A Model for Homeostatic Plasticity in Striatum

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PROJECT SUMMARY Changes in synaptic weights encode new learning and the execution of learned behaviors. Such changes occur across different timescales, all within dynamic systems that recalibrate and compensate homeostatically to stabilize network activity and maintain activity within a useful dynamic range. Strong data support that these stabilizing mechanisms are conserved evolutionarily and represented across neural systems. In animal models, they have been best studied in sensory systems and at the neuromuscular junction. Despite broad acceptance of these mechanisms, the homeostatically stabilizing actions of most networks have not been documented and/or are poorly understood. A normal functioning synapse can be strengthened or weakened over fast timescales (seconds to minutes) and includes Hebbian forms of synapse plasticity such as LTP or LTD. In cortical synapses forming on striatal projection neurons (SPNs), abnormal Hebbian synaptic plasticity is a hallmark of anxiety- and addiction-like states and neurological disease models associated with cognitive impairment or dementia. Collectively, the data indicate that Hebbian plasticity is vulnerable to a variety of pathological conditions. However, the data also suggest that under such conditions, corticostriatal networks are no longer kept within a useful working range—that the adaptive actions designed to stabilize this largely closed-loop system may also be particularly vulnerable. Importantly, whether or how corticostriatal circuits adapt to sustained increases or decreases in activity is not clear, a significant lapse in understanding overall corticostriatal network function in health and disease states. The specific goals of this multi-PI R21 are to define the nature of homeostatic adaptation within SPNs. We will assess responses to widespread, targeted, and cell autonomous increases or decreases in neural activity in vitro and within an intact system. These data will permit us to build a testable model that can be used in the future for assessing how homeostatic mechanisms become maladaptive or subverted by disease-related pathologies.