Yalda Mohsenzadeh

This study investigates the spatiotemporal dynamics of cross-modal memory recall and imagery using fMRI, finding a reversed hierarchy in neural activity during visual and auditory recall.

This study uses EEG-fMRI fusion to show distinct perceptual and conceptual processing of natural actions in the lateral and dorsal visual streams, with specific encoding of action targets in LOTC and pSTS.

This study investigates how the brain processes naturalistic audiovisual events using fMRI and EEG, revealing early cross-modal interactions and late integration in multi-modal areas.

This study uses fNIRS to examine functional connectivity in newborns, finding increased sensorimotor network connectivity with gestational and postnatal age.

This study uses multivariate pattern analysis of EEG to investigate the neural mechanisms of attentional blink in naturalistic target processing, finding that short inter-target intervals suppress neural representations of targets.

The paper uses machine learning on fMRI data to predict cognitive abilities in children and adolescents with ADHD, finding distinct neural mechanisms in different age groups.

The paper investigates how action representations are organized in human cognition and language models, finding shared structure based on action targets across video and sentence modalities.

The paper investigates the neural dynamics of object recognition in rapid visual sequences, finding that object categorization occurs via feedforward mechanisms around 120ms, while identification requires recurrent processing around 190ms.

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

This paper uses a generative adversarial autoencoder to model feedback processes in the ventral visual pathway by comparing neural dynamics with brain imaging data.

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.

The paper shows that the magnitude of neural responses in the inferotemporal cortex correlates with image memorability, independent of object identity coding.

The paper investigates object recognition under occlusion using MEG, behavioral data, and computational models, showing that recurrent processes are essential and that a local recurrent model explains human performance.

The paper identifies an early and prolonged neural signal of memorability during visual processing using MEG, detected outside subjective awareness.

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

This study uses ultra-rapid serial visual presentation with MEG to distinguish feedforward and feedback processing stages in the ventral visual pathway.

This study uses multivariate pattern analysis on MEG data to show that gamma oscillations encode orientation information, with stronger decoding for cardinal than oblique orientations.