Cognitive and Behavioral Profile of Patients with Amyotrophic Lateral Sclerosis Spectrum in the Indian Context.

Introduction: Amyotrophic lateral sclerosis (ALS) is characterized by motor, cognitive, and behavioral impairment. There is a paucity of evidence about the cognitive/behavioral features of ALS patients from India. We aimed to investigate the cognitive/behavioral profile of ALS spectrum disorders in the Indian context.

Myotonic Dystrophy Type 1 (DM1): Clinical Characteristics and Disease Progression in a Large Cohort.

Background: DM1 is a multisystem disorder caused by expansion of a CTG triplet repeat in the 3' non-coding region of DMPK. Neuropsychological consequences and sleep abnormalities are important associations in DM1.

Objective: To describe the clinical phenotype, disease progression and characterize the sleep alterations and cognitive abnormalities in a sub-set of patients.

CASPR2-Related Morvan Syndrome: Autonomic, Polysomnographic, and Neuropsychological Observations.

Objective: Morvan syndrome is characterized by central, autonomic, and peripheral hyperexcitability due to contactin-associated protein 2 (CASPR2) antibody. Our objective was to study the clinical spectrum, electrophysiologic, autonomic, polysomnographic, and neuropsychological profile in patients with CASPR2-related Morvan syndrome.

Methods: Serum and CSF samples that were CASPR2 antibody positive from 2016 to 2019 were assessed.

Long-term Cognitive Outcomes in Tuberculous Meningitis.

Objective: Data on cognitive changes in patients with tuberculous meningitis (TBM) are sparse. We aimed to study the cognitive profiles of patients with grade I TBM and correlate them with the cytokine values.

Methods: Prospectively, 60 patients (M:F-31:29) with grade I TBM were recruited.

Machine learning identifies "rsfMRI epilepsy networks" in temporal lobe epilepsy.

Objectives: Experimental models have provided compelling evidence for the existence of neural networks in temporal lobe epilepsy (TLE). To identify and validate the possible existence of resting-state "epilepsy networks," we used machine learning methods on resting-state functional magnetic resonance imaging (rsfMRI) data from 42 individuals with TLE.

Methods: Probabilistic independent component analysis (PICA) was applied to rsfMRI data from 132 subjects (42 TLE patients + 90 healthy controls) and 88 independent components (ICs) were obtained following standard procedures.

Unraveling Brain Functional Connectivity of encoding and retrieval in the context of education.

Human memory is an enigmatic component of cognition which many researchers have attempted to comprehend. Accumulating studies on functional connectivity see brain as a complex dynamic unit with positively and negatively correlated networks in perfect coherence during a task. We aimed to examine coherence of network connectivity during visual memory encoding and retrieval in the context of education.