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bioRxiv2025

The hypoxic response extends lifespan through a bioaminergic and peptidergic neural circuit.

A coordinated response to stress is crucial for promoting the short- and long-term health of an organism. The perception of stress, frequently through the nervous system, can lead to physiological changes that are fundamental to maintaining homeostasis. Activating the response to low oxygen, or hypoxia, extends healthspan and lifespan in C. elegans. However, despite some positive impacts, negative effects of the hypoxic response in specific tissues prevent translation of their benefits in mammals. Thus, it is imperative to identify which components of this response promote longevity. Here, we interrogate the cell-nonautonomous signaling pathway downstream of genetic activation of the hypoxic response. We find that HIF-1-mediated signaling in ADF serotonergic neurons is both necessary and sufficient for lifespan extension. Signaling through the serotonin receptor SER-7 in the GABAergic RIS interneurons is necessary in this process. Our findings also highlight the involvement of additional neural signaling molecules, including the neurotransmitters tyramine and GABA, and the neuropeptide NLP-17, in mediating longevity effects. Finally, we demonstrate that oxygen- and carbon-dioxide-sensing neurons act downstream of HIF-1 in this circuit. Together, these insights develop a circuit for how genetic induction of the hypoxic response cell-nonautonomously modulates aging and suggests valuable targets for modulating aging in mammals.

physiology↗

bioRxiv2024

BlueRecording: A Pipeline for the efficient calculation of extracellular recordings in large-scale neural circuit models

As the size and complexity of network simulations accessible to computational neuroscience grows, new avenues open for research into extracellularly recorded electric signals. Biophysically detailed simulations permit the identification of the biological origins of the different components of recorded signals, the evaluation of signal sensitivity to different anatomical, physiological, and geometric factors, and selection of recording parameters to maximize the signal information content. Simultaneously, virtual extracellular signals produced by these networks may become important metrics for neuro-simulation validation. To enable efficient calculation of extracellular signals from large neural network simulations, we have developed BlueRecording, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. In particular, we implement a general form of the reciprocity theorem, which is capable of handling non-dipolar current sources, such as may be found in long axons and recordings close to the current source, as well as complex tissue anatomy, dielectric heterogeneity, and electrode geometries. To our knowledge, this is the first application of this generalized (i.e., non-dipolar) reciprocity-based approach to simulate EEG recordings. We use these tools to calculate extracellular signals from an in silico model of the rat somatosensory cortex and hippocampus and to study signal contribution differences between regions and cell types.

neuroscience↗

bioRxiv2021

Embryonic exposure to cannabidiol disrupts active neural circuits, an effect increased by Δ-tetrahydrocannabinol and involving CB1R and CB2R in zebrafish

In the light of legislative changes and the widespread use of cannabis as a recreational and medicinal drug, delayed effects of cannabis upon brief exposure during embryonic development are of high interest as early pregnancies often go undetected. Here, zebrafish embryos were exposed to cannabidiol (CBD) and {Delta}-9-tetrahydrocannabinol l (THC) until the end of gastrulation (1-10 hours post-fertilization) and analyzed later in development (4-5 days post-fertilization). In order to measure neural activity, we implemented CaMPARI (Calcium-Modulated Photoactivatable Ratiometric Integrator) and optimized the protocol for a 96-well format complemented by locomotor analysis. Our results revealed that neural activity was decreased by CBD more than THC. At higher doses, both cannabinoids could dramatically reduce neural activity and locomotor activity. Interestingly, the decrease was more pronounced when CBD and THC were combined. At the receptor level, CBD-mediated reduction of locomotor activity was partially prevented using cannabinoid type 1 and 2 receptor inhibitors. Overall, we report that CBD toxicity occurs via two cannabinoid receptors and is synergistically enhanced by THC exposure to negatively impact neural activity late in larval development. Future studies are warranted to reveal other cannabinoids and receptors involved in this pathway to understand the subsequent health implications of cannabis consumption on fetal development.

pharmacology and toxicology↗

bioRxiv2022

Polyphasic circadian neural circuits drive differential activities in multiple downstream rhythmic centers

Circadian clocks align various behaviors such as locomotor activity, sleep/wake, feeding, and mating to times of day that are most adaptive. How rhythmic information in pacemaker circuits is translated to neuronal outputs is not well understood. Here we used brain-wide, 24-hr in vivo calcium imaging in the Drosophila brain and searched for circadian rhythmic activity among identified clusters of dopaminergic (DA) and peptidergic neuroendocrine (PNE) neurons. Such rhythms were widespread and imposed by the PERIOD-dependent clock activity within the [~]150 cell circadian pacemaker network. The rhythms displayed either a Morning, an Evening, or Mid-Day phase. Different sub-groups of circadian pacemakers imposed neural activity rhythms onto different downstream non-clock neurons. Outputs from the canonical M and E pacemakers converged to regulate DA-PPM3 and DA-PAL neurons. E pacemakers regulate the Evening-active DA-PPL1 neurons. In addition to these canonical M and E oscillators, we present evidence for a third dedicated phase occurring at Mid-Day (MD): the l-LNv pacemakers present the MD activity peak and they regulate the MD-active DA-PPM1/2 neurons and three distinct PNE cell types. Thus, the Drosophila circadian pacemaker network is a polyphasic rhythm generator. It presents dedicated M, E and MD phases that are functionally transduced as neuronal outputs to organize diverse daily activity patterns in downstream circuits.

neuroscience↗

bioRxiv2017

Neural circuits for long-range color filling-in

Surface color appearance depends on both local surface chromaticity and global context. How are these inter-dependencies supported by cortical networks? Combining functional imaging and psychophysics, we examined if color from long-range filling-in engages distinct pathways from responses caused by a field of uniform chromaticity. We find that color from filling-in is best classified and best correlated with appearance by two dorsal areas, V3A and V3B/KO. In contrast, a field of uniform chromaticity is best classified by ventral areas hV4 and LO. Dynamic causal modeling revealed feedback modulation from area V3A to areas V1 and LO for filling-in, contrasting with feedback from LO modulating areas V1 and V3A for a matched uniform chromaticity. These results indicate a dorsal stream role in color filling-in via feedback modulation of area V1 coupled with a cross-stream modulation of ventral areas suggesting that local and contextual influences on color appearance engage distinct neural networks.

neuroscience↗

bioRxiv2024

An Atlas of Brain-Bone Sympathetic Neural Circuits

There is clear evidence that the sympathetic nervous system (SNS) mediates bone metabolism. Histological studies show abundant SNS innervation of the periosteum and bone marrow--these nerves consist of noradrenergic fibers that immunostain for tyrosine hydroxylase, dopamine beta hydroxylase, or neuropeptide Y. Nonetheless, the brain sites that send efferent SNS outflow to bone have not yet been characterized. Using pseudorabies (PRV) viral transneuronal tracing, we report, for the first time, the identification of central SNS outflow sites that innervate bone. We find that the central SNS outflow to bone originates from 87 brain nuclei, sub-nuclei and regions of six brain divisions, namely the midbrain and pons, hypothalamus, hindbrain medulla, forebrain, cerebral cortex, and thalamus. We also find that certain sites, such as the raphe magnus (RMg) of the medulla and periaqueductal gray (PAG) of the midbrain, display greater degrees of PRV152 infection, suggesting that there is considerable site-specific variation in the levels of central SNS outflow to bone. This comprehensive compendium illustrating the central coding and control of SNS efferent signals to bone should allow for a greater understanding of the neural regulation of bone metabolism, and importantly and of clinical relevance, mechanisms for central bone pain.

neuroscience↗

bioRxiv2021

Visual recognition of social signals by a tecto-thalamic neural circuit

Social affiliation emerges from individual-level behavioral rules that are driven by conspecific signals1-5. Long-distance attraction and short-distance repulsion, for example, are rules that jointly set a preferred inter-animal distance in swarms6-8. However, little is known about their perceptual mechanisms and executive neuronal circuits3. Here we trace the neuronal response to self-like biological motion9,10 (BM), a visual trigger for affiliation in developing zebrafish2,11. Unbiased activity mapping and targeted volumetric two-photon calcium imaging revealed 19 activity hotspots distributed throughout the brain and clustered BM-tuned neurons in a multimodal, socially activated nucleus of the dorsal thalamus (DT). Individual DT neurons encode fish-like local acceleration but are insensitive to global or continuous motion. Electron microscopic reconstruction of DT neurons revealed synaptic input from the optic tectum (TeO/superior colliculus) and projections into nodes of the conserved social behavior network12,13. Chemogenetic ablation of the TeO selectively disrupted DT responses to BM and social attraction without affecting short-distance repulsion. Together, we discovered a tecto-thalamic pathway that drives a core network for social affiliation. Our findings provide an example of visual social processing, and dissociate neuronal control of attraction from repulsion during affiliation, thus revealing neural underpinnings of collective behavior.

neuroscience↗

bioRxiv2016

Matching tutor to student: rules and mechanisms for efficient two-stage learning in neural circuits

Trial-and-error learning requires evaluating variable actions and reinforcing successful variants. In songbirds, vocal exploration is induced by LMAN, the output of a basal ganglia-circuit that also contributes a corrective bias to the vocal output. This bias is gradually consolidated in RA, a motor cortex analogue downstream of LMAN. We develop a new model of such two-stage learning. Using stochastic gradient descent, we derive how the activity in tutor circuits (e.g., LMAN) should match plasticity mechanisms in student circuits (e.g., RA) to achieve efficient learning. We further describe a reinforcement learning framework through which the tutor can build its teaching signal. We show that mismatches between the tutor signal and the plasticity mechanism can impair learning. Applied to birdsong, our results predict the temporal structure of the corrective bias from LMAN given a plasticity rule in RA. Our framework can be applied predictively to other paired brain areas showing two-stage learning.

Animal Behavior and Cognition↗

bioRxiv2017

Conserved Neural Circuit Structure Across Drosophila Larva Development Revealed By Comparative Connectomics

Throughout an animals postembryonic development, neuronal circuits must maintain appropriate output even as the body grows. The contribution of structural adaptation -- neuronal morphology and synaptic connectivity -- to circuit development remains unclear. In a previous paper (Schneider-Mizell et al., 2016), we measured the detailed neuronal morphological structures subserving neuronal connectivity in Drosophila. Here, we examine how neuronal morphology and connectivity change across postembyronic development. Using new and existing serial section electron microscopy volumes, we reconstructed an identified nociceptive circuit in two larvae, one 1st instar and one 3rd instar. We found extremely consistent, topographically-arranged circuit structure. Five-fold increases in size of interneurons were associated with compensatory structural changes that maintained cell-type-specific synaptic input as a fraction of total inputs. An increase in number of synaptic contacts was accompanied with a disproportionate increase in the number of small dendritic terminal branches relative to other neuronal compartments. We propose that these precise patterns of structural growth act to conserve the computational function of a circuit, for example determining the location of a nociceptive stimulus.

neuroscience↗

bioRxiv2020

Navigating the translational roadblock: Towards highly specific and effective all-optical interrogations of neural circuits

Two-photon (2-P) all-optical approaches combine in vivo 2-P calcium imaging and 2-P optogenetic modulations and have the potential to build a framework for network-based therapies, e.g. for rebalancing maladaptive activity patterns in preclinical models of neurological disorders. Here, our goal was to tailor these approaches for this purpose: Firstly, we combined in vivo juxtacellular recordings and GCaMP6f-based 2-P calcium imaging in layer II/III of mouse visual cortex to tune our detection algorithm towards a 100 % specific identification of AP-related calcium transients. False-positive-free detection was achieved at a sensitivity of approximately 73 %. To further increase specificity, secondly, we minimized photostimulation artifacts as a potential source for false-positives by using extended-wavelength-spectrum laser sources for optogenetic stimulation of the excitatory opsin C1V1. We achieved artifact-free all-optical experiments performing photostimulations at 1100 nm or higher and simultaneous calcium imaging at 920 nm in mouse visual cortex in vivo. Thirdly, we determined the spectral range for maximizing efficacy of optogenetic control by performing 2-P photostimulations of individual neurons with wavelengths up to 1300 nm. The rate of evoked transients in GCaMP6f/C1V1-co-expressing cortical neurons peaked already at 1100 nm. By refining spike detection and defining 1100 nm as the optimal wavelength for artifact-free and effective stimulations of C1V1 in GCaMP-based all-optical interrogations, we increased the translational value of these approaches, e.g. for the use in preclinical applications of network-based therapies. One Sentence SummaryWe maximize translational relevance of 2-P all-optical physiology by increasing specificity, minimizing artifacts and optimizing stimulation efficacy.

neuroscience↗

bioRxiv2020

Neural circuits for somatosensory control of auditory thalamocortical processing

Integration of information across the senses is critical for perception and is a common property of neurons in the cerebral cortex, where it is thought to arise primarily from corticocortical connections. Much less is known about the role of subcortical circuits in shaping the multisensory properties of cortical neurons. We show that stimulation of the whiskers causes widespread suppression of sound-evoked activity in mouse primary auditory cortex (A1). This suppression depends on the primary somatosensory cortex (S1), and is implemented through a descending circuit that links S1, via the auditory midbrain, with thalamic neurons that project to A1. Furthermore, a direct pathway from S1 has a facilitatory effect on auditory responses in higher-order thalamic nuclei that project to other brain areas. Crossmodal corticofugal projections to the auditory midbrain and thalamus therefore play a pivotal role in integrating multisensory signals and in enabling communication between different sensory cortical areas.

neuroscience↗

bioRxiv2020

Daily rewiring of a neural circuit generates a predictive model of environmental light

Ongoing sensations are compared to internal, experience-based, reference models; mismatch between reality and expectation can signal opportunity or danger, and can shape behavior. The nature of internal reference models is largely unknown. We describe a model that enables moment-to-moment luminance evaluation in flies. Abrupt shifts to lighting conditions inconsistent with the subjective time-of-day trigger locomotion, whereas shifts to appropriate conditions induce quiescence. The time-of-day prediction is generated by a slowly shifting activity balance between opposing neuronal populations, LNvs and DN1as. The two populations undergo structural changes in axon length that accord with, and are required for, conveying time-of-day information. Each day, in each population, the circadian clock directs cellular remodeling such that the maximum axonal length in one population coincides with the minimum in the other; preventing remodeling prevents transitioning between opposing internal states. We propose that a dynamic predictive model resides in the shifting connectivities of the LNv- DN1a circuit.

neuroscience↗

bioRxiv2020

Behavioral elements and neural circuits underlying exploratory decisions in normative anxiety

Exploration reduces uncertainty about the environment and improves the quality of future decisions, but at the cost of provisional uncertain and suboptimal outcomes. Although anxiety promotes intolerance to uncertainty, it remains unclear whether and by which mechanisms anxiety modulates exploratory decision-making. We use a dynamic three-armed-bandit task and find that higher trait-anxiety increases exploration, which in turn harms overall performance. We identify two distinct behavioral sources: first, decisions made by anxious individuals were guided towards reduction of uncertainty; and second, decisions were less guided by immediate value gains. Imaging (fMRI) revealed that anxiety correlated negatively with the representation of expected-value in the dorsal-anterior-cingulate-cortex, and in contrast, positively with the representation of uncertainty in the anterior-insula. Moreover, the findings were similar in both loss and gain domains, and demonstrated that affective trait modulates exploration and results in an inverse-U-shaped relationship between anxiety and overall performance. We conclude that a shift in balance towards representation of uncertainty in the insula prevails over reduced value representation in the dACC, and entails maladaptive decision-making in individuals with higher normal-range anxiety.

neuroscience↗

bioRxiv2020

Sticks and Stones, a conserved cell surface ligand for the Type IIa RPTP Lar, regulates neural circuit wiring in Drosophila

Control of tyrosine phosphorylation is an essential element of many cellular processes, including proliferation, differentiation neurite outgrowth, and synaptogenesis. Receptor-like protein-tyrosine phosphatases (RPTPs) have cytoplasmic phosphatase domains and cell adhesion molecule (CAM)-like extracellular domains that interact with cell-surface ligands and/or co-receptors. We identified a new ligand for the Drosophila Lar RPTP, the immunoglobulin superfamily CAM Sticks and Stones (Sns). Lar is orthologous to the three Type IIa mammalian RPTPs, PTPRF (LAR), PTPRD (PTP{delta}), and PTPRS (PTP{sigma}). Lar and Sns bind to each other in embryos and in vitro. The human Sns ortholog, Nephrin, binds to PTPRD and PTPRF. Genetic interaction studies show that Sns is essential to Lars functions in several developmental contexts in the larval and adult nervous systems. In the larval neuromuscular system, Lar and sns transheterozygotes (Lar/sns transhets) have synaptic defects like those seen in Lar mutants and Sns knockdown animals. Lar and Sns reporters are both expressed in motor neurons and not in muscles, so Lar and Sns likely act in cis (in the same neurons). Lar mutants and Lar/sns transhets have identical axon guidance defects in the larval mushroom body in which Kenyon cell axons fail to stop at the midline and do not branch. Pupal Kenyon cell axon guidance is similarly affected, resulting in adult mushroom body defects. Lar is expressed in larval and pupal Kenyon cells, but Sns is not, so Lar-Sns interactions in this system must be in trans (between neurons). Lastly, R7 photoreceptor axons in Lar mutants and Lar/sns transhets fail to innervate the correct M6 layer of the medulla in the optic lobe. Lar acts cell-autonomously in R7s, while Sns is only in lamina and medulla neurons that arborize near the R7 target layer. Therefore, the Lar-Sns interactions that control R7 targeting also occur in trans.

neuroscience↗

bioRxiv2021

A rapid and efficient learning rule for biological neural circuits

The dominant view in neuroscience is that changes in synaptic weights underlie learning. It is unclear, however, how the brain is able to determine which synapses should change, and by how much. This uncertainty stands in sharp contrast to deep learning, where changes in weights are explicitly engineered to optimize performance. However, the main tool for that, backpropagation, has two problems. One is neuro-science related: it is not biologically plausible. The other is inherent: networks trained with this rule tend to forget old tasks when learning new ones. Here we introduce the Dendritic Gated Network (DGN), a variant of the Gated Linear Network, which offers a biologically plausible alternative to backpropagation. DGNs combine dendritic gating (whereby interneurons target dendrites to shape neuronal responses) with local learning rules to yield provably efficient performance. They are significantly more data efficient than conventional artificial networks, and are highly resistant to forgetting. Consequently, they perform well on a variety of tasks, in some cases better than backpropagation. Importantly, DGNs have structural and functional similarities to the cerebellum, a link that we strengthen by using in vivo two-photon calcium imaging to show that single interneurons suppress activity in individual dendritic branches of Purkinje cells, a key feature of the model. Thus, DGNs leverage targeted dendritic inhibition and local learning - two features ubiquitous in the brain - to achieve fast and efficient learning.

neuroscience↗

bioRxiv2021

A neural circuit for wind-guided olfactory navigation

To navigate towards a food source, animals must frequently combine odor cues that tell them what sources are useful with wind direction cues that tell them where the source can be found. Where and how these two cues are integrated to support navigation is unclear. Here we identify a pathway to the Drosophila fan-shaped body (FB) that encodes attractive odor and promotes upwind navigation. We show that neurons throughout this pathway encode odor, but not wind direction. Using connectomics, we identify FB local neurons called h{Delta}C that receive input from this odor pathway and a previously described wind pathway. We show that h{Delta}C neurons exhibit odor-gated, wind direction-tuned activity, that sparse activation of h{Delta}C neurons promotes navigation in a reproducible direction, and that h{Delta}C activity is required for persistent upwind orientation during odor. Based on connectome data, we develop a computational model showing how h{Delta}C activity can promote navigation towards a goal such as an upwind odor source. Our results suggest that odor and wind cues are processed by separate pathways and integrated within the FB to support goal-directed navigation.

neuroscience↗

bioRxiv2021

Neural circuits for dynamics-based segmentation of time series

The brain must extract behaviorally relevant latent variables from the signals streamed by the sensory organs. Such latent variables are often encoded in the dynamics that generated the signal rather than in the specific realization of the waveform. Therefore, one problem faced by the brain is to segment time series based on underlying dynamics. We present two algorithms for performing this segmentation task that are biologically plausible, which we define as acting in a streaming setting and all learning rules being local. One algorithm is model-based and can be derived from an optimization problem involving a mixture of autoregressive processes. This algorithm relies on feedback in the form of a prediction error, and can also be used for forecasting future samples. In some brain regions, such as the retina, the feedback connections necessary to use the prediction error for learning are absent. For this case, we propose a second, model-free algorithm that uses a running estimate of the autocorrelation structure of the signal to perform the segmentation. We show that both algorithms do well when tasked with segmenting signals drawn from autoregressive models with piecewise-constant parameters. In particular, the segmentation accuracy is similar to that obtained from oracle-like methods in which the ground-truth parameters of the autoregressive models are known. We also test our methods on datasets generated by alternating snippets of voice recordings. We provide implementations of our algorithms at https://github.com/ttesileanu/bio-time-series.

neuroscience↗

bioRxiv2021

Cannabis Vapour Exposure Alters Neural Circuit Oscillatory Activity In A Neurodevelopmental Model Of Schizophrenia: Exploring The Differential Impact Of Cannabis Constituents

Cannabis use is highly prevalent in patients with schizophrenia and worsens the course of the disorder. To understand the causal impacts of cannabis on schizophrenia-related oscillatory disruptions, we herein investigated the impact of exposure to cannabis vapour (containing delta-9-tetrahydrocannabinol [THC] or balanced THC and cannabidiol [CBD]) on oscillatory activity in the neonatal ventral hippocampal lesion (NVHL) rat model of schizophrenia. Male Sprague Dawley rats underwent NVHL or sham surgeries on postnatal day 7. In adulthood, electrodes were implanted targeting the cingulate cortex (Cg), the prefrontal cortex (PFC), the dorsal hippocampus (HIP), and the nucleus accumbens (NAc). Local field potential recordings were obtained following exposure to two strains of vapourized cannabis flower (with ~10% THC or ~10% balanced THC:CBD) in a cross-over design with a two-week wash-out period between exposures. Compared to controls, NVHL rats had reduced baseline gamma power in the Cg, dHIP, and NAc, and reduced high-gamma coherence between the dHIP-Cg. THC-only vapour broadly suppressed oscillatory power and coherence, even beyond the baseline suppressions observed in NHVL rats. Balanced THC:CBD vapour appeared to ameliorate the THC-induced impacts on power and coherence in both sham and NVHL rats. For NVHL rats, THC-only vapour also normalized the baseline dHIP-Cg high-gamma coherence deficits. NHVL rats also demonstrated a 20ms delay in dHIP theta to high-gamma phase coupling, which was ameliorated by both exposures in the PFC and NAc. In conclusion, THC-only cannabis vapour suppressed oscillatory activity in NVHL and sham rats, while balanced THC:CBD vapour may ameliorate some of these effects.

neuroscience↗