Visual Deprivation during Mouse Critical Period Reorganizes Network-Level Functional Connectivity

A classic example of experience-dependent plasticity is ocular dominance (OD) shift, in which the responsiveness of neurons in the visual cortex is profoundly altered following monocular deprivation (MD). It has been postulated that OD shifts also modify global neural networks, but such effects have never been demonstrated. Here, we use wide-field fluorescence optical imaging (WFOI) to characterize calcium-based resting-state functional connectivity during acute (3 d) MD in female and male mice with genetically encoded calcium indicators (Thy1-GCaMP6f). We first establish the fundamental performance of WFOI by computing signal to noise properties throughout our data processing pipeline. Following MD, we found that Δ band (0.4-4 Hz) GCaMP6 activity in the deprived visual cortex decreased, suggesting that excitatory activity in this region was reduced by MD. In addition, interhemispheric visual homotopic functional connectivity decreased following MD, which was accompanied by a reduction in parietal and motor homotopic connectivity. Finally, we observed enhanced internetwork connectivity between the visual and parietal cortex that peaked 2 d after MD. Together, these findings support the hypothesis that early MD induces dynamic reorganization of disparate functional networks including the association cortices.

Sleep restores an optimal computational regime in cortical networks

Sleep is assumed to subserve homeostatic processes in the brain; however, the set point around which sleep tunes circuit computations is unknown. Slow-wave activity (SWA) is commonly used to reflect the homeostatic aspect of sleep; although it can indicate sleep pressure, it does not explain why animals need sleep. This study aimed to assess whether criticality may be the computational set point of sleep. By recording cortical neuron activity continuously for 10-14 d in freely behaving rats, we show that normal waking experience progressively disrupts criticality and that sleep functions to restore critical dynamics. Criticality is perturbed in a context-dependent manner, and waking experience is causal in driving these effects. The degree of deviation from criticality predicts future sleep/wake behavior more accurately than SWA, behavioral history or other neural measures. Our results demonstrate that perturbation and recovery of criticality is a network homeostatic mechanism consistent with the core, restorative function of sleep.

Protosequences in human cortical organoids model intrinsic states in the developing cortex

Neuronal firing sequences are thought to be the basic building blocks of neural coding and information broadcasting within the brain. However, when sequences emerge during neurodevelopment remains unknown. We demonstrate that structured firing sequences are present in spontaneous activity of human brain organoids and ex vivo neonatal brain slices from the murine somatosensory cortex. We observed a balance between temporally rigid and flexible firing patterns that are emergent phenomena in human brain organoids and early postnatal murine somatosensory cortex, but not in primary dissociated cortical cultures. Our findings suggest that temporal sequences do not arise in an experience-dependent manner, but are rather constrained by an innate preconfigured architecture established during neurogenesis. These findings highlight the potential for brain organoids to further explore how exogenous inputs can be used to refine neuronal circuits and enable new studies into the genetic mechanisms that govern assembly of functional circuitry during early human brain development.

Visual deprivation during mouse critical period reorganizes network-level functional connectivity

A classic example of experience-dependent plasticity is ocular dominance (OD) shift, in which the responsiveness of neurons in the visual cortex is profoundly altered following monocular deprivation (MD). It has been postulated that OD shifts also modify global neural networks, but such effects have never been demonstrated. Here, we used longitudinal wide-field optical calcium imaging to measure resting-state functional connectivity during acute (3-day) MD in mice. First, delta GCaMP6 power in the deprived visual cortex decreased, suggesting that excitatory activity was reduced in the region. In parallel, interhemispheric visual homotopic functional connectivity was rapidly reduced by the disruption of visual drive through MD and was sustained significantly below baseline state. This reduction of visual homotopic connectivity was accompanied by a reduction in parietal and motor homotopic connectivity. Finally, we observed enhanced internetwork connectivity between visual and parietal cortex that peaked at MD2. Together, these findings support the hypothesis that early MD induces dynamic reorganization of disparate functional networks including association cortices.

Tauopathy severely disrupts homeostatic set-points in emergent neural dynamics but not in the activity of individual neurons

The homeostatic regulation of neuronal activity is essential for robust computation; key set-points, such as firing rate, are actively stabilized to compensate for perturbations. From this perspective, the disruption of brain function central to neurodegenerative disease should reflect impairments of computationally essential set-points. Despite connecting neurodegeneration to functional outcomes, the impact of disease on set-points in neuronal activity is unknown. Here we present a comprehensive, theory-driven investigation of the effects of tau-mediated neurodegeneration on homeostatic set-points in neuronal activity. In a mouse model of tauopathy, we examine 27,000 hours of hippocampal recordings during free behavior throughout disease progression. Contrary to our initial hypothesis that tauopathy would impact set-points in spike rate and variance, we found that cell-level set-points are resilient to even the latest stages of disease. Instead, we find that tauopathy disrupts neuronal activity at the network-level, which we quantify using both pairwise measures of neuron interactions as well as measurement of the network's nearness to criticality, an ideal computational regime that is known to be a homeostatic set-point. We find that shifts in network criticality 1) track with symptoms, 2) predict underlying anatomical and molecular pathology, 3) occur in a sleep/wake dependent manner, and 4) can be used to reliably classify an animal's genotype. Our data suggest that the critical set-point is intact, but that homeostatic machinery is progressively incapable of stabilizing hippocampal networks, particularly during waking. This work illustrates how neurodegenerative processes can impact the computational capacity of neurobiological systems, and suggest an important connection between molecular pathology, circuit function, and animal behavior.

A non-oscillatory, millisecond-scale embedding of brain state provides insight into behavior

Sleep and wake are understood to be slow, long-lasting processes that span the entire brain. Brain states correlate with many neurophysiological changes, yet the most robust and reliable signature of state is enriched in rhythms between 0.1 and 20 Hz. The possibility that the fundamental unit of brain state could be a reliable structure at the scale of milliseconds and microns has not been addressed due to the physical limits associated with oscillation-based definitions. Here, by analyzing high resolution neural activity recorded in 10 anatomically and functionally diverse regions of the murine brain over 24 h, we reveal a mechanistically distinct embedding of state in the brain. Sleep and wake states can be accurately classified from on the order of 100 to 101 ms of neuronal activity sampled from 100 μm of brain tissue. In contrast to canonical rhythms, this embedding persists above 1,000 Hz. This high frequency embedding is robust to substates and rapid events such as sharp wave ripples and cortical ON/OFF states. To ascertain whether such fast and local structure is meaningful, we leveraged our observation that individual circuits intermittently switch states independently of the rest of the brain. Brief state discontinuities in subsets of circuits correspond with brief behavioral discontinuities during both sleep and wake. Our results suggest that the fundamental unit of state in the brain is consistent with the spatial and temporal scale of neuronal computation, and that this resolution can contribute to an understanding of cognition and behavior.

Transcriptomic cell type structures in vivo neuronal activity across multiple timescales

Cell type is hypothesized to be a key determinant of a neuron's role within a circuit. Here, we examine whether a neuron's transcriptomic type influences the timing of its activity. We develop a deep-learning architecture that learns features of interevent intervals across timescales (ms to >30 min). We show that transcriptomic cell-class information is embedded in the timing of single neuron activity in the intact brain of behaving animals (calcium imaging and extracellular electrophysiology) as well as in a bio-realistic model of the visual cortex. Further, a subset of excitatory cell types are distinguishable but can be classified with higher accuracy when considering cortical layer and projection class. Finally, we show that computational fingerprints of cell types may be universalizable across structured stimuli and naturalistic movies. Our results indicate that transcriptomic class and type may be imprinted in the timing of single neuron activity across diverse stimuli.

Detecting change points in neural population activity with contrastive metric learning

Finding points in time where the distribution of neural responses changes (change points) is an important step in many neural data analysis pipelines. However, in complex and free behaviors, where we see different types of shifts occurring at different rates, it can be difficult to use existing methods for change point (CP) detection because they can't necessarily handle different types of changes that may occur in the underlying neural distribution. Additionally, response changes are often sparse in high dimensional neural recordings, which can make existing methods detect spurious changes. In this work, we introduce a new approach for finding changes in neural population states across diverse activities and arousal states occurring in free behavior. Our model follows a contrastive learning approach: we learn a metric for CP detection based on maximizing the Sinkhorn divergences of neuron firing rates across two sides of a labeled CP. We apply this method to a 12-hour neural recording of a freely behaving mouse to detect changes in sleep stages and behavior. We show that when we learn a metric, we can better detect change points and also yield insights into which neurons and sub-groups are important for detecting certain types of switches that occur in the brain.

IoT cloud laboratory: Internet of Things architecture for cellular biology

The Internet of Things (IoT) provides a simple framework to control online devices easily. IoT is now a commonplace tool used by technology companies but is rarely used in biology experiments. IoT can benefit cloud biology research through alarm notifications, automation, and the real-time monitoring of experiments. We developed an IoT architecture to control biological devices and implemented it in lab experiments. Lab devices for electrophysiology, microscopy, and microfluidics were created from the ground up to be part of a unified IoT architecture. The system allows each device to be monitored and controlled from an online web tool. We present our IoT architecture so other labs can replicate it for their own experiments.

Human microglia states are conserved across experimental models and regulate neural stem cell responses in chimeric organoids

Microglia are resident macrophages in the brain that emerge in early development and respond to the local environment by altering their molecular and phenotypic states. Fundamental questions about microglia diversity and function during development remain unanswered because we lack experimental strategies to interrogate their interactions with other cell types and responses to perturbations ex vivo. We compared human microglia states across culture models, including cultured primary and pluripotent stem cell-derived microglia. We developed a "report card" of gene expression signatures across these distinct models to facilitate characterization of their responses across experimental models, perturbations, and disease conditions. Xenotransplantation of human microglia into cerebral organoids allowed us to characterize key transcriptional programs of developing microglia in vitro and reveal that microglia induce transcriptional changes in neural stem cells and decrease interferon signaling response genes. Microglia additionally accelerate the emergence of synchronized oscillatory network activity in brain organoids by modulating synaptic density.

Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity

Meaningful and simplified representations of neural activity can yield insights into how and what information is being processed within a neural circuit. However, without labels, finding representations that reveal the link between the brain and behavior can be challenging. Here, we introduce a novel unsupervised approach for learning disentangled representations of neural activity called Swap-VAE. Our approach combines a generative modeling framework with an instance-specific alignment loss that tries to maximize the representational similarity between transformed views of the input (brain state). These transformed (or augmented) views are created by dropping out neurons and jittering samples in time, which intuitively should lead the network to a representation that maintains both temporal consistency and invariance to the specific neurons used to represent the neural state. Through evaluations on both synthetic data and neural recordings from hundreds of neurons in different primate brains, we show that it is possible to build representations that disentangle neural datasets along relevant latent dimensions linked to behavior.

A MYT1L syndrome mouse model recapitulates patient phenotypes and reveals altered brain development due to disrupted neuronal maturation

Human genetics have defined a new neurodevelopmental syndrome caused by loss-of-function mutations in MYT1L, a transcription factor known for enabling fibroblast-to-neuron conversions. However, how MYT1L mutation causes intellectual disability, autism, ADHD, obesity, and brain anomalies is unknown. Here, we developed a Myt1l haploinsufficient mouse model that develops obesity, white-matter thinning, and microcephaly, mimicking common clinical phenotypes. During brain development we discovered disrupted gene expression, mediated in part by loss of Myt1l gene-target activation, and identified precocious neuronal differentiation as the mechanism for microcephaly. In contrast, in adults we discovered that mutation results in failure of transcriptional and chromatin maturation, echoed in disruptions in baseline physiological properties of neurons. Myt1l haploinsufficiency also results in behavioral anomalies, including hyperactivity, muscle weakness, and social alterations, with more severe phenotypes in males. Overall, our findings provide insight into the mechanistic underpinnings of this disorder and enable future preclinical studies.

Construction and Implementation of Carbon Fiber Microelectrode Arrays for Chronic and Acute In Vivo Recordings

Multichannel electrode arrays offer insight into the working brain and serve to elucidate neural processes at the single-cell and circuit levels. Development of these tools is crucial for understanding complex behaviors and cognition and for advancing clinical applications. However, it remains a challenge to densely record from cell populations stably and continuously over long time periods. Many popular electrodes, such as tetrodes and silicon arrays, feature large cross-diameters that produce damage upon insertion and elicit chronic reactive tissue responses associated with neuronal death, hindering the recording of stable, continuous neural activity. In addition, most wire bundles exhibit broad spacing between channels, precluding simultaneous recording from a large number of cells clustered in a small area. The carbon fiber microelectrode arrays described in this protocol offer an accessible solution to these concerns. The study provides a detailed method for fabricating carbon fiber microelectrode arrays that can be used for both acute and chronic recordings in vivo. The physical properties of these electrodes make them ideal for stable and continuous long-term recordings at high cell densities, enabling the researcher to make robust, unambiguous recordings from single units across months.

Homeostatic mechanisms regulate distinct aspects of cortical circuit dynamics

Homeostasis is indispensable to counteract the destabilizing effects of Hebbian plasticity. Although it is commonly assumed that homeostasis modulates synaptic strength, membrane excitability, and firing rates, its role at the neural circuit and network level is unknown. Here, we identify changes in higher-order network properties of freely behaving rodents during prolonged visual deprivation. Strikingly, our data reveal that functional pairwise correlations and their structure are subject to homeostatic regulation. Using a computational model, we demonstrate that the interplay of different plasticity and homeostatic mechanisms can capture the initial drop and delayed recovery of firing rates and correlations observed experimentally. Moreover, our model indicates that synaptic scaling is crucial for the recovery of correlations and network structure, while intrinsic plasticity is essential for the rebound of firing rates, suggesting that synaptic scaling and intrinsic plasticity can serve distinct functions in homeostatically regulating network dynamics.

Autism-Associated Shank3 Is Essential for Homeostatic Compensation in Rodent V1

Mutations in Shank3 are strongly associated with autism spectrum disorders and neural circuit changes in several brain areas, but the cellular mechanisms that underlie these defects are not understood. Homeostatic forms of plasticity allow central circuits to maintain stable function during experience-dependent development, leading us to ask whether loss of Shank3 might impair homeostatic plasticity and circuit-level compensation to perturbations. We found that Shank3 loss in vitro abolished synaptic scaling and intrinsic homeostatic plasticity, deficits that could be rescued by treatment with lithium. Further, Shank3 knockout severely compromised the in vivo ability of visual cortical circuits to recover from perturbations to sensory drive. Finally, lithium treatment ameliorated a repetitive self-grooming phenotype in Shank3 knockout mice. These findings demonstrate that Shank3 loss severely impairs the ability of central circuits to harness homeostatic mechanisms to compensate for perturbations in drive, which, in turn, may render them more vulnerable to such perturbations.

Currently Unstable: Daily Ups and Downs in E-I Balance

Balance between excitation and inhibition (E-I balance) in neural circuits is believed to be tightly regulated. To the contrary, in this issue of Neuron, Bridi et al. (2020) reveal that inverse oscillations of synaptic inhibition and excitation lead to peaks and valleys in E-I balance across the 24 h day.

Cortical Circuit Dynamics Are Homeostatically Tuned to Criticality In Vivo

Homeostatic mechanisms stabilize neuronal activity in vivo, but whether this process gives rise to balanced network dynamics is unknown. Here, we continuously monitored the statistics of network spiking in visual cortical circuits in freely behaving rats for 9 days. Under control conditions in light and dark, networks were robustly organized around criticality, a regime that maximizes information capacity and transmission. When input was perturbed by visual deprivation, network criticality was severely disrupted and subsequently restored to criticality over 48 h. Unexpectedly, the recovery of excitatory dynamics preceded homeostatic plasticity of firing rates by >30 h. We utilized model investigations to manipulate firing rate homeostasis in a cell-type-specific manner at the onset of visual deprivation. Our results suggest that criticality in excitatory networks is established by inhibitory plasticity and architecture. These data establish that criticality is consistent with a homeostatic set point for visual cortical dynamics and suggest a key role for homeostatic regulation of inhibition.

Neuronal Firing Rate Homeostasis Is Inhibited by Sleep and Promoted by Wake

Homeostatic mechanisms stabilize neural circuit function by keeping firing rates within a set-point range, but whether this process is gated by brain state is unknown. Here, we monitored firing rate homeostasis in individual visual cortical neurons in freely behaving rats as they cycled between sleep and wake states. When neuronal firing rates were perturbed by visual deprivation, they gradually returned to a precise, cell-autonomous set point during periods of active wake, with lengthening of the wake period enhancing firing rate rebound. Unexpectedly, this resetting of neuronal firing was suppressed during sleep. This raises the possibility that memory consolidation or other sleep-dependent processes are vulnerable to interference from homeostatic plasticity mechanisms. PAPERCLIP.

Daily isoflurane exposure increases barbiturate insensitivity in medullary respiratory and cortical neurons via expression of ε-subunit containing GABA ARs

The parameters governing GABA_A receptor subtype expression patterns are not well understood, although significant shifts in subunit expression may support key physiological events. For example, the respiratory control network in pregnant rats becomes relatively insensitive to barbiturates due to increased expression of ε-subunit-containing GABA_ARs in the ventral respiratory column. We hypothesized that this plasticity may be a compensatory response to a chronic increase in inhibitory tone caused by increased central neurosteroid levels. Thus, we tested whether increased inhibitory tone was sufficient to induce ε-subunit upregulation on respiratory and cortical neurons in adult rats. Chronic intermittent increases in inhibitory tone in male and female rats was induced via daily 5-min exposures to 3% isoflurane. After 7d of treatment, phrenic burst frequency was less sensitive to barbiturate in isoflurane-treated male and female rats in vivo. Neurons in the ventral respiratory group and cortex were less sensitive to pentobarbital in vitro following 7d and 30d of intermittent isoflurane-exposure in both male and female rats. The pentobarbital insensitivity in 7d isoflurane-treated rats was reversible after another 7d. We hypothesize that increased inhibitory tone in the respiratory control network and cortex causes a compensatory increase in ε-subunit-containing GABA_ARs.

Firing rate homeostasis in visual cortex of freely behaving rodents

It has been postulated that homeostatic mechanisms maintain stable circuit function by keeping neuronal firing within a set point range, but such firing rate homeostasis has never been demonstrated in vivo. Here we use chronic multielectrode recordings to monitor firing rates in visual cortex of freely behaving rats during chronic monocular visual deprivation (MD). Firing rates in V1 were suppressed over the first 2 day of MD but then rebounded to baseline over the next 2-3 days despite continued MD. This drop and rebound in firing was accompanied by bidirectional changes in mEPSC amplitude measured ex vivo. The rebound in firing was independent of sleep-wake state but was cell type specific, as putative FS and regular spiking neurons responded to MD with different time courses. These data establish that homeostatic mechanisms within the intact CNS act to stabilize neuronal firing rates in the face of sustained sensory perturbations.

Increased GABA(A) receptor ε-subunit expression on ventral respiratory column neurons protects breathing during pregnancy

GABAergic signaling is essential for proper respiratory function. Potentiation of this signaling with allosteric modulators such as anesthetics, barbiturates, and neurosteroids can lead to respiratory arrest. Paradoxically, pregnant animals continue to breathe normally despite nearly 100-fold increases in circulating neurosteroids. ε subunit-containing GABA_ARs are insensitive to positive allosteric modulation, thus we hypothesized that pregnant rats increase ε subunit-containing GABA_AR expression on brainstem neurons of the ventral respiratory column (VRC). In vivo, pregnancy rendered respiratory motor output insensitive to otherwise lethal doses of pentobarbital, a barbiturate previously used to categorize the ε subunit. Using electrode array recordings in vitro, we demonstrated that putative respiratory neurons of the preBötzinger Complex (preBötC) were also rendered insensitive to the effects of pentobarbital during pregnancy, but unit activity in the VRC was rapidly inhibited by the GABA_AR agonist, muscimol. VRC unit activity from virgin and post-partum females was potently inhibited by both pentobarbital and muscimol. Brainstem ε subunit mRNA and protein levels were increased in pregnant rats, and GABA_AR ε subunit expression co-localized with a marker of rhythm generating neurons (neurokinin 1 receptors) in the preBötC. These data support the hypothesis that pregnancy renders respiratory motor output and respiratory neuron activity insensitive to barbiturates, most likely via increased ε subunit-containing GABA_AR expression on respiratory rhythm-generating neurons. Increased ε subunit expression may be critical to preserve respiratory function (and life) despite increased neurosteroid levels during pregnancy.

Changes in ventral respiratory column GABAaR ε- and δ-subunits during hibernation mediate resistance to depression by EtOH and pentobarbital

During hibernation in the 13-lined ground squirrel, Ictidomys tridecemlineatus, the cerebral cortex is electrically silent, yet the brainstem continues to regulate cardiorespiratory function. Previous work showed that neurons in slices through the medullary ventral respiratory column (VRC) but not the cortex are insensitive to high doses of pentobarbital during hibernation, leading to the hypothesis that GABA(A) receptors (GABA(A)R) in the VRC undergo a seasonal modification in subunit composition. To test whether alteration of GABA(A)R subunits are responsible for hibernation-associated pentobarbital insensitivity, we examined an array of subunits using RT-PCR and Western blots and identified changes in ε- and δ-subunits in the medulla but not the cortex. Using immunohistochemistry, we confirmed that during hibernation, the expression of ε-subunit-containing GABA(A)Rs nearly doubles in the VRC. We also identified a population of δ-subunit-containing GABA(A)Rs adjacent to the VRC that were differentially expressed during hibernation. As δ-subunit-containing GABA(A)Rs are particularly sensitive to ethanol (EtOH), multichannel electrodes were inserted in slices of medulla and cortex from hibernating squirrels and EtOH was applied. EtOH, which normally inhibits neuronal activity, excited VRC but not cortical neurons during hibernation. This excitation was prevented by bicuculline pretreatment, indicating the involvement of GABA(A)Rs. We propose that neuronal activity in the VRC during hibernation is unaffected by pentobarbital due to upregulation of ε-subunit-containing GABA(A)Rs on VRC neurons. Synaptic input from adjacent inhibitory interneurons that express δ-subunit-containing GABA(A)Rs is responsible for the excitatory effects of EtOH on VRC neurons during hibernation.

Hibernation induces pentobarbital insensitivity in medulla but not cortex

The 13-lined ground squirrel (Ictidomys tridecemlineatus), a hibernating species, is a natural model of physiological adoption to an extreme environment. During torpor, body temperature drops to 0-4 degrees C, and the cortex is electrically silent, yet the brain stem continues to regulate cardiorespiratory function. The mechanisms underlying selective inhibition in the brain during torpor are not known. To test whether altered GABAergic function is involved in regional and seasonal differences in neuronal activity, cortical and medullary slices from summer-active (SA) and interbout aroused (IBA) squirrels were placed in a standard in vitro recording chamber. Silicon multichannel electrodes were placed in cortex, ventral respiratory column (VRC), and nucleus tractus solitarius (NTS) to record spontaneous neuronal activity. In slices from IBA squirrels, bath-applied pentobarbital sodium (300 microM) nearly abolished cortical neuronal activity, but VRC and NTS neuronal activity was unaltered. In contrast, pentobarbital sodium (300 microM) nearly abolished all spontaneous cortical, VRC, and NTS neuronal activity in slices from SA squirrels. Muscimol (20 microM; GABA(A) receptor agonist) abolished all neuronal activity in cortical and medullary slices from both IBA and SA squirrels, thereby demonstrating the presence of functional GABA(A) receptors. Pretreatment of cortical slices from IBA squirrels with bicuculline (100 microM; GABA(A) receptor antagonist) blocked pentobarbital-dependent inhibition of spontaneous neuronal activity. We hypothesize that GABA(A) receptors undergo a seasonal modification in subunit composition, such that cardiorespiratory neurons are uniquely unaffected by surges of an endogenous positive allosteric modulator.