Miracle-dz/UniFAR-FTUs huggingface dataset:
Total Number and Ratio of GABAergic Neuron Types in the Mouse Lateral and Basal Amygdala

GABAergic neurons are key circuit elements in cortical networks. Despite growing evidence showing that inhibitory cells play a critical role in the lateral (LA) and basal (BA) amygdala functions, neither the number of GABAergic neurons nor the ratio of their distinct types has been determined in these amygdalar nuclei. Using unbiased stereology, we found that the ratio of GABAergic neurons in the BA (22%) is significantly higher than in the LA (16%) in both male and female mice. No difference was observed between the right and left hemispheres in either sex. In addition, we assessed the ratio of the major inhibitory cell types in both amygdalar nuclei. Using transgenic mice and a viral strategy for visualizing inhibitory cells combined with immunocytochemistry, we estimated that the following cell types together compose the vast majority of GABAergic cells in the LA and BA: axo-axonic cells (5.5%-6%), basket cells expressing parvalbumin (17%-20%) or cholecystokinin (7%-9%), dendrite-targeting inhibitory cells expressing somatostatin (10%-16%), NPY-containing neurogliaform cells (14%-15%), VIP and/or calretinin-expressing interneuron-selective interneurons (29%-38%), and GABAergic projection neurons expressing somatostatin and neuronal nitric oxide synthase (5.5%-8%). Our results show that these amygdalar nuclei contain all major GABAergic neuron types as found in other cortical regions. Furthermore, our data offer an essential reference for future studies aiming to reveal changes in GABAergic cell number and in inhibitory cell types typically observed under different pathologic conditions, and to model functioning amygdalar networks in health and disease. SIGNIFICANCE STATEMENT GABAergic cells in cortical structures, as in the lateral and basal nucleus of the amygdala, have a determinant role in controlling circuit operation. In this study, we provide the first estimate for the total number of inhibitory cells in these two amygdalar nuclei. In addition, our study is the first to define the ratio of the major GABAergic cell types present in these cortical networks. Taking into account that hyperexcitability in the amygdala, arising from the imbalance between excitation and inhibition typifies many altered brain functions, including anxiety, post-traumatic stress disorder, schizophrenia, and autism, uncovering the number and ratio of distinct amygdalar inhibitory cell types offers a solid base for comparing the changes in inhibition in pathologic brain states.
Discrete ripples reflect a spectrum of synchronous spiking activity in human association cortex

Direct brain recordings have provided important insights into how persistent oscillatory activity support human memory retrieval, but the extent to which transient fluctuations in intracranial EEG (iEEG) captures the dynamic coordination of underlying neurons involved in memory processing remains unclear. Here, we simultaneously record iEEG, local field potential (LFP), and single unit activity in the human temporal cortex. We demonstrate that cortical ripples contribute to broadband high frequency activity and exhibit a spectrum of amplitudes and durations related to the amount of underlying neuronal spiking. Ripples in the macro-scale iEEG are related to the number and synchrony of ripples in the micro-scale LFP, which in turn are related to the synchrony of neuronal spiking. Our data suggest that neural activity in the human cortex is organized into dynamic, discrete packets of information.
A model of Ponto-Geniculo-Occipital waves supports bidirectional control of cortical plasticity across sleep-stages

During sleep, cortical network connectivity likely undergoes both synaptic potentiation and depression through system consolidation and homeostatic processes. However, how these modifications are coordinated across sleep stages remains largely unknown. Candidate mechanisms are Ponto-Geniculo-Occipital (PGO) waves, propagating across several structures during Rapid Eye Movement (REM) sleep and the transitional stage from non-REM sleep to REM sleep (pre-REM), and exhibiting sleep stage-specific dynamic patterns. To understand their impact on cortical plasticity, we built an acetylcholine-modulated neural mass model of PGO wave propagation through pons, thalamus and cortex, reproducing a broad range of electrophysiological characteristics across sleep stages. Using a population model of Spike-Time-Dependent Plasticity, we show that cortical circuits undergo different transient regimes depending on the sleep stage, with different impacts on plasticity. Specifically, PGO-induced recurrent cortical activities lead to the potentiation of cortico-cortical synapses during pre-REM, and to their depression during REM sleep. Overall, these results shed light on how the dynamical properties of sleep events propagating to cortical circuits can favor different types of local plastic changes. The variety of events occurring across sleep stages may thus be instrumental in controlling the reorganization of cortical networks from one day to the next. Significance statement Considerable evidence supports rescaling of cortical synaptic connec-tions during sleep, requiring both long term potentiation to consolidate newly acquired memories, and long-term depression to maintain homeostatic levels of brain activity. However, which aspects of sleep activity contribute to this bidirectional control of plasticity remains unclear. This computational modeling study suggests that widespread transient phenomena called Ponto-geniculo-occipital (PGO) waves, have a sleep-stage dependent effect on plasticity. The alternation between sleep stages can thus be exploited in combination with spontaneously occurring transients, to trigger both up- and down-regulating effects on cortical connectivity, and may explain why the basic structure of sleep-cycles is a well-preserved property across mammalian species.
Altered effective connectivity in sensorimotor cortices is a signature of severity and clinical course in depression

Significance Research into neurobiology of depression primarily focuses on its complex psychological aspects. Here we propose an alternative approach and target sensorimotor alterations—a prominent but often neglected feature of depression. We demonstrated using resting-state functional MRI data and computational modeling that top-down and bottom-up information flow in sensory and motor cortices is altered with increasing depression severity in a way that is consistent with depression symptoms. Depression-associated changes were found to be consistent across sessions, amenable to treatment and of effect size sufficiently large to predict whether somebody has mild or severe depression. These results pave the way for an avenue of research into the neural underpinnings of mental health conditions. Functional neuroimaging research on depression has traditionally targeted neural networks associated with the psychological aspects of depression. In this study, instead, we focus on alterations of sensorimotor function in depression. We used resting-state functional MRI data and dynamic causal modeling (DCM) to assess the hypothesis that depression is associated with aberrant effective connectivity within and between key regions in the sensorimotor hierarchy. Using hierarchical modeling of between-subject effects in DCM with parametric empirical Bayes we first established the architecture of effective connectivity in sensorimotor cortices. We found that in (interoceptive and exteroceptive) sensory cortices across participants, the backward connections are predominantly inhibitory, whereas the forward connections are mainly excitatory in nature. In motor cortices these parities were reversed. With increasing depression severity, these patterns are depreciated in exteroceptive and motor cortices and augmented in the interoceptive cortex, an observation that speaks to depressive symptomatology. We established the robustness of these results in a leave-one-out cross-validation analysis and by reproducing the main results in a follow-up dataset. Interestingly, with (nonpharmacological) treatment, depression-associated changes in backward and forward effective connectivity partially reverted to group mean levels. Overall, altered effective connectivity in sensorimotor cortices emerges as a promising and quantifiable candidate marker of depression severity and treatment response.
Morphological principles of neuronal mitochondria

In the highly dynamic metabolic landscape of a neuron, mitochondrial membrane architectures can provide critical insight into the unique energy balance of the cell. Current theoretical calculations of functional outputs like ATP and heat often represent mitochondria as idealized geometries and therefore can miscalculate the metabolic fluxes. To analyze mitochondrial morphology in neurons of mouse cerebellum neuropil, 3D tracings of complete synaptic and axonal mitochondria were constructed using a database of serial TEM tomography images and converted to watertight meshes with minimal distortion of the original microscopy volumes with a granularity of 1.6 nanometer isotropic voxels. The resulting in silico representations were subsequently quantified by differential geometry methods in terms of the mean and Gaussian curvatures, surface areas, volumes, and membrane motifs, all of which can alter the metabolic output of the organelle. Finally, we identify structural motifs that are present across this population of mitochondria; observations which may contribute to future modeling studies of mitochondrial physiology and metabolism in neurons.
Selective corticofugal modulation on sound processing in auditory thalamus of awake marmosets

Cortical feedback has long been considered crucial for modulation of sensory processing. In the mammalian auditory system, studies have suggested that corticofugal feedback can have excitatory, inhibitory, or both effects on the response of subcortical neurons, leading to controversies regarding the role of corticothalamic influence. This has been further complicated by studies conducted under different brain states. In the current study, we used cryo-inactivation in the primary auditory cortex (A1) to examine the role of corticothalamic feedback on medial geniculate body (MGB) neurons in awake marmosets. The primary effects of A1 inactivation were a frequency-specific decrease in the auditory response of MGB neurons coupled with an increased spontaneous firing rate, which together resulted in a decrease in the signal-to-noise ratio. In addition, we report for the first-time that A1 robustly modulated the long-lasting sustained response of MGB neurons which changed the frequency tuning after A1 inactivation, e.g., neurons with sharp tuning increased tuning bandwidth whereas those with broad tuning decreased tuning bandwidth. Taken together, our results demonstrate that corticothalamic modulation in awake marmosets serves to enhance sensory processing in a way similar to center-surround models proposed in visual and somatosensory systems, a finding which supports common principles of corticothalamic processing across sensory systems.
Bump attractor dynamics underlying stimulus integration in perceptual estimation tasks

Perceptual decision and continuous stimulus estimation tasks involve making judgments based on accumulated sensory evidence. Network models of evidence integration usually rely on competition between neural populations each encoding a discrete categorical choice and do not maintain information that is necessary for a continuous perceptual judgement. Here, we show that a continuous attractor network can integrate a circular stimulus feature and track the stimulus average in the phase of its activity bump. We show analytically that the network can compute the running average of the stimulus almost optimally, and that the nonlinear internal dynamics affect the temporal weighting of sensory evidence. Whether the network shows early (primacy), uniform or late (recency) weighting depends on the relative strength of the stimuli compared to the bump’s amplitude and initial state. The global excitatory drive, a single model parameter, modulates the specific relation between internal dynamics and sensory inputs. We show that this can account for the heterogeneity of temporal weighting profiles and reaction times observed in humans integrating a stream of oriented stimulus frames. Our findings point to continuous attractor dynamics as a plausible mechanism underlying stimulus integration in perceptual estimation tasks.
Open Data Commons for Preclinical Traumatic Brain Injury Research: Empowering Data Sharing and Big Data Analytics

Traumatic brain injury (TBI) is a major unsolved public health problem worldwide with considerable preclinical research dedicated to recapitulating clinical TBI, deciphering the underlying pathophysiology, and developing therapeutics. However, the heterogeneity of clinical TBI and correspondingly in preclinical studies have made translation from bench to bedside difficult. Here, we present the potential of data sharing, data aggregation, and multivariate analytics to integrate heterogeneity and empower researchers. We introduce the Open Data Commons for Traumatic Brain Injury (ODC-TBI.org) as a user-centered web platform and cloudbased repository focused on preclinical TBI research that enables data citation with persistent identifiers, promotes data element harmonization, and follows FAIR data sharing principles. Importantly, the ODC-TBI implements data sharing at the level of individual subjects, thus enabling data reuse for granular big data analytics and data-hungry machine learning approaches. We provide use cases applying descriptive analytics and unsupervised machine learning on pooled ODC-TBI data. Descriptive statistics included subject-level data for 11 published papers (N = 1250 subjects) representing six distinct TBI models across mice and rats (implementing controlled cortical impact, closed head injury, fluid percussion injury, and CHIMERA TBI modalities). We performed principal component analysis (PCA) on cohorts of animals combined through the ODC-TBI to identify persistent inflammatory patterns across different experimental designs. Our workflow ultimately improved the sensitivity of our analyses in uncovering patterns of pro- vs anti-inflammation and oxidative stress without the multiple testing problems of univariate analyses. As the practice of open data becomes increasingly required by the scientific community, ODC-TBI provides a foundation that creates new scientific opportunities for researchers and their work, facilitates multi-dataset and multidimensional analytics, and drives collaboration across molecular and computational biologists to bridge preclinical research to the clinic.
Dynamic accumulation of a helper NLR at the plant-pathogen interface underpins pathogen recognition

Plants employ sensor-helper pairs of NLR immune receptors to recognize pathogen effectors and activate immune responses. Yet the subcellular localization of NLRs pre- and post-activation during pathogen infection remains poorly known. Here we show that NRC4, from the ‘NRC’ solanaceous helper NLR family, undergoes dynamic changes in subcellular localization by shuttling to and from the plant-pathogen haustorium interface established during infection by the Irish potato famine pathogen Phytophthora infestans. Specifically, prior to activation, NRC4 accumulates at the extra-haustorial membrane (EHM), presumably to mediate response to perihaustorial effectors, that are recognized by NRC4-dependent sensor NLRs. However not all NLRs accumulate at the EHM, as the closely related helper NRC2, and the distantly related ZAR1, did not accumulate at the EHM. NRC4 required an intact N-terminal coiled coil domain to accumulate at the EHM, whereas the functionally conserved MADA motif implicated in cell death activation and membrane insertion was dispensable for this process. Strikingly, a constitutively autoactive NRC4 mutant did not accumulate at the EHM and showed punctate distribution that mainly associated with the plasma membrane, suggesting that post-activation, NRC4 probably undergoes a conformation switch to form clusters that do not preferentially associate with the EHM. When NRC4 is activated by a sensor NLR during infection however, NRC4 formed puncta mainly at the EHM and to a lesser extent at the plasma membrane. We conclude that following activation at the EHM, NRC4 may spread to other cellular membranes from its primary site of activation to trigger immune responses. Significance statement Plant NLR immune receptors function as intracellular sensors of pathogen virulence factors known as effectors. In resting state, NLRs localize to subcellular sites where the effectors they sense operate. However, the extent to which NLRs alter their subcellular distribution during infection remains elusive. We describe dynamic changes in spatiotemporal localization of an NLR protein in infected plant cells. Specifically, the NLR protein accumulates at the newly synthesized plant-pathogen interface membrane, where the corresponding effectors are deployed. Following immune recognition, the activated receptor re-organizes to form punctate structures that target the cell periphery. We propose that NLRs are not necessarily stationary immune receptors, but instead may spread to other cellular membranes from the primary site of activation to boost immune responses.
Evaluation of the OsTIR1 and AtAFB2 AID systems for chromatin protein degradation in mammalian cells

Auxin-inducible degron (AID) system is a promising tool for dynamic protein degradation. In mammalian cells, this approach has become indispensable to study fundamental molecular functions, such as replication, chromatin dynamics or transcription, that are otherwise difficult to dissect. We present evaluation of the two prominent AID systems based on OsTIR1 and AtAFB2 auxin receptor F-box proteins (AFBs). We analyzed degradation dynamics of cohesin/condensin complexes subunits in mouse embryonic stem cells (mRad21, mSMC2, mCapH, mCapH2) and human haploid HAP1 line (hRad21, hSMC2). Double antibiotic selection helped to achieve high homozygous AID targeting efficiency for all genes, ranging from 11 to 77%. We found that the main challenge for successful protein degradation is obtaining cell clones with high and stable AFB expression levels due to mosaic expression of AFBs, which also tends to decline with passages in the absence of constant puromycin selection, even at the AAVS1 safe-harbor locus. Comparing two AFBs, we found that OsTIR1 system showed weak dynamics of protein degradation. At the same time, AtAFB2 approach was very efficient even in random integration. Other factors such as degradation dynamics and low basal depletion were also in favor of AtAFB2 system. Our main conclusion is that repeated addition of puromycin to culture medium prevents AtAFB2 silencing and restores auxin sensitivity, facilitating robust protein degradation. We hope that our report will be useful for researchers that plan to establish AID method in their lab.
Sequencing

The rapid global spread and continued evolution of SARS-CoV-2 has highlighted an unprecedented need for viral genomic surveillance and clinical viral sequencing. Amplicon-based sequencing methods provide a sensitive, low-cost and rapid approach but suffer a high potential for contamination, which can undermine lab processes and results. This challenge will only increase with expanding global production of sequences by diverse research groups for epidemiological and clinical interpretation. We present an approach which uses synthetic DNA spike-ins (SDSIs) to track samples and detect inter-sample contamination through a sequencing workflow. Applying this approach to the ARTIC Consortium’s amplicon design, we define a series of best practices for Illumina-based sequencing and provide a detailed characterization of approaches to increase sensitivity for low-viral load samples incorporating the SDSIs. We demonstrate the utility and efficiency of the SDSI method amidst a real-time investigation of a suspected hospital cluster of SARS-CoV-2 cases.
Metagenomic analysis reveals the signature of gut microbiota associated with human chronotypes

Patterns of diurnal activity differ substantially between individuals, with early risers and late sleepers being examples of opposite chronotypes. Growing evidence suggests that the late chronotype significantly impacts the risk of developing mood disorders, obesity, diabetes, and other chronic diseases. Despite the vast potential of utilizing chronotype information for precision medicine, those factors that shape chronotypes remain poorly understood. Here, we assessed whether the various chronotypes are associated with different gut microbiome compositions. Using metagenomic sequencing analysis, we established a distinct signature associated with chronotype based on two bacterial genera, Alistipes (elevated in “larks”) and Lachnospira (elevated in “owls”). We identified three metabolic pathways associated with the early chronotype, and linked distinct dietary patterns with different chronotypes. Our work demonstrates an association between the gut microbiome and chronotype and may represent the first step towards developing dietary interventions aimed at ameliorating the deleterious health correlates of the late chronotype.
fmr1 mutation interacts with sensory experience to alter the early development of behavior and sensory coding in zebrafish

While Autism Spectrum Disorders (ASDs) are developmental in origin little is known about how they affect the early development of behavior and sensory coding, or how this is modulated by the sensory environment. The most common inherited form of autism is Fragile X syndrome, caused by a mutation in fmr1. Here we show that zebrafish fmr1-/- mutant larvae raised in a naturalistic visual environment display early deficits in hunting behavior, tectal map development, tectal network properties and decoding of spatial stimuli. However when given a choice they preferred an environment with reduced visual stimulation, and rearing them in this environment improved these metrics. Older fmr1-/- fish showed differences in social behavior, spending more time observing a conspecific, but responding more slowly to social cues. Together these results help reveal how fmr1-/- changes the early development of vertebrate brain function, and how manipulating the environment could potentially help reduce these changes.