Corey J. Keller

SafeLens uses nonlinear machine learning with statistical control to detect subtle, trial-varying neural dynamics in event-locked activity, outperforming traditional methods in sensitivity and specificity.

The paper uses intracranial recordings to show that nociception and salience have distinct neural representations in the human brain, with different anatomical, temporal, and functional characteristics.

This study identifies early functional connectivity changes in MDD patients treated with antidepressants or placebo, revealing common and distinct treatment effects.

The paper identifies and mitigates a step-drift artifact in TMS-EEG recordings through a processing pipeline involving polynomial detrending and modified filtering.

This paper uses TMS-EEG to show that prefrontal cortex excitability changes with cognitive load during a multi-source interference task, linking it to theta power and showing region-specific effects.

This study shows that ibogaine treatment in PTSD veterans is linked to reorganization of high-beta brain networks, which correlates with symptom improvement.

This study shows that TMS to the dlPFC modulates single-neuron activity in humans, with facilitation of inhibitory firing and suppression of excitatory drive in specific brain networks.

This paper presents a preprocessing pipeline for TMS-iEEG data, showing it reduces artifacts and noise, and highlights methodological choices that impact results.

The paper identifies distinct neural mechanisms for encoding rapid facial expressions and sustained mood states using multimodal data from epilepsy patients.

This paper characterizes human prefrontal cortex excitability using noninvasive TMS and EEG, finding sigmoidal input-output curves in 57% of participants and strong correlations between TMS-evoked potentials and motor-evoked potentials.

NaviNIBS provides open-source software for neuronavigated noninvasive brain stimulation, offering tools for imaging data import, target planning, and integration with robotic systems.

This study shows that sensory entrained iTBS (se-iTBS) significantly enhances motor-evoked potentials compared to standard iTBS, with effects lasting at least 30 minutes.

This study introduces seTMS, a method that enhances motor cortex excitability by synchronizing TMS pulses with sensorimotor alpha rhythms using musical rhythms, resulting in larger motor-evoked potentials.

This paper identifies two neurophysiology-informed symptom dimensions in MDD using contrastive functional connectivity analysis of fMRI data.

The paper decodes naturalistic acute pain states using neural and facial dynamics in epilepsy patients, identifying reliable neurobehavioral markers.

This study identifies neurophysiological signatures predicting response to TMS in treatment-resistant depression using combined EEG and computational modeling.

The paper shows scalp EEG can predict intracranial brain activity in humans, with accuracy varying by region, depth, and frequency.

This study shows that TMS to the DLPFC reduces high-frequency neural activity in the sgACC, suggesting a mechanism for its antidepressant effects.

This study uses TMS-iEEG to show that dlPFC stimulation evokes activity in sgACC, providing electrophysiologic evidence of its connectivity.

This study investigates how theta-burst stimulation affects neural activity in human brain networks using intracranial EEG during direct electrical stimulation.

This paper develops a real-time closed-loop optimization method to enhance TMS-EEG measurements of prefrontal cortex excitability by reducing artifacts and increasing signal magnitude.

This study evaluates the reliability of TMS-evoked potentials in the dorsolateral prefrontal cortex across different anatomical targets and analytical parameters.

The paper uses electrophysiology and modeling to show that high-order brain regions have higher excitability due to recurrent feedback, revealing a gradient linked to cortical hierarchy.

This study investigates how TMS trains affect neural activity in the human prefrontal cortex using noninvasive measurements and finds no evidence of amplitude changes but detects non-local and phase-based neural effects.

This study shows that 10Hz brain stimulation induces predictable changes in neural oscillations, with low frequencies showing broad effects and high frequencies showing stronger magnitude changes, linked to baseline activity patterns.

This study investigates how TMS affects neural rhythms in different brain regions using intracranial recordings, finding both low-frequency increases and high-frequency decreases in response to stimulation.

The paper investigates how TMS location and angle affect early TEPs in the dlPFC and identifies optimal targets for enhancing EL-TEP responses.

This paper introduces a novel sensory suppression protocol called ATTENUATE for suprathreshold TMS to dlPFC, showing it reduces sensory EEG responses and perception more effectively than standard masking.

This study uses intracranial electrocorticography to evaluate the effects of transcranial magnetic stimulation in humans, showing localized and network-level brain responses.

This study shows that measuring neural activity during repetitive electrical stimulation can predict post-stimulation changes in brain network connectivity.