Life Sciences Commons^™

Invariant Object Recognition In Deep Neural Networks And Humans, Haider Al-Tahan

Electronic Thesis and Dissertation Repository

Invariant object recognition, a cornerstone of human vision, enables recognizing objects despite variations in rotations, positions, and scales. To emulate human-like generalization across object transformations, computational models must perform well in this aspect. Deep neural networks (DNNs) are popular models for human ventral visual stream processing, though their alignment with human performance remains inconsistent. We examine object recognition across transformations in human adults and pretrained feedforward DNNs. DNNs are grouped in model families by architecture, visual diet, and learning goal. We focus on object rotation in depth, and observe that object recognition performance is better preserved in humans than in …

Selective Recruitment Of Cerebellum In Cognition, Ladan Shahshahani

Electronic Thesis and Dissertation Repository

Previous studies of cerebellar function in humans have shown that it is activated by a myriad of tasks ranging from motor learning and language to working memory and more. These studies have prompted a deviation from the traditional view of the cerebellum as a purely motor structure. However, the precise contribution of the cerebellum to these tasks remains ambiguous.

A prevalent assumption in fMRI studies is interpreting BOLD activation as evidence of the cerebellum's involvement in specific tasks. However, this interpretation is potentially misleading, especially considering that the BOLD signal predominantly represents cerebellar input, with output activity largely absent. Consequently, …

Visual Cortical Traveling Waves: From Spontaneous Spiking Populations To Stimulus-Evoked Models Of Short-Term Prediction, Gabriel B. Benigno

Electronic Thesis and Dissertation Repository

Thanks to recent advances in neurotechnology, waves of activity sweeping across entire cortical regions are now routinely observed. Moreover, these waves have been found to impact neural responses as well as perception, and the responses themselves are found to be structured as traveling waves. How exactly do these waves arise? Do they confer any computational advantages? These traveling waves represent an opportunity for an expanded theory of neural computation, in which their dynamic local network activity may complement the moment-to-moment variability of our sensory experience.

This thesis aims to help uncover the origin and role of traveling waves in the …

Neural Dynamics Of Visual Processes In Challenging Visibility Conditions, Saba Charmi Motlagh

Electronic Thesis and Dissertation Repository

In our daily visual experience, our brain effortlessly categorizes countless objects, enabling us to perceive and interpret the world around us. This core object recognition process is vital for our survival and adaptive behavior, allowing us to recognize objects despite variations in appearance. The incredible speed at which we accomplish this task is a testament to the efficiency of our visual system and the significance of visual processing is evident in the allocation of nearly half of the neocortex in primates to this function. Unraveling the intricacies of how the human visual system tackles this complex challenge has long been …

Neural Dynamics Of Target Processing In Attentional Blink, Mansoure Jahanian

Electronic Thesis and Dissertation Repository

The attentional blink (AB) phenomenon refers to the failure to report the second target (T2) if it appears 200-500 ms after the first target (T1) in a stream of rapidly presented images. The present study aimed to investigate the neural representations of target processing under conditions where AB does or does not occur. We recorded EEG and behavioral data while participants viewed a rapid sequence of natural object images embedded with two face targets presented at two lag conditions: lag 3 (targets were 252 ms apart) and lag 7 (targets were 588 ms apart). Consistent with AB, our behavioral results …

Temporal Dynamics Of Natural Sound Categorization, Ali Tafakkor

Electronic Thesis and Dissertation Repository

While extensive research has elucidated the brain’s processing of semantics from speech sound waves and their mapping onto the auditory cortex, the temporal dynamics of how meaningful non-speech sounds are processed remain less examined. Understanding these dynamics is key to resolving the debate between cascaded and parallel hierarchical processing models, both plausible given the anatomical evidence. This study investigates how semantic category information from environmental sounds is processed in the temporal domain, using electroencephalography (EEG) collected from 25 participants and representational similarity analysis (RSA) along with models of acoustic and semantic information. We examined information extracted by the brain from …

Machine Learning Techniques For Improved Functional Brain Parcellation, Da Zhi

Electronic Thesis and Dissertation Repository

Brain parcellation studies are fundamental for neuroscience as they serve as a bridge between anatomy and function, helping researchers interpret how functions are distributed across different brain regions. However, two substantial challenges exist in current imaging-based brain parcellation studies: large variations in the functional organization across individuals and the intrinsic spatial dependence which causes nearby brain locations to have a similar function. This thesis presents a series of projects aimed to tackle these challenges from different perspectives by using advanced machine learning techniques.

To handle the challenge of individual variability in building precise individual parcellations, Chapter 3 introduces a novel …