Nonlinear interactions of high-frequency oscillations in the human somatosensory system

Further characterisation of late somatosensory evoked potentials using electroencephalogram and magnetoencephalogram source imaging

Beside the well-documented involvement of secondary somatosensory area, the cortical network underlying late somatosensory evoked potentials (P60/N60 and P100/N100) is still unknown. Electroencephalogram and magnetoencephalogram source imaging were performed to further investigate the origin of the brain cortical areas involved in late somatosensory evoked potentials, using sensory inputs of different strengths and by testing the correlation between cortical sources. Simultaneous high-density electroencephalograms and magnetoencephalograms were performed in 19 participants, and electrical stimulation was applied to the median nerve (wrist level) at intensity between 1.5 and 9 times the perceptual threshold. Source imaging was undertaken to map the stimulus-induced brain cortical activity according to each individual brain magnetic resonance imaging, during three windows of analysis covering early and late somatosensory evoked potentials. Results for P60/N60 and P100/N100 were compared with those for P20/N20 (early response). According to literature, maximal activity during P20/N20 was found in central sulcus contralateral to stimulation site. During P60/N60 and P100/N100, activity was observed in contralateral primary sensorimotor area, secondary somatosensory area (on both hemispheres) and premotor and multisensory associative cortices. Late responses exhibited similar characteristics but different from P20/N20, and no significant correlation was found between early and late generated activities. Specific clusters of cortical activities were activated with specific input/output relationships underlying early and late somatosensory evoked potentials. Cortical networks, partly common to and distinct from early somatosensory responses, contribute to late responses, all participating in the complex somatosensory brain processing.

Primary somatosensory contextual modulation is encoded by oscillation frequency change

OBJECTIVE

This study characterized thalamo-cortical communication by assessing the effect of context-dependent modulation on the very early somatosensory evoked high-frequency oscillations (HF oscillations).

METHODS

We applied electrical stimuli to the median nerve together with an auditory oddball paradigm, presenting standard and deviant target tones representing differential cognitive contexts to the constantly repeated electrical stimulation. Median nerve stimulation without auditory stimulation served as unimodal control.

RESULTS

A model consisting of one subcortical (near thalamus) and two cortical (Brodmann areas 1 and 3b) dipolar sources explained the measured HF oscillations. Both at subcortical and the cortical levels HF oscillations were significantly smaller during bimodal (somatosensory plus auditory) than unimodal (somatosensory only) stimulation. A delay differential equation model was developed to investigate interactions within the 3-node thalamo-cortical network. Importantly, a significant change in the eigenfrequency of Brodmann area 3b was related to the context-dependent modulation, while there was no change in the network coupling.

CONCLUSION

This model strongly suggests cortico-thalamic feedback from both cortical Brodmann areas 1 and 3b to the thalamus. With the 3-node network model, thalamo-cortical feedback could be described.

SIGNIFICANCE

Frequency encoding plays an important role in contextual modulation in the somatosensory thalamo-cortical network.

MEG reveals a fast pathway from somatosensory cortex to occipital areas via posterior parietal cortex in a blind subject

Cross-modal activity in visual cortex of blind subjects has been reported during performance of variety of non-visual tasks. A key unanswered question is through which pathways non-visual inputs are funneled to the visual cortex. Here we used tomographic analysis of single trial magnetoencephalography (MEG) data recorded from one congenitally blind and two sighted subjects after stimulation of the left and right median nerves at three intensities: below sensory threshold, above sensory threshold and above motor threshold; the last sufficient to produce thumb twitching. We identified reproducible brain responses in the primary somatosensory (S1) and motor (M1) cortices at around 20 ms post-stimulus, which were very similar in sighted and blind subjects. Time-frequency analysis revealed strong 45-70 Hz activity at latencies of 20-50 ms in S1 and M1, and posterior parietal cortex Brodmann areas (BA) 7 and 40, which compared to lower frequencies, were substantially more pronounced in the blind than the sighted subjects. Critically, at frequencies from α-band up to 100 Hz we found clear, strong, and widespread responses in the visual cortex of the blind subject, which increased with the intensity of the somatosensory stimuli. Time-delayed mutual information (MI) revealed that in blind subject the stimulus information is funneled from the early somatosensory to visual cortex through posterior parietal BA 7 and 40, projecting first to visual areas V5 and V3, and eventually V1. The flow of information through this pathway occurred in stages characterized by convergence of activations into specific cortical regions. In sighted subjects, no linked activity was found that led from the somatosensory to the visual cortex through any of the studied brain regions. These results provide the first evidence from MEG that in blind subjects, tactile information is routed from primary somatosensory to occipital cortex via the posterior parietal cortex.

Focal corticothalamic sources during generalized absence seizures: a MEG study

Magnetoencephalography (MEG) was used to determine cortical and subcortical contributions to the formation of spike and wave discharges in twelve newly diagnosed, drug naïve children during forty-four generalized absence seizures. Previous studies have implicated various cortical areas and thalamic nuclei in the generation of absence seizures, but the relative timing of their activity remains unclear. Beamformer analysis using synthetic aperture magnetometry (SAM) was used to confirm the presence of independent thalamic activity, and standardized Low Resolution Brain Electromagnetic Topography (sLORETA) was used to compute statistical maps indicating source locations during absence seizures. Sources detected in the 50ms prior to the start of the seizure were more likely to be localized to the frontal cortex or thalamus. At the time of the first spike on EEG, focal source localization was seen in the lateral frontal cortex with decreased thalamic localization. Following the spike, localization became more widespread throughout the cortex. Comparison of the earliest spike and wave discharge (SWD) (Ictal Onset) and a SWD occurring 3s into the seizure (mid-Ictal) revealed significant differences during the slow wave portion of the SWDs. This study of MEG recordings in childhood absence seizures provides additional evidence that there are focal brain areas responsible for these seizures which appear bilaterally symmetric and generalized with a conventional 10-20 placement scalp EEG.

Time-frequency mixed-norm estimates: sparse M/EEG imaging with non-stationary source activations

Magnetoencephalography (MEG) and electroencephalography (EEG) allow functional brain imaging with high temporal resolution. While solving the inverse problem independently at every time point can give an image of the active brain at every millisecond, such a procedure does not capitalize on the temporal dynamics of the signal. Linear inverse methods (minimum-norm, dSPM, sLORETA, beamformers) typically assume that the signal is stationary: regularization parameter and data covariance are independent of time and the time varying signal-to-noise ratio (SNR). Other recently proposed non-linear inverse solvers promoting focal activations estimate the sources in both space and time while also assuming stationary sources during a time interval. However such a hypothesis holds only for short time intervals. To overcome this limitation, we propose time-frequency mixed-norm estimates (TF-MxNE), which use time-frequency analysis to regularize the ill-posed inverse problem. This method makes use of structured sparse priors defined in the time-frequency domain, offering more accurate estimates by capturing the non-stationary and transient nature of brain signals. State-of-the-art convex optimization procedures based on proximal operators are employed, allowing the derivation of a fast estimation algorithm. The accuracy of the TF-MxNE is compared with recently proposed inverse solvers with help of simulations and by analyzing publicly available MEG datasets.

Reconstruction of quasi-radial dipolar activity using three-component magnetic field measurements

OBJECTIVE

While standard magnetoencephalographic systems record only one component of the biomagnetic field, novel vector-biomagnetometers enable measurement of all three components of the field at each sensing point. Because information content in standard one-component magnetoencephalography (MEG) is often not adequate to reconstruct quasi-radial dipolar activity, we tested the hypothesis that quasi-radial activity can be estimated using three-component MEG.

METHODS

We stimulated the right median nerve in 11 healthy volunteers and recorded the somatosensory evoked fields over the contralateral hemisphere using a novel vector-biomagnetometer system comprised of SQUID-based magnetometer triplets. Source reconstruction for the early cortical components N20m and P25m was subsequently performed.

RESULTS

Both tangential and quasi-radial dipolar activity could be reconstructed in 10 of the 11 participants. Dipole locations were found in the vicinity of the central sulcus, and dipole orientations were predominantly tangential for N20m and quasi-radial for P25m. The mean location difference between the tangential and quasi-radial dipoles was 11.9 mm and the mean orientation difference was 97.5°.

CONCLUSIONS

Quasi-radial dipolar activity can be reconstructed from three-component magnetoencephalographic measurements.

SIGNIFICANCE

Three-component MEG provides higher information content than does standard MEG.

Functional brain imaging with M/EEG using structured sparsity in time-frequency dictionaries

Magnetoencephalography (MEG) and electroencephalography (EEG) allow functional brain imaging with high temporal resolution. While time-frequency analysis is often used in the field, it is not commonly employed in the context of the ill-posed inverse problem that maps the MEG and EEG measurements to the source space in the brain. In this work, we detail how convex structured sparsity can be exploited to achieve a principled and more accurate functional imaging approach. Importantly, time-frequency dictionaries can capture the non-stationary nature of brain signals and state-of-the-art convex optimization procedures based on proximal operators allow the derivation of a fast estimation algorithm. We compare the accuracy of our new method to recently proposed inverse solvers with help of simulations and analysis of real MEG data.

Linear and nonlinear temporal interaction components of mid-latency auditory evoked potentials obtained with maximum length sequence stimulation

A maximum length sequence (MLS) is a quasi-random sequence of clicks and silences that enables simultaneous recording of linear components and nonlinear temporal interaction components (NLTICs). NLTICs are produced when the stimulation rate is fast enough such that several stimuli occur within the memory length of the system. The present study was designed to characterise the NLTICs of auditory mid-latency responses (MLR). Forty normally hearing subjects (19-45-year-old) were tested at MLS rates between 20 and 120 clicks/s. Linear components could be identified at all rates. The NLTICs of the MLS-MLR were identified in only a few subjects. This suggests two possibilities: (1) there may not be strong nonlinear temporal interactions within the MLR generators; (2) the memory length of the MLR is much shorter than expected from the linear component rates. If so, NLTICs should be obtained at higher rates of stimulation.