Neuronal circuit function is governed by precise patterns of connectivity between specialized groups of neurons. The diversity of GABAergic interneurons is a hallmark of cortical circuits, yet little is known about their targeting to individual postsynaptic dendrites. We examined synaptic connectivity between molecularly defined inhibitory interneurons and CA1 pyramidal cell dendrites using correlative light-electron microscopy and large-volume array tomography. We show that interneurons can be highly selective in their connectivity to specific dendritic branch types and, furthermore, exhibit precisely targeted connectivity to the origin or end of individual branches. Computational simulations indicate that the observed subcellular targeting enables control over the nonlinear integration of synaptic input or the initiation and backpropagation of action potentials in a branch-selective manner. Our results demonstrate that connectivity between interneurons and pyramidal cell dendrites is more precise and spatially segregated than previously appreciated, which may be a critical determinant of how inhibition shapes dendritic computation.

Dendritic spines are the nearly ubiquitous site of excitatory synaptic input onto neurons and as such are critically positioned to influence diverse aspects of neuronal signalling. Decades of theoretical studies have proposed that spines may function as highly effective and modifiable chemical and electrical compartments that regulate synaptic efficacy, integration and plasticity. Experimental studies have confirmed activity-dependent structural dynamics and biochemical compartmentalization by spines. However, there is a longstanding debate over the influence of spines on the electrical aspects of synaptic transmission and dendritic operation. Here we measure the amplitude ratio of spine head to parent dendrite voltage across a range of dendritic compartments and calculate the associated spine neck resistance (R(neck)) for spines at apical trunk dendrites in rat hippocampal CA1 pyramidal neurons. We find that R(neck) is large enough ( 500 MΩ) to amplify substantially the spine head depolarization associated with a unitary synaptic input by  1.5- to  45-fold, depending on parent dendritic impedance. A morphologically realistic compartmental model capable of reproducing the observed spatial profile of the amplitude ratio indicates that spines provide a consistently high-impedance input structure throughout the dendritic arborization. Finally, we demonstrate that the amplification produced by spines encourages electrical interaction among coactive inputs through an R(neck)-dependent increase in spine head voltage-gated conductance activation. We conclude that the electrical properties of spines promote nonlinear dendritic processing and associated forms of plasticity and storage, thus fundamentally enhancing the computational capabilities of neurons.

In the hippocampus, the classical pyramidal cell type of the subiculum acts as a primary output, conveying hippocampal signals to a diverse suite of downstream regions. Accumulating evidence suggests that the subiculum pyramidal cell population may actually be comprised of discrete subclasses. Here, we investigated the extent and organizational principles governing pyramidal cell heterogeneity throughout the mouse subiculum. Using single-cell RNA-seq, we find that the subiculum pyramidal cell population can be deconstructed into eight separable subclasses. These subclasses were mapped onto abutting spatial domains, ultimately producing a complex laminar and columnar organization with heterogeneity across classical dorsal-ventral, proximal-distal, and superficial-deep axes. We further show that these transcriptomically defined subclasses correspond to differential protein products and can be associated with specific projection targets. This work deconstructs the complex landscape of subiculum pyramidal cells into spatially segregated subclasses that may be observed, controlled, and interpreted in future experiments.

The revolution in neuroscientific data acquisition is creating an analysis challenge. We propose leveraging cloud-computing technologies to enable large-scale neurodata storing, exploring, analyzing, and modeling. This utility will empower scientists globally to generate and test theories of brain function and dysfunction.

Long-term memory depends on the control of activity-dependent neuronal gene expression, which is regulated by epigenetic modifications. The epigenetic modification of histones is orchestrated by the opposing activities of two classes of regulatory complexes: permissive co-activators and silencing co-repressors. Much work has focused on co-activator complexes, but little is known about the co-repressor complexes that suppress the expression of plasticity-related genes. Here, we define a critical role for the co-repressor SIN3A in memory and synaptic plasticity, showing that postnatal neuronal deletion of Sin3a enhances hippocampal long-term potentiation and long-term contextual fear memory. SIN3A regulates the expression of genes encoding proteins in the post-synaptic density. Loss of SIN3A increases expression of the synaptic scaffold Homer1, alters the mGluR1α- and mGluR5-dependence of long-term potentiation, and increases activation of extracellular signal regulated kinase (ERK) in the hippocampus after learning. Our studies define a critical role for co-repressors in modulating neural plasticity and memory consolidation and reveal that Homer1/mGluR signaling pathways may be central molecular mechanisms for memory enhancement.