BRCA2 is an essential tumor suppressor protein involved in promoting faithful repair of DNA lesions. The activity of BRCA2 needs to be tuned precisely to be active when and where it is needed. Here, we quantified the spatio-temporal dynamics of BRCA2 in living cells using aberration-corrected multifocal microscopy (acMFM). Using multicolor imaging to identify DNA damage sites, we were able to quantify its dynamic motion patterns in the nucleus and at DNA damage sites. While a large fraction of BRCA2 molecules localized near DNA damage sites appear immobile, an additional fraction of molecules exhibits subdiffusive motion, providing a potential mechanism to retain an increased number of molecules at DNA lesions. Super-resolution microscopy revealed inhomogeneous localization of BRCA2 relative to other DNA repair factors at sites of DNA damage. This suggests the presence of multiple nanoscale compartments in the chromatin surrounding the DNA lesion, which could play an important role in the contribution of BRCA2 to the regulation of the repair process.

Survival behaviors are orchestrated by hardwired circuits located in deep subcortical brain regions, most prominently the hypothalamus. Artificial activation of spatially localized, genetically defined hypothalamic cell populations is known to trigger distinct behaviors, suggesting a nucleus-centered organization of behavioral control. However, no study has investigated the hypothalamic representation of innate behaviors using unbiased, large-scale single neuron recordings. Here, using custom silicon probes, we performed recordings across the rostro-caudal extent of the medial hypothalamus in freely moving animals engaged in a diverse array of social and predator defense (“fear”) behaviors. Nucleus-averaged activity revealed spatially distributed generic “ignition signals” that occurred at the onset of each behavior, and did not identify sparse, nucleus-specific behavioral representations. Single-unit analysis revealed that social and fear behavior classes are encoded by activity in distinct sets of spatially distributed neuronal ensembles spanning the entire hypothalamic rostro-caudal axis. Individual ensemble membership, however, was drawn from neurons in 3-4 adjacent nuclei. Mixed selectivity was identified as the most prevalent mode of behavior representation by individual hypothalamic neurons. Encoding models indicated that a significant fraction of the variance in single neuron activity is explained by behavior. This work reveals that innate behaviors are encoded in the hypothalamus by activity in spatially distributed neural ensembles that each span multiple neighboring nuclei, complementing the prevailing view of hypothalamic behavioral control by single nucleus-restricted cell types derived from perturbational studies.

Task-related neural activity is widespread across populations of neurons during goal-directed behaviors. However, little is known about the synaptic reorganization and circuit mechanisms that lead to broad activity changes. Here we trained a subset of neurons in a spiking network with strong synaptic interactions to reproduce the activity of neurons in the motor cortex during a decision-making task. Task-related activity, resembling the neural data, emerged across the network, even in the untrained neurons. Analysis of trained networks showed that strong untrained synapses, which were independent of the task and determined the dynamical state of the network, mediated the spread of task-related activity. Optogenetic perturbations suggest that the motor cortex is strongly-coupled, supporting the applicability of the mechanism to cortical networks. Our results reveal a cortical mechanism that facilitates distributed representations of task-variables by spreading the activity from a subset of plastic neurons to the entire network through task-independent strong synapses.

The C9orf72 hexanucleotide repeat expansion (HRE) is the most frequent genetic cause of the neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Here, we describe the pathogenic cascades that are initiated by the C9orf72 HRE DNA. The HRE DNA binds to its protein partner DAXX and promotes its liquid-liquid phase separation, which is capable of reorganizing genomic structures. An HRE-dependent nuclear accumulation of DAXX drives chromatin remodeling and epigenetic changes such as histone hypermethylation and hypoacetylation in patient cells. While regulating global gene expression, DAXX plays a key role in the suppression of basal and stress-inducible expression of C9orf72 via chromatin remodeling and epigenetic modifications of the promoter of the major C9orf72 transcript. Downregulation of DAXX or rebalancing the epigenetic modifications mitigates the stress-induced sensitivity of C9orf72-patient-derived motor neurons. These studies reveal a C9orf72 HRE DNA-dependent regulatory mechanism for both local and genomic architectural changes in the relevant diseases.

The mushroom body (MB) is the center for associative learning in insects. In Drosophila, intersectional split-GAL4 drivers and electron microscopy (EM) connectomes have laid the foundation for precise interrogation of the MB neural circuits. However, many cell types upstream and downstream of the MB remained to be investigated due to lack of driver lines. Here we describe a new collection of over 800 split-GAL4 and split-LexA drivers that cover approximately 300 cell types, including sugar sensory neurons, putative nociceptive ascending neurons, olfactory and thermo-/hygro-sensory projection neurons, interneurons connected with the MB-extrinsic neurons, and various other cell types. We characterized activation phenotypes for a subset of these lines and identified the sugar sensory neuron line most suitable for reward substitution. Leveraging the thousands of confocal microscopy images associated with the collection, we analyzed neuronal morphological stereotypy and discovered that one set of mushroom body output neurons, MBON08/MBON09, exhibits striking individuality and asymmetry across animals. In conjunction with the EM connectome maps, the driver lines reported here offer a powerful resource for functional dissection of neural circuits for associative learning in adult Drosophila.

The nearly constant downward force of gravity has powerfully shaped the behaviors of many organisms [1]. Walking flies readily orient against gravity in a behavior termed negative gravitaxis. In Drosophila this behavior is studied by observing the position of flies in vials [2–4] or simple mazes [5–9]. These assays have been used to conduct forward-genetic screens [5, 6, 8] and as simple tests of locomotion deficits [10–12]. Despite this long history of investigation, the sensory basis of gravitaxis is largely unknown [1]. Recent studies have implicated the antennae as a major mechanosensory input [3, 4], but many details remain unclear. Fly orientation behavior is expected to depend on the direction and amplitude of the gravitational pull, but little is known about the sensitivity of flies to these features of the environment. Here we directly measure the gravity-dependent orientation behavior of flies walking on an adjustable tilted platform, that is inspired by previous insect studies [13–16]. In this arena, flies can freely orient with respect to gravity. Our findings indicate that flies are exquisitely sensitive to the direction of gravity’s pull. Surprisingly, this orientation behavior does not require antennal mechanosensory input, suggesting that other sensory structures must be involved.

Neurons throughout the sensory pathway adapt their responses depending on the statistical structure of the sensory environment. Contrast gain control is a form of adaptation in the auditory cortex, but it is unclear whether the dynamics of gain control reflect efficient adaptation, and whether they shape behavioral perception. Here, we trained mice to detect a target presented in background noise shortly after a change in the contrast of the background. The observed changes in cortical gain and behavioral detection followed the dynamics of a normative model of efficient contrast gain control; specifically, target detection and sensitivity improved slowly in low contrast, but degraded rapidly in high contrast. Auditory cortex was required for this task, and cortical responses were not only similarly affected by contrast but predicted variability in behavioral performance. Combined, our results demonstrate that dynamic gain adaptation supports efficient coding in auditory cortex and predicts the perception of sounds in noise.

Sparse coding can improve discrimination of sensory stimuli by reducing overlap between their representations. Two factors, however, can offset sparse coding's benefits: similar sensory stimuli have significant overlap and responses vary across trials. To elucidate the effects of these 2 factors, we analyzed odor responses in the fly and mouse olfactory regions implicated in learning and discrimination-the mushroom body (MB) and the piriform cortex (PCx). We found that neuronal responses fall along a continuum from extremely reliable across trials to extremely variable or stochastic. Computationally, we show that the observed variability arises from noise within central circuits rather than sensory noise. We propose this coding scheme to be advantageous for coarse- and fine-odor discrimination. More reliable cells enable quick discrimination between dissimilar odors. For similar odors, however, these cells overlap and do not provide distinguishing information. By contrast, more unreliable cells are decorrelated for similar odors, providing distinguishing information, though these benefits only accrue with extended training with more trials. Overall, we have uncovered a conserved, stochastic coding scheme in vertebrates and invertebrates, and we identify a candidate mechanism, based on variability in a winner-take-all (WTA) inhibitory circuit, that improves discrimination with training.

To interpret the sensory environment, the brain combines ambiguous sensory measurements with knowledge that reflects context-specific prior experience. But environmental contexts can change abruptly and unpredictably, resulting in uncertainty about the current context. Here we address two questions: how should context-specific prior knowledge optimally guide the interpretation of sensory stimuli in changing environments, and do human decision-making strategies resemble this optimum? We probe these questions with a task in which subjects report the orientation of ambiguous visual stimuli that were drawn from three dynamically switching distributions, representing different environmental contexts. We derive predictions for an ideal Bayesian observer that leverages knowledge about the statistical structure of the task to maximize decision accuracy, including knowledge about the dynamics of the environment. We show that its decisions are biased by the dynamically changing task context. The magnitude of this decision bias depends on the observer's continually evolving belief about the current context. The model therefore not only predicts that decision bias will grow as the context is indicated more reliably, but also as the stability of the environment increases, and as the number of trials since the last context switch grows. Analysis of human choice data validates all three predictions, suggesting that the brain leverages knowledge of the statistical structure of environmental change when interpreting ambiguous sensory signals.

Focal epilepsy is associated with intermittent brief population discharges (interictal spikes), which resemble sentinel spikes that often occur at the onset of seizures. Why interictal spikes self-terminate whilst seizures persist and propagate is incompletely understood. We used fluorescent glutamate and GABA sensors in an awake rodent model of neocortical seizures to resolve the spatiotemporal evolution of both neurotransmitters in the extracellular space. Interictal spikes were accompanied by brief glutamate transients which were maximal at the initiation site and rapidly propagated centrifugally. GABA transients lasted longer than glutamate transients and were maximal ∼1.5 mm from the focus where they propagated centripetally. Prior to seizure initiation GABA transients were attenuated, whilst glutamate transients increased, consistent with a progressive failure of local inhibitory restraint. As seizures increased in frequency, there was a gradual increase in the spatial extent of spike-associated glutamate transients associated with interictal spikes. Neurotransmitter imaging thus reveals a progressive collapse of an annulus of feed-forward GABA release, allowing seizures to escape from local inhibitory restraint.