Mark Joseph A. Fiecas

Fast Generalized Longitudinal Functional Principal Components Analysis with Applications to Population-Level Neuronal Dynamics

This paper introduces a fast generalized LFPCA method for analyzing longitudinal functional data, showing it is faster and scalable while applied to neuronal firing rate data under DBS.

Spontaneous eye behavior is an objective marker of parkinsonian severity

The paper shows that spontaneous eye behavior in a nonhuman primate PD model correlates with disease severity and beta oscillatory activity, suggesting it as a potential biomarker.

Cerebral cortical structures linked to intelligence

This study identifies the dorsolateral prefrontal cortex as strongly linked to intelligence using large-scale MRI data and Mendelian randomization, with additional regions showing causal relationships.

Excessive cortical beta oscillations are associated with slow-wave sleep dysfunction in mild parkinsonism

The paper links excessive cortical beta oscillations to slow-wave sleep dysfunction in mild parkinsonism using a nonhuman primate model.

Deep Learning-based Feature Extraction with MRI Data in Neuroimaging Genetics for Alzheimer's Disease

The paper uses deep learning to extract neuroimaging features from MRI data for Alzheimer's disease GWAS, identifying associated SNPs linked to neurodegenerative disorders.

Approximate Hidden Semi-Markov Models for Dynamic Connectivity Analysis in Resting-State fMRI

This paper introduces an approximate hidden semi-Markov model for dynamic connectivity analysis in resting-state fMRI, showing how dwell-time distributions vary with NSSI severity in adolescents.

CLEAN: Leveraging spatial autocorrelation in neuroimaging data in clusterwise inference

CLEAN improves clusterwise inference in neuroimaging by accounting for spatial autocorrelation, enhancing sensitivity and reproducibility.

High-frequency oscillations in the internal globus pallidus: a pathophysiological biomarker in Parkinson's disease?

This study identifies high-frequency oscillations in the internal globus pallidus as a pathophysiological feature of Parkinson's disease using clinical and preclinical data.

A Longitudinal Model for Functional Connectivity Networks Using Resting-State fMRI

This paper introduces a longitudinal functional connectivity network model for fMRI data, accounting for autocorrelation and subject variability, and applies it to Alzheimer's Disease Neuroimaging Initiative data.