Prolonged anesthesia alters brain synaptic architecture

Prolonged medically induced coma (pMIC) is carried out routinely in intensive care medicine. pMIC leads to cognitive impairment, yet the underlying neuromorphological correlates are still unknown, as no direct studies of MIC exceeding ∼6 h on neural circuits exist. Here, we establish pMIC (up to 24 h) in adolescent and mature mice, and combine longitudinal two-photon imaging of cortical synapses with repeated behavioral object recognition assessments. We find that pMIC affects object recognition, and that it is associated with enhanced synaptic turnover, generated by enhanced synapse formation during pMIC, while the postanesthetic period is dominated by synaptic loss. Our results demonstrate major side effects of prolonged anesthesia on neural circuit structure.

Prolonged anesthesia alters brain synaptic architecture

SUMMARYProlonged medically-induced coma (pMIC), a procedure performed in millions of patients worldwide, leads to cognitive impairment, yet the underlying brain mechanism remains unknown. No experimental studies of medically-induced coma (MIC) exceeding ~6 hours exist. For MIC of less than 6 hours, studies in developing rodents have documented transient changes of cortical synapse formation. However, in adulthood, cortical synapses are thought to become stabilized. Here, we establish pMIC (up to 24 hrs) in adolescent and mature mice, and combine repeated behavioral object recognition assessments with longitudinal two-photon imaging of cortical synapses. We find that pMIC affects cognitive function, and is associated with enhanced synaptic turnover, generated by enhanced synapse formation during pMIC, while the post-anesthetic period is dominated by synaptic loss. These results carry profound implications for intensive medical care, as they point out at significant structural side effects of pMIC on cortical brain synaptic architecture across age levels.

Biophysics of object segmentation in a collision-detecting neuron

Collision avoidance is critical for survival, including in humans, and many species possess visual neurons exquisitely sensitive to objects approaching on a collision course. Here, we demonstrate that a collision-detecting neuron can detect the spatial coherence of a simulated impending object, thereby carrying out a computation akin to object segmentation critical for proper escape behavior. At the cellular level, object segmentation relies on a precise selection of the spatiotemporal pattern of synaptic inputs by dendritic membrane potential-activated channels. One channel type linked to dendritic computations in many neural systems, the hyperpolarization-activated cation channel, HCN, plays a central role in this computation. Pharmacological block of HCN channels abolishes the neuron's spatial selectivity and impairs the generation of visually guided escape behaviors, making it directly relevant to survival. Additionally, our results suggest that the interaction of HCN and inactivating K+ channels within active dendrites produces neuronal and behavioral object specificity by discriminating between complex spatiotemporal synaptic activation patterns.

Biophysics of object segmentation in a collision-detecting neuron

Collision avoidance is critical for survival, including in humans, and many species possess visual neurons exquisitely sensitive to objects approaching on a collision course. The most studied such collision-detecting neuron within the optic lobe of grasshoppers has long served as a model for understanding collision avoidance behaviors and their underlying neural computations. Here, we demonstrate that this neuron detects the spatial coherence of a simulated impending object, thereby carrying out a computation akin to object segmentation critical for proper escape behavior. At the cellular level, object segmentation relies on a precise selection of the spatiotemporal pattern of synaptic inputs by dendritic membrane potential-activated channels. One channel type linked to dendritic computations in many neural systems, the hyperpolarization-activated cation channel, HCN, plays a central role in this computation as its pharmacological block abolishes the neuron's spatial selectivity and impairs the generation of visually guided escape behaviors, making it directly relevant to survival. Our results elucidate how active dendritic channels produce neuronal and behavioral object specificity by discriminating between complex spatiotemporal synaptic activation patterns.