Although all sensory circuits ascend to higher brain areas where stimuli are represented in sparse, stimulus-specific activity patterns, relatively little is known about sensory coding on the descending side of neural circuits, as a network converges. In insects, mushroom bodies have been an important model system for studying sparse coding in the olfactory system, where this format is important for accurate memory formation. In Drosophila, it has recently been shown that the 2,000 Kenyon cells of the mushroom body converge onto a population of only 34 mushroom body output neurons (MBONs), which fall into 21 anatomically distinct cell types. Here we provide the first, to our knowledge, comprehensive view of olfactory representations at the fourth layer of the circuit, where we find a clear transition in the principles of sensory coding. We show that MBON tuning curves are highly correlated with one another. This is in sharp contrast to the process of progressive decorrelation of tuning in the earlier layers of the circuit. Instead, at the population level, odour representations are reformatted so that positive and negative correlations arise between representations of different odours. At the single-cell level, we show that uniquely identifiable MBONs display profoundly different tuning across different animals, but that tuning of the same neuron across the two hemispheres of an individual fly was nearly identical. Thus, individualized coordination of tuning arises at this level of the olfactory circuit. Furthermore, we find that this individualization is an active process that requires a learning-related gene, rutabaga. Ultimately, neural circuits have to flexibly map highly stimulus-specific information in sparse layers onto a limited number of different motor outputs. The reformatting of sensory representations we observe here may mark the beginning of this sensory-motor transition in the olfactory system.

The cerebellum plays an important role in both motor control and cognitive function. Cerebellar function is topographically organized and diseases that affect specific parts of the cerebellum are associated with specific patterns of symptoms. Accordingly, delineation and quantification of cerebellar sub-regions from magnetic resonance images are important in the study of cerebellar atrophy and associated functional losses. This paper describes an automated cerebellar lobule segmentation method based on a graph cut segmentation framework. Results from multi-atlas labeling and tissue classification contribute to the region terms in the graph cut energy function and boundary classification contributes to the boundary term in the energy function. A cerebellar parcellation is achieved by minimizing the energy function using the α-expansion technique. The proposed method was evaluated using a leave-one-out cross-validation on 15 subjects including both healthy controls and patients with cerebellar diseases. Based on reported Dice coefficients, the proposed method outperforms two state-of-the-art methods. The proposed method was then applied to 2(j) 77 subjects to study the region-specific cerebellar structural differences in three spinocerebellar ataxia (SCA) genetic subtypes. Quantitative analysis of the lobule volumes show distinct patterns of volume changes associated with different SCA subtypes consistent with known patterns of atrophy in these genetic subtypes.

Spatial and temporal features of synaptic inputs engage integration mechanisms on multiple scales, including presynaptic release sites, postsynaptic dendrites, and networks of inhibitory interneurons. Here we investigate how these mechanisms cooperate to filter synaptic input in hippocampal area CA1. Dendritic recordings from CA1 pyramidal neurons reveal that proximal inputs from CA3 as well as distal inputs from entorhinal cortex layer III (ECIII) sum sublinearly or linearly at low firing rates due to feedforward inhibition, but sum supralinearly at high firing rates due to synaptic facilitation, producing a high-pass filter. However, during ECIII and CA3 input comparison, supralinear dendritic integration is dynamically balanced by feedforward and feedback inhibition, resulting in suppression of dendritic complex spiking. We find that a particular subpopulation of CA1 interneurons expressing neuropeptide Y (NPY) contributes prominently to this dynamic filter by integrating both ECIII and CA3 input pathways and potently inhibiting CA1 pyramidal neuron dendrites.

TFIID-a complex of TATA-binding protein (TBP) and TBP-associated factors (TAFs)-is a central component of the Pol II promoter recognition apparatus. Recent studies have revealed significant downregulation of TFIID subunits in terminally differentiated myocytes, hepatocytes and adipocytes. Here, we report that TBP protein levels are tightly regulated by the ubiquitin-proteasome system. Using an in vitro ubiquitination assay coupled with biochemical fractionation, we identified Huwe1 as an E3 ligase targeting TBP for K48-linked ubiquitination and proteasome-mediated degradation. Upregulation of Huwe1 expression during myogenesis induces TBP degradation and myotube differentiation. We found that Huwe1 activity on TBP is antagonized by the deubiquitinase USP10, which protects TBP from degradation. Thus, modulating the levels of both Huwe1 and USP10 appears to fine-tune the requisite degradation of TBP during myogenesis. Together, our study unmasks a previously unknown interplay between an E3 ligase and a deubiquitinating enzyme regulating TBP levels during cellular differentiation.

Animals use acoustic signals across a variety of social behaviors, particularly courtship. In Drosophila, song is detected by antennal mechanosensory neurons and further processed by second-order aPN1/aLN(al) neurons. However, little is known about the central pathways mediating courtship hearing. In this study, we identified a male-specific pathway for courtship hearing via third-order ventrolateral protocerebrum Projection Neuron 1 (vPN1) neurons and fourth-order pC1 neurons. Genetic inactivation of vPN1 or pC1 disrupts song-induced male-chaining behavior. Calcium imaging reveals that vPN1 responds preferentially to pulse song with long inter-pulse intervals (IPIs), while pC1 responses to pulse song closely match the behavioral chaining responses at different IPIs. Moreover, genetic activation of either vPN1 or pC1 induced courtship chaining, mimicking the behavioral response to song. These results outline the aPN1-vPN1-pC1 pathway as a labeled line for the processing and transformation of courtship song in males.

Genetically encoded calcium indicators (GECIs) permit imaging intracellular calcium transients. Among GECIs, the GFP-based GCaMPs are the most widely used because of their high sensitivity and rapid response to changes in intracellular calcium concentrations. Here we report that the fluorescence of GCaMPs-including GCaMP3, GCaMP5 and GCaMP6-can be converted from green to red following exposure to blue-green light (450-500 nm). This photoconversion occurs in both insect and mammalian cells and is enhanced in a low oxygen environment. The red fluorescent GCaMPs retained calcium responsiveness, albeit with reduced sensitivity. We identified several amino acid residues in GCaMP important for photoconversion and generated a GCaMP variant with increased photoconversion efficiency in cell culture. This light-induced spectral shift allows the ready labeling of specific, targeted sets of GCaMP-expressing cells for functional imaging in the red channel. Together, these findings indicate the potential for greater utility of existing GCaMP reagents, including transgenic animals.

Novel body structures are often generated by the redeployment of ancestral components of the genome. In this issue of Developmental Cell, Glassford et al. (2015) present a thorough analysis of the co-option of a gene regulatory network in the origin of an evolutionary novelty.

N-Methyl-D-aspartate receptors (NMDA-Rs) are ion channels that are important for synaptic plasticity, which is involved in learning and drug addiction. We show enzymatic targeting of an NMDA-R antagonist, MK801, to a molecularly defined neuronal population with the cell-type-selectivity of genetic methods and the temporal control of pharmacology. We find that NMDA-Rs on dopamine neurons are necessary for cocaine-induced synaptic potentiation, demonstrating that cell type-specific pharmacology can be used to dissect signaling pathways within complex brain circuits.

Progressive depletion of midbrain dopamine neurons (PDD) is associated with deficits in the initiation, speed, and fluidity of voluntary movement. Models of basal ganglia function focus on initiation deficits; however, it is unclear how they account for deficits in the speed or amplitude of movement (vigor). Using an effort-based operant conditioning task for head-fixed mice, we discovered distinct functional classes of neurons in the dorsal striatum that represent movement vigor. Mice with PDD exhibited a progressive reduction in vigor, along with a selective impairment of its neural representation in striatum. Restoration of dopaminergic tone with a synthetic precursor ameliorated deficits in movement vigor and its neural representation, while suppression of striatal activity during movement was sufficient to reduce vigor. Thus, dopaminergic input to the dorsal striatum is indispensable for the emergence of striatal activity that mediates adaptive changes in movement vigor. These results suggest refined intervention strategies for Parkinson’s disease.

Brains are optimized for processing ethologically relevant sensory signals. However, few studies have characterized the neural coding mechanisms that underlie the transformation from natural sensory information to behavior. Here, we focus on acoustic communication in Drosophila melanogaster and use computational modeling to link natural courtship song, neuronal codes, and female behavioral responses to song. We show that melanogaster females are sensitive to long timescale song structure (on the order of tens of seconds). From intracellular recordings, we generate models that recapitulate neural responses to acoustic stimuli. We link these neural codes with female behavior by generating model neural responses to natural courtship song. Using a simple decoder, we predict female behavioral responses to the same song stimuli with high accuracy. Our modeling approach reveals how long timescale song features are represented by the Drosophila brain and how neural representations can be decoded to generate behavioral selectivity for acoustic communication signals.