Chronotopic maps in human supplementary motor area

Time is a fundamental dimension of everyday experiences. We can unmistakably sense its passage and adjust our behavior accordingly. Despite its ubiquity, the neuronal mechanisms underlying the capacity to perceive time remains unclear. Here, in two experiments using ultrahigh-field 7-Tesla (7T) functional magnetic resonance imaging (fMRI), we show that in the medial premotor cortex (supplementary motor area [SMA]) of the human brain, neural units tuned to different durations are orderly mapped in contiguous portions of the cortical surface so as to form chronomaps. The response of each portion in a chronomap is enhanced by neighboring durations and suppressed by nonpreferred durations represented in distant portions of the map. These findings suggest duration-sensitive tuning as a possible neural mechanism underlying the recognition of time and demonstrate, for the first time, that the representation of an abstract feature such as time can be instantiated by a topographical arrangement of duration-sensitive neural populations.

Physiological noise in human cerebellar fMRI

Denis Butticaz, João Pedro Forjaco Jorge, Rolf Gruetter, Wietske Van der Zwaag

Objectives To compare physiological noise contributions in cerebellar and cerebral regions of interest in high-resolution functional magnetic resonance imaging (fMRI) data acquired at 7T, to estimate the need for physiological noise removal in cerebellar fMRI. Materials and methods Signal fluctuations in high resolution (1 mm isotropic) 7T fMRI data were attributed to one of the following categories: task-induced BOLD changes, slow drift, signal changes correlated with the cardiac and respiratory cycles, signal changes related to the cardiac rate and respiratory volume per unit of time or other. R2adj values for all categories were compared across regions of interest. Results In this high-resolution data, signal fluctuations related to the phase of the cardiac cycle and cardiac rate were shown to be significant, but comparable between cerebellar and cerebral regions of interest. However, respiratory related signal fluctuations were increased in the cerebellar regions, with explained variances that were up to 80 % higher than for the primary motor cortex region. Conclusion Even at a millimetre spatial resolution, significant correlations with both cardiac and respiratory RETROICOR components were found in all healthy volunteer data. Therefore, physiological noise correction is highly likely to improve the temporal signal-to-noise ratio (SNR) for cerebellar fMRI at 7T, even at high spatial resolution.

Springer Verlag2015

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

Friedhelm Christoph Hummel

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.

Elsevier2016

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

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

Friedhelm Christoph Hummel

Elsevier2016