Lilianne Rivka Mujica-Parodi

Mechanistic simulation identifies predictive dose-dependent biomarkers of propofol anesthesia

The paper uses a mechanistic model to simulate propofol's effects on brain circuits, identifying a dose-dependent biomarker confirmed in empirical data.

Mechanistic corticostriatal circuit model predicts learning-dependent fMRI dynamics and individual reward bias in humans

The paper uses a biophysical corticostriatal model to predict fMRI dynamics and individual reward bias in humans, confirming predictions through fMRI data.

Computational modeling of neurotransmitter cycling predicts human brain glutamate and GABA dynamics in response to administration of exogenous ketones

This study develops a computational model of neurotransmitter cycling to predict glutamate and GABA dynamics in response to exogenous ketones, supported by MRS data.

Motion-Corrected Structural Realignment and Quantitative Voxel Targeting in Magnetic Resonance Spectroscopy

This paper improves voxel targeting accuracy in MRS by correcting motion-induced displacement and quantifying anatomical targeting using a voxel-ROI overlap metric.

The role of structural connectivity on brain function through a Markov model of signal transmission

The paper links brain structure to function by showing that commute time, derived from diffusion MRI, correlates better with functional MRI data than other measures.

Ketosis Elevates Antioxidants and Enhances Neural Function Through Improved Bioenergetics: A 1H MR Spectroscopy Study

This study uses 1H MR Spectroscopy and rsfMRI to show that ketosis increases antioxidants and energy markers while improving neural function through enhanced bioenergetics.

Spatially convergent fMRI signatures of diabetes and male sex identify genetic vulnerabilities to accelerated brain aging

Increasing spectral DCM flexibility and speed by leveraging Julia's ModelingToolkit and automated differentiation

The paper introduces a Julia package that enhances spectral DCM flexibility and speed using ModelingToolkit and automatic differentiation for parameter estimation in neuroimaging data.

Brain signaling becomes less integrated and more segregated with age

The paper defines brain integration and segregation using the Ising model to analyze functional MRI data, finding that these states become less balanced with age.

D--hydroxybutyrate stabilizes hippocampal CA3-CA1 circuit during acute insulin resistance.

This study examines how D--hydroxybutyrate affects hippocampal circuit function during acute insulin resistance in mice, showing it rescues neuronal activity and synaptic function.

Ketosis regulates K+ ion channels, strengthening brain-wide signaling disrupted by age.

The paper investigates how ketosis affects brain signaling by reversing age-related desynchronization observed in resting-state fMRI, using EEG data and a neural mass model.

Biomimetic model of corticostriatal micro-assemblies discovers new neural code

The paper introduces a biomimetic model that generates simulated neural activity and cognitive phenomena, validated against experimental data, and discovers a new neural code predicting erroneous behaviors.

Early Path Dominance as a Principle for Neurodevelopment

The paper uses percolation theory to analyze brain development, finding that early white matter tracts become longest and densest, maintaining a giant cluster across aging and disease.

Ion Gradient-driven Bifurcations of a Multi-Scale Neuronal Model

The paper analyzes ion gradient variability in a neuronal model to show how depolarization affects neural activity and inter-regional coherence, aligning with human neuroimaging observations.

Neuropredictome: a data-driven predictome for cognitive, psychiatric, medical, and lifestyle factors on the brain

NeuroPredictome uses machine learning on UK-Biobank data to identify neurological links between brain imaging and diverse phenotypes, showing equal associations with physical/lifestyle factors as cognitive factors.

Metabolism modulates network synchrony in the aging brain

This study shows that aging reduces brain network synchrony, modeled as a critical point in communication strength, and demonstrates that metabolic changes can drive these global shifts.

Quantifying control circuit regulation in the human brain.

This paper applies control systems engineering methods to fMRI data to quantify brain circuit regulation and its dysregulation in psychiatric disorders.

Parameter estimation for correlated Ornstein-Uhlenbeck time-series

This paper develops a maximum likelihood method to estimate parameters of correlated Ornstein-Uhlenbeck processes and validates it using simulations and fMRI data.

Development of an MRI Compatible Nasal Drug Delivery Method: Probing Nicotine Addiction Dynamics

This paper develops an MRI-compatible nasal delivery system for nicotine to study addiction dynamics and confirms its ability to elicit craving cycles and activate addiction-related brain circuits.