Biology subjects

Meesen, R.

Publications and source records attributed to Meesen, R..

3 recordsLinked to original sources

bioRxiv2024

EEG Responses to Upper Limb Pinprick Stimulation in Acute and Early Subacute Motor and Sensorimotor Stroke

BackgroundElectroencephalography (EEG) during pinprick stimulation has the potential to unveil neural mechanisms underlying sensorimotor impairments post-stroke. This study explored event-related peak pinprick amplitude and oscillatory responses in healthy controls, in people with motor and sensorimotor in acute and early subacute stroke, their relationship and to what extent EEG somatosensory responses can predict sensorimotor impairment. MethodsIn this study, involving 26 individuals, 10 people with a (sub-)acute sensorimotor stroke, 6 people with a (sub)acute motor stroke and 10 age-matched controls, pinpricks were applied to the dorsa of the impaired hand to collect somatosensory evoked potentials. Time(-frequency) analyses of somatosensory evoked potential (SEP) data at electrodes C3 and C4 explored peak pinprick amplitude and oscillatory responses across the three groups. Also, in stroke, (sensori-)motor impairments were assessed at baseline Fugl Meyer Assessment Upper Extremity (FMA-UE) and Erasmus modified Nottingham Sensory Assessment (EmNSA) at baseline and 7 to 14 days later including Fugl Meyer Assessment Upper Extremity (FMA-UE) and Erasmus modified Nottingham Sensory Assessment (EmNSA). Mixed model analyses were used to address objectives. ResultsIt was demonstrated that increased beta desynchronization magnitude correlated with milder motor impairments (R2 =0.213), whereas increased beta resynchronization and delta power were associated to milder somatosensory impairment (R2 =0.550). At the second session, larger peak-to-peak SEP amplitude and beta band resynchronization at baseline were related to greater improvements in EMNSA and FMA-UE score, respectively, in sensorimotor stroke group. ConclusionsThese findings highlight the potential of EEG combined with somatosensory stimuli to differentiate between sensorimotor and motor impairments in stroke, offering preliminary insights into both diagnostic and prognostic aspects of upper limb recovery.

neuroscience↗

bioRxiv2023

From scalp to cortex, the whole isn't greater than the sum of its parts: introducing GetTissueThickness (GTT) to assess age and sex differences in tissue thicknesses

Noninvasive techniques to record and stimulate the brain rely on passing through the tissues in between the scalp and cortex. Currently, there is no method to obtain detailed information about these scalp-to-cortex distance (SCD) tissues. We introduce GetTissueThickness (GTT), an open-source, automated approach to quantify SCD, and unveil how tissue thicknesses differ across age groups, sexes and brain regions (n = 250). We show that men have larger SCD in lower scalp regions and women have similar-to-larger SCD in regions closer to the vertex, with aging resulting in increased SCD in fronto-central regions. Soft tissue thickness varies by sex and age, with thicker layers and greater age-related decreases in men. Compact and spongy bone thickness also differ across sexes and age groups, with thicker compact bone in women in both age groups and an age-related thickening. Older men generally have the thickest cerebrospinal fluid layer and younger women and men having similar cerebrospinal fluid layers. Aging mostly results in grey matter thinning. Concerning SCD, the whole isnt greater than the sum of its parts. GTT enables rapid quantification of the SCD tissues. The distinctive sensitivity of noninvasive recording and stimulation modalities to different tissues underscores the relevance of GTT.

neuroscience↗

bioRxiv2023

A Systematic Review and Large-Scale tES and TMS Electric Field Modeling Study Reveals How Outcome Measure Selection Alters Results in a Person- and Montage-Specific Manner

BackgroundElectric field (E-field) modeling is a potent tool to examine the cortical effects of transcranial magnetic and electrical stimulation (TMS and tES, respectively) and to address the high variability in efficacy observed in the literature. However, outcome measures used to report E-field magnitude vary considerably and have not yet been compared in detail. ObjectivesThe goal of this two-part study, encompassing a systematic review and modeling experiment, was to provide an overview of the different outcome measures used to report the magnitude of tES and TMS E-fields, and to conduct a direct comparison of these measures across different stimulation montages. MethodsThree electronic databases were searched for tES and/or TMS studies reporting E-field magnitude. We extracted and discussed outcome measures in studies meeting the inclusion criteria. Additionally, outcome measures were compared via models of four common tES and two TMS modalities in 100 healthy younger adults. ResultsIn the systematic review, we included 118 studies using 151 outcome measures related to E-field magnitude. Structural and spherical regions of interest (ROI) analyses and percentile-based whole-brain analyses were used most often. In the modeling analyses, we found that there was an average of only 6% overlap between ROI and percentile-based whole-brain analyses in the investigated volumes within the same person. The overlap between ROI and whole-brain percentiles was montage- and person-specific, with more focal montages such as 4x1 and APPS-tES, and figure-of-eight TMS showing up to 73%, 60%, and 52% overlap between ROI and percentile approaches respectively. However, even in these cases, 27% or more of the analyzed volume still differed between outcome measures in every analyses. ConclusionsThe choice of outcome measures meaningfully alters the interpretation of tES and TMS E-field models. Well-considered outcome measure selection is imperative for accurate interpretation of results, valid between-study comparisons, and depends on stimulation focality and study goals. We formulated four recommendations to increase the quality and rigor of E-field modeling outcome measures. With these data and recommendations, we hope to guide future studies towards informed outcome measure selection, and improve the comparability of studies.

neuroscience↗