Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons^™

In-Season Concussion Symptom Reporting In Male And Female Collegiate Rugby Athletes, Emily E. Kieffer,, P. Gunnar Brolinson, Arthur C. Maerlender, Eric Smith, Steven Rowson

Center for Brain, Biology, and Behavior: Faculty and Staff Publications

Symptom inventories are generally only collected after a suspected concussion, but regular in-season monitoring may allude to clinical symptoms associated with repetitive subconcussive impacts and potential undiagnosed concussions. Despite sex-specific differences in symptom presentation and outcome of concussion, no return-to-play protocol takes sex into account. The objective of this study was to monitor a cohort of contact-sport athletes and compare the frequency and severity of in-season concussion-like symptom reporting between sexes. Graded symptom checklists from 144 female and 104 male athlete-seasons were administered weekly to quantify the effect of subconcussive impacts on frequency and severity of in-season symptom reporting. In-season, …

Evaluating The Perspectives Of Those With Severe Physical Impairments While Learning Bci Control Of A Commercial Augmentative And Alternative Communication Paradigm, Kevin Pitt, Jonathan S. Brumberg

Department of Special Education and Communication Disorders: Faculty Publications

Augmentative and alternative communication (AAC) techniques can provide access to communication for individuals with severe physical impairments. Brain–computer interface (BCI) access techniques may serve alongside existing AAC access methods to provide communication device control. However, there is limited information available about how individual perspectives change with motor-based BCI-AAC learning. Four individuals with ALS completed 12 BCI-AAC training sessions in which they made letter selections during an automatic row-column scanning pattern via a motor-based BCI-AAC. Recurring measures were taken before and after each BCI-AAC training session to evaluate changes associated with BCI-AAC performance, and included measures of fatigue, frustration, mental effort, …

Overview Of The Microbiome Among Nurses Study (Micro-N) As An Example Of Prospective Characterization Of The Microbiome Within Cohort Studies, Christine Everett, Chengchen Li, Jeremy E. Wilkinson, Long H. Nguyen, Lauren J. Mciver, Kerry Ivey, Jacques Izard, Natalia Palacios, A. Heather Eliassen, Walter C. Willett, Alberto Ascherio, Qi Sun, Shelley S. Tworoger, Andrew T. Chan, Wendy S. Garrett, Curtis Huttenhower, Eric B. Rimm, Mingyang Song

Department of Food Science and Technology: Faculty Publications

A lack of prospective studies has been a major barrier for assessing the role of the microbiome in human health and disease on a population-wide scale. To address this significant knowledge gap, we have launched a large-scale collection targeting fecal and oral microbiome specimens from 20,000 women within the Nurses’ Health Study II cohort (the Microbiome Among Nurses study, or Micro-N). Leveraging the rich epidemiologic data that have been repeatedly collected from this cohort since 1989; the established biorepository of archived blood, urine, buccal cell, and tumor tissue specimens; the available genetic and biomarker data; the cohort’s ongoing follow-up; and …

Deep-Learning-Based Multivariate Pattern Analysis (Dmvpa): A Tutorial And A Toolbox, Karl M. Kuntzelman, Jacob M. Williams, Phui Cheng Lim, Ashtok Samal, Prahalada K. Rao, Matthew R. Johnson

Center for Brain, Biology, and Behavior: Faculty and Staff Publications

In recent years, multivariate pattern analysis (MVPA) has been hugely beneficial for cognitive neuroscience by making new experiment designs possible and by increasing the inferential power of functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and other neuroimaging methodologies. In a similar time frame, “deep learning” (a term for the use of artificial neural networks with convolutional, recurrent, or similarly sophisticated architectures) has produced a parallel revolution in the field of machine learning and has been employed across a wide variety of applications. Traditional MVPA also uses a form of machine learning, but most commonly with much simpler techniques based on …

Testing The Use Of A Social Networking App For American Indians Recovering From Addiction, Nicholas Guenzel, Dennis Mcchargue, Hongying Dai

Department of Psychology: Faculty Publications

Objectives: American Indians (AIs) have higher rates of addiction than most other groups. Social networking mobile apps are growing in popularity but their use has not been studied among AIs specifically. Methods: This paper describes a pilot program in which 27 AIs recovering from addiction were given access to a mobile app to support addiction recovery (Sober Grid) for up to six months. They completed a technology acceptability survey, monthly surveys of cravings, social connectedness, and quality of life, and a follow-up survey. Their use of the app was also tracked. Findings: We found that individuals in the sample often …

Resting Cerebral Oxygen Metabolism Exhibits Archetypal Network Features, Nicholas A. Hubbard, Monroe P. Turner, Kevin R. Sitek, Kathryn L. West, Jakub R. Kaczmarzyk, Lyndahl Himes, Binu P. Thomas, Hanzhang Lu, Bart Rypma

Center for Brain, Biology, and Behavior: Faculty and Staff Publications

Standard magnetic resonance imaging approaches offer high-resolution but indirect measures of neural activity, limiting understanding of the physiological processes associated with imaging findings. Here, we used calibrated functional magnetic resonance imaging during the resting state to recover low-frequency fluctuations of the cerebral metabolic rate of oxygen (CMRO2). We tested whether functional connections derived from these fluctuations exhibited organization properties similar to those established by previous standard functional and anatomical connectivity studies. Seventeen participants underwent 20 min of resting imaging during dual-echo, pseudocontinuous arterial spin labeling, and blood-oxygen-level dependent (BOLD) signal acquisition. Participants also underwent a 10 min normocapnic and hypercapnic …

Test-Retest Reliability And Minimal Detectable Change Of The Computerized Dynamic Posturography Proprio For Adults With Chronic Traumatic Brain Injury, Guilherme Manna Cesar, Thad W. Buster, Judith M. Burnfield

Department of Mechanical and Materials Engineering: Faculty Publications

Purpose: Balance deficits after brain injury, including reactive recovery from unexpected perturbations, can persist well after rehabilitation is concluded. While traditional clinical assessments are practical, the anticipatory nature of the tasks may mask perceptible balance control. Computerized dynamic posturography can directly quantify capacity to respond to unexpected, external perturbations. This study examined the reliability of the computerized dynamic posturography assessment with the device PROPRIO® 4000 in adults with traumatic brain injury and created the minimal detectable change for its standardized test.

Methods: Ten adults (ages 21–55 years) with chronic (average 10 ± 6 years post-injury) severe (loss of consciousness 2–75 …

Somatosensory Dysfunction Is Masked By Variable Cognitive Deficits Across Patients On The Alzheimer’S Disease Spectrum, Alex I. Wiesman, Victoria M. Mundorf, Chloe C. Casagrande, Sara L. Wolfson, Craig M. Johnson, Pamela E. May, Daniel L. Murman, Tony W. Wilson

Center for Brain, Biology, and Behavior: Faculty and Staff Publications

Background: Alzheimer’s disease (AD) is generally thought to spare primary sensory function; however, such interpretations have drawn from a literature that has rarely taken into account the variable cognitive declines seen in patients with AD. As these cognitive domains are now known to modulate cortical somato-sensory processing, it remains possible that abnormalities in somatosensory function in patients with AD have been suppressed by neuropsychological variability in previous research. Methods: In this study, we combine magnetoencephalographic (MEG) brain imaging during a paired-pulse somatosensory gating task with an extensive battery of neuropsychological tests to investigate the influence of cognitive variability on estimated …