Stephanie R. Jones

The paper updates the Human Neocortical Neurosolver model to include biophysically realistic dynamics in human neurons, enabling better interpretation of EEG/MEG signals.

This paper proposes a computational model of deviance detection in neocortical circuits based on competitive inhibition between neural ensembles, showing it can encode short-term stimulus memory and explain experimental observations.

This paper demonstrates how physics-based neural simulations can interpret EEG biomarkers of neurotherapeutics by connecting localized EEG signals to multi-scale neural generators.

This paper introduces a biophysically detailed reservoir computing framework to study how biophysical properties affect cognitive task performance in neural networks.

This paper evaluates the universality and reliability of a spectrolaminar motif in primate neocortex, finding it not universal and methods unreliable.

This paper uses biophysical modeling to investigate the neurophysiology of mismatch negativity (MMN) in humans, identifying specific cortical layers and circuits involved in deviant processing.

This study examines how burst features of oscillatory activity in alpha, beta, and high frequency bands relate to working memory accuracy in healthy adults.

The paper investigates bursting patterns in EEG data from adolescents with ADHD and finds that deviations in alpha/beta and gamma burst dynamics correlate with working memory errors and clinical symptoms.

The paper uses a biophysical model to simulate the neural mechanisms of frontocentral ERP features during action-stopping and links them to a behavioral race model.

This paper provides guidelines for applying simulation based inference to estimate parameters in large-scale biophysically detailed neural models, focusing on time series data like MEG/EEG waveforms.

This paper identifies distinct neocortical mechanisms for human SI responses to median nerve and laser-evoked peripheral stimulation using computational modeling.

This study examines age-related changes in transient gamma band activity during working memory maintenance in adolescents using EEG and spectral event processing.

The paper constructs a biophysically detailed model of the STN-GPe network to investigate how theta band activity and spiking in the subthalamic nucleus arise during response conflict.

This study identifies laminar dynamics of beta bursts in human motor cortex using high precision MEG and a neocortical circuit model, showing distinct excitatory inputs to deep and superficial layers.

This study investigates how thalamocortical beta events influence tactile perception using MEG and biophysical modeling, finding both suppressive and facilitatory effects depending on timing.

The paper quantifies and classifies multi-cycle oscillation events in primate auditory cortex, revealing non-constant frequency and amplitude characteristics across frequency bands.

The paper introduces HNN, a software tool that interprets the cellular and network origin of human MEG/EEG data using a neocortical circuit model.

The paper investigates how neocortical beta events influence tactile perception using MEG and computational modeling, finding that beta events suppress sensory processing through GABAB inhibition.

This paper develops a biophysical model of VIM to investigate how extrinsic and intrinsic oscillatory activity contribute to essential tremor.

This paper uses computational modeling to show that symmetric biphasic DBS is more effective than standard DBS at reducing tremor frequency oscillations in the thalamus, with stronger effects on intrinsic networks.

The paper shows that the rate of transient high-power beta events in brain signals predicts impaired function across human and mouse tasks.