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Author

Rafael Yuste

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Open access Aug 2026

Highly attenuated dendritic propagation of isolated synaptic potentials in vivo

The integration of synaptic inputs is a fundamental function of neurons. In the traditional model, excitatory inputs are summed at the soma to generate action potentials. However, how synaptic inputs are integrated by dendrites in vivo remains poorly explored. We used intravital two-photon dendritic imaging with a genetically encoded voltage indicator (accelerated sensor of action potentials 5) together with somatic whole-cell patch clamp recordings to investigate how synaptic depolarizations are transferred to the soma in pyramidal neurons of the mouse somatosensory cortex. We studied the integration of synaptic inputs under spontaneous and sensory-evoked conditions, as well as following electrical and optogenetic stimulation. In all cases, while multiple inputs evoked measurable depolarizations in the cell body, isolated synaptic potentials were strongly attenuated. Our results suggest that isolated synaptic inputs have a minimal contribution to somatic depolarization, whereas coincident inputs within short temporal windows are more effective, indicating a regime of dendritic integration that favors coincident or clustered neuronal activity in cortical networks.

V. Cornejo, Boris Bouazza-Arostegui, Tzitzitlini Alejandre-García et al. · 0 citations
Open access Aug 2026

Protocol for analyzing slow cortical dynamics in mouse neuronal recordings

Summary Temporal information processing is critical for brain function, supporting neural computations such as novelty detection, adaptation, and temporal normalization. Its disruption is implicated in schizophrenia. We present a protocol for analyzing ongoing neuronal network activity using binwise decoding, trial-to-trial variability analysis, and estimation of network-intrinsic timescales (INTs). We apply these techniques to identify slow dynamics that encode the memory of recent stimuli in neuronal populations in the mouse auditory cortex and in artificial neural networks trained on a novelty-detection task. For complete details on the use and execution of this protocol, please refer to Shymkiv et al.1

Yuriy Shymkiv, Rafael Yuste · 0 citations

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