Jan-Mathijs Schoffelen

FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data

This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages.

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.

Prestimulus Oscillatory Activity in the Alpha Band Predicts Visual Discrimination Ability

Although the resting and baseline states of the human electroencephalogram and magnetoencephalogram (MEG) are dominated by oscillations in the alpha band (∼10 Hz), the functional role of these oscillations remains unclear. In this study we used MEG to investigate how spontaneous oscillations in humans presented before visual stimuli modulate visual perception. Subjects had to report if there was a subtle difference in gray levels between two superimposed presented discs. We then compared the prestimulus brain activity for correctly (hits) versus incorrectly (misses) identified stimuli. We found that visual discrimination ability decreased with an increase in prestimulus alpha power. Given that reaction times did not vary systematically with prestimulus alpha power changes in vigilance are not likely to explain the change in discrimination ability. Source reconstruction using spatial filters allowed us to identify the brain areas accounting for this effect. The dominant sources modulating visual perception were localized around the parieto-occipital sulcus. We suggest that the parieto-occipital alpha power reflects functional inhibition imposed by higher level areas, which serves to modulate the gain of the visual stream.

Attentional stimulus selection through selective synchronization between monkey visual areas.

A central motif in neuronal networks is convergence, linking several input neurons to one target neuron. In visual cortex, convergence renders target neurons responsive to complex stimuli. Yet, convergence typically sends multiple stimuli to a target, and the behaviorally relevant stimulus must be selected. We used two stimuli, activating separate electrocorticographic V1 sites, and both activating an electrocorticographic V4 site equally strongly. When one of those stimuli activated one V1 site, it gamma synchronized (60-80 Hz) to V4. When the two stimuli activated two V1 sites, primarily the relevant one gamma synchronized to V4. Frequency bands of gamma activities showed substantial overlap containing the band of interareal coherence. The relevant V1 site had its gamma peak frequency 2-3 Hz higher than the irrelevant V1 site and 4-6 Hz higher than V4. Gamma-mediated interareal influences were predominantly directed from V1 to V4. We propose that selective synchronization renders relevant input effective, thereby modulating effective connectivity.

Visual areas exert feedforward and feedback influences through distinct frequency channels

Visual cortical areas subserve cognitive functions by interacting in both feedforward and feedback directions. While feedforward influences convey sensory signals, feedback influences modulate feedforward signaling according to the current behavioral context. We investigated whether these interareal influences are subserved differentially by rhythmic synchronization. We correlated frequency-specific directed influences among 28 pairs of visual areas with anatomical metrics of the feedforward or feedback character of the respective interareal projections. This revealed that in the primate visual system, feedforward influences are carried by theta-band (∼ 4 Hz) and gamma-band (∼ 60-80 Hz) synchronization, and feedback influences by beta-band (∼ 14-18 Hz) synchronization. The functional directed influences constrain a functional hierarchy similar to the anatomical hierarchy, but exhibiting task-dependent dynamic changes in particular with regard to the hierarchical positions of frontal areas. Our results demonstrate that feedforward and feedback signaling use distinct frequency channels, suggesting that they subserve differential communication requirements.

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].

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.

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 systems 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.

Selective Movement Preparation Is Subserved by Selective Increases in Corticomuscular Gamma-Band Coherence

Local groups of neurons engaged in a cognitive task often exhibit rhythmically synchronized activity in the gamma band, a phenomenon that likely enhances their impact on downstream areas. The efficacy of neuronal interactions may be enhanced further by interareal synchronization of these local rhythms, establishing mutually well timed fluctuations in neuronal excitability. This notion suggests that long-range synchronization is enhanced selectively for connections that are behaviorally relevant. We tested this prediction in the human motor system, assessing activity from bilateral motor cortices with magnetoencephalography and corresponding spinal activity through electromyography of bilateral hand muscles. A bimanual isometric wrist extension task engaged the two motor cortices simultaneously into interactions and coherence with their respective corresponding contralateral hand muscles. One of the hands was cued before each trial as the response hand and had to be extended further to report an unpredictable visual go cue. We found that, during the isometric hold phase, corticomuscular coherence was enhanced, spatially selective for the corticospinal connection that was effectuating the subsequent motor response. This effect was spectrally selective in the low gamma-frequency band (40–47 Hz) and was observed in the absence of changes in motor output or changes in local cortical gamma-band synchronization. These findings indicate that, in the anatomical connections between the cortex and the spinal cord, gamma-band synchronization is a mechanism that may facilitate behaviorally relevant interactions between these distant neuronal groups.

Neural mechanisms of communicative innovation

Human referential communication is often thought as coding–decoding a set of symbols, neglecting that establishing shared meanings requires a computational mechanism powerful enough to mutually negotiate them. Sharing the meaning of a novel symbol might rely on similar conceptual inferences across communicators or on statistical similarities in their sensorimotor behaviors. Using magnetoencephalography, we assess spectral, temporal, and spatial characteristics of neural activity evoked when people generate and understand novel shared symbols during live communicative interactions. Solving those communicative problems induced comparable changes in the spectral profile of neural activity of both communicators and addressees. This shared neuronal up-regulation was spatially localized to the right temporal lobe and the ventromedial prefrontal cortex and emerged already before the occurrence of a specific communicative problem. Communicative innovation relies on neuronal computations that are shared across generating and understanding novel shared symbols, operating over temporal scales independent from transient sensorimotor behavior.