Biology subjects

Grabowecky, M.

Publications and source records attributed to Grabowecky, M..

9 recordsLinked to original sources

bioRxiv2024

Dynamic formation of a posterior-to-anterior peak-alpha-frequency gradient driven by two distinct processes

Peak-alpha frequency varies across individuals and mental states, but it also forms a negative gradient from posterior to anterior regions in association with increases in cortical thickness and connectivity reflecting the cortical hierarchy in temporal integration. Tracking the spatial standard deviation of peak-alpha frequency in scalp EEG, we observed that the posterior-to-anterior gradient dynamically formed and dissolved. Periods of high spatial standard deviation yielded robustly negative posterior-to-anterior gradients--the gradient state--while periods of low spatial standard deviation yielded globally converged peak-alpha frequency--the uniform state. Our analyses suggest that the fluctuations between the gradient and uniform states are associated with two separate variables: (1) coordinated variations in peak-alpha frequency in anterior regions and (2) coordinated variations in peak-alpha power in central regions driven by posterior regions. These variables each accounted for [~]25% of the state fluctuations, were uncorrelated with each other, and together accounted for [~]50% of the state fluctuations. These results reflect general mechanisms as they replicated while participants engaged in a variety of behavioral tasks with their eyes closed (breath focus, vigilance, working memory, mental arithmetic, and generative thinking). Overall, our results suggest that the spatial pattern of peak-alpha frequency dynamically fluctuates between the gradient state, potentially facilitating information influx and temporal integration toward anterior regions, and the uniform state, potentially facilitating global communication, with the state fluctuations controlled by at least two distinct mechanisms, an anterior mechanism that directly adjusts peak-alpha frequencies and a posterior mechanism that indirectly adjusts them by influencing synchronization.

neuroscience↗

bioRxiv2023

Spontaneous anterior-posterior convergences of oscillation frequencies in the alpha band

Alpha oscillation frequencies vary along the anterior-posterior axis, but they also dynamically converge. We investigated spontaneous anterior-posterior oscillation-frequency convergences while participants rested with their eyes open or closed, by tracking their oscillatory EEG activity in an extended alpha range (5-15 Hz) with appropriate temporal ({bsim}370 ms) and spectral ({bsim}1 Hz) resolutions. Oscillation-frequency convergences were prominent in the alpha band (8-12 Hz) and our analyses revealed three primary characteristics. First, the probability of an additional site joining a frequency convergence increased as more sites frequency-converged, suggesting that synergistic interactions drive anterior-posterior frequency convergences. Second, the oscillatory power at participating sites increased as more sites frequency-converged, suggesting that the synergistic interactions are mediated by regional synchronizations, being boosted by inter-regional frequency matching, facilitating the entrainment of additional regions. Third, frequency convergences generated two opposing phase gradients, posterior-behind and posterior-ahead, potentially mediating directional information flows to and from posterior regions. These gradients became steeper as more sites frequency-converged (while maintaining relatively constant levels of phase consistency), suggesting that frequency convergences increase the directionality of anterior-posterior information flows. Interestingly, when participants closed their eyes, the opposing phase gradients spatially organized, forming posterior-ahead gradients along the midline and posterior-behind gradients within each hemisphere, suggesting that closing eyes streamlines the opposing information flows. Taken together, these results suggest that synergistic interactions drive spontaneous anterior-posterior oscillation-frequency convergences in the alpha band, which may contribute to directional flows of information to and from posterior regions.

neuroscience↗

bioRxiv2021

A phase-shifting anterior-posterior network organizes global phase relations

Prior research has identified a variety of task-dependent networks that form through inter-regional phase-locking of oscillatory activity that are neural correlates of specific behaviors. Despite ample knowledge of task-specific functional networks, general rules governing global phase relations have not been investigated. To discover such general rules, we focused on phase modularity, measured as the degree to which global phase relations in EEG comprised distinct synchronized clusters interacting with one another at large phase lags. Synchronized clusters were detected with a standard community-detection algorithm, and the degree of phase modularity was quantified by the index q. Notably, we found that the mechanism controlling phase modularity is remarkably simple. A network comprising anterior-posterior long-distance connectivity coherently shifted phase relations from low-angles (|{Delta}{theta}| < {pi}/4) in low-modularity states (bottom 5% in q) to high-angles (|{Delta}{theta}| > 3{pi}/4) in high-modularity states (top 5% in q), accounting for fluctuations in phase modularity. This anterior-posterior network may play a fundamental functional role as (1) it controls phase modularity across a broad range of frequencies (3-50 Hz examined) in different behavioral conditions (resting with the eyes closed or watching a silent nature video) and (2) neural interactions (measured as power correlations) in beta-to-gamma bands were consistently elevated in high-modularity states. These results may motivate future investigations into the functional roles of phase modularity as well as the anterior-posterior network that controls it.

neuroscience↗

bioRxiv2021

Spatiotemporal dynamics of maximal and minimal EEG spectral power

Oscillatory neural activities are prevalent in the brain with their phase realignment contributing to the coordination of neural communication. Phase realignments may have especially strong (or weak) impact when neural activities are strongly synchronized (or desynchronized) within the interacting populations. We report that the spatiotemporal dynamics of strong regional synchronization measured as maximal EEG spectral power--referred to as activation--and strong regional desynchronization measured as minimal EEG spectral power--referred to as suppression--are characterized by the spatial segregation of small-scale and large-scale networks. Specifically, small-scale spectral-power activations and suppressions involving only 2-7% (1-4 of 60) of EEG scalp sites were prolonged (relative to stochastic dynamics) and consistently co-localized in a frequency specific manner. For example, the small-scale networks for{theta} , , {beta}1, and {beta}2 bands (4-30 Hz) consistently included frontal sites when the eyes were closed, whereas the small-scale network for{gamma} band (31-55 Hz) consistently clustered in medial-central-posterior sites whether the eyes were open or closed. Large-scale activations and suppressions involving over 17-30% (10-18 of 60) of EEG sites were also prolonged and generally clustered in regions complementary to where small-scale activations and suppressions clustered. In contrast, intermediate-scale activations and suppressions (involving 7-17% of EEG sites) tended to follow stochastic dynamics and were less consistently localized. These results suggest that strong synchronizations and desynchronizations tend to occur in small-scale and large-scale networks that are spatially segregated and frequency specific. These synchronization networks may broadly segregate the relatively independent and highly cooperative oscillatory processes while phase realignments fine-tune the network configurations based on behavioral demands.

neuroscience↗

bioRxiv2020

Visual speech differentially modulates beta, theta, and high gamma bands in auditory cortex

Speech perception is a central component of social communication. While principally an auditory process, accurate speech perception in everyday settings is supported by meaningful information extracted from visual cues (e.g., speech content, timing, and speaker identity). Previous research has shown that visual speech modulates activity in cortical areas subserving auditory speech perception, including the superior temporal gyrus (STG), potentially through feedback connections from the multisensory posterior superior temporal sulcus (pSTS). However, it is unknown whether visual modulation of auditory processing in the STG is a unitary phenomenon or, rather, consists of multiple temporally, spatially, or functionally distinct processes. To explore these questions, we examined neural responses to audiovisual speech measured from intracranially implanted electrodes within the temporal cortex of 21 patients undergoing clinical monitoring for epilepsy. We found that visual speech modulates auditory processes in the STG in multiple ways, eliciting temporally and spatially distinct patterns of activity that differ across theta, beta, and high-gamma frequency bands. Before speech onset, visual information increased high-gamma power in the posterior STG and suppressed beta power in mid-STG regions, suggesting crossmodal prediction of speech signals in these areas. After sound onset, visual speech decreased theta power in the middle and posterior STG, potentially reflecting a decrease in sustained feedforward auditory activity. These results are consistent with models that posit multiple distinct mechanisms supporting audiovisual speech perception and provide a crucial map for subsequent studies to identify the types of visual features that are encoded by these separate mechanisms.

neuroscience↗

bioRxiv2020

Probabilistic, entropy-maximizing control of large-scale neural synchronization

Oscillatory neural activity is dynamically controlled to coordinate perceptual, attentional and cognitive processes. On the macroscopic scale, this control is reflected in the U-shaped deviations of EEG spectral-power dynamics from stochastic dynamics, characterized by disproportionately elevated occurrences of the lowest and highest ranges of power. To understand the mechanisms that generate these low- and high-power states, we fit a simple mathematical model of synchronization of oscillatory activity to human EEG data. The results consistently indicated that the majority (~95%) of synchronization dynamics is controlled by slowly adjusting the probability of synchronization while maintaining maximum entropy within the timescale of a few seconds. This strategy appears to be universal as the results generalized across oscillation frequencies, EEG current sources, and participants (N = 52) whether they rested with their eyes closed, rested with their eyes open in a darkened room, or viewed a silent nature video. Given that precisely coordinated behavior requires tightly controlled oscillatory dynamics, the current results suggest that the large-scale spatial synchronization of oscillatory activity is controlled by the relatively slow, entropy-maximizing adjustments of synchronization probability (demonstrated here) in combination with temporally precise phase adjustments (e.g., phase resetting generated by sensorimotor interactions). Interestingly, we observed a modest but consistent spatial pattern of deviations from the maximum-entropy rule, potentially suggesting that the mid-central-posterior region serves as an "entropy dump" to facilitate the temporally precise control of spectral-power dynamics in the surrounding regions.

neuroscience↗

bioRxiv2020

Spectral-power associations reflect amplitude modulation and within-frequency interactions on the sub-second timescale and cross-frequency interactions on the seconds timescale

We investigated the global structure of intrinsic cross-frequency dynamics by systematically examining power-based temporal associations among a broad range of oscillation frequencies both within and across EEG-based current sources (sites). We focused on power-based associations that could reveal unique timescale dependence independently of interacting frequencies. Large spectral-power fluctuations across all sites occurred at two characteristic timescales, sub-second and seconds, yielding distinct patterns of cross-frequency associations. On the fast sub-second timescale, within-site (local) associations were consistently between pairs of {beta}-{gamma} frequencies differing by a constant {Delta}f (particularly {Delta}f [~] 10 Hz at posterior sites and {Delta}f [~] 16 Hz at lateral sites) suggesting that higher-frequency oscillations are organized into {Delta}f amplitude-modulated packets, whereas cross-site (long-distance) associations were all within-frequency (particularly in the >30 Hz and 6-12 Hz ranges, suggestive of feedforward and feedback interactions). On the slower seconds timescale, within-site (local) associations were characterized by a broad range of frequencies selectively associated with [~]10 Hz at posterior sites and associations among higher (>20 Hz) frequencies at lateral sites, whereas cross-site (long-distance) associations were characterized by a broad range of frequencies at posterior sites selectively associated with [~]10 Hz at other sites, associations among higher (>20 Hz) frequencies among lateral and anterior sites, and prevalent associations at [~]10 Hz. Regardless of timescale, within-site (local) cross-frequency associations were weak at anterior sites indicative of frequency-specific operations. Overall, these results suggest that the fast sub-second-timescale coordination of spectral power is limited to local amplitude modulation and insulated within-frequency long-distance interactions (likely feedforward and feedback interactions), while characteristic patterns of cross-frequency interactions emerge on the slower seconds timescale. The results also suggest that the occipital oscillations play a role in organizing higher-frequency oscillations into [~]10 Hz amplitude-modulated packets to communicate with other regions. Functional implications of these timescale-dependent cross-frequency associations await future investigations.

neuroscience↗

bioRxiv2019

EEG state-trajectory instability and speed reveal global principles of intrinsic spatiotemporal neural dynamics

Spatiotemporal dynamics of EEG/MEG (electro-/magneto-encephalogram) have typically been investigated by applying time-frequency decomposition and examining amplitude-amplitude, phase-phase, or phase-amplitude associations between combinations of frequency bands and scalp sites, primarily to identify neural correlates of behaviors and traits. Instead, we directly extracted global EEG spatiotemporal dynamics as trajectories of k-dimensional state vectors (k = the number of estimated current sources) to investigate potential global rules governing neural dynamics. We chose timescale-dependent measures of trajectory instability (approximately the 2nd temporal derivative) and speed (approximately the 1st temporal derivative) as state variables, that succinctly characterized trajectory forms. We compared trajectories across posterior, central, anterior, and lateral scalp regions as the current sources under those regions may serve distinct functions. We recorded EEG while participants rested with their eyes closed (likely engaged in spontaneous thoughts) to investigate intrinsic neural dynamics. Some potential global rules emerged. Time-averaged trajectory instability from all five regions tightly converged (with their variability minimized) at the level of generating nearly unconstrained but slightly conservative turns ([~]100{degrees} on average) on the timescale of [~]25 ms, suggesting that spectral-amplitude profiles are globally adjusted to maintain this convergence. Further, within-frequency and cross-frequency phase relations appear to be independently coordinated to reduce average trajectory speed and increase the variability in trajectory speed and instability in a relatively timescale invariant manner, and to make trajectories less oscillatory. Future research may investigate the functional relevance of these intrinsic global-dynamics rules by examining how they adjust to various sensory environments and task demands or remain invariant. The current results also provide macroscopic constraints for quantitative modeling of neural dynamics as the timescale dependencies of trajectory instability and speed are relatable to oscillatory dynamics.

neuroscience↗

bioRxiv2019

Neural, functional, and aesthetic impacts of spatially heterogeneous flicker: A potential role of natural flicker

Spatially heterogeneous flicker, characterized by probabilistic and locally independent luminance modulations, abounds in nature. It is generated by flames, water surfaces, rustling leaves, and so on, and it is pleasant to the senses. It affords spatiotemporal multistability that allows sensory activation conforming to the biases of the visual system, thereby generating the perception of spontaneous motion and likely facilitating the calibration of motion detectors. One may thus hypothesize that spatially heterogeneous flicker might potentially provide restoring stimuli to the visual system that engage fluent (requiring minimal top-down control) and self-calibrating processes. Here, we present some converging behavioral and electrophysiological evidence consistent with this idea. Spatially heterogeneous (multistable) flicker (relative to controls matched in temporal statistics) reduced posterior EEG (electroencephalography) beta power implicated in long-range neural interactions that impose top-down influences on sensory processing. Further, the degree of spatiotemporal multistability, the amount of posterior beta-power reduction, and the aesthetic responses to flicker were closely associated. These results are consistent with the idea that the pleasantness of natural flicker may derive from its spatiotemporal multistability that affords fluent and self-calibrating visual processing.

neuroscience↗