Oula Puonti

This study quantifies whole-brain E-field distributions from STN-DBS in Parkinson's patients, finding cortical peak magnitudes exceeding typical transcranial stimulation values.

This paper develops a computational framework to standardize tDCS stimulation doses across brain regions while preserving individual variability, validated in an independent sample.

The paper introduces a fast segmentation tool for brain MRI scans using a hybrid method, achieving comparable accuracy to a Bayesian approach but with significantly reduced runtime.

This study evaluates how phase lags in dual-site tACS affect electric field properties and recommends individualized montage selection to improve E-field consistency.

The paper optimizes a finite-element method for faster electric field calculations in transcranial magnetic stimulation, achieving higher update rates with reduced computational resources.

The paper introduces an EM-algorithm for banded regression to enable group-specific shrinkage in neuroscience models, demonstrating its use in fMRI and EEG analyses.

The paper introduces NextBrain, a probabilistic histological atlas of the human brain, and presents a tool for automated MRI segmentation of anatomical regions.

The paper introduces an extended head model for transcranial electric stimulation simulations, showing improved accuracy for extracephalic montages and better focality in cerebellar stimulation.

This paper introduces a semi-supervised segmentation model for identifying supragranular and infragranular layers in human cerebral cortex MRI scans with high precision.

This study evaluates how anatomical accuracy and electrode positions affect EEG forward solutions, finding that SimNIBS provides more accurate results than MNE-Python and FieldTrip.

This study evaluates how anatomical details affect electric fields in transcranial stimulation simulations using a non-human primate model.

This paper investigates how the electric field induced by tDCS in the motor cortex correlates with changes in GABA levels, finding that grey matter volume modulates this relationship.

This paper analyzes the limitations of current MRCDI reconstruction methods and proposes a statistical testing framework to improve accuracy in human brain current density imaging.

SimNIBS 2.1 provides automated tools for individualized electric field modeling in transcranial brain stimulation, demonstrating accurate electrode placement and group field extraction.