P137 Coordinated Multi-frequency Oscillatory Bursts Enable Time-structured Dynamic Information Transfer
Jung Young Kim*1, Jee Hyun Choi1, Demian Battaglia*2
1Korea Institute of Science and Technology (KIST), Seoul, South Korea
2Functional System Dynamics / LNCA UMR 7364, University of Strasbourg, France
*Email: jungyoungk51@kist.re.kr; dbattaglia@unistra.fr
Introduction
Slower (e.g., beta) and faster (e.g., gamma) oscillatory bursts have been linked to multiplexed neural communication, respectively relaying top-down expectations and bottom-up prediction errors [1,2]. These signals target distinct cortical layers with different dominant frequencies [3]. However, this theory faces challenges: multiplexed routing might not require distinct frequencies [4], and phasic enhancement from slow oscillations may be too sluggish to modulate faster oscillatory processes. What fundamental functional advantage, then, could multi-frequency oscillatory bursting offer?
Methods
We investigate information transfer between two neural circuits (e.g., different cortical layers or regions) generating sparsely synchronized, transient oscillatory bursts with distinct intrinsic frequencies in spiking neural networks [5]. Through a systematic parameter space exploration, guided by unsupervised classification, we uncover a diverse range of Multi-Frequency Oscillatory Patterns (MFOPs). These include configurations in which the populations emit bursts at their natural frequencies, deviating from them, or even at more than one frequency simultaneously or sequentially. We then use transfer entropy [6] between simulated multi-unit activity and analyses of single unit spike transmission to assess functional interactions.
Results
We demonstrate that distinct MFOPs correspond to different Information Routing Patterns (IRPs), dynamically boosting or suppressing transfer in different directions at precise times, forming thus specific temporal graph motifs. Notably, the “slow” population can send information with latencies shorter than a fast oscillation period and also affect multiple faster cycles within a single slow cycle. Supported by precise analyses of the spiking dynamics of synaptically-coupled single neurons, we propose that MFOPs act as complex "attention mechanisms" (in the sense of ANNs) as they provide a controllable way to selectively weight the relevance of different incoming inputs, as a function of their latencies relative to currently emitted spikes.
Discussion
Our findings show that the coexistence and coordination of oscillatory bursts at different frequencies enables rich, temporally-structured choreographies of information exchange, moving well beyond simple multiplexing (one direction = one frequency). The presence of multiple frequencies considerably expands the repertoire of possible space-time information transfer patterns, providing a resource that could be harnessed to support distinct functional computations. Notably, multi-frequency oscillatory bursting could provide a self-organized manner to tag spiking activity with sequential context information, reminiscent of attention masks in transformers or other ANNs.
Figure 1. A) Networks of spiking neurons with "hardwired" slow and fast oscillatory frequencies. B) Because of network interactions, these networks develop MFOPs with different frequency properties bypassing frequency hardwiring. We extract these bursting events (C) and show that they systematically correspond to spatiotemporal motifs of information transfer (D), aka Information Routing Patterns (IRPs)
Acknowledgements
STEAM Global (Korea Global Cooperative Convergence Research Program)
References[1] Bastos, A.M., et al. (2015). Neuron 85, 390. [2] Bastos, A. M., et al. (2020) Proc Natl Ac Sci 117, 31459. [3] Mendoza-Halliday, D., et al. (2024) Nature Neurosci 27, 547. [4] Battaglia, D., et al. (2012). PLoS Comp Biol 8, e1002438. [5] Wang, X.J., and Buzsáki, G.B. (1996). J Neurosci 16, 6402–6413. [6] Palmigiano, A., et al. (2017). Nat Neurosci 20, 1014.
