Biology subjects

Sermet, B. S.

Publications and source records attributed to Sermet, B. S..

6 recordsLinked to original sources

bioRxiv2026

Synaptic dynamics as a tunable substrate shaping neuronal activity sequences

A central tenet of cerebellar computation posits that granule cells generate sparse spatiotemporal activity patterns that support precisely timed motor and cognitive outputs. Using high-speed in vivo calcium and glutamate imaging combined with slice electrophysiology, we show that heterogeneous synaptic dynamics transform mossy fiber inputs into temporally sparse, sequential patterns of GC activity. Region-specific differences in MF glutamate release shape GC response duration and sparsity, tuning the temporal statistics of population sequences to match sensorimotor associative learning demands. These findings provide direct evidence for temporally sparse GC sequences and establish synaptic dynamics as a ubiquitous, tunable mechanism structuring neural activity in time.

neuroscience↗

bioRxiv2025

Dopaminergic Control of Retinal Oscillations Driving Infantile Nystagmus

Infantile nystagmus is a debilitating involuntary eye movement disorder often associated with retinal diseases such as Congenital Stationary Night Blindness (CSNB). The oscillating eye movements of infantile nystagmus come with reduced visual acuity, strongly impairing quality of life. No cure exists for this condition. Previously, we demonstrated that nystagmus in the CSNB mouse model Nyxnob has a retinal cause. Specifically, we found that synchronized oscillations of retinal ganglion cells (RGCs) are transmitted to the accessory optic system, triggering compensatory eye movements. The RGC oscillations appear to originate from a specific retinal cell type, the AII amacrine cell (AII AC), making these cells the preferred target for treatment. Here we found that pharmacologically activating the dopaminergic input to AII ACs in Nyxnob mice completely suppresses the pathological oscillations of both AII ACs and RGCs and improves the signal fidelity of RGCs. Moreover, our retinal network simulations confirm that the experimentally observed changes to AII AC voltage-gated currents are sufficient to account for the dopamine-dependent abolishment of these oscillations. Our findings provide a novel mechanistic understanding of the retinal mechanism underlying infantile nystagmus as well as the associated low visual performance. Consequently, they offer the first pharmacological therapeutic strategy for this disorder. SignificanceOscillatory eye movements in infantile nystagmus arise from abnormal retinal activity, yet the cellular basis of this instability has remained unclear. Here we show that this abnormal activity stems from disrupted dopaminergic modulation. By defining how dopamine regulates the activity of a key retinal cell type, the AII amacrine cell, we demonstrate that restoring dopamine levels can return the retinal circuit to a stable state and improve the clarity of visual signals leaving the eye. This work links neuromodulation to retinal circuit instability and identifies dopaminergic control of AII amacrine cells as a pharmacologically targetable point of intervention. These findings suggest a retina-focused pharmacological treatment strategy for infantile nystagmus, a disorder that currently lacks effective therapeutic options.

neuroscience↗

bioRxiv2025

The Rod Bipolar Cell Pathway Contributes To Surround Responses In OFFRetinal Ganglion Cells

Sensory neurons can be influenced by stimuli beyond their receptive field center, yet the mechanisms underlying this surround modulation remain poorly understood. In the retina, many OFF ganglion cells exhibit responses to ON stimulation outside their receptive field center. However, disentangling the pathways and cell types contributing to these responses has been challenging with traditional experimental approaches. Here, we combined optogenetics, two-photon holographic stimulation, and multi-electrode array recordings to identify the intermediate retinal cell types involved in this circuit. We found that the pathway formed by rod bipolar cells and AII amacrine cells--one of the primary relays of rod-driven signals under low-light conditions--plays a key role in mediating this surround modulation. Specifically, crossover inhibition exploits the same amacrine cells responsible for surround suppression to disinhibit distant ganglion cells. This suggests that the retina repurposes existing circuits for surround modulation, optimizing resources through multifunctional inhibitory pathways.

neuroscience↗

bioRxiv2025

Precise calcium-to-spike inference using biophysical generative models

The intramolecular dynamics of fluorescent calcium indicators distort the relationship between calcium signals and action potentials ("spikes"), hampering efficient spike inference from calcium imaging. To address this problem, we characterized the calcium response kinetics of three widely used indicators, GCaMP6f, jGCaMP7f, and jGCaMP8f, using in vitro stopped-flow measurements and brain slice recordings. We identify previously unreported kinetic features, including use-dependent slowing of fluorescence decay, that introduce systematic errors in linear model-based inference methods. Using these observations, we developed a multistate model of GCaMP and used it to create biophysically-inspired Bayesian Sequential Monte Carlo and machine learning inference models trained on synthetic datasets. These methods outperform existing methods on spike timing accuracy and correlation benchmarks derived from diverse cell types. Our results show that using synthetic data derived from our biophysical model yields a decoder that outperforms even those trained on extensive experimental data. By separating indicator characterization from inference, our framework, Calcium Spike Processing using Integrated Kinetic Estimation and Simulation (C-SPIKES), provides a generalizable strategy applicable to existing and future calcium indicators.

neuroscience↗

bioRxiv2023

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

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 enable the retina to signal an omitted stimulus in a flash sequence. 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. We also generated new predictions with this model, that we confirmed experimentally. Depressing inhibitory synapses could thus be a key component to generate the predictive responses observed in many brain areas.

neuroscience↗

bioRxiv2022

High frequency spike inference with particle Gibbs sampling

Calcium-sensitive fluorescent indicators enable monitoring of spiking activity in large neuronal populations in animal models. Despite the plethora of algorithms developed over the past decades, accurate spike-time inference methods for spike rates exceeding 20 Hz are lacking. More importantly, little attention has been devoted to the quantification of statistical uncertainties in spike time estimation, which is essential for assigning confidence levels to inferred spike patterns. To address these challenges, we introduce (1) a statistical model that accounts for bursting neuronal activity and baseline fluorescence modulation and (2) apply a Monte Carlo strategy (particle Gibbs with ancestor sampling) to estimate the joint posterior distribution of spike times and model parameters. Our method is competitive with state-of-the-art supervised and unsupervised algorithms, as evaluated on the CASCADE benchmark datasets. Analysis of fluorescence transients recorded with the ultrafast genetically encoded calcium indicator GCaMP8f demonstrates that our method can resolve interspike intervals as short as 5 ms. Overall, our study describes a Bayesian inference method for detecting neuronal spiking patterns and quantifying their uncertainty. The use of particle Gibbs samplers enables unbiased estimates of spike times and all model parameters, and provides a flexible statistical framework for testing more specific models of calcium indicators.

neuroscience↗