The desire to reduce the dependence on curated, labeled datasets and to leverage the vast
quantities of unlabeled data has triggered renewed interest in unsupervised (or self …

Memory reactivations and replay, widely reported in the hippocampus and cortex across
species, have been implicated in memory consolidation, planning, and spatial and skill …

As datasets in neuroscience increase in size and complexity, interpreting these high-
dimensional data is becoming more critical. However, develo** an intuition for patterns or …

Neuroscientists and neuroengineers have long relied on multielectrode neural recordings to
study the brain. However, in a typical experiment, many factors corrupt neural recordings …

This article presents an innovative solution for electromyography (EMG)-based human
motion analysis systems, addressing challenges of sensor comfort, interindividual variations …

Objective Cluster analysis of spatio-temporal event-related potential (ERP) data is a
promising tool for exploring the measurement time window of ERPs. However, even after …

Relating behavior to brain activity in animals is a fundamental goal in neuroscience, with
practical applications in building robust brain-machine interfaces. However, the domain gap …

Objective Neural dynamical models reconstruct neural data using dynamical systems. These
models enable direct reconstruction and estimation of neural time-series data as well as …

There are significant milestones in modern human's civilization in which mankind stepped
into a different level of life with a new spectrum of possibilities and comfort. From fire-lighting …

Electroencephalography (EEG) is a noninvasive neuroimaging technique that records
neurological brain activities via electrodes on the scalp, capturing voltage potentials …