Activity labeling in vivo using CaMPARI2 reveals intrinsic and synaptic differences between neurons with high and low firing rate set points

HDAC4 Inhibits NMDA Receptor-mediated Stimulation of Neurogranin Expression

The coordination of neuronal wiring and activity within the central nervous system (CNS) is crucial for cognitive function, particularly in the context of aging and neurological disorders. Neurogranin (Ng), an abundant forebrain protein, modulates calmodulin (CaM) activity and deeply influences synaptic plasticity and neuronal processing. This study investigates the regulatory mechanisms of Ng expression, a critical but underexplored area for combating cognitive impairment. Utilizing both in vitro and in vivo hippocampal models, we show that Ng expression arises during late developmental stages, coinciding with the processes of synaptic maturation and neuronal circuit consolidation. We observed that Ng expression increases in neuronal networks with heightened synaptic activity and identified GluN2B-containing N-methyl-D-aspartate (NMDA) receptors as key drivers of this expression. Additionally, we discovered that nuclear-localized HDAC4 inhibits Ng expression, establishing a regulatory axis that is counteracted by NMDA receptor stimulation. Analysis of the Ng gene promoter activity revealed regulatory elements between the - 2.4 and - 0.85 Kbp region, including a binding site for RE1-Silencing Transcription factor (REST), which may mediate HDAC4's repressive effect on Ng expression. Further analysis of the promoter sequence revealed conserved binding sites for the myocyte enhancer factor-2 (MEF2) transcription factor, a target of HDAC4-mediated transcription regulation. Our findings elucidate the interplay between synaptic activity, NMDAR function, and transcriptional regulation in controlling Ng expression, offering insights into synaptic plasticity mechanisms and potential therapeutic strategies to prevent cognitive dysfunction.

Cutting-edge methodologies for tagging and tracing active neuronal coding in the brain

Decoding the neural substrates that underlie learning and behavior is a fundamental goal in neuroscience. Identifying "key players" at the molecular, cellular, and circuit levels has become possible with recent advancements in molecular technologies offering high spatiotemporal resolution. Immediate-early genes are effective markers of neural activity and plasticity, allowing for the identification of active cells involved in memory-based behavior. A calcium-dependent labeling system coupled with light or biochemical proximity labeling allows characterization of active cell ensembles and circuitry across broader brain regions within short time windows, particularly during transient behaviors. The integration of these systems expands the ability to address diverse research questions across behavioral paradigms. This review examines current molecular systems for activity-dependent labeling, highlighting their applications in identifying specific cell ensembles and circuits relevant to various scientific questions and further discuss their significance, along with future directions for the development of innovative methodologies.

A Massively Parallel CRISPR-Based Screening Platform for Modifiers of Neuronal Activity

Understanding the complex interplay between gene expression and neuronal activity is crucial for unraveling the molecular mechanisms underlying cognitive function and neurological disorders. Here, we developed pooled screens for neuronal activity, using CRISPR interference (CRISPRi) and the fluorescent calcium integrator CaMPARI2. Using this screening method, we evaluated 1343 genes for their effect on excitability in human iPSC-derived neurons, revealing potential links to neurodegenerative and neurodevelopmental disorders. These genes include known regulators of neuronal excitability, such as TARPs and ion channels, as well as genes associated with autism spectrum disorder and Alzheimer's disease not previously described to affect neuronal excitability. This CRISPRi-based screening platform offers a versatile tool to uncover molecular mechanisms controlling neuronal activity in health and disease.

Spatial Mapping of Activity Changes across Sensory Areas Following Visual Deprivation in Adults

Loss of a sensory modality triggers global adaptation across brain areas, allowing the remaining senses to guide behavior more effectively. There are specific synaptic and circuit plasticity observed across many sensory areas, which suggests potential widespread changes in activity. Here we used a cFosTRAP2 mouse line to drive tdTomato (tdT) expression in active cells to spatially map the extent of activity changes in various sensory areas in adult mice of both sexes following two modes of visual deprivation. We found that in the primary visual cortex (V1), both dark exposure (DE) and enucleation (EN) caused an initial loss of active cells followed by a partial rebound, which occurred relatively more in the superficial layers. A similar pattern was observed in the secondary visual cortex, especially in the lateral areas (V2L). The spared primary sensory cortices adapted distinctly. In the primary somatosensory barrel cortex (S1BF), there was a change in the density of active cells dependent on the duration and the mode of visual deprivation. In the primary auditory cortex (A1), there was a relative reduction in the density of active cells in the superficial layers without a significant change in the overall density. There were minimal changes in the active cell density in the secondary cortices of the spared senses and the multisensory retrosplenial cortex (RSP). Our results are consistent with cross-modal recruitment of the deprived visual cortex and compensatory plasticity in the spared primary sensory cortices that can support enhanced processing and refinement of the spared senses.

Keeping Your Brain in Balance: Homeostatic Regulation of Network Function

To perform computations with the efficiency necessary for animal survival, neocortical microcircuits must be capable of reconfiguring in response to experience, while carefully regulating excitatory and inhibitory connectivity to maintain stable function. This dynamic fine-tuning is accomplished through a rich array of cellular homeostatic plasticity mechanisms that stabilize important cellular and network features such as firing rates, information flow, and sensory tuning properties. Further, these functional network properties can be stabilized by different forms of homeostatic plasticity, including mechanisms that target excitatory or inhibitory synapses, or that regulate intrinsic neuronal excitability. Here we discuss which aspects of neocortical circuit function are under homeostatic control, how this homeostasis is realized on the cellular and molecular levels, and the pathological consequences when circuit homeostasis is impaired. A remaining challenge is to elucidate how these diverse homeostatic mechanisms cooperate within complex circuits to enable them to be both flexible and stable.

Basal forebrain cholinergic activity is necessary for upward firing rate homeostasis in the rodent visual cortex

Bidirectional homeostatic plasticity allows neurons and circuits to maintain stable firing in the face of developmental or learning-induced perturbations. In the primary visual cortex (V1), upward firing rate homeostasis (FRH) only occurs during active wake (AW) and downward during sleep, but how this behavioral state-dependent gating is accomplished is unknown. Here, we focus on how AW enables upward FRH in V1 of juvenile Long Evans rats. A major difference between quiet wake (QW), when upward FRH is absent, and AW, when it is present, is increased cholinergic (ACh) tone, and the main cholinergic projections to V1 arise from the horizontal diagonal band of the basal forebrain (HDB ACh). We therefore chemogenetically inhibited HDB ACh neurons while inducing upward homeostatic compensation using direct activity-suppression in V1. We found that synaptic scaling up and intrinsic homeostatic plasticity, two important cellular mediators of upward FRH, were both impaired when HDB ACh neurons were inhibited. Most strikingly, HDB ACh inhibition flipped the sign of intrinsic plasticity so that it became anti-homeostatic, and this effect was phenocopied by knockdown of the M1 ACh receptor in V1, indicating that this modulation of intrinsic plasticity is the result of direct actions of ACh within V1. Finally, we found that upward FRH induced by visual deprivation was completely prevented by HDB ACh inhibition. Together, our results show that HDB ACh modulation is a key enabler of upward homeostatic plasticity and FRH, and more broadly suggest that neuromodulatory inputs can segregate upward and downward homeostatic plasticity into distinct behavioral states.

Neuronal Spike Shapes (NSS): A straightforward approach to investigate heterogeneity in neuronal excitability states

The mammalian brain exhibits a remarkable diversity of neurons, contributing to its intricate architecture and functional complexity. The analysis of multimodal single-cell datasets enables the investigation of cell types and states heterogeneity. In this study, we introduce the Neuronal Spike Shapes (NSS), a straightforward approach for the exploration of excitability states of neurons based on their Action Potential (AP) waveforms. The NSS method describes the AP waveform based on a triangular representation complemented by a set of derived electrophysiological (EP) features. To support this hypothesis, we validate the proposed approach on two datasets of murine cortical neurons, focusing it on GABAergic neurons. The validation process involves a combination of NSS-based clustering analysis, features exploration, Differential Expression (DE), and Gene Ontology (GO) enrichment analysis. Results show that the NSS-based analysis captures neuronal excitability states that possess biological relevance independently of cell subtype. In particular, Neuronal Spike Shapes (NSS) captures, among others, a well-characterized fast-spiking excitability state, supported by both electrophysiological and transcriptomic validation. Gene Ontology Enrichment Analysis reveals voltage-gated potassium (K+) channels as specific markers of the identified NSS partitions. This finding strongly corroborates the biological relevance of NSS partitions as excitability states, as the expression of voltage-gated K+ channels regulates the hyperpolarization phase of the AP, being directly implicated in the regulation of neuronal excitability.

Approaches and considerations of studying neuronal ensembles: a brief review

First theorized by Hebb, neuronal ensembles have provided a framework for understanding how the mammalian brain operates, especially regarding learning and memory. Neuronal ensembles are discrete, sparsely distributed groups of neurons that become activated in response to a specific stimulus and are thought to provide an internal representation of the world. Beyond the study of region-wide or projection-wide activation, the study of ensembles offers increased specificity and resolution to identify and target specific memories or associations. Neuroscientists interested in the neurobiology of learning, memory, and motivated behavior have used electrophysiological-, calcium-, and protein-based proxies of neuronal activity in preclinical models to better understand the neurobiology of learned and motivated behaviors. Although these three approaches may be used to pursue the same general goal of studying neuronal ensembles, technical differences lead to inconsistencies in the output and interpretation of data. This mini-review highlights some of the methodologies used in electrophysiological-, calcium-, and protein-based studies of neuronal ensembles and discusses their strengths and weaknesses.

Plasticity of neuronal dynamics in the lateral habenula for cue-punishment associative learning

The brain's ability to associate threats with external stimuli is vital to execute essential behaviours including avoidance. Disruption of this process contributes instead to the emergence of pathological traits which are common in addiction and depression. However, the mechanisms and neural dynamics at the single-cell resolution underlying the encoding of associative learning remain elusive. Here, employing a Pavlovian discrimination task in mice we investigate how neuronal populations in the lateral habenula (LHb), a subcortical nucleus whose excitation underlies negative affect, encode the association between conditioned stimuli and a punishment (unconditioned stimulus). Large population single-unit recordings in the LHb reveal both excitatory and inhibitory responses to aversive stimuli. Additionally, local optical inhibition prevents the formation of cue discrimination during associative learning, demonstrating a critical role of LHb activity in this process. Accordingly, longitudinal in vivo two-photon imaging tracking LHb calcium neuronal dynamics during conditioning reveals an upward or downward shift of individual neurons' CS-evoked responses. While recordings in acute slices indicate strengthening of synaptic excitation after conditioning, support vector machine algorithms suggest that postsynaptic dynamics to punishment-predictive cues represent behavioral cue discrimination. To examine the presynaptic signaling in LHb participating in learning we monitored neurotransmitter dynamics with genetically-encoded indicators in behaving mice. While glutamate, GABA, and serotonin release in LHb remain stable across associative learning, we observe enhanced acetylcholine signaling developing throughout conditioning. In summary, converging presynaptic and postsynaptic mechanisms in the LHb underlie the transformation of neutral cues in valued signals supporting cue discrimination during learning.

A biophysical perspective on the resilience of neuronal excitability across timescales

Neuronal membrane excitability must be resilient to perturbations that can take place over timescales from milliseconds to months (or even years in long-lived animals). A great deal of attention has been paid to classes of homeostatic mechanisms that contribute to long-term maintenance of neuronal excitability through processes that alter a key structural parameter: the number of ion channel proteins present at the neuronal membrane. However, less attention has been paid to the self-regulating 'automatic' mechanisms that contribute to neuronal resilience by virtue of the kinetic properties of ion channels themselves. Here, we propose that these two sets of mechanisms are complementary instantiations of feedback control, together enabling resilience on a wide range of temporal scales. We further point to several methodological and conceptual challenges entailed in studying these processes - both of which involve enmeshed feedback control loops - and consider the consequences of these mechanisms of resilience.

Molecularly targetable cell types in mouse visual cortex have distinguishable prediction error responses

Predictive processing postulates the existence of prediction error neurons in cortex. Neurons with both negative and positive prediction error response properties have been identified in layer 2/3 of visual cortex, but whether they correspond to transcriptionally defined subpopulations is unclear. Here we used the activity-dependent, photoconvertible marker CaMPARI2 to tag neurons in layer 2/3 of mouse visual cortex during stimuli and behaviors designed to evoke prediction errors. We performed single-cell RNA-sequencing on these populations and found that previously annotated Adamts2 and Rrad layer 2/3 transcriptional cell types were enriched when photolabeling during stimuli that drive negative or positive prediction error responses, respectively. Finally, we validated these results functionally by designing artificial promoters for use in AAV vectors to express genetically encoded calcium indicators. Thus, transcriptionally distinct cell types in layer 2/3 that can be targeted using AAV vectors exhibit distinguishable negative and positive prediction error responses.

Logarithmically scaled, gamma distributed neuronal spiking

Naturally log-scaled quantities abound in the nervous system. Distributions of these quantities have non-intuitive properties, which have implications for data analysis and the understanding of neural circuits. Here, we review the log-scaled statistics of neuronal spiking and the relevant analytical probability distributions. Recent work using log-scaling revealed that interspike intervals of forebrain neurons segregate into discrete modes reflecting spiking at different timescales and are each well-approximated by a gamma distribution. Each neuron spends most of the time in an irregular spiking 'ground state' with the longest intervals, which determines the mean firing rate of the neuron. Across the entire neuronal population, firing rates are log-scaled and well approximated by the gamma distribution, with a small number of highly active neurons and an overabundance of low rate neurons (the 'dark matter'). These results are intricately linked to a heterogeneous balanced operating regime, which confers upon neuronal circuits multiple computational advantages and has evolutionarily ancient origins.

Creation of Neuronal Ensembles and Cell-Specific Homeostatic Plasticity through Chronic Sparse Optogenetic Stimulation

Cortical computations emerge from the dynamics of neurons embedded in complex cortical circuits. Within these circuits, neuronal ensembles, which represent subnetworks with shared functional connectivity, emerge in an experience-dependent manner. Here we induced ensembles in ex vivo cortical circuits from mice of either sex by differentially activating subpopulations through chronic optogenetic stimulation. We observed a decrease in voltage correlation, and importantly a synaptic decoupling between the stimulated and nonstimulated populations. We also observed a decrease in firing rate during Up-states in the stimulated population. These ensemble-specific changes were accompanied by decreases in intrinsic excitability in the stimulated population, and a decrease in connectivity between stimulated and nonstimulated pyramidal neurons. By incorporating the empirically observed changes in intrinsic excitability and connectivity into a spiking neural network model, we were able to demonstrate that changes in both intrinsic excitability and connectivity accounted for the decreased firing rate, but only changes in connectivity accounted for the observed decorrelation. Our findings help ascertain the mechanisms underlying the ability of chronic patterned stimulation to create ensembles within cortical circuits and, importantly, show that while Up-states are a global network-wide phenomenon, functionally distinct ensembles can preserve their identity during Up-states through differential firing rates and correlations.SIGNIFICANCE STATEMENT The connectivity and activity patterns of local cortical circuits are shaped by experience. This experience-dependent reorganization of cortical circuits is driven by complex interactions between different local learning rules, external input, and reciprocal feedback between many distinct brain areas. Here we used an ex vivo approach to demonstrate how simple forms of chronic external stimulation can shape local cortical circuits in terms of their correlated activity and functional connectivity. The absence of feedback between different brain areas and full control of external input allowed for a tractable system to study the underlying mechanisms and development of a computational model. Results show that differential stimulation of subpopulations of neurons significantly reshapes cortical circuits and forms subnetworks referred to as neuronal ensembles.

Network instability dynamics drive a transient bursting period in the developing hippocampus in vivo

Spontaneous correlated activity is a universal hallmark of immature neural circuits. However, the cellular dynamics and intrinsic mechanisms underlying network burstiness in the intact developing brain are largely unknown. Here, we use two-photon Ca2+ imaging to comprehensively map the developmental trajectories of spontaneous network activity in the hippocampal area CA1 of mice in vivo. We unexpectedly find that network burstiness peaks after the developmental emergence of effective synaptic inhibition in the second postnatal week. We demonstrate that the enhanced network burstiness reflects an increased functional coupling of individual neurons to local population activity. However, pairwise neuronal correlations are low, and network bursts (NBs) recruit CA1 pyramidal cells in a virtually random manner. Using a dynamic systems modeling approach, we reconcile these experimental findings and identify network bi-stability as a potential regime underlying network burstiness at this age. Our analyses reveal an important role of synaptic input characteristics and network instability dynamics for NB generation. Collectively, our data suggest a mechanism, whereby developing CA1 performs extensive input-discrimination learning prior to the onset of environmental exploration.

ΔFosB accumulation in hippocampal granule cells drives cFos pattern separation during spatial learning

Mice display signs of fear when neurons that express cFos during fear conditioning are artificially reactivated. This finding gave rise to the notion that cFos marks neurons that encode specific memories. Here we show that cFos expression patterns in the mouse dentate gyrus (DG) change dramatically from day to day in a water maze spatial learning paradigm, regardless of training level. Optogenetic inhibition of neurons that expressed cFos on the first training day affected performance days later, suggesting that these neurons continue to be important for spatial memory recall. The mechanism preventing repeated cFos expression in DG granule cells involves accumulation of ΔFosB, a long-lived splice variant of FosB. CA1 neurons, in contrast, repeatedly expressed cFos. Thus, cFos-expressing granule cells may encode new features being added to the internal representation during the last training session. This form of timestamping is thought to be required for the formation of episodic memories.

Paradoxical self-sustained dynamics emerge from orchestrated excitatory and inhibitory homeostatic plasticity rules

Cortical networks have the remarkable ability to self-assemble into dynamic regimes in which excitatory positive feedback is balanced by recurrent inhibition. This inhibition-stabilized regime is increasingly viewed as the default dynamic regime of the cortex, but how it emerges in an unsupervised manner remains unknown. We prove that classic forms of homeostatic plasticity are unable to drive recurrent networks to an inhibition-stabilized regime due to the well-known paradoxical effect. We next derive a novel family of cross-homeostatic rules that lead to the unsupervised emergence of inhibition-stabilized networks. These rules shed new light on how the brain may reach its default dynamic state and provide a valuable tool to self-assemble artificial neural networks into ideal computational regimes.

Self-sustained neural activity maintained through local recurrent connections is of fundamental importance to cortical function. Converging theoretical and experimental evidence indicates that cortical circuits generating self-sustained dynamics operate in an inhibition-stabilized regime. Theoretical work has established that four sets of weights (W_E←E, W_E←I, W_I←E, and W_I←I) must obey specific relationships to produce inhibition-stabilized dynamics, but it is not known how the brain can appropriately set the values of all four weight classes in an unsupervised manner to be in the inhibition-stabilized regime. We prove that standard homeostatic plasticity rules are generally unable to generate inhibition-stabilized dynamics and that their instability is caused by a signature property of inhibition-stabilized networks: the paradoxical effect. In contrast, we show that a family of “cross-homeostatic” rules overcome the paradoxical effect and robustly lead to the emergence of stable dynamics. This work provides a model of how—beginning from a silent network—self-sustained inhibition-stabilized dynamics can emerge from learning rules governing all four synaptic weight classes in an orchestrated manner.

VTA-projecting cerebellar neurons mediate stress-dependent depression-like behaviors

Although cerebellar alterations have been implicated in stress symptoms, the exact contribution of the cerebellum to stress symptoms remains to be elucidated. Here, we demonstrated the crucial role of cerebellar neurons projecting to the ventral tegmental area (VTA) in the development of chronic stress-induced behavioral alterations in mice. Chronic chemogenetic activation of inhibitory Purkinje cells in crus I suppressed c-Fos expression in the DN and an increase in immobility in the tail suspension test or forced swimming test, which were triggered by chronic stress application. The combination of adeno-associated virus-based circuit mapping and electrophysiological recording identified network connections from crus I to the VTA via the dentate nucleus (DN) of the deep cerebellar nuclei. Furthermore, chronic inhibition of specific neurons in the DN that project to the VTA prevented stressed mice from showing such depression-like behavior, whereas chronic activation of these neurons alone triggered behavioral changes that were comparable with the depression-like behaviors triggered by chronic stress application. Our results indicate that the VTA-projecting cerebellar neurons proactively regulate the development of depression-like behavior, raising the possibility that cerebellum may be an effective target for the prevention of depressive disorders in human.

Developmental Regulation of Homeostatic Plasticity in Mouse Primary Visual Cortex

Homeostatic plasticity maintains network stability by adjusting excitation, inhibition, or the intrinsic excitability of neurons, but the developmental regulation and coordination of these distinct forms of homeostatic plasticity remains poorly understood. A major contributor to this information gap is the lack of a uniform paradigm for chronically manipulating activity at different developmental stages. To overcome this limitation, we used designer receptors exclusively activated by designer drugs (DREADDs) to directly suppress neuronal activity in layer2/3 (L2/3) of mouse primary visual cortex of either sex at two important developmental timepoints: the classic visual system critical period [CP; postnatal day 24 (P24) to P29], and adulthood (P45 to P55). We show that 24 h of DREADD-mediated activity suppression simultaneously induces excitatory synaptic scaling up and intrinsic homeostatic plasticity in L2/3 pyramidal neurons during the CP, consistent with previous observations using prolonged visual deprivation. Importantly, manipulations known to block these forms of homeostatic plasticity when induced pharmacologically or via visual deprivation also prevented DREADD-induced homeostatic plasticity. We next used the same paradigm to suppress activity in adult animals. Surprisingly, while excitatory synaptic scaling persisted into adulthood, intrinsic homeostatic plasticity was completely absent. Finally, we found that homeostatic changes in quantal inhibitory input onto L2/3 pyramidal neurons were absent during the CP but were present in adults. Thus, the same population of neurons can express distinct sets of homeostatic plasticity mechanisms at different development stages. Our findings suggest that homeostatic forms of plasticity can be recruited in a modular manner according to the evolving needs of a developing neural circuit.SIGNIFICANCE STATEMENT Developing brain circuits are subject to dramatic changes in inputs that could destabilize activity if left uncompensated. This compensation is achieved through a set of homeostatic plasticity mechanisms that provide slow, negative feedback adjustments to excitability. Given that circuits are subject to very different destabilizing forces during distinct developmental stages, the forms of homeostatic plasticity present in the network must be tuned to these evolving needs. Here we developed a method to induce comparable homeostatic compensation during distinct developmental windows and found that neurons in the juvenile and mature brain engage strikingly different forms of homeostatic plasticity. Thus, homeostatic mechanisms can be recruited in a modular manner according to the developmental needs of the circuit.

Genetically Encoded Fluorescent Indicators for Imaging Brain Chemistry

Genetically encoded fluorescent indicators, combined with optical imaging, enable the detection of physiologically or behaviorally relevant neural activity with high spatiotemporal resolution. Recent developments in protein engineering and screening strategies have improved the dynamic range, kinetics, and spectral properties of genetically encoded fluorescence indicators of brain chemistry. Such indicators have detected neurotransmitter and calcium dynamics with high signal-to-noise ratio at multiple temporal and spatial scales in vitro and in vivo. This review summarizes the current trends in these genetically encoded fluorescent indicators of neurotransmitters and calcium, focusing on their key metrics and in vivo applications.

Ciliary neuropeptidergic signaling dynamically regulates excitatory synapses in postnatal neocortical pyramidal neurons

Primary cilia are compartmentalized sensory organelles present on the majority of neurons in the mammalian brain throughout adulthood. Recent evidence suggests that cilia regulate multiple aspects of neuronal development, including the maintenance of neuronal connectivity. However, whether ciliary signals can dynamically modulate postnatal circuit excitability is unknown. Here we show that acute cell-autonomous knockdown of ciliary signaling rapidly strengthens glutamatergic inputs onto cultured rat neocortical pyramidal neurons and increases spontaneous firing. This increased excitability occurs without changes to passive neuronal properties or intrinsic excitability. Further, the neuropeptide receptor somatostatin receptor 3 (SSTR3) is localized nearly exclusively to excitatory neuron cilia both in vivo and in culture, and pharmacological manipulation of SSTR3 signaling bidirectionally modulates excitatory synaptic inputs onto these neurons. Our results indicate that ciliary neuropeptidergic signaling dynamically modulates excitatory synapses and suggest that defects in this regulation may underlie a subset of behavioral and cognitive disorders associated with ciliopathies.