Publications by authors named "Risto J Ilmoniemi"

119 Publications

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

Brain Stimul 2021 Nov 21. Epub 2021 Nov 21.

Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.

Background: Transcranial 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.

Objective: To develop an mTMS system that allows adjusting the location and orientation of the E-field maximum within a cortical region.

Methods: We 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.

Results: The 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.

Conclusion: The developed mTMS system enables electronically targeted brain stimulation within a cortical region.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.brs.2021.11.014DOI Listing
November 2021

Trade-off between stimulation focality and the number of coils in multi-locus transcranial magnetic stimulation.

J Neural Eng 2021 Nov 12;18(6). Epub 2021 Nov 12.

Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.

. Coils designed for transcranial magnetic stimulation (TMS) must incorporate trade-offs between the required electrical power or energy, focality and depth penetration of the induced electric field (E-field), coil size, and mechanical properties of the coil, as all of them cannot be optimally met at the same time. In multi-locus TMS (mTMS), a transducer consisting of several coils allows electronically targeted stimulation of the cortex without physically moving a coil. In this study, we aimed to investigate the relationship between the number of coils in an mTMS transducer, the focality of the induced E-field, and the extent of the cortical region within which the location and orientation of the maximum of the induced E-field can be controlled.We applied convex optimization to design planar and spherically curved mTMS transducers of different E-field focalities and analyzed their properties. We characterized the trade-off between the focality of the induced E-field and the extent of the cortical region that can be stimulated with an mTMS transducer with a given number of coils.At the expense of the E-field focality, one can, with the same number of coils, design an mTMS transducer that can control the location and orientation of the peak of the induced E-field within a wider cortical region.. With E-fields of moderate focality, the problem of electronically targeted TMS becomes considerably easier compared with highly focal E-fields; this may speed up the development of mTMS and the emergence of new clinical and research applications.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1088/1741-2552/ac3207DOI Listing
November 2021

Effect of stimulus orientation and intensity on short-interval intracortical inhibition (SICI) and facilitation (SICF): A multi-channel transcranial magnetic stimulation study.

PLoS One 2021 22;16(9):e0257554. Epub 2021 Sep 22.

Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.

Besides stimulus intensities and interstimulus intervals (ISI), the electric field (E-field) orientation is known to affect both short-interval intracortical inhibition (SICI) and facilitation (SICF) in paired-pulse transcranial magnetic stimulation (TMS). However, it has yet to be established how distinct orientations of the conditioning (CS) and test stimuli (TS) affect the SICI and SICF generation. With the use of a multi-channel TMS transducer that provides electronic control of the stimulus orientation and intensity, we aimed to investigate how changes in the CS and TS orientation affect the strength of SICI and SICF. We hypothesized that the CS orientation would play a major role for SICF than for SICI, whereas the CS intensity would be more critical for SICI than for SICF. In eight healthy subjects, we tested two ISIs (1.5 and 2.7 ms), two CS and TS orientations (anteromedial (AM) and posteromedial (PM)), and four CS intensities (50, 70, 90, and 110% of the resting motor threshold (RMT)). The TS intensity was fixed at 110% RMT. The intensities were adjusted to the corresponding RMT in the AM and PM orientations. SICI and SICF were observed in all tested CS and TS orientations. SICI depended on the CS intensity in a U-shaped manner in any combination of the CS and TS orientations. With 70% and 90% RMT CS intensities, stronger PM-oriented CS induced stronger inhibition than weaker AM-oriented CS. Similar SICF was observed for any CS orientation. Neither SICI nor SICF depended on the TS orientation. We demonstrated that SICI and SICF could be elicited by the CS perpendicular to the TS, which indicates that these stimuli affected either overlapping or strongly connected neuronal populations. We concluded that SICI is primarily sensitive to the CS intensity and that CS intensity adjustment resulted in similar SICF for different CS orientations.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0257554PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8457500PMC
November 2021

The impact of artifact removal approaches on TMS-EEG signal.

Neuroimage 2021 10 16;239:118272. Epub 2021 Jun 16.

Neurophysiology lab, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Via Pilastroni 4, 25125 Brescia, Italy. Electronic address:

Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs) allow one to assess cortical excitability and effective connectivity in clinical and basic research. However, obtaining clean TEPs is challenging due to the various TMS-related artifacts that contaminate the electroencephalographic (EEG) signal when the TMS pulse is delivered. Different preprocessing approaches have been employed to remove the artifacts, but the degree of artifact reduction or signal distortion introduced in this phase of analysis is still unknown. Knowing and controlling this potential source of uncertainty will increase the inter-rater reliability of TEPs and improve the comparability between TMS-EEG studies. The goal of this study was to assess the variability in TEP waveforms due to of the use of different preprocessing pipelines. To accomplish this aim, we preprocessed the same TMS-EEG data with four different pipelines and compared the results. The dataset was obtained from 16 subjects in two identical recording sessions, each session consisting of both left dorsolateral prefrontal cortex and left inferior parietal lobule stimulation at 100% of the resting motor threshold. Considerable differences in TEP amplitudes and global mean field power (GMFP) were found between the preprocessing pipelines. Topographies of TEPs from the different pipelines were all highly correlated (ρ>0.8) at latencies over 100 ms. By contrast, waveforms at latencies under 100 ms showed a variable level of correlation, with ρ ranging between 0.2 and 0.9. Moreover, the test-retest reliability of TEPs depended on the preprocessing pipeline. Taken together, these results take us to suggest that the choice of the preprocessing approach has a marked impact on the final TEP, and that further studies are needed to understand advantages and disadvantages of the different approaches.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuroimage.2021.118272DOI Listing
October 2021

Superconducting receiver arrays for magnetic resonance imaging.

Biomed Phys Eng Express 2020 01 13;6(1):015016. Epub 2020 Jan 13.

Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, FI-00076 AALTO, Finland.

Superconducting QUantum-Interference Devices (SQUIDs) make magnetic resonance imaging (MRI) possible in ultra-low microtesla-range magnetic fields. In this work, we investigate the design parameters affecting the signal and noise performance of SQUID-based sensors and multichannel magnetometers for MRI of the brain. Besides sensor intrinsics, various noise sources along with the size, geometry and number of superconducting detector coils are important factors affecting the image quality. We derive figures of merit based on optimal combination of multichannel data, analyze different sensor array designs, and provide tools for understanding the signal detection and the different noise mechanisms. The work forms a guide to making design decisions for both imaging- and sensor-oriented readers.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1088/2057-1976/ab5c61DOI Listing
January 2020

Signal-Space Projection Suppresses the tACS Artifact in EEG Recordings.

Front Hum Neurosci 2020 18;14:536070. Epub 2020 Dec 18.

Experimental Psychology Lab, Cluster of Excellence "Hearing4all", European Medical School, University of Oldenburg, Oldenburg, Germany.

Background: To probe the functional role of brain oscillations, transcranial alternating current stimulation (tACS) has proven to be a useful neuroscientific tool. Because of the excessive tACS-caused artifact at the stimulation frequency in electroencephalography (EEG) signals, tACS + EEG studies have been mostly limited to compare brain activity between recordings before and after concurrent tACS. Critically, attempts to suppress the artifact in the data cannot assure that the entire artifact is removed while brain activity is preserved. The current study aims to evaluate the feasibility of specific artifact correction techniques to clean tACS-contaminated EEG data.

New Method: In the first experiment, we used a phantom head to have full control over the signal to be analyzed. Driving pre-recorded human brain-oscillation signals through a dipolar current source within the phantom, we simultaneously applied tACS and compared the performance of different artifact-correction techniques: sine subtraction, template subtraction, and signal-space projection (SSP). In the second experiment, we combined tACS and EEG on one human subject to demonstrate the best-performing data-correction approach in a proof of principle.

Results: The tACS artifact was highly attenuated by SSP in the phantom and the human EEG; thus, we were able to recover the amplitude and phase of the oscillatory activity. In the human experiment, event-related desynchronization could be restored after correcting the artifact.

Comparison With Existing Methods: The best results were achieved with SSP, which outperformed sine subtraction and template subtraction.

Conclusion: Our results demonstrate the feasibility of SSP by applying it to a phantom measurement with pre-recorded signal and one human tACS + EEG dataset. For a full validation of SSP, more data are needed.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fnhum.2020.536070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775555PMC
December 2020

Safety and recommendations for TMS use in healthy subjects and patient populations, with updates on training, ethical and regulatory issues: Expert Guidelines.

Clin Neurophysiol 2021 01 24;132(1):269-306. Epub 2020 Oct 24.

Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, USA.

This article is based on a consensus conference, promoted and supported by the International Federation of Clinical Neurophysiology (IFCN), which took place in Siena (Italy) in October 2018. The meeting intended to update the ten-year-old safety guidelines for the application of transcranial magnetic stimulation (TMS) in research and clinical settings (Rossi et al., 2009). Therefore, only emerging and new issues are covered in detail, leaving still valid the 2009 recommendations regarding the description of conventional or patterned TMS protocols, the screening of subjects/patients, the need of neurophysiological monitoring for new protocols, the utilization of reference thresholds of stimulation, the managing of seizures and the list of minor side effects. New issues discussed in detail from the meeting up to April 2020 are safety issues of recently developed stimulation devices and pulse configurations; duties and responsibility of device makers; novel scenarios of TMS applications such as in the neuroimaging context or imaging-guided and robot-guided TMS; TMS interleaved with transcranial electrical stimulation; safety during paired associative stimulation interventions; and risks of using TMS to induce therapeutic seizures (magnetic seizure therapy). An update on the possible induction of seizures, theoretically the most serious risk of TMS, is provided. It has become apparent that such a risk is low, even in patients taking drugs acting on the central nervous system, at least with the use of traditional stimulation parameters and focal coils for which large data sets are available. Finally, new operational guidelines are provided for safety in planning future trials based on traditional and patterned TMS protocols, as well as a summary of the minimal training requirements for operators, and a note on ethics of neuroenhancement.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.clinph.2020.10.003DOI Listing
January 2021

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

Sci Rep 2020 10 15;10(1):17397. Epub 2020 Oct 15.

Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.

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 less spherical head, proportionally much thicker neck region, and overall much smaller size compared to the TMS coils. 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: for some coil orientations, the strongest stimulation is in the brainstem even when the coil is over the motor cortex. With modelling prior to an experiment, such problematic coil orientations can be avoided for more accurate targeting.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41598-020-74431-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7567095PMC
October 2020

Spatial extent of cortical motor hotspot in navigated transcranial magnetic stimulation.

J Neurosci Methods 2020 12 10;346:108893. Epub 2020 Aug 10.

Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland; Department of Applied Physics, University of Eastern Finland, Kuopio, Finland. Electronic address:

Background: Motor mapping with navigated transcranial magnetic stimulation (nTMS) requires defining a "hotspot", a stimulation site consistently producing the highest-amplitude motor-evoked potentials (MEPs). The exact location of the hotspot is difficult to determine, and the spatial extent of high-amplitude MEPs usually remains undefined due to MEP variability and the spread of the TMS-induced electric field (E-field). Therefore, here we aim to define the hotspot as a sub-region of a motor map.

New Method: We analyzed MEP amplitude distributions in motor mappings of 30 healthy subjects in two orthogonal directions on the motor cortex. Based on the widths of these distributions, the hotspot extent was estimated as an elliptic area. In addition, E-field distributions induced by motor map edge stimulations were simulated for ten subjects, and the E-field attenuation was analyzed to obtain another estimate for hotspot extent.

Results: The median MEP-based hotspot area was 13 mm (95% confidence interval (CI) = [10, 18] mm). The mean E-field-based hotspot area was 26 mm (95% CI = [13, 38] mm).

Comparison With Existing Methods: In contrast to the conventional hotspot, the new definition considers its spatial extent, indicating the most easily excited area where subsequent nTMS stimuli should be targeted for maximal response. The E-field-based hotspot provides an estimate for the extent of cortical structures where the E-field is close to its maximum.

Conclusions: The nTMS hotspot should be considered as an area rather than a single qualitatively defined spot due to MEP variability and E-field spread.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jneumeth.2020.108893DOI Listing
December 2020

Source-based artifact-rejection techniques available in TESA, an open-source TMS-EEG toolbox.

Brain Stimul 2020 Sep - Oct;13(5):1349-1351. Epub 2020 Jul 10.

The Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash Biomedical Imaging, Monash University, Victoria, 3168, Australia; Hopwood Centre for Neurobiology, Lifelong Health Theme, South Australian Health and Medical Research Institute (SAHMRI), P.O. Box 11060, Adelaide, 5001, Australia; Discipline of Psychiatry, Adelaide Medical School, University of Adelaide, Adelaide Health and Medical Sciences Building, Corner of North Terrace & George Street, Adelaide, 5000, Australia.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.brs.2020.06.079DOI Listing
July 2020

Automated search of stimulation targets with closed-loop transcranial magnetic stimulation.

Neuroimage 2020 10 25;220:117082. Epub 2020 Jun 25.

Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.

Transcranial magnetic stimulation (TMS) protocols often include a manual search of an optimal location and orientation of the coil or peak stimulating electric field to elicit motor responses in a target muscle. This target search is laborious, and the result is user-dependent. Here, we present a closed-loop search method that utilizes automatic electronic adjustment of the stimulation based on the previous responses. The electronic adjustment is achieved by multi-locus TMS, and the adaptive guiding of the stimulation is based on the principles of Bayesian optimization to minimize the number of stimuli (and time) needed in the search. We compared our target-search method with other methods, such as systematic sampling in a predefined cortical grid. Validation experiments on five healthy volunteers and further offline simulations showed that our adaptively guided search method needs only a relatively small number of stimuli to provide outcomes with good accuracy and precision. The automated method enables fast and user-independent optimization of stimulation parameters in research and clinical applications of TMS.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuroimage.2020.117082DOI Listing
October 2020

Safety of rTMS in patients with intracranial metallic objects.

Brain Stimul 2020 May - Jun;13(3):928-929. Epub 2019 Dec 28.

Neuromodulation Program, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA. Electronic address:

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.brs.2019.12.010DOI Listing
December 2019

Transcranial magnetic stimulation-evoked potentials after the stimulation of the right-hemispheric homologue of Broca's area.

Neuroreport 2019 11;30(16):1110-1114

Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo.

The combination of transcranial magnetic stimulation and electroencephalography can be applied to probe effective connectivity. Neurons are excited by magnetic pulses, which produce transcranial magnetic stimulation-evoked potentials that can be monitored with electroencephalography. Effective connectivity refers to causal connections in the brain; it describes how different brain areas communicate with each other. Broca's area is crucial for all phases of speech processing and is located in the frontotemporal region of the cortex. Only a few studies have investigated this region using transcranial magnetic stimulation-electroencephalography because of the large cranial muscles that are located over these areas, resulting in large artifacts covering the transcranial magnetic stimulation-evoked potentials. However, it is shown that this obstacle can be overcome with new artifact-removal tools. We used minimum-norm estimation to locate the sources of the neuronal signals in electroencephalography data after stimulating the right-hemispheric homologue of Broca's area in three right-handed subjects; it was shown that the spreading of brain activity might be different for different individuals and that the brain activity spread fast to the contralateral hemisphere.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/WNR.0000000000001337DOI Listing
November 2019

Short-interval intracortical inhibition in human primary motor cortex: A multi-locus transcranial magnetic stimulation study.

Neuroimage 2019 12 13;203:116194. Epub 2019 Sep 13.

Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.

Short-interval intracortical inhibition (SICI) has been studied with paired-pulse transcranial magnetic stimulation (TMS) by administering two pulses at a millisecond-scale interstimulus interval (ISI) to a single cortical target. It has, however, been difficult to study the interaction of nearby cortical targets with paired-pulse TMS. To overcome this limitation, we have developed a multi-locus TMS (mTMS) device, which allows controlling the stimulus location electronically. Here, we applied mTMS to study SICI in primary motor cortex with paired pulses targeted to adjacent locations, aiming to quantify the extent of the cortical region producing SICI in the location of a test stimulus. We varied the location and timing of the conditioning stimulus with respect to a test stimulus targeted to the cortical hotspot of the abductor pollicis brevis (APB) in order to study their effects on motor evoked potentials. We further applied a two-coil protocol with the conditioning stimulus given by an oval coil only to the surroundings of the APB hotspot, to which a subsequent test stimulus was administered with a figure-of-eight coil. The strongest SICI occurred at ISIs below 1 ms and at ISIs around 2.5 ms. These ISIs increased when the conditioning stimulus receded from the APB hotspot. Our two-coil paired-pulse TMS study suggests that SICI at ISIs of 0.5 and 2.5 ms originate from different mechanisms or neuronal elements.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuroimage.2019.116194DOI Listing
December 2019

EEG Artifact Removal in TMS Studies of Cortical Speech Areas.

Brain Topogr 2020 01 9;33(1):1-9. Epub 2019 Jul 9.

Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, P.O. Box 12200, 00076 AALTO, Espoo, Finland.

The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) is commonly applied for studying the effective connectivity of neuronal circuits. The stimulation excites neurons, and the resulting TMS-evoked potentials (TEPs) are recorded with EEG. A serious obstacle in this method is the generation of large muscle artifacts from scalp muscles, especially when frontolateral and temporoparietal, such as speech, areas are stimulated. Here, TMS-EEG data were processed with the signal-space projection and source-informed reconstruction (SSP-SIR) artifact-removal methods to suppress these artifacts. SSP-SIR suppressed muscle artifacts according to the difference in frequency contents of neuronal signals and muscle activity. The effectiveness of SSP-SIR in rejecting muscle artifacts and the degree of excessive attenuation of brain EEG signals were investigated by comparing the processed versions of the recorded TMS-EEG data with simulated data. The calculated individual lead-field matrix describing how the brain signals spread on the cortex were used as simulated data. We conclude that SSP-SIR was effective in suppressing artifacts also when frontolateral and temporoparietal cortical sites were stimulated, but it may have suppressed also the brain signals near the stimulation site. Effective connectivity originating from the speech-related areas may be studied even when speech areas are stimulated at least on the contralateral hemisphere where the signals were not suppressed that much.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s10548-019-00724-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6943412PMC
January 2020

["ConnectToBrain" : Synergy project for therapeutic closed-loop stimulation of brain network disorders].

Nervenarzt 2019 Aug;90(8):804-808

Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, P.O. Box 12200, FI-00076, AALTO, Finnland.

Therapeutic non-invasive transcranial brain stimulation with previous treatment protocols showed at best moderate effect sizes and large interindividual variability with a substantial proportion of non-responders. A currently intensively discussed approach to address these problems is individualized closed-loop stimulation. ConnectToBrain is a synergy project funded by the European Research Council to develop noninvasive closed-loop therapeutic stimulation of network disorders of the human brain.It consists of three main pillars: (1) development of a multichannel transcranial magnetic stimulation (mTMS) coil array that covers nearly all of the cerebral cortex and enables highly precise electronic control of location, direction, intensity and timing of the induced electrical fields, (2) development of real-time analysis of activity and connectivity in brain networks using electroencephalography (EEG) for instantaneous spatial and temporal control of stimulation (brain state-dependent, closed-loop stimulation) and adaptive optimization of treatment effects by machine learning and (3) translation of these neurotechnological innovations into physiological and clinical studies.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00115-019-0747-xDOI Listing
August 2019

Predicting Alzheimer's disease severity by means of TMS-EEG coregistration.

Neurobiol Aging 2019 08 13;80:38-45. Epub 2019 Apr 13.

Cognitive Neuroscience Section, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.

Clinical manifestations of Alzheimer's disease (AD) are associated with a breakdown in large-scale communication, such that AD may be considered as a "disconnection syndrome." An established method to test effective connectivity is the combination of transcranial magnetic stimulation with electroencephalography (TMS-EEG) because the TMS-induced cortical response propagates to distant anatomically connected regions. To investigate whether prefrontal connectivity alterations may predict disease severity, we explored the relationship of dorsolateral prefrontal cortex connectivity (derived from TMS-EEG) with cognitive decline (measured with Mini Mental State Examination and a face-name association memory task) in 26 patients with AD. The amplitude of TMS-EEG evoked component P30, which was found to be generated in the right superior parietal cortex, predicted Mini Mental State Examination and face-name memory scores: higher P30 amplitudes predicted poorer cognitive and memory performances. The present results indicate that advancing disease severity might be associated with effective connectivity increase involving long-distance frontoparietal connections, which might represent a maladaptive pathogenic mechanism reflecting a damaged excitatory-inhibitory balance between anterior and posterior regions.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neurobiolaging.2019.04.008DOI Listing
August 2019

The impact of improved MEG-MRI co-registration on MEG connectivity analysis.

Neuroimage 2019 08 25;197:354-367. Epub 2019 Apr 25.

Department of Neuroscience, Imaging and Clinical Sciences, G. d'Annunzio University of Chieti-Pescara, via dei Vestini 31, 66100 Chieti, Italy; Institute for Advanced Biomedical Technologies, G. d'Annunzio University of Chieti-Pescara, via dei Vestini 31, 66100 Chieti, Italy.

Co-registration between structural head images and functional MEG data is needed for anatomically-informed MEG data analysis. Despite the efforts to minimize the co-registration error, conventional landmark- and surface-based strategies for co-registering head and MEG device coordinates achieve an accuracy of typically 5-10 mm. Recent advances in instrumentation and technical solutions, such as the development of hybrid ultra-low-field (ULF) MRI-MEG devices or the use of 3D-printed individualized foam head-casts, promise unprecedented co-registration accuracy, i.e., 2 mm or better. In the present study, we assess through simulations the impact of such an improved co-registration on MEG connectivity analysis. We generated synthetic MEG recordings for pairs of connected cortical sources with variable locations. We then assessed the capability to reconstruct source-level connectivity from these recordings for 0-15-mm co-registration error, three levels of head modeling detail (one-, three- and four-compartment models), two source estimation techniques (linearly constrained minimum-variance beamforming and minimum-norm estimation MNE) and five separate connectivity metrics (imaginary coherency, phase-locking value, amplitude-envelope correlation, phase-slope index and frequency-domain Granger causality). We found that beamforming can better take advantage of an accurate co-registration than MNE. Specifically, when the co-registration error was smaller than 3 mm, the relative error in connectivity estimates was down to one-third of that observed with typical co-registration errors. MNE provided stable results for a wide range of co-registration errors, while the performance of beamforming rapidly degraded as the co-registration error increased. Furthermore, we found that even moderate co-registration errors (>6 mm, on average) essentially decrease the difference of four- and three- or one-compartment models. Hence, a precise co-registration is important if one wants to take full advantage of highly accurate head models for connectivity analysis. We conclude that an improved co-registration will be beneficial for reliable connectivity analysis and effective use of highly accurate head models in future MEG connectivity studies.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuroimage.2019.04.061DOI Listing
August 2019

The effect of experimental pain on short-interval intracortical inhibition with multi-locus transcranial magnetic stimulation.

Exp Brain Res 2019 Jun 27;237(6):1503-1510. Epub 2019 Mar 27.

Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, AALTO, P.O. Box 12200, 00076, Espoo, Finland.

Chronic neuropathic pain is known to alter the primary motor cortex (M1) function. Less is known about the normal, physiological effects of experimental neurogenic pain on M1. The objective of this study is to determine how short-interval intracortical inhibition (SICI) is altered in the M1 representation area of a muscle exposed to experimental pain compared to SICI of another muscle not exposed to pain. The cortical representation areas of the right abductor pollicis brevis (APB) and biceps brachii (BB) muscles of 11 subjects were stimulated with a multi-locus transcranial magnetic stimulation device while the resulting motor-evoked potentials (MEPs) were recorded with electromyography. Single- and paired-pulse TMS was administered in seven conditions, including one with the right hand placed in cold water. The stimulation intensity for the conditioning pulses in the paired-pulse examination was 80% of the resting motor threshold (RMT) of the stimulated site and 120% of RMT for both the test and single pulses. The paired-pulse MEP amplitudes were normalized with the mean amplitude of the single-pulse MEPs of the same condition and muscle. SICI was compared between conditions. After the cold pain, the normalized paired-pulse MEP amplitudes decreased in APB, but not in BB, indicating that SICI was potentially increased only in the cortical area of the muscle subjected to pain. These data suggest that SICI is increased in the M1 representation area of a hand muscle shortly after exposure to pain has ended, which implies that short-lasting pain can alter the inhibitory balance in M1.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00221-019-05502-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525662PMC
June 2019

Automatic Spatial Calibration of Ultra-Low-Field MRI for High-Accuracy Hybrid MEG-MRI.

IEEE Trans Med Imaging 2019 06 20;38(6):1317-1327. Epub 2019 Mar 20.

With a hybrid magnetoencephalography (MEG)-MRI device that uses the same sensors for both modalities, the co-registration of MRI and MEG data can be replaced by an automatic calibration step. Based on the highly accurate signal model of ultra-low-field (ULF) MRI, we introduce a calibration method that eliminates the error sources of traditional co-registration. The signal model includes complex sensitivity profiles of the superconducting pickup coils. In the ULF MRI, the profiles are independent of the sample and therefore well-defined. In the most basic form, the spatial information of the profiles, captured in parallel ULF-MR acquisitions, is used to find the exact coordinate transformation required. We assessed our calibration method by simulations assuming a helmet-shaped pickup-coil-array geometry. Using a carefully constructed objective function and sufficient approximations, even with low-SNR images, sub-voxel and sub-millimeter calibration accuracy were achieved. After the calibration, distortion-free MRI and high spatial accuracy for MEG source localization can be achieved. For an accurate sensor-array geometry, the co-registration and associated errors are eliminated, and the positional error can be reduced to a negligible level.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1109/TMI.2019.2905934DOI Listing
June 2019

Combining rTMS With Intensive Language-Action Therapy in Chronic Aphasia: A Randomized Controlled Trial.

Front Neurosci 2018 4;12:1036. Epub 2019 Feb 4.

Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.

Neuromodulation technologies, such as transcranial magnetic stimulation (TMS), are promising tools for neurorehabilitation, aphasia therapy included, but not yet in common clinical use. Combined with behavioral techniques, in particular treatment-efficient (ILAT, previously CIAT or CILT), TMS could substantially amplify the beneficial effect of such behavioral therapy alone (Thiel et al., 2013; Martin et al., 2014; Mendoza et al., 2016; Kapoor, 2017). In this randomized study of 17 subjects with post-stroke aphasia in the chronic stage, we studied the combined effect of ILAT and 1-Hz placebo-controlled navigated repetitive TMS (rTMS) to the right-hemispheric inferior frontal cortex-that is, to the anterior part of the non-dominant hemisphere's homolog Broca's area (pars triangularis). Patients were randomized to groups A and B. Patients in group A received a 2-week period of rTMS during naming training where they named pictures displayed on the screen once every 10 s, followed by 2 weeks of rTMS and naming combined with ILAT. Patients in group B received the same behavioral therapy but TMS was replaced by sham stimulation. The primary outcome measures for changes in language performance were the Western Aphasia Battery's aphasia quotient AQ; the secondary outcome measures were the Boston naming test (BNT) and the Action naming test (Action BNT, ANT). All subjects completed the study. At baseline, no statistically significant group differences were discovered for age, post-stroke time or diagnosis. ILAT was associated with significant improvement across groups, as documented by both primary and secondary outcome measures. No significant effect of rTMS could be documented. Our results agree with previous results proving ILAT's ability to improve language in patients with chronic aphasia. In contrast with earlier claims, however, a beneficial effect of rTMS in chronic post-stroke aphasia rehabilitation was not detected in this study. www.ClinicalTrials.gov, identifier: NCT03629665.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fnins.2018.01036DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6369187PMC
February 2019

Clinical utility and prospective of TMS-EEG.

Clin Neurophysiol 2019 05 19;130(5):802-844. Epub 2019 Jan 19.

Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, and Department of Psychiatry, University of Toronto, Toronto, ON, Canada.

Concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) has emerged as a powerful tool to non-invasively probe brain circuits in humans, allowing for the assessment of several cortical properties such as excitability and connectivity. Over the past decade, this technique has been applied to various clinical populations, enabling the characterization and development of potential TMS-EEG predictors and markers of treatments and of the pathophysiology of brain disorders. The objective of this article is to present a comprehensive review of studies that have used TMS-EEG in clinical populations and to discuss potential clinical applications. To provide a technical and theoretical framework, we first give an overview of TMS-EEG methodology and discuss the current state of knowledge regarding the use of TMS-EEG to assess excitability, inhibition, plasticity and connectivity following neuromodulatory techniques in the healthy brain. We then review the insights afforded by TMS-EEG into the pathophysiology and predictors of treatment response in psychiatric and neurological conditions, before presenting recommendations for how to address some of the salient challenges faced in clinical TMS-EEG research. Finally, we conclude by presenting future directions in line with the tremendous potential of TMS-EEG as a clinical tool.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.clinph.2019.01.001DOI Listing
May 2019

Individual Activation Patterns After the Stimulation of Different Motor Areas: A Transcranial Magnetic Stimulation-Electroencephalography Study.

Brain Connect 2018 Sep;8(7):420-428

Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.

The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) enables one to study effective connectivity and activation order in neuronal networks. To characterize effective connectivity originating from the primary motor cortex (M1), dorsal premotor area (PMd), and supplementary motor area (SMA). Three right-handed volunteers (two men, aged 25-30 years) participated in a navigated TMS-EEG experiment. M1, PMd, and SMA over the nondominant hemisphere were stimulated with 150 TMS pulses. Minimum-norm estimates were derived from the EEG data to estimate the spatial spreading of TMS-elicited neuronal activation on an individual level. The activation order of the cortical areas varied depending on the stimulated area. There were similarities and differences in the spatial distribution of the TMS-evoked potentials between subjects. Similarities in cortical activation patterns were seen at short poststimulus latencies and the differences at long latencies. This pilot study suggests that cortical activation patterns and the activation order of motor areas differ interindividually and depend on the stimulated motor area. It further indicates that TMS-activated effective connections or underlying structural connections vary between subjects. The spatial patterns of TMS-evoked potentials differ between subjects especially at long latencies, when probably more complex neuronal networks are active.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1089/brain.2018.0593DOI Listing
September 2018

Theta-burst stimulation causally affects side perception in the Deutsch's octave illusion.

Sci Rep 2018 08 27;8(1):12844. Epub 2018 Aug 27.

Department of Psychological, Health and Territory Sciences, "G. d'Annunzio" University of Chieti and Pescara, Chieti, Italy.

Deutsch's octave illusion is produced by a sequence of two specular dichotic stimuli presented in alternation to the left and right ear causing an illusory segregation of pitch (frequency) and side (ear of origin). Previous studies have indicated that illusory perception of pitch takes place in temporo-frontal areas, whereas illusory perception of side is primarily associated to neural activity in parietal cortex and in particular in the inferior parietal lobule (IPL). Here we investigated the causal role of left IPL in the perception of side (ear of origin) during the octave illusion by following its inhibition through continuous theta-burst stimulation (cTBS), as compared to the left posterior intraparietal sulcus (pIPS), whose activity is thought to be unrelated to side perception during the illusion. We observed a prolonged modification in the side of the illusory perceived tone during the first 10 minutes following the stimulation. Specifically, while after cTBS over the left IPS subjects reported to perceive the last tone more often at the right compared to the left ear, cTBS over left IPL significantly reverted this distribution, as the number of last perceived tones at the right ear was smaller than at the left ear. Such alteration was not maintained in the successive 10 minutes. These results provide the first evidence of the causal involvement of the left IPL in the perception of side during the octave illusion.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41598-018-31248-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6110737PMC
August 2018

Multi-locus transcranial magnetic stimulation-theory and implementation.

Brain Stimul 2018 Jul - Aug;11(4):849-855. Epub 2018 Mar 23.

Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.

Background: Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation method: a magnetic field pulse from a TMS coil can excite neurons in a desired location of the cortex. Conventional TMS coils cause focal stimulation underneath the coil centre; to change the location of the stimulated spot, the coil must be moved over the new target. This physical movement is inherently slow, which limits, for example, feedback-controlled stimulation.

Objective: To overcome the limitations of physical TMS-coil movement by introducing electronic targeting.

Methods: We propose electronic stimulation targeting using a set of large overlapping coils and introduce a matrix-factorisation-based method to design such sets of coils. We built one such device and demonstrated the electronic stimulation targeting in vivo.

Results: The demonstrated two-coil transducer allows translating the stimulated spot along a 30-mm-long line segment in the cortex; with five coils, a target can be selected from within a region of the cortex and stimulated in any direction. Thus, far fewer coils are required by our approach than by previously suggested ones, none of which have resulted in practical devices.

Conclusion: Already with two coils, we can adjust the location of the induced electric field maximum along one dimension, which is sufficient to study, for example, the primary motor cortex.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.brs.2018.03.014DOI Listing
February 2019

Optimized 3D co-registration of ultra-low-field and high-field magnetic resonance images.

PLoS One 2018 6;13(3):e0193890. Epub 2018 Mar 6.

Department of Neuroscience, Imaging and Clinical Science, Chieti, Italy.

The prototypes of ultra-low-field (ULF) MRI scanners developed in recent years represent new, innovative, cost-effective and safer systems, which are suitable to be integrated in multi-modal (Magnetoencephalography and MRI) devices. Integrated ULF-MRI and MEG scanners could represent an ideal solution to obtain functional (MEG) and anatomical (ULF MRI) information in the same environment, without errors that may limit source reconstruction accuracy. However, the low resolution and signal-to-noise ratio (SNR) of ULF images, as well as their limited coverage, do not generally allow for the construction of an accurate individual volume conductor model suitable for MEG localization. Thus, for practical usage, a high-field (HF) MRI image is also acquired, and the HF-MRI images are co-registered to the ULF-MRI ones. We address here this issue through an optimized pipeline (SWIM-Sliding WIndow grouping supporting Mutual information). The co-registration is performed by an affine transformation, the parameters of which are estimated using Normalized Mutual Information as the cost function, and Adaptive Simulated Annealing as the minimization algorithm. The sub-voxel resolution of the ULF images is handled by a sliding-window approach applying multiple grouping strategies to down-sample HF MRI to the ULF-MRI resolution. The pipeline has been tested on phantom and real data from different ULF-MRI devices, and comparison with well-known toolboxes for fMRI analysis has been performed. Our pipeline always outperformed the fMRI toolboxes (FSL and SPM). The HF-ULF MRI co-registration obtained by means of our pipeline could lead to an effective integration of ULF MRI with MEG, with the aim of improving localization accuracy, but also to help exploit ULF MRI in tumor imaging.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0193890PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5839578PMC
June 2018

Noninvasive extraction of microsecond-scale dynamics from human motor cortex.

Hum Brain Mapp 2018 06 2;39(6):2405-2411. Epub 2018 Mar 2.

Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.

State-of-the-art noninvasive electromagnetic recording techniques allow observing neuronal dynamics down to the millisecond scale. Direct measurement of faster events has been limited to in vitro or invasive recordings. To overcome this limitation, we introduce a new paradigm for transcranial magnetic stimulation. We adjusted the stimulation waveform on the microsecond scale, by varying the duration between the positive and negative phase of the induced electric field, and studied corresponding changes in the elicited motor responses. The magnitude of the electric field needed for given motor-evoked potential amplitude decreased exponentially as a function of this duration with a time constant of 17 µs. Our indirect noninvasive measurement paradigm allows studying neuronal kinetics on the microsecond scale in vivo.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/hbm.24010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6866442PMC
June 2018

Truncated RAP-MUSIC (TRAP-MUSIC) for MEG and EEG source localization.

Neuroimage 2018 02 8;167:73-83. Epub 2017 Nov 8.

Department of Neuroscience and Biomedical Engineering (NBE), Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital (HUH), Helsinki, Finland.

Electrically active brain regions can be located applying MUltiple SIgnal Classification (MUSIC) on magneto- or electroencephalographic (MEG; EEG) data. We introduce a new MUSIC method, called truncated recursively-applied-and-projected MUSIC (TRAP-MUSIC). It corrects a hidden deficiency of the conventional RAP-MUSIC algorithm, which prevents estimation of the true number of brain-signal sources accurately. The correction is done by applying a sequential dimension reduction to the signal-subspace projection. We show that TRAP-MUSIC significantly improves the performance of MUSIC-type localization; in particular, it successfully and robustly locates active brain regions and estimates their number. We compare TRAP-MUSIC and RAP-MUSIC in simulations with varying key parameters, e.g., signal-to-noise ratio, correlation between source time-courses, and initial estimate for the dimension of the signal space. In addition, we validate TRAP-MUSIC with measured MEG data. We suggest that with the proposed TRAP-MUSIC method, MUSIC-type localization could become more reliable and suitable for various online and offline MEG and EEG applications.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuroimage.2017.11.013DOI Listing
February 2018

Automatic and robust noise suppression in EEG and MEG: The SOUND algorithm.

Neuroimage 2018 02 20;166:135-151. Epub 2017 Oct 20.

Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, P.O. Box 12200, FI-00076, AALTO, Finland; BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, P.O. Box 340, FI-00029, HUS, Finland.

Electroencephalography (EEG) and magnetoencephalography (MEG) often suffer from noise- and artifact-contaminated channels and trials. Conventionally, EEG and MEG data are inspected visually and cleaned accordingly, e.g., by identifying and rejecting the so-called "bad" channels. This approach has several shortcomings: data inspection is laborious, the rejection criteria are subjective, and the process does not fully utilize all the information in the collected data. Here, we present noise-cleaning methods based on modeling the multi-sensor and multi-trial data. These approaches offer objective, automatic, and robust removal of noise and disturbances by taking into account the sensor- or trial-specific signal-to-noise ratios. We introduce a method called the source-estimate-utilizing noise-discarding algorithm (the SOUND algorithm). SOUND employs anatomical information of the head to cross-validate the data between the sensors. As a result, we are able to identify and suppress noise and artifacts in EEG and MEG. Furthermore, we discuss the theoretical background of SOUND and show that it is a special case of the well-known Wiener estimators. We explain how a completely data-driven Wiener estimator (DDWiener) can be used when no anatomical information is available. DDWiener is easily applicable to any linear multivariate problem; as a demonstrative example, we show how DDWiener can be utilized when estimating event-related EEG/MEG responses. We validated the performance of SOUND with simulations and by applying SOUND to multiple EEG and MEG datasets. SOUND considerably improved the data quality, exceeding the performance of the widely used channel-rejection and interpolation scheme. SOUND also helped in localizing the underlying neural activity by preventing noise from contaminating the source estimates. SOUND can be used to detect and reject noise in functional brain data, enabling improved identification of active brain areas.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuroimage.2017.10.021DOI Listing
February 2018
-->