Neurosciences Commons^™

Mathematical Models Of Multisensory Detection And Decision-Making, Rebecca M. Brady

Doctoral

The brain seamlessly integrates signals from multiple sensory modalities to interpret the world efficiently. By using information from various senses, the brain can enhance its ability to detect and respond to stimuli more quickly and accurately. However, combining sensory cues from multiple modalities is only sometimes beneficial as it may lead to illusions and reduced behavioural performance. Behavioural and electrophysiological experiments have revealed that detection and decision-making strategies for multisensory cues evolve throughout human development and ageing. Additionally, studies have demonstrated that maladaptive multisensory processing is a key indicator of a proclivity to falls in older adults and individuals with …

The Making Of An Extremist: How Do We Become Someone Else’S Nightmare?, María Paula Morales

The Confluence

This article explores how ordinary people can be pulled into extremist movements and what psychological forces drive that process. It looks at three perspectives: social identity theory, which explains how group belonging shapes behavior, identity development, which shows how people searching for meaning may find it in extremist causes; and social neuroscience, which connects radicalization to brain activity linked to fear, loyalty, and moral judgement. Together, these approaches show that radicalization is not simply about ideology but about identity, emotion, and belonging. By understanding these dynamics, we can find better ways to prevent extremism and promote healthier, more inclusive communities.

Utilizing Brain Computer Interfaces That Interact With A Virtual Keyboard, Skye Lilienthal

Honors Theses

A brain-computer interface (BCI) can allow someone to utilize electrical signals in their brain to complete tasks using a computer. BCIs can help people take advantage of technology to type without the need for a traditional keyboard setup. This paper used the OpenBCI Mark IV to test the effectiveness of non-invasive BCIs with dry electrodes within the OpenViBE P300 Speller. This paper shows how to use the P300 speller through a setup pipeline. Results indicate that electrode placement affects P300 accuracy and that areas related to visual processing improve accuracy, suggesting that P300 signals can be detected within OpenBCI Mark …

Brain Computer Interfaces: Enhancing Low-Cost Eeg Performance Through Deep, Anwar Rassoul

Shelby Hall Graduate Research Forum Posters

The field of Brain Computer Interfacing (BCI) has traditionally been confined to clinical and research environments due to the high cost and complexity of medical-grade EEG systems. However, the emergence of low-cost hardware exemplified has catalyzed a shift toward accessible, portable BCI applications. While these devices lower the barrier to entry for developers and researchers, they often suffer from a lower signal-to-noise ratio (SNR). This increased noise makes it difficult to extract the clean neural signatures required for high-accuracy control, particularly when operating in non-shielded, real-world environments.

This research focuses on Steady-State Visually Evoked Potentials (SSVEP), a robust BCI paradigm …

Biologically-Inspired Multiscale Neuromorphic Architecture, Christian O'Reilly, Ramtin Zand

Publications

This white paper proposes a biologically-inspired multiscale neuromorphic architecture that bridges key gaps between artificial neural networks (ANNs), spiking neural networks (SNNs), and biological neural networks (BNNs). While SNNs offer promising energy efficiency, their broader adoption remains limited by suboptimal performance and the need for novel learning paradigms. To address these challenges, the proposed framework integrates structural and functional principles observed in the brain, including hierarchical organization, sparse and modular connectivity, predictive coding, and diverse neuronal dynamics.

The architecture operates across micro-, meso-, and macro-scales, incorporating neuron-level diversity (e.g., excitatory/inhibitory and principal/support cells), canonical microcircuits (CMCs), and large-scale hierarchical organization. …

Task-Optimized Brain Parcellations Reveal Latent Functional Organization For Enhanced Connectivity-Based Neuroimaging Classification, Andrew Hannum, Mario A. Lopez

Computer Science: Faculty Scholarship

Brain parcellation schemes are fundamental to neuroimaging, yet general-purpose atlases may obscure the specific functional architecture relevant to a given cognitive task or clinical condition. This reflects a growing consensus that the “optimal” brain map is context-dependent. Here, we introduce a novel framework that validates this principle by generating task-optimized human brain parcellation maps directly from supervised learning objectives. Our method defines functional parcels by grouping brain regions based on the similarity of their contributions to a classifier's decision boundary for a specific goal (e.g., cognitive state decoding or clinical group separation). This approach prioritizes a region's discriminative role over …

Implementation And Assessment Of The Openbci Platform As An Accessible Brain- Computer Interface, Jewell Norris

Honors Theses

OpenBCI is a low-cost, open-source platform for alternative brain-computer interface (BCI) software and hardware. This thesis evaluates OpenBCI’s electroencephalogram (EEG) and electromyography (EMG) capabilities by constructing and testing a 16-channel EEG system using the Ultracortex Mark IV headset and Cyton + Daisy biosensing board. The viability of the system was assessed through real-time BCI control and comparison to a clinical-grade EEG system. Real-time BCI control of an online falling-block game was tested via the use of eye blinks EMG (channels Fp1/Fp2) and head-tilt accelerometer inputs. The BCI game demonstrated reliable control despite minor latency and artifact sensitivity. For clinical comparison, …

Living With Alzheimer’S: A Guide To How To Lower The Risk Of Memory Loss & Care For Those With Alzheimer’S, Mona Muzammil, Washain Muzammil

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Chemistry)

Despite the frequent characterization of Alzheimer's disease as a “loss of self,"" this enlightening book demonstrates unequivocally that a person's unique self persists throughout the course of the disease. The important message in Caring for People with Alzheimer’s is how much can be done in care settings to support a person's sense of identity and thereby enrich the lives of people experiencing the many losses associated with dementia. Drawing from a diverse body of research, this book brings together the recommendations of the best thinkers and practitioners in multiple disciplines to illustrate the meaning of self and the importance of …

Enhancing State-Of-The-Art Motor Imagery Classification With Reinforcement Learning, Anton Shepelev

USF Tampa Graduate Theses and Dissertations

One of the key obstacles to the rapid adoption of non-invasive Brain-Computer Interfaces (BCIs) for Motor Imagery (MI) is the low signal-to-noise ratio, and the substantial data requirements which can be mentally taxing for users. EEGNet, a compact Convolutional Neural Network (CNN), has long been considered the state-of-the-art (SOTA) for MI classification, demonstrating strong performance even with limited data. However, recent studies advocate for integrating Deep Reinforcement Learning (RL) to further enhance classification accuracy by dynamically optimizing feature extraction and decision-making processes. Despite this potential, practical implementations remain scarce due to challenges in stabilizing RL training and adapting it to …

Children Suspected For Developmental Coordination Disorder In Hong Kong And Associated Health-Related Functioning: A Survey Study, Kathlynne F. Eguia, Sum Kwing Cheung, Kevin K.H. Chung, Catherine M. Capio

Health Sciences Faculty Publications

Children with developmental coordination disorder (DCD) have motor difficulties that interfere with their daily functions. The extent to which DCD affects children in Hong Kong has not been established. In this study, we aimed to estimate the prevalence of children suspected of DCD (sDCD) in Hong Kong and to examine the relationship between motor performance difficulties and health-related functioning. We conducted a cross-sectional survey of parents of children aged 5 to 12 years across Hong Kong (N = 656). The survey consisted of the Developmental Coordination Disorder Questionnaire (DCDQ) and short forms on global health, physical activity, positive affect, and …

Optimizing Electrode Configurations For Eeg Mild Cognitive Impairment Detection, Yi Jiang, Xin Zhang, Zhiwei Guo, Xiaobo Zhou, Jiayuan He, Ning Jiang

Faculty, Staff and Student Publications

The Optimal electrode configuration of Electroencephalograms (EEG) systems for mild cognitive impairment (MCI) detection and monitoring in non-clinical settings, i.e. number of electrodes and the positions of the electrodes, remains to be explored. In the current study, we explored the optimization of electrode configuration for MCI detection. We used a 32-channel EEG device to record the data of 21 MCI patients and 20 cognitively normal elderly (NC) undergoing working memory (WM) tasks. Based on the differential value (MCI group vs. NC group) from the Power Spectral Density (PSD) value of each electrode in θ and α frequency band during WM …

Optimizing Decision-Making In A Cerebral Palsy Model Using Reinforcement Learning, Richard Ampah

Pitzer Senior Theses

This study presents an original interdisciplinary investigation into how reinforcement learning (RL) can model motor and cognitive defects and potentially improve motor and cognitive functions in individuals with cerebral palsy (CP), a non-progressive neurological disorder that impairs movement and adaptability. Integrating computational neuroscience and machine learning, the research applies policy gradient methods and Markov Decision Processes (MDPs) to simulate adaptive learning in agents with and without CP-related constraints.

The central aim is to compare the cumulative rewards of optimal policies, derived from value iteration, and human-like learning policies using the REINFORCE algorithm, both with and without the Bellman baseline. The …

Alpha-Synuclein Interaction With Gedunin, Tony Matundura Nyabayo

Graduate Theses/Dissertations

Parkinson’s disease (PD) and other Proteinopathies develop when α-synuclein misfolds and aggregates into toxic amyloids. While existing treatments for PD are primarily focused on managing its symptoms, a viable solution for slowing down the progress of Parkinson’s disease involves targeting the toxic α-synuclein amyloids. Gedunin, a natural inhibitor of heat shock protein 90, has been extensively used to treat malaria. Also, recent research investigations have shed light on its potential beyond malaria therapy, indicating that Gedunin may offer a possible solution for treating a variety of neurodegenerative diseases. Using plate-based assays, we examined how Gedunin influences α-synuclein fibrillation and its …

Comparative Efficacy Of Hallucinogens In Treating Mood Disorders Through A Meta-Analysis Of Symptom Reduction, Dosage, And Duration, John Marco D.F. Muniz

Honors Undergraduate Theses

Background: Hallucinogens including psilocybin, lysergic acid diethylamide (LSD), ketamine, N,N-dimethyltryptamine (DMT) (as ayahuasca), have re-emerged as potential rapid-acting treatments for mood disorders. We conducted a meta-analysis of placebo-controlled trials evaluating their efficacy in depression and anxiety disorders. Methods: A systematic review identified 12 trials (Total ≈ 670) meeting inclusion criteria (randomized, placebo-controlled). Data on Cohen’s d and Hedges’ g effect sizes for depression- and anxiety-related outcomes were extracted. We computed pooled effect sizes (weighted by sample size and inverse variance), performed subgroup analyses by drug, diagnosis, follow-up duration, and outcome measure type, and assessed heterogeneity (I², Q …

Synthesis And Design Of Clpp Activators As Novel Antibiotics, Schyler Odum

Theses and Dissertations (ETD)

Purpose. Design and synthesize novel compounds to treat Staphylococcus aureus infections by targeting the dysregulation of the Casein Protease P, ClpP. Methods. Utilize established chemical methods to synthesize ureadepsipeptides, small-molecule ClpP activators, and ureadepsipeptide hybrids. Assess their effectiveness by using minimum inhibitory concentration assays and in vitro biochemical assays for ClpP activation. Explore their potential as antibiotics through mitochondrial toxicity tests, glucose/galactose assays, and biophysical measurements related to metabolism and clearance, including thermal shift and surface plasmon resonance assays. Results. Synthesized and tested 33 novel compounds, comprising a total of 80 synthetic steps. Conclusion. The three-part conclusion from the dissertation …

Learning Paradigms For Rhythm Detection And Generation Using Mathematical Models, Biophysical And Artificial Neural Networks, Prianka Bose

Dissertations

Humans possess an inherent ability to recognize evenly-spaced rhythms, known as isochronous rhythms, owing to the brain's predisposition to entrain to external auditory stimuli with regular temporal intervals. The central focus of this research is to understand how the brain learns and retains rhythmic time intervals in the context of music. This dissertation studies rhythm detection and generation through mathematical models, biophysical networks, and artificial neural networks, addressing both isochronous and non-isochronous patterns.

A primary focus of the thesis is on isochronous rhythms. In particular, given a perturbation to an isochronous rhythm such as a tempo change or phase shift …

Smartphone Haptics Can Uncover Differences In Touch Interactions Between Asd And Neurotypicals, Ivonne Monarca, Franceli L. Cibrian, Isabel López Hurtado, Monica Tentori

Engineering Faculty Articles and Research

Utilizing touch interactions from smartphones for gathering data and identifying digital markers for screening and monitoring neurological disorders, such as Autism Spectrum Disorder (ASD), is an emerging area of research. Smartphones provide multiple benefits for this kind of study, including unobtrusive data collection via built-in sensors, integrated haptic feedback systems, and the capability to create specialized applications. Acknowledging the significant yet understudied presence of tactile processing differences in individuals with ASD, we designed and developed Feel and Touch, a mobile game that leverages the haptic capabilities of smartphones. This game provides vibrotactile feedback in response to touch interactions and collects …

On The Role Of Prediction In Streaming Hierarchical Learning, Ramy Mounir

USF Tampa Graduate Theses and Dissertations

In today's world, AI systems need to make sense of large amounts of data as it unfolds in real-time, whether it's a video from surveillance and monitoring cameras, streams of egocentric footage, or sequences in other domains such as text or audio. The ability to break these continuous data streams into meaningful events, discover nested structures, and predict what might happen next at different levels of abstraction is crucial for applications ranging from passive surveillance systems to sensory-motor autonomous learning. However, most existing models rely heavily on large, annotated datasets with fixed data distributions and offline epoch-based training, which makes …

Amino Acid-Based Protein-Mimic Hydrogel Incorporating Pro-Regenerative Lipid Mediator And Microvascular Fragments Promotes The Healing Of Deep Burn Wounds, Yan Lu, Shanchun Su, Chih Chang Chu, Yuichi Kobayashi, Abdul Razak Masoud, Hongying Peng, Nathan Lien, Mingyu He, Christopher Vuong, Ryan Tran, Song Hong

School of Medicine Faculty Publications

Pro-regenerative lipid mediator 1 (PreM1) is a specialized pro-resolving lipid mediator that promotes wound healing and regenerative functions of mesenchymal stem cells (MSCs), endothelial cells, and macrophages. The healing of third-degree (3°) burns and regenerative functions of MSCs are enhanced by ACgel1, an arginine-and-chitosan-based protein-mimic hybrid hydrogel. Adipose-tissue derived microvascular fragments (MVFs) are native vascularization units and a rich source of MSCs, endothelial cells, and perivascular cells for tissue regeneration. Here we describe an innovative PreM1-MVFs-ACgel1 construct that incorporated PreM1 and MVFs into ACgel1 via optimal design and fabrication. This construct delivered PreM1 to 3°-burn wounds at least up to …

Cortisol And Alpha-Synuclein Stability In Saliva Under Varying Storage And Handling Conditions, Mo Zheng, Sujata Srikanth, Jeremiah Carpenter, Delphine Dean

Journal of the South Carolina Academy of Science

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor impairments and non-motor symptoms, significantly impacting patients' quality of life. Currently, cerebrospinal fluid (CSF) is the primary biofluid used for PD biomarker studies, notably α-synuclein, despite the invasive nature of lumbar puncture procedures. Recent work has shown that some of these PD biomarkers have been measured in saliva. As an alternative to CSF, saliva can be non-invasively self-collected by patients repeatedly over time to monitor biomarker levels. However, the stability of these biomarkers in saliva needs to be evaluated before saliva can be considered for patient self-collection studies. Therefore, …

Multimodal Mixing Convolutional Neural Network And Transformer For Alzheimer’S Disease Recognition, Junde Chen, Yun Wang, Adnan Zeb, M. D. Suzauddola, Yuxin Wen

Engineering Faculty Articles and Research

Early recognition of Alzheimer’s disease (AD) and its precursor state, mild cognitive impairment (MCI), is pivotal in interrupting the progression of the disease and providing suitable treatment. Recent development in deep learning techniques has drawn great research attention for improving the efficacy of AD recognition. However, numerous current methods solely utilize data from a single auxiliary domain, limiting their ability to harness valuable intrinsic insights from multiple domains. To cope with the challenge, this paper is devoted to establishing an innovative multimodal medical data fusion model, termed as MMDF, to perform Alzheimer’s disease recognition. Multimodal data including clinical records and …

Generalizing Parkinson’S Disease Detection Using Keystroke Dynamics: A Self-Supervised Approach, Shikha Tripathi, Alejandro Acien, Ashley A Holmes, Teresa Arroyo-Gallego, Luca Giancardo

Faculty, Staff and Student Publications

Objective: Passive monitoring of touchscreen interactions generates keystroke dynamic signals that can be used to detect and track neurological conditions such as Parkinson's disease (PD) and psychomotor impairment with minimal burden on the user. However, this typically requires datasets with clinically confirmed labels collected in standardized environments, which is challenging, especially for a large subject pool. This study validates the efficacy of a self-supervised learning method in reducing the reliance on labels and evaluates its generalizability.

Materials and methods: We propose a new type of self-supervised loss combining Barlow Twins loss, which attempts to create similar feature representations with reduced …

Alterations In Brain Morphometric Networks And Their Relationship With Memory Dysfunction In Patients With Type 2 Diabetes Mellitus, Rye Young Kim, Yoonji Joo, Eunji Ha, Haejin Hong, Chaewon Suh, Youngeun Shim, Hyeonji Lee, Yejin Kim, Jae-Hyoung Cho, Sujung Yoon, In Kyoon Lyoo

Faculty, Staff and Student Publications

Cognitive dysfunction, a significant complication of type 2 diabetes mellitus (T2DM), can potentially manifest even from the early stages of the disease. Despite evidence of global brain atrophy and related cognitive dysfunction in early-stage T2DM patients, specific regions vulnerable to these changes have not yet been identified. The study enrolled patients with T2DM of less than five years’ duration and without chronic complications (T2DM group, n=100) and demographically similar healthy controls (control group, n=50). High-resolution T1-weighted magnetic resonance imaging data were subjected to independent component analysis to identify structurally significant components indicative of morphometric networks. Within these networks, the groups’ …

Apigenin Alleviates Autistic-Like Stereotyped Repetitive Behaviors And Mitigates Brain Oxidative Stress In Mice, Petrilla Jayaprakash, Dmytro Isaev, Keun-Hang Susan Yang, Rami Beiram, Murat Oz, Bassem Sadek

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Studying the involvement of nicotinic acetylcholine receptors (nAChRs), specifically α7-nAChRs, in neuropsychiatric brain disorders such as autism spectrum disorder (ASD) has gained a growing interest. The flavonoid apigenin (APG) has been confirmed in its pharmacological action as a positive allosteric modulator of α7-nAChRs. However, there is no research describing the pharmacological potential of APG in ASD. The aim of this study was to evaluate the effects of the subchronic systemic treatment of APG (10–30 mg/kg) on ASD-like repetitive and compulsive-like behaviors and oxidative stress status in the hippocampus and cerebellum in BTBR mice, utilizing the reference drug aripiprazole (ARP, 1 …

Novel Lipid Mediator 7s,14r-Docosahexaenoic Acid: Biogenesis And Harnessing Mesenchymal Stem Cells To Ameliorate Diabetic Mellitus And Retinal Pericyte Loss, Yan Lu, Haibin Tian, Hongying Peng, Quansheng Wang, Bruce A. Bunnell, Nicolas G. Bazan, Song Hong

School of Medicine Faculty Publications

Introduction: Stem cells can be used to treat diabetic mellitus and complications. ω3-docosahexaenoic acid (DHA) derived lipid mediators are inflammation-resolving and protective. This study found novel DHA-derived 7S,14R-dihydroxy-4Z,8E,10Z,12E,16Z,19Z-docosahexaenoic acid (7S,14R-diHDHA), a maresin-1 stereoisomer biosynthesized by leukocytes and related enzymes. Moreover, 7S,14R-diHDHA can enhance mesenchymal stem cell (MSC) functions in the amelioration of diabetic mellitus and retinal pericyte loss in diabetic db/db mice. Methods: MSCs treated with 7S,14R-diHDHA were delivered into db/db mice i.v. every 5 days for 35 days. Results: Blood glucose levels in diabetic mice were lowered by 7S,14R-diHDHA-treated MSCs compared to control and untreated MSC groups, accompanied by …

Bactericidal Efficacy Of The Combination Of Maresin-Like Proresolving Mediators And Carbenicillin Action On Biofilm-Forming Burn Trauma Infection-Related Bacteria, Anbu Mozhi Thamizhchelvan, Abdul Razak Masoud, Shanchun Su, Yan Lu, Hongying Peng, Yuichi Kobayashi, Yu Wang, Nathan K. Archer, Song Hong

School of Medicine Faculty Publications

Biofilm-associated bacterial infections are the major reason for treatment failure in many diseases including burn trauma infections. Uncontrolled inflammation induced by bacteria leads to materiality, tissue damage, and chronic diseases. Specialized proresolving mediators (SPMs), including maresin-like lipid mediators (MarLs), are enzymatically biosynthesized from omega-3 essential long-chain polyunsaturated fatty acids, especially docosahexaenoic acid (DHA), by macrophages and other leukocytes. SPMs exhibit strong inflammation-resolving activities, especially inflammation provoked by bacterial infection. In this study, we explored the potential direct inhibitory activities of three MarLs on Gram-positive (Staphylococcus aureus) and Gram-negative (Pseudomonas aeruginosa and Escherichia coli) bacteria in their biofilms that are leading …

Strategies To Combine 3d Vasculature And Brain Cta With Deep Neural Networks: Application To Lvo, Uma M Lal-Trehan Estrada, Arnau Oliver, Sunil A Sheth, Xavier Lladó, Luca Giancardo

Faculty, Staff and Student Publications

Automated tools to detect large vessel occlusion (LVO) in acute ischemic stroke patients using brain computed tomography angiography (CTA) have been shown to reduce the time for treatment, leading to better clinical outcomes. There is a lot of information in a single CTA and deep learning models do not have an obvious way of being conditioned on areas most relevant for LVO detection, i.e., the vasculature structure. In this work, we compare and contrast strategies to make convolutional neural networks focus on the vasculature without discarding context information of the brain parenchyma and propose an attention-inspired strategy to encourage this. …

Human System Composite Performance Measures: General Systems Performance Theory Insights, Lawrence Disalvi

Bioengineering Dissertations - Archive

Composite Performance Measures (CPMs) of human performance are widely employed in applications that range from mundane to life-changing, yet they are frequently presented without explanation or reference to theoretical underpinnings. The conceptual soundness of a widely used CPM approach, based on additive combination of constituent components, has been called into question by Kondraske. He argues the relevance of General Systems Performance Theory (GSPT) and performance capacity envelope concepts when applied to multidimensional CPM measures.

To obtain evidence-based answers to assertions regarding CPM types and rationale employed in medical and non-medical contexts, a Systematic Descriptive Review was conducted. Separately, the GSPT-based …

Outpatient Fall Prevention In Ambulatory Adults 65 Years Old And Over, Dorothy L. Osborne-White

Doctor of Nursing Practice (DNP) Scholarly Projects - Archive

Background: In the United States (U.S.), falls are the leading cause of injury among adults 65 and over, resulting in 36 million falls yearly (Moreland et al., 2020). According to the Centers for Disease Control and Prevention (CDC, 2023), one in four older adults experiences a fall each year. Falls are the world's second most prominent cause of accidental deaths (World Health Organization [WHO], 2021). Falls are the leading cause of both fatal and non-fatal injuries among older adults (Moreland et al., 2020).

Methods: A quality improvement project that included a fall bundle was implemented in a primary clinic. A …

Pupillometry As A Viable Augmentative And Alternative Communication Pathway: A Machine Learning Application, Kouadio Marc-Antoine Niamba

Dissertations and Theses

Every year, clinicians diagnose 5000 new Amyotrophic Lateral Sclerosis (ALS) cases in the United States (Mehta et al., 2018). ALS is a degenerative neuromuscular disease that prevents neurons from sending impulses to the muscles, thus resulting in paralysis and death. People with ALS (PALS) not only experience limited mobility but also lose their ability to communicate. Although the disease currently remains incurable, efforts to improve the patients’ communication are increasingly leading toward Augmentative and Alternative Communication (AAC) systems (Beukelman and Mirenda, 2013). AAC systems are assistive technologies that propose to counteract the defects resulting from ALS through non-verbal communication channels. …