Digital Commons Network^™

The Emerging Role Of Neurodiagnostic Informatics In Integrated Neurological And Mental Health Care, William Bosl

Nursing and Health Professions Faculty Research and Publications

Mental, neurological, and neurodevelopmental (MNN) disorders impose an enormous burden of disease globally. Many MNN disorders follow a developmental trajectory. Thus, defining symptoms of MNN disorders may be conceived as the end product of a long developmental process. Many pharmaceutical therapies are aimed at the end symptoms, essentially attempting to reverse pathological brain function that has developed over a long time. A new paradigm is needed to leverage the developmental trajectory of MNN disorders, based on measuring brain function through the life span. Electroencephalography (EEG) is ideally suited for this task. New developments in several fields, including consumer EEG hardware, …

Working Memory And Falls Risk In Older Adults: An Event-Related Potential Study, Yee (Michelle) S. Wong

Electronic Thesis and Dissertation Repository

BACKGROUND: The aging population is rapidly increasing, where currently in North America, the population of older adults (ages 60+) outnumbers the population of children. Falls are a major concern for older adults and their quality of life. Cognitive impairment has been shown to be declined in older adults at-risk for falls, but working memory has not been thoroughly investigated within this population. PURPOSE: To examine differences in Non-Fallers, Moderate Risk for Falls, and Fallers in a working memory task using electroencephalography (EEG). METHODS: Older adults (n=44, female=27) aged 60 – 80 years (m=68.8, SD=4.7) completed two sessions. The first session …

Cortical Statistical Correlation Tomography Of Eeg Resting State Networks, Chuang Li, Han Yuan, Guofa Shou, Yoon-Hee Cha, Sridhar Sunderam, Walter Besio, Lei Ding

Biomedical Engineering Faculty Publications

Resting state networks (RSNs) have been found in human brains during awake resting states. RSNs are composed of spatially distributed regions in which spontaneous activity fluctuations are temporally and dynamically correlated. A new computational framework for reconstructing RSNs with human EEG data has been developed in the present study. The proposed framework utilizes independent component analysis (ICA) on short-time Fourier transformed inverse source maps imaged from EEG data and statistical correlation analysis to generate cortical tomography of electrophysiological RSNs. The proposed framework was evaluated on three sets of resting-state EEG data obtained in the comparison of two conditions: (1) healthy …

Electrophysiological Biomarkers Of Chemotherapy-Related Cognitive Impairment In Hematological Malignancy Patients, David E. Anderson

Theses & Dissertations

Multiple cancer populations frequently report cognitive impairment following treatment with chemotherapy agents (“chemo-brain”). Impaired neuropsychological performance is commonly reported in cognitive domains of attention and executive function. Understanding neural mechanisms underlying cognitive impairments is essential to developing prevention and rehabilitation strategies. Brain imaging studies frequently show chemotherapy-related impairments within the attentional control network, which is comprised of a constellation of cortical regions that govern reportedly impaired cognitive functions. In the current dissertation research, I developed a novel electrophysiology battery aimed at recording near-instantaneous neural activity within the attentional control network during cognitive task performance. Cancer patients diagnosed with hematological malignancy …

Treating Adhd With Suggestion: Neurofeedback And Placebo Therapeutics, Robert T. Thibault, Samuel Vassière, Jay A. Olson, Amir Raz

Psychology Faculty Articles and Research

Objective: We propose that clinicians can use suggestion to help treat conditions such as ADHD. Methods: We use EEG neurofeedback as a case study, alongside evidence from a recent pilot experiment utilizing a sham MRI scanner to highlight the therapeutic potential of suggestion-based treatments. Results: The medical literature demonstrates that many practitioners already prescribe treatments that hardly outperform placebo comparators. Moreover, the sham MRI experiment showed that, even with full disclosure of the procedure, suggestion alone can reduce the symptomatology of ADHD. Conclusion: Non-deceptive suggestion-based treatments, especially those drawing on accessories from neuroscience, may offer a safe complement and potential …

Sensorimotor Modulations By Cognitive Processes During Accurate Speech Discrimination: An Eeg Investigation Of Dorsal Stream Processing, David E. Jenson

Theses and Dissertations (ETD)

Internal models mediate the transmission of information between anterior and posterior regions of the dorsal stream in support of speech perception, though it remains unclear how this mechanism responds to cognitive processes in service of task demands. The purpose of the current study was to identify the influences of attention and working memory on sensorimotor activity across the dorsal stream during speech discrimination, with set size and signal clarity employed to modulate stimulus predictability and the time course of increased task demands, respectively. Independent Component Analysis of 64–channel EEG data identified bilateral sensorimotor mu and auditory alpha components from a …

Cross-Participant Eeg-Based Assessment Of Cognitive Workload Using Multi-Path Convolutional Recurrent Neural Networks, Ryan G. Hefron, Brett J. Borghetti, Christine M. Schubert Kabban, James Christensen, Justin Estep

Faculty Publications

Applying deep learning methods to electroencephalograph (EEG) data for cognitive state assessment has yielded improvements over previous modeling methods. However, research focused on cross-participant cognitive workload modeling using these techniques is underrepresented. We study the problem of cross-participant state estimation in a non-stimulus-locked task environment, where a trained model is used to make workload estimates on a new participant who is not represented in the training set. Using experimental data from the Multi-Attribute Task Battery (MATB) environment, a variety of deep neural network models are evaluated in the trade-space of computational efficiency, model accuracy, variance and temporal specificity yielding three …

Assessing Listening With Engaging, Real-World Auditory Signals, Brainscan , Western University, Björn Herrmann, Ingrid Johnsrude 6612111

Project Summaries

Our project will develop and evaluate a novel way (using functional imaging, fMRI, and electrophysiology, EEG) to assess this cognitive impact of hearing loss with engaging, real‐world auditory stimuli. We will try to assess listening effort in more realistic listening situations among healthy listeners, comparing detected effort in degraded and clear acoustic conditions.

Using EEG, we will then develop measures that are sensitive to the cognitive demands imposed by degraded speech, using these features to assess hearing function with engaging narratives in natural listening conditions.

Cognitive Load Reduces The Effects Of Optic Flow On Gait And 2 Electrocortical Dynamics During Treadmill Walking 3, Brenda Malcolm, John J. Foxe, John Butler, Sophie Molholm, Pierfilippo De Sanctis

Articles

While navigating complex environments the brain must continuously adapt to both external demands such as fluctuating sensory inputs, as well as internal demands, such as engagement in a cognitively demanding task. Previous studies have demonstrated changes in behavior and gait with increased sensory and cognitive load, but the underlying cortical mechanisms remain largely unknown. Here, in a Mobile Brain/Body Imaging (MoBI) approach sixteen young adults walked on a treadmill with high-density EEG while 3D motion capture tracked kinematics of the head and feet. Visual load was manipulated with the presentation of optic flow with and without continuous mediolateral perturbations. The …

The Signature Of Undetected Change: An Exploratory Electrotomographic Investigation Of Gradual Change Blindness, John E. Kiat, Michael D. Dodd, Robert F. Belli, Jacob E. Cheadle

Department of Psychology: Faculty Publications

Neuroimaging-based investigations of change blindness, a phenomenon in which seemingly obvious changes in visual scenes fail to be detected, have significantly advanced our understanding of visual awareness. The vast majority of prior investigations, however, utilize paradigms involving visual disruptions (e.g., intervening blank screens, saccadic movements, “mudsplashes”), making it difficult to isolate neural responses toward visual changes cleanly. To address this issue in this present study, high-density EEG data (256 channel) were collected from 25 participants using a paradigm in which visual changes were progressively introduced into detailed real-world scenes without the use of visual disruption. Oscillatory activity associated with undetected …