Sarang S. Dalal

High frequency oscillations measured with optically pumped magnetometers from the human retina

This study measures high-frequency oscillations in the human retina using optically pumped magnetometers and finds they can be detected up to 140 Hz.

Detection of threshold-level stimuli modulated by temporal predictions of the cerebellum

This study shows that cerebellar activity related to temporal expectations affects detection performance of at-threshold stimuli in a sequence-dependent manner.

Information redundancy across spatial scales modulates early visual cortical processing

The paper shows that redundant low-spatial frequency information in images reduces high-spatial frequency representational dominance and gamma-band power in visual cortex.

Contactless recordings of retinal activity using optically pumped magnetometers

This study uses optically pumped magnetometers to record human retinal activity and compares it to electroretinograms, finding significant shared information and potential for contactless retinal activity recording.

The cerebellar clock: predicting and timing somatosensory touch

This study uses magnetoencephalography to show that the cerebellum generates beta and theta band responses to predict and time rhythmic somatosensory stimuli.

Comparison of beamformer implementations for MEG source localization

This study compares LCMV beamformer implementations across four MEG toolboxes, finding reliable source localization at typical SNR but differences in sensitivity to preprocessing parameters and SNR effects.

Faster than the brain's speed of light: Retinocortical interactions differ in high frequency activity when processing darks and lights

The paper investigates retinocortical interactions during dark and light stimulus processing, finding that darks propagate faster with narrow-band high-frequency coupling, while lights use wide-band coupling.

Across-subjects classification of stimulus modality from human MEG high frequency activity

This paper decodes stimulus modality from single-trial MEG high frequency activity across subjects using beamformer source reconstruction and random forest classification, achieving 66.44% accuracy.