Biology subjects

Vinding, M. C.

Publications and source records attributed to Vinding, M. C..

9 recordsLinked to original sources

bioRxiv2026

Striatal Dopaminergic Dysfunction Constrains Motor Invigoration in Parkinson's Disease

Bradykinesia is a cardinal motor feature of Parkinson's disease and is characterised by a reduced ability to generate movements with normal speed and force. Although nigrostriatal dopamine loss is regarded as the primary cause, direct human evidence linking dopaminergic degeneration to striatal dysfunction and impaired motor output and vigour remains limited. To investigate this relationship, we developed a grip-force paradigm that quantified movement vigour as the ability to rapidly generate force. Fifty-three individuals with Parkinson's disease, 30 with levodopa-induced dyskinesia and 23 without, and 25 age-matched healthy controls performed the task during 3T functional MRI. Thirty-five patients additionally underwent dopamine transporter PET imaging to assess associations among nigrostriatal dopaminergic integrity, striatal activity and motor performance. Patients with Parkinson's disease showed marked reductions in initial movement vigour accompanied by reduced bilateral putaminal activation during force generation. Lower putaminal dopamine transporter binding was associated with both poorer movement vigour and weaker grip-related putaminal activation during functional MRI, establishing a direct link between nigrostriatal degeneration, impaired striatal recruitment and motor slowing. Functional MRI further revealed reduced reward-related responses in the nucleus accumbens. Across participants, stronger reward-related ventral striatal activity was associated with greater movement vigour, suggesting that motivational processes contribute independently to motor performance. Patients with levodopa-induced dyskinesia exhibited more severe putaminal dopaminergic denervation than patients without dyskinesia but showed no additional impairment of movement vigour or striatal task responses. These findings provide direct in vivo evidence that dorsal nigrostriatal dopaminergic degeneration constrains movement vigour in Parkinson's disease through reduced striatal recruitment during action generation. Impaired reward-related signalling in ventral striatum emerges as an additional, partly independent mechanism influencing motor performance, highlighting distinct motor and motivational contributions to bradykinesia.

neuroscience↗

bioRxiv2025

Motor prediction reduces beta-band power and enhances cerebellar-somatosensory connectivity before self-touch to enable its attenuation

Motor control theories suggest that the brain uses forward models to predict self-generated tactile input during voluntary movements, thereby reducing the intensity of reafferent tactile sensations. When ones own body is the target, this phenomenon is called self-touch attenuation. Although self-touch attenuation is well-documented, it remains unclear how prediction-related neural mechanisms drive attenuation before the self-touch input. We used magnetoencephalography (MEG) to examine the neural correlates of self-touch prediction. 24 human participants (12 female, 12 male) performed a self-touch, and two control tasks. In one control, they received externally generated touch without movement. In the other, the touch was triggered by the participants movement, but the hands were spatially misaligned. This manipulation is known to weaken attenuation despite identical tactile input, movement, and task demands, because the sensorimotor context reduces prediction of touch at that body site. Self-touch evoked weaker somatosensory activity (M50 component) than both control conditions. A psychophysics task mirrored the pattern of neural attenuation, as the perception of self-touch was attenuated compared to the two control conditions. To isolate predictive neural mechanisms from general movement-related activity, we subtracted activity from corresponding stimulus-absent trials. Comparing self-touch with misaligned touch allowed us to refine the signal specific to predictive processing in self-touch and revealed greater pre-stimulus beta-band desynchronization and increased cerebellar-to-somatosensory connectivity before self-touch compared to misaligned touch. Our results provide the first evidence of predictive neural activity that shapes the sensory consequences of self-touch, offering insights into the mechanisms through which predictive models modulate somatosensory processing. Significance statementThe brain is thought to predict and attenuate the sensory consequences of self-generated actions, but neural evidence for prediction before sensation has been limited. Using magnetoencephalography, we show that self-touch attenuation is preceded by beta-band desynchronization and increased directed connectivity from the cerebellum to the primary somatosensory cortex. These effects cannot be attributed to movement, as they were reduced in a control condition with similar motor output but lower congruence between the action and tactile consequence, suggesting spatially specific predictive processing. Our study provides the first neural evidence of cerebellar influence on cortical sensory areas before self-touch. These pre-stimulus effects support forward models of sensorimotor control and shed new light on how the brain anticipates and modulates upcoming sensory input.

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bioRxiv2024

Methodological choices matter: A systematic comparison of TMS-EEG studies targeting the primary motor cortex

BackgroundTranscranial magnetic stimulation (TMS) triggers time-locked cortical activity that can be recorded with electroencephalography (EEG). Transcranial evoked potentials (TEPs) are widely used to probe brain responses to TMS. MethodsHere, we systematically reviewed 137 published experiments that studied TEPs elicited from TMS to the human primary motor cortex (M1) in healthy individuals to investigate the impact of methodological choices. We scrutinized prevalent methodological choices and assessed how consistently they were reported in published papers. We extracted amplitudes and latencies from reported TEPs and compared total cortical activation and specific TEP peaks and components. ResultsReporting of methodological details was overall sufficient, but some relevant information regarding the TMS settings and the recording and pre-processing of EEG data were missing in more than 25% of the included experiments. The published TEP latencies and amplitudes confirm the prototypical TEP waveform of M1, comprising distinct N15, P30, N45, P60, N100, and P180 peaks. However, variations in amplitude and latencies were evident across studies. Higher stimulation intensities were associated with overall larger TEP amplitudes. Active noise masking during TMS generally resulted in lower TEP amplitudes compared to no or passive masking but did not specifically impact those TEP peaks linked to long-latency sensory processing. Studies implementing independent component analysis (ICA) for artifact removal generally reported lower TEP amplitudes. ConclusionSome aspects of reporting practices could be improved in TEP studies to enable replication. Methodological choices, including TMS intensity and the use of noise masking or ICA, introduce systematic differences in reported TEP amplitudes. Further investigation into the significance of these and other methodological factors and their interactions is warranted.

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bioRxiv2023

Transcranial magnetic stimulation of primary motor cortex elicits a site-specific immediate transcranial evoked potential

BackgroundTranscranial evoked potentials (TEPs) measured via electroencephalography (EEG) are widely used to study the cortical responses to transcranial magnetic stimulation (TMS). Immediate transcranial evoked potentials (i-TEPs) have been obscured by pulse and muscular artifacts. Thus, the TEP peaks that are commonly reported have latencies that are too long to be caused by direct excitation of cortical neurons. MethodsIn 14 healthy individuals, we recorded i-TEPs evoked by a single biphasic TMS pulse targeting the primary motor hand area (M1HAND) or parietal or midline control sites. Sampling EEG at 50 kHz enabled us to reduce the duration of the TMS pulse artifact to a few milliseconds, while minor adjustments of the TMS coil tilt or position enabled us to avoid cranial muscular twitches during the experiment. ResultsWe observed an early positive EEG deflection starting after approx. 2 ms combined with a series of peaks with an inter-peak interval of [~]1.1-1.4 ms in electrodes overlying the stimulated sensorimotor region. This multi-peak i-TEP response was only evoked by TMS of the M1HAND region and was modified by changes in stimulation intensity and current direction. DiscussionSingle-pulse TMS of the M1HAND evokes an immediate local multi-peak response at the cortical site of stimulation. Our results suggest that the observed i-TEP patterns are genuine cortical responses evoked by TMS caused by synchronized excitation of pyramidal neurons in the targeted precentral cortex. This notion needs to be corroborated in future studies, including further investigations into the potential contribution of instrumental or physiological artifacts.

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bioRxiv2023

Cortex-wide topography of 1/f-exponent in Parkinson's disease

Parkinsons Disease causes progressive and debilitating changes to the brain as well as to the mind. While the diagnostic hallmark features are the characteristic movement-related symptoms, the disease also causes decline in sensory processing, cognitive, emotional performance and most patients develop dementia over time. The extent of symptoms and the brain-wide projections of neuromodulators such as dopamine suggest that many brain regions are simultaneously affected in Parkinsons disease. To characterise such disease-related and brain-wide changes in neuronal function, we performed a source level analysis of resting state magnetoencephalogram (MEG) from two groups: Parkinsons disease patients and healthy controls. Besides standard spectral analysis, we quantified the aperiodic component of the neural activity by fitting a power law ({kappa}/f {lambda}) to the MEG spectrum and then studied its relationship with age and UPDRS. Consistent with previous results, the most significant spectral changes were observed in the high theta/low alpha band (7-10 Hz) in all brain regions. Furthermore, analysis of the aperiodic part of the spectrum showed that, in all but frontal regions, {lambda} was significantly larger in Parkinsons disease patients than in control subjects. Our results indicate for the first time that Parkinsons disease is associated with significant changes in population activity across the whole neocortex. Surprisingly, even early sensory areas showed a significantly larger {lambda} in patients than in healthy controls. Moreover, {lambda} was not affected by the L-dopa medication. Finally, {lambda} was positively correlated with patient age but not with UPDRS-III (summary measure of motor symptoms clinical rating). Because {lambda} is closely associated excitationinhibition balance, our results propose new hypotheses about manifestation of Parkinsons disease in cortical networks.

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bioRxiv2021

Sharing individualised template MRI data for MEG source reconstruction: a solution for open data while keeping subject confidentiality

The increasing requirements for adoption of FAIR data management and sharing original research data from neuroimaging studies can be at odds with protecting the anonymity of the research participants due to the person-identifiable anatomical features in the data. We propose a solution to this dilemma for anatomical MRIs used in MEG source analysis. In MEG analysis, the channel-level data is reconstructed to the source-level using models derived from anatomical MRIs. Sharing data, therefore, requires sharing the anatomical MRI to replicate the analysis. The suggested solution is to replace the individual anatomical MRIs with individualised warped templates that can be used to carry out the MEG source analysis and that provide sufficient geometrical similarity to the original participants MRIs. First, we demonstrate how the individualised template warping can be implemented with one of the leading open-source neuroimaging analysis toolboxes. Second, we compare results from four different MEG source reconstruction methods performed with an individualised warped template to those using the participants original MRI. While the source reconstruction results are not numerically identical, there is a high similarity between the results for single dipole fits, dynamic imaging of coherent sources beamforming, and atlas-based virtual channel beamforming. There is a moderate similarity between minimum-norm estimates, as anticipated due to this method being anatomically constrained and dependent on the exact morphological features of the cortical sheet. We also compared the morphological features of the warped template to those of the original MRI. These showed a high similarity in grey matter volume and surface area, but a low similarity in the average cortical thickness and the mean folding index within cortical parcels. Taken together, this demonstrates that the results obtained by MEG source reconstruction can be preserved with the warped templates, whereas the anatomical and morphological fingerprint is sufficiently altered to protect the anonymity of research participants. In cases where participants consent to sharing anatomical MRI data, it remains preferable to share the original defaced data with an appropriate data use agreement. In cases where participants did not consent to share their MRIs, the individualised warped MRI template offers a good compromise in sharing data for reuse while retaining anonymity for those research participants.

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bioRxiv2020

Investigating motor preparatory processes and conscious volition using machine learning

BackgroundConscious volition is a broad term and is difficult to reduce to a single empirical paradigm. It encompasses many areas of cognition, including decision-making and empirical studies can be done on these components. This work follows on the seminal work of Libet et al. (1983) which focused on brain activity preceding motor activity and conscious awareness of the intention to move. Previous results have subsequently faced criticism, particularly methods used to average out EEG data over all the trials and the readiness potential not being present on an individual trial basis. This following study aims to address these criticisms. ObjectivesTo use machine learning to investigate brain activity preceding left/right hand movements with relation to conscious intent and motor action. MethodologyThe data collection involved the recreation of the Libet experiment, with electroencephalography (EEG) data being collected. An addition made in this study was the choice between "left" and "right" while observing the Libet clock to subjectively mark the moment of conscious awareness. Twenty-one participants were included (four females, all right-handed). A deep (machine) learning model known as a convolutional neural network (CNN) was used for the EEG data analysis. ResultsSubjectively reported conscious intent preceded the action by 108 ms. The CNN model was able to predict the decision "left" or "right" as early as 4.45 seconds before the action with a test accuracy of 98%. ConclusionThis study has shown motor preparatory processes start up to 4.45 seconds before conscious awareness of a decision to move.

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bioRxiv2019

Reduction of spontaneous cortical beta bursts in Parkinson’s disease is linked to symptom severity

Parkinsons disease is characterized by a gradual loss of dopaminergic neurons, which are associated with altered neuronal activity in the beta band (13-30 Hz). Assessing beta band activity typically involves transforming the time-series to get the power of the signal in the frequency-domain. Such transformation assumes that the time-series can be reduced to a combination of steady-state sine-and cosine waves. However, recent studies have suggested that this approach masks relevant biophysical features in the beta band activity--for example, that the beta band exhibits transient bursts of high-amplitude activity.\n\nIn an exploratory study we used magnetoencephalography (MEG) to record cortical beta band activity to characterize how spontaneous cortical beta bursts manifest in Parkinsons patients ON and OFF dopaminergic medication, and compare this to matched healthy controls. From three minutes of MEG data, we extracted the time-course of beta band activity from the sensorimotor cortex and characterized high-amplitude epochs in the signal to test if they exhibited burst like properties. We then compared the rate, duration, inter-burst interval, and peak amplitude of the high-amplitude epochs between the Parkinsons patients and healthy controls.\n\nOur results show that Parkinsons patients OFF medication had a 6-17% lower beta bursts rate compared to healthy controls, while both the duration and the amplitude of the bursts were the same for Parkinsons patients and healthy controls and medicated state of the Parkinsons patients. These data thus support the view that beta bursts are fundamental underlying features of beta band activity, and show that changes in cortical beta band power in PD can be explained primarily by changes in the underlying burst rate. Importantly, our results also revealed a relationship between beta bursts rate and motor symptom severity in PD: a lower burst rate scaled with increased in severity of bradykinesia and postural/kinetic tremor. Beta burst rate might thus serve as neuromarker for Parkinsons disease that can help in the assessment of symptom severity in Parkinsons disease or evaluate treatment effectiveness.

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bioRxiv2018

Attenuated post-movement beta rebound in Parkinson’s disease to proprioceptive afferent feedback

Motor symptoms are defining traits in the diagnosis of Parkinsons disease (PD). A crucial component in motor function and control of movements is the integration of efferent signals from the motor network to the peripheral motor system, and afferent proprioceptive sensory feedback. Previous studies have indicated abnormal movement-related cortical oscillatory activity in PD, but the role of the proprioceptive afference on abnormal oscillatory activity in PD has not been elucidated. In the present study, we examine the role of proprioception by studying the cortical processing of proprioceptive stimulation in PD patients, ON/OFF levodopa medication, as compared to that of healthy controls (HC). We used a proprioceptive stimulator that generated precisely controlled passive movements of the index finger and measured the induced cortical oscillatory responses following the proprioceptive stimulation using magnetoencephalography (MEG). Both PD patients and HC showed a typical initial mu/beta-band (8-30 Hz) desynchronization during the passive movement. However, the subsequent beta rebound after the passive movement that was apparent in HC was much attenuated and almost absent in PD patients. Furthermore, we found no difference in the degree of beta rebound attenuation between patients ON and OFF levodopa medication. Our results hence demonstrate a disease-related deterioration in cortical processing of proprioceptive afference in PD, and further suggest that such disease-related loss of proprioceptive function is due to processes outside the dopaminergic system affected by levodopa medication.

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