P042 Feedforward and Feedback Inhibition Flexibly Modulates Theta-Gamma Cross-Frequency Interactions in Neural Circuits
Dimitrios Chalkiadakis*1,2, Jaime Sánchez-Claros1, Víctor J López-Madrona3, Santiago Canals2, Claudio R. Mirasso1
1Instituto de Física Interdisciplinar y Sistemas Complejos (IFISC),Consejo Superior de Investigaciones Científicas (CSIC) - Universitat de les Illes Baleares(UIB), Palma de Mallorca, Spain
2Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas (CSIC) - Universidad Miguel Hernández (UMH), Sant Joan d’Alacant, Spain
3Institut de Neurosciences des Systèmes, Aix Marseille Univ -Inserm,Marseille, France
*Email:dimitrios@ifisc.uib-csic.es
Introduction
Brain rhythms are essential for coordinating neuronal activity. Cross-frequency coupling (CFC), particularly between theta (~8 Hz) and gamma (~30 Hz) rhythms, is critical for memory formation [1]. Traditionally, CFC was attributed to slow oscillations modulating faster activity at specific phases. However, metrics such as Cross-Frequency Directionality (CFD) have revealed bidirectional interactions, with both slow-to-fast and fast-to-slow influences [1, 2]. Here, we introduce a computational circuit model that flexibly exhibits both directionality interactions based on the balance of inhibitory feedforward and feedback motifs. Our framework is supported by electrophysiology measurements in the rat’s hippocampus.
MethodsWe analyzed two motifs based on variations of the (Pyramidal) Interneuron Network Gamma (PING/ING) models, both of which generate gamma rhythms through interactions between pyramidal cells (PCs) and inhibitory basket cells (BCs). An external theta drive modulatedthe network’s activity, inducing cross-frequency interactions (see Fig. 1). Somatic transmembrane currents were computed for cross-frequency dynamics analysis.Our model was validated using the experimental dataset presented in [1], which includes a detailed analysis of pathway-specific field potentials reflecting the activity of Entorhinal Cortex layer III (ECIII) projections to the hippocampal CA1 area in rats navigating both familiar and novel environments.
Results
Our analysis revealed that in θ-ING motifs, feedforward recruitment of BCs drives gamma-to-theta directionality (CFD<0), while in θ-PING motifs, feedback inhibition favors theta-to-gamma directionality (CFD>0, Fig. 1b-iii vs 1c-iii). In combined motifs, varying synaptic strengths within realistic ranges, we found smooth transitions between directionalities (Fig. 1d). Experimental data validated our framework, as behavioral conditions modulated CFD and gamma frequency in line with our model predictions (Fig. 1e). Finally, by evaluating each motif’s capacity to integrate distinct inputs impinging at different sites of the PC dendritic tree, we report their differential role in prioritizing transmission across different information channels.
Discussion
Our framework suggests that feedforward/feedback inhibitory balance regulates the directionality of theta-gamma interactions. Notably, θ-ING/θ-PING modes exist along a continuum rather than as distinct alternatives. In our model, CFD analysis identified transitions between functional modes, aligning with experimental observations across different behavioral states.
We further showed that a feedback-shifted balance promotes strong afferent-driven cross-frequency rhythmicity, while a feedforward-shifted motif broadens encoding windows,favoring parallel pathway transmission. Thus, dynamic CFD measures may reflect predominant inhibitory motifs and flexible prioritization of functional connectivity pathways.
Figure 1. Figure 1. (a) Motifs’ connections with dashed lines differentiating θ-ING (purple) from θ-PING (blue). (b, c) Cross-frequency interactions in θ-ING and θ-PING. (i) Transmembrane currents (gray) with PC/BC spikes in blue/orange. (ii) Cross-frequency coupling. (iii) CFD. (d) Mixed θ-ING/θ-PING motifs show CFD changes inversely to peak γ. (e) Experiments confirm the CFD–γ peak relationship of (d).
AcknowledgementsD. C., J. C. and C. M. acknowledge support from the Spanish Ministerio de Ciencia, Innovación y Universidades through projects PID2021-128158NB-C22 and María de Maeztu CEX2021-001164-M. D. C. and S. C. acknowledge support from the Spanish Ministerio de Ciencia, Innovación y Universidades through projects PID2021-128158NB-C21 and Severo Ochoa CEX2021-001165-S
References
[1] López-Madrona, V. J., Pérez-Montoyo, E., Álvarez-Salvado, E., Moratal, D., Herreras, O., Pereda, E., … Canals, S. (2020). Different Theta Frameworks Coexist in the Rat Hippocampus and Are Coordinated during Memory-Guided and Novelty Tasks.eLife,9, e57313. doi:10.7554/eLife.57313
[2] Jiang, H., Bahramisharif, A., Van Gerven, M. A. J., & Jensen, O. (2015). Measuring Directionality between Neuronal Oscillations of Different Frequencies.NeuroImage,118, 359–367. doi:10.1016/j.neuroimage.2015.05.044
