Phase of Neural Oscillations as a Reference Frame for Attention-Based Routing in Visual Cortex

Phase of Neural Oscillations and Attention Switching One of the key issues in understanding the visual system’s selective attention is how it optimizes the perception and processing of visual information in specific behavioral contexts. Although previous research has analyzed the pivotal role of individual neuron firing rates in information transmission, our understanding remains limited regarding how the activity of single neurons effectively represents and transmits attention signals in relation to neighboring neural networks. This study hypothesizes that the phase of neural oscillations relative to the neighboring network acts as a reference framework for attention switching, possibly playing a significant role in the visual cortex. A series of experiments were conducted to test this hypothesis.

Source of the Paper

This paper is jointly authored by Ehsan Aboutorabi (Schulich School of Medicine and Dentistry, Robarts Research Institute), Sonia Baloni Ray (Indraprastha Institute of Information Technology), Daniel Kaping (Helmholtz Centre for Environmental Research), Farhad Shahbazi (Isfahan University of Technology), Stefan Treue (German Primate Center, University of Goettingen), and Moein Esghaei (Westa Higher Education Center, German Primate Center). On December 23, 2023, this paper was published in the renowned journal “Progress in Neurobiology” and is available online.

Research Process

Subjects and Task

The subjects of the study were two macaque monkeys (Macaca mulatta). The experiment involved head-fixed monkeys performing a visual attention task in front of a display. During the task, the monkeys had to focus on a central fixation point and shift their attention to a specific spiral motion pattern based on instructions to receive a liquid reward. Local field potentials (LFPs) and single-cell activity in the monkeys’ visual cortex were recorded to analyze the relationship between neuronal activity and LFP phase.

Data Recording and Processing

  1. Data Recording: Neuronal activity was recorded using a tri-channel microdrive system at a sampling frequency of 40kHz.
  2. LFP and Unit Activity Analysis: Recorded LFPs were frequency-filtered, and phase distributions in different frequency bands were analyzed. Additionally, neuronal spikes were compared with the corresponding LFP phases in those frequency bands.
  3. Adaptive Neural Delay Model: A computational model containing sensory and regulatory subnetworks was established. By adjusting synaptic delays, the effect of different synaptic delays on neuronal phase preference values was evaluated.

Experimental Steps

The experimental steps included training the monkeys to perform the visual attention task, recording local field potentials and single-cell activity in the visual cortex MST area, and analyzing the phase distribution of neural spikes in different LFP frequency bands under attention conditions. Furthermore, computational models were used to simulate the effect of synaptic delays on phase encoding.

Main Research Results

  1. Neuronal Phase Locking: It was found that neurons significantly lock to the β oscillations in the surrounding network at 20Hz ~ 24Hz. When monkeys focused their attention within the receptive field of neurons, the locking phase shifted to a later stage, correlating positively with the speed of visual change reporting.
  2. Support from Computational Models: Model results indicated that neuronal coupling with LFP β oscillation phase can be manipulated by setting different synaptic delays, verifying the effectiveness of the new method.
  3. Phase Dependence of Spatial Attention: The study demonstrated that the spatial allocation of attention significantly modulates the phenomenon of neuronal phase locking, with this modulation having predictive effects on response time performance.

Conclusion and Research Value

This study reveals the phenomenon of neuronal spikes locking to the phase of nearby network LFP β oscillations within the visual cortex MST area of monkeys and emphasizes the crucial role of spatial attention in phase encoding. This finding helps in understanding how selective attention optimizes attention-related visual information transmission through phase locking mechanisms and provides new insights into how high-level cortical regions decode attentional focus.

Research Highlights

  1. New Phase Encoding Mechanism: The study first proposed and verified a new method of manipulating LFP β oscillation phase coupling by adjusting synaptic delays.
  2. Combination of Theoretical Support and Experimental Verification: The study effectively supported the hypothesis through a combination of behavioral experiments and computational model verification.

Research Significance

By revealing the phenomenon of neuronal phase locking relative to LFP in the visual cortex, this study provides a new perspective on understanding the neural mechanisms of selective attention, especially how neural oscillation phase can be used as a reference framework to improve the efficiency of related information transmission. This has important implications for the future development of new neural rehabilitation and enhancement technologies and optimizing artificial neural networks.

Appendix

This study was supported by the Deutsche Forschungsgemeinschaft, and the data can be publicly accessed through figshare. The authors express their gratitude for technical support from Jinghe, Beatrix Glaser, Dirk Prüsse, among others.


This report provides a detailed analysis and summary of the paper “Phase of neural oscillations as a reference frame for attention-based routing in visual cortex,” showcasing the phase encoding mechanism of selective attention in the visual cortex of monkeys and its impact on information transmission, thus offering valuable data and theoretical support for future research in this field.