Anatomically Resolved Oscillatory Bursts Reveal Dynamic Motifs of Thalamocortical Activity During Naturalistic Stimulus Viewing
Research Background
The visual system is one of the most complex sensory systems in the mammalian brain, relying on the coordinated activity of multiple brain regions, particularly the information transfer between the thalamus and the primary visual cortex (V1). The processing of visual information involves not only the extraction of basic features such as luminance, contrast, and motion but also the simultaneous handling of multiple spatiotemporal features in complex natural scenes. Although previous studies have revealed many details about neuronal activity in the visual system, many questions remain unanswered regarding how visual information is dynamically encoded in the thalamocortical circuits, especially in the context of neural oscillations under natural visual stimuli.
Neural oscillations are a significant feature of brain activity, typically manifested as periodic fluctuations in the local field potential (LFP). These oscillations are believed to play a critical role in information transfer, feature encoding, and neural synchronization. However, most studies have focused on oscillatory activities under artificial stimuli (e.g., gratings or flashes), while the dynamics of oscillations under natural visual stimuli are less understood. Natural visual stimuli are non-stationary and complex, providing a more realistic simulation of daily visual experiences. Therefore, studying neural oscillations under natural stimuli holds substantial scientific significance.
The core question of this study is: How does the thalamocortical visual system in mice process complex visual input through fast neural oscillations during natural visual stimulation? Specifically, the researchers aimed to analyze local oscillatory activities in V1 to reveal how different visual features (e.g., luminance, contrast, motion) induce specific oscillatory patterns and explore how these patterns coordinate the activity of neurons across layers, thereby forming dynamic neural circuit motifs.
Source of the Paper
This paper was co-authored by Lukas Sebastian Meyerolbersleben, Anton Sirota, and Laura Busse, all affiliated with the Department of Neurobiology at Ludwig-Maximilians-Universität München in Germany. The paper was published on July 9, 2025, in the journal Neuron, titled “Anatomically Resolved Oscillatory Bursts Reveal Dynamic Motifs of Thalamocortical Activity During Naturalistic Stimulus Viewing.” The open-access version of the paper is available on Elsevier’s official website, with the DOI 10.1016/j.neuron.2025.03.030.
Research Process and Results
1. Research Process
This study is based on data from the Allen Institute’s Neuropixels Visual Coding Project, combining natural scenes and dynamic video stimuli to analyze local field potential (LFP) and neuronal activity in the mouse V1. The research process includes the following steps:
a) Data Collection and Preprocessing
The researchers used multi-channel Neuropixels probes to record neuronal activity in the mouse V1 and the dorsolateral geniculate nucleus (dLGN) of the thalamus. Experimental stimuli included full-screen flashes, natural images, and dynamic videos. LFP data were processed using multitaper spectral analysis to extract oscillatory activities in different frequency bands.
b) Oscillatory Burst Detection
To capture transient non-stationary oscillatory events, the researchers developed an algorithm based on local power maxima in time, frequency, and cortical depth to identify oscillatory bursts in V1. These bursts were classified into four categories: narrowband gamma (nb-gamma, 50-70 Hz), low-gamma (20-40 Hz), L4 epsilon (80-180 Hz), and L5 epsilon (100-180 Hz).
c) Visual Feature Extraction
The researchers extracted visual features such as local luminance, spatial frequency power, and optic flow from natural images and videos and analyzed their relationship with oscillatory bursts.
d) Neuronal Phase Coupling Analysis
By calculating the phase consistency between neuronal activity and LFP oscillations, the researchers analyzed the cross-layer neuronal activity patterns under different oscillatory burst categories. Additionally, current-source density (CSD) analysis was used to localize the current sources of oscillatory bursts.
2. Main Results
a) Relationship Between Oscillatory Bursts and Visual Features
The study found that different oscillatory burst categories were closely associated with specific visual features. Narrowband gamma bursts (nb-gamma) were significantly correlated with local luminance, while low-gamma bursts (low-gamma) were associated with optic flow (particularly moving edges). L4 and L5 epsilon bursts were related to local contrast (spatial frequency power).
b) Cross-Layer Neuronal Activity During Oscillatory Bursts
Oscillatory bursts were not confined to specific cortical layers but also coordinated the activity of neurons across layers. For example, narrowband gamma bursts were most prominent in L4 but also influenced neuronal activity in L2/3 and L5/6. Low-gamma bursts were primarily observed in L4 and L5, associated with the processing of moving edges.
c) Neuronal Phase Coupling Patterns
The study revealed phase preferences of neurons under different oscillatory burst categories. For instance, during narrowband gamma bursts, excitatory neurons in L4 fired during the early phase of the oscillation cycle, while inhibitory neurons fired slightly later. This phase separation pattern remained consistent across different stimulus conditions, suggesting it may represent a general neural circuit motif.
3. Conclusions and Significance
This study uncovered local oscillatory bursts in the mouse V1 under natural visual stimuli and their relationship with specific visual features, proposing the concept of “dynamic circuit motifs.” These motifs reflect the dynamic coordination mechanisms of the thalamocortical visual system in processing complex visual information, potentially supporting multiplexed visual information encoding and feature-specific information transfer.
The scientific value of this study lies in its systematic revelation of oscillatory activity patterns under natural visual stimuli and the proposal of phase coordination mechanisms in cross-layer neuronal activity. This not only deepens our understanding of the visual system’s functionality but also provides a new framework for future research, such as decoding visual content through oscillatory activities or developing oscillation-based brain-computer interfaces.
Research Highlights
- Oscillatory Activity Under Natural Visual Stimuli: This study is the first to systematically analyze local oscillatory bursts in V1 under natural visual stimuli, revealing their relationship with visual features such as luminance, contrast, and motion.
- Dynamic Circuit Motifs: The concept of “dynamic circuit motifs” was introduced, describing the phase coordination mechanisms of cross-layer neuronal activity under different oscillatory burst categories.
- Potential for Cross-Species Comparisons: The findings provide a new framework for comparing oscillatory activities in the visual systems of different species, potentially uncovering common principles in visual information processing.
Additional Valuable Information
The code and data from this study have been made publicly available for further analysis and verification by other researchers. Additionally, the study suggests future research directions, such as using multi-probe recording techniques to investigate the oscillatory coordination mechanisms of distributed neurons and employing closed-loop experiments to reveal the roles of specific neuronal types in oscillation generation and propagation.
Through this research, we have gained a deeper understanding of the dynamic functionality of the visual system and provided new tools and perspectives for future neuroscience studies.