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Obaid, S.

Publications and source records attributed to Obaid, S..

2 recordsLinked to original sources

Statistical learning in epilepsy: Behavioral, anatomical, and causal mechanisms in the human brain

Statistical learning, the fundamental cognitive ability of humans to extract regularities across experiences over time, engages the medial temporal lobe in the healthy brain. This leads to the hypothesis that statistical learning may be impaired in epilepsy patients, and that this impairment could contribute to their varied memory deficits. In turn, epilepsy patients provide a platform to advance basic understanding of statistical learning by helping to evaluate the necessity of medial temporal lobe circuitry through disease and causal perturbations. We implemented behavioral testing, volumetric analysis of the medial temporal lobe substructures, and direct electrical brain stimulation to examine statistical learning across a cohort of 61 epilepsy patients and 28 healthy controls. Behavioral performance in a statistical learning task was negatively associated with seizure frequency, irrespective of where seizures originated in the brain. The volume of hippocampal subfields CA1 and CA2/3 correlated with statistical learning performance, suggesting a more specific role of the hippocampus. Indeed, transient direct electrical stimulation of the hippocampus disrupted statistical learning. Furthermore, the relationship between statistical learning and seizure frequency was selective: behavioral performance in an episodic memory task was impacted by structural lesions in the medial temporal lobe and by antiseizure medications, but not by seizure frequency. Overall, these results suggest that statistical learning may be hippocampally dependent and that this task could serve as a clinically useful behavioral assay of seizure frequency distinct from existing neuropsychological tests. Simple and short statistical learning tasks may thus provide patient-centered endpoints for evaluating the efficacy of novel treatments in epilepsy.

neuroscience↗

Graphene Biointerface for Cardiac Arrhythmia Diagnosis and Treatment

Heart rhythm disorders, known as arrhythmias, cause significant morbidity and are one of the leading causes of mortality. Cardiac arrhythmias are primarily treated by implantable devices, such as pacemakers and defibrillators, or by ablation therapy guided by electroanatomical mapping. Pharmacological treatments are mostly ineffective. Both implantable and ablation therapies require sophisticated biointerfaces for electrophysiological measurements of electrograms and delivery of therapeutic stimulation or ablation energy. In this work, we report for the first time on graphene biointerface for in vivo cardiac electrophysiology. Leveraging sub-micrometer thick tissue-conformable graphene arrays, we demonstrate sensing and stimulation of the open mammalian heart both in vitro and in vivo. Furthermore, we demonstrate graphene pacemaker treatment of a pharmacologically-induced arrhythmia, AV block. The arrays show effective electrochemical properties, namely interface impedance down to 40 Ohmxcm2 at 1kHz, charge storage capacity up to 63.7 mC/cm2, and charge injection capacity up to 704 C/cm2. Transparency of the graphene structures allows for simultaneous optical mapping of cardiac action potentials and optogenetic stimulation while performing electrical measurements and stimulation. Our report presents evidence of the significant potential of graphene biointerfaces for the future clinical device- and catheter-based cardiac arrhythmias therapies.

bioengineering↗