Biology subjects

Zich, C.

Publications and source records attributed to Zich, C..

15 recordsLinked to original sources

bioRxiv2025

Closed-loop beta stimulation enhances beta activity and motor behaviour

Movement-related beta event-related synchronization (ERS) has been linked to motor control and learning, showing potential as a therapeutic target for those with movement deficits, such as stroke survivors. However, whether directly modulating beta ERS can causally influence motor performance remains unclear, largely due to the lack of methods designed to specifically target this neural activity. To address this gap, we developed a novel behaviourally-driven, closed-loop transcranial alternating current stimulation (tACS) approach to target movement-related beta ERS during a visuomotor adaptation task. We found that the behaviourally-driven, closed-loop beta-tACS specifically enhances beta ERS without affecting beta event-related desynchronization (ERD). Critically, this targeted enhancement significantly improves retention of motor adaptation. These findings establish a causal relationship between beta ERS and motor behaviour and highlight the potential of behaviourally-driven beta-tACS as a therapeutic approach for improving motor function in clinical populations characterized by impaired beta activity.

neuroscience↗

bioRxiv2025

Dual-site beta transcranial alternating current stimulation during a bimanual coordination task modulates functional connectivity between motor areas

BackgroundCommunication within brain networks depends on functional connectivity. One promising approach to modulate such connectivity between cortical areas is dual-site transcranial alternating current stimulation (tACS), which non-invasively applies weak alternating currents to two brain areas. Objectives/HypothesesIn the current study, we aimed to modulate inter-regional functional connectivity with dual-site tACS to bilateral primary motor cortices (M1s) during bimanual coordination and, in turn, alter behaviour. MethodsUsing functional magnetic resonance imaging (fMRI), we recorded participants brain responses during a bimanual coordination task in a concurrent tACS-fMRI design. While performing a slow and fast version of the task, participants received one of three types of beta (20 Hz) dual-site tACS over both M1s: in-phase, jittered-phase or sham, in a within-subject, repeated measures design. ResultsWhile we did not observe any significant tACS effects on behaviour, the study revealed a disruptive effect of in-phase tACS on interhemispheric connectivity. Additionally, the two active types of tACS (in-phase and jittered-phase) differed in the task-related M1 connectivity with other motor cortical regions, such as premotor cortex and supplementary motor area. Furthermore, individual E-field strengths were related to functional connectivity in the in-phase condition. ConclusionsDual-site beta tACS over both M1s altered functional connectivity between motor areas. However, this effect did not translate to the behavioural level, possibly due to compensatory mechanisms. HighlightsO_LIInterhemispheric connectivity between the primary motor cortices was targeted with dual-site beta tACS during bimanual coordination. C_LIO_LIIn-phase as compared to sham tACS disrupted interhemispheric connectivity during task performance. C_LIO_LIIn-phase and jittered-phase tACS led to different task-related functional connectivity patterns within the motor network. C_LIO_LIThe relationship between individual in-phase E-field strengths and interhemispheric connectivity depended on task demand. C_LIO_LIThere were no significant tACS effects on behavioural performance of bimanual coordination, possibly due to compensatory mechanisms. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/647211v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@17ecdd8org.highwire.dtl.DTLVardef@1fc5b25org.highwire.dtl.DTLVardef@c3df42org.highwire.dtl.DTLVardef@17671bb_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2024

The effects of varying intensities of unilateral handgrip fatigue on bilateral movement

The human ability to maintain adequate movement quality despite muscle fatigue is of critical importance to master physically demanding activities of daily life and for retaining independence following motor impairments. Many real-life situations call for asymmetrical activation of extremity muscles leading to unilateral manifestations of muscle fatigue. Repeated unilateral handgrip contractions at submaximal force have been shown to be associated with neural dynamics in both contralateral and ipsilateral cortical motor areas and improved response times of the contralateral, unfatigued homologue in a button-press task. However, it remains unclear whether the observed improvement in contralateral response latency translates into higher-level benefits in movement quality. To investigate this, 30 healthy participants underwent unilateral handgrip fatiguing tasks at 5%, 50%, and 75% of maximum voluntary contraction (MVC) force. Subsequently, bimanual movement quality was assessed in an object-hit task using a Kinarm robot. The protocol at 50% and 75% of MVC elicited clear signs of muscle fatigue compared to the control condition (5%) measured by a decline in force, post-exercise deterioration in MVC, characteristic changes in surface electromyography magnitudes, and increases in ratings of perceived exertion. No change was observed on kinematic measures in the object-hit task for both arms indicating that unilateral handgrip fatigue did not elicit measurable effects on higher-level movement quality on the ipsilateral or contralateral homologue. Previously reported improvements on contralateral response latency were not found to translate into advanced movement quality benefits.

neuroscience↗

bioRxiv2024

Differential beta and gamma activity modulation during unimanual and bimanual motor learning

Movement-related dynamics in the beta and gamma bands have been studied in relation to motor execution and learning during unimanual movements, but their roles in complex bimanual tasks remain largely unexplored. This study aimed to investigate how beta and gamma activity differs between unimanual and bimanual movements, and how these neural signatures evolve during the learning process. Our motor task incorporated varying levels of bimanual interaction: unimanual, bimanual-equal, and bimanual-unequal. Magnetoencephalography data were recorded during task performance, and beta and gamma dynamics were quantified. As expected, increasing task complexity from unimanual to bimanual-equal, and then to bimanual-unequal movements resulted in slower and less accurate performance. Across all conditions, significant beta event-related desynchronization (ERD) and gamma event-related synchronization (ERS) were observed during movement, as well as beta ERS after movement. Bimanual movements exhibited greater beta ERD, beta ERS, and gamma ERS compared to unimanual movements. With practice, participants demonstrated faster and more accurate movements, accompanied by enhanced beta ERS responses. Furthermore, learning-related reductions in errors correlated with increases in beta ERS. These findings suggest the distinct behavioural and neural demands of unimanual versus bimanual movements and highlight the important role of beta dynamics in motor performance and learning.

physiology↗

bioRxiv2022

The GLM-Spectrum: A multilevel framework for spectrum analysis with covariate and confound modelling

The frequency spectrum is a central method for representing the dynamics within electrophysiological data. Some widely used spectrum estimators make use of averaging across time segments to reduce noise in the final spectrum. The core of this approach has not changed substantially since the 1960s, though many advances in the field of regression modelling and statistics have been made during this time. Here, we propose a new approach, the General Linear Model (GLM) Spectrum, which reframes time averaged spectral estimation as multiple regression. This brings several benefits, including the ability to do confound modelling, hierarchical modelling and significance testing via non-parametric statistics. We apply the approach to a dataset of EEG recordings of participants who alternate between eyes-open and eyes-closed resting state. The GLM-Spectrum can model both conditions, quantify their differences, and perform denoising through confound regression in a single step. This application is scaled up from a single channel to a whole head recording and, finally, applied to quantify age differences across a large group-level dataset. We show that the GLM-Spectrum lends itself to rigorous modelling of within- and between-subject contrasts as well as their interactions, and that the use of model-projected spectra provides an intuitive visualisation. The GLM-Spectrum is a flexible framework for robust multi-level analysis of power spectra, with adaptive covariance and confound modelling.

neuroscience↗

bioRxiv2022

Spatiotemporal organization of human sensorimotor beta burst activity

Beta oscillations in human sensorimotor cortex are hallmark signatures of healthy and pathological movement. In single trials, beta oscillations include bursts of intermittent, transient periods of high-power activity. These burst events have been linked to a range of sensory and motor processes, but their precise spatial, spectral, and temporal structure remains unclear. Specifically, a role for beta burst activity in information coding and communication suggests spatiotemporal patterns, or travelling wave activity, along specific anatomical gradients. We here show in human magnetoencephalography recordings that burst activity in sensorimotor cortex occurs in planar spatiotemporal wave-like patterns that dominate along two axes either parallel or perpendicular to the central sulcus. Moreover, we find that the two propagation directions are characterised by distinct anatomical and physiological features. Finally, our results suggest that sensorimotor beta bursts occurring before and after a movement share the same generator but can be distinguished by their anatomical, spectral and spatiotemporal characteristics, indicating distinct functional roles.

neuroscience↗

bioRxiv2022

Concurrent spinal and brain imaging with optically pumped magnetometers

The spinal cord and its interactions with the brain are fundamental for movement control and somatosensation. However, brain and spinal cord electrophysiology in humans have largely been treated as distinct enterprises, in part due to the relative inaccessibility of the spinal cord. Consequently, there is a dearth of knowledge on human spinal electrophysiology, including the multiple pathologies of the central nervous system that affect the spinal cord as well as the brain. Here we exploit recent advances in the development of wearable optically pumped magnetometers (OPMs) which can be flexibly arranged to provide coverage of both the spinal cord and the brain concurrently in unconstrained environments. Our system for magnetospinoencephalography (MSEG) measures both spinal and cortical signals simultaneously by employing a custom-made spinal scanning cast. We evidence the utility of such a system by recording simultaneous spinal and cortical evoked responses to median nerve stimulation, demonstrating the novel ability for concurrent non-invasive millisecond imaging of brain and spinal cord.

neuroscience↗

bioRxiv2021

Fatigue induces behavioural improvements in the unfatigued hand via altered functional connectivity and neurochemicals in cortical motor areas

In humans, motor learning is underpinned by changes in sensorimotor network functional connectivity (FC). Unilateral contractions increase FC in the ipsilateral primary motor cortex (M1) and supplementary motor area (SMA); areas involved in motor planning and execution of the contralateral hand. Therefore, unilateral contractions are a promising approach to augment motor performance in the contralateral hand. In a within-participant, randomized, cross-over design, 15 right-handed adults had two magnetic resonance imaging (MRI) sessions, where functional-MRI and MR-Spectroscopic Imaging were acquired before and after repeated right-hand contractions at either 5% or 50% maximum voluntary contraction (MVC). Before and after scanning, response times (RTs) were determined in both hands. Nine minutes of 50% MVC contractions resulted in decreased handgrip force in the contracting hand, and decreased RTs in the contralateral hand. This improved motor performance in the contralateral hand was supported by significant neural changes: increased FC between SMA-SMA and increased FC between right M1 and right Orbitofrontal Cortex. At a neurochemical level, the degree of GABA decline in left M1, left and right SMA correlated with subsequent behavioural improvements in the left-hand. These results support the use of repeated handgrip contractions as a potential modality for improving motor performance in the contralateral hand. Significance StatementEnhanced functional connectivity and decreased inhibition in sensorimotor areas of the brain underpin enhancements in motor performance and learning. In this study we investigated the impact of repeated right handgrip contractions at 50% MVC to improve behaviour, enhance functional connectivity and alter sensorimotor inhibition. We found that after nine minutes of repeated 50% MVC handgrip contractions with the right-hand, left-hand response times were significantly improved. This behavioural improvement was accompanied by altered interhemispheric functional connectivity and neurochemical changes across sensorimotor areas. Repeated unilateral handgrip contractions may be an effective method for enhancing contralateral limb motor performance in rehabilitation settings.

neuroscience↗

bioRxiv2021

Human motor cortical gamma activity relates to GABAergic signalling and to behaviour

Gamma activity ({gamma}, >30 Hz) is universally demonstrated across brain regions and species. However, the physiological basis and functional role of {gamma} sub-bands (slow-{gamma}, mid-{gamma}, fast-{gamma}) have been predominantly studied in rodent hippocampus; {gamma} activity in the human neocortex is much less well understood. Here we combined neuroimaging and non-invasive brain stimulation to examine the properties of {gamma} activity sub-bands in the primary motor cortex (M1), and their relationship to both local GABAergic activity and to motor learning. In 33 healthy individuals, we quantified movement-related {gamma} activity in M1 using magnetoencephalography, assessed GABAergic signaling using transcranial magnetic stimulation (TMS), and estimated motor learning via a serial reaction time task. We characterised two distinct {gamma} sub-bands (slow-{gamma}, mid-{gamma}) which show movement-related increase in activity during unilateral index finger movements and are characterised by distinct temporal-spectral-spatial profiles. Bayesian correlation analysis revealed strong evidence for a positive relationship between slow-{gamma} ([~]30-60Hz) peak frequency and endogenous GABA signalling during movement preparation (as assessed using the TMS-metric short interval intracortical inhibition). There was also moderate evidence for a relationship between power of the movement-related mid-{gamma} activity (60-90Hz) and motor learning. These relationships were neurochemically- and frequency-specific. These data provide new insights into the neurophysiological basis and functional roles of {gamma} activity in human M1 and allow the development of a new theoretical framework for {gamma} activity in the human neocortex. Significance StatementGamma ({gamma}) activity is ubiquitous in the brain, yet our understanding of the mechanisms and function of {gamma} activity in the human neocortex, and particularly in the human motor cortex, is limited. Using a multimodal approach, we characterised two patterns of movement-related {gamma} activity in the human motor cortex (slow-{gamma} and mid-{gamma}), with different spatial, temporal and spectral properties. Slow-{gamma} peak frequency was correlated to local GABA-A activity, whereas mid-gamma power predicted performance in a subsequent motor learning task. Based on these findings and previous research, we propose a theoretical framework to explain how human motor cortical {gamma} activities may arise and their potential role in plasticity and motor learning, providing new hypotheses to be tested in future studies. Key PointsO_LIWe combined neuroimaging (i.e. MEG) and non-invasive brain stimulation (i.e. TMS) to examine the properties of {gamma} activity sub-bands in the primary motor cortex. C_LIO_LITwo distinct {gamma} sub-bands (slow-{gamma}, mid-{gamma}) show a movement-related increase in activity during finger movements and are characterised by distinct temporal-spectral-spatial profiles. C_LIO_LIWe found strong evidence for a positive relationship between slow-{gamma} ([~]30-60Hz) peak frequency and endogenous GABA signalling during movement preparation (as assessed using the TMS-metric short interval intracortical inhibition). C_LI

neuroscience↗

bioRxiv2021

The impact of brain lesions on tDCS-induced electric field magnitude

BackgroundTranscranial direct current stimulation (tDCS) has been used to enhance motor and language rehabilitation following a stroke. However, improving the effectiveness of clinical tDCS protocols depends on understanding how lesions may influence tDCS-induced current flow through the brain. ObjectiveWe systematically investigated the effect of brain lesions on the magnitude of electric fields (e-mag) induced by tDCS, and how to overcome lesion-induced inter-individual variability in e-mag. MethodsWe simulated the effect of 630 different lesions - by varying lesion location, distance from the target region of interest (ROI), size and conductivity - on tDCS-induced e-mag in the brains of two participants. Current flow modelling was conducted for two tDCS montages commonly used in clinical applications, which target either primary motor cortex (M1) or Brocas area (BA44), respectively. We further explored how the inherent variability in e-mag that is introduced by inter-lesion differences can be overcome by individualising tDCS protocols. ResultsThe effect on absolute e-mag was highly dependent on lesion size, conductance and the distance from the target ROI. Larger lesions, with high conductivity, closer to the ROI caused e-mag changes of more than 30%. The sign of this change was determined by the location of the lesion. Specifically, lesions located in-line with the predominant direction of current flow increased e-mag in the ROI, whereas lesions located in the opposite direction caused a decrease. Lesions had a large impact on the optimal electrode configuration if attempting to maximise for the total e-mag in the ROI, but little impact if only the component of e-mag flowing radially inward to the cortex was maximised. Knowing the effect of a given lesion on e-mag also allows for individualising tDCS intensity to reduce variability. ConclusionsThese results demonstrate that tDCS-induced electric fields are profoundly influenced by lesion characteristics, and further exacerbate the known variability in e-mag across individuals. Additionally, the dependence of these results on the assigned conductance of the lesion underlines the need for improved estimates of lesion conductivity for current flow models. Our results highlight the need for individualised dose control of tDCS in the lesioned brain to overcome the substantial inter-individual variability in electric fields delivered to a cortical target region. Highlights- Lesions can alter tDCS-induced electric field magnitude (e-mag) in a target by 30% - Lesions can cause increases or decreases to e-mag - Direction of change depends on the position of the lesion relative to current flow - Lesion conductivity - the true value for which is unknown - also impacts change - E-mag variability can be reduced by individualising montage and stimulation intensity

neuroscience↗

bioRxiv2020

Motor Imagery EEG Neurofeedback Skill Acquisition in the Context of Declarative Interference and Sleep

Motor imagery (MI) practice in combination with neurofeedback (NF) is a promising supplement to facilitate the acquisition of motor abilities and the recovery of impaired motor abilities following brain injuries. However, the ability to control MI NF is subject to a wide range of inter-individual variability. A substantial number of users experience difficulties in achieving good results, which compromises their chances to benefit from MI NF in a learning or rehabilitation context. It has been suggested that context factors, that is, factors outside the actual motor task, can explain individual differences in motor skill acquisition. Retrospective declarative interference and sleep have already been identified as critical factors for motor execution (ME) and MI based practice. Here, we investigate whether these findings generalize to MI NF practice. Three groups underwent three blocks of MI NF practice each on two subsequent days. In two of the groups, MI NF blocks were followed by either immediate or delayed declarative memory tasks. The control group performed only MI NF and no specific interference tasks. Two of the MI NF blocks were run on the first day of the experiment, the third in the morning of the second day. Significant within-block NF gains in mu and beta frequency event-related desynchronization (ERD) where evident for all groups. However, effects of sleep on MI NF ERD were not found. Data did also not indicate an impact of immediate or delayed declarative interference on MI NF ERD. Our results indicate that effects of sleep and declarative interference context on ME or MI practice cannot unconditionally be generalized to MI NF skill acquisition. The findings are discussed in the context of variable experimental task designs, inter-individual differences, and performance measures.

neuroscience↗

bioRxiv2020

Determinants of Real-Time fMRI Neurofeedback Performance and Improvement: a Machine Learning Mega-Analysis

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments. With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in Open Science and data sharing.

neuroscience↗

bioRxiv2020

Can we predict real-time fMRI neurofeedback learning success from pre-training brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large interindividual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pre-training functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pre-training activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.

neuroscience↗

bioRxiv2018

Modulatory effects of dynamic fMRI-based neurofeedback on emotion regulation networks during adolescence

Research has shown that difficulties with emotion regulation abilities in childhood and adolescence increase the risk for developing symptoms of mental disorders, e.g anxiety. We investigated whether functional magnetic resonance imaging (fMRI)-based neurofeedback (NF) can modulate brain networks supporting emotion regulation abilities in adolescent females. We performed three studies (total N=63). We first compared different NF implementations regarding their effectiveness of modulating prefrontal cortex (PFC)-amygdala functional connectivity (fc). Further we assessed the effects of fc-NF on neural measures, emotional/metacognitive measures and their associations. Finally, we probed the mechanism underlying fc-NF by examining concentrations of inhibitory and excitatory neurotransmitters. Results showed that NF implementations differentially modulate PFC-amygdala fc. Using the most effective NF implementation we observed important relationships between neural and emotional/metacognitive measures, such as practice-related change in fc was related with change in thought control ability. Further, we found that the relationship between state anxiety prior to the MRI session and the effect of fc-NF was moderated by GABA concentrations in the PFC and anterior cingulate cortex. To conclude, we were able to show that fc-NF can be used in adolescent females to shape neural and emotional/metacognitive measures underlying emotion regulation. We further show that neurotransmitter concentrations moderate fc-NF-effects.

neuroscience↗

bioRxiv2018

Motor learning shapes temporal activity in human sensorimotor cortex

Although neuroimaging techniques have provided vital insights into the anatomical regions involved in motor learning, the underlying changes in temporal dynamics are not well understood. Using magnetoencephalography and Hidden Markov Modelling to model the dynamics of neural oscillations on data-adaptive time-scales, we detected specific changes in movement-related sensorimotor {beta}-activity during practice of a self-paced sequential visuo-motor task. The behaviourally-relevant neural signature generalised to another motor task, emphasising the centrality of {beta}-activity in motor plasticity.

neuroscience↗