Neuroscience and Neurobiology Commons^™

Towards Understanding And Improving Speech Processing, Sonia Yasmin

Electronic Thesis and Dissertation Repository

This dissertation explores mechanisms for understanding and improving speech processing. First, I used EEG to investigate the acoustic and semantic processing of continuous naturalistic speech masked by multi-talker babble. I found that different features of the same speech signal are reflected in different aspects of the neural tracking response, which are themselves differentially affected by noise. These findings point to a complex relationship between speech intelligibility and neural speech encoding.

Next, I systematically reviewed the current advancements in speech enhancement technologies. I find that speech enhancement algorithms are limited in their generalizability to speech-noise (i.e., babble). I demonstrate that, for …

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 …

Using Machine Learning To Identify Neural Mechanisms Underlying The Development Of Cognition In Children And Adolescents With Adhd, Brian Pho

Electronic Thesis and Dissertation Repository

Childhood and adolescence are marked by improvements to cognition and by the emergence of neurodevelopmental disorders such as attention deficit hyperactivity disorder (ADHD). What neural mechanisms are associated with cognitive development in ADHD? In this study, I applied machine learning models to functional connectivity profiles to identify patterns of network connectivity that predict various cognitive abilities in a group of participants ages 6 to 16 with ADHD. The models successfully predicted IQ, visual spatial, verbal comprehension, and fluid reasoning in children ages 6 to 11, but not adolescents. Furthermore, the models identified connections with the default mode, memory retrieval, and …

An Implementation Of Integrated Information Theory In Resting-State Fmri, Idan E. Nemirovsky

Electronic Thesis and Dissertation Repository

Integrated Information Theory (IIT) is a framework developed to explain consciousness, arguing that conscious systems consist of interacting elements that are integrated through their causal properties. In this study, we present the first application of IIT to functional magnetic resonance imaging (fMRI) data and investigate whether its principal metric, Phi, can meaningfully quantify resting-state cortical activity patterns. Data was acquired from 17 healthy subjects who underwent sedation with propofol, a short acting anesthetic. Using PyPhi, a software package developed for IIT, we thoroughly analyze how Phi varies across different networks and throughout sedation. Our findings indicate that variations in Phi …

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 …

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

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, …

Optimizing Preprocessing Of Fmri Data To Maximize Correspondence Of Functional Anatomy Across Individuals, Nargess Ghazaleh

Electronic Thesis and Dissertation Repository

In movie-activation fMRI, intersubject correlation (ISC) indicates a functional correspondence across viewers. Brains di↵er in shape; spatial normalization and smoothing enhance inter-subject functional overlap. We compare three normalization methods and six smoothing levels to discover which method yields the best functional overlap, indexed by ISC. This is key to optimizing data analysis in clinical studies using movie-activation fMRI in future. In a 3T scanner, 44 healthy subjects watched an 8-min movie. Both normalization and smoothing a↵ected the strength and extent of the ISC. ISC values were more robust for ANTs and DARTELthanforSPM12andwere(asymptotically)thestrongestat12mmsmoothing. When image data are preprocessed with high-dimensional volumetric …

The Origins And Development Of Visual Categorization, Laura Cabral

Electronic Thesis and Dissertation Repository

Forming categories is a core part of human cognition, allowing us to make quickly make inferences about our environment. This thesis investigated some of the major theoretical interpretations surrounding the neural basis of visual category development. In adults, there are category-selective regions (e.g. in ventral temporal cortex) and networks (which include regions outside traditional visual regions—e.g. the amygdala) that support visual categorization. While there has been extensive behavioural work investigating visual categorization in infants, the neural sequence of development remains poorly understood. Based on behavioral experiments, one view holds that infants are initially using subcortical structures to recognize faces. Indeed, …

Calculating The Dimensionality Of The Brain, And Other Applications Of An Optimized Generalized Ising Model In Predicting Brain's Spontaneous Functions, Pubuditha M. Abeyasinghe

Electronic Thesis and Dissertation Repository

Understanding a system as complex as the human brain is a very demanding task. Directly working with structural and functional neuroimaging data has led to most of the understanding we have gained about the human brain. However, performing only the direct statistical comparisons on the empirical function and the structure does not fully explain the observed long-range functional correlations. Therefore, implementations of mathematical models to gain further understanding of the relationship between the structure and function of the brain is critical. Additionally, spontaneous functions of the brain can only be predicted using computer simulated models; which will be pivotal for …

Ultra-High Field Magnetic Resonance Imaging For Stereotactic Neurosurgery, Jonathan Lau

Electronic Thesis and Dissertation Repository

Stereotactic neurosurgery is a subspecialty within neurosurgery concerned with accurate targeting of brain structures. Deep brain stimulation (DBS) is a specific type of stereotaxy in which electrodes are implanted in deep brain structures. It has proven therapeutic efficacy in Parkinson’s disease and Essential Tremor, but with an expanding number of indications under evaluation including Alzheimer’s disease, depression, epilepsy, and obesity, many more Canadians with chronic health conditions may benefit. Accurate surgical targeting is crucial with millimeter deviations resulting in unwanted side effects including muscle contractions, or worse, vessel injury. Lack of adequate visualization of surgical targets with conventional lower field …

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 – …

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 …

Navigating The "Little Brain": Comprehensive Mapping Of Functional Organisation, Maedbh King

Electronic Thesis and Dissertation Repository

Two decades of neuroimaging research suggests that the cerebellum is functionally involved in a range of cognitive and motor processes. However, missing from the literature is a comprehensive map detailing a clear functional organisation of the cerebellum. Previous studies have used a restricted task-mapping approach to localise task-specific functional activation to cerebellar lobules. However, this approach, which is often limited to one or two functional domains within individual subjects, fails to characterise the full breadth of functional specialisation within the cerebellum. To overcome this restricted task-mapping problem, we tested 17 subjects on a condition-rich task battery (61 task conditions) across …

Functional Connectivity In The Motor Network Largely Matures Before Motor Function, Jordynne L V Ropat

Electronic Thesis and Dissertation Repository

The brain changes in many ways in the first year. It is not known which of these changes are most critical for the development of cognitive functions. According to the Interactive Specialization Theory, developments in behaviour result from changes in brain connectivity. We tested this using functional connectivity magnetic resonance imaging (fcMRI) of the motor system. fcMRI was acquired at three and nine months – two time-points between which motor behaviour develops enormously. Infants were additionally compared with adults. Subjects were scanned with a 3T MRI scanner, yielding BOLD signal time-courses that were correlated with one another. Our results do …

Unravelling The Subfields Of The Hippocampal Head Using 7-Tesla Structural Mri, Jordan M. K. Dekraker

Electronic Thesis and Dissertation Repository

Probing the functions of human hippocampal subfields is a promising area of research in cognitive neuroscience. However, defining subfield borders in Magnetic Resonance Imaging (MRI) is challenging. Here, we present a user-guided, semi-automated protocol for segmenting hippocampal subfields on T2-weighted images obtained with 7-Tesla MRI. The protocol takes advantage of extant knowledge about regularities in hippocampal morphology and ontogeny that have not been systematically considered in prior related work. An image feature known as the hippocampal ‘dark band’ facilitates tracking of subfield continuities, allowing for unfolding and segmentation of convoluted hippocampal tissue. Initial results suggest that this protocol offers sufficient …

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, …

Optimizing The Analysis Of Electroencephalographic Data By Dynamic Graphs, Mehrsasadat Golestaneh

Electronic Thesis and Dissertation Repository

The brain’s underlying functional connectivity has been recently studied using tools offered by graph theory and network theory. Although the primary research focus in this area has so far been mostly on static graphs, the complex and dynamic nature of the brain’s underlying mechanism has initiated the usage of dynamic graphs, providing groundwork for time sensi- tive and finer investigations. Studying the topological reconfiguration of these dynamic graphs is done by exploiting a pool of graph metrics, which describe the network’s characteristics at different scales. However, considering the vast amount of data generated by neuroimaging tools, heavy computation load and …