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Kallioniemi, E.

Publications and source records attributed to Kallioniemi, E..

2 recordsLinked to original sources
bioRxiv2026

PRIME: A Neurophysiology-Informed Bayesian Optimization Framework for Adaptive TMS Motor Hotspot Mapping, Algorithm Design and Monte Carlo Evaluation

BackgroundAccurate primary motor cortex (M1) hotspot identification is a prerequisite for reliable transcranial magnetic stimulation (TMS) protocols, yet conventional grid search is stimulation-intensive and operator-dependent. Existing Bayesian optimization (BO) implementations, including BOOST and 3D-BOOST, do not model within-session neurophysiological variability. MethodsWe present PROBE (Probabilistic Response-guided Optimization for Brain Exploration), a closed-loop BO framework for three-parameter TMS hotspot mapping over coil position (X, Y) and orientation ({theta}), with five innovations targeting cortical excitability drift, amplitude-dependent noise, transient artifacts, sub-threshold MEP integration (10 {micro}V floor), and cross-subject Gaussian process (GP) prior warm-starting. These were evaluated alone and in combination with amplitude-weighted center-of-gravity (CoG) convergence and estimation across 18 configurations in a Monte Carlo simulation (30 subjects, 3 repetitions each). ResultsAlgorithm configuration significantly affected all outcomes (Friedman tests, all p < 0.001, Kendalls W = 0.50-0.65). MultiFid_CoG_10uV achieved the lowest median XY error (1.14 [0.62-2.12] mm; 50.9 {+/-} 6.2 stimuli; 96.7% convergence), a 68.2% error reduction and 41.5% stimulus reduction relative to grid Search (3.58 [2.66-5.12] mm; 87 stimuli). CoG estimation significantly reduced XY error relative to peak-response selection in 10 of 11 non-CoG configurations (largest gain: MultiFid, 58.7%; adjusted p < 0.001). ConclusionsNeurophysiology-informed BO improved simulated performance under the specified model, extending the 3-DOF approach of Grano et al. (2025) with explicit noise modeling and CoG-based convergence. MultiFid_CoG_10uV and DeltaBO_CoG are selected as candidates for prospective validation in a prospective triple-blind human study.

neuroscience↗
bioRxiv2019

Transcranial photobiomodulation with infrared laser increases power of brain oscillations

Non-invasive transcranial photobiomodulation with a 1064-nm laser (tPBML1064) has been reported to improve human performance on cognitive tasks as well as locally upregulate cerebral oxygen metabolism and hemodynamics. However, it is unknown whether tPBML1064 also modulates electrophysiology, and specifically neural oscillations, in the human brain. The hypothesis guiding this study was that tPBML1064 of the right prefrontal cortex enhances neurophysiological rhythms at specific frequency bands in the human brain under resting conditions. To test this hypothesis, we recorded the 64-channel scalp electroencephalogram (EEG) before, during, and after the application of 11 minutes of 4-cm-diameter tPBML1064 to the right forehead of human subjects (n=20) using a within-subject, sham-controlled design. Time-resolved scalp topographies of EEG power at five frequency bands were computed to examine tPBML1064-induced EEG power changes across the scalp. The results showed time-dependent, significant increases of EEG spectral powers at the alpha (8-13 Hz) and beta (13-30 Hz) bands at broad scalp regions, exhibiting a front-to-back pattern. The findings provide the first sham-controlled topographic mapping that tPBML1064 increases the strength of electrophysiological oscillations (alpha and beta bands), while also shedding light on the mechanisms of tPBM in the human brain.

bioengineering↗