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Cerebello-thalamo-cortical loops play a major role in the emergence of pathological tremors and voluntary rhythmic movements. It is unclear whether these loops differ anatomically or functionally in different types of tremor. We compared age- and sex-matched groups of patients with Parkinson's disease or essential tremor and healthy controls (n = 34 per group). High-density 256-channel EEG and multi-channel EMG from extensor and flexor muscles of both wrists were recorded simultaneously while extending the hands against gravity with the forearms supported. Tremor was thereby recorded from patients, and voluntarily mimicked tremor was recorded from healthy controls. Tomographic maps of EEG-EMG coherence were constructed using a beamformer algorithm coherent source analysis. The direction and strength of information flow between different coherent sources were estimated using time-resolved partial-directed coherence analyses. Tremor severity and motor performance measures were correlated with connection strengths between coherent sources. The topography of oscillatory coherent sources in the cerebellum differed significantly among the three groups, but the cortical sources in the primary sensorimotor region and premotor cortex were not significantly different. The cerebellar and cortical source combinations matched well with known cerebello-thalamo-cortical connections derived from functional MRI resting state analyses according to the Buckner-atlas. The cerebellar sources for Parkinson's tremor and essential tremor mapped primarily to primary sensorimotor cortex, but the cerebellar source for mimicked tremor mapped primarily to premotor cortex. Time-resolved partial-directed coherence analyses revealed activity flow mainly from cerebellum to sensorimotor cortex in Parkinson's tremor and essential tremor and mainly from cerebral cortex to cerebellum in mimicked tremor. EMG oscillation flowed mainly to the cerebellum in mimicked tremor, but oscillation flowed mainly from the cerebellum to EMG in Parkinson's and essential tremor. The topography of cerebellar involvement differed among Parkinson's, essential and mimicked tremors, suggesting different cerebellar mechanisms in tremorogenesis. Indistinguishable areas of sensorimotor cortex and premotor cerebral cortex were involved in all three tremors. Information flow analyses suggest that sensory feedback and cortical efferent copy input to cerebellum are needed to produce mimicked tremor, but tremor in Parkinson's disease and essential tremor do not depend on these mechanisms. Despite the subtle differences in cerebellar source topography, we found no evidence that the cerebellum is the source of oscillation in essential tremor or that the cortico-bulbo-cerebello-thalamocortical loop plays different tremorogenic roles in Parkinson's and essential tremor. Additional studies are needed to decipher the seemingly subtle differences in cerebellocortical function in Parkinson's and essential tremors.

Recently, interest has been growing to understand the underlying dynamic directional relationship between simultaneously activated regions of the brain during motor task performance. Such directionality analysis (or effective connectivity analysis), based on non-invasive electrophysiological (electroencephalography-EEG) and hemodynamic (functional near infrared spectroscopy-fNIRS; and functional magnetic resonance imaging-fMRI) neuroimaging modalities can provide an estimate of the motor task-related information flow from one brain region to another. Since EEG, fNIRS and fMRI modalities achieve different spatial and temporal resolutions of motor-task related activation in the brain, the aim of this study was to determine the effective connectivity of cortico-cortical sensorimotor networks during finger movement tasks measured by each neuroimaging modality. Nine healthy subjects performed right hand finger movement tasks of different complexity (simple finger tapping-FT, simple finger sequence-SFS, and complex finger sequence-CFS). We focused our observations on three cortical regions of interest (ROIs), namely the contralateral sensorimotor cortex (SMC), the contralateral premotor cortex (PMC) and the contralateral dorsolateral prefrontal cortex (DLPFC). We estimated the effective connectivity between these ROIs using conditional Granger causality (GC) analysis determined from the time series signals measured by fMRI (blood oxygenation level-dependent-BOLD), fNIRS (oxygenated-O2Hb and deoxygenated-HHb hemoglobin), and EEG (scalp and source level analysis) neuroimaging modalities. The effective connectivity analysis showed significant bi-directional information flow between the SMC, PMC, and DLPFC as determined by the EEG (scalp and source), fMRI (BOLD) and fNIRS (O2Hb and HHb) modalities for all three motor tasks. However the source level EEG GC values were significantly greater than the other modalities. In addition, only the source level EEG showed a significantly greater forward than backward information flow between the ROIs. This simultaneous fMRI, fNIRS and EEG study has shown through independent GC analysis of the respective time series that a bi-directional effective connectivity occurs within a cortico-cortical sensorimotor network (SMC, PMC and DLPFC) during finger movement tasks.

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Electroencephalography (EEG) and magnetoencephalography (MEG) are the two modalities for measuring neuronal dynamics at a millisecond temporal resolution. Different source analysis methods, to locate the dipoles in the brain from which these dynamics originate, have been readily applied to both modalities alone. However, direct comparisons and possible advantages of combining both modalities have rarely been assessed during voluntary movements using coherent source analysis. In the present study, the cortical and sub-cortical network of coherent sources at the finger tapping task frequency (2–4 Hz) and the modes of interaction within this network were analysed in 15 healthy subjects using a beamformer approach called the dynamic imaging of coherent sources (DICS) with subsequent source signal reconstruction and renormalized partial directed coherence analysis (RPDC). MEG and EEG data were recorded simultaneously allowing the comparison of each of the modalities separately to that of the combined approach. We found the identified network of coherent sources for the finger tapping task as described in earlier studies when using only the MEG or combined MEG+EEG whereas the EEG data alone failed to detect single sub-cortical sources. The signal-to-noise ratio (SNR) level of the coherent rhythmic activity at the tapping frequency in MEG and combined MEG+EEG data was significantly higher than EEG alone. The functional connectivity analysis revealed that the combined approach had more active connections compared to either of the modalities during the finger tapping (FT) task. These results indicate that MEG is superior in the detection of deep coherent sources and that the SNR seems to be more vital than the sensitivity to theoretical dipole orientation and the volume conduction effect in the case of EEG.

The assessment of effects associated with cognitive impairment using electroencephalography (EEG) power mapping allows the visualization of frequency-band specific local changes in oscillatory activity. In contrast, measures of coherence and dynamic source synchronization allow for the study of functional and effective connectivity, respectively. Yet, these measures have rarely been assessed in parallel in the context of mild cognitive impairment (MCI) and furthermore it has not been examined if they are related to risk factors of Alzheimer’s disease (AD) such as amyloid deposition and apolipoprotein ε4 (ApoE) allele occurrence. Here, we investigated functional and directed connectivities with Renormalized Partial Directed Coherence (RPDC) in 17 healthy controls (HC) and 17 participants with MCI. Participants underwent ApoE-genotyping and Pittsburgh compound B positron emission tomography (PiB-PET) to assess amyloid deposition. We observed lower spectral source power in MCI in the alpha and beta bands. Coherence was stronger in HC than MCI across different neuronal sources in the delta, theta, alpha, beta and gamma bands. The directed coherence analysis indicated lower information flow between fronto-temporal (including the hippocampus) sources and unidirectional connectivity in MCI. In MCI, alpha and beta RPDC showed an inverse correlation to age and gender; global amyloid deposition was inversely correlated to alpha coherence, RPDC and beta and gamma coherence. Furthermore, the ApoE status was negatively correlated to alpha coherence and RPDC, beta RPDC and gamma coherence. A classification analysis of cognitive state revealed the highest accuracy using EEG power, coherence and RPDC as input. For this small but statistically robust (Bayesian power analyses) sample, our results suggest that resting EEG related functional and directed connectivities are sensitive to the cognitive state and are linked to ApoE and amyloid burden.

We show that the oscillating cerebral networks underlying classical essential tremor and aging-related tremor differ, suggesting a pathophysiological difference.