In order to execute complex behavioral tasks, neural circuits must be precisely connected and each connection must be finely tuned. Neural circuits are shaped by molecular mechanisms that regulate the establishment of synaptic connections, as well as by changes in activity, which modifies those circuits. Both processes are needed to support a functional, plastic neural circuit. In the hippocampus, CA1 axons make divergent connections onto several classes of local interneurons. Remarkably, the presynaptic properties of each synapse depend on the identity of the post-synaptic partner. Synapses from CA1 axons onto basket cells exhibit short-term depression, whereas those onto oriens-lacunosum molecular (OLM) interneurons are strongly facilitating (Ali et al., 1998; Ali and Thomson, 1998). The molecular mechanisms underlying such target-cell specific synaptic specification remain unknown. Here we show that Elfn1, a single-pass transmembrane protein with extracellular leucine-rich repeat (LLR) and fibronectin type 3 (FN3) domains, is expressed selectively by OLM interneurons and localizes to excitatory synapses. Lentiviral-mediated postsynaptic knockdown of Elfn1 in OLM interneurons strongly reduces short-term facilitation and increases the amplitude of synaptic currents. These effects are explained by an increase in presynaptic release probability, while postsynaptic properties are left unaffected. Thus, Elfn1 regulates facilitation at the CA1- OLM synapse by acting trans-synaptically to reduce presynaptic probability of release. These observations indicate that cell- and synapse- specific expression of LRR- containing proteins in postsynaptic neurons can contribute to the generation of functional synaptic diversity. Activity-dependent modification, in addition to molecular mechanisms, can shape synaptic function. Synaptic scaling is a form of homeostatic synaptic plasticity characterized by cell-wide changes in synaptic strength in response to changes in overall levels of neuronal activity. Here we report that bicuculline-induced increase in neuronal activity leads to a decrease in mEPSC amplitude and a decrease in expression of the AMPA receptor subunit GluR2 in rat hippocampal cultures. Bicuculline treatment also leads to an increase in the levels of the transcriptional repressor MeCP2, which binds to the GluR2 promoter along with the co-repressors HDAC1 and mSin3A. Down-regulation of MeCP2 by shRNA expression or genetic deletion blocks the bicuculline-induced decrease in GluR2 expression and mEPSC amplitude. These observations indicate that MeCP2 mediates activity- dependent synaptic scaling, and suggest that the pathophysiology of Rett syndrome, which is caused by mutations in MeCP2, may involve defects in activity- dependent regulation of synaptic currents. Taken together, these studies on the role of Elfn1 in target-cell specificity and MeCP2 regulation of synaptic scaling present novel roles for molecules in the specification and activity-dependent regulation of synapses

Computational analysis of cellular activity has developed largely independently of modern transcriptomic cell typology, but integrating these approaches may be essential for full insight into cellular-level mechanisms underlying brain function and dysfunction. Applying this approach to the habenula (a structure with diverse, intermingled molecular, anatomical, and computational features), we identified encoding of reward-predictive cues and reward outcomes in distinct genetically defined neural populations, including TH+ cells and Tac1+ cells. Data from genetically targeted recordings were used to train an optimized nonlinear dynamical systems model and revealed activity dynamics consistent with a line attractor. High-density, cell-type-specific electrophysiological recordings and optogenetic perturbation provided supporting evidence for this model. Reverse-engineering predicted how Tac1+ cells might integrate reward history, which was complemented by in vivo experimentation. This integrated approach describes a process by which data-driven computational models of population activity can generate and frame actionable hypotheses for cell-type-specific investigation in biological systems.