Cross-frequency and inter-regional phase synchronization in explicit transitive inference.

Explicit logical reasoning, like transitive inference, is a hallmark of human intelligence. This study investigated cortical oscillations and their interactions in transitive inference with EEG. Participants viewed premises describing abstract relations among items. They accurately recalled the relationship between old pairs of items, effectively inferred the relationship between new pairs of items, and discriminated between true and false relationships for new pairs. First, theta (4-7 Hz) and alpha oscillations (8-15 Hz) had distinct functional roles. Frontal theta oscillations distinguished between new and old pairs, reflecting the inference of new information. Parietal alpha oscillations changed with serial position and symbolic distance of the pairs, representing the underlying relational structure. Frontal alpha oscillations distinguished between true and false pairs, linking the new information with the underlying relational structure. Second, theta and alpha oscillations interacted through cross-frequency and inter-regional phase synchronization. Frontal theta-alpha 1:2 phase locking appeared to coordinate spectrally diverse neural activity, enhanced for new versus old pairs and true versus false pairs. Alpha-band frontal-parietal phase coherence appeared to coordinate anatomically distributed neural activity, enhanced for new versus old pairs and false versus true pairs. It suggests that cross-frequency and inter-regional phase synchronization among theta and alpha oscillations supports human transitive inference.

Cortical oscillations and interareal synchronization as a preparatory activity for postural response.

Neural mechanisms of human standing are expected to be elucidated for preventing fallings. Postural response evoked by sudden external perturbation originates from various areas in the central nervous system. Recent studies have revealed that the corticospinal pathway is one of the key nodes for an appropriate postural response. The corticospinal pathway that mediates the early part of the electromyographic response is modulated with prediction before a perturbation occurs. Temporal prediction explicitly exhibiting an onset timing contributes to enhancing corticospinal excitability. However, how the cortical activities in the sensorimotor area with temporal prediction are processed before the corticospinal pathway enhancement remains unclear. In this study, using electroencephalography, we investigated how temporal prediction affects both neural oscillations and synchronization between sensorimotor and distal areas. Our results revealed that desynchronization of cortical oscillation at α- and ß-bands was observed in the sensorimotor and parietooccipital areas (Cz, CPz, Pz and POz), and those are nested in the phase at θ-band frequency. Furthermore, a reduction in the interareal phase synchrony in the α-band was induced after the timing cue for the perturbation onset. The phase synchrony at the low frequency can relay the temporal prediction among the distant areas and initiate the modulation of the local cortical activities. Such modulations contribute to the preparation for sensory processing and motor execution that are necessary for optimal responses.

Daily resting-state intracranial EEG connectivity for seizure risk forecasts.

Forecasting seizure risk aims to detect proictal states in which seizures would be more likely to occur. Classical seizure prediction models are trained over long-term electroencephalographic (EEG) recordings to detect specific preictal changes for each seizure, independently of those induced by shifts in states of vigilance. A daily single measure-during a vigilance-controlled period-to estimate the risk of upcoming seizure(s) would be more convenient. Here, we evaluated whether intracranial EEG connectivity (phase-locking value), estimated from daily vigilance-controlled resting-state recordings, could allow distinguishing interictal (no seizure) from preictal (seizure within the next 24 h) states. We also assessed its relevance for daily forecasts of seizure risk using machine learning models. Connectivity in the theta band was found to provide the best prediction performances (area under the curve ≥ .7 in 80% of patients), with accurate daily and prospective probabilistic forecasts (mean Brier score and Brier skill score of .13 and .72, respectively). More efficient ambulatory clinical application could be considered using mobile EEG or chronic implanted devices.

Reading direct speech quotes increases theta phase-locking: Evidence for cortical tracking of inner speech?

Growing evidence shows that theta-band (4-7 Hz) activity in the auditory cortex phase-locks to rhythms of overt speech. Does theta activity also encode the rhythmic dynamics of inner speech? Previous research established that silent reading of direct speech quotes (e.g., Mary said: "This dress is lovely!") elicits more vivid inner speech than indirect speech quotes (e.g., Mary said that the dress was lovely). As we cannot directly track the phase alignment between theta activity and inner speech over time, we used EEG to measure the brain's phase-locked responses to the onset of speech quote reading. We found that direct (vs. indirect) quote reading was associated with increased theta phase synchrony over trials at 250-500 ms post-reading onset, with sources of the evoked activity estimated in the speech processing network. An eye-tracking control experiment confirmed that increased theta phase synchrony in direct quote reading was not driven by eye movement patterns, and more likely reflects synchronous phase resetting at the onset of inner speech. These findings suggest a functional role of theta phase modulation in reading-induced inner speech.

Electrophysiological correlates of saving-enhanced memory: Exploring similarities to list-method directed forgetting.

People regularly outsource parts of their memory onto external memory stores like computers or smartphones. Such cognitive offloading can enhance subsequent memory performance, as referred to the saving-enhanced memory effect (Storm & Stone, 2015). The cognitive mechanisms of this effect are not clear to date, however similarities to list-method directed forgetting (LMDF) have been stated. Here, we examined in 52 participants the electrophysiological (EEG) correlates of the saving-enhanced memory effect and compared our results to earlier LMDF findings (Hanslmayr et al., 2012). For this purpose, EEG alpha power and alpha phase synchrony during the encoding of two word lists were compared as a function of saving or no-saving. We hypothesised that if saving-enhanced memory was related to LMDF, saving in comparison to no-saving between lists should reduce alpha power and alpha phase synchrony during List 2 encoding, two effects that have been related to List 2 encoding benefits and List 1 inhibition in the earlier LMDF work. The results showed no statistically significant saving-enhanced memory effect and no significant effects in EEG alpha power or alpha phase synchrony. Possible explanations for and implications of these non-significant findings are discussed.

Working memory deficits in patients with idiopathic restless legs syndrome are associated with abnormal theta-band neural synchrony.

Cognitive impairment, particularly prefrontal function, has been reported in patients with restless legs syndrome. However, working memory performance in patients with restless legs syndrome remains uncertain. The present study aimed to examine working memory performance in patients with restless legs syndrome by investigating electroencephalography theta-band oscillations within task-relevant brain regions and the synchronization among oscillations during a working memory task. Twelve female idiopathic patients with restless legs syndrome and 12 female healthy controls participated in this study. Nineteen-channel electroencephalography data were recorded while participants performed a Sternberg working memory task. We analysed event-related theta-band activity and interregional theta-band phase synchrony during the memory retrieval phase. The spatial pattern of theta-band phase synchrony was quantified using graph theory measures, including the clustering coefficient, characteristic path length, and small-world propensity. Considerable increases in theta-band activity and theta-band phase synchrony were observed at 600-700 ms in controls and at 650-750 ms in restless legs syndrome subjects after the probe item was presented. During this period, induced theta-band activity showed lower with borderline significance in the restless legs syndrome subjects than in the controls regardless of channel location (F4,88  = 3.92, p = .06). Theta-band phase synchrony between the frontal and posterior regions was significantly reduced in the restless legs syndrome subjects. Inefficiency in both global and local networks in the restless legs syndrome subjects was revealed by the decreased small-world propensity (t22  = 2.26, p = .03). Small-world propensity was negatively correlated with restless legs syndrome severity (r = -.65, p = .02). Our findings suggest that patients with restless legs syndrome have multiple deficits in cognitive processes, including attentional allocation, evaluation of incoming stimuli, and memory manipulation of encoded information during a working memory task. Abnormal local theta-band neural synchrony and global theta-band neural synchrony may underlie the neurophysiological mechanism of the working memory dysfunction associated with restless legs syndrome.

EEG phase synchronization during semantic unification relates to individual differences in children's vocabulary skill.

As we listen to speech, our ability to understand what was said requires us to retrieve and bind together individual word meanings into a coherent discourse representation. This so-called semantic unification is a fundamental cognitive skill, and its development relies on the integration of neural activity throughout widely distributed functional brain networks. In this proof-of-concept study, we examine, for the first time, how these functional brain networks develop in children. Twenty-six children (ages 4-17) listened to well-formed sentences and sentences containing a semantic violation, while EEG was recorded. Children with stronger vocabulary showed N400 effects that were more concentrated to centroparietal electrodes and greater EEG phase synchrony (phase lag index; PLI) between right centroparietal and bilateral frontocentral electrodes in the delta frequency band (1-3 Hz) 1.27-1.53 s after listening to well-formed sentences compared to sentences containing a semantic violation. These effects related specifically to individual differences in receptive vocabulary, perhaps pointing to greater recruitment of functional brain networks important for top-down semantic unification with development. Less skilled children showed greater delta phase synchrony for violation sentences 3.41-3.64 s after critical word onset. This later effect was partly driven by individual differences in nonverbal reasoning, perhaps pointing to non-verbal compensatory processing to extract meaning from speech in children with less developed vocabulary. We suggest that functional brain network communication, as measured by momentary changes in the phase synchrony of EEG oscillations, develops throughout the school years to support language comprehension in different ways depending on children's verbal and nonverbal skill levels.

What's in Your Gamma? Activation of the Ventral Fronto-Parietal Attentional Network in Response to Distracting Sounds.

Auditory attention operates through top-down (TD) and bottom-up (BU) mechanisms that are supported by dorsal and ventral brain networks, respectively, with the main overlap in the lateral prefrontal cortex (lPFC). A good TD/BU balance is essential to be both task-efficient and aware of our environment, yet it is rarely investigated. Oscillatory activity is a novel method to probe the attentional dynamics with evidence that gamma activity (>30 Hz) could signal BU processing and thus would be a good candidate to support the activation of the ventral BU attention network. Magnetoencephalography data were collected from 21 young adults performing the competitive attention task, which enables simultaneous investigation of BU and TD attentional mechanisms. Distracting sounds elicited an increase in gamma activity in regions of the BU ventral network. TD attention modulated these gamma responses in regions of the inhibitory cognitive control system: the medial prefrontal and anterior cingulate cortices. Finally, distracting-sound-induced gamma activity was synchronous between the auditory cortices and several distant brain regions, notably the lPFC. We provide novel insight into the role of gamma activity 1) in supporting the activation of the ventral BU attention network and 2) in subtending the TD/BU attention balance in the PFC.

Phase Synchrony Analysis of Rolling Bearing Vibrations and Its Application to Failure Identification.

As the failure-induced component (FIC) in the vibration signals of bearings transmits through housings and shafts, potential phase synchronization is excited among multichannel signals. As phase synchrony analysis (PSA) does not involve the chaotic behavior of signals, it is suitable for characterizing the operating state of bearings considering complicated vibration signals. Therefore, a novel PSA method was developed to identify and track the failure evolution of bearings. First, resonance demodulation and variational mode decomposition (VMD) were combined to extract the mono-component or band-limited FIC from signals. Then, the instantaneous phase of the FIC was analytically solved using Hilbert transformation. The generalized phase difference (GPD) was used to quantify the relationship between FICs extracted from different vibration signals. The entropy of the GPD was regarded as the indicator for quantifying failure evolution. The proposed method was applied to the vibration signals obtained from an accelerated failure experiment and a natural failure experiment. Results showed that phase synchronization in bearing failure evolution was detected and evaluated effectively. Despite the chaotic behavior of the signals, the phase synchronization indicator could identify bearing failure during the initial stage in a robust manner.

On the relationship between instantaneous phase synchrony and correlation-based sliding windows for time-resolved fMRI connectivity analysis.

Correlation-based sliding window analysis (CSWA) is the most commonly used method to estimate time-resolved functional MRI (fMRI) connectivity. However, instantaneous phase synchrony analysis (IPSA) is gaining popularity mainly because it offers single time-point resolution of time-resolved fMRI connectivity. We aim to provide a systematic comparison between these two approaches, on temporal, topological and anatomical levels. For this purpose, we used resting-state fMRI data from two separate cohorts with different temporal resolutions (45 healthy subjects from Human Connectome Project fMRI data with repetition time of 0.72 s and 25 healthy subjects from a separate validation fMRI dataset with a repetition time of 3 s). For time-resolved functional connectivity analysis, we calculated tapered CSWA over a wide range of different window lengths that were compared to IPSA. We found a strong association in connectivity dynamics between IPSA and CSWA when considering the absolute values of CSWA. The association between CSWA and IPSA was stronger for a window length of ∼20 s (shorter than filtered fMRI wavelength) than ∼100 s (longer than filtered fMRI wavelength), irrespective of the sampling rate of the underlying fMRI data. Narrow-band filtering of fMRI data (0.03-0.07 Hz) yielded a stronger relationship between IPSA and CSWA than wider-band (0.01-0.1 Hz). On a topological level, time-averaged IPSA and CSWA nodes were non-linearly correlated for both short (∼20 s) and long (∼100 s) windows, mainly because nodes with strong negative correlations (CSWA) displayed high phase synchrony (IPSA). IPSA and CSWA were anatomically similar in the default mode network, sensory cortex, insula and cerebellum. Our results suggest that IPSA and CSWA provide comparable characterizations of time-resolved fMRI connectivity for appropriately chosen window lengths. Although IPSA requires narrow-band fMRI filtering, it does not mandate a (semi-)arbitrary choice of window length and window overlap. A code for calculating IPSA is provided.

Ghost interactions in MEG/EEG source space: A note of caution on inter-areal coupling measures.

When combined with source modeling, magneto- (MEG) and electroencephalography (EEG) can be used to study long-range interactions among cortical processes non-invasively. Estimation of such inter-areal connectivity is nevertheless hindered by instantaneous field spread and volume conduction, which artificially introduce linear correlations and impair source separability in cortical current estimates. To overcome the inflating effects of linear source mixing inherent to standard interaction measures, alternative phase- and amplitude-correlation based connectivity measures, such as imaginary coherence and orthogonalized amplitude correlation have been proposed. Being by definition insensitive to zero-lag correlations, these techniques have become increasingly popular in the identification of correlations that cannot be attributed to field spread or volume conduction. We show here, however, that while these measures are immune to the direct effects of linear mixing, they may still reveal large numbers of spurious false positive connections through field spread in the vicinity of true interactions. This fundamental problem affects both region-of-interest-based analyses and all-to-all connectome mappings. Most importantly, beyond defining and illustrating the problem of spurious, or "ghost" interactions, we provide a rigorous quantification of this effect through extensive simulations. Additionally, we further show that signal mixing also significantly limits the separability of neuronal phase and amplitude correlations. We conclude that spurious correlations must be carefully considered in connectivity analyses in MEG/EEG source space even when using measures that are immune to zero-lag correlations.

Dance on cortex: enhanced theta synchrony in experts when watching a dance piece.

When watching performing arts, a wide and complex network of brain processes emerge. These processes can be shaped by professional expertise. When compared to laymen, dancers have enhanced processes in observation of short dance movement and listening to music. But how do the cortical processes differ in musicians and dancers when watching an audio-visual dance performance? In our study, we presented the participants long excerpts from the contemporary dance choreography of Carmen. During multimodal movement of a dancer, theta phase synchrony over the fronto-central electrodes was stronger in dancers when compared to musicians and laymen. In addition, alpha synchrony was decreased in all groups during large rapid movement when compared to nearly motionless parts of the choreography. Our results suggest an enhanced cortical communication in dancers when watching dance and, further, that this enhancement is rather related to multimodal, cognitive and emotional processes than to simple observation of dance movement.

A mathematical model to mimic the shape of event related desynchronization/synchronization.

Rhythmic oscillatory activities of the sensory cortex have been observed after a presentation of a stimulus. This activity first drops dramatically and then increases considerably that are respectively named event-related desynchronization (ERD) and event-related synchronization (ERS). There are several effective factors that can alter the ERD and ERS pattern. In this study, a mathematical model was presented that produced ERD and ERS pattern in response to a stimulus. This model works based on the synchronization concepts. The proposed model provided different suggestions about the reason behind the relationship between the encoding of incoming sensory information and the oscillatory activities, effective factors on the characteristics of neuronal units, and how may these factors affect the amplitude and latency of the ERD and ERS.

Exploiting the heightened phase synchrony in patients with neuromuscular disease for the establishment of efficient motor imagery BCIs.

BACKGROUND: Phase synchrony has extensively been studied for understanding neural coordination in health and disease. There are a few studies concerning the implications in the context of BCIs, but its potential for establishing a communication channel in patients suffering from neuromuscular disorders remains totally unexplored. We investigate, here, this possibility by estimating the time-resolved phase connectivity patterns induced during a motor imagery (MI) task and adopting a supervised learning scheme to recover the subject's intention from the streaming data. METHODS: Electroencephalographic activity from six patients suffering from neuromuscular disease (NMD) and six healthy individuals was recorded during two randomly alternating, externally cued, MI tasks (clenching either left or right fist) and a rest condition. The metric of Phase locking value (PLV) was used to describe the functional coupling between all recording sites. The functional connectivity patterns and the associate network organization was first compared between the two cohorts. Next, working at the level of individual patients, we trained support vector machines (SVMs) to discriminate between "left" and "right" based on different instantiations of connectivity patterns (depending on the encountered brain rhythm and the temporal interval). Finally, we designed and realized a novel brain decoding scheme that could interpret the intention from streaming connectivity patterns, based on an ensemble of SVMs. RESULTS: The group-level analysis revealed increased phase synchrony and richer network organization in patients. This trend was also seen in the performance of the employed classifiers. Time-resolved connectivity led to superior performance, with distinct SVMs acting as local experts, specialized in the patterning emerged within specific temporal windows (defined with respect to the external trigger). This empirical finding was further exploited in implementing a decoding scheme that can be activated without the need of the precise timing of a trigger. CONCLUSION: The increased phase synchrony in NMD patients can turn to a valuable tool for MI decoding. Considering the fast implementation for the PLV pattern computation in multichannel signals, we can envision the development of efficient personalized BCI systems in assistance of these patients.

Why don't you like me? Midfrontal theta power in response to unexpected peer rejection feedback.

Social connectedness theory posits that the brain processes social rejection as a threat to survival. Recent electrophysiological evidence suggests that midfrontal theta (4-8Hz) oscillations in the EEG provide a window on the processing of social rejection. Here we examined midfrontal theta dynamics (power and inter-trial phase synchrony) during the processing of social evaluative feedback. We employed the Social Judgment paradigm in which 56 undergraduate women (mean age=19.67 years) were asked to communicate their expectancies about being liked vs. disliked by unknown peers. Expectancies were followed by feedback indicating social acceptance vs. rejection. Results revealed a significant increase in EEG theta power to unexpected social rejection feedback. This EEG theta response could be source-localized to brain regions typically reported during activation of the saliency network (i.e., dorsal anterior cingulate cortex, insula, inferior frontal gyrus, frontal pole, and the supplementary motor area). Theta phase dynamics mimicked the behavior of the time-domain averaged feedback-related negativity (FRN) by showing stronger phase synchrony for feedback that was unexpected vs. expected. Theta phase, however, differed from the FRN by also displaying stronger phase synchrony in response to rejection vs. acceptance feedback. Together, this study highlights distinct roles for midfrontal theta power and phase synchrony in response to social evaluative feedback. Our findings contribute to the literature by showing that midfrontal theta oscillatory power is sensitive to social rejection but only when peer rejection is unexpected, and this theta response is governed by a widely distributed neural network implicated in saliency detection and conflict monitoring.

Hippocampal-prefrontal theta phase synchrony in planning of multi-step actions based on memory retrieval.

Planning of multi-step actions based on the retrieval of acquired information is essential for efficient foraging. The hippocampus (HPC) and prefrontal cortex (PFC) may play critical roles in this process. However, in rodents, many studies investigating such roles utilized T-maze tasks that only require one-step actions (i.e., selection of one of two alternatives), in which memory retrieval and selection of an action based on the retrieval cannot be clearly differentiated. In monkeys, PFC has been suggested to be involved in planning of multi-step actions; however, the synchrony between HPC and PFC has not been evaluated. To address the combined role of the regions in planning of multi-step actions, we introduced a task in rats that required three successive nose-poke responses to three sequentially illuminated nose-poke holes. During the task, local field potentials (LFP) and spikes from hippocampal CA1 and medial PFC (mPFC) were simultaneously recorded. The position of the first hole indicated whether the following two holes would be presented in a predictable sequence or not. During the first nose-poke period, phase synchrony of LFPs in the theta range (4-10 Hz) between the regions was not different between predictable and unpredictable trials. However, only in trials of predictable sequences, the magnitude of theta phase synchrony during the first nose-poke period was negatively correlated with latency of the two-step ahead nose-poke response. Our findings point to the HPC-mPFC theta phase synchrony as a key mechanism underlying planning of multi-step actions based on memory retrieval rather than the retrieval itself.

Intentional gaze shift to neglected space: a compensatory strategy during recovery after unilateral spatial neglect.

Unilateral spatial neglect is a common neurological syndrome following predominantly right hemispheric stroke. While most patients lack insight into their neglect behaviour and do not initiate compensatory behaviours in the early recovery phase, some patients recognize it and start to pay attention towards the neglected space. We aimed to characterize visual attention capacity in patients with unilateral spatial neglect with specific focus on cortical processes underlying compensatory gaze shift towards the neglected space during the recovery process. Based on the Behavioural Inattention Test score and presence or absence of experience of neglect in their daily life from stroke onset to the enrolment date, participants were divided into USN+‰‰+ (do not compensate, n = 15), USN+ (compensate, n = 10), and right hemisphere damage groups (no neglect, n = 24). The patients participated in eye pursuit-based choice reaction tasks and were asked to pursue one of five horizontally located circular objects flashed on a computer display. The task consisted of 25 trials with 4-s intervals, and the order of highlighted objects was randomly determined. From the recorded eye tracking data, eye movement onset and gaze shift were calculated. To elucidate the cortical mechanism underlying behavioural results, electroencephalagram activities were recorded in three USN+‰‰+, 13 USN+ and eight patients with right hemisphere damage. We found that while lower Behavioural Inattention Test scoring patients (USN+‰‰+) showed gaze shift to non-neglected space, some higher scoring patients (USN+) showed clear leftward gaze shift at visual stimuli onset. Moreover, we found a significant correlation between Behavioural Inattention Test score and gaze shift extent in the unilateral spatial neglect group (r = -0.62, P < 0.01). Electroencephalography data clearly demonstrated that the extent of increase in theta power in the frontal cortex strongly correlated with the leftward gaze shift extent in the USN+‰‰+ and USN+ groups. Our results revealed a compensatory strategy (continuous attention to the neglected space) and its neural correlates in patients with unilateral spatial neglect. In conclusion, patients with unilateral spatial neglect who recognized their own neglect behaviour intentionally focused on the neglected space as a compensatory strategy to avoid careless oversight.

Cortical Low-Frequency Power and Progressive Phase Synchrony Precede Successful Memory Encoding.

Neural activity preceding an event can influence subsequent memory formation, yet the precise cortical dynamics underlying this activity and the associated cognitive states remain unknown. We investigate these questions here by examining intracranial EEG recordings as 28 participants with electrodes placed for seizure monitoring participated in a verbal paired-associates memory task. We found that, preceding successfully remembered word pairs, an orientation cue triggered a low-frequency 2-4 Hz phase reset in the right temporoparietal junction with concurrent increases in low-frequency power across cortical regions that included the prefrontal cortex and left temporal lobe. Regions that exhibited a significant increase in 2-4 Hz power were functionally bound together through progressive low-frequency 2-4 Hz phase synchrony. Our data suggest that the interaction between power and phase synchrony reflects the engagement of attentional networks that in large part determine the extent to which memories are successfully encoded. SIGNIFICANCE STATEMENT: Here we investigate the spatiotemporal cortical dynamics that precede successful memory encoding. Using intracranial EEG, we observed significant changes in oscillatory power, intertrial phase consistency, and pairwise phase synchrony that predict successful encoding. Our data suggest that the interaction between power and phase synchrony reflects the engagement of attentional networks that in large part determine the extent to which memories are successfully encoded.

Dynamic network mechanisms of relational integration.

A prominent hypothesis states that specialized neural modules within the human lateral frontopolar cortices (LFPCs) support "relational integration" (RI), the solving of complex problems using inter-related rules. However, it has been proposed that LFPC activity during RI could reflect the recruitment of additional "domain-general" resources when processing more difficult problems in general as opposed to RI specifically. Moreover, theoretical research with computational models has demonstrated that RI may be supported by dynamic processes that occur throughout distributed networks of brain regions as opposed to within a discrete computational module. Here, we present fMRI findings from a novel deductive reasoning paradigm that controls for general difficulty while manipulating RI demands. In accordance with the domain-general perspective, we observe an increase in frontoparietal activation during challenging problems in general as opposed to RI specifically. Nonetheless, when examining frontoparietal activity using analyses of phase synchrony and psychophysiological interactions, we observe increased network connectivity during RI alone. Moreover, dynamic causal modeling with Bayesian model selection identifies the LFPC as the effective connectivity source. Based on these results, we propose that during RI an increase in network connectivity and a decrease in network metastability allows rules that are coded throughout working memory systems to be dynamically bound. This change in connectivity state is top-down propagated via a hierarchical system of domain-general networks with the LFPC at the apex. In this manner, the functional network perspective reconciles key propositions of the globalist, modular, and computational accounts of RI within a single unified framework.

Dynamic regional phase synchrony (DRePS): An Instantaneous Measure of Local fMRI Connectivity Within Spatially Clustered Brain Areas.

Dynamic functional brain connectivity analysis is a fast expanding field in computational neuroscience research with the promise of elucidating brain network interactions. Sliding temporal window based approaches are commonly used in order to explore dynamic behavior of brain networks in task-free functional magnetic resonance imaging (fMRI) data. However, the low effective temporal resolution of sliding window methods fail to capture the full dynamics of brain activity at each time point. These also require subjective decisions regarding window size and window overlap. In this study, we introduce dynamic regional phase synchrony (DRePS), a novel analysis approach that measures mean local instantaneous phase coherence within adjacent fMRI voxels. We evaluate the DRePS framework on simulated data showing that the proposed measure is able to estimate synchrony at higher temporal resolution than sliding windows of local connectivity. We applied DRePS analysis to task-free fMRI data of 20 control subjects, revealing ultra-slow dynamics of local connectivity in different brain areas. Spatial clustering based on the DRePS feature time series reveals biologically congruent local phase synchrony networks (LPSNs). Taken together, our results demonstrate three main findings. Firstly, DRePS has increased temporal sensitivity compared to sliding window correlation analysis in capturing locally synchronous events. Secondly, DRePS of task-free fMRI reveals ultra-slow fluctuations of ∼0.002-0.02 Hz. Lastly, LPSNs provide plausible spatial information about time-varying brain local phase synchrony. With the DRePS method, we introduce a framework for interrogating brain local connectivity, which can potentially provide biomarkers of human brain function in health and disease. Hum Brain Mapp 37:1970-1985, 2016. © 2016 Wiley Periodicals, Inc.