Compared to the dorsal hippocampus, relatively few studies have characterized neuronal responses in the ventral hippocampus. In particular, it is unclear whether and how cells in the ventral region represent space and/or respond to contextual changes. We recorded from dorsal and ventral CA1 neurons in freely moving mice exposed to manipulations of visuospatial and olfactory contexts. We found that ventral cells respond to alterations of the visuospatial environment such as exposure to novel local cues, cue rotations, and contextual expansion in similar ways to dorsal cells, with the exception of cue rotations. Furthermore, we found that ventral cells responded to odors much more strongly than dorsal cells, particularly to odors of high valence. Similar to earlier studies recording from the ventral hippocampus in CA3, we also found increased scaling of place cell field size along the longitudinal hippocampal axis. Although the increase in place field size observed toward the ventral pole has previously been taken to suggest a decrease in spatial information coded by ventral place cells, we hypothesized that a change in spatial scaling could instead signal a shift in representational coding that preserves the resolution of spatial information. To explore this possibility, we examined population activity using principal component analysis (PCA) and neural location reconstruction techniques. Our results suggest that ventral populations encode a distributed representation of space, and that the resolution of spatial information at the population level is comparable to that of dorsal populations of similar size. Finally, through the use of neural network modeling, we suggest that the redundancy in spatial representation along the longitudinal hippocampal axis may allow the hippocampus to overcome the conflict between memory interference and generalization inherent in neural network memory. Our results suggest that ventral population activity is well suited for generalization across locations and contexts. © 2014 Wiley Periodicals, Inc.

Neuronal cell types are the nodes of neural circuits that determine the flow of information within the brain. Neuronal morphology, especially the shape of the axonal arbor, provides an essential descriptor of cell type and reveals how individual neurons route their output across the brain. Despite the importance of morphology, few projection neurons in the mouse brain have been reconstructed in their entirety. Here we present a robust and efficient platform for imaging and reconstructing complete neuronal morphologies, including axonal arbors that span substantial portions of the brain. We used this platform to reconstruct more than 1,000 projection neurons in the motor cortex, thalamus, subiculum, and hypothalamus. Together, the reconstructed neurons constitute more than 85 meters of axonal length and are available in a searchable online database. Axonal shapes revealed previously unknown subtypes of projection neurons and suggest organizational principles of long-range connectivity.

A number of recent studies have provided compelling demonstrations that both mice and rats can be trained to perform a variety of behavioral tasks while restrained by mechanical elements mounted to the skull. The independent development of this technique by a number of laboratories has led to diverse solutions. We found that these solutions often used expensive materials and impeded future development and modification in the absence of engineering support. In order to address these issues, here we report on the development of a flexible single hardware design for electrophysiology and imaging both in brain tissue in vitro. Our hardware facilitates the rapid conversion of a single preparation between physiology and imaging system and the conversion of a given system between preparations. In addition, our use of rapid prototyping machines ("3D printers") allows for the deployment of new designs within a day. Here, we present specifications for design and manufacturing as well as some data from our lab demonstrating the suitability of the design for physiology in behaving animals and imaging in vitro and in vivo.

The transformation of synaptic input into patterns of spike output is a fundamental operation that is determined by the particular complement of ion channels that a neuron expresses. Although it is well established that individual ion channel proteins make stochastic transitions between conducting and non-conducting states, most models of synaptic integration are deterministic, and relatively little is known about the functional consequences of interactions between stochastically gating ion channels. Here, we show that a model of stellate neurons from layer II of the medial entorhinal cortex implemented with either stochastic or deterministically gating ion channels can reproduce the resting membrane properties of stellate neurons, but only the stochastic version of the model can fully account for perithreshold membrane potential fluctuations and clustered patterns of spike output that are recorded from stellate neurons during depolarized states. We demonstrate that the stochastic model implements an example of a general mechanism for patterning of neuronal output through activity-dependent changes in the probability of spike firing. Unlike deterministic mechanisms that generate spike patterns through slow changes in the state of model parameters, this general stochastic mechanism does not require retention of information beyond the duration of a single spike and its associated afterhyperpolarization. Instead, clustered patterns of spikes emerge in the stochastic model of stellate neurons as a result of a transient increase in firing probability driven by activation of HCN channels during recovery from the spike afterhyperpolarization. Using this model, we infer conditions in which stochastic ion channel gating may influence firing patterns in vivo and predict consequences of modifications of HCN channel function for in vivo firing patterns.

Enkephalin modulates striatal function, thereby affecting motor performance and addictive behaviors. The proenkephalin gene is also used as a model to study cyclic AMP-mediated gene expression in striatal neurons. The second messenger pathway leading to proenkephalin expression demonstrates how cyclic AMP pathways are synchronized with depolarization. We show that cyclic AMP-mediated regulation of the proenkephalin gene is dependent on the activity of L-type Ca2+ channels. Inhibition of L-type Ca2+ channels blocks forskolin-mediated induction of proenkephalin. The Ca2+-activated kinase, Ca2+/calmodulin kinase, as well as the cyclic AMP-activated kinase, protein kinase A (PKA), are both necessary for the induction of the proenkephalin promoter. Similarly, both kinases are needed for the L-type Ca2+ channel-mediated induction of proenkephalin. This synchronization of second messenger pathways provides a coincidence mechanism that gates proenkephalin synthesis in striatal neurons, ensuring that levels are increased only in the presence of activated PKA and depolarization.

The basal ganglia plays a significant role in transforming activity in the cerebral cortex into directed behavior, involving motor learning, habit formation and the selection of actions based on desirable outcomes, and the organization of the basal ganglia is intimately linked to that of the cerebral cortex. In this chapter, we focus primarily on the neocortical part of the basal ganglia. A general canonical organizational plan of the neocortical-related basal ganglia is described. An understanding of the canonical organization of the neostriatal part of the basal ganglia, provides a framework for determining the general organizational principles of the parts of the basal ganglia connected with allocortical areas and the amygdala, and this is discussed. While it has been proposed that the basal ganglia provide interactions between disparate functional circuits, another approach might be that there are parallel functional circuits, in which distinct functions are for the most part maintained, or segregated, one from the other. This chapter, however, is biased toward the view that there is maintenance of functional parallel circuits in the organization of the basal ganglia, but that the circuit contains neuroanatomical features that provide for considerable interaction between adjacent circuits.

Vertebrates are remarkable for their ability to select and execute goal-directed actions: motor skills critical for thriving in complex, competitive environments. A key aspect of a motor skill is the ability to execute its component movements over a range of speeds, amplitudes and frequencies (vigor). Recent work has indicated that a subcortical circuit, the basal ganglia, is a critical determinant of movement vigor in rodents and primates. We propose that the basal ganglia evolved from a circuit that in lower vertebrates and some mammals is sufficient to directly command simple or stereotyped movements to one that indirectly controls the vigor of goal-directed movements. The implications of a dual role of the basal ganglia in the control of vigor and response to reward are also discussed.

In contrast to our increasingly detailed understanding of how synaptic plasticity provides a cellular substrate for learning and memory, it is less clear how a neuron’s voltage-gated ion channels interact with plastic changes in synaptic strength to influence behavior. We find, using generalized and regional knockout mice, that deletion of the HCN1 channel causes profound motor learning and memory deficits in swimming and rotarod tasks. In cerebellar Purkinje cells, which are a key component of the cerebellar circuit for learning of correctly timed movements, HCN1 mediates an inward current that stabilizes the integrative properties of Purkinje cells and ensures that their input-output function is independent of the previous history of their activity. We suggest that this nonsynaptic integrative function of HCN1 is required for accurate decoding of input patterns and thereby enables synaptic plasticity to appropriately influence the performance of motor activity.

Dysfunction of the basal ganglia produces severe deficits in the timing, initiation, and vigor of movement. These diverse impairments suggest a control system gone awry. In engineered systems, feedback is critical for control. By contrast, models of the basal ganglia highlight feedforward circuitry and ignore intrinsic feedback circuits. In this study, we show that feedback via axon collaterals of substantia nigra projection neurons control the gain of the basal ganglia output. Through a combination of physiology, optogenetics, anatomy, and circuit mapping, we elaborate a general circuit mechanism for gain control in a microcircuit lacking interneurons. Our data suggest that diverse tonic firing rates, weak unitary connections and a spatially diffuse collateral circuit with distinct topography and kinetics from feedforward input is sufficient to implement divisive feedback inhibition. The importance of feedback for engineered systems implies that the intranigral microcircuit, despite its absence from canonical models, could be essential to basal ganglia function. DOI: http://dx.doi.org/10.7554/eLife.02397.001.

Animals adapt their behavior in response to informative sensory cues using multiple brain circuits. The activity of midbrain dopaminergic neurons is thought to convey a critical teaching signal: reward-prediction error. Although reward-prediction error signals are thought to be essential to learning, little is known about the dynamic changes in the activity of midbrain dopaminergic neurons as animals learn about novel sensory cues and appetitive rewards. Here we describe a large dataset of cell-attached recordings of identified dopaminergic neurons as naive mice learned a novel cue-reward association. During learning midbrain dopaminergic neuron activity results from the summation of sensory cue-related and movement initiation-related response components. These components are both a function of reward expectation yet they are dissociable. Learning produces an increasingly precise coordination of action initiation following sensory cues that results in apparent reward-prediction error correlates. Our data thus provide new insights into the circuit mechanisms that underlie a critical computation in a highly conserved learning circuit.