Digital Commons Network^™

Flanker Task Performance In Young And Older Adults: A Behavioral And Erp Study, Fatima Medrano

Dissertations, Theses, and Capstone Projects

Research suggests that as we get older, executive function abilities decline (Hasher & Zacks, 1988; Salthouse, 1996). One affected ability is that of inhibitory control, which aids in monitoring our responses to non-target stimuli or information. Current research on inhibition reveals inconsistencies across studies. Monitoring brain responses during the Flanker (used to measure inhibitory control) task may add valuable insight into the processes underlying group differences behaviorally, by studying the N200 and P300 event-related potentials which have been associated with inhibitory control processes. This study investigated whether there are differences between older and younger adults in inhibitory control and whether …

Multi-Class Emotion Classification With Xgboost Model Using Wearable Eeg Headband Data, James Khamthung, Nibhrat Lohia, Seement Srivastava

SMU Data Science Review

Electroencephalography (EEG) or brainwave signals serve as a valuable source for discerning human activities, thoughts, and emotions. This study explores the efficacy of EXtreme Gradient Boosting (XGBoost) models in sentiment classification using EEG signals, specifically those captured by the MUSE EEG headband. The MUSE device, equipped with four EEG electrodes (TP9, AF7, AF8, TP10), offers a cost-effective alternative to traditional EEG setups, which often utilize over 60 channels in laboratory-grade settings. Leveraging a dataset from previous MUSE research (Bird, J. et al., 2019), emotional states (positive, neutral, and negative) were observed in a male and a female participant, each for …

Out Of Time: Altered Mental Status And Temporal Seizure On Background Of Dementia & Uti, Jennifer Nguyen, Victoria Wong Murray, Judith Anne Lightfoot, Mukarram Razvi, Kasturi Etukuru

Rowan-Virtua Research Day

Herpes simplex virus is common in the US, with an estimated seroprevalence of HSV-1 of 40% and HSV-2 of 11%. Although herpes encephalitis is rare, with an incidence of roughly 1/100,000 individuals per year in the US, the mortality rate of 70% and rapid progression make identification and treatment imperative.

An 85 year old woman was brought to the emergency department from nursing home with altered mental status of unknown duration in refractory status epilepticus on a background of dementia, history of multiple falls, and indwelling foley catheter in addition to hypertension and bilateral knee replacement. EEG demonstrated abnormal discharges …

P300 Event-Related Potential Responses To Self-Relevant Stimuli, Jordan Razzak

Electronic Theses and Dissertations

Previous literature has suggested an apparent P300 sensitivity to self-relevant stimuli. To further explore this relationship, we asked participants to submit 10 photos, each of a particular category (e.g. footwear, plants), to be used as either targets or distractors in a given condition of an oddball task. Furthermore, we attempted to see whether the effect of self-relevance on the P300 could be induced in a participant by allowing them to study a set of unique photos which would then be used as targets. Our analysis suggested that P300 amplitude elicited in response to self-relevant stimuli used as targets was statistically …

Human Electrical Brain Dynamics During Locomotor Obstacle Avoidance In Virtual Reality, Carter L. Hartman, Yu-Po Cheng, Andrew Nordin

International Journal of Exercise Science: Conference Proceedings

Visually identifying and avoiding obstacles encountered during walking is crucial for navigating real world environments. Motor deficits that affect gait and balance, and changes due to aging, can increase fall risk. There is a needed to better understand the complex relationships between gaze behaviors of the eye and electrical brain dynamics during locomotor obstacle avoidance. Virtual reality provides nearly limitless opportunities to create experimentally controlled, complex, realistic environments to study human behaviors, such as locomotion. PURPOSE: Our aim was to identify human electrocortical dynamics during walking and obstacle avoidance in virtual reality, to better understand visually guided human locomotor …

Exploring Cross-Linguistic Speech Perception In Hindi, English, And Romance-Language Through Temporal Dynamics Of Neural Activity, Yuga Kothari

Dissertations, Theses, and Capstone Projects

This study examines the effect of linguistic experience on the neural processing of Voice Onset Time (VOT) in Hindi and Romance language (Spanish and Portuguese) individuals who are bilingual in English and monolingual English speakers using the event-related potential (ERP) Mismatch Negativity (MMN) response. VOT is a linguistic property that measures the time elapsed between the release of a stop consonant and the beginning of voicing, that is, vocal fold vibration of a following vowel. In a double-oddball paradigm, participants’ (n = 41) ERP were recorded while listening to speech sounds differing in VOT. The bilabial short lag stop [p] …

Comparison Of Two At-Home Sleep Monitoring Technologies, Raymond Chong, Alex Willis, Sonya Kakaiya, Casey Schambach, Carla Todd, Alex Young

Asian Journal of Physical Therapy

Background: Despite the importance of regular sleep patterns being well-known throughout society, a growing number of people claim to be sleep-deprived. There is a need to identify a simple and unobtrusive method in which people can accurately track their sleep to monitor changes and track how their sleep affects their daytime function. Methods: Here, we compared two at-home sleep monitors, the Zeo EEG headband system and the OURA physiological ring, in twenty-seven healthy young adults to determine their relative accuracy in classifying the various sleep stages. The two devices track sleep differently. The ring relies on hand movements and hemodynamic …

Case Report: Nocturnal Low-Frequency Stimulation Of The Centromedian Thalamic Nucleus Improves Sleep Quality And Seizure Control, Surya Suresh, Ganne Chaitanya, Ajay Deep Kachhvah, Vladimir Vashin, Manojkumar Saranathan, Sandipan Pati

Journal Articles

Sleep disturbances and drug-resistant seizures significantly impact people with idiopathic generalized epilepsy (IGE). Thalamic deep brain stimulation (DBS) offers potential treatment, but its effect on sleep and seizure control needs clarification. In this study, we combined wearable sleep monitoring with electroencephalogram (EEG) confirmation to investigate the impact of nocturnal centromedian nucleus (CM) DBS parameters in a patient with drug-resistant IGE. We found that high-frequency (125 Hz) CM stimulation during sleep severely disrupted sleep macro architecture and exacerbated seizures. Conversely, switching to low-frequency (10 Hz) stimulation enhanced both sleep quality and seizure control. This study underscores the critical need to personalize …

The Influence Of Visual Perspective On The Cognitive Effort Required For Mental Representation, Jeffrey P. Hong

Theses and Dissertations (Comprehensive)

Mental representation is the process by which an individual simulates an event in their mind’s eye. This process is the foundation of the ability to remember the past, engage in prospective thinking, or imagine fictitious scenarios. An individual can mentally represent any event through their own eyes—the first-person perspective or from the viewpoint of an external observer—the third-person perspective. The perspective of representation influences outcomes related to memory, visuospatial processing, affect, social cognition, clinical diagnoses, and language processing. In turn, an individual’s tendency to favour either perspective is shaped by related factors.

The current research consists of four experiments, designed …

Are Human-Like Robots Trusted Like Humans? An Investigation Into The Effect Of Anthropomorphism On Trust In Robots Measured By Expected Value As Reflected By Feedback Related Negativity And P300, Lucy Olivia Wilson

The Plymouth Student Scientist

Robots are becoming more prevalently used in industry and society. However, in order to ensure effective use of the trust, must be calibrated correctly. Anthropomorphism is one factors which is important in trust in robots (Hancock et al., 2011). Questionnaires and investment games have been used to investigate the impact of anthropomorphism on trust, however, these methods have led to disparate findings. Neurophysiological methods have also been used as an implicit measure of trust. Feedback related negativity (FRN) and P300 are event related potential (ERP) components which have been associated with processes involved in trust such as outcome evaluation. This …

Are Human-Like Robots Trusted Like Humans? An Investigation Into The Effect Of Anthropomorphism On Trust In Robots Measured By Expected Value As Reflected By Feedback Related Negativity And P300, Lucy Olivia Wilson

The Plymouth Student Scientist

Robots are becoming more prevalently used in industry and society. However, in order to ensure effective use of the trust, must be calibrated correctly. Anthropomorphism is one factors which is important in trust in robots (Hancock et al., 2011). Questionnaires and investment games have been used to investigate the impact of anthropomorphism on trust, however, these methods have led to disparate findings. Neurophysiological methods have also been used as an implicit measure of trust. Feedback related negativity (FRN) and P300 are event related potential (ERP) components which have been associated with processes involved in trust such as outcome evaluation. This …

Estimating And Detecting Slow-Wave Events In Eeg Signals, Zhenghao Xiong

McKelvey School of Engineering Theses & Dissertations

Slow wave activity (SWA) is an electroencephalogram (EEG) pattern commonly occurring during anesthesia and deep sleep, and is hence a candidate biomarker to quantify such states and understand their connection to various phenotypes. SWA consists of individual slow waves (ISW), high-amplitude deflections lasting for approximately 0.5 to 1 second, and occurring quasi-periodically. This latter fact poses a challenge for conventional power spectral density EEG analysis methods that perform best when there is persistency of oscillatory activity. In this work, we pursue a time-domain detection framework for identifying and quantifying ISWs as a metric for SWA. Our method works, in essence, …

Multiple Dipole Source Position And Orientation Estimation Using Non-Invasive Eeg-Like Signals, Saina Namazifard

Mechanical and Aerospace Engineering Dissertations

The human brain comprises of neurons that connect with each other via electrical signals. One can record and measure these activities using an electroencephalogram (EEG). An essential use of the EEG is in locating the generating source of these signals, usually approximated by dipoles. This is important because, in some particular circumstances, neurons may not function optimally and could make the equivalent dipole generate abnormal signals. This could be a result of seizures or other brain disorders. In order to isolate such disorders, the challenge is to find a non-invasive way to locate the anomalous source. This research aims to …

Sync: Novel Bci Design For Neural Synchrony, Connectedness, And Empathy, Yaara Schattner, Yoav Zamir, Niv Siton, Karin Kimel, Noa Zecharia, Noam Goldway Goldway

IASDR Conference Series

Recent years have shown a remarkable advancement in making neural technologies accessible, transcending the confines of clinical settings, with companies introducing neural hardware once limited to specialized environments. Concurrently, scientific research has made significant strides in demonstrating the effectiveness of neurofeedback as a closed-loop system, enabling individuals to regulate neural signals consciously. While studies focus on individual-based learning, emerging evidence suggests that NF can facilitate neural synchronicity among multiple individuals. To optimize NF and achieve favorable neuro-behavioral outcomes, recent investigations propose integration of immersive interfaces that provide a holistic and meaningful learning experience. However, a disconnect between scientists and designers …

Cortical Activation During Mobility In An Indoor Real-World Environment: A Mobile Eeg Study, Sam Marshall

Electronic Thesis and Dissertation Repository

Human mobility requires neurocognitive inputs to safely navigate the environment. Previous research has examined neural processes that underly walking using mobile neuroimaging technologies, yet few studies have incorporated true real-world methods without a specific task imposed on participants (e.g., dual-task, motor demands). The present study utilized mobile electroencephalography to examine and compare theta, alpha, and beta frequency band power (μV2) in young adults during sitting and walking in laboratory and real-world environments. Our findings support that mobility and environment may modulate neural activity, as we observed increased brain activation for walking compared to sitting, and for real-world walking compared to …

Cognitive Load Detection Using Ci-Ssa For Eeg Signal Decomposition And Nature-Inspired Feature Selection, Jammisetty Yedukondalu, Lakhan Dev Sharma

Turkish Journal of Electrical Engineering and Computer Sciences

Cognitive load detection is eminent during the mental assignment of neural activity because it indicates how the brain reacts to stimuli. The level of cognitive load experienced during mental arithmetic tasks can be determined using an electroencephalogram (EEG). The EEG data were collected from publicly available datasets, namely, mental arithmetic task (MAT) and simultaneous task workload (STEW). The first phase comprises decomposing the electroencephalogram (EEG) signal into intrinsic mode functions (IMFs) using circulant singular spectrum analysis (Ci-SSA). In the second phase, entropy-based features were evaluated using IMFs. After that, the extracted features were fed to nature-inspired feature selection algorithms: genetic …

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 …

Neurodiagnostic Program Director Perceptions On Low Enrollments, Daniella Krantz

Student Dissertations

Higher education enrollments have trended downward over the last several years and fallen further due to the impact of the COVID-19 pandemic. The problem addressed in this study was low student enrollment in neurodiagnostic programs in the United States, resulting in an increasing shortage of neurodiagnostic professionals working in the field. The purpose of this descriptive qualitative study was to explore the perceptions of neurodiagnostic program directors and their views on the low enrollments in neurodiagnostic programs in the United States. A descriptive qualitative design was used to understand the perspectives of these program directors. Human capital theory, the theory …

Electrophysiological Signatures Of Error Commission And Adjustment, Mark Lavelle

Psychology ETDs

Errors inhibit attainment of our goals. Behavioral and neural adjustments following errors are often framed as independent aspects of decision-making termed threshold (or response caution) and drift rate (or evidence accumulation). We replicated and extended the association of single-trial threshold with frontal midline theta power from the previous trial, as measured from EEG in 21 participants completing a flankers task. Surprisingly, theta power also predicted next trial drift rate. Variation in brightness of the stimuli was associated with drift rate and various EEG and time-frequency features, including posterior alpha/beta power. Posterior alpha/beta power also correlated with drift rate and significantly …

Visual Complexity Of The Time-Frequency Image Pinpoints The Epileptogenic Zone: An Unsupervised Deep-Learning Tool To Analyze Interictal Intracranial Eeg, Sarvagya Gupta

Graduate Masters Theses

Epilepsy, a prevalent neurological disorder characterized by recurrent seizures, continues to pose significant challenges in diagnosis and treatment, particularly among children. Despite substantial advancements in medical technology and treatment modalities, localization of the part of brain that causes seizures (Epileptogenic Zone) remains a difficult task. Intracranial EEG (iEEG) is often used to estimate the epileptogenic zone (EZ) in children with drugresistant epilepsy (DRE) and target it during surgery. Conventionally, iEEG signals are inspected in the time domain by human experts aiming to locate epileptiform activity.

Visual scrutiny of the iEEG time-frequency (TF) images can be an alternative way to review …

Optimized Generative Pre-Training Eeg To Sentiment Classification (Ogptsc), Amira Hassan

Theses

This research aims to revolutionize electroencephalogram (EEG) analysis by proposing and developing an innovative method for sentiment classification, introducing the groundbreaking "Optimized Chat Generative Pre-training EEG to Sentiment Classification (OGPTSC)." This novel approach harnesses the power of Generative Pre-training (GPT2) as the vocabulary language model while utilizing an intelligent hyper-parameter selection method to fine-tune and optimize the model's performance. Extensive testing is conducted on a widely recognized dataset to evaluate the OGPTSC's prowess, demonstrating its exceptional capabilities in sentiment classification. Notably, this research extends its scrutiny beyond the OGPTSC by applying the same hyper-parameter selection technique to well-established models such …

An Eeg-Based Cognitive Fatigue Detection System, Karim Enamul, Pavel Hamza Reza, Ashish Jaiswal, Zadeh Mohammad Zaki, Michail Theodanidis, Glenn Wylie, Fillia Makedon

Association of Computing Machinery Open Access Agreement Publications

Mental or Cognitive fatigue (CF) is the exhaustion of the neurological system brought on by prolonged cognitive tasks. It causes performance to decline in day-to-day life. Throughout this paper, we present an experimental setup where we artificially induce cognitive fatigue to participants. During the experimental process, we collected electroencephalogram (EEG) signals from the subjects that participated in the experiment. The goal of the study is to detect the presence or absence of cognitive fatigue. Our proposed solution was able to classify cognitive fatigue of the subjects with an accuracy of 88.17%.

An Eeg-Based Cognitive Fatigue Detection System, Karim Enamul, Pavel Hamza Reza, Ashish Jaiswal, Zadeh Mohammad Zaki, Michail Theodanidis, Glenn Wylie, Fillia Makedon

Computer Science and Engineering Faculty Publications

Mental or Cognitive fatigue (CF) is the exhaustion of the neurological system brought on by prolonged cognitive tasks. It causes performance to decline in day-to-day life. Throughout this paper, we present an experimental setup where we artificially induce cognitive fatigue to participants. During the experimental process, we collected electroencephalogram (EEG) signals from the subjects that participated in the experiment. The goal of the study is to detect the presence or absence of cognitive fatigue. Our proposed solution was able to classify cognitive fatigue of the subjects with an accuracy of 88.17%.

Classifying Unstable And Stable Walking Patterns Using Electroencephalography Signals And Machine Learning Algorithms, Rahul Soangra, Jo Armour Smith, Sivakumar Rajagopal, Sai Viswanth Reddy Yedavalli, Erandumveetil Ramadas Anirudh

Physical Therapy Faculty Articles and Research

Analyzing unstable gait patterns from Electroencephalography (EEG) signals is vital to develop real-time brain-computer interface (BCI) systems to prevent falls and associated injuries. This study investigates the feasibility of classification algorithms to detect walking instability utilizing EEG signals. A 64-channel Brain Vision EEG system was used to acquire EEG signals from 13 healthy adults. Participants performed walking trials for four different stable and unstable conditions: (i) normal walking, (ii) normal walking with medial-lateral perturbation (MLP), (iii) normal walking with dual-tasking (Stroop), (iv) normal walking with center of mass visual feedback. Digital biomarkers were extracted using wavelet energy and entropies from …

Neural Mechanisms Of Language Development In Infancy, Scott Huberty, Christian O'Reilly, Virginia Carter Leno, Mandy Steiman, Sara J. Webb, Mayada Elsabbagh, The Basis Team

Publications

Understanding the neural processes underpinning individual differences in early language development is of increasing interest, as it is known to vary in typical development and to be quite heterogeneous in neurodevelopmental conditions. However, few studies to date have tested whether early brain measures are indicative of the developmental trajectory of language, as opposed to language outcomes at specific ages. We combined recordings from two longitudinal studies, including typically developing infants without a family history of autism, and infants with increased likelihood of developing autism (infant-siblings) (N = 191). Electroencephalograms (EEG) were recorded at 6 months, and behavioral assessments at …

Eeg Decoding Of Finger Numeral Configurations With Machine Learning, Roya Salehzadeh, Brian Rivera, Kaiwen Man, Nader Jalili, Firat Soylu

Department of Psychology: Faculty Publications

In this study, we used multivariate decoding methods to study processing differences between canonical (montring and count) and noncanonical finger numeral configurations (FNCs). While previous research investigated these processing differences using behavioral and event-related potentials (ERP) methods, conventional univariate ERP analyses focus on specific time intervals and electrode sites and fail to capture broader scalp distribution and EEG frequency patterns. To address this issue a supervised learning classifier—support vector machines (SVM)—was used to decode ERP scalp distributions and alpha-band power for montring, counting, and noncanonical FNCs (for integers 1 to 4). The SVM was used to test whether the numerical …

A Single-Case Alternating Treatments Design Utilzing Quantitative Electroencephalography To Observe And Measure Mental State Trends During Individual Participant Non-Nature-Based Small Initiative Adventure Therapy Experiences, Patrick Lane Robert Mcmillion

Graduate Research Theses & Dissertations

This single-case alternating-treatments design research study observed and measured mental state trends during the counseling approach known as Adventure Therapy (AT) using quantitative electroencephalography (qEEG). Participants wore a qEEG headset while participating in a multi-stage AT experience. Two problems were addressed in this study. The first was the lack of research in AT utilizing other empirical measures beyond subjective report surveys and the outcomes of specific programs. The second was the lack of neuroscientific measurement of counseling approaches and interventions within the field of counseling in general. There is a need for empirical evidence supporting AT to address access barriers …

Correlation Between Electroencephalogram And Clinical Assessment Of Neonatal Seizures In Full Term Neonates, Nikhil Bhana

Cooper Medical School of Rowan University Capstone Projects

Background: There is minimal consensus on how to properly treat subclinical seizure events detected on physical exam without electroencephalogram (EEG) findings, or how aggressively to treat seizures detected on EEG. Many of these newborns are discharged from neonatal intensive care units (NICU), while on anticonvulsant medications, without clear guidance on when to discontinue medication and the factors supporting this decision. Objective: To determine whether there is a difference in continuing need for medical seizure treatment at the time of NICU discharge and one year after discharge in full term babies diagnosed with seizures primarily via physical exam versus …