Marie Schaer

The paper analyzes EEG data from 4,812 individuals to identify shared and distinct neurophysiological signatures across psychiatric conditions and rare genetic variants.

The paper examines neural speech processing differences in infants at high and low likelihood for autism using EEG, finding reduced syllable tracking in high likelihood infants linked to verbal outcomes.

This study investigates speech processing in children with ASD and finds reduced auditory response encoding and disrupted audio-visual temporal coordination.

The paper analyzes longitudinal eye-tracking data to show divergent gaze patterns in children with autism compared to typically developing peers during social interaction viewing, with differences increasing over time.

This study identifies atypical neural oscillation coupling in young children with ASD that predicts speech reception difficulties.

The paper examines temporal dynamics of brain networks in young children with autism using EEG microstates, finding altered microstate patterns and compensatory mechanisms in ASD.

The paper quantifies spatio-temporal brain dynamics in autism using two novel measures and finds atypical connectivity patterns, with differences based on symptom severity and domain.

This study uses network control theory to analyze brain dynamics in 22q11DS, finding altered persistence control energy and reduced dynamic efficiency in brain states.

The paper analyzes brain network dynamics in 22q11.2 deletion syndrome to identify biomarkers for psychosis and anxiety risk.

The paper investigates early brain network alterations in toddlers and preschoolers with autism using gaze patterns and brain activity during social scene exploration, finding increased hyper-activity and hyper-connectivity in social brain networks.

MRIQC is a tool for predicting MRI image quality that generalizes across sites with 76% accuracy but struggles with site-specific artifacts.