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bioRxiv2026

Polytraumatic SCI worsens maladaptive plasticity in spinal motor systems

Spinal cord injury (SCI) results in dysfunction of both motor and sensory systems, which can be characterized by neuropathic pain, hypersensitivity, muscular spasticity and rigidity. Most SCIs result from incidents such as vehicle accidents or falls, resulting in polytraumatic SCI that includes peripheral injuries in addition to direct CNS damage. Recent findings suggest that spinal cord synaptic plasticity plays a crucial role in neuropathic pain pathophysiology, specifically in association with spinal sensitization and the consequent onset of AMPA-related maladaptive plasticity. Further findings have demonstrated that nociceptive peripheral stimulation in the acute phase of SCI results in maladaptive spinal synaptic plasticity by overdriving GluA2-lacking calcium-permeable AMPARs (CP-AMPARs). Here, we investigated the effect of a spared nerve injury (SNI) in conjunction with SCI to determine the effect of polytraumatic SCI on maladaptive plasticity in the spinal cord. Near-IR quantitative Western blot analysis demonstrated that SCI+SNI increases spinal GluA1 expression, but not GluA2. Patch-clamp confirmed that AMPAR currents in spinal motorneurons increase after SCI with SNI, and decrease after the administration of NASPM, a CP-AMPAR antagonist. Data-driven analysis using non-linear principal components analysis (NL-PCA) also demonstrated that SCI with SNI produces a multivariate signature of AMPAR plasticity that is observed in other forms of nociceptive peripheral input, indicating a general mechanism for maladaptive plasticity in spinal motor systems in response to polytraumatic SCI.

neuroscience↗

bioRxiv2023

A neuronal least-action principle for real-time learning in cortical circuits

AO_SCPLOWBSTRACTC_SCPLOWOne of the most fundamental laws of physics is the principle of least action. Motivated by its predictive power, we introduce a neuronal least-action principle for cortical processing of sensory streams to produce appropriate behavioural outputs in real time. The principle postulates that the voltage dynamics of cortical pyramidal neurons prospectively minimizes the local somato-dendritic mismatch error within individual neurons. For output neurons, the principle implies minimizing an instantaneous behavioural error. For deep network neurons, it implies the prospective firing to overcome integration delays and correct for possible output errors right in time. The neuron-specific errors are extracted in the apical dendrites of pyramidal neurons through a cortical microcircuit that tries to explain away the feedback from the periphery, and correct the trajectory on the fly. Any motor output is in a moving equilibrium with the sensory input and the motor feedback during the ongoing sensory-motor transform. Online synaptic plasticity reduces the somato-dendritic mismatch error within each cortical neuron and performs gradient descent on the output cost at any moment in time. The neuronal least-action principle offers an axiomatic framework to derive local neuronal and synaptic laws for global real-time computation and learning in the brain.

neuroscience↗