Elizabeth Barbara Torres

The paper identifies an auditory brainstem response (ABR) biomarker for Alzheimer's Disease risk in rats, showing genetic risk prediction and intervention effects.

This paper uses facial micro-movements and heart rate variability to detect pressure pain and its impact on physiological signals across different tasks.

The paper characterizes visuomotor and proprioceptive information processing by analyzing the irregularity of instantaneous gamma frequency in neural recordings during goal-directed movements.

This paper identifies temporal misalignment in auditory brainstem responses (ABR) as an early biomarker for neurodevelopmental derailment, offering a new statistical approach for early detection of autism.

The paper analyzes transcriptome dynamics during neuronal differentiation to identify two distinct gene classes associated with psychiatric and neurological disorders.

The paper reframes statistical learning as a dynamic stochastic process influenced by motor system dynamics, identifying two learning strategies based on environmental stability.

This paper develops interpretable digital biomarkers for Parkinson's disease by combining multimodal biosensor data and identifies magnetometer signals during walking as optimal for distinguishing patients from controls.

The paper stratifies Autism spectrum disorders using genomic data to identify overlapping genes and propose subtypes for personalized therapies.

This paper introduces methods to stratify and forecast nervous system pathology using causal prediction models and motor timing analysis from walking tasks.

This paper investigates gene expression in human tissues across mental illnesses and neurological conditions, finding convergence between psychiatric and neurological disorders.

This paper investigates how fluctuations in autonomic nervous system activity differentiate between levels of motor intent and hand dominance.

This paper identifies tissues most affected by SFARI Autism genes removal and finds convergence between autism and neurological disorders in tissue expression patterns.

This study examines the empirical variability and limitations of the research-grade ADOS in characterizing autism, finding issues with normality, variance, and longitudinal consistency.