Resonating neurons stabilize heterogeneous grid-cell networks
- Indian Institute of Science, Bangalore, India
Abstract
A central theme that governs the functional design of biological networks is their ability to sustain stable function despite widespread parametric variability. Here, we investigated the impact of distinct forms of biological heterogeneities on the stability of a two-dimensional continuous attractor network (CAN) implicated in grid-patterned activity generation. We show that increasing degrees of biological heterogeneities progressively disrupted the emergence of grid-patterned activity and resulted in progressively large perturbations in low-frequency neural activity. We postulated that targeted suppression of low-frequency perturbations could ameliorate heterogeneity-induced disruptions of grid-patterned activity. To test this, we introduced intrinsic resonance, a physiological mechanism to suppress low-frequency activity, either by adding an additional high-pass filter (phenomenological) or by incorporating a slow negative feedback loop (mechanistic) into our model neurons. Strikingly, CAN models with resonating neurons were resilient to the incorporation of heterogeneities and exhibited stable grid-patterned firing. We found CAN networks with mechanistic resonators to be more effective in targeted suppression of low-frequency activity, with the slow kinetics of the negative feedback loop essential in stabilizing these networks. As low-frequency perturbations (1/f noise) are pervasive across biological systems, our analyses suggest a universal role for mechanisms that suppress low-frequency activity in stabilizing heterogeneous biological networks.
Data availability
All data generated or analyzed during this study are included in the manuscript and supporting files. Source code employed for simulations are uploaded.
Article and author information
Author details
Rishikesh Narayanan
Funding
The Wellcome Trust DBT India Alliance (Senior Fellowship IA/S/16/2/502727)
- Rishikesh Narayanan
Human Frontier Science Program (Career development award)
- Rishikesh Narayanan
Department of Biotechnology, Ministry of Science and Technology, India (DBT-IISc partnership Program)
- Rishikesh Narayanan
Revati and Satya Nadham Atluri Chair (Chair Professorship)
- Rishikesh Narayanan
Ministry of Human Resource Development (Scholarship funds)
- Divyansh Mittal
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Mittal & Narayanan
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Resonating neurons stabilize heterogeneous grid-cell networks
eLife 10:e66804.
https://doi.org/10.7554/eLife.66804
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