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Item American Clinical Neurophysiology Society Guideline 1: Minimum Technical Requirements for Performing Clinical Electroencephalography(Lippincott, Williams, and Wilkins, 2016-08) Sinha, Saurabh R.; Sullivan, Lucy; Sabau, Dragos; San-Juan, Daniel; Dombrowski, Keith; Halford, Jonathan J.; Hani, Abeer; Drislane, Frank W.; Stecker, Mark; Department of Neurology, IU School of MedicineItem American Clinical Neurophysiology Society Guideline 1: Minimum Technical Requirements for Performing Clinical Electroencephalography(Taylor & Francis, 2016) Sinha, Saurabh R.; Sullivan, Lucy; Sabau, Dragos; San-Juan, Daniel; Dombrowski, Keith; Halford, Jonathan J.; Hani, Abeer; Drislane, Frank W.; Stecker, Mark; Department of Neurology, School of MedicineItem Cognitive manipulation of brain electric microstates(Elsevier, 2017-02-01) Seitzman, Benjamin A.; Abell, Malene; Bartley, Samuel C.; Erickson, Molly A.; Bolbecker, Amanda R.; Hetrick, William P.; Psychiatry, School of MedicineEEG studies of wakeful rest have shown that there are brief periods in which global electrical brain activity on the scalp remains semi-stable (so-called microstates). Topographical analyses of this activity have revealed that much of the variance is explained by four distinct microstates that occur in a repetitive sequence. A recent fMRI study showed that these four microstates correlated with four known functional systems, each of which is activated by specific cognitive functions and sensory inputs. The present study used high density EEG to examine the degree to which spatial and temporal properties of microstates may be altered by manipulating cognitive task (a serial subtraction task vs. wakeful rest) and the availability of visual information (eyes open vs. eyes closed conditions). The hypothesis was that parameters of microstate D would be altered during the serial subtraction task because it is correlated with regions that are part of the dorsal attention functional system. It was also expected that the sequence of microstates would preferentially transition from all other microstates to microstate D during the task as compared to rest. Finally, it was hypothesized that the eyes open condition would significantly increase one or more microstate parameters associated with microstate B, which is associated with the visual system. Topographical analyses indicated that the duration, coverage, and occurrence of microstate D were significantly higher during the cognitive task compared to wakeful rest; in addition, microstate C, which is associated with regions that are part of the default mode and cognitive control systems, was very sensitive to the task manipulation, showing significantly decreased duration, coverage, and occurrence during the task condition compared to rest. Moreover, microstate B was altered by manipulations of visual input, with increased occurrence and coverage in the eyes open condition. In addition, during the eyes open condition microstates A and D had significantly shorter durations, while C had increased occurrence. Microstate D had decreased coverage in the eyes open condition. Finally, at least 15 microstates (identified via k-means clustering) were required to explain a similar amount of variance of EEG activity as previously published values. These results support important aspects of our hypotheses and demonstrate that cognitive manipulation of microstates is possible, but the relationships between microstates and their corresponding functional systems are complex. Moreover, there may be more than four primary microstates.Item Cortical Activation Patterns in Art Making vs. Fine Motor Movement as Measured by EEG(2017) Knapp, Kaitlin; Shaikh, Alex; King, JulietThis quantitative study explores the differences in cortical activation patterns when subjects create art versus when they engage in a rote motor task. It is hypothesized that a statistically significant difference occurs in cortical activity patterns during art making compared with non- creative rote motor behavior and that such differences can be detected and quantified with the electroencephalogram (EEG.) Ten consenting study subjects (one with formal art training, three with some art experience, and six with no art experience) underwent EEG recording at baseline (multiple measures) and with art making, and also with rote motor tasking. Baseline control recordings showed minimal changes in EEG while art making was associated with a persistent change from baseline of significant direction and amplitude involving both hemispheres, a change that was similar to the persistent change in EEG following rote motor tasks. These preliminary findings suggest that EEG may be a meaningful biomarker for cortical activation in the study of creative arts and points to further exploration using Mobile Brain Body Imaging (MoBI) in experimental designs. This system provides a reproducible, measurable, and quantitative methodology for evaluating brain activity and function in the study of the neuroscientific basis of creative arts, neuroaesthetics, and art therapy.Item A Genome Wide Association Study of Interhemispheric Theta EEG Coherence: Implications for Neural Connectivity and Alcohol Use Behavior(Springer Nature, 2021) Meyers, Jacquelyn L.; Zhang, Jian; Chorlian, David B.; Pandey, Ashwini K.; Kamarajan, Chella; Wang, Jen-Chyong; Wetherill, Leah; Lai, Dongbing; Chao, Michael; Chan, Grace; Kinreich, Sivan; Kapoor, Manav; Bertelsen, Sarah; McClintick, Jeanette; Bauer, Lance; Hesselbrock, Victor; Kuperman, Samuel; Kramer, John; Salvatore, Jessica E.; Dick, Danielle M.; Agrawal, Arpana; Foroud, Tatiana; Edenberg, Howard J.; Goate, Alison; Porjesz, Bernice; Medical and Molecular Genetics, School of MedicineAberrant connectivity of large-scale brain networks has been observed among individuals with alcohol use disorders (AUDs) as well as in those at risk, suggesting deficits in neural communication between brain regions in the liability to develop AUD. Electroencephalographical (EEG) coherence, which measures the degree of synchrony between brain regions, may be a useful measure of connectivity patterns in neural networks for studying the genetics of AUD. In 8810 individuals (6644 of European and 2166 of African ancestry) from the Collaborative Study on the Genetics of Alcoholism (COGA), we performed a Multi-Trait Analyses of genome-wide association studies (MTAG) on parietal resting-state theta (3-7 Hz) EEG coherence, which previously have been associated with AUD. We also examined developmental effects of GWAS findings on trajectories of neural connectivity in a longitudinal subsample of 2316 adolescent/young adult offspring from COGA families (ages 12-30) and examined the functional and clinical significance of GWAS variants. Six correlated single nucleotide polymorphisms located in a brain-expressed lincRNA (ENSG00000266213) on chromosome 18q23 were associated with posterior interhemispheric low theta EEG coherence (3-5 Hz). These same variants were also associated with alcohol use behavior and posterior corpus callosum volume, both in a subset of COGA and in the UK Biobank. Analyses in the subsample of COGA offspring indicated that the association of rs12954372 with low theta EEG coherence occurred only in females, most prominently between ages 25 and 30 (p < 2 × 10-9). Converging data provide support for the role of genetic variants on chromosome 18q23 in regulating neural connectivity and alcohol use behavior, potentially via dysregulated myelination. While findings were less robust, genome-wide associations were also observed with rs151174000 and parieto-frontal low theta coherence, rs14429078 and parieto-occipital interhemispheric high theta coherence, and rs116445911 with centro-parietal low theta coherence. These novel genetic findings highlight the utility of the endophenotype approach in enhancing our understanding of mechanisms underlying addiction susceptibility.Item Perioperative Multimodal General Anesthesia Focusing on Specific CNS Targets in Patients Undergoing Cardiac Surgeries: The Pathfinder Feasibility Trial(Frontiers Media, 2021-10-14) Shanker, Akshay; Abel, John H.; Narayanan, Shilpa; Mathur, Pooja; Work, Erin; Schamberg, Gabriel; Sharkey, Aidan; Bose, Ruma; Rangasamy, Valluvan; Senthilnathan, Venkatachalam; Brown, Emery N.; Subramaniam, Balachundhar; Anesthesia, School of MedicineMultimodal general anesthesia (MMGA) is a strategy that utilizes the well-known neuroanatomy and neurophysiology of nociception and arousal control in designing a rational and clinical practical paradigm to regulate the levels of unconsciousness and antinociception during general anesthesia while mitigating side effects of any individual anesthetic. We sought to test the feasibility of implementing MMGA for seniors undergoing cardiac surgery, a high-risk cohort for hemodynamic instability, delirium, and post-operative cognitive dysfunction. Twenty patients aged 60 or older undergoing on-pump coronary artery bypass graft (CABG) surgery or combined CABG/valve surgeries were enrolled in this non-randomized prospective observational feasibility trial, wherein we developed MMGA specifically for cardiac surgeries. Antinociception was achieved by a combination of intravenous remifentanil, ketamine, dexmedetomidine, and magnesium together with bupivacaine administered as a pecto-intercostal fascial block. Unconsciousness was achieved by using electroencephalogram (EEG)-guided administration of propofol along with the sedative effects of the antinociceptive agents. EEG-guided MMGA anesthesia was safe and feasible for cardiac surgeries, and exploratory analyses found hemodynamic stability and vasopressor usage comparable to a previously collected cohort. Intraoperative EEG suppression events and postoperative delirium were found to be rare. We report successful use of a total intravenous anesthesia (TIVA)-based MMGA strategy for cardiac surgery and establish safety and feasibility for studying MMGA in a full clinical trial.Item Resting-state EEG, impulsiveness, and personality in daily and nondaily smokers(Elsevier, 2016-01) Rass, Olga; Ahn, Woo-Young; O'Donnell, Brian F.; Department of Psychiatry, IU School of MedicineOBJECTIVES: Resting EEG is sensitive to transient, acute effects of nicotine administration and abstinence, but the chronic effects of smoking on EEG are poorly characterized. This study measures the resting EEG profile of chronic smokers in a non-deprived, non-peak state to test whether differences in smoking behavior and personality traits affect pharmaco-EEG response. METHODS: Resting EEG, impulsiveness, and personality measures were collected from daily smokers (n=22), nondaily smokers (n=31), and non-smokers (n=30). RESULTS: Daily smokers had reduced resting delta and alpha EEG power and higher impulsiveness (Barratt Impulsiveness Scale) compared to nondaily smokers and non-smokers. Both daily and nondaily smokers discounted delayed rewards more steeply, reported lower conscientiousness (NEO-FFI), and reported greater disinhibition and experience seeking (Sensation Seeking Scale) than non-smokers. Nondaily smokers reported greater sensory hedonia than nonsmokers. CONCLUSIONS: Altered resting EEG power in daily smokers demonstrates differences in neural signaling that correlated with greater smoking behavior and dependence. Although nondaily smokers share some characteristics with daily smokers that may predict smoking initiation and maintenance, they differ on measures of impulsiveness and resting EEG power. SIGNIFICANCE: Resting EEG in non-deprived chronic smokers provides a standard for comparison to peak and trough nicotine states and may serve as a biomarker for nicotine dependence, relapse risk, and recovery.Item Silent speech recognition in EEG-based brain computer interface(2015) Ghane, Parisa; Li, Lingxi; Tovar, Andres; Christopher, Lauren Ann; King, BrianA Brain Computer Interface (BCI) is a hardware and software system that establishes direct communication between human brain and the environment. In a BCI system, brain messages pass through wires and external computers instead of the normal pathway of nerves and muscles. General work ow in all BCIs is to measure brain activities, process and then convert them into an output readable for a computer. The measurement of electrical activities in different parts of the brain is called electroencephalography (EEG). There are lots of sensor technologies with different number of electrodes to record brain activities along the scalp. Each of these electrodes captures a weighted sum of activities of all neurons in the area around that electrode. In order to establish a BCI system, it is needed to set a bunch of electrodes on scalp, and a tool to send the signals to a computer for training a system that can find the important information, extract them from the raw signal, and use them to recognize the user's intention. After all, a control signal should be generated based on the application. This thesis describes the step by step training and testing a BCI system that can be used for a person who has lost speaking skills through an accident or surgery, but still has healthy brain tissues. The goal is to establish an algorithm, which recognizes different vowels from EEG signals. It considers a bandpass filter to remove signals' noise and artifacts, periodogram for feature extraction, and Support Vector Machine (SVM) for classification.