Neuroscience and Neurobiology Commons^™

Data Preprocessing And Machine Learning For Intracranial Electroencephalography, Mauricio Cespedes Tenorio

Electronic Thesis and Dissertation Repository

This thesis serves to address the problem of non-standardized preprocessing of intracranial electroencephalography (iEEG) recordings by implementing a software workflow that compiles some of the most common steps followed for the preparation of this type of data. This workflow improves the consistency, replicability, and ease of use of iEEG preprocessing, facilitating the replication and extension of previous studies and the combination of separately preprocessed inter-institutional datasets. Automatic detection of artifacts for iEEG data was also explored as a potential step to include in the preprocessing workflow. Despite training the models with cross-institutional data, poor performance was observed when tested on …

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 …

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 …

Neural Correlates Of Post-Traumatic Brain Injury (Tbi) Attention Deficits In Children, Meng Cao

Dissertations

Traumatic brain injury (TBI) in children is a major public health concern worldwide. Attention deficits are among the most common neurocognitive and behavioral consequences in children post-TBI which have significant negative impacts on their educational and social outcomes and compromise the quality of their lives. However, there is a paucity of evidence to guide the optimal treatment strategies of attention deficit related symptoms in children post-TBI due to the lack of understanding regarding its neurobiological substrate. Thus, it is critical to understand the neural mechanisms associated with TBI-induced attention deficits in children so that more refined and tailored strategies can …