Biology subjects

Stenroos, M.

Publications and source records attributed to Stenroos, M..

11 recordsLinked to original sources

bioRxiv2026

Brief Trains of Closed-loop TMS Induce Controllable Power in FM-theta Oscillations

Objective. Frontal-midline theta (FM-theta; 4-8 Hz) oscillations are thought to support cognition. Brief trains of transcranial magnetic stimulation (TMS) can probe these oscillations with high temporal precision but have rarely changed theta power. One possible reason is that prior studies ignored the instantaneous phase of the oscillation, which strongly shapes the cortical response to TMS. We tested whether brief TMS trains triggered at specific FM-theta phases in real time directionally modulate post-train FM-theta power. Approach. Six healthy adults received TMS over dorsomedial prefrontal cortex (Fz) with concurrent electroencephalography during a whole-report working memory task. A beamformer and real-time phase-estimation pipeline triggered four-pulse 6 Hz trains (110% of resting motor threshold) at FM-theta peaks (0 degrees) or troughs (180 degrees), randomized trial by trial. Post-train spectral power was decomposed into total, induced (non-phase-locked) and evoked (phase-locked) components. Main results. Trough-triggered trains transiently increased post-train FM-theta power relative to peak-triggered trains; task performance did not differ. Cluster-based permutation tests showed trough-peak differences in total (4.6-7.1 Hz) and induced (5.0-7.8 Hz) power ~50-440 ms after the train, suggesting amplification of the oscillation . No evoked effect was detected. The total-power effect was robust at the subject level (Cohen's dz = 1.32, p = 0.023). Within-train theta power did not differ between conditions, suggesting a cortical origin. Significance. To our knowledge, this is the first study to lock brief rhythmic TMS trains to the real-time phase of an ongoing oscillation, and to show phase-dependent modulation of FM-theta power after individual trains on timescales relevant to behavior. Open-loop brief-train protocols may have missed such effects by mixing faciliatory and suppressive phases. Phase-locked brief trains offer a precise tool for testing the causal role of oscillations in cognition.

neuroscience↗

bioRxiv2026

Adaptive Bayesian localization of motor representation areas

Transcranial magnetic stimulation (TMS) enables non-invasive localization of cortical motor representations, with important clinical applications in presurgical planning. Existing methods either disregard spatial information about the TMS-induced electric field (E-field) or use acquisition schemes that do not leverage previously elicited motor responses to guide subsequent stimulation. We present an adaptive Bayesian localization method that combines real-time E-field optimization with per-trial probabilistic inference. The cortical origin of the motor responses is represented as a spatial probability distribution that is updated after each stimulus. Subsequent stimuli are then optimized to maximize the expected localization improvement given previous responses. We validated the method experimentally, using multi-locus TMS for adaptive localization and single-coil TMS as a non-adaptive reference with randomized coil placements. Across eight subjects, the adaptive protocol at least halved the number of stimuli required for stable localization compared to the randomized protocol, converging in 60 stimuli on average, with 95% highest-density regions often below 10 mm2 by 150 stimuli.

neuroscience↗

bioRxiv2024

Volume conductor models for magnetospinography

The recent development of small, wearable, magnetic field sensors allow for the investigation of biomagnetic fields with a flexibility previously unavailable. We carry out forward computations to describe how current flow in the spinal cord and thorax gives rise to measurable magnetic fields outside the torso. We compare various open-access volume conductor models, in order to select the most parsimonious and accurate descriptor of the magnetic fields due to source current in the spinal cord. We find that fields produced due to current flow along the superior-inferior axis of the cord are relatively insensitive to the choice of volume conductor model. However, fields produced by current flow in predominantly left-right or anterior-posterior direction are significantly attenuated by the presence of bone in the forward model. Furthermore, volume conductors with bone demonstrate larger differences in field topographies for nearby sources compared to bone-free models. These findings suggest that precise modelling of spinal cord location and surrounding vertebrae will be important a-priori knowledge going forward.

neuroscience↗

bioRxiv2021

Multi-locus transcranial magnetic stimulation system for electronically targeted brain stimulation

BackgroundTranscranial magnetic stimulation (TMS) allows non-invasive stimulation of the cortex. In multi-locus TMS (mTMS), the stimulating electric field (E-field) is controlled electronically without coil movement by adjusting currents in the coils of a transducer. ObjectiveTo develop an mTMS system that allows adjusting the location and orientation of the E-field maximum within a cortical region. MethodsWe designed and manufactured a planar 5-coil mTMS transducer to allow controlling the maximum of the induced E-field within a cortical region approximately 30 mm in diameter. We developed electronics with a design consisting of independently controlled H-bridge circuits to drive up to six TMS coils. To control the hardware, we programmed software that runs on a field-programmable gate array and a computer. To induce the desired E-field in the cortex, we developed an optimization method to calculate the currents needed in the coils. We characterized the mTMS system and conducted a proof-of-concept motor-mapping experiment on a healthy volunteer. In the motor mapping, we kept the transducer placement fixed while electronically shifting the E-field maximum on the precentral gyrus and measuring electromyography from the contralateral hand. ResultsThe transducer consists of an oval coil, two figure-of-eight coils, and two four-leaf-clover coils stacked on top of each other. The technical characterization indicated that the mTMS system performs as designed. The measured motor evoked potential amplitudes varied consistently as a function of the location of the E-field maximum. ConclusionThe developed mTMS system enables electronically targeted brain stimulation within a cortical region.

neuroscience↗

bioRxiv2021

Closed-loop optimization of transcranial magnetic stimulation with electroencephalography feedback

BackgroundTranscranial magnetic stimulation (TMS) is widely used in brain research and treatment of various brain dysfunctions. However, the optimal way to target stimulation and administer TMS therapies, for example, where and in which electric field direction the stimuli should be given, is yet to be determined. ObjectiveTo develop an automated closed-loop system for adjusting TMS parameters (in this work, the stimulus orientation) online based on TMS-evoked brain activity measured with electroencephalography (EEG). MethodsWe developed an automated closed-loop TMS-EEG set-up. In this set-up, the stimulus parameters are electronically adjusted with multi-locus TMS. As a proof of concept, we developed an algorithm that automatically optimizes the stimulation orientation based on single-trial EEG responses. We applied the algorithm to determine the electric field orientation that maximizes the amplitude of the TMS- EEG responses. The validation of the algorithm was performed with six healthy volunteers, repeating the search twenty times for each subject. ResultsThe validation demonstrated that the closed-loop control worked as desired despite the large variation in the single-trial EEG responses. We were often able to get close to the orientation that maximizes the EEG amplitude with only a few tens of pulses. ConclusionOptimizing stimulation with EEG feedback in a closed-loop manner is feasible and enables effective coupling to brain activity.

bioengineering↗

bioRxiv2019

Individual head models for estimating the TMS-induced electric field in rat brain

In transcranial magnetic stimulation (TMS), the initial cortical activation due to stimulation is determined by the state of the brain and the magnitude, waveform, and direction of the induced electric field (E-field) in the cortex. The E-field distribution depends on the conductivity geometry of the head. The effects of deviations from a spherically symmetric conductivity profile have been studied in detail in humans. In small mammals, such as rats, these effects are more pronounced due to their smaller and less spherical heads. In this study, we describe a simple method for building individual realistically shaped head models for rats from high-resolution X-ray tomography images. We computed the TMS-induced E-field with the boundary element method and assessed the effect of head-model simplifications on the estimated E-field. The deviations from spherical symmetry have large, non-trivial effects on the E-field distribution: in some cases, even the direction of the E-field in the cortex cannot be reliably predicted by the coil orientation unless these deviations are properly considered.

neuroscience↗

bioRxiv2019

Comparison of beamformer implementations for MEG source localization

Beamformers are applied for estimating spatiotemporal characteristics of neuronal sources underlying measured MEG/EEG signals. Several MEG analysis toolboxes include an implementation of a linearly constrained minimum-variance (LCMV) beamformer. However, differences in implementations and in their results complicate the selection and application of beamformers and may hinder their wider adoption in research and clinical use. Additionally, combinations of different MEG sensor types (such as magnetometers and planar gradiometers) and application of preprocessing methods for interference suppression, such as signal space separation (SSS), can affect the results in different ways for different implementations. So far, a systematic evaluation of the different implementations has not been performed. Here, we compared the localization performance of the LCMV beamformer pipelines in four widely used open-source toolboxes (FieldTrip, SPM12, Brainstorm, and MNE-Python) using datasets both with and without SSS interference suppression.\n\nWe analyzed MEG data that were i) simulated, ii) recorded from a static and moving phantom, and iii) recorded from a healthy volunteer receiving auditory, visual, and somatosensory stimulation. We also investigated the effects of SSS and the combination of the magnetometer and gradiometer signals. We quantified how localization error and point-spread volume vary with SNR in all four toolboxes.\n\nWhen applied carefully to MEG data with a typical SNR (3-15 dB), all four toolboxes localized the sources reliably; however, they differed in their sensitivity to preprocessing parameters. As expected, localizations were highly unreliable at very low SNR, but we found high localization error also at very high SNRs. We also found that the SNR improvement offered by SSS led to more accurate localization.

neuroscience↗

bioRxiv2019

Towards an Objective Evaluation of EEG/MEG Source Estimation Methods: The Linear Tool Kit

The question \"What is the spatial resolution of EEG/MEG?\" can only be answered with many ifs and buts, as the answer depends on a large number of parameters. Here, we describe a framework for resolution analysis of EEG/MEG source estimation, focusing on linear methods. The spatial resolution of linear methods can be evaluated using the resolution matrix, which contains the point-spread and cross-talk functions (PSFs and CTFs), respectively. Both of them have to be taken into account for a full characterization of spatial resolution. They can be used to compute a range of quantitative resolution metrics, which should cover at the last three aspects of those functions: localization accuracy, spatial extent, and relative amplitude. Here, we first provide a tutorial-style introduction to resolution analysis of linear source estimation methods. We then apply these concepts to evaluate the benefit of combining EEG and MEG measurements, and to compare weighted and normalized L2-minimum-norm estimation and spatial filters. We confirm and extend previous results, showing that adding EEG to MEG improves spatial resolution, and that different methods offer different compromises among different resolution criteria. We hope that our approach will help EEG/MEG researchers in the interpretation of source estimation results, the design of new experiments, and the development of new MEG systems.

neuroscience↗

bioRxiv2019

Real-time computation of the TMS-induced electric field in a realistic head model

BackgroundTranscranial magnetic stimulation (TMS) is often targeted using a model of TMS-induced electric field (E). In such navigated TMS, the E-field models have been based on spherical approximation of the head. Such models omit the effects of cerebrospinal fluid (CSF) on the E-field, leading to potentially large errors in the computed field. So far, realistic models have been too slow for interactive TMS navigation. ObjectiveWe present computational methods that enable real-time solving of the E-field in a realistic head model that contains the CSF. MethodsUsing reciprocity and Geselowitz integral equation, we separate the computations to coil-dependent and -independent parts. For the coil-dependent part of Geselowitz integrals, we present a fast numerical quadrature. Further, we present a moment-matching approach for optimizing dipole-based coil models. We verify the new methods using simulations in a realistic head model that contains the brain, CSF, skull, and scalp. ResultsThe new quadrature introduces a relative error of 1.1%. The total error of the quadrature and coil model was 1.43% and 1.15% for coils with 38 and 76 dipoles, respectively. The difference between our head model and a simpler realistic model that omits the CSF was 29%. Using a standard PC and a 38-dipole coil, our solver computed the E-field in 84 coil positions per second in 20000 points on the cortex. ConclusionThe presented methods enable real-time solving of the TMS-induced E-field in a realistic head model that contains the CSF. The new methodology allows more accurate targeting and precise adjustment of intensity during experimental or clinical TMS mapping.

neuroscience↗

bioRxiv2017

Locating highly correlated sources from MEG with (recursive) (R)DS-MUSIC

We introduce a source localization method of the MUltiple Signal Classification (MUSIC) family that can locate brain-signal sources robustly and reliably, irrespective of their temporal correlations. The method, double-scanning (DS) MUSIC, is based on projecting out the topographies of source candidates during topographical scanning in a way that breaks the mutual dependence of highly correlated sources, but keeps the uncorrelated sources intact. We also provide a recursive version of DS-MUSIC (RDS-MUSIC), which overcomes the peak detection problem present in the non-recursive methods. We compare DS-MUSIC and RDS-MUSIC with other localization techniques in numerous simulations with varying source configurations, correlations, and signal-to-noise ratios. DS- and RDS-MUSIC were the most robust localization methods; they had a high success rate and localization accuracy for both uncorrelated and highly correlated sources. In addition, we validated RDS-MUSIC by showing that it successfully locates bilateral synchronous activity from measured auditory-evoked MEG.

neuroscience↗

bioRxiv2017

Requirements for coregistration accuracy in on-scalp MEG

Recent advances in magnetic sensing has made on-scalp magnetoencephalography (MEG) possible. In particular, optically-pumped magnetometers (OPMs) have reached sensitivity levels that enable their use in MEG. In contrast to the SQUID sensors used in current MEG systems, OPMs do not require cryogenic cooling and can thus be placed within millimetres from the head, enabling the construction of sensor arrays that conform to the shape of an individuals head. To properly estimate the location of neural sources within the brain, one must accurately know the position and orientation of sensors in relation to the head. With the adaptable on-scalp MEG sensor arrays, this coregistration becomes more challenging than in current SQUID-based MEG systems that use rigid sensor arrays.\n\nHere, we used simulations to quantify how accurately one needs to know the position and orientation of sensors in an on-scalp MEG system. The effects that different types of localisation errors have on forward modelling and source estimates obtained by minimum-norm estimation, dipole fitting, and beamforming are detailed.\n\nWe found that sensor position errors generally have a larger effect than orientation errors and that these errors affect the localisation accuracy of superficial sources the most. To obtain similar or higher accuracy than with current SQUID-based MEG systems, RMS sensor position and orientation errors should be < 4 mm and < 10{degrees}, respectively.

neuroscience↗