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Macroscopic Traveling Waves Dominate Human Cortical Phase Dynamics Across Frequencies


Temel Kavramlar
Low spatial frequency phase dynamics, manifesting as macroscopic traveling waves, dominate human cortical activity across a wide range of temporal frequencies, suggesting a critical role in global brain function and challenging previous interpretations based on localized activity.
Özet
  • Bibliographic Information: This content appears to be extracted from a research paper, but the bibliographic information is not provided in the XML.
  • Research Objective: The study aims to quantify the contribution of low spatial frequency components, particularly macroscopic traveling waves, to the overall spectrum of cortical phase dynamics across different temporal frequencies.
  • Methodology: Researchers analyzed a publicly available stereotactic EEG dataset (RAM Public Data) from 11 participants. They employed a novel method involving complex-valued phase analysis, higher-order singular value decomposition (HOSVD), and the construction of equilateral triangle sets from electrode contacts to estimate the spatial frequency spectrum of phase dynamics.
  • Key Findings:
    • The spatial power of cortical phase dynamics is highest at the lowest spatial frequencies (longest wavelengths), indicating the dominance of macroscopic traveling waves.
    • This dominance persists across a wide range of temporal frequencies, from delta (2Hz) to high gamma (100Hz).
    • The peak spatial frequency is constrained by the size of the recording array, suggesting even larger wavelengths might be present at the whole-cortex level.
    • Macroscopic phase dynamics exhibit narrowband temporal frequency correlations compared to more broadband correlations in mesoscopic dynamics.
  • Main Conclusions:
    • Macroscopic traveling waves are not artifacts of volume conduction or localized activity but represent a dominant mode of cortical organization.
    • These findings challenge previous interpretations of extracranial measurements and highlight the importance of large-scale cortical dynamics for understanding brain function.
    • The dominance of low spatial frequencies suggests that local cortical activity is strongly influenced by global phase organization.
  • Significance:
    • This research provides new insights into the large-scale organization of brain activity and the role of traveling waves in cortical communication.
    • It has implications for understanding the functional significance of different temporal frequency bands and their interaction with spatial scales.
    • The findings emphasize the need to consider global brain dynamics in interpreting neuroimaging data.
  • Limitations and Future Research:
    • The study was limited by the irregular and incomplete coverage of the cortex by stereotactic EEG electrodes.
    • Future research should investigate the functional consequences of the observed dominance of macroscopic traveling waves.
    • Exploring the relationship between macroscopic phase dynamics and specific cognitive processes is crucial.
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Kaynak

İstatistikler
The study analyzed data from 11 participants with sufficient grey-matter electrode coverage. Phase dynamics were analyzed at 36 center frequencies, logarithmically spaced from 1.0 to 128.0 Hz. Short time-window Morlet wavelets (2 cycles) were used for phase estimation. The study found that the spatial power of phase dynamics decreased monotonically with increasing spatial frequency. The peak spatial frequency was found to be dependent on the maximum size of the contact array. Macroscopic phase dynamics showed narrower cross-frequency correlations compared to mesoscopic dynamics.
Alıntılar
"Low spatial frequency activity dominates the cortical phase dynamics; most of the spatial power is at the longest wavelengths." "This means either the results were biased by a low pass filter, or had a maximum measurable spatial frequency below the macroscopic range, respectively." "The present results are therefore consistent with the existence of macroscopic TWs in the cortex (Figure 1D) and not with the alternative hypotheses for the measurement of these waves extra-cranially (Figure 1E & F)."

Daha Derin Sorular

How might the understanding of macroscopic traveling waves impact the development of brain-computer interfaces or neuromodulatory therapies?

Answer: The dominance of macroscopic traveling waves (TWs) in cortical communication opens exciting avenues for brain-computer interfaces (BCIs) and neuromodulatory therapies. Here's how: Improved Signal Detection and Decoding for BCIs: Current BCIs primarily rely on localized activity. Recognizing the significance of global phase dynamics, particularly the low spatial frequency components, could lead to more robust signal detection. By incorporating algorithms that account for these macroscopic waves, BCIs could decode intentions and commands more accurately, even from limited sensor arrays. Targeted Neuromodulation: Understanding the spatial and temporal characteristics of macroscopic TWs could enable more precise and effective neuromodulation. Techniques like transcranial magnetic stimulation (TMS) or transcranial electrical stimulation (tES) could be tailored to interact with these waves, either amplifying beneficial patterns or disrupting pathological ones. This could lead to novel treatments for neurological and psychiatric disorders. Closed-Loop Systems: The predictive capacity of TWs, as highlighted in the context, could be harnessed for closed-loop neuromodulation. By monitoring these waves in real-time, therapeutic interventions could be dynamically adjusted to maintain a desired brain state. This personalized approach could optimize treatment outcomes. Biomarker Development: Alterations in macroscopic TWs might serve as biomarkers for disease states. Characterizing these changes could aid in early diagnosis, monitoring disease progression, and evaluating treatment efficacy. However, several challenges need to be addressed: Measurement Techniques: Capturing the full complexity of macroscopic TWs requires high spatial resolution and coverage. While the study used stereotactic EEG, less invasive techniques with comparable capabilities are needed for wider clinical application. Individual Variability: The study hints at individual differences in TW patterns. Understanding this variability is crucial for tailoring BCIs and neuromodulatory therapies to individual patients. Functional Significance: While the study establishes the dominance of low spatial frequencies, further research is needed to elucidate the precise functional roles of different TW patterns.

Could there be alternative explanations, beyond the resolution limits of previous studies, for the apparent dominance of low spatial frequencies in cortical phase dynamics?

Answer: While the study presents compelling evidence for the dominance of low spatial frequencies in cortical phase dynamics, it's prudent to consider alternative explanations: Volume Conduction Bias: Even with stereotactic EEG, volume conduction can still influence recordings, potentially overestimating the contribution of low spatial frequencies. While the study used white matter referencing to mitigate this, it might not be entirely eliminated. Cortical Folding: The complex folding patterns of the cortex could lead to spurious correlations between distant regions, artificially inflating low spatial frequency power. Advanced computational modeling that accounts for cortical geometry is needed to address this. Behavioral State Dependence: The study used data from a memory task. Macroscopic TW patterns might vary across different behavioral states (e.g., sleep, wakefulness, attention). The observed dominance might be specific to the task or state under investigation. Developmental and Aging Effects: Cortical dynamics change throughout the lifespan. The dominance of low spatial frequencies might be more pronounced at certain ages, reflecting developmental or aging-related changes in brain connectivity. Undersampled High Spatial Frequencies: It's theoretically possible that very high spatial frequency activity, beyond the resolution of current techniques, exists and plays a significant role. Novel measurement approaches with even finer spatial resolution are needed to explore this possibility. Further research should investigate these alternative explanations to confirm the robustness of the findings and refine our understanding of cortical phase dynamics.

If the brain prioritizes energy efficiency, what evolutionary advantage might be conferred by the dominance of macroscopic traveling waves in cortical communication?

Answer: The brain is an energy-intensive organ, and efficient information processing is crucial for survival. The dominance of macroscopic traveling waves in cortical communication, despite their seemingly global nature, could offer several evolutionary advantages: Rapid Information Integration: Macroscopic TWs could facilitate rapid information transfer across distant brain regions. This global synchronization might be crucial for tasks requiring swift responses to environmental stimuli, such as threat detection or prey capture. Flexible Network Configuration: By dynamically altering their spatial and temporal properties, macroscopic TWs could support flexible network configurations. This adaptability might be advantageous in complex and changing environments, allowing the brain to rapidly switch between different processing modes. Reduced Wiring Cost: While counterintuitive, coordinating activity through global waves might be more metabolically efficient than maintaining a dense network of point-to-point connections. This "wireless" communication strategy could minimize wiring costs and energy expenditure. Noise Reduction: Macroscopic TWs might enhance signal-to-noise ratios by amplifying relevant signals and suppressing background noise. This could be particularly important for processing weak or ambiguous sensory information. Synchronization for Plasticity: Coordinated activity through macroscopic TWs might facilitate synaptic plasticity, the brain's ability to change and adapt. This could underlie learning and memory processes, crucial for survival in dynamic environments. In essence, the brain might have evolved to leverage the efficiency of macroscopic TWs for coordinating activity across its vast network, striking a balance between global integration and local processing demands. This strategy could provide a significant evolutionary advantage by enabling rapid, flexible, and energy-efficient information processing.
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