High-precision coding in visual cortex.

Individual neurons in visual cortex provide the brain with unreliable estimates of visual features. It is not known whether the single-neuron variability is correlated across large neural populations, thus impairing the global encoding of stimuli. We recorded simultaneously from up to 50,000 neurons in mouse primary visual cortex (V1) and in higher order visual areas and measured stimulus discrimination thresholds of 0.35° and 0.37°, respectively, in an orientation decoding task. These neural thresholds were almost 100 times smaller than the behavioral discrimination thresholds reported in mice. This discrepancy could not be explained by stimulus properties or arousal states. Furthermore, behavioral variability during a sensory discrimination task could not be explained by neural variability in V1. Instead, behavior-related neural activity arose dynamically across a network of non-sensory brain areas. These results imply that perceptual discrimination in mice is limited by downstream decoders, not by neural noise in sensory representations.

Mesolimbic dopamine adapts the rate of learning from action.

Recent success in training artificial agents and robots derives from a combination of direct learning of behavioural policies and indirect learning through value functions1-3. Policy learning and value learning use distinct algorithms that optimize behavioural performance and reward prediction, respectively. In animals, behavioural learning and the role of mesolimbic dopamine signalling have been extensively evaluated with respect to reward prediction4; however, so far there has been little consideration of how direct policy learning might inform our understanding5. Here we used a comprehensive dataset of orofacial and body movements to understand how behavioural policies evolved as naive, head-restrained mice learned a trace conditioning paradigm. Individual differences in initial dopaminergic reward responses correlated with the emergence of learned behavioural policy, but not the emergence of putative value encoding for a predictive cue. Likewise, physiologically calibrated manipulations of mesolimbic dopamine produced several effects inconsistent with value learning but predicted by a neural-network-based model that used dopamine signals to set an adaptive rate, not an error signal, for behavioural policy learning. This work provides strong evidence that phasic dopamine activity can regulate direct learning of behavioural policies, expanding the explanatory power of reinforcement learning models for animal learning6.

TEMPO enables sequential genetic labeling and manipulation of vertebrate cell lineages.

During development, regulatory factors appear in a precise order to determine cell fates over time. Consequently, to investigate complex tissue development, it is necessary to visualize and manipulate cell lineages with temporal control. Current strategies for tracing vertebrate cell lineages lack genetic access to sequentially produced cells. Here, we present TEMPO (Temporal Encoding and Manipulation in a Predefined Order), an imaging-readable genetic tool allowing differential labeling and manipulation of consecutive cell generations in vertebrates. TEMPO is based on CRISPR and powered by a cascade of gRNAs that drive orderly activation and inactivation of reporters and/or effectors. Using TEMPO to visualize zebrafish and mouse neurogenesis, we recapitulated birth-order-dependent neuronal fates. Temporally manipulating cell-cycle regulators in mouse cortex progenitors altered the proportion and distribution of neurons and glia, revealing the effects of temporal gene perturbation on serial cell fates. Thus, TEMPO enables sequential manipulation of molecular factors, crucial to study cell-type specification.

A Sparse, Spatially Biased Subtype of Mature Granule Cell Dominates Recruitment in Hippocampal-Associated Behaviors.

Animals can store information about experiences by activating specific neuronal populations, and subsequent reactivation of these neural ensembles can lead to recall of salient experiences. In the hippocampus, granule cells of the dentate gyrus participate in such memory engrams; however, whether there is an underlying logic to granule cell participation has not been examined. Here, we find that a range of novel experiences preferentially activates granule cells of the suprapyramidal blade relative to the infrapyramidal blade. Motivated by this, we identify a suprapyramidal-blade-enriched population of granule cells with distinct spatial, morphological, physiological, and developmental properties. Via transcriptomics, we map these traits onto a sparse and discrete granule cell subtype that is recruited at a 10-fold greater frequency than expected by subtype prevalence, constituting the majority of all recruited granule cells. Thus, in behaviors known to involve hippocampal-dependent memory formation, a rare and spatially localized subtype dominates overall granule cell recruitment.

Deconstructing behavioral neuropharmacology with cellular specificity.

Behavior has molecular, cellular, and circuit determinants. However, because many proteins are broadly expressed, their acute manipulation within defined cells has been difficult. Here, we combined the speed and molecular specificity of pharmacology with the cell type specificity of genetic tools. DART (drugs acutely restricted by tethering) is a technique that rapidly localizes drugs to the surface of defined cells, without prior modification of the native target. We first developed an AMPAR antagonist DART, with validation in cultured neuronal assays, in slices of mouse dorsal striatum, and in behaving mice. In parkinsonian animals, motor deficits were causally attributed to AMPARs in indirect spiny projection neurons (iSPNs) and to excess phasic firing of tonically active interneurons (TANs). Together, iSPNs and TANs (i.e., D2 cells) drove akinesia, whereas movement execution deficits reflected the ratio of AMPARs in D2 versus D1 cells. Finally, we designed a muscarinic antagonist DART in one iteration, demonstrating applicability of the method to diverse targets.

A Designer AAV Variant Permits Efficient Retrograde Access to Projection Neurons.

Efficient retrograde access to projection neurons for the delivery of sensors and effectors constitutes an important and enabling capability for neural circuit dissection. Such an approach would also be useful for gene therapy, including the treatment of neurodegenerative disorders characterized by pathological spread through functionally connected and highly distributed networks. Viral vectors, in particular, are powerful gene delivery vehicles for the nervous system, but all available tools suffer from inefficient retrograde transport or limited clinical potential. To address this need, we applied in vivo directed evolution to engineer potent retrograde functionality into the capsid of adeno-associated virus (AAV), a vector that has shown promise in neuroscience research and the clinic. A newly evolved variant, rAAV2-retro, permits robust retrograde access to projection neurons with efficiency comparable to classical synthetic retrograde tracers and enables sufficient sensor/effector expression for functional circuit interrogation and in vivo genome editing in targeted neuronal populations. VIDEO ABSTRACT.