Rajanikant Panda

4Rose Dawn Bharath
3Lija George
2Arumugam Thamodharan
2Rose D. Bharath
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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(More)
Current research suggests that human consciousness is associated with complex, synchronous interactions between multiple cortical networks. In particular, the default mode network (DMN) of the resting brain is thought to be altered by changes in consciousness, including the meditative state. However, it remains unclear how meditation alters the fast and(More)
BACKGROUND Patients with Parkinson's disease (PD) may develop several gait disturbances during the course of illness and Freezing of gait (FOG) is one of them. Several neuroimaging studies have been conducted to identify the neural correlates of FOG but results have not been uniform. Resting state functional MRI (rs-fMRI) is relatively less explored in PD(More)
Brains reveal amplified plasticity as they recover from an injury. We aimed to define time dependent plasticity changes in patients recovering from mild traumatic brain injury (mTBI). Twenty-five subjects with mild head injury were longitudinally evaluated within 36 h, 3 and 6 months using resting state functional connectivity (RSFC). Region of interest(More)
Measuring neuro-haemodynamic correlates in the brain of epilepsy patients using EEG-fMRI has opened new avenues in clinical neuroscience, as these are two complementary methods for understanding brain function. In this study, we investigated three patients with drug-resistant reflex epilepsy using EEG-fMRI. Different types of reflex epilepsy such as eating,(More)
BACKGROUND Resting state (task independent) Functional Magnetic Resonance Imaging (fMRI) has opened a new avenue in cognitive studies and has found practical clinical applications. MATERIALS AND METHODS Resting fMRI analysis was performed in six patients with brain tumor in the motor cortex. For comparison, task-related mapping of the motor cortex was(More)
– Feature extraction and classification of electro-physiological signals is an important issue in development of disease diagnostic expert system (DDES). In this paper we propose a method based on chaos methodology for EEG signal classification. The nonlinear dynamics of original EEGs are quantified in the form of entropy, largest Lyapunov exponent (LLE),(More)
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