Borja Rodríguez‐Herreros

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 shows that small sample sizes in EEG case-control studies lead to unreliable results, while larger samples produce consistent and reproducible findings.

The paper identifies three neurophysiological biotypes in youth using EEG data, revealing brain-behavior relationships that challenge traditional diagnostic categories.

This study shows that satiety accelerates, rather than abolishes, the influence of food-associated cues in humans, with real-time ingestion affecting reward devaluation dynamics.

This study investigates how BMI and satiety affect attentional bias toward high-calorie food cues, finding that BMI modulates this bias even when satiated.

The paper examines how attentional bias toward food cues is influenced by macronutrient composition and participants' prior protein consumption.

The paper identifies altered functional connectivity patterns in young children with ASD using EEG data and links them to cognitive, social, and sensory dimensions of the disorder.

This paper quantifies EEG heterogeneity in psychiatric disorders using normative modeling, finding significant individual deviations that correlate with clinical assessments.

This study examines subcortical brain alterations in CNV carriers across multiple neuropsychiatric disorders, finding shared and distinct patterns of structural changes.

This study examines how fasting affects response inhibition to food-related cues, finding increased commission errors in high-caloric food trials during fasting.

The paper identifies a sustained decrease in corticomotor excitability as a neural marker of proactive inhibitory control during error correction.

The paper investigates how eight rare CNVs affect brain structure and phenotypes across 534 carriers, finding structural divergence and phenotypic convergence despite different genetic origins.

The paper estimates the effect sizes of deletions and duplications on autism risk and IQ using statistical models applied to CNV data from multiple cohorts.

The paper examines the effects of neuropsychiatric CNVs on brain structure using neuroimaging data and identifies shared anatomical patterns across multiple CNVs.