Neurotransmitter classification from electron microscopy images at synaptic sites in Drosophila melanogaster.

High-resolution electron microscopy of nervous systems has enabled the reconstruction of synaptic connectomes. However, we do not know the synaptic sign for each connection (i.e., whether a connection is excitatory or inhibitory), which is implied by the released transmitter. We demonstrate that artificial neural networks can predict transmitter types for presynapses from electron micrographs: a network trained to predict six transmitters (acetylcholine, glutamate, GABA, serotonin, dopamine, octopamine) achieves an accuracy of 87% for individual synapses, 94% for neurons, and 91% for known cell types across a D. melanogaster whole brain. We visualize the ultrastructural features used for prediction, discovering subtle but significant differences between transmitter phenotypes. We also analyze transmitter distributions across the brain and find that neurons that develop together largely express only one fast-acting transmitter (acetylcholine, glutamate, or GABA). We hope that our publicly available predictions act as an accelerant for neuroscientific hypothesis generation for the fly.

Analysis and Optimization of Equitable US Cancer Clinical Trial Center Access by Travel Time.

Importance: Racially minoritized and socioeconomically disadvantaged populations are currently underrepresented in clinical trials. Data-driven, quantitative analyses and strategies are required to help address this inequity. Objective: To systematically analyze the geographical distribution of self-identified racial and socioeconomic demographics within commuting distance to cancer clinical trial centers and other hospitals in the US. Design, Setting, and Participants: This longitudinal quantitative study used data from the US Census 2020 Decennial and American community survey (which collects data from all US residents), OpenStreetMap, National Cancer Institute-designated Cancer Centers list, Nature Index of Cancer Research Health Institutions, National Trial registry, and National Homeland Infrastructure Foundation-Level Data. Statistical analyses were performed on data collected between 2006 and 2020. Main Outcomes and Measures: Population distributions of socioeconomic deprivation indices and self-identified race within 30-, 60-, and 120-minute 1-way driving commute times from US cancer trial sites. Map overlay of high deprivation index and high diversity areas with existing hospitals, existing major cancer trial centers, and commuting distance to the closest cancer trial center. Results: The 78 major US cancer trial centers that are involved in 94% of all US cancer trials and included in this study were found to be located in areas with socioeconomically more affluent populations with higher proportions of self-identified White individuals (+10.1% unpaired mean difference; 95% CI, +6.8% to +13.7%) compared with the national average. The top 10th percentile of all US hospitals has catchment populations with a range of absolute sum difference from 2.4% to 35% from one-third each of Asian/multiracial/other (Asian alone, American Indian or Alaska Native alone, Native Hawaiian or Other Pacific Islander alone, some other race alone, population of 2 or more races), Black or African American, and White populations. Currently available data are sufficient to identify diverse census tracks within preset commuting times (30, 60, or 120 minutes) from all hospitals in the US (N = 7623). Maps are presented for each US city above 500 000 inhabitants, which display all prospective hospitals and major cancer trial sites within commutable distance to racially diverse and socioeconomically disadvantaged populations. Conclusion and Relevance: This study identified biases in the sociodemographics of populations living within commuting distance to US-based cancer trial sites and enables the determination of more equitably commutable prospective satellite hospital sites that could be mobilized for enhanced racial and socioeconomic representation in clinical trials. The maps generated in this work may inform the design of future clinical trials or investigations in enrollment and retention strategies for clinical trials; however, other recruitment barriers still need to be addressed to ensure racial and socioeconomic demographics within the geographical vicinity of a clinical site can translate to equitable trial participant representation.

Determinants of left atrial local impedance: Relationships with contact force, atrial fibrosis, and rhythm.

INTRODUCTION: The relationships between baseline tissue local impedance (LI), contact force (CF), atrial fibrosis, and atrial rhythm are uninvestigated in a clinical setting. We compared the relationship of LI and CF between atrial fibrillation (AF) and sinus rhythm (SR) accounting for the effects of atrial fibrosis as assessed by bipolar voltage and LI. METHODS: Patients undergoing persistent AF ablation were recruited. LI was recorded referenced to patient blood pool (LIr) and concurrent to changes in CF, with data collected at the same locations in AF and SR. RESULTS: Twenty patients were recruited. 109 locations were sampled obtaining 1903 data points (SR: 966, AF: 937). CF correlated strongly with LI (repeated measures correlation = 0.64). The relationship between CF and LIr was logarithmic. Rhythm and CF had a significant main (both p < .0005) and interaction effect (p = .022) on tissue LI: AF demonstrated higher LIr values than SR for similar CF. Bipolar voltage had no effect on the relationship of CF to LIr in either rhythm. Assessing fibrosis using LIr showed an interaction effect with CF for LIr in SR and AF, (SR: p < .0005, AF: p = .01), with increased fibrosis showing lesser change in LIr per gram of CF. CONCLUSIONS: CF and rhythm significantly affect the measured LIr of LA myocardium. Optimal catheter-tissue coupling may be better achieved with higher levels of CF and in AF rather than SR. Atrial fibrosis, as assessed by LIr but not bipolar voltage, affected the CF-LI relationship.

Network Statistics of the Whole-Brain Connectome of Drosophila.

Brains comprise complex networks of neurons and connections. Network analysis applied to the wiring diagrams of brains can offer insights into how brains support computations and regulate information flow. The completion of the first whole-brain connectome of an adult Drosophila, the largest connectome to date, containing 130,000 neurons and millions of connections, offers an unprecedented opportunity to analyze its network properties and topological features. To gain insights into local connectivity, we computed the prevalence of two- and three-node network motifs, examined their strengths and neurotransmitter compositions, and compared these topological metrics with wiring diagrams of other animals. We discovered that the network of the fly brain displays rich club organization, with a large population (30% percent of the connectome) of highly connected neurons. We identified subsets of rich club neurons that may serve as integrators or broadcasters of signals. Finally, we examined subnetworks based on 78 anatomically defined brain regions or neuropils. These data products are shared within the FlyWire Codex and will serve as a foundation for models and experiments exploring the relationship between neural activity and anatomical structure.

Comparison of voltages between atria: differences in sinus rhythm and atrial fibrillation.

BACKGROUND: Ultra high-density mapping systems allow for comparison of atrial electroanatomical maps in unprecedented detail. Atrial scar determined by voltages and surface area between atria, rhythm and atrial fibrillation (AF) types was assessed. METHODS: Left (LA) and right atrial (RA) maps were created using Rhythmia HDx in patients listed for ablation for paroxysmal (PAF, sinus rhythm (SR) maps only) or persistent AF (PeAF, AF and SR maps). Electrograms on corresponding SR/AF maps were paired for direct comparison. Percentage surface area of scar was assigned low- (LVM, ≤ 0.05 mV), intermediate- (IVM, 0.05-0.5 mV) or normal voltage myocardium, (NVM, > 0.5 mV). RESULTS: Thirty-eight patients were recruited generating 96 maps using 913,480 electrograms. Paired SR-AF bipolar electrograms showed fair correlation in LA (Spearman's ρ = 0.32) and weak correlation in RA (ρ = 0.19) and were significantly higher in SR in both (LA: 0.61 mV (0.20-1.67) vs 0.31 mV (0.10-0.74), RA: 0.68 mV (0.19-1.88) vs 0.47 mV (0.14-1.07), p < 0.0005 both). Voltages were significantly higher in patients with PAF over PeAF, (LA: 1.13 mV (0.39-2.93) vs 0.52 mV (0.16-1.49); RA: 0.93 mV (0.24-2.46) vs 0.57 mV (0.17-1.69)). Minimal differences were seen in electrogram voltages between atria. Significantly more IVM/LVM surface areas were seen in AF over SR (LA only, p < 0005), and PeAF over PAF (LA: p = 0.01, RA: p = 0.04). There was minimal difference between atria within patients. CONCLUSIONS: Ultra high-density mapping shows paired electrograms correlate poorly between SR and AF. SR electrograms are typically (but not always) larger than those in AF. Patients with PeAF have a lower global electrogram voltage than those with PAF. Electrogram voltages are similar between atria within individual patients.

Whole-brain annotation and multi-connectome cell typing quantifies circuit stereotypy in Drosophila.

The fruit fly Drosophila melanogaster combines surprisingly sophisticated behaviour with a highly tractable nervous system. A large part of the fly's success as a model organism in modern neuroscience stems from the concentration of collaboratively generated molecular genetic and digital resources. As presented in our FlyWire companion paper 1 , this now includes the first full brain connectome of an adult animal. Here we report the systematic and hierarchical annotation of this ~130,000-neuron connectome including neuronal classes, cell types and developmental units (hemilineages). This enables any researcher to navigate this huge dataset and find systems and neurons of interest, linked to the literature through the Virtual Fly Brain database 2 . Crucially, this resource includes 4,552 cell types. 3,094 are rigorous consensus validations of cell types previously proposed in the hemibrain connectome 3 . In addition, we propose 1,458 new cell types, arising mostly from the fact that the FlyWire connectome spans the whole brain, whereas the hemibrain derives from a subvolume. Comparison of FlyWire and the hemibrain showed that cell type counts and strong connections were largely stable, but connection weights were surprisingly variable within and across animals. Further analysis defined simple heuristics for connectome interpretation: connections stronger than 10 unitary synapses or providing >1% of the input to a target cell are highly conserved. Some cell types showed increased variability across connectomes: the most common cell type in the mushroom body, required for learning and memory, is almost twice as numerous in FlyWire as the hemibrain. We find evidence for functional homeostasis through adjustments of the absolute amount of excitatory input while maintaining the excitation-inhibition ratio. Finally, and surprisingly, about one third of the cell types proposed in the hemibrain connectome could not yet be reliably identified in the FlyWire connectome. We therefore suggest that cell types should be defined to be robust to inter-individual variation, namely as groups of cells that are quantitatively more similar to cells in a different brain than to any other cell in the same brain. Joint analysis of the FlyWire and hemibrain connectomes demonstrates the viability and utility of this new definition. Our work defines a consensus cell type atlas for the fly brain and provides both an intellectual framework and open source toolchain for brain-scale comparative connectomics.

Neuronal wiring diagram of an adult brain.

Connections between neurons can be mapped by acquiring and analyzing electron microscopic (EM) brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative, yet inadequate for understanding brain function more globally. Here, we present the first neuronal wiring diagram of a whole adult brain, containing 5×107 chemical synapses between ~130,000 neurons reconstructed from a female Drosophila melanogaster. The resource also incorporates annotations of cell classes and types, nerves, hemilineages, and predictions of neurotransmitter identities. Data products are available by download, programmatic access, and interactive browsing and made interoperable with other fly data resources. We show how to derive a projectome, a map of projections between regions, from the connectome. We demonstrate the tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine, and descending neurons), across both hemispheres, and between the central brain and the optic lobes. Tracing from a subset of photoreceptors all the way to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviors. The technologies and open ecosystem of the FlyWire Consortium set the stage for future large-scale connectome projects in other species.

Combinatorial encoding of odors in the mosquito antennal lobe.

Among the cues that a mosquito uses to find a host for blood-feeding, the smell of the host plays an important role. Previous studies have shown that host odors contain hundreds of chemical odorants, which are detected by different receptors on the peripheral sensory organs of mosquitoes. But how individual odorants are encoded by downstream neurons in the mosquito brain is not known. We developed an in vivo preparation for patch-clamp electrophysiology to record from projection neurons and local neurons in the antennal lobe of Aedes aegypti. Combining intracellular recordings with dye-fills, morphological reconstructions, and immunohistochemistry, we identify different sub-classes of antennal lobe neurons and their putative interactions. Our recordings show that an odorant can activate multiple neurons innervating different glomeruli, and that the stimulus identity and its behavioral preference are represented in the population activity of the projection neurons. Our results provide a detailed description of the second-order olfactory neurons in the central nervous system of mosquitoes and lay a foundation for understanding the neural basis of their olfactory behaviors.

A U.K. Multicenter Retrospective Study of the Learning Curve and Relative Impact on Success Rates and Procedural Metrics of the RHYTHMIA HDx™ Mapping System.

The learning curve for the novel RHYTHMIA HDx™ 3-dimensional electroanatomic system is unknown. Retrospective data collection was carried out at 3 U.K. centers from the introduction of RHYTHMIA HDx™ (Boston Scientific, Marlborough, MA, USA) and associated mapping and ablation catheters. Patients were matched with controls using the CARTO® 3 mapping system (Biosense Webster Inc., Diamond Bar, CA, USA). Fluoroscopy, radiofrequency ablation, and procedure times; acute and long-term success; and complications were assessed. A total of 253 study patients along with 253 controls were included. Significant correlations existed between procedural efficiency metrics and center experience for de novo atrial fibrillation (AF) ablation (procedure time, Spearman's ρ = -0.624; ablation time, ρ = -0.795; both P < .0005) and de novo atrial flutter (AFL) ablation (ablation time, ρ = -0.566; fluoroscopy time, ρ = -0.520; both P = .001). No correlations existed for other assessed atrial arrhythmias. For de novo AF and AFL, metrics significantly improved after 10 procedures in each center (procedure time [AF only, P = .001], ablation time [AF, P < .0005; AFL, P < .0005], and fluoroscopy time [AFL only, P = .0022]) and became comparable to those of controls. Acute success and long-term success did not experience significant improvements with experience, but they were comparable to the control group throughout. Complications with RHYTHMIA HDx™ were comparable to those associated with CARTO® 3. In conclusion, a short learning curve exists with the use of RHYTHMIA HDx™ for standardized procedures (de novo AF/AFL). Procedural performance improved and became comparable to that seen with CARTO® 3 following 10 cases at each center. Clinical outcomes at 6 and 12 months and complications were no different from those observed in controls.

A leaky integrate-and-fire computational model based on the connectome of the entire adult Drosophila brain reveals insights into sensorimotor processing.

The forthcoming assembly of the adult Drosophila melanogaster central brain connectome, containing over 125,000 neurons and 50 million synaptic connections, provides a template for examining sensory processing throughout the brain. Here, we create a leaky integrate-and-fire computational model of the entire Drosophila brain, based on neural connectivity and neurotransmitter identity, to study circuit properties of feeding and grooming behaviors. We show that activation of sugar-sensing or water-sensing gustatory neurons in the computational model accurately predicts neurons that respond to tastes and are required for feeding initiation. Computational activation of neurons in the feeding region of the Drosophila brain predicts those that elicit motor neuron firing, a testable hypothesis that we validate by optogenetic activation and behavioral studies. Moreover, computational activation of different classes of gustatory neurons makes accurate predictions of how multiple taste modalities interact, providing circuit-level insight into aversive and appetitive taste processing. Our computational model predicts that the sugar and water pathways form a partially shared appetitive feeding initiation pathway, which our calcium imaging and behavioral experiments confirm. Additionally, we applied this model to mechanosensory circuits and found that computational activation of mechanosensory neurons predicts activation of a small set of neurons comprising the antennal grooming circuit that do not overlap with gustatory circuits, and accurately describes the circuit response upon activation of different mechanosensory subtypes. Our results demonstrate that modeling brain circuits purely from connectivity and predicted neurotransmitter identity generates experimentally testable hypotheses and can accurately describe complete sensorimotor transformations.

Radiofrequency Ablation of the Diseased Human Left Ventricle: Biophysical and Electrogram-Based Analysis.

BACKGROUND: Predictors of effective ablation lesion delivery in the human left ventricle are not established, particularly in scar. Impedance drop and electrogram (EGM) attenuation are potential surrogates to assess this. OBJECTIVES: This study sought to establish the relationships between ablation index (AI) and force-time integral (FTI) with impedance drop and EGM attenuation in the human left ventricle. METHODS: Patients undergoing ventricular tachycardia ablation were recruited. EGMs were collected preablation and postablation, with impedance, AI, and FTI measured during. Based on preablation bipolar voltage, myocardium was adjudged a low-voltage myocardium (LVM) (<0.50 mV), intermediate-voltage myocardium (IVM) (0.51-1.50 mV), and normal-voltage myocardium (NVM) (>1.50 mV). Relationships between these parameters were explored. RESULTS: A total of 402 ablations were analyzed in 15 patients. The percent impedance drop correlated with AI and FTI (P < 0.0005; repeated-measures correlation coefficient: 0.54 and 0.44, respectively), a relationship that became weaker with increased myocardial fibrosis, (repeated-measures correlation coefficient for NVM, IVM, and LVM, AI: 0.67, 0.60, and 0.52, respectively; FTI: 0.59, 0.51, and 0.42, respectively). The curve between AI/FTI and impedance drop plateaued at 763 AI and 713 gram-seconds, an impedance drop of 7.5%. Shallower curves occurred progressively from NVM to LVM (P < 0.0005). Mixed models demonstrated that AI and FTI had a greater effect on impedance drop than myocardial fibrosis, drift, or orientation, (standardized ß: 0.54 and 0.48, respectively). EGMs were attenuated with ablation (29.3%; IQR: 4.4%-53.3%; P < 0.0005), but attenuation did not correlate with AI or FTI. CONCLUSIONS: On biophysical analysis, ablation beyond an AI of 763 and FTI of 713 gs offers minimal additional efficacy on average. Fibrosis blunts ablation efficacy. AI is a stronger correlate with impedance drop than FTI. EGM attenuation does not correlate with ablation parameters. (Late Potentials and Ablation Index in Ventricular Tachycardia Ablation; NCT03437408).

Systems neuroscience: Auditory processing at synaptic resolution.

Deeper layers of the auditory system have not been fully mapped in any model system. A new study links comprehensive connectomics of Drosophila song perception circuits to physiological response profiles.

Iatrogenic cardiac perforation due to pacemaker and defibrillator leads: a contemporary multicentre experience.

AIMS: To determine the incidence, clinical features, management, and outcomes of pacemaker (PM) and implantable cardioverter-defibrillator (ICD) lead cardiac perforation. Cardiac perforations due to PM and ICD leads are rare but serious complications. Clinical features vary widely and may cause diagnostic delay. Management strategies are non-guideline based due to paucity of data. METHODS AND RESULTS: A multicentre retrospective series including 3 UK cardiac tertiary centres from 2016 to 2020. Patient, device, and lead characteristics were obtained including 6-month outcomes. Seventy cases of perforation were identified from 10 631 procedures; perforation rate was 0.50% for local implants. Thirty-nine (56%) patients were female, mean ( ± standard deviation) age 74 ( ± 13.8) years. Left ventricular ejection fraction 51 ( ± 13.2) %. Median time to diagnosis was 9 (range: 0-989) days. Computed tomography (CT) diagnosed perforation with 97% sensitivity. Lead parameter abnormalities were present in 86% (whole cohort) and 98.6% for perforations diagnosed >24 h. Chest pain was the commonest symptom, present in 46%. The management strategy was percutaneous in 98.6% with complete procedural success in 98.6%. Pericardial effusion with tamponade was present in 17% and was associated with significantly increased mortality and major complications. Anticoagulation status was associated with tamponade by multivariate analysis (odds ratio 21.7, 95% confidence interval: 1.7-275.5, P = 0.018). CONCLUSIONS: Perforation was rare (0.50%) and managed successfully by a percutaneous strategy with good outcomes. Tamponade was associated with increased mortality and major complications. Anticoagulation status was an independent predictor of tamponade. Case complexity is highly variable and requires skilled operators with a multi-disciplinary approach to achieve good outcomes.

Prolonged standing behaviour in people with joint hypermobility syndrome.

BACKGROUND: Joint Hypermobility Syndrome (JHS) is a rare Heritable Disorder of Connective tissue characterised by generalised joint laxity and chronic widespread pain. Joint Hypermobility Syndrome has a large impact on patients' day to day activities, and many complain of symptoms when standing for prolonged periods. This study investigates whether people with JHS exhibit the same behaviours to deal with the effects of prolonged standing as people with equal hypermobility and no pain, and people with normal flexibility and no pain. METHODS: Twenty three people with JHS, 22 people with Generalised Joint Hypermobility (GJH), and 22 people with normal flexibility (NF) were asked to stand for a maximum of 15 min across two force-plates. Fidgets were counted and quantified using a cumulative sum algorithm and sway parameters of the quiet standing periods between fidgets were calculated. RESULTS: Average standing time for participants with JHS was 7.35 min and none stood for the full 15 min. All participants with GJH and NF completed 15 min of standing. There were no differences in fidgeting behaviour between any groups. There was a difference in anteroposterior sway (p = .029) during the quiet standing periods. CONCLUSION: There is no evidence to suggest people with JHS exhibit different fidgeting behaviour. Increased anteroposterior-sway may suggest a muscle weakness and strengthening muscles around the ankle may reduce postural sway and potentially improve the ability to stand for prolonged periods.

Comparing sagittal plane kinematics and kinetics of gait and stair climbing between hypermobile and non-hypermobile people; a cross-sectional study.

BACKGROUND: Joint Hypermobility Syndrome (JHS) presents with a range of symptoms including widespread joint hypermobility and chronic arthralgia. The study objective was to investigate whether impairments in JHS are due to hypermobility or another factor of JHS by identifying impairments in gait and stair-climbing tasks; an activity that is demanding and so may better show differences between the cohorts. METHODS: Sixty-eight adults participated; 23 JHS, 23 Generalised Joint Hypermobility (GJH), and 22 Normal Flexibility (NF). Inclusion criteria for JHS participants were a positive classification using the Brighton Criteria, for GJH a Beighton Score ≥ 4, and for NF a Beighton Score < 4 with no hypermobile knees. Participants were recorded with a 10-camera Vicon system whilst they performed gait and stair-climbing. Temporal-spatial, and sagittal plane kinematic and kinetic outcome measures were calculated and input to statistical analyses by statistical parametric mapping (SPM). RESULTS: During the gait activity JHS had significantly greater stride time and significantly lower velocity than NF, and significantly greater stride time, lower velocity, and lower stride length than GJH. SPM analysis showed no significant differences between groups in gait kinematics. There were significant differences between groups for gait moments and powers; people with JHS tended to have lower moments and generate less power at the ankle, and favour power generation at the knee. A similar strategy was present in stair ascent. During stair descent people with JHS showed significantly more hip flexion than people with NF. CONCLUSIONS: As there was only one significant difference between GJH and NF we conclude that impairments cannot be attributed to hypermobility alone, but rather other factor(s) of JHS. The results show that both gait and stair-climbing is impaired in JHS. Stair-climbing results indicate that JHS are using a knee-strategy and avoiding use of the ankle, which may be a factor for clinicians to consider during treatment.

Information flow, cell types and stereotypy in a full olfactory connectome.

The hemibrain connectome provides large-scale connectivity and morphology information for the majority of the central brain of Drosophila melanogaster. Using this data set, we provide a complete description of the Drosophila olfactory system, covering all first, second and lateral horn-associated third-order neurons. We develop a generally applicable strategy to extract information flow and layered organisation from connectome graphs, mapping olfactory input to descending interneurons. This identifies a range of motifs including highly lateralised circuits in the antennal lobe and patterns of convergence downstream of the mushroom body and lateral horn. Leveraging a second data set we provide a first quantitative assessment of inter- versus intra-individual stereotypy. Comparing neurons across two brains (three hemispheres) reveals striking similarity in neuronal morphology across brains. Connectivity correlates with morphology and neurons of the same morphological type show similar connection variability within the same brain as across two brains.

Adaptation of balance reactions following forward perturbations in people with joint hypermobility syndrome.

BACKGROUND: Joint Hypermobility Syndrome (JHS) is a Heritable Disorder of Connective tissue characterised by joint laxity and chronic widespread arthralgia. People with JHS exhibit a range of other symptoms including balance problems. To explore balance further, the objective of this study is to compare responses to forward perturbations between three groups; people who are hypermobile with (JHS) and without symptoms and people with normal flexibility. METHODS: Twenty-one participants with JHS, 23 participants with Generalised Joint Hypermobility (GJH) and 22 participants who have normal flexibility (NF) stood on a platform that performed 6 sequential, sudden forward perturbations (the platform moved to the anterior to the participant). Electromyographic outcomes (EMG) and kinematics for the lower limbs were recorded using a Vicon motion capture system. Within and between group comparisons were made using Kruskal Wallis tests. RESULTS: There were no significant differences between groups in muscle onset latency. At the 1st perturbation the group with JHS had significantly longer time-to-peak amplitude than the NF group in tibialis anterior, vastus medialis, rectus femoris, vastus lateralis, and than the GJH group in the gluteus medius. The JHS group showed significantly higher cumulative joint angle (CA) than the NF group in the hip and knee at the 1st and 2nd and 6th perturbation, and in the ankle at the 2nd perturbation. Participants with JHS had significantly higher CA than the GJH group at the in the hip and knee in the 1st and 2nd perturbation. There were no significant differences in TTR. CONCLUSIONS: The JHS group were able to normalise the timing of their muscular response in relation to control groups. They were less able to normalise joint CA, which may be indicative of impaired balance control and strength, resulting in reduced stability.

The connectome of the adult Drosophila mushroom body provides insights into function.

Making inferences about the computations performed by neuronal circuits from synapse-level connectivity maps is an emerging opportunity in neuroscience. The mushroom body (MB) is well positioned for developing and testing such an approach due to its conserved neuronal architecture, recently completed dense connectome, and extensive prior experimental studies of its roles in learning, memory, and activity regulation. Here, we identify new components of the MB circuit in Drosophila, including extensive visual input and MB output neurons (MBONs) with direct connections to descending neurons. We find unexpected structure in sensory inputs, in the transfer of information about different sensory modalities to MBONs, and in the modulation of that transfer by dopaminergic neurons (DANs). We provide insights into the circuitry used to integrate MB outputs, connectivity between the MB and the central complex and inputs to DANs, including feedback from MBONs. Our results provide a foundation for further theoretical and experimental work.

BAcTrace, a tool for retrograde tracing of neuronal circuits in Drosophila.

Animal behavior is encoded in neuronal circuits in the brain. To elucidate the function of these circuits, it is necessary to identify, record from and manipulate networks of connected neurons. Here we present BAcTrace (Botulinum-Activated Tracer), a genetically encoded, retrograde, transsynaptic labeling system. BAcTrace is based on Clostridium botulinum neurotoxin A, Botox, which we engineered to travel retrogradely between neurons to activate an otherwise silent transcription factor. We validated BAcTrace at three neuronal connections in the Drosophila olfactory system. We show that BAcTrace-mediated labeling allows electrophysiological recording of connected neurons. Finally, in a challenging circuit with highly divergent connections, BAcTrace correctly identified 12 of 16 connections that were previously observed by electron microscopy.