Benjamin Lahner

MOSAIC aggregates eight fMRI datasets to enable large-scale modeling of human vision, showing improved decoding accuracy with diverse stimuli and joint brain-optimized encoding models.

The paper introduces BOLD Moments Dataset (BMD), a video fMRI dataset capturing whole-brain responses to naturalistic videos, and shows its ability to capture temporal dynamics and correlate with video memorability.

This study shows that stimulating engram neurons during the trough of theta oscillations enhances memory recall more than fixed frequency or peak stimulation.

This study reveals a hierarchical progression of category selectivity in sound processing by analyzing spatiotemporal dynamics using MEG and fMRI.

This study shows that layers in deep convolutional neural networks exhibit spatial organization similar to human brain regions, with central and peripheral biases matching foveal and parahippocampal areas.

This study evaluates the reliability and generalizability of fMRI-MEG data fusion using representational similarity analysis in human visual streams.