Faculty Bibliography

gamma-Aminobutyric acid (GABA)ergic inputs are strategically positioned to gate synaptic integration along the dendritic arbor of pyramidal cells. However, their spatiotemporal dynamics during behavior are poorly understood. Using an optical-tagging electrophysiological approach to record and label somatostatin-expressing (Sst) interneurons (GABAergic neurons specialized for dendritic inhibition), we discovered a layer-specific modulation of their activity in behaving mice. Sst interneuron subtypes, residing in different cortical layers and innervating complementary laminar domains, exhibited opposite activity changes during transitions to active wakefulness. The relative weight of vasoactive intestinal peptide-expressing (Vip) interneuron-mediated inhibition of distinct Sst interneurons and cholinergic modulation determined their in vivo activity. These results reveal a state-dependent laminar influence of Sst interneuron-mediated inhibition, with implications for the compartmentalized regulation of dendritic signaling in the mammalian neocortex.

A fundamental impediment to understanding the brain is the availability of inexpensive and robust methods for targeting and manipulating specific neuronal populations. The need to overcome this barrier is pressing because there are considerable anatomical, physiological, cognitive and behavioral differences between mice and higher mammalian species in which it is difficult to specifically target and manipulate genetically defined functional cell types. In particular, it is unclear the degree to which insights from mouse models can shed light on the neural mechanisms that mediate cognitive functions in higher species, including humans. Here we describe a novel recombinant adeno-associated virus that restricts gene expression to GABAergic interneurons within the telencephalon. We demonstrate that the viral expression is specific and robust, allowing for morphological visualization, activity monitoring and functional manipulation of interneurons in both mice and non-genetically tractable species, thus opening the possibility to study GABAergic function in virtually any vertebrate species.

Systematic genetic access to GABAergic cell types will facilitate studying the function and development of inhibitory circuitry. However, single gene-driven recombinase lines mark relatively broad and heterogeneous cell populations. Although intersectional approaches improve precision, it remains unclear whether they can capture cell types defined by multiple features. Here we demonstrate that combinatorial genetic and viral approaches target restricted GABAergic subpopulations and cell types characterized by distinct laminar location, morphology, axonal projection, and electrophysiological properties. Intersectional embryonic transcription factor drivers allow finer fate mapping of progenitor pools that give rise to distinct GABAergic populations, including laminar cohorts. Conversion of progenitor fate restriction signals to constitutive recombinase expression enables viral targeting of cell types based on their lineage and birth time. Properly designed intersection, subtraction, conversion, and multi-color reporters enhance the precision and versatility of drivers and viral vectors. These strategies and tools will facilitate studying GABAergic neurons throughout the mouse brain.

Jiang et al (Research Article, 27 November 2015, aac9462) describe detailed experiments that substantially add to the knowledge of cortical microcircuitry and are unique in the number of connections reported and the quality of interneuron reconstruction. The work appeals to experts and laypersons because of the notion that it unveils new principles and provides a complete description of cortical circuits. We provide a counterbalance to the authors' claims to give those less familiar with the minutiae of cortical circuits a better sense of the contributions and the limitations of this study.

Hunger is a powerful drive that stimulates food intake. Yet, the mechanism that determines how the energy deficits that result in hunger are represented in the brain and promote feeding is not well understood. We previously described SLC5A11-a sodium/solute co-transporter-like-(or cupcake) in Drosophila melanogaster, which is required for the fly to select a nutritive sugar over a sweeter nonnutritive sugar after periods of food deprivation. SLC5A11 acts on approximately 12 pairs of ellipsoid body (EB) R4 neurons to trigger the selection of nutritive sugars, but the underlying mechanism is not understood. Here, we report that the excitability of SLC5A11-expressing EB R4 neurons increases dramatically during starvation and that this increase is abolished in the SLC5A11 mutation. Artificial activation of SLC5A11-expresssing neurons is sufficient to promote feeding and hunger-driven behaviors; silencing these neurons has the opposite effect. Notably, SLC5A11 transcript levels in the brain increase significantly when flies are starved and decrease shortly after starved flies are refed. Furthermore, expression of SLC5A11 is sufficient for promoting hunger-driven behaviors and enhancing the excitability of SLC5A11-expressing neurons. SLC5A11 inhibits the function of the Drosophila KCNQ potassium channel in a heterologous expression system. Accordingly, a knockdown of dKCNQ expression in SLC5A11-expressing neurons produces hunger-driven behaviors even in fed flies, mimicking the overexpression of SLC5A11. We propose that starvation increases SLC5A11 expression, which enhances the excitability of SLC5A11-expressing neurons by suppressing dKCNQ channels, thereby conferring the hunger state.

Cortical networks are composed of glutamatergic excitatory projection neurons and local GABAergic inhibitory interneurons that gate signal flow and sculpt network dynamics. Although they represent a minority of the total neocortical neuronal population, GABAergic interneurons are highly heterogeneous, forming functional classes based on their morphological, electrophysiological, and molecular features, as well as connectivity and in vivo patterns of activity. Here we review our current understanding of neocortical interneuron diversity and the properties that distinguish cell types. We then discuss how the involvement of multiple cell types, each with a specific set of cellular properties, plays a crucial role in diversifying and increasing the computational power of a relatively small number of simple circuit motifs forming cortical networks. We illustrate how recent advances in the field have shed light onto the mechanisms by which GABAergic inhibition contributes to network operations.

The precise connectivity of somatostatin and parvalbumin cortical interneurons is generated during development. An understanding of how these interneuron classes incorporate into cortical circuitry is incomplete but essential to elucidate the roles they play during maturation. Here, we report that somatostatin interneurons in infragranular layers receive dense but transient innervation from thalamocortical afferents during the first postnatal week. During this period, parvalbumin interneurons and pyramidal neurons within the same layers receive weaker thalamocortical inputs, yet are strongly innervated by somatostatin interneurons. Further, upon disruption of the early (but not late) somatostatin interneuron network, the synaptic maturation of thalamocortical inputs onto parvalbumin interneurons is perturbed. These results suggest that infragranular somatostatin interneurons exhibit a transient early synaptic connectivity that is essential for the establishment of thalamic feedforward inhibition mediated by parvalbumin interneurons.

Brain networks contain a large diversity of functionally distinct neuronal elements, each with unique properties, enabling computational capacities and supporting brain functions. Understanding their functional implications for behavior requires the precise identification of the cell types of a network and in vivo monitoring of their activity profiles. Here, we developed a channelrhodopsin-assisted patching method allowing the efficient in vivo targeted recording of neurons identified by their molecular, electrophysiological, and morphological features. The method has a high yield, does not require visual guidance, and thus can be applied at any depth in the brain. This approach overcomes limitations of present technologies. We validate this strategy with in vivo recordings of identified subtypes of GABAergic and glutamatergic neurons in deep cortical layers, subcortical cholinergic neurons, and neurons in the thalamic reticular nucleus in anesthetized and awake mice. We propose this method as an important complement to existing technologies to relate specific cell-type activity to brain circuitry, function, and behavior.

The signaling properties of thalamocortical (TC) neurons depend on the diversity of ion conductance mechanisms that underlie their rich membrane behavior at subthreshold potentials. Using patch-clamp recordings of TC neurons in brain slices from mice and a realistic conductance-based computational model, we characterized seven subthreshold ion currents of TC neurons and quantified their individual contributions to the total steady-state conductance at levels below tonic firing threshold. We then used the TC neuron model to show that the resting membrane potential results from the interplay of several inward and outward currents over a background provided by the potassium and sodium leak currents. The steady-state conductances of depolarizing Ih (hyperpolarization-activated cationic current), IT (low-threshold calcium current), and INaP (persistent sodium current) move the membrane potential away from the reversal potential of the leak conductances. This depolarization is counteracted in turn by the hyperpolarizing steady-state current of IA (fast transient A-type potassium current) and IKir (inwardly rectifying potassium current). Using the computational model, we have shown that single parameter variations compatible with physiological or pathological modulation promote burst firing periodicity. The balance between three amplifying variables (activation of IT, activation of INaP, and activation of IKir) and three recovering variables (inactivation of IT, activation of IA, and activation of Ih) determines the propensity, or lack thereof, of repetitive burst firing of TC neurons. We also have determined the specific roles that each of these variables have during the intrinsic oscillation.