Edward M. Callaway

Genetic dissection of neural circuits.

Understanding the principles of information processing in neural circuits requires systematic characterization of the participating cell types and their connections, and the ability to measure and perturb their activity. Genetic approaches promise to bring experimental access to complex neural systems, including genetic stalwarts such as the fly and mouse, but also to nongenetic systems such as primates. Together with anatomical and physiological methods, cell-type-specific expression of protein markers and sensors and transducers will be critical to construct circuit diagrams and to measure the activity of genetically defined neurons. Inactivation and activation of genetically defined cell types will establish causal relationships between activity in specific groups of neurons, circuit function, and animal behavior. Genetic analysis thus promises to reveal the logic of the neural circuits in complex brains that guide behaviors. Here we review progress in the genetic analysis of neural circuits and discuss directions for future research and development.

Monosynaptic Restriction of Transsynaptic Tracing from Single, Genetically Targeted Neurons

There has never been a wholesale way of identifying neurons that are monosynaptically connected either to some other cell group or, especially, to a single cell. The best available tools, transsynaptic tracers, are unable to distinguish weak direct connections from strong indirect ones. Furthermore, no tracer has proven potent enough to label any connected neurons whatsoever when starting from a single cell. Here we present a transsynaptic tracer that crosses only one synaptic step, unambiguously identifying cells directly presynaptic to the starting population. Based on rabies virus, it is genetically targetable, allows high-level expression of any gene of interest in the synaptically coupled neurons, and robustly labels connections made to single cells. This technology should enable a far more detailed understanding of neural connectivity than has previously been possible.

Excitatory cortical neurons form fine-scale functional networks.

The specificity of cortical neuron connections creates columns of functionally similar neurons spanning from the pia to the white matter. Here we investigate whether there is an additional, finer level of specificity that creates subnetworks of excitatory neurons within functional columns. We tested for fine-scale specificity of connections to cortical layer 2/3 pyramidal neurons in rat visual cortex by using cross-correlation analyses of synaptic currents evoked by photostimulation. Recording simultaneously from adjacent layer 2/3 pyramidal cells, we find that when they are connected to each other (20% of all recorded pairs) they share common input from layer 4 and within layer 2/3. When adjacent layer 2/3 neurons are not connected to each other, they share very little (if any) common excitatory input from layers 4 and 2/3. In contrast, all layer 2/3 neurons share common excitatory input from layer 5 and inhibitory input from layers 2/3 and 4, regardless of whether they are connected to each other. Thus, excitatory connections from layer 4 to layer 2/3 and within layer 2/3 form fine-scale assemblies of selectively interconnected neurons; inhibitory connections and excitatory connections from layer 5 link neurons across these fine-scale subnetworks. Relatively independent subnetworks of excitatory neurons are therefore embedded within the larger-scale functional architecture; this allows neighbouring neurons to convey information more independently than suggested by previous descriptions of cortical circuitry.

Genetic dissection of an amygdala microcircuit that gates conditioned fear

The role of different amygdala nuclei (neuroanatomical subdivisions) in processing Pavlovian conditioned fear has been studied extensively, but the function of the heterogeneous neuronal subtypes within these nuclei remains poorly understood. Here we use molecular genetic approaches to map the functional connectivity of a subpopulation of GABA-containing neurons, located in the lateral subdivision of the central amygdala (CEl), which express protein kinase C-δ (PKC-δ). Channelrhodopsin-2-assisted circuit mapping in amygdala slices and cell-specific viral tracing indicate that PKC-δ+ neurons inhibit output neurons in the medial central amygdala (CEm), and also make reciprocal inhibitory synapses with PKC-δ− neurons in CEl. Electrical silencing of PKC-δ+ neurons in vivo suggests that they correspond to physiologically identified units that are inhibited by the conditioned stimulus, called CEloff units. This correspondence, together with behavioural data, defines an inhibitory microcircuit in CEl that gates CEm output to control the level of conditioned freezing.

Parallel Processing Strategies of the Primate Visual System

Incoming sensory information is sent to the brain along modality-specific channels corresponding to the five senses. Each of these channels further parses the incoming signals into parallel streams to provide a compact, efficient input to the brain. Ultimately, these parallel input signals must be elaborated on and integrated in the cortex to provide a unified and coherent percept. Recent studies in the primate visual cortex have greatly contributed to our understanding of how this goal is accomplished. Multiple strategies including retinal tiling, hierarchical and parallel processing and modularity, defined spatially and by cell type-specific connectivity, are used by the visual system to recover the intricate detail of our visual surroundings.

Retrograde neuronal tracing with a deletion-mutant rabies virus

We have constructed a deletion-mutant rabies virus encoding EGFP and find it to be an excellent tool for studying detailed morphology and physiology of neurons projecting to injection sites within the mammalian brain. The virus cannot spread beyond initially infected cells yet, unlike other viral vectors, replicates its core within them. The cells therefore fluoresce intensely, revealing fine dendritic and axonal structure with no background from partially or faintly labeled cells.

Cortical representations of olfactory input by trans-synaptic tracing

In the mouse, each class of olfactory receptor neurons expressing a given odorant receptor has convergent axonal projections to two specific glomeruli in the olfactory bulb, thereby creating an odour map. However, it is unclear how this map is represented in the olfactory cortex. Here we combine rabies-virus-dependent retrograde mono-trans-synaptic labelling with genetics to control the location, number and type of ‘starter’ cortical neurons, from which we trace their presynaptic neurons. We find that individual cortical neurons receive input from multiple mitral cells representing broadly distributed glomeruli. Different cortical areas represent the olfactory bulb input differently. For example, the cortical amygdala preferentially receives dorsal olfactory bulb input, whereas the piriform cortex samples the whole olfactory bulb without obvious bias. These differences probably reflect different functions of these cortical areas in mediating innate odour preference or associative memory. The trans-synaptic labelling method described here should be widely applicable to mapping connections throughout the mouse nervous system.

V1 spinal neurons regulate the speed of vertebrate locomotor outputs

The neuronal networks that generate vertebrate movements such as walking and swimming are embedded in the spinal cord. These networks, which are referred to as central pattern generators (CPGs), are ideal systems for determining how ensembles of neurons generate simple behavioural outputs. In spite of efforts to address the organization of the locomotor CPG in walking animals, little is known about the identity and function of the spinal interneuron cell types that contribute to these locomotor networks. Here we use four complementary genetic approaches to directly address the function of mouse V1 neurons, a class of local circuit inhibitory interneurons that selectively express the transcription factor Engrailed1. Our results show that V1 neurons shape motor outputs during locomotion and are required for generating ‘fast’ motor bursting. These findings outline an important role for inhibition in regulating the frequency of the locomotor CPG rhythm, and also suggest that V1 neurons may have an evolutionarily conserved role in controlling the speed of vertebrate locomotor movements.

Laminar sources of synaptic input to cortical inhibitory interneurons and pyramidal neurons

The functional role of an individual neuron within a cortical circuit is largely determined by that neurons synaptic input. We examined the laminar sources of local input to subtypes of cortical neurons in layer 2/3 of rat visual cortex using laser scanning photostimulation. We identified three distinct laminar patterns of excitatory input that correspond to physiological and morphological subtypes of neurons. Fast-spiking inhibitory basket cells and excitatory pyramidal neurons received strong excitatory input from middle cortical layers. In contrast, adapting inhibitory interneurons received their strongest excitatory input either from deep layers or laterally from within layer 2/3. Thus, differential laminar sources of excitatory inputs contribute to the functional diversity of cortical inhibitory interneurons.

Fine-scale specificity of cortical networks depends on inhibitory cell type and connectivity.

Excitatory cortical neurons form fine-scale networks of precisely interconnected neurons. Here we tested whether inhibitory cortical neurons in rat visual cortex might also be connected with fine-scale specificity. Using paired intracellular recordings and cross-correlation analyses of photostimulation-evoked synaptic currents, we found that fast-spiking interneurons preferentially connected to neighboring pyramids that provided them with reciprocal excitation. Furthermore, they shared common fine-scale excitatory input with neighboring pyramidal neurons only when the two cells were reciprocally connected, and not when there was no connection or a one-way, inhibitory-to-excitatory connection. Adapting inhibitory neurons shared little or no common input with neighboring pyramids, regardless of their direct connectivity. We conclude that inhibitory connections and also excitatory connections to inhibitory neurons can both be precise on a fine scale. Furthermore, fine-scale specificity depends on the type of inhibitory neuron and on direct connectivity between neighboring pyramidal-inhibitory neuron pairs.