Luca Cocchi

This paper evaluates null models for Lesion Network Mapping, showing they replace the connectome matrix but do not resolve non-specificity across conditions.

This paper evaluates specificity testing in Lesion Network Mapping to address concerns about the biological interpretation and disease-specificity of derived brain circuits.

The paper investigates how frontoparietal and corticothalamic circuits contribute to relational reasoning by analyzing EEG data and neural field models during problem-solving tasks.

The paper uses EEG data from TMS-treated patients to show that changes in anterior default mode brain state dynamics predict depressive symptom improvement during treatment.

The paper evaluates how different censoring strategies affect cortical parcellations and TMS targets in rs-fMRI, finding that lenient censoring yields better results than strict censoring.

This study compares transformer models and human brain activity during relational reasoning tasks, finding alignment between attention mechanisms and neural networks involved in reasoning.

The paper investigates how brain activity patterns in alpha and beta rhythms within higher-order cortical networks track relational complexity during reasoning tasks.

This paper introduces T-TVFC, a method for targeted time-varying functional connectivity analysis, and shows it captures task-related information in thalamocortical networks not found in traditional methods.

The paper introduces a standardized nomenclature for PET-based molecular connectivity and covariance to improve reproducibility and interpretation across imaging modalities and radiotracers.

This study examines how chronic gut inflammation in IBD affects brain dynamics using EEG, finding altered brain states and connectivity patterns in CD and UC patients.

The paper investigates how metabolic demands of the posteromedial default mode network (DMN) are influenced by task-positive networks during attention-demanding tasks.

This study shows that human brain dynamics differ from chimpanzees in dynamic range distribution, supporting faster integration in transmodal systems.

This study investigates how gut microbiota influences neural dynamics in threat processing by combining neuroimaging, 16S rRNA profiling, and computational modeling in healthy participants.

This study examines white matter microstructural and morphometric differences in autism spectrum disorder (ASD) across subgroups with and without intellectual impairment, finding key alterations in corpus callosum and cerebellum.

The paper maps individual deviations from normative brain structure in schizophrenia patients and finds high heterogeneity, with most patients showing infra-normal deviations in at least one region.

The paper identifies Core and Matrix thalamic sub-populations and links them to spatio-temporal cortical connectivity gradients using fMRI and calcium-binding protein data.

The paper examines how brain age gaps relate to psychopathology dimensions in youth, finding significant associations with psychosis, obsessive-compulsive, and general psychopathology.

The paper links anatomical and functional brain features of the default mode network to pediatric concussion recovery and shows they predict persistent symptoms.

The paper identifies reduced structure-function coupling in ADHD, linking it to increased neural noise variability in fronto-parietal networks.

This study links brain connectivity patterns with persistent symptoms in children after mild traumatic brain injury using resting-state fMRI and behavioral assessments.

This study investigates brain network activity in individuals with corpus callosum dysgenesis during cognitive tasks, finding reduced connectivity in the fronto-parietal network with increased task complexity.

The paper identifies a dimensional biotype in medication-naïve adults with ADHD using brain-behavior patterns from functional connectivity and symptom correlations.

The paper examines how brain network architectures change between resting state and task-driven cognitive reasoning, finding that increased complexity leads to merging of resting state modules and selective connectivity changes.

This study shows that four weeks of unimanual motor training improves motor performance and induces structural and functional brain changes in motor-related regions.

The paper shows that neural decoding of visual stimuli is higher during periods of high global network efficiency compared to low efficiency.