Alfonso Nieto-Castañón

The paper uses fMRI to show that language network lateralization is adult-like by age 4, despite continued development of other language network features.

The paper introduces IC-TFCE, an algorithm that improves the computational efficiency of threshold-free cluster enhancement for functional connectivity analysis, achieving significant speedups for large-scale analyses.

The paper identifies brain regions outside the language network involved in semantic processing of both linguistic and pictorial stimuli using fMRI experiments.

The paper uses precision fMRI to show the language-selective network supports both phrase-structure building and lexical access during language production, with stronger responses in production than comprehension.

The paper introduces a probabilistic atlas for the language network using fMRI data from 806 individuals to bridge gaps between group-level and individual-level language research.

This study investigates how rhythmic speech affects neural activity in people who stutter, finding increased cerebellar connectivity during rhythmic speech.

The paper predicts future changes in sedentary behavior using resting state functional connectivity and baseline measures in older adults.

The paper assesses the reliability of speech-related brain activation patterns across multiple sessions and finds high reliability using traditional and machine-learning methods.