Properties Of Neural Circuits Research Articles

Spatial transcriptomics in neuroscience.

The brain is one of the most complex living tissue types and is composed of an exceptional diversity of cell types displaying unique functional connectivity. Single-cell RNA sequencing (scRNA-seq) can be used to efficiently map the molecular identities of the various cell types in the brain by providing the transcriptomic profiles of individual cells isolated from the tissue. However, the lack of spatial context in scRNA-seq prevents a comprehensive understanding of how different configurations of cell types give rise to specific functions in individual brain regions and how each distinct cell is connected to form a functional unit. To understand how the various cell types contribute to specific brain functions, it is crucial to correlate the identities of individual cells obtained through scRNA-seq with their spatial information in intact tissue. Spatial transcriptomics (ST) can resolve the complex spatial organization of cell types in the brain and their connectivity. Various ST tools developed during the past decade based on imaging and sequencing technology have permitted the creation of functional atlases of the brain and have pulled the properties of neural circuits into ever-sharper focus. In this review, we present a summary of several ST tools and their applications in neuroscience and discuss the unprecedented insights these tools have made possible.

Recent advances in understanding neuronal diversity and neural circuit complexity across different brain regions using single-cell sequencing.

Neural circuits are characterized as interconnecting neuron networks connected by synapses. Some kinds of gene expression and/or functional changes of neurons and synaptic connections may result in aberrant neural circuits, which has been recognized as one crucial pathological mechanism for the onset of many neurological diseases. Gradual advances in single-cell sequencing approaches with strong technological advantages, as exemplified by high throughput and increased resolution for live cells, have enabled it to assist us in understanding neuronal diversity across diverse brain regions and further transformed our knowledge of cellular building blocks of neural circuits through revealing numerous molecular signatures. Currently published transcriptomic studies have elucidated various neuronal subpopulations as well as their distribution across prefrontal cortex, hippocampus, hypothalamus, and dorsal root ganglion, etc. Better characterization of brain region-specific circuits may shed light on new pathological mechanisms involved and assist in selecting potential targets for the prevention and treatment of specific neurological disorders based on their established roles. Given diverse neuronal populations across different brain regions, we aim to give a brief sketch of current progress in understanding neuronal diversity and neural circuit complexity according to their locations. With the special focus on the application of single-cell sequencing, we thereby summarize relevant region-specific findings. Considering the importance of spatial context and connectivity in neural circuits, we also discuss a few published results obtained by spatial transcriptomics. Taken together, these single-cell sequencing data may lay a mechanistic basis for functional identification of brain circuit components, which links their molecular signatures to anatomical regions, connectivity, morphology, and physiology. Furthermore, the comprehensive characterization of neuron subtypes, their distributions, and connectivity patterns via single-cell sequencing is critical for understanding neural circuit properties and how they generate region-dependent interactions in different context.

Kinesin-3 mediated axonal delivery of presynaptic neurexin stabilizes dendritic spines and postsynaptic components.

The functional properties of neural circuits are defined by the patterns of synaptic connections between their partnering neurons, but the mechanisms that stabilize circuit connectivity are poorly understood. We systemically examined this question at synapses onto newly characterized dendritic spines of C. elegans GABAergic motor neurons. We show that the presynaptic adhesion protein neurexin/NRX-1 is required for stabilization of postsynaptic structure. We find that early postsynaptic developmental events proceed without a strict requirement for synaptic activity and are not disrupted by deletion of neurexin/nrx-1. However, in the absence of presynaptic NRX-1, dendritic spines and receptor clusters become destabilized and collapse prior to adulthood. We demonstrate that NRX-1 delivery to presynaptic terminals is dependent on kinesin-3/UNC-104 and show that ongoing UNC-104 function is required for postsynaptic maintenance in mature animals. By defining the dynamics and temporal order of synapse formation and maintenance events in vivo, we describe a mechanism for stabilizing mature circuit connectivity through neurexin-based adhesion.

Ultra-low-power switching circuits based on a binary pattern generator with spiking neurons

Research on various neuro-inspired technologies has received much attention. However, while higher-order neural functions such as recognition have been emphasized, the fundamental properties of neural circuits as advanced control systems have not been fully exploited. Here, we applied the functions of central pattern generators, biological neural circuits for motor control, to the control technology of switching circuits for extremely power-saving terminal edge devices. By simply applying a binary waveform with an arbitrary temporal pattern to the transistor gate, low-power and real-time switching control can be achieved. This binary pattern generator consists of a specially designed spiking neuron circuit that generates spikes after a pre-programmed wait time in the six-order range, but consumes negligible power, with an experimental record of 1.2 pW per neuron. This control scheme has been successfully applied to voltage conversion circuits consuming only a few nanowatts, providing an ultra-low power technology for trillions of self-powered edge systems.

LRRTM3 regulates activity-dependent synchronization of synapse properties in topographically connected hippocampal neural circuits

Synaptic cell-adhesion molecules (CAMs) organize the architecture and properties of neural circuits. However, whether synaptic CAMs are involved in activity-dependent remodeling of specific neural circuits is incompletely understood. Leucine-rich repeat transmembrane protein 3 (LRRTM3) is required for the excitatory synapse development of hippocampal dentate gyrus (DG) granule neurons. Here, we report that Lrrtm3-deficient mice exhibit selective reductions in excitatory synapse density and synaptic strength in projections involving the medial entorhinal cortex (MEC) and DG granule neurons, accompanied by increased neurotransmitter release and decreased excitability of granule neurons. LRRTM3 deletion significantly reduced excitatory synaptic innervation of hippocampal mossy fibers (Mf) of DG granule neurons onto thorny excrescences in hippocampal CA3 neurons. Moreover, LRRTM3 loss in DG neurons significantly decreased mossy fiber long-term potentiation (Mf-LTP). Remarkably, silencing MEC-DG circuits protected against the decrease in the excitatory synaptic inputs onto DG and CA3 neurons, excitability of DG granule neurons, and Mf-LTP in Lrrtm3-deficient mice. These results suggest that LRRTM3 may be a critical factor in activity-dependent synchronization of the topography of MEC-DG-CA3 excitatory synaptic connections. Collectively, our data propose that LRRTM3 shapes the target-specific structural and functional properties of specific hippocampal circuits.

Reverse optogenetics of G protein signaling by zebrafish non-visual opsin Opn7b for synchronization of neuronal networks

Opn7b is a non-visual G protein-coupled receptor expressed in zebrafish. Here we find that Opn7b expressed in HEK cells constitutively activates the Gi/o pathway and illumination with blue/green light inactivates G protein-coupled inwardly rectifying potassium channels. This suggests that light acts as an inverse agonist for Opn7b and can be used as an optogenetic tool to inhibit neuronal networks in the dark and interrupt constitutive inhibition in the light. Consistent with this prediction, illumination of recombinant expressed Opn7b in cortical pyramidal cells results in increased neuronal activity. In awake mice, light stimulation of Opn7b expressed in pyramidal cells of somatosensory cortex reliably induces generalized epileptiform activity within a short (<10 s) delay after onset of stimulation. Our study demonstrates a reversed mechanism for G protein-coupled receptor control and Opn7b as a tool for controlling neural circuit properties.

Proper synaptic adhesion signaling in the control of neural circuit architecture and brain function.

Trans-synaptic cell-adhesion molecules are critical for governing various stages of synapse development and specifying neural circuit properties via the formation of multifarious signaling pathways. Recent studies have pinpointed the putative roles of trans-synaptic cell-adhesion molecules in mediating various cognitive functions. Here, we review the literature on the roles of a diverse group of central synaptic organizers, including neurexins (Nrxns), leukocyte common antigen-related receptor protein tyrosine phosphatases (LAR-RPTPs), and their associated binding proteins, in regulating properties of specific type of synapses and neural circuits. In addition, we highlight the findings that aberrant synaptic adhesion signaling leads to alterations in the structures, transmission, and plasticity of specific synapses across diverse brain areas. These results seem to suggest that proper trans-synaptic signaling pathways by Nrxns, LAR-RPTPs, and their interacting network is likely to constitute central molecular complexes that form the basis for cognitive functions, and that these complexes are heterogeneously and complexly disrupted in many neuropsychiatric and neurodevelopmental disorders.

Trans-synaptic interactions of ionotropic glutamate receptors.

Trans-synaptic interactions organize the multiple steps of synaptic development and are critical to generate fully functional neuronal circuits. While trans-synaptic interactions are primarily mediated by cell adhesion molecules (CAMs), some directly involve ionotropic glutamate receptors (iGluRs). Here, we review the expanding extracellular and trans-synaptic proteome of iGluRs. We discuss the role of these molecular networks in specifying the formation of excitatory and inhibitory circuits and in the input-specific recruitment of iGluRs at synapses in various cell types and brain regions. We also shed light on human-specific mutations affecting iGluR-mediated trans-synaptic interactions that may provide unique features to the human brain and contribute to its susceptibility to neurodevelopmental disorders. Together, these data support a view in which iGluR function goes far beyond fast excitatory synaptic transmission by shaping the wiring and the functional properties of neural circuits.

Role of synaptic nonlinearity in persistent firing rate shifts caused by external periodic forcing

Information storage and processing in the brain largely relies on the neural population coding principle. In this framework, information is reflected in the population firing rate that reflects asynchronous irregular spiking of its constituent neurons. Periodic modulations of neural activity can lead to neural activity oscillations. Data indicate that such oscillations are ubiquitous in brain activity and are modulated, in frequency and amplitude, in a functionally meaningful manner. The relationship between oscillations and the population rate code remains an open issue. While ample works show how changes in the mean firing rate may alter neural oscillations, the reverse connection is unclear. One notable possibility is that oscillatory activity impinging on a neural population modulates its mean firing rate, thereby impacting information processing. We suggest that such modulation requires nonlinearities and propose nonlinear excitatory coupling via slow N-methyl-D-aspartate (NMDA) receptors as the prevalent mechanism. The aim of our paper is to theoretically explore to what extent the NMDA-related mechanism could account for oscillation-induced mean firing rate changes. We consider a mean-field model of a neural circuit containing an excitatory and an inhibitory population with linear transfer functions. Along with NMDA excitation, the model included fast recurrent excitatory and inhibitory connectivity. To explicitly study the effects of impinging oscillation on the rate dynamics, we subjected the circuit to a sinusoidal input signal imitating an input from distant brain regions or from a larger network into which the circuit is embedded. Using time-scale separation and time-averaging techniques, we developed a geometric method to determine the oscillation-induced mean firing rate shifts and validated it by numeric simulations of the model. Our results indicate that a large-amplitude stable firing rate shift requires nonlinear NMDA synapses on both the excitatory and the inhibitory populations. Our results delineate specific neural synaptic properties that enable neural oscillations to act as flexible modulators of the population rate code.

Two-Color Volumetric Imaging of Neuronal Activity of Cortical Columns

SUMMARYTo capture the emergent properties of neural circuits, high-speed volumetric imaging of neural activity at cellular resolution is needed. Here, we introduce wavelength multiplexing to perform fast volumetric two-photon imaging of cortical columns (>2,000 neurons in 10 planes at 10 vol/s), using two different calcium indicators, an electrically tunable lens and a spatial light modulator. We image the activity of neuronal populations from layers 2/3 to 5 of primary visual cortex from awake mice, finding a lack of columnar structures in orientation responses and revealing correlations between layers which differ from trial to trial. We also simultaneously image functional correlations between presynaptic layer 1 axons and postsynaptic layer 2/3 neurons. Wavelength multiplexing enhances high-speed volumetric microscopy and can be combined with other optical multiplexing methods to easily boost imaging throughput.

Plasticity of paternity: Effects of fatherhood on synaptic, intrinsic and morphological characteristics of neurons in the medial preoptic area of male California mice

Parental care by fathers enhances offspring survival and development in numerous species. In the biparental California mouse, Peromyscus californicus, behavioral plasticity is seen during the transition into fatherhood: adult virgin males often exhibit aggressive or indifferent responses to pups, whereas fathers engage in extensive paternal care. In this species and other biparental mammals, the onset of paternal behavior is associated with increased neural responsiveness to pups in specific brain regions, including the medial preoptic area of the hypothalamus (MPOA), a region strongly implicated in both maternal and paternal behavior. To assess possible changes in neural circuit properties underlying this increased excitability, we evaluated synaptic, intrinsic, and morphological properties of MPOA neurons in adult male California mice that were either virgins or first-time fathers. We used standard whole-cell recordings in a novel in vitro slice preparation. Excitatory and inhibitory post-synaptic currents from MPOA neurons were recorded in response to local electrical stimulation, and input/output curves were constructed for each. Responses to trains of stimuli were also examined. We quantified intrinsic excitability by measuring voltage changes in response to square-pulse injections of both depolarizing and hyperpolarizing current. Biocytin was injected into neurons during recording, and their morphology was analyzed. Most parameters did not differ significantly between virgins and fathers. However, we document a decrease in synaptic inhibition in fathers. These findings suggest that the onset of paternal behavior in California mouse fathers may be associated with limited electrophysiological plasticity within the MPOA.

Dopaminergic Modulation of Synaptic Plasticity, Its Role in Neuropsychiatric Disorders, and Its Computational Modeling.

Neuromodulators modify intrinsic characteristics of the nervous system in order to reconfigure the functional properties of neural circuits. This reconfiguration is crucial for the flexibility of the nervous system to respond on an input-modulated basis. Such a functional rearrangement is realized by modification of intrinsic properties of the neural circuits including synaptic interactions. Dopamine is an important neuromodulator involved in motivation and stimulus-reward learning process, and adjusts synaptic dynamics in multiple time scales through different pathways. The modification of synaptic plasticity by dopamine underlies the change in synaptic transmission and integration mechanisms, which affects intrinsic properties of the neural system including membrane excitability, probability of neurotransmitters release, receptors’ response to neurotransmitters, protein trafficking, and gene transcription. Dopamine also plays a central role in behavioral control, whereas its malfunction can cause cognitive disorders. Impaired dopamine signaling is implicated in several neuropsychiatric disorders such as Parkinson’s disease, drug addiction, schizophrenia, attention-deficit/hyperactivity disorder, obsessive-compulsive disorder and Tourette’s syndrome. Therefore, dopamine plays a crucial role in the nervous system, where its proper modulation of neural circuits may enhance plasticity-related procedures, but disturbances in dopamine signaling might be involved in numerous neuropsychiatric disorders. In recent years, several computational models are proposed to formulate the involvement of dopamine in synaptic plasticity or neuropsychiatric disorders and address their connection based on the experimental findings.

Inferring neural circuit properties from optogenetic stimulation.

Optogenetics has become an important tool for perturbing neural circuitry with unparalleled temporal precision and cell-type specificity. However, direct activation of a specific subpopulation of neurons can rapidly modulate the activity of other neurons within the network and may lead to unexpected and complex downstream effects. Here, we have developed a biologically-constrained computational model that exploits these non-intuitive network responses in order to gain insight into underlying properties of the network. We apply this model to data recorded during optogenetic stimulation in the primary visual cortex of the alert macaque. In these experiments, we found that optogenetic depolarization of excitatory neurons often suppressed neuronal responses, consistent with engagement of normalization circuitry. Our model suggests that the suppression seen in these responses may be mediated by slow excitatory and inhibitory conductance channels. Furthermore, the model predicted that the response of the network to optogenetic perturbation depends critically on the relationship between inherent temporal properties of the network and the temporal properties of the opsin. Consistent with model predictions, stimulation of the C1V1TT opsin, an opsin with a fast time constant (tau = 45 ms), caused faster and stronger suppressive effects after laser offset, as compared to stimulation of the slower C1V1T opsin (tau = 60ms). This work illustrates how the non-intuitive network responses that result from optogenetic stimulation can be exploited to gain insight regarding network properties that underlie fundamental neuronal computations, such as normalization. This novel hybrid opto-theoretical approach can thus enhance the power of optogenetics to dissect complex neural circuits.

Distinct Co-Modulation Rules of Synapses and Voltage-Gated Currents Coordinate Interactions of Multiple Neuromodulators.

Multiple neuromodulators act in concert to shape the properties of neural circuits. Different neuromodulators usually activate distinct receptors but can have overlapping targets. Therefore, circuit output depends on neuromodulator interactions at shared targets, a poorly understood process. We explored quantitative rules of co-modulation of two principal targets of neuromodulation: synapses and voltage-gated ionic currents. In the stomatogastric ganglion of the male crab Cancer borealis, the neuropeptides proctolin (Proc) and the crustacean cardioactive peptide (CCAP) modulate synapses of the pyloric circuit and activate a voltage-gated current (IMI) in multiple neurons. We examined the validity of a simple dose-dependent quantitative rule, that co-modulation by Proc and CCAP is predicted by the linear sum of the individual effects of each modulator up to saturation. We found that this rule is valid for co-modulation of synapses, but not for the activation of IMI, in which co-modulation was sublinear. The predictions for the co-modulation of IMI activation were greatly improved if we assumed that the intracellular pathways activated by two peptide receptors inhibit one another. These findings suggest that the pathways activated by two neuromodulators could have distinct interactions, leading to distinct co-modulation rules for different targets even in the same neuron. Given the evolutionary conservation of neuromodulator receptors and signaling pathways, such distinct rules for co-modulation of different targets are likely to be common across neuronal circuits.SIGNIFICANCE STATEMENT We examine the quantitative rules of co-modulation at multiple shared targets, the first such characterization to our knowledge. Our results show that dose-dependent co-modulation of distinct targets in the same cells by the same two neuromodulators follows different rules: co-modulation of synaptic currents is linearly additive up to saturation, whereas co-modulation of the voltage-gated ionic current targeted in a single neuron is nonlinear, a mechanism that is likely generalizable. Given that all neural systems are multiply modulated and neuromodulators often act on shared targets, these findings and the methodology could guide studies to examine dynamic actions of neuromodulators at the biophysical and systems level in sensory and motor functions, sleep/wake regulation, and cognition.

Ion channels in EEG: isolating channel dysfunction in NMDA receptor antibody encephalitis.

See Roberts and Breakspear (doi:10.1093/brain/awy136) for a scientific commentary on this article.Neurological and psychiatric practice frequently lack diagnostic probes that can assess mechanisms of neuronal communication non-invasively in humans. In N-methyl-d-aspartate (NMDA) receptor antibody encephalitis, functional molecular assays are particularly important given the presence of NMDA antibodies in healthy populations, the multifarious symptomology and the lack of radiological signs. Recent advances in biophysical modelling techniques suggest that inferring cellular-level properties of neural circuits from macroscopic measures of brain activity is possible. Here, we estimated receptor function from EEG in patients with NMDA receptor antibody encephalitis (n = 29) as well as from encephalopathic and neurological patient controls (n = 36). We show that the autoimmune patients exhibit distinct fronto-parietal network changes from which ion channel estimates can be obtained using a microcircuit model. Specifically, a dynamic causal model of EEG data applied to spontaneous brain responses identifies a selective deficit in signalling at NMDA receptors in patients with NMDA receptor antibody encephalitis but not at other ionotropic receptors. Moreover, though these changes are observed across brain regions, these effects predominate at the NMDA receptors of excitatory neurons rather than at inhibitory interneurons. Given that EEG is a ubiquitously available clinical method, our findings suggest a unique re-purposing of EEG data as an assay of brain network dysfunction at the molecular level.

Developmental excitatory-to-inhibitory GABA polarity switch is delayed in Ts65Dn mice, a genetic model of Down syndrome

Down syndrome (DS) is the most frequent genetic cause of developmental abnormalities leading to intellectual disability. One notable phenomenon affecting the formation of nascent neural circuits during late developmental periods is developmental switch of GABA action from depolarizing to hyperpolarizing mode. We examined properties of this switch in DS using primary cultures and acute hippocampal slices from Ts65Dn mice, a genetic model of DS. Cultures of DIV3–DIV13 Ts65Dn and control normosomic (2 N) neurons were loaded with FURA-2 AM, and GABA action was assessed using local applications. In 2 N cultures, the number of GABA-activated cells dropped from ~100% to 20% between postnatal days 3–13 (P3–P13) reflecting the switch in GABA action polarity. In Ts65Dn cultures, the timing of this switch was delayed by 2–3 days. Next, microelectrode recordings of multi-unit activity (MUA) were performed in CA3 slices during bath application of the GABAA agonist isoguvacine. MUA frequency was increased in P8–P12 and reduced in P14–P22 slices reflecting the switch of GABA action from excitatory to inhibitory mode. The timing of this switch was delayed in Ts65Dn by approximately 2 days. Finally, frequency of giant depolarizing potentials (GDPs), a form of primordial neural activity, was significantly increased in slices from Ts65Dn pups at P12 and P14. These experimental evidences show that GABA action polarity switch is delayed in Ts65Dn model of DS, and that these changes lead to a delay in maturation of nascent neural circuits. These alterations may affect properties of neural circuits in adult animals and, therefore, represent a prospective target for pharmacotherapy of cognitive impairment in DS.

A network model of behavioural performance in a rule learning task.

Humans demonstrate differences in performance on cognitive rule learning tasks which could involve differences in properties of neural circuits. An example model is presented to show how gating of the spread of neural activity could underlie rule learning and the generalization of rules to previously unseen stimuli. This model uses the activity of gating units to regulate the pattern of connectivity between neurons responding to sensory input and subsequent gating units or output units. This model allows analysis of network parameters that could contribute to differences in cognitive rule learning. These network parameters include differences in the parameters of synaptic modification and presynaptic inhibition of synaptic transmission that could be regulated by neuromodulatory influences on neural circuits. Neuromodulatory receptors play an important role in cognitive function, as demonstrated by the fact that drugs that block cholinergic muscarinic receptors can cause cognitive impairments. In discussions of the links between neuromodulatory systems and biologically based traits, the issue of mechanisms through which these linkages are realized is often missing. This model demonstrates potential roles of neural circuit parameters regulated by acetylcholine in learning context-dependent rules, and demonstrates the potential contribution of variation in neural circuit properties and neuromodulatory function to individual differences in cognitive function.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'.

Neural Circuitry for Target Selection and Action Selection in Animal Behavior.

Animal behaviorists have long strived for a comprehensive understanding of the proximate and ultimate causes of complex behavior, and we propose that recent advances in neurobiology can help reshape or clarify this behavior-oriented understanding. We begin with an overview of current views of neural circuit mechanisms that mediate target selection and action selection. In target selection, different stimuli compete for priority in sensory-motor processing. Action selection is the process by which multiple possible motor actions compete for priority in a manner which balances the needs of the animal with opportunities or threats in the environment. We next discuss spatial and temporal aspects of target and action selection, highlighting how neurophysiological responses to complex displays depend on spatial and temporal components of multisensory stimuli. We use two examples-(1) spatial attention as an example of target selection in the vertebrate midbrain and (2) goal-directed locomotion as an example of action selection in the insect central complex-to further clarify neural circuit dynamics as they relate to target and action selection, and their interaction. We suggest that a deeper understanding of neural circuit properties will introduce new hypotheses into behavioral studies, especially those aimed at understanding the evolution of complex displays based on receiver sensory biases. Additionally, knowledge of neural circuit properties can elucidate ways in which current context and previous experience can together modify neural circuit dynamics to produce complex context-dependent behavioral responses that often characterize animal behavior.

Imaging Voltage in Genetically Defined Neuronal Subpopulations with a Cre Recombinase-Targeted Hybrid Voltage Sensor.

Genetically encoded voltage indicators create an opportunity to monitor electrical activity in defined sets of neurons as they participate in the complex patterns of coordinated electrical activity that underlie nervous system function. Taking full advantage of genetically encoded voltage indicators requires a generalized strategy for targeting the probe to genetically defined populations of cells. To this end, we have generated a mouse line with an optimized hybrid voltage sensor (hVOS) probe within a locus designed for efficient Cre recombinase-dependent expression. Crossing this mouse with Cre drivers generated double transgenics expressing hVOS probe in GABAergic, parvalbumin, and calretinin interneurons, as well as hilar mossy cells, new adult-born neurons, and recently active neurons. In each case, imaging in brain slices from male or female animals revealed electrically evoked optical signals from multiple individual neurons in single trials. These imaging experiments revealed action potentials, dynamic aspects of dendritic integration, and trial-to-trial fluctuations in response latency. The rapid time response of hVOS imaging revealed action potentials with high temporal fidelity, and enabled accurate measurements of spike half-widths characteristic of each cell type. Simultaneous recording of rapid voltage changes in multiple neurons with a common genetic signature offers a powerful approach to the study of neural circuit function and the investigation of how neural networks encode, process, and store information.SIGNIFICANCE STATEMENT Genetically encoded voltage indicators hold great promise in the study of neural circuitry, but realizing their full potential depends on targeting the sensor to distinct cell types. Here we present a new mouse line that expresses a hybrid optical voltage sensor under the control of Cre recombinase. Crossing this line with Cre drivers generated double-transgenic mice, which express this sensor in targeted cell types. In brain slices from these animals, single-trial hybrid optical voltage sensor recordings revealed voltage changes with submillisecond resolution in multiple neurons simultaneously. This imaging tool will allow for the study of the emergent properties of neural circuits and permit experimental tests of the roles of specific types of neurons in complex circuit activity.

Non-overlapping Neural Networks in Hydra vulgaris

To understand the emergent properties of neural circuits, it would be ideal to record the activity of every neuron in a behaving animal and decode how it relates to behavior. We have achieved this with the cnidarian Hydra vulgaris, using calcium imaging of genetically engineered animals to measure the activity of essentially all of its neurons. Although the nervous system of Hydra is traditionally described as a simple nerve net, we surprisingly find instead a series of functional networks that are anatomically non-overlapping and are associated with specific behaviors. Three major functional networks extend through the entire animal and are activated selectively during longitudinal contractions, elongations in response to light, and radial contractions, whereas an additional network is located near the hypostome and is active during nodding. These results demonstrate the functional sophistication of apparently simple nerve nets, and the potential of Hydra and other basal metazoans as a model system for neural circuit studies.