Computing the center of mass for traveling alpha waves in the human brain

Probing the Functional and Structural Connectivity Underlying EEG Traveling Waves

Neural oscillations play an important role in the maintenance of brain function by regulating multi-scale neural activity. Characterizing the traveling properties of EEG is helpful for understanding the spatiotemporal dynamics of neural oscillations. However, traveling EEG based on non-invasive approach has little been investigated, and the relationship with brain intrinsic connectivity is not well known. In this study, traveling EEG of different frequency bands on the scalp in terms of the center of mass (EEG-CM) was examined. Then, two quantitative indexes describing the spatiotemporal features of EEG-CM were proposed, i.e., the traveling lateralization and velocity of EEG-CM. Further, based on simultaneous EEG-MRI approach, the relationship between traveling EEG-CM and the resting-state functional networks, as well as the microstructural connectivity of white matter was investigated. The results showed that there was similar spatial distribution of EEG-CM under different frequency bands, while the velocity of rhythmic EEG-CM increased in higher frequency bands. The lateralization of EEG-CM in low frequency bands (< 30 Hz) demonstrated negative relationship with the basal ganglia network (BGN). In addition, the velocity of the traveling EEG-CM was associated with the fractional anisotropy (FA) in corpus callosum and corona radiate. These results provided valid quantitative EEG index for understanding the spatiotemporal characteristics of the scalp EEG, and implied that the EEG dynamics were representations of functional and structural organization of cortical and subcortical structures.

Resting state alpha oscillatory activity is a valid and reliable marker of schizotypy

Schizophrenia is among the most debilitating neuropsychiatric disorders. However, clear neurophysiological markers that would identify at-risk individuals represent still an unknown. The aim of this study was to investigate possible alterations in the resting alpha oscillatory activity in normal population high on schizotypy trait, a physiological condition known to be severely altered in patients with schizophrenia. Direct comparison of resting-state EEG oscillatory activity between Low and High Schizotypy Group (LSG and HSG) has revealed a clear right hemisphere alteration in alpha activity of the HSG. Specifically, HSG shows a significant slowing down of right hemisphere posterior alpha frequency and an altered distribution of its amplitude, with a tendency towards a reduction in the right hemisphere in comparison to LSG. Furthermore, altered and reduced connectivity in the right fronto-parietal network within the alpha range was found in the HSG. Crucially, a trained pattern classifier based on these indices of alpha activity was able to successfully differentiate HSG from LSG on tested participants further confirming the specific importance of right hemispheric alpha activity and intrahemispheric functional connectivity. By combining alpha activity and connectivity measures with a machine learning predictive model optimized in a nested stratified cross-validation loop, current research offers a promising clinical tool able to identify individuals at-risk of developing psychosis (i.e., high schizotypy individuals).

Decreased peak alpha frequency and impaired visual evoked potentials in first episode psychosis

Abnormal spontaneous and evoked oscillations have been reported in several studies of patients with psychotic disorders. Resting alpha power and peak alpha frequency may be decreased in patients with psychosis. We used high-density EEG (hd-EEG) to record resting-state data and steady-state visual evoked potentials (SSVEPs) in patients with first episode psychosis (FEP) and healthy controls to compare brain resonances across multiple frequencies. We recorded hd-EEG (128 channels) from 22 FEP patients and 22 healthy controls during eyes-closed resting state and eyes-closed photic stimulation at 1 Hz, 4 Hz, 10 Hz, 20 Hz, and 40 Hz. Alpha power, peak alpha frequency, and SSVEP amplitude were analyzed using ANOVA and statistical non-parametric mapping. We found that FEP patients had lower peak alpha frequencies (9.72 Hz vs 10.40 Hz, p = .02, Cohen's d = 0.73) and this decrease was driven by slowing over the central and posterior scalp. There was no difference in alpha power. Alpha waves propagated primarily from anterior to posterior and that propagation was slowed in patients. During SSVEP, patients had smaller increases in EEG power in the stimulation band (F(1,184) = 5.3, p = .02). Patients had attenuated responses to SSVEP stimulation at alpha, beta and gamma frequencies. The gamma response was partially preserved in patients who also had depressive symptoms. We conclude that even in early stages of illness, psychotic disorders are associated with decreased alpha peak frequency and impaired evoked resonances. These findings implicate multiple patterns of dysconnectivity in cortico-cortico and cortico-thalamic networks in FEP.

Early Appearance and Spread of Fast Ripples in the Hippocampus in a Model of Cortical Traumatic Brain Injury

Fast ripples (FRs; activity of >250 Hz) have been considered as a biomarker of epileptic activity in the hippocampus and entorhinal cortex; it is thought that they signal the focus of seizure generation. Similar high-frequency network activity has been produced in vitro by changing extracellular medium composition, by using pro-epileptic substances, or by electrical stimulation. Here we study the propagation of these events between different subregions of the male rat hippocampus in a recently introduced experimental model of FRs in entorhinal cortex-hippocampal slices in vitro By using a matrix of 4096 microelectrodes, the sites of initiation, propagation pathways, and spatiotemporal characteristics of activity patterns could be studied with unprecedented high resolution. To this end, we developed an analytic tool based on bidimensional current source density estimation, which delimits sinks and sources with a high precision and evaluates their trajectories using the concept of center of mass. With this methodology, we found that FRs can arise almost simultaneously at noncontiguous sites in the CA3-to-CA1 direction, underlying the spatial heterogeneity of epileptogenic foci, while continuous somatodendritic waves of activity develop. An unexpected, yet important propagation route is the propagation of activity from CA3 into the hilus and dentate gyrus. This pathway may cause reverberating activation of both regions, supporting sustained pathological network events and altered information processing in hippocampal networks.SIGNIFICANCE STATEMENT Fast ripples (FRs) have been considered as a biomarker of epileptic activity and may signal the focus of seizure generation. In a model of traumatic brain injury in the rat, FRs appear in the hippocampus within a couple of hours after an extrahippocampal, cortical lesion. We analyzed the origin and dynamics of the FRs in the hippocampus using massive electrophysiological recordings, allowing an unprecedented high spatiotemporal resolution. We show that FRs originate in distinct and noncontiguous locations within the CA3 region and uncover, with high precision, the extent and dynamics of their current density. This activity propagates toward CA1 but also backpropagates to the hilus and the dentate gyrus, suggesting activation of defined microcircuits that can sustain recurrent excitation.

A Comparative Study on the Dynamic EEG Center of Mass with Different References

One of the most fundamental issues during an EEG study is choosing an available neutral reference. The infinity zero reference obtained by the reference electrode standardization technique (REST) has been recommended and used for its higher accuracy. This paper examined three traditional references, the average reference (AR), the linked mastoids reference (LM), and REST, in the study of the EEG center of mass (CM) using simulated and real ERPs. In the simulation, the relative error of REST was the smallest among the references. As for the ERP data with the visual oddball paradigm, the dynamic CM trajectory and its traveling velocity obtained by REST characterized three typical stages in spatial domain and temporal speed metrics, which provided useful information in addition to the distinct ERP waveform in the temporal domain. The results showed that the CM traveling from the frontal to parietal areas corresponding to the earlier positive components (i.e., P200 and P250), stays temporarily at the parietal area corresponding to P300 and then returns to the frontal area during the recovery stage. Compared with REST, AR, and LM not only changed the amplitude of P300 significantly but distorted the CM trajectory and its instantaneous velocity. As REST continues to provide objective results, we recommend that REST be used in future EEG/ERP CM studies.

Associations between prospective symptom changes and slow-wave activity in patients with Internet gaming disorder: A resting-state EEG study

The identification of the predictive factors and biological markers associated with treatment-related changes in the symptoms of Internet gaming disorder (IGD) may provide a better understanding of the pathophysiology underlying this condition. Thus, the present study aimed to identify neurophysiological markers associated with symptom changes in IGD patients and to identify factors that may predict symptom improvements following outpatient treatment with pharmacotherapy. The present study included 20 IGD patients (mean age: 22.71 ± 5.47 years) and 29 healthy control subjects (mean age: 23.97 ± 4.36 years); all IGD patients completed a 6-month outpatient management program that included pharmacotherapy with selective serotonin reuptake inhibitors. Resting-state electroencephalography scans were acquired prior to and after treatment, and the primary treatment outcome was changes in scores on Young's Internet Addiction Test (IAT) from pre- to posttreatment. IGD patients showed increased resting-state electroencephalography activity in the delta and theta bands at baseline, but the increased delta band activity was normalized after 6 months of treatment and was significantly correlated with improvements in IGD symptoms. Additionally, higher absolute theta activity at baseline predicted a greater possibility of improvement in addiction symptoms following treatment, even after adjusting for the effects of depressive or anxiety symptoms. The present findings demonstrated that increased slow-wave activity represented a state neurophysiological marker in IGD patients and suggested that increased theta activity at baseline may be a favorable prognostic marker for this population.

Synchronization and Propagation of Global Sleep Spindles

Sleep spindles occur thousands of times during normal sleep and can be easily detected by visual inspection of EEG signals. These characteristics make spindles one of the most studied EEG structures in mammalian sleep. In this work we considered global spindles, which are spindles that are observed simultaneously in all EEG channels. We propose a methodology that investigates both the signal envelope and phase/frequency of each global spindle. By analysing the global spindle phase we showed that 90% of spindles synchronize with an average latency time of 0.1 s. We also measured the frequency modulation (chirp) of global spindles and found that global spindle chirp and synchronization are not correlated. By investigating the signal envelopes and implementing a homogeneous and isotropic propagation model, we could estimate both the signal origin and velocity in global spindles. Our results indicate that this simple and non-invasive approach could determine with reasonable precision the spindle origin, and allowed us to estimate a signal speed of 0.12 m/s. Finally, we consider whether synchronization might be useful as a non-invasive diagnostic tool.

Donders is dead: cortical traveling waves and the limits of mental chronometry in cognitive neuroscience

An assumption nearly all researchers in cognitive neuroscience tacitly adhere to is that of space–time separability. Historically, it forms the basis of Donders’ difference method, and to date, it underwrites all difference imaging and trial-averaging of cortical activity, including the customary techniques for analyzing fMRI and EEG/MEG data. We describe the assumption and how it licenses common methods in cognitive neuroscience; in particular, we show how it plays out in signal differencing and averaging, and how it misleads us into seeing the brain as a set of static activity sources. In fact, rather than being static, the domains of cortical activity change from moment to moment: Recent research has suggested the importance of traveling waves of activation in the cortex. Traveling waves have been described at a range of different spatial scales in the cortex; they explain a large proportion of the variance in phase measurements of EEG, MEG and ECoG, and are important for understanding cortical function. Critically, traveling waves are not space–time separable. Their prominence suggests that the correct frame of reference for analyzing cortical activity is the dynamical trajectory of the system, rather than the time and space coordinates of measurements. We illustrate what the failure of space–time separability implies for cortical activation, and what consequences this should have for cognitive neuroscience.

Load effects in auditory selective attention: evidence for distinct facilitation and inhibition mechanisms

It is unknown whether facilitation and inhibition of stimulus processing represent one or two mechanisms in auditory attention. We performed electrophysiological experiments in humans to address these two competing hypothesis. Participants performed an attention task under low or high memory load. Facilitation and inhibition were measured by recording electrophysiological responses to attended and ignored sounds and comparing them to responses to these same sounds when attention was considered to be equally distributed towards all sounds. We observed two late frontally distributed components: a negative one in response to attended sounds, and a positive one to ignored sounds. These two frontally distributed responses had distinct timing and scalp topographies and were differentially affected by memory load. Taken together these results provide evidence that attention-mediated top-down control reflects the activity of distinct facilitation and inhibition mechanisms.

Spatio-temporal EEG waves in first episode schizophrenia

OBJECTIVE

Schizophrenia is characterized by a deficit in context processing, with physiological correlates of hypofrontality and reduced amplitude P3b event-related potentials. We hypothesized an additional physiological correlate: differences in the spatio-temporal dynamics of cortical activity along the anterior-posterior axis of the scalp.

METHODS

This study assessed latency topographies of spatio-temporal waves under task conditions that elicit the P3b. EEG was recorded during separate auditory and visual tasks. Event-related spatio-temporal waves were quantified from scalp EEG of subjects with first episode schizophrenia (FES) and matched controls.

RESULTS

The P3b-related task conditions elicited a peak in spatio-temporal waves in the delta band at a similar latency to the P3b event-related potential. Subjects with FES had fewer episodes of anterior to posterior waves in the 2-4 Hz band compared to controls. Within the FES group, a tendency for fewer episodes of anterior to posterior waves was associated with high Psychomotor Poverty symptom factor scores.

CONCLUSIONS

Subjects with FES had altered global EEG dynamics along the anterior-posterior axis during task conditions involving context update.

SIGNIFICANCE

The directional nature of this finding and its association with Psychomotor Poverty suggest this result is related to findings of hypofrontality in schizophrenia.

Propagation of sinusoidal electrical waves along the spinal cord during a fictive motor task

We present for the first time direct electrophysiological evidence of the phenomenon of traveling electrical waves produced by populations of interneurons within the spinal cord. We show that, during a fictive rhythmic motor task, scratching, an electrical field potential of spinal interneurons takes the shape of a sinuous wave, "sweeping" the lumbosacral spinal cord rostrocaudally with a mean speed of approximately 0.3 m/s. We observed that traveling waves and scratching have the same cycle duration and that duration of the flexor phase, but not of the extensor phase, is highly correlated with the cycle duration of the traveling waves. Furthermore, we found that the interneurons from the deep dorsal horn and the intermediate nucleus can generate the spinal traveling waves, even in the absence of motoneuronal activity. These findings show that the sinusoidal field potentials generated during fictive scratching could be a powerful tool to disclose the organization of central pattern generator networks.

Region-specific network plasticity in simulated and living cortical networks: comparison of the center of activity trajectory (CAT) with other statistics

Electrically interfaced cortical networks cultured in vitro can be used as a model for studying the network mechanisms of learning and memory. Lasting changes in functional connectivity have been difficult to detect with extracellular multi-electrode arrays using standard firing rate statistics. We used both simulated and living networks to compare the ability of various statistics to quantify functional plasticity at the network level. Using a simulated integrate-and-fire neural network, we compared five established statistical methods to one of our own design, called center of activity trajectory (CAT). CAT, which depicts dynamics of the location-weighted average of spatiotemporal patterns of action potentials across the physical space of the neuronal circuitry, was the most sensitive statistic for detecting tetanus-induced plasticity in both simulated and living networks. By reducing the dimensionality of multi-unit data while still including spatial information, CAT allows efficient real-time computation of spatiotemporal activity patterns. Thus, CAT will be useful for studies in vivo or in vitro in which the locations of recording sites on multi-electrode probes are important.