id_998. A HIGH-DENSITY ELECTROPHYSIOLOGICAL FRAMEWORK FOR POPULATION-LEVEL CHARACTERIZATION OFD SPINAL SENSORY NEURONS IN VIVO
Joanna Bernacka1, Eliza Kramarska2, Mateusz W. Kucharczyk1,,2,,3
1 Cancer Neurophysiology Research Group, Polish Centre for Technology Development, Łukasiewicz-PORT, Wrocław, PL
2 Biophotonics and Electrophysiology Lab, Bioimaging Laboratories, Center for the Development of Therapies for Civilization and Age-Related Diseases, Jagiellonian University Medical College, Kraków, PL
3 Wolfson Sensory, Pain and Regeneration Centre, King’s College London, UK
INTRODUCTION: Spinal dorsal horn is the first central stage of somatosensory integration, where peripheral inputs and intensity are transformed into ascending signals. While individual spinal neurons have been extensively studied, the population-level encoding of sensory information across dorsal horn laminae remains less studied. Single-unit recordings limit insight into how spinal neurons collectively represent stimulus features. We decided to use high-density electrophysiological recordings for sampling of large neuronal ensembles, enabling investigation of spinal sensory processing at the population level.
AIM(S): To establish a high-density in vivo framework for investigating population-level sensory encoding in the mouse spinal dorsal horn.
METHOD(S): We performed an acute in vivo recording accross the lumbar spinal cord of anesthetized mice using a Neuropixels 1.0 probe. Graded mechanical, light tactile, cold, and electrical stimulation was presented to the receptive fields on animal’s ipsilateral hind paw. Neuronal depth was reconstructed from the probe geometry. Spike sorting was performed using Kilosort4 with manual curation in Phy. Downstream analyses were implemented in custom Python pipelines.
RESULTS: This framework enabled characterization of spinal neurons based on multimodal responsiveness, graded intensity coding, and laminar localization. Population level recordings reveal coordinated activity patterns across dorsal horn layers, suggesting structured sensory representations rather than isolated unit responses. This approach enables identification of neuron subtypes with distinct responses to different stimuli and spinal locations.
CONCLUSIONS: High-density population recordings provide a scalable method for investigating spinal sensory coding beyond single-neuron descriptions. By integrating multimodal stimulation with laminar and population-level analysis, this paradigm advances the study of spinal circuit organization and the network mechanisms underlying sensory integration.
FINANCIAL SUPPORT: Funded by National Science Centre grant (2022/D/NZ4/02676), held by MW Kucharczyk.