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Robustness of STDP to spike timing jitter

In Hebbian plasticity, neural circuits adjust their synaptic weights depending on patterned firing of action potential on either side of the synapse. Spike-timing-dependent plasticity (STDP) is an experimental implementation of Hebbs postulate that relies on the precise order and the millisecond timing of the paired activities in pre- and postsynaptic neurons. In recent years, STDP has attracted considerable attention in computational and experimental neurosciences. However, canonical STDP is assessed with deterministic (constant) spike timings and time intervals between successive pairings, thus exhibiting a regularity that strongly differs from the biological variability. Hence, the emergence of STDP from noisy neural activity patterns as expected in in vivo-like firing remains unresolved. Here, we used noisy STDP stimulations where the spike timing and/or the interval between successive pairings were jittered. We explored with a combination of experimental neurophysiology and mathematical modeling, the impact of jittering on three distinct forms of STDP at corticostriatal synapses: NMDAR-mediated tLTP, endocannabinoid-mediated tLTD and endocannabinoid-mediated tLTP. As the main result, we found a differential sensitivity to jittered spike timing: NMDAR-tLTP was highly fragile whereas endocannabinoid-plasticity (tLTD and tLTP) appeared more resistant. Moreover, when the frequency or the number of pairings was increased, NMDAR-tLTP became more robust and could be expressed despite strong jittering of the spike timing. Taken together, our results identify endocannabinoid-mediated plasticity as a robust form of STDP while the sensitivity to jitter of NMDAR-tLTP varies with activity frequency. This provides new insights into the mechanisms at play during the different phases of learning and memory and the emergence of Hebbian plasticity in in vivo-like firing.

neuroscience

Development of photoactivatable drugs enables nicotinic optopharmacology

Photoactivatable ( caged) pharmacological agents have revolutionized neuroscience but the palette of available ligands is limited. We describe a general method for caging tertiary amines using an unconventional quaternary ammonium linkage that is chemically stable and elicits a desirable red-shift in activation wavelength. A photoactivatable nicotine (PA-Nic) prepared using this strategy could be uncaged via 1- or 2-photon excitation, making it useful for optopharmacology experiments to study nicotinic acetylcholine receptors (nAChRs) in different experimental preparations and spatiotemporal scales.

neuroscience

Inferring mechanistic models of neuronal microcircuits from single-trial spike trains

The interpretation of neuronal spike train recordings often relies on abstract statistical models that allow for principled parameter estimation and model selection but provide only limited insights into underlying microcircuits. In contrast, mechanistic models are useful to interpret microcircuit dynamics, but are rarely quantitatively matched to experimental data due to methodological challenges. Here we present analytical methods to efficiently fit spiking circuit models to single-trial spike trains. Using derived likelihood functions, we statistically infer the mean and variance of hidden inputs, neuronal adaptation properties and connectivity for coupled integrate-and-fire neurons. Comprehensive evaluations on synthetic data, validations using ground truth in-vitro and in-vivo recordings, and comparisons with existing techniques demonstrate that parameter estimation is very accurate and efficient, even for highly subsampled networks. Our methods bridge statistical, data-driven and theoretical, model-based neurosciences at the level of spiking circuits, for the purpose of a quantitative, mechanistic interpretation of recorded neuronal population activity.

neuroscience

The relationship between brain atrophy and cognitive-behavioral symptoms in retired Canadian football players with multiple concussions

Multiple concussions, particularly in contact sports, have been associated with cognitive deficits, psychiatric impairment and neurodegenerative diseases like chronic traumatic encephalopathy. We used volumetric and deformation-based morphometric analyses to test the hypothesis that repeated concussions may be associated with smaller regional brain volumes, poorer cognitive performance and behavioural symptoms among former professional football players compared to healthy controls. This study included fifty-three retired Canadian Football League players, 25 age- and education-matched healthy controls, and controls from the Cambridge Centre for Aging and Neuroscience database for validation. Volumetric analyses revealed greater hippocampal atrophy than expected for age in former athletes with multiple concussions than controls and smaller left hippocampal volume was associated with poorer verbal memory performance. Deformation-based morphometric confirmed smaller bilateral hippocampal volume that were associated with poorer verbal memory performance in athletes. Repeated concussions may lead to greater regional atrophy than expected for age.

neuroscience

An animal-actuated rotational head-fixation system for 2-photon imaging during 2-d navigation

Understanding how the biology of the brain gives rise to the computations that drive behavior requires high fidelity, large scale, and subcellular measurements of neural activity. 2-photon microscopy is the primary tool that satisfies these requirements, particularly for measurements during behavior. However, this technique requires rigid head-fixation, constraining the behavioral repertoire of experimental subjects. Increasingly, complex task paradigms are being used to investigate the neural substrates of complex behaviors, including navigation of complex environments, resolving uncertainty between multiple outcomes, integrating unreliable information over time, and/or building internal models of the world. In rodents, planning and decision making processes are often expressed via head and body motion. This produces a significant limitation for head-fixed two-photon imaging. We therefore developed a system that overcomes a major problem of head-fixation: the lack of rotational vestibular input. The system measures rotational strain exerted by mice on the head restraint, which consequently drives a motor, rotating the constraint system and dissipating the strain. This permits mice to rotate their heads in the azimuthal plane with negligible inertia and friction. This stable rotating head-fixation system allows mice to explore physical or virtual 2-D environments. To demonstrate the performance of our system, we conducted 2-photon GCaMP6f imaging in somas and dendrites of pyramidal neurons in mouse retrosplenial cortex. We show that the subcellular resolution of the systems 2-photon imaging is comparable to that of conventional head-fixed experiments. Additionally, this system allows the attachment of heavy instrumentation to the animal, making it possible to extend the approach to large-scale electrophysiology experiments in the future. Our method enables the use of state-of-the-art imaging techniques while animals perform more complex and naturalistic behaviors than currently possible, with broad potential applications in systems neuroscience.

neuroscience

Lifestyle activities in mid-life contribute to cognitive reserve in late-life, independent of education, occupation and late-life activities

IntroductionThis study tested the hypothesis that mid-life intellectual, physical and social activities contribute to cognitive reserve (CR).\n\nMethods205 individuals (196 with MRI) aged 66-88 from the Cambridge Centre for Ageing and Neuroscience (www.cam-can.com) were studied, with cognitive ability and structural brain health measured as fluid IQ and total grey matter volume, respectively. Mid-life activities were measured using the Lifetime of Experiences Questionnaire.\n\nResultsMultivariable linear regression found that mid-life activities (MA) made a unique contribution to late-life cognitive ability independent of education, occupation and late-life activities. Crucially, MA moderated the relationship between late-life cognitive ability and brain structure, with the cognitive ability of people with higher MA less dependent on their brain structure, consistent with the concept of CR.\n\nConclusions. Mid-life intellectual, physical and social activities contribute uniquely to CR. The modifiability of these activities has implications for public health initiatives aimed at dementia prevention.

neuroscience

Active Learning of Cortical Connectivity from Two-Photon Imaging Data

Understanding how groups of neurons interact within a network is a fundamental question in system neuroscience. Instead of passively observing the ongoing activity of a network, we can typically perturb its activity, either by external sensory stimulation or directly via techniques such as two-photon optogenetics. A natural question is how to use such perturbations to identify the connectivity of the network efficiently. Here we introduce a method to infer sparse connectivity graphs from in-vivo, two-photon imaging of population activity in response to external stimuli. A novel aspect of the work is the introduction of a recommended distribution, incrementally learned from the data, to optimally refine the inferred network.. Unlike existing system identification techniques, this \"active learning\" method automatically focuses its attention on key undiscovered areas of the network, instead of targeting global uncertainty indicators like parameter variance. We show how active learning leads to faster inference while, at the same time, provides confidence intervals for the network parameters. We present simulations on artificial small-world networks to validate the methods and apply the method to real data. Analysis of frequency of motifs recovered show that cortical networks are consistent with a small-world topology model.

neuroscience

Long-term depression is independent of GluN2 subunit composition.

NMDA receptors (NMDARs) mediate major forms of both long-term potentiation (LTP) and long-term depression (LTD) and understanding how a single receptor can initiate both phenomena remains a major question in neuroscience. A prominent hypothesis implicates the NMDAR subunit composition, specifically GluN2A and GluN2B, in dictating the rules of synaptic plasticity. However, studies testing this hypotheses have yielded inconsistent and often contradictory results, especially for LTD. These inconsistent results may be due to challenges in the interpretation of subunit-selective pharmacology and in dissecting out the contributions of differential channel properties versus the interacting proteins unique to GluN2A or GluN2B. In this study, we address the pharmacological and biochemical challenges by utilizing a single-neuron genetic approach to delete NMDAR subunits in both male and female conditional knock-out mice. In addition, emerging evidence that non-ionotropic signaling through the NMDAR is sufficient for NMDAR-dependent LTD allowed the rigorous assessment of unique subunit contributions to NMDAR-dependent LTD while eliminating the variable of differential charge transfer. Here we find that neither the GluN2A nor the GluN2B subunit is strictly necessary for either non-ionotropic or ionotropic LTD.

neuroscience

High-accuracy Decoding of Complex Visual Scenes from Neuronal Calcium Responses

The brain contains billions of neurons defined by diverse cytoarchitectural, anatomical, genetic, and functional properties. Sensory encoding and decoding are popular research areas in the fields of neuroscience, neuroprosthetics and artificial intelligence but the contribution of neuronal diversity to these processes is not well understood. Deciphering this contribution necessitates development of sophisticated neurotechnologies that can monitor brain physiology and behavior via simultaneous assessment of individual genetically-defined neurons during the presentation of discrete sensory cues and behavioral contexts. Neural networks are a powerful technique for formulating hierarchical representations of data using layers of nonlinear transformations. Here we leverage the availability of an unprecedented collection of neuronal activity data, derived from [~]25,000 individual genetically-defined neurons of the parcellated mouse visual cortex during the presentation of 118 unique and complex naturalistic scenes, to demonstrate that neural networks can be used to decode discrete visual scenes from neuronal calcium responses with high ([~]96%) accuracy. Our findings highlight the novel use of neural networks for sensory decoding using neuronal calcium imaging data and reveal a neuroanatomical map of visual decoding strength traversing brain regions, cortical layers, neuron types, and time. Our findings also demonstrate the utility of feature selection in assigning contributions of neuronal diversity to visual decoding accuracy and the low requirement of network architecture complexity for high accuracy decoding in this experimental context.

neuroscience

The hippocampal film-editor: sensitivity and specificity to event boundaries in continuous experience

The function of the human hippocampus is normally investigated by experimental manipulation of discrete events. Less is unknown about what triggers hippocampal activity during more naturalistic, continuous experience. We hypothesized that the hippocampus would be sensitive to the occurrence of event boundaries, i.e. moments in time identified by observers as a transition between events. To address this, we analysed functional MRI data from two groups: one (N=253, 131 female) who viewed an 8.5min film and another (N=15, 6 female) who viewed a 120min film. We observed a strong hippocampal response at boundaries defined by independent observers, which was modulated by boundary strength (the number of observers that identified each boundary). In the longer film, there were sufficient boundaries to show that this modulation remained after covarying out a large number of perceptual factors. The hippocampus was the only brain region whose response showed a significant monotonic increase with boundary strength in both films, suggesting that modulation by boundary strength is selective to the hippocampus. This hypothesis-driven approach was complemented by a data-driven approach, in which we identified hippocampal-events as moments in time with the strongest hippocampal activity: The correspondence between these hippocampalevents and event boundaries was highly-significant, revealing that the hippocampal response is not only sensitive, but also specific to event boundaries. We conclude that the hippocampus plays an important role in segmenting the continuous experience that is typical of naturalistic settings.\n\nSignificance statementRecent years have seen the field of human neuroscience research transitioning from experiments with simple stimuli to the study of more complex and naturalistic experience. Nonetheless, our understanding of the function of many brain regions, such as the hippocampus, is based primarily on the study of brief, discrete events. As a result, we know little of what triggers hippocampal activity in real-life settings, when we are exposed to a continuous stream of information. When does the hippocampus \"decide\" to respond during the encoding of naturalistic experience? We reveal here that hippocampal activity measured by fMRI during film-watching is both sensitive and specific to event boundaries, identifying a potential mechanism whereby event boundaries shape experience by modulation of hippocampal activity.

neuroscience

Dynamic integration of multisensory turn commands supports active reorienting during ongoing navigation.

A longstanding goal of systems neuroscience is to quantitatively describe how the brain integrates cues from multiple modalities over time. Here we develop a closed-loop orienting paradigm in Drosophila to study the algorithms by which stimuli from different modalities are combined during ongoing navigation. We show that flies faced with an attractive visual and an aversive mechanosensory cue exhibit sequential responses, first turning away from the co-localized stimuli before turning back toward them. We also find that the presence of the aversive cue slows flies turns toward the attractive target, suggesting that conflicting unimodal turn commands are summed to produce multisensory turns of intermediate velocity. We then test a series of computational frameworks and find that integration is best described by a model in which multimodal stimuli are continuously and dynamically scaled, converted into turn commands, and then summed to produce ongoing orientation behavior.

neuroscience

Cortical recruitment determines learning dynamics and strategy

Salience is a broad and widely used concept in neuroscience whose neuronal correlates, however, remain elusive. In behavioral conditioning, salience is used to explain various effects, such as stimulus overshadowing, and refers to how fast and strongly a stimulus can be associated with a conditioned event. Here, we show that sounds of diverse quality, but equal intensity and perceptual detectability, can recruit different levels of population activity in mouse auditory cortex. When using these sounds as cues in a Go/NoGo discrimination task, the degree of cortical recruitment matches the salience parameter of a reinforcement learning model used to analyze learning speed. We test an essential prediction of this model by training mice to discriminate light-sculpted optogenetic activity patterns in auditory cortex, and verify that cortical recruitment causally determines association or overshadowing of the stimulus components. This demonstrates that cortical recruitment underlies major aspects of stimulus salience during reinforcement learning.

neuroscience

Age differences in head motion and estimates of cortical morphology

Cortical morphology is known to differ with age, as measured by cortical thickness, fractal dimensionality, and gyrification. However, head motion during MRI scanning has been shown to influence estimates of cortical thickness as well as increase with age. Studies have also found task-related differences in head motion and relationships between body-mass index (BMI) and head motion. Here I replicated these prior findings, as well as several others, within a large, open-access dataset (Centre for Ageing and Neuroscience, CamCAN). This is a larger dataset than these results have been demonstrated previously, within a sample size of more than 600 adults across the adult lifespan. While replicating prior findings is important, demonstrating these key findings concurrently also provides an opportunity for additional related analyses: Critically, I test for the influence of head motion on cortical fractal dimensionality and gyrification; effects were statistically significant in some cases, but small in magnitude.

neuroscience

Fusing Mobile Phone Sensing and Brain Imaging to Assess Depression in College Students: A Proof-of-Concept study

As smartphone usage has become increasingly prevalent in our society, so have rates of depression, particularly among young adults. Individual differences in smartphone usage patterns have been shown to reflect individual differences in underlying affective processes such as depression (Wang et al., 2018). In the current study, we identified a positive relationship between smartphone screen time (e.g. phone unlock duration) and resting-state functional connectivity (RSFC) between the subgenual cingulate cortex (sgCC), a brain region implicated in depression and antidepressant treatment response, and regions of the ventromedial/orbitofrontal cortex, such that increased phone usage was related to stronger connectivity between these regions. We then used this cluster to constrain subsequent analyses looking at depressive symptoms in the same cohort and observed partial replication in a separate cohort. We believe the data and analyses presented here provide relatively simplistic initial analyses which replicate and provide a first step in combining functional brain activity and smartphone usage patterns to better understand issues related to mental health. Smartphones are a prevalent part of modern life and the usage of mobile sensing data from smartphones promises to be an important tool for mental health diagnostics and neuroscience research.

neuroscience

Flexible Learning-Free Segmentation and Reconstruction for Sparse Neuronal Circuit Tracing

Imaging is a dominant strategy for data collection in neuroscience, yielding stacks of images that often scale to gigabytes of data for a single experiment. Machine learning algorithms from computer vision can serve as a pair of virtual eyes that tirelessly processes these images, automatically constructing more complete and realistic circuits. In practice, such algorithms are often too error-prone and computationally expensive to be immediately useful. We address these shortcomings with a new fast, flexible, learning-free method for sparse segmentation and reconstruction of neural volumes. Unlike learning methods, our Flexible Learning-free Reconstruction of Imaged Neural volumes (FLoRIN) pipeline exploits structure-specific contextual clues and requires no training. This approach generalizes across different modalities, including serially-sectioned scanning electron microscopy (sSEM) of genetically labeled and contrast enhanced processes, spectral confocal reflectance (SCoRe) microscopy, and high-energy synchrotron X-ray microtomography (CT) of large tissue volumes. We deploy the FLoRIN pipeline on newly published and novel mouse datasets, demonstrating the high biological fidelity of the pipelines reconstructions, which are of sufficient quality for preliminary biological study. Compared to existing supervised learning methods, it is both significantly faster (up to several orders of magnitude) and produces high-quality reconstructions that are robust to noise and artifacts.

neuroscience

Early-life social environment alters juvenile behavior and neuroendocrine function in a highly social cichlid fish

Early-life experiences can shape adult behavior, with consequences for fitness and health, yet fundamental questions remain unanswered about how early-life social experiences are translated into variation in brain and behavior. The African cichlid fish Astatotilapia burtoni, a model system in social neuroscience, is well known for its highly plastic social phenotypes in adulthood. Here, we rear juveniles in either social groups or pairs to investigate the effects of early-life social environments on behavior and neuroendocrine gene expression. We find that both juvenile behavior and neuroendocrine function are sensitive to early-life effects. Behavior robustly co-varies across multiple contexts (open field, social cue investigation, and dominance behavior assays) to form a behavioral syndrome, with pair-reared juveniles towards the end of syndrome that is less active and socially interactive. Pair-reared juveniles also submit more readily as subordinates. In a separate cohort, we measured whole brain expression of stress and sex hormone genes. Expression of glucocorticoid receptor (GR) 1a was elevated in group-reared juveniles, supporting a highly-conserved role for the stress axis mediating early-life effects. The effect of rearing environment on androgen receptor (AR) and estrogen receptor (ER) expression was mediated by treatment duration (1 vs. 5 weeks). Finally, expression of corticotropin-releasing factor (CRF) and GR2 decreased significantly over time. Rearing environment also caused striking differences in gene co-expression, such that expression was tightly integrated in pair-reared juveniles, but not group-reared or isolates. Together, this research demonstrates the important developmental origins of behavioral phenotypes and identifies potential behavioral and neuroendocrine mechanisms.

neuroscience

All-optical electrophysiology reveals brain-state dependent changes in hippocampal subthreshold dynamics and excitability

A technology to record membrane potential from multiple neurons, simultaneously, in behaving animals will have a transformative impact on neuroscience research1. Parallel recordings could reveal the subthreshold potentials and intercellular correlations that underlie network behavior2. Paired stimulation and recording can further reveal the input-output properties of individual cells or networks in the context of different brain states3. Genetically encoded voltage indicators are a promising tool for these purposes, but were so far limited to single-cell recordings with marginal signal to noise ratio (SNR) in vivo4-6. We developed improved near infrared voltage indicators, high speed microscopes and targeted gene expression schemes which enabled recordings of supra- and subthreshold voltage dynamics from multiple neurons simultaneously in mouse hippocampus, in vivo. The reporters revealed sub-cellular details of back-propagating action potentials, correlations in sub-threshold voltage between multiple cells, and changes in dynamics associated with transitions from resting to locomotion. In combination with optogenetic stimulation, the reporters revealed brain state-dependent changes in neuronal excitability, reflecting the interplay of excitatory and inhibitory synaptic inputs. These tools open the possibility for detailed explorations of network dynamics in the context of behavior.

neuroscience

Distinct Functional Connectivity Mode during Viewing Natural Scenes Revealed by Principal Component Analysis

A fundamental question in systems neuroscience is how spontaneous activity at rest is reorganized during task performance. Recent studies suggest a strong relationship between resting and task FC. Furthermore, the relationship between resting and task FC has been shown to reflect individual differences. Particularly, various studies have demonstrated that the FC has higher reliability and provides enhanced detection of individual differences while viewing natural scenes. Although the large-scale organization of FC during rest and movie-viewing conditions have been well studied in relation to individual variations, the re-organization of FC during viewing natural scenes have not been studied in depth. In this study, we used principal component analysis on FC during rest and movie-viewing condition to characterize the dimensionality of FC patterns across conditions and subjects. We found that the variations in FC patterns related to viewing natural scenes can be explained by a single component, which enables identification of the task over subjects with 100% accuracy. We showed that the FC mode associated to viewing natural scenes better reflects individual variations. Furthermore, we investigated the signatures of movie-viewing-specific functional modes in dynamic FC based on phase-locking values between brain regions. We found that the movie-specific functional mode is persistent across time; suggesting the emergence of a stable processing mode. To explain the reorganization of whole-brain FC through the changes in local dynamics, we appeal to a large-scale computational model. This modelling suggested that the reorganization of whole-brain FC is associated to the interaction between frontal-parietal and frontal-temporal activation patterns.

neuroscience