Faculty Bibliography

Excitation in neural circuits must be carefully controlled by inhibition to regulate information processing and network excitability. During development, cortical inhibitory and excitatory inputs are initially mismatched but become co-tuned or balanced with experience. However, little is known about how excitatory-inhibitory balance is defined at most synapses or about the mechanisms for establishing or maintaining this balance at specific set points. Here we show how coordinated long-term plasticity calibrates populations of excitatory-inhibitory inputs onto mouse auditory cortical pyramidal neurons. Pairing pre- and postsynaptic activity induced plasticity at paired inputs and different forms of heterosynaptic plasticity at the strongest unpaired synapses, which required minutes of activity and dendritic Ca²⁺ signaling to be computed. Theoretical analyses demonstrated how the relative rate of heterosynaptic plasticity could normalize and stabilize synaptic strengths to achieve any possible excitatory-inhibitory correlation. Thus, excitatory-inhibitory balance is dynamic and cell specific, determined by distinct plasticity rules across multiple excitatory and inhibitory synapses.

Neocortical Layer 1 consists of a dense mesh of excitatory and inhibitory axons, dendrites of pyramidal neurons, as well as neuromodulatory inputs from diverse brain regions. Layer 1 also consists of a sparse population of inhibitory interneurons, which are appropriately positioned to receive and integrate the information from these regions of the brain and modulate cortical processing. Despite being among the sparsest neuronal population in the cortex, Layer 1 interneurons perform powerful computations and have elaborate morphologies. Here we review recent studies characterizing their origin, morphology, physiology, and molecular profiles, as well as their connectivity and in vivo response properties.

Pain is an integrated sensory and affective experience. Cortical mechanisms of sensory and affective integration, however, remain poorly defined. Here, we investigate the projection from the primary somatosensory cortex (S1), which encodes the sensory pain information, to the anterior cingulate cortex (ACC), a key area for processing pain affect, in freely behaving rats. By using a combination of optogenetics, in vivo electrophysiology, and machine learning analysis, we find that a subset of neurons in the ACC receives S1 inputs, and activation of the S1 axon terminals increases the response to noxious stimuli in ACC neurons. Chronic pain enhances this cortico-cortical connection, as manifested by an increased number of ACC neurons that respond to S1 inputs and the magnified contribution of these neurons to the nociceptive response in the ACC. Furthermore, modulation of this S1→ACC projection regulates aversive responses to pain. Our results thus define a cortical circuit that plays a potentially important role in integrating sensory and affective pain signals.

The Kv3.1b potassium channel subunit is associated with narrow spike widths and fast-spiking properties. In macaque primary visual cortex (V1), subsets of neurons have previously been found to be Kv3.1b-immunoreactive (ir) but not parvalbumin (PV)-ir or not GABA-ir, suggesting that they may be both fast-spiking and excitatory. This population includes Meynert cells, the large layer 5/6 pyramidal neurons that are also labeled by the neurofilament antibody SMI-32. In the present study, triple immunofluorescence labeling and confocal microscopy were used to measure the distribution of Kv3.1b-ir, non-PV-ir, non-GABA-ir neurons across cortical depth in V1, and to determine whether, like the Meynert cells, other Kv3.1b-ir excitatory neurons were also SMI-32-ir pyramidal neurons. We found that Kv3.1b-ir, non-PV-ir, non-GABA-ir neurons were most prevalent in the M pathway-associated layers 4 Cα and 4B. GABAergic neurons accounted for a smaller fraction (11%) of the total neuronal population across layers 1-6 than has previously been reported. Of Kv3.1b-ir neurons, PV expression reliably indicated GABA expression. Kv3.1b-ir, non-PV-ir neurons varied in SMI-32 coimmunoreactivity. The results suggest the existence of a heterogeneous population of excitatory neurons in macaque V1 with the potential for sustained high firing rates, and these neurons were particularly abundant in layers 4B and 4 Cα.

Sensory perception depends on neocortical computations that contextually adjust sensory signals in different internal and environmental contexts. Neocortical layer 1 (L1) is the main target of cortical and subcortical inputs that provide "top-down" information for context-dependent sensory processing. Although L1 is devoid of excitatory cells, it contains the distal "tuft" dendrites of pyramidal cells (PCs) located in deeper layers. L1 also contains a poorly characterized population of GABAergic interneurons (INs), which regulate the impact that different top-down inputs have on PCs. A poor comprehension of L1 IN subtypes and how they affect PC activity has hampered our understanding of the mechanisms that underlie contextual modulation of sensory processing. We used novel genetic strategies in male and female mice combined with electrophysiological and morphological methods to help resolve differences that were unclear when using only electrophysiological and/or morphological approaches. We discovered that L1 contains four distinct populations of INs, each with a unique molecular profile, morphology, and electrophysiology, including a previously overlooked IN population (named here "canopy cells") representing 40% of L1 INs. In contrast to what is observed in other layers, most L1 neurons appear to be unique to the layer, highlighting the specialized character of the signal processing that takes place in L1. This new understanding of INs in L1, as well as the application of genetic methods based on the markers described here, will enable investigation of the cellular and circuit mechanisms of top-down processing in L1 with unprecedented detail.SIGNIFICANCE STATEMENT Neocortical layer 1 (L1) is the main target of corticocortical and subcortical projections that mediate top-down or context-dependent sensory perception. However, this unique layer is often referred to as "enigmatic" because its neuronal composition has been difficult to determine. Using a combination of genetic, electrophysiological, and morphological approaches that helped to resolve differences that were unclear when using a single approach, we were able to decipher the neuronal composition of L1. We identified markers that distinguish L1 neurons and found that the layer contains four populations of GABAergic interneurons, each with unique molecular profiles, morphologies, and electrophysiological properties. These findings provide a new framework for studying the circuit mechanisms underlying the processing of top-down inputs in neocortical L1.

Cortical interneurons display a remarkable diversity in their morphology, physiological properties, and connectivity. Elucidating the molecular determinants underlying this heterogeneity is essential for understanding interneuron development and function. We discovered that alternative splicing differentially regulates the integration of somatostatin- and parvalbumin-expressing interneurons into nascent cortical circuits through the cell-type-specific tailoring of mRNAs. Specifically, we identified a role for the activity-dependent splicing regulator Rbfox1 in the development of cortical interneuron-subtype-specific efferent connectivity. Our work demonstrates that Rbfox1 mediates largely non-overlapping alternative splicing programs within two distinct but related classes of interneurons.

Inhibitory interneurons represent 10-15% of the neurons in the somatosensory cortex, and their activity powerfully shapes sensory processing. Three major groups of GABAergic interneurons have been defined according to developmental, molecular, morphological, electrophysiological, and synaptic features. Dendritic-targeting somatostatin-expressing interneurons (SST-INs) have been shown to display diverse morphological, electrophysiological and molecular properties and activity patterns in vivo. However, the correlation between these properties and SST-IN subtype is unclear. In this study we aimed to correlate the morphological diversity of layer 5 (L5) SST-INs with their electrophysiological and molecular diversity in mice of either sex. Our morphological analysis demonstrated the existence of three subtypes of L5 SST-INs with distinct electrophysiological properties: T-shaped Martinotti cells innervate L1, and are low-threshold spiking; fanning-out Martinotti cells innervate L2/3 and the lower half of L1, and show adapting firing patterns; non-Martinotti cells innervate L4, and show a quasi-fast spiking firing pattern. We estimated the proportion of each subtype in L5 and found that T-shaped Martinotti, fanning-out Martinotti and Non-Martinotti cells represent ∼10, ∼50 and ∼40% of L5 SST-INs, respectively. Lastly we examined the connectivity between the three SST-IN subtypes and L5 pyramidal cells (PCs). We found that L5 T-shapped Martinotti cells inhibit the L1 apical tuft of nearby PCs; L5 fanning-out Martinotti cells also inhibit nearby PCs but they target the dendrite mainly in L2/3. On the other hand non-Martinotti cells inhibit the dendrites of L4 neurons while avoiding L5 PCs. Our data suggest that morphologically distinct SST-INs gate different excitatory inputs in the barrel cortex.SIGNIFICANCE STATEMENTMorphologically diverse layer 5 SST-INs show different patterns of activity in behaving animals. However, little is known about the abundance and connectivity of each morphological type and the correlation between morphological subtype and spiking properties. We demonstrate a correlation between the morphological and electrophysiological diversity of layer 5 SST-INs. Based on these findings we built a classifier to infer the abundance of each morphological subtype. Lastly, using paired recordings combined with morphological analysis, we investigated the connectivity of each morphological subtype. Our data suggest that, by targeting different cell types and cellular compartments, morphologically diverse SST-INs might gate different excitatory inputs in the mouse barrel cortex.

As an essential means of resolving conflicts, aggression is expressed by both sexes but often at a higher level in males than in females. Recent studies suggest that cells in the ventrolateral part of the ventromedial hypothalamus (VMHvl) that express estrogen receptor-alpha (Esr1) and progesterone receptor are essential for male but not female mouse aggression. In contrast, here we show that VMHvlEsr1+ cells are indispensable for female aggression. This population was active when females attacked naturally. Inactivation of these cells reduced female aggression whereas their activation elicited attack. Additionally, we found that female VMHvl contains two anatomically distinguishable subdivisions that showed differential gene expression, projection and activation patterns after mating and fighting. These results support an essential role of the VMHvl in both male and female aggression and reveal the existence of two previously unappreciated subdivisions in the female VMHvl that are involved in distinct social behaviors.

Venom peptide toxins such as conotoxins play a critical role in the characterization of nicotinic acetylcholine receptor (nAChR) structure and function and have potential as nervous system therapeutics as well. However, the lack of solved structures of conotoxins bound to nAChRs and the large size of these peptides are barriers to their computational docking and design. We addressed these challenges in the context of the alpha4beta2 nAChR, a widespread ligand-gated ion channel in the brain and a target for nicotine addiction therapy, and the 19-residue conotoxin alpha-GID that antagonizes it. We developed a docking algorithm, ToxDock, which used ensemble-docking and extensive conformational sampling to dock alpha-GID and its analogs to an alpha4beta2 nAChR homology model. Experimental testing demonstrated that a virtual screen with ToxDock correctly identified three bioactive alpha-GID mutants (alpha-GID[A10V], alpha-GID[V13I], and alpha-GID[V13Y]) and one inactive variant (alpha-GID[A10Q]). Two mutants, alpha-GID[A10V] and alpha-GID[V13Y], had substantially reduced potency at the human alpha7 nAChR relative to alpha-GID, a desirable feature for alpha-GID analogs. The general usefulness of the docking algorithm was highlighted by redocking of peptide toxins to two ion channels and a binding protein in which the peptide toxins successfully reverted back to near-native crystallographic poses after being perturbed. Our results demonstrate that ToxDock can overcome two fundamental challenges of docking large toxin peptides to ion channel homology models, as exemplified by the alpha-GID:alpha4beta2 nAChR complex, and is extendable to other toxin peptides and ion channels. ToxDock is freely available at rosie.rosettacommons.org/tox_dock.