporating dorsal stream information. The current study aims to investigate two questions: 1) does incorporating action information improve computational models of the ventral visual system? 2) how do the ventral and dorsal streams influence each other during development?

Three models will be …


Memoir Dataset: Quantifying Image Memorability In Adolescents, Gal Almog, Yalda Mohsenzadeh Aug 2021

Memoir Dataset: Quantifying Image Memorability In Adolescents, Gal Almog, Yalda Mohsenzadeh

Undergraduate Student Research Internships Conference

Every day, humans observe and interact with hundreds of images and scenes; whether it be on a cellphone, on television, or in print. Yet a vast majority of these images are forgotten, some immediately and some after variable lengths of time. Memorability is indeed a property intrinsic to all images that can be extracted, as well as predicted. While memory itself is a process that occurs in the brain of an individual, the concept of memorability is an intrinsic, continuous property of a stimulus that can be both measured and manipulated. We selected images from the MemCat data set that …


Tracking The Mechanisms Of Short-Term Motor Adaptation Within The Framework Of A Two-State Model, Susan K. Coltman Aug 2021

Tracking The Mechanisms Of Short-Term Motor Adaptation Within The Framework Of A Two-State Model, Susan K. Coltman

Electronic Thesis and Dissertation Repository

The motor system is continuously monitoring our performance, ensuring that our actions are occurring as planned. Sensory prediction errors, which arise from a discrepancy between the expected and actual sensory consequence of a motor command (i.e., a planned action), are assumed to drive sensorimotor adaptation. Sensorimotor adaptation is thought to involve changes in motor output that allow the motor system to regain its former level of performance in perturbed circumstances. We employed experimental paradigms that involved both mechanical and visual perturbations to evoke sensory prediction errors while participants performed planar reaching movements. Movement error activates learning processes in the brain, …


Brain Representations Of Dexterous Hand Control: Investigating The Functional Organization Of Individuated Finger Movements And Somatosensory Integration, Spencer Arbuckle Aug 2021

Brain Representations Of Dexterous Hand Control: Investigating The Functional Organization Of Individuated Finger Movements And Somatosensory Integration, Spencer Arbuckle

Electronic Thesis and Dissertation Repository

Using our hands to manipulate objects in our daily life requires both dexterous movements and the integration of somatosensory information across fingers. Although the primary motor (M1) and somatosensory cortices (S1) are critical for these two complementary roles, it is unclear how neural populations in these regions functionally represent these processes. This thesis examined the functional organization of brain representations (the representational geometry) in M1 and S1 for dexterous hand control and somatosensory processing. To that end, representational geometries were estimated from fine-grained brain activity patterns measured with functional MRI (fMRI). Since fMRI measures a blood-based proxy of neural activity, …