Dynamic causal modelling of EEG and fMRI to characterize network architectures in a simple motor task

Dynamic causal modelling (DCM) has extended the understanding of brain network dynamics in a variety of functional systems. In the motor system, DCM studies based on functional magnetic resonance imaging (fMRI) or on magneto-/electroencephalography (M/EEG) have demonstrated movement-related causal information flow from secondary to primary motor areas and have provided evidence for nonlinear cross-frequency interactions among motor areas. The present study sought to investigate to what extent fMRI- and EEG-based DCM might provide complementary and synergistic insights into neuronal network dynamics. Both modalities share principal similarities in the formulation of the DCM. Thus, we hypothesized that DCM based on induced EEG responses (DCM-IR) and on fMRI would reveal congruent task-dependent network dynamics. Brain electrical (63-channel surface EEG) and Blood Oxygenation Level Dependent (BOLD) signals were recorded in separate sessions from 14 healthy participants performing simple isometric right and left hand grips. DCM-IR and DCM-fMRI were used to estimate coupling parameters modulated by right and left hand grips within a core motor network of six regions comprising bilateral primary motor cortex (M1), ventral premotor cortex (PMv) and supplementary motor area (SMA). We found that DCM-fMRI and DCM-IR similarly revealed significant grip-related increases in facilitatory coupling between SMA and M1 contralateral to the active hand. A grip-dependent interhemispheric reciprocal inhibition between M1 bilaterally was only revealed by DCM-fMRI but not by DCM-IR. Frequency-resolved coupling analysis showed that the information flow from contralateral SMA to M1 was predominantly a linear alpha-to-alpha (9-13Hz) interaction. We also detected some cross-frequency coupling from SMA to contralateral M1, i.e., between lower beta (14-21Hz) at the SMA and higher beta (22-30Hz) at M1 during right hand grip and between alpha (9-13Hz) at SMA and lower beta (14-21Hz) at M1 during left hand grip. In conclusion, the strategy of informing EEG source-space configurations with fMRI-derived coordinates, cross-validating basic connectivity maps and analysing frequency coding allows for deeper insight into the motor network architecture of the human brain. The present results provide evidence for the robustness of non-invasively measured causal information flow from secondary motor areas such as SMA towards M1 and further contribute to the validation of the methodological approach of multimodal DCM to explore human network dynamics.

Spontaneous locally restricted EEG alpha activity determines cortical excitability in the motor cortex

Friedhelm Christoph Hummel

There is growing interest in the functional meaning of rhythmical brain activity. For oscillatory brain activity around 10 Hz in the human electroencephalogram (EEG) it is discussed whether it is associated with the level of cortical excitation. However, it is not clear whether the relation between 10 Hz EEG oscillatory activity and cortical excitability is a global, locally very unspecific phenomenon or whether focal 10 Hz oscillations in the human brain are a highly specific correlate of the cortical excitation level. To determine this open question, multichannel EEG was combined with transcranial magnetic stimulation (TMS) applied to the primary motor cortex in this study. The present data showed that a motor evoked potential was elicited more easily when alpha power immediately preceding the magnetic pulse was low, and vice versa. Interestingly, this effect was only found for very local EEG alpha activity at sites overlying the cortical motor areas to which the TMS pulses were applied. This was verified using source localization in 3D space. These data provide evidence that the magnitude of motor cortical excitability is determined by the amount of topographically specific alpha oscillations in the sensorimotor cortex.

Elsevier2009

Inhibitory control of acquired motor programmes in the human brain

Friedhelm Christoph Hummel

An important basis of skilled human behaviour is the appropriate retrieval of acquired and memorized motor programmes ('motor memory traces'). Appropriate retrieval is warranted if motor programmes are only activated if necessary and are, probably more often, inhibited if required by the context of a given situation. It is unknown how this type of inhibition is accomplished in the brain. We studied context-dependent modulation of motor memory traces in 18 volunteers and six patients with focal dystonia. Cortical function was assessed with transcranial magnetic stimulation over the primary motor cortex (M1) and with task-related analysis of oscillatory EEG activity. An activation (ACT) and inhibition (INH) condition were compared. In both, visual cues were presented at 1/s. In ACT, subjects had to respond to these cues with individual finger movements as learned in a preceding training session. In INH, subjects had to observe the cues without retrieval of motor responses. During INH, inhibitory control of the motor memory trace was confirmed by significant amplitude reduction of motor evoked potentials (MEPs) compared with baseline. This was accompanied by a significant increase of 11-13 Hz oscillatory activity over the sensorimotor areas during INH. During active retrieval of the motor memory traces, the reverse was true (increased MEP amplitudes, decreased oscillatory 11-13 Hz activity). In a small sample of dystonic patients (n = 6), the increase of 11-13 Hz oscillatory activity during INH was consistently absent. The present data demonstrate for the first time cortical correlates of appropriate, context-dependent inhibition of motor memory traces. We propose that focal increases of oscillatory activity are instrumental for inhibitory control at the cortical level. This concept is supported by the preliminary observations in dystonic patients who are known to have deficits of inhibitory motor control and in whom these context-dependent focal increases of oscillatory activity were absent.

Oxford University Press2002

Determining patterns of post-stroke motor recovery through longitudinal multimodal MRI: A step towards patient stratification

Julia Brügger

Motivated by the need for a better understanding of post-stroke recovery and new biomarkers to improve stroke patient stratification and outcomes, this thesis investigated structure-function coupling and its role in post-stroke recovery. Furthermore, in order to increase data comparability between sessions and centers (a critical challenge in contemporary clinical research), this thesis assessed the reproducibility of microstructure-informed structural connectivity measures in a multi-center dataset.Stroke is one of the major sources of permanent impairment, frequently of motor origin. However the clinical picture is very heterogeneous: patients show divergent courses of recovery and the underlying mechanisms are still unclear. In addition, current treatments still have limited success and are restricted to a 'one-fits-all' approach, not considering the individual patient's phenotype. As efforts to stratify patients based on structural or functional biomarkers are still needed, we chose to investigate the potential of a multimodal biomarker, the Structural Decoupling Index (SDI) (Preti & Van De Ville, 2019b), a new metric assessing the structure-function coupling strength in the brain. The first part (Studies 1 and 2) of this thesis investigates the potential of the SDI as a biomarker. In Study 1, the goals were to evaluate the feasibility of applying the SDI on an individual level in healthy older adults and to investigate the effect of an acute stroke on it. Consistent with the literature, we found a network gradient of SDI in healthy older adults, from high coupling in lower-level sensory areas, to low coupling in higher-level cognitive areas. This confirmed the applicability of SDI on an individual level. Furthermore, we showed that stroke impacts the SDI, with a higher decoupling on the ipsi- compared to the contralesional side, and with network-specific effects in RH stroke patients. In Study 2, the goal was to see whether the SDI evolved over time post-stroke and whether it links to behavior. The longitudinal analysis revealed differential network effects of stroke at T1 and T3. Furthermore, we showed that impairment in cognitive and psychological behavioral domains significantly correlates with variations in SDI in a number of key areas including motor regions (e.g., primary motor cortex) and that the brain pattern associated to behavior changes between T1 and T2. Surprisingly, motor performance did not explain variability in key motor areas (e.g., primary motor cortex). The link between post-stroke behavioral performance and SDI underlines its potential clinical relevance.Driven by the quest for more reproducible analysis pipelines in the context of longitudinal and clinical studies, the second part of this thesis (Study 3) addressed the subject-specific reproducibility and repeatability of microstructure-informed tractography. Through a multi-center study, we demonstrated its high reproducibility and subject-specificity, and we found evidence for increased biological accuracy. My thesis made a contribution by showing that the SDI is sensitive to pathophysiological changes that occur following a stroke and that it links to clinically relevant behavioral measures. In addition, it confirms the reproducibility and subject-specificity of microstructure-informed tractography. Together, my findings pave the way towards patient stratification and more personalized treatments in stroke rehabilitation.

EPFL2022

Inhibitory control of acquired motor programmes in the human brain

Friedhelm Christoph Hummel

Oxford University Press2002

Determining patterns of post-stroke motor recovery through longitudinal multimodal MRI: A step towards patient stratification

Julia Brügger

EPFL2022