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Full-Text Articles in Bioelectrical and Neuroengineering

Transcranial Ac Modulation Of Cerebellar Nuclear Activity In Awake Animals, Nuran Kavakli May 2026

Transcranial Ac Modulation Of Cerebellar Nuclear Activity In Awake Animals, Nuran Kavakli

Dissertations

Entrainment of cerebellar nuclear (CN) cells via cerebellar transcranial alternating current stimulation (ctACS) has been reported in animals under ketamine/xylazine anesthesia. Our main objective was to demonstrate modulation of CN activity in unanesthetized, freely moving animals using ctACS. Multi-channel carbon-fiber electrodes were implanted into the interpositus nucleus for recording multi-unit (MU) activity, and thin-film electrodes were implanted subcutaneously over the posterior cerebellum for stimulation. A frequency-domain-based metric was developed to quantify modulation from MU signals. The results demonstrated modulation in a wide range of frequencies (4 Hz-300 Hz) as in anesthetized animals. In contrast, the amplitude of the peak in …


Empirical Dynamical Modeling Of Cortico-Hippocampal Information Transfer During Memory Encoding, Sam Y. Cole Jan 2026

Empirical Dynamical Modeling Of Cortico-Hippocampal Information Transfer During Memory Encoding, Sam Y. Cole

Theses and Dissertations

Understanding how brain dynamics support successful memory formation remains a central challenge in neuroscience. This dissertation applies tools from empirical dynamical systems theory to investigate the neural mechanisms underlying episodic encoding, with a focus on cortico-hippocampal interactions. Using stereoelectroencephalography (sEEG) data recorded during a delayed free recall of word lists task, this work reveals nonlinear, state-dependent shifts in directed information flow between cortex and hippocampus that distinguish successful from unsuccessful encoding. To further characterize these dynamics, state-space trajectories are reconstructed using time-delay embedding and recurrence-based methods, and features derived from these trajectories are used to classify memory outcomes. By integrating …


Modulation Of Motor Learning With High-Intensity Transcranial Electric Stimulation, Gavin Hsu Jan 2024

Modulation Of Motor Learning With High-Intensity Transcranial Electric Stimulation, Gavin Hsu

Dissertations and Theses

Research thus far on noninvasive, transcranial electric stimulation have produced mixed results from in vivo human experiments. This work tests the hypothesis that applying higher stimulation intensities would induce intracranial electric fields that more closely match the higher magnitudes used in animal and in vitro studies and subsequently yield more robust effects. As done commonly in the literature, we targeted the motor cortex (M1), specifically in the context of neuroplastic changes taking place during motor learning in healthy adult humans. This work also seeks a better understanding of the neural correlates underlying motor skill learning.

Through multiple large-sample studies, this …


Characterization And Decoding Of Speech Activity From Intracranial Signals, Pedram Zanganeh Soroush Jan 2023

Characterization And Decoding Of Speech Activity From Intracranial Signals, Pedram Zanganeh Soroush

Theses and Dissertations

Speech is the first and foremost means of human communication. Millions of people worldwide suffer from severe speech disorders due to neurological diseases such as amyotrophic lateral sclerosis (ALS), brain stem stroke, and severe paralysis. A speech neuroprosthesis that decodes speech directly from neural signals could dramatically improve life for these individuals. Recent studies have demonstrated that it is possible to decode and synthesize various aspects of acoustic speech directly from intracranial measurements of electrophysiological brain activity. For those who have completely lost the ability to speak, the objective is to synthesize acoustic speech directly from brain activity during imagined …


Closed-Loop Brain-Computer Interfaces For Memory Restoration Using Deep Brain Stimulation, David Xiaoliang Wang May 2022

Closed-Loop Brain-Computer Interfaces For Memory Restoration Using Deep Brain Stimulation, David Xiaoliang Wang

Electrical Engineering Theses and Dissertations

The past two decades have witnessed the rapid growth of therapeutic brain-computer interfaces (BCI) targeting a diversity of brain dysfunctions. Among many neurosurgical procedures, deep brain stimulation (DBS) with neuromodulation technique has emerged as a fruitful treatment for neurodegenerative disorders such as epilepsy, Parkinson's disease, post-traumatic amnesia, and Alzheimer's disease, as well as neuropsychiatric disorders such as depression, obsessive-compulsive disorder, and schizophrenia. In parallel to the open-loop neuromodulation strategies for neuromotor disorders, recent investigations have demonstrated the superior performance of closed-loop neuromodulation systems for memory-relevant disorders due to the more sophisticated underlying brain circuitry during cognitive processes. Our efforts are …


When The Brain Plays A Game: Neural Responses To Visual Dynamics During Naturalistic Visual Tasks, Jason Ki Jan 2021

When The Brain Plays A Game: Neural Responses To Visual Dynamics During Naturalistic Visual Tasks, Jason Ki

Dissertations and Theses

Many day-to-day tasks involve processing of complex visual information in a continuous stream. While much of our knowledge on visual processing has been established from reductionist approaches in lab-controlled settings, very little is known about the processing of complex dynamic stimuli experienced in everyday scenarios. Traditional investigations employ event-related paradigms that involve presentation of simple stimuli at select locations in visual space and discrete moments in time. In contrast, visual stimuli in real-life are highly dynamic, spatially-heterogeneous, and semantically rich. Moreover, traditional experiments impose unnatural task constraints (e.g., inhibited saccades), thus, it is unclear whether theories developed under the reductionist …


Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre May 2019

Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre

Honors Scholar Theses

Abnormal ocular motility is a common manifestation of many underlying pathologies particularly those that are neurological. Dynamics of saccades, when the eye rapidly changes its point of fixation, have been characterized for many neurological disorders including concussions, traumatic brain injuries (TBI), and Parkinson’s disease. However, widespread saccade analysis for diagnostic and research purposes requires the recognition of certain eye movement parameters. Key information such as velocity and duration must be determined from data based on a wide set of patients’ characteristics that may range in eye shapes and iris, hair and skin pigmentation [36]. Previous work on saccade analysis has …