Temporal pattern recognition in retinal ganglion cells is mediated by dynamical inhibitory synapses

• Published in: Nature communications 2024-07, Vol.15 (1), p.6118-14, Article 6118
• Main Authors: Ebert, Simone, Buffet, Thomas, Sermet, B.Semihcan, Marre, Olivier, Cessac, Bruno
• Format: Article
• Language: English
• Subjects: 631/378/2591; 631/378/2613/1786; 631/378/2613/2615; 631/378/3920; Animals; Brain; Humanities and Social Sciences; Latency; Life Sciences; Mice; Models, Neurological; multidisciplinary; Neural Inhibition - physiology; Neural networks; Neurobiology; Neurogenesis; Neurons and Cognition; Pattern recognition; Performance prediction; Photic Stimulation; Predictions; Retina; Retina - physiology; Retinal ganglion cells; Retinal Ganglion Cells - physiology; Science; Science (multidisciplinary); Sensory neurons; Shape recognition; Stimuli; Synapses; Synapses - physiology
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-024-50506-7

A fundamental task for the brain is to generate predictions of future sensory inputs, and signal errors in these predictions. Many neurons have been shown to signal omitted stimuli during periodic stimulation, even in the retina. However, the mechanisms of this error signaling are unclear. Here we show that depressing inhibitory synapses shape the timing of the response to an omitted stimulus in the retina. While ganglion cells, the retinal output, responded to an omitted flash with a constant latency over many frequencies of the flash sequence, we found that this was not the case once inhibition was blocked. We built a simple circuit model and showed that depressing inhibitory synapses were a necessary component to reproduce our experimental findings. A new prediction of our model is that the accuracy of the constant latency requires a sufficient amount of flashes in the stimulus, which we could confirm experimentally. Depressing inhibitory synapses could thus be a key component to generate the predictive responses observed in the retina, and potentially in many brain areas. The retina is known to strongly respond to omitted stimuli in periodic patterns. Here the authors propose that depressing inhibitory synapses shape the timing of such a response and are key to perform temporal pattern recognition in neural networks.