Improving the interpretability of all-to-all pairwise source connectivity analysis in MEG with nonhomogeneous smoothing

Studying the interaction between brain regions is important to increase our understanding of brain function. Magnetoencephalography (MEG) is well suited to investigate brain connectivity, because it provides measurements of activity of the whole brain at very high temporal resolution. Typically, brain activity is reconstructed from the sensor recordings with an inverse method such as a beamformer, and subsequently a connectivity metric is estimated between predefined reference regions-of-interest (ROIs) and the rest of the source space. Unfortunately, this approach relies on a robust estimate of the relevant reference regions and on a robust estimate of the activity in those reference regions, and is not generally applicable to a wide variety of cognitive paradigms. Here, we investigate the possibility to perform all-to-all pairwise connectivity analysis, thus removing the need to define ROIs. Particularly, we evaluate the effect of nonhomogeneous spatial smoothing of differential connectivity maps. This approach is inspired by the fact that the spatial resolution of source reconstructions is typically spatially nonhomogeneous. We use this property to reduce the spatial noise in the cerebro-cerebral connectivity map, thus improving interpretability. Using extensive data simulations we show a superior detection rate and a substantial reduction in the number of spurious connections. We conclude that nonhomogeneous spatial smoothing of cerebro-cerebral connectivity maps could be an important improvement of the existing analysis tools to study neuronal interactions noninvasively.

Functional integration within the human pain system as revealed by Granger causality

Pain is a complex experience subserved by an extended network of brain areas. However, the functional integration among these brain areas, i.e., how they interact and communicate to generate a coherent pain percept and an adequate behavioral response is largely unknown. Here, we used magnetoencephalography to investigate functional integration among pain-related cortical activations in terms of Granger causality and compared it with tactile-related activations. The results show causal influences of primary somatosensory cortex on secondary somatosensory cortex for tactile-related but not for pain-related activations, which supports the proposition of a partially parallel organization of pain processing in the human brain. Furthermore, during a simple reaction time task, the strength of causal influences between somatosensory areas but not the latencies between activations correlated significantly with the speed of reaction times. These findings show how the analysis of functional integration complements traditional analyses of electrophysiological data and provides novel and behaviorally relevant information about the organization of the human pain system.

Source connectivity analysis with MEG and EEG

Interactions between functionally specialized brain regions are crucial for normal brain function. Magnetoencephalography (MEG) and electroencephalography (EEG) are techniques suited to capture these interactions, because they provide whole head measurements of brain activity in the millisecond range. More than one sensor picks up the activity of an underlying source. This field spread severely limits the utility of connectivity measures computed directly between sensor recordings. Consequentially, neuronal interactions should be studied on the level of the reconstructed sources. This article reviews several methods that have been applied to investigate interactions between brain regions in source space. We will mainly focus on the different measures used to quantify connectivity, and on the different strategies adopted to identify regions of interest. Despite various successful accounts of MEG and EEG source connectivity, caution with respect to the interpretation of the results is still warranted. This is due to the fact that effects of field spread can never be completely abolished in source space. However, in this very exciting and developing field of research this cautionary note should not discourage researchers from further investigation into the connectivity between neuronal sources.

Imaging the human motor system's beta-band synchronization during isometric contraction

Rhythmic synchronization likely subserves interactions among neuronal groups. One of the best studied rhythmic synchronization phenomena in the human nervous system is the beta-band (15-30 Hz) synchronization in the motor system. In this study, we imaged structures across the human brain that are synchronized to the motor system's beta rhythm. We recorded whole-head magnetoencephalograms (MEG) and electromyograms (EMG) of left/right extensor carpi radialis muscle during left/right wrist extension. We analyzed coherence, on the one hand between the EMG and neuronal sources in the brain, and on the other hand between different brain sources, using a spatial filtering approach. Cortico-muscular coherence analysis revealed a spatial maximum of coherence to the muscle in motor cortex contralateral to the muscle in accordance with earlier findings. Moreover, by applying a two-dipole source model, we unveiled significantly coherent clusters of voxels in the ipsilateral cerebellar hemisphere and ipsilateral cerebral motor regions. The spatial pattern of coherence to the right and left arm EMG was roughly mirror reversed across the midline, in agreement with known physiology. Subsequently, we analyzed the brain-wide pattern of beta-band coherence to the motor cortex contralateral to the contracting muscle. This analysis did not reveal any convincing pattern. Because the prior cortico-muscular analysis had demonstrated the expected pattern in our data, this negative finding demonstrates a current limitation of the applied method for cortico-cortical coherence analysis. We conclude that during an isometric muscle contraction, several distributed brain regions form a brain-wide beta-band network for motor control.

Modulation of neuronal interactions through neuronal synchronization

Brain processing depends on the interactions between neuronal groups. Those interactions are governed by the pattern of anatomical connections and by yet unknown mechanisms that modulate the effective strength of a given connection. We found that the mutual influence among neuronal groups depends on the phase relation between rhythmic activities within the groups. Phase relations supporting interactions between the groups preceded those interactions by a few milliseconds, consistent with a mechanistic role. These effects were specific in time, frequency, and space, and we therefore propose that the pattern of synchronization flexibly determines the pattern of neuronal interactions.

Nonparametric statistical testing of coherence differences

Many important questions in neuroscience are about interactions between neurons or neuronal groups. These interactions are often quantified by coherence, which is a frequency-indexed measure that quantifies the extent to which two signals exhibit a consistent phase relation. In this paper, we consider the statistical testing of the difference between coherence values observed in two experimental conditions. We pay special attention to problems induced by (1) unequal sample sizes and (2) the fact that coherence is typically evaluated at a large number of frequency bins and between large numbers of pairs of neurons or neuronal groups (the multiple comparisons problem). We show that nonparametric statistical tests provide convincing and elegant solutions for both problems. We also show that these tests allow to incorporate biophysically motivated constraints in the test statistic, which may drastically increase the sensitivity of the test. Finally, we explain why the nonparametric test is formally correct. This means that we formulate a null hypothesis (identical probability distribution in the different experimental conditions) and show that the nonparametric test controls the false alarm rate under this null hypothesis. The proposed methodology is illustrated by analyses of data collected in a study on cortico-spinal coherence [Schoffelen JM, Oostenveld R, Fries P. Neuronal coherence as a mechanism of effective corticospinal interaction. Science 2005;308(5718):111-3].

Oscillatory activity in human parietal and occipital cortex shows hemispheric lateralization and memory effects in a delayed double-step saccade task

We applied magnetoencephalography (MEG) to record oscillatory brain activity from human subjects engaged in planning a double-step saccade. In the experiments, subjects (n = 8) remembered the locations of 2 sequentially flashed targets (each followed by a 2-s delay), presented in either the left or right visual hemifield, and then made saccades to the 2 locations in sequence. We examined changes in spectral power in relation to target location (left or right) and memory load (one or two targets), excluding error trials based on concurrent eye tracking. During the delay period following the first target, power in the alpha (8-12 Hz) and beta (13-25 Hz) bands was significantly suppressed in the hemisphere contralateral to the target. When the second target was presented, there was a further suppression in the alpha- and beta-band power over both hemispheres. In this period, the same sensors also showed contralateral power enhancements in the gamma band (60-90 Hz), most significantly prior to the initiation of the saccades. Adaptive spatial filtering techniques localized the neural sources of the directionally selective power changes in parieto-occipital areas. These results provide further support for a topographic organization for delayed saccades in human parietal and occipital cortex.

Comparing spectra and coherences for groups of unequal size

Spectra and coherences are standard measures of association within and between time series. These measures have several advantages over their time-domain counterparts, not the least of which is the ability to derive and estimate confidence intervals. However, comparing spectra and coherences between two groups of observation is a problem that has not received much attention. This problem is important in neuroscience since it is often of great interest to determine whether the estimates differ between distinct experimental/behavioral conditions. Here we propose one approach to this problem. Based on the known distributional properties of spectral and coherence estimates, we derive a test for equality of two spectral or coherence estimates. The test is applicable to unequal sample sizes. We also derive jackknifed estimates of the variance of the proposed test statistic. We suggest that comparing the estimates obtained from the jackknife procedure with the theoretical estimates provides a robust means of determining whether the data in question shows non-Gaussian or non-stationary behavior. Finally, we present applications of the method to simulated and real data.

Localizing human visual gamma-band activity in frequency, time and space

Neuronal gamma-band (30-100 Hz) synchronization subserves fundamental functions in neuronal processing. However, different experimental approaches differ widely in their success in finding gamma-band activity. We aimed at linking animal and human studies of gamma-band activity and at preparing optimized methods for an in-depth investigation of the mechanisms and functions of gamma-band activity and gamma-band coherence in humans. In the first step described here, we maximized the signal-to-noise ratio with which we can observe visually induced gamma-band activity in human magnetoencephalographic recordings. We used a stimulus and task design that evoked strong gamma-band activity in animals and combined it with multi-taper methods for spectral analysis and adaptive spatial filtering for source analysis. With this approach, we found human visual gamma-band activity very reliably across subjects and across multiple recording sessions of a given subject. While increases in gamma-band activity are typically accompanied by decreases in alpha- and beta-band activity, the gamma-band enhancement was often the spectral component with the highest signal-to-noise ratio. Furthermore, some subjects demonstrated two clearly separate visually induced gamma bands, one around 40 Hz and another between 70 and 80 Hz. Gamma-band activity was sustained for the entire stimulation period, which was up to 3 s. The sources of gamma-band activity were in the calcarine sulcus in all subjects. The results localize human visual gamma-band activity in frequency, time and space and the described methods allow its further investigation with great sensitivity.

Neuronal coherence as a mechanism of effective corticospinal interaction

Neuronal groups can interact with each other even if they are widely separated. One group might modulate its firing rate or its internal oscillatory synchronization to influence another group. We propose that coherence between two neuronal groups is a mechanism of efficient interaction, because it renders mutual input optimally timed and thereby maximally effective. Modulations of subjects' readiness to respond in a simple reaction-time task were closely correlated with the strength of gamma-band (40 to 70 hertz) coherence between motor cortex and spinal cord neurons. This coherence may contribute to an effective corticospinal interaction and shortened reaction times.