Sanjeev Nara

The paper shows that early EEG responses can predict liking for artworks presented in rapid visual streams, even without explicit liking judgments.

The paper investigates how presentation time and task affect neural representations of scene beauty using EEG, finding they are largely unaffected.

The paper compares effective connectivity in chronic pain patients and placebo responders using resting-state fMRI to identify markers of nociception and placebo response.

The paper shows that language experience influences how the brain predicts rhythmic sounds using long-term priors, as evidenced by differences in mismatch negativity responses to sound omissions.

The paper shows that integrative processing in both artificial neural networks and human visual cortex predicts the perceived beauty of natural images.

This study uses MEG and MVPA to show early dissociation in brain activity for number and letter processing, with stronger dissociation in strings than single items.

This study uses MEG and machine learning to show that language selection in bilinguals can be decoded from neural activity, with distinct brain regions involved in picture naming and word reading.

The paper investigates how temporal uncertainty affects neural responses to predictable visual stimuli, finding that uncertainty increases expectation suppression and reduces sustained decoding accuracy for early visual responses.

The paper investigates the temporal dynamics of processing happy and sad facial expressions, finding faster processing of happy emotions and increased amplitude for sad emotions when viewed from the right side.