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The most robust and reliable signatures of brain states are enriched in rhythms between 0.1 and 20 Hz. Here we address the possibility that the fundamental unit of brain state could be at the scale of milliseconds and micrometers. By analyzing high-resolution neural activity recorded in ten mouse brain regions over 24 h, we reveal that brain states are reliably identifiable (embedded) in fast, nonoscillatory activity. Sleep and wake states could be classified from 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, sharp-wave ripples and cortical on/off states. Individual regions intermittently switched states independently of the rest of the brain, and such brief state discontinuities coincided with brief behavioral discontinuities. Our results suggest that the fundamental unit of state in the brain is consistent with the spatial and temporal scale of neuronal computation.
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The development of motor control over sensory organs is a critical milestone in sensory processing, enabling active exploration and shaping of the sensory environment. However, whether the onset of sensory organ motor control directly influences the development of corresponding sensory cortices remains unknown. Here, we exploit the late onset of whisking behavior in mice to address this question in the somatosensory system. Using ex vivo electrophysiology, we discovered a transient increase in the intrinsic excitability of excitatory neurons in layer IV of the barrel cortex, which processes whisker input, precisely coinciding with the onset of active whisking at postnatal day 14 (P14). This increase in neuronal gain was specific to layer IV, independent of changes in synaptic strength, and required prior sensory experience. Strikingly, the effect was not observed in layer II/III of the barrel cortex or in the visual cortex upon eye opening, suggesting a unique interaction between the development of active sensing and the thalamocortical input layer in the somatosensory system. Predictive modeling indicated that changes in active membrane conductances alone could reliably distinguish P14 neurons in control but not whisker-deprived hemispheres. Our findings demonstrate an experience-dependent, lamina-specific refinement of neuronal excitability tightly linked to the emergence of active whisking. This transient increase in the gain of the thalamic input layer coincides with a critical period for synaptic plasticity in downstream layers, suggesting a role in facilitating cortical maturation and sensory processing. Together, our results provide evidence for a direct interaction between the development of motor control and sensory cortex, offering new insights into the experience-dependent development and refinement of sensory systems. These findings have broad implications for understanding the interplay between motor and sensory development, and how the mechanisms of perception cooperate with behavior.
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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 (3â 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 (0.4-4â 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 2â d after MD. Together, these findings support the hypothesis that early MD induces dynamic reorganization of disparate functional networks including the association cortices.
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Ratones Endogámicos C57BL , Red Nerviosa , Privación Sensorial , Corteza Visual , Animales , Ratones , Masculino , Femenino , Privación Sensorial/fisiología , Corteza Visual/fisiología , Red Nerviosa/fisiología , Plasticidad Neuronal/fisiología , Predominio Ocular/fisiología , Período Crítico Psicológico , Vías Visuales/fisiologíaRESUMEN
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.
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Electroencefalografía , Sueño , Ratas , Animales , Electroencefalografía/métodos , Sueño/fisiología , Encéfalo/fisiología , Neuronas , Homeostasis/fisiología , Vigilia/fisiologíaRESUMEN
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.
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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.
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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.
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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.
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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.
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Neuronas , Transcriptoma , Animales , Transcriptoma/genética , Neuronas/fisiología , AprendizajeRESUMEN
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.
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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.
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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.
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Discapacidad Intelectual , Proteínas del Tejido Nervioso/genética , Factores de Transcripción/genética , Animales , Encéfalo/metabolismo , Humanos , Discapacidad Intelectual/genética , Masculino , Ratones , Proteínas del Tejido Nervioso/metabolismo , Neurogénesis , Fenotipo , Factores de Transcripción/metabolismoRESUMEN
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.
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Células Madre Pluripotentes Inducidas , Células-Madre Neurales , Encéfalo , Diferenciación Celular , Humanos , Microglía , Modelos Teóricos , OrganoidesRESUMEN
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.
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Neuronas , Silicio , Fibra de Carbono , Electrodos Implantados , MicroelectrodosRESUMEN
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.
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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.
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Homeostasis , Plasticidad Neuronal , Animales , Neuronas/química , Neuronas/fisiología , Roedores , Sinapsis/fisiología , Corteza Visual/química , Corteza Visual/fisiologíaRESUMEN
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.
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Homeostasis/genética , Proteínas del Tejido Nervioso/genética , Plasticidad Neuronal/genética , Neuronas/efectos de los fármacos , Corteza Visual/efectos de los fármacos , Animales , Antimaníacos/farmacología , Trastorno Autístico/genética , Conducta Animal/efectos de los fármacos , Potenciales Postsinápticos Excitadores/efectos de los fármacos , Potenciales Postsinápticos Excitadores/genética , Técnicas de Silenciamiento del Gen , Glucógeno Sintasa Quinasa 3/antagonistas & inhibidores , Aseo Animal/efectos de los fármacos , Homeostasis/efectos de los fármacos , Compuestos de Litio/farmacología , Ratones , Ratones Noqueados , Proteínas de Microfilamentos , Proteínas del Tejido Nervioso/efectos de los fármacos , Vías Nerviosas , Plasticidad Neuronal/efectos de los fármacos , Neuronas/metabolismo , Ratas , Bloqueadores de los Canales de Sodio/farmacología , Tetrodotoxina/farmacología , Corteza Visual/citología , Corteza Visual/metabolismoRESUMEN
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.
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Corteza Visual , NeuronasRESUMEN
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.