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The neocortex is disproportionately expanded in human compared with mouse1,2, both in its total volume relative to subcortical structures and in the proportion occupied by supragranular layers composed of neurons that selectively make connections within the neocortex and with other telencephalic structures. Single-cell transcriptomic analyses of human and mouse neocortex show an increased diversity of glutamatergic neuron types in supragranular layers in human neocortex and pronounced gradients as a function of cortical depth3. Here, to probe the functional and anatomical correlates of this transcriptomic diversity, we developed a robust platform combining patch clamp recording, biocytin staining and single-cell RNA-sequencing (Patch-seq) to examine neurosurgically resected human tissues. We demonstrate a strong correspondence between morphological, physiological and transcriptomic phenotypes of five human glutamatergic supragranular neuron types. These were enriched in but not restricted to layers, with one type varying continuously in all phenotypes across layers 2 and 3. The deep portion of layer 3 contained highly distinctive cell types, two of which express a neurofilament protein that labels long-range projection neurons in primates that are selectively depleted in Alzheimer’s disease4,5. Together, these results demonstrate the explanatory power of transcriptomic cell-type classification, provide a structural underpinning for increased complexity of cortical function in humans, and implicate discrete transcriptomic neuron types as selectively vulnerable in disease., Combined patch clamp recording, biocytin staining and single-cell RNA-sequencing of human neurocortical neurons shows an expansion of glutamatergic neuron types relative to mouse that characterizes the greater complexity of the human neocortex.

The Patch-seq approach is a powerful variation of the patch-clamp technique that allows for the combined electrophysiological, morphological, and transcriptomic characterization of individual neurons. To generate Patch-seq datasets at scale, we identified and refined key factors that contribute to the efficient collection of high-quality data. We developed patch-clamp electrophysiology software with analysis functions specifically designed to automate acquisition with online quality control. We recognized the importance of extracting the nucleus for transcriptomic success and maximizing membrane integrity during nucleus extraction for morphology success. The protocol is generalizable to different species and brain regions, as demonstrated by capturing multimodal data from human and macaque brain slices. The protocol, analysis and acquisition software are compiled at https://githubcom/AllenInstitute/patchseqtools. This resource can be used by individual labs to generate data across diverse mammalian species and that is compatible with large publicly available Patch-seq datasets.

Understanding the diversity of cell types in the brain has been an enduring challenge and requires detailed characterization of individual neurons in multiple dimensions. To systematically profile morpho-electric properties of mammalian neurons, we established a single-cell characterization pipeline using standardized patch-clamp recordings in brain slices and biocytin-based neuronal reconstructions. We built a publicly accessible online database, the Allen Cell Types Database, to display these datasets. Intrinsic physiological properties were measured from 1,938 neurons from the adult laboratory mouse visual cortex, morphological properties were measured from 461 reconstructed neurons, and 452 neurons had both measurements available. Quantitative features were used to classify neurons into distinct types using unsupervised methods. We established a taxonomy of morphologically and electrophysiologically defined cell types for this region of the cortex, with 17 electrophysiological types, 38 morphological types and 46 morpho-electric types. There was good correspondence with previously defined transcriptomic cell types and subclasses using the same transgenic mouse lines.

To elucidate cortical microcircuit structure and synaptic properties we present a unique, extensive, and public synaptic physiology dataset and analysis platform. Through its application, we reveal principles that relate cell type to synapse properties and intralaminar circuit organization in the mouse and human cortex. The dynamics of excitatory synapses align with the postsynaptic cell subclass, whereas inhibitory synapse dynamics partly align with presynaptic cell subclass but with considerable overlap. Despite these associations, synaptic properties are heterogeneous in most subclass to subclass connections. The two main axes of heterogeneity are strength and variability. Cell subclasses divide along the variability axis, while the strength axis accounts for significant heterogeneity within the subclass. In human cortex, excitatory to excitatory synapse dynamics are distinct from those in mouse and short-term plasticity varies with depth across layers 2 and 3. With a novel connectivity analysis that enables fair comparisons between circuit elements, we find that intralaminar connection probability among cell subclasses exhibits a strong layer dependence.These and other findings combined with the analysis platform create new opportunities for the neuroscience community to advance our understanding of cortical microcircuits.

Fluorescent calcium indicators are often used to investigate neural dynamics, but the relationship between fluorescence and action potentials (APs) remains unclear. Most APs can be detected when the soma almost fills the microscope’s field of view, but calcium indicators are used to image populations of neurons, necessitating a large field of view, generating fewer photons per neuron, and compromising AP detection. Here, we characterized the AP-fluorescence transfer function in vivo for 48 layer 2/3 pyramidal neurons in primary visual cortex, with simultaneous calcium imaging and cell-attached recordings from transgenic mice expressing GCaMP6s or GCaMP6f. While most APs were detected under optimal conditions, under conditions typical of population imaging studies, only a minority of 1 AP and 2 AP events were detected (often, eLife digest Neurons, the cells that make up the nervous system, transmit information using electrical signals known as action potentials or spikes. Studying the spiking patterns of neurons in the brain is essential to understand perception, memory, thought, and behaviour. One way to do that is by recording electrical activity with microelectrodes. Another way to study neuronal activity is by using molecules that change how they interact with light when calcium binds to them, since changes in calcium concentration can be indicative of neuronal spiking. That change can be observed with specialized microscopes know as two-photon fluorescence microscopes. Using calcium indicators, it is possible to simultaneously record hundreds or even thousands of neurons. However, calcium fluorescence and spikes do not translate one-to-one. In order to interpret fluorescence data, it is important to understand the relationship between the fluorescence signals and the spikes associated with individual neurons. The only way to directly measure this relationship is by using calcium imaging and electrical recording simultaneously to record activity from the same neuron. However, this is extremely challenging experimentally, so this type of data is rare. To shed some light on this, Huang, Ledochowitsch et al. used mice that had been genetically modified to produce a calcium indicator in neurons of the visual cortex and simultaneously obtained both fluorescence measurements and electrical recordings from these neurons. These experiments revealed that, while the majority of time periods containing multi-spike neural activity could be identified using calcium imaging microscopy, on average, less than 10% of isolated single spikes were detectable. This is an important caveat that researchers need to take into consideration when interpreting calcium imaging results. These findings are intended to serve as a guide for interpreting calcium imaging studies that look at neurons in the mammalian brain at the population level. In addition, the data provided will be useful as a reference for the development of activity sensors, and to benchmark and improve computational approaches for detecting and predicting spikes.

Abundant evidence supports the presence of at least three distinct types of thalamocortical (TC) neurons in the primate dorsal lateral geniculate nucleus (dLGN) of the thalamus, the brain region that conveys visual information from the retina to the primary visual cortex (V1). Different types of TC neurons in mice, humans, and macaques have distinct morphologies, distinct connectivity patterns, and convey different aspects of visual information to the cortex. To investigate the molecular underpinnings of these cell types, and how these relate to differences in dLGN between human, macaque, and mice, we profiled gene expression in single nuclei and cells using RNA-sequencing. These efforts identified four distinct types of TC neurons in the primate dLGN: magnocellular (M) neurons, parvocellular (P) neurons, and two types of koniocellular (K) neurons. Despite extensively documented morphological and physiological differences between M and P neurons, we identified few genes with significant differential expression between transcriptomic cell types corresponding to these two neuronal populations. Likewise, the dominant feature of TC neurons of the adult mouse dLGN is high transcriptomic similarity, with an axis of heterogeneity that aligns with core vs. shell portions of mouse dLGN. Together, these data show that transcriptomic differences between principal cell types in the mature mammalian dLGN are subtle relative to the observed differences in morphology and cortical projection targets. Finally, alignment of transcriptome profiles across species highlights expanded diversity of GABAergic neurons in primate versus mouse dLGN and homologous types of TC neurons in primates that are distinct from TC neurons in mouse.

The Patch-seq approach is a powerful variation of the standard patch clamp technique that allows for the combined electrophysiological, morphological, and transcriptomic characterization of individual neurons. To generate Patch-seq datasets at a scale and quality that can be integrated with high-throughput dissociated cell transcriptomic data, we have optimized the technique by identifying and refining key factors that contribute to the efficient collection of high-quality data. To rapidly generate high-quality electrophysiology data, we developed patch clamp electrophysiology software with analysis functions specifically designed to automate acquisition with online quality control. We recognized a substantial improvement in transcriptomic data quality when the nucleus was extracted following the recording. For morphology success, the importance of maximizing the neuron’s membrane integrity during the extraction of the nucleus was much more critical to success than varying the duration of the electrophysiology recording. We compiled the lab protocol with the analysis and acquisition software athttps://github.com/AllenInstitute/patchseqtools. This resource can be used by individual labs to generate Patch-seq data across diverse mammalian species and that is compatible with recent large-scale publicly available Allen Institute Patch-seq datasets.

The neocortex is disproportionately expanded in human compared to mouse, both in its total volume relative to subcortical structures and in the proportion occupied by supragranular layers that selectively make connections within the cortex and other telencephalic structures. Single-cell transcriptomic analyses of human and mouse cortex show an increased diversity of glutamatergic neuron types in supragranular cortex in human and pronounced gradients as a function of cortical depth. To probe the functional and anatomical correlates of this transcriptomic diversity, we describe a robust Patch-seq platform using neurosurgically-resected human tissues. We characterize the morphological and physiological properties of five transcriptomically defined human glutamatergic supragranular neuron types. Three of these types have properties that are specialized compared to the more homogeneous properties of transcriptomically defined homologous mouse neuron types. The two remaining supragranular neuron types, located exclusively in deep layer 3, do not have clear mouse homologues in supragranular cortex but are transcriptionally most similar to deep layer mouse intratelencephalic-projecting neuron types. Furthermore, we reveal the transcriptomic types in deep layer 3 that express high levels of non-phosphorylated heavy chain neurofilament protein that label long-range neurons known to be selectively depleted in Alzheimer’s disease. Together, these results demonstrate the power of transcriptomic cell type classification, provide a mechanistic underpinning for increased complexity of cortical function in human cortical evolution, and implicate discrete transcriptomic cell types as selectively vulnerable in disease.

Neurons are frequently classified into distinct groups or cell types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intrinsic physiological properties of over 3,700 GABAergic mouse visual cortical neurons and reconstructed the local morphologies of 350 of those neurons. We found that most transcriptomic types (t-types) occupy specific laminar positions within mouse visual cortex, and many of those t-types exhibit consistent electrophysiological and morphological features. We observed that these properties could vary continuously between t-types, which limited the ability to predict specific t-types from other data modalities. Despite that, the data support the presence of at least 20 interneuron met-types that have congruent morphological, electrophysiological, and transcriptomic properties.HighlightsPatch-seq data obtained from >3,700 GABAergic cortical interneuronsComprehensive characterization of morpho-electric features of transcriptomic types20 interneuron met-types that have congruent properties across data modalitiesDifferent Sst met-types preferentially innervate different cortical layers

Neurons are frequently classified into distinct groups or cell types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intrinsic physiological properties of over 3,700 GABAergic mouse visual cortical neurons and reconstructed the local morphologies of 350 of those neurons. We found that most transcriptomic types (t-types) occupy specific laminar positions within mouse visual cortex, and many of those t-types exhibit consistent electrophysiological and morphological features. We observed that these properties could vary continuously between t- types, which limited the ability to predict specific t-types from other data modalities. Despite that, the data support the presence of at least 20 interneuron met-types that have congruent morphological, electrophysiological, and transcriptomic properties.

The most common synaptic connections between neurons in different cortical layers form the basis of the canonical cortical microcircuit. Understanding of cortical function will require further development and application of methods to efficiently characterize synaptic connections within and outside of the canonical pathway. Accordingly, we measured synaptic inputs onto superficial excitatory neurons in response to sequential two-photon optogenetic stimulation of neurons in deeper layers. Layer 4 excitatory neurons and somatostatin-neurons within layer 2/3 represented the most common sources of input. Although connections from excitatory and somatostatin-neurons in layer 5 were less common, the amplitudes of synaptic responses were equally strong. We examined synaptic strength across all connections, as well as the relationships between the strength of connections diverging from a common presynaptic neuron or converging to a single target. While the overall distribution indicates synaptic weight is concentrated to a few connections, strong excitatory connections are distributed across cells.

Defining a complete set of cell types within the cortex requires reconciling disparate results achieved through diverging methodologies. To address this correspondence problem, multiple methodologies must be applied to the same cells across multiple single-cell experiments. Here we present a new approach applying spatial transcriptomics using multiplexed fluorescencein situhybridization, (mFISH) to brain tissue previously interrogated through two photon optogenetic mapping of synaptic connectivity. This approach can resolve the anatomical, transcriptomic, connectomic, electrophysiological, and morphological characteristics of single cells within the mouse cortex.

Neurons respond to specific features of sensory stimuli. In the visual system, for example, some neurons respond to motion of small but not large objects, whereas other neurons prefer motion of the entire visual field. Separate neurons respond equally to local and global motion but selectively to additional features of visual stimuli. How and where does response selectivity emerge? Here, we show that wide-field (WF) cells in retino-recipient layers of the mouse superior colliculus (SC) respond selectively to small moving objects. Moreover, we identify two mechanisms that contribute to this selectivity. First, we show that input restricted to a small portion of the broad dendritic arbor of WF cells is sufficient to trigger dendritic spikes that reliably propagate to the soma/axon. In vivo whole-cell recordings reveal that nearly every action potential evoked by visual stimuli has characteristics of spikes initiated in dendrites. Second, inhibitory input from a different class of SC neuron, horizontal cells, constrains the range of stimuli to which WF cells respond. Horizontal cells respond preferentially to the sudden appearance or rapid movement of large stimuli. Optogenetic reduction of their activity reduces movement selectivity and broadens size tuning in WF cells by increasing the relative strength of responses to stimuli that appear suddenly or cover a large region of space. Therefore, strongly propagating dendritic spikes enable small stimuli to drive spike output in WF cells and local inhibition helps restrict responses to stimuli that are both small and moving. SIGNIFICANCE STATEMENT How do neurons respond selectively to some sensory stimuli but not others? In the visual system, a particularly relevant stimulus feature is object motion, which often reveals other animals. Here, we show how specific cells in the superior colliculus, one synapse downstream of the retina, respond selectively to object motion. These wide-field (WF) cells respond strongly to small objects that move slowly anywhere through a large region of space, but not to stationary objects or full-field motion. Action potential initiation in dendrites enables small stimuli to trigger visual responses and inhibitory input from cells that prefer large, suddenly appearing, or quickly moving stimuli restricts responses of WF cells to objects that are small and moving.

Our results suggest that the mouse superior colliculus (SC) has access to input from most of the retinal ganglion cells (RGCs) that innervate the dorsal lateral geniculate nucleus (dLGN). By comparison, a number of RGC types appear to innervate the SC but not the dLGN; these RGCs generally exhibit more transient responses and respond best to small stimuli., The mammalian retina conveys the vast majority of information about visual stimuli to two brain regions: the dorsal lateral geniculate nucleus (dLGN) and the superior colliculus (SC). The degree to which retinal ganglion cells (RGCs) send similar or distinct information to the two areas remains unclear despite the important constraints that different patterns of RGC input place on downstream visual processing. To resolve this ambiguity, we injected a glycoprotein-deficient rabies virus coding for the expression of a fluorescent protein into the dLGN or SC; rabies virus labeled a smaller fraction of RGCs than lipophilic dyes such as DiI but, crucially, did not label RGC axons of passage. Approximately 80% of the RGCs infected by rabies virus injected into the dLGN were colabeled with DiI injected into the SC, suggesting that many dLGN-projecting RGCs also project to the SC. However, functional characterization of RGCs revealed that the SC receives input from several classes of RGCs that largely avoid the dLGN, in particular RGCs in which 1) sustained changes in light intensity elicit transient changes in firing rate and/or 2) a small range of stimulus sizes or temporal fluctuations in light intensity elicit robust activity. Taken together, our results illustrate several unexpected asymmetries in the information that the mouse retina conveys to two major downstream targets and suggest that differences in the output of dLGN and SC neurons reflect, at least in part, differences in the functional properties of RGCs that innervate the SC but not the dLGN.

Neurons are frequently classified into distinct types on the basis of structural, physiological, or genetic attributes. To better constrain the definition of neuronal cell types, we characterized the transcriptomes and intrinsic physiological properties of over 4,200 mouse visual cortical GABAergic interneurons and reconstructed the local morphologies of 517 of those neurons. We find that most transcriptomic types (t-types) occupy specific laminar positions within visual cortex, and, for most types, the cells mapping to a t-type exhibit consistent electrophysiological and morphological properties. These properties display both discrete and continuous variation among t-types. Through multimodal integrated analysis, we define 28 met-types that have congruent morphological, electrophysiological, and transcriptomic properties and robust mutual predictability. We identify layer-specific axon innervation pattern as a defining feature distinguishing different met-types. These met-types represent a unified definition of cortical GABAergic interneuron types, providing a systematic framework to capture existing knowledge and bridge future analyses across different modalities.

Understanding the diversity of cell types in the brain has been an enduring challenge and requires detailed characterization of individual neurons in multiple dimensions. To profile morpho-electric properties of mammalian neurons systematically, we established a single cell characterization pipeline using standardized patch clamp recordings in brain slices and biocytin-based neuronal reconstructions. We built a publicly-accessible online database, the Allen Cell Types Database, to display these data sets. Intrinsic physiological and morphological properties were measured from over 1,800 neurons from the adult laboratory mouse visual cortex. Quantitative features were used to classify neurons into distinct types using unsupervised methods. We establish a taxonomy of morphologically- and electrophysiologically-defined cell types for this region of cortex with 17 e-types and 35 m-types, as well as an initial correspondence with previously-defined transcriptomic cell types using the same transgenic mouse lines.

The outer sheet of brain tissue, the neocortex, is composed of circuits formed from trillions of connections among billions of neurons, of which there are about one hundred different neuron types. The scale and complexity of cortical circuitry pose experimental challenges, leading to an incomplete understanding of how cortical cell types are connected and the computations that take place at the connections. About half of the cell types in the brain are excitatory, which means they can activate other cells. The cortex consists of several distinct layers of cells, within which excitatory cells cooperate to process the signals they receive from other cortical layers and brain areas. Using recordings of electrical activity arising from the connections between pairs of excitatory neurons, Seeman, Campagnola et al. measured the likelihood and strength of connectivity among related groups of excitatory cell types in slices of cortex taken from human and mouse brains. The initial results confirm previous findings that individual layers of human cortex can have more and stronger excitatory connections than the same layers of mouse cortex. In most layers of mouse cortex, repeatedly activating the excitatory cells leads to progressively weaker responses. However, in the upper layers of mouse cortex, the opposite effect is sometimes seen: more excitatory activity causes the connections to generate stronger responses. By feeding these data into a computer model, Seeman, Campagnola et al. described and compared the activity of the groups of related excitatory cell types. These results are the first of a new, large-scale project where findings can be integrated across experiments to gain a more detailed picture of cortical circuitry and computation. Neuroscientists will be able to use the results to build advanced computer models of cortical circuits. Such models will, for example, generate predictions for how the attributes of excitatory connectivity revealed by Seeman, Campagnola et al. influence how information is processed in the cortex. In so doing, the models will add to our understanding of how the human brain works both in health and in disease.

Summary Higher-order thalamic nuclei, such as the visual pulvinar, play essential roles in cortical function by connecting functionally related cortical and subcortical brain regions. A coherent framework describing pulvinar function remains elusive because of its anatomical complexity and involvement in diverse cognitive processes. We combined large-scale anatomical circuit mapping with high-density electrophysiological recordings to dissect a homolog of the pulvinar in mice, the lateral posterior thalamic nucleus (LP). We define three broad LP subregions based on correspondence between connectivity and functional properties. These subregions form corticothalamic loops biased toward ventral or dorsal stream cortical areas and contain separate representations of visual space. Silencing the visual cortex or superior colliculus revealed that they drive visual tuning properties in separate LP subregions. Thus, by specifying the driving input sources, functional properties, and downstream targets of LP circuits, our data provide a roadmap for understanding the mechanisms of higher-order thalamic function in vision.

Modern genetic approaches are powerful in providing access to diverse cell types in the brain and facilitating the study of their function. Here, we report a large set of driver and reporter transgenic mouse lines, including 23 new driver lines targeting a variety of cortical and subcortical cell populations and 26 new reporter lines expressing an array of molecular tools. In particular, we describe the TIGRE2.0 transgenic platform and introduce Cre-dependent reporter lines that enable optical physiology, optogenetics, and sparse labeling of genetically defined cell populations. TIGRE2.0 reporters broke the barrier in transgene expression level of single-copy targeted-insertion transgenesis in a wide range of neuronal types, along with additional advantage of a simplified breeding strategy compared to our first-generation TIGRE lines. These novel transgenic lines greatly expand the repertoire of high-precision genetic tools available to effectively identify, monitor, and manipulate distinct cell types in the mouse brain.

During night (i.e., scotopic) vision in mammals, rod photoreceptor output is conveyed to ganglion cells (GCs), the output cells of the retina, by a specialized neural circuit comprising rod bipolar (RB) and AII amacrine cells. Here, we examined how intrinsic postsynaptic conductances in AIIs contribute to transmission of rod-derived signals. Using paired recordings from synaptically-coupled RBs and AIIs, we found that a voltage-gated Na conductance in AII amacrines accelerated excitatory postsynaptic potentials (EPSPs) arising from RB synaptic input. EPSPs also could be amplified by the Na conductance when AIIs were hyperpolarized below resting membrane potential, thereby increasing the availability of Na channels. AII amacrines are coupled electrically and coupled AII amacrines likely receive common input from individual RBs. Na channel-mediated effects on EPSPs, however, appeared to occur at the single-cell rather than the AII network level. By recording light-evoked synaptic currents from GCs, we determined that the Na channel-dependent acceleration, but not amplification, of RB output by AII amacrines is reflected in the dynamics of AII synaptic output to retinal ganglion cells: synaptic inputs to both ON and OFF GCs are slowed equivalently --though not attenuated in amplitude-- when Na channels in AIIs are blocked. Thus, during scotopic vision, Na conductances in AIIs serve to accelerate RB output.

Transmission of visual signals at the first retinal synapse is associated with changes in calcium concentration in photoreceptors and bipolar cells. We investigated how loss of plasma membrane Ca2+ATPase isoform 2 (PMCA2), the calcium transporter isoform with the highest affinity for Ca2+/calmodulin, affects transmission of rod- and cone-mediated responses. PMCA2 expression in the neuroblast layer was observed soon after birth; in the adult, PMCA2 was expressed in inner segments and synaptic terminals of rod photoreceptors, in rod bipolar cells, and in most inner retinal neurons but was absent from cones. To determine the role of PMCA2 in retinal signaling, we compared morphology and light responses of retinas from control mice and deafwaddlerdfw2Jmice, which lack functional PMCA2 protein. The cytoarchitecture of retinas from control anddfw2Jmice was indistinguishable at the light microscope level. Suction electrode recordings revealed no difference in the sensitivity or amplitude of outer segment light responses of control anddfw2Jrods. However, rod-mediated ERG b-wave responses indfw2Jmice were ∼45% smaller and significantly slower than those of control mice. Furthermore, recordings from individual rod bipolar cells showed that the sensitivity of transmission at the rod output synapse was reduced by ∼50%. No changes in the amplitude or timing of cone-mediated ERG responses were observed. These results suggest that PMCA2-mediated Ca2+extrusion modulates the amplitude and timing of the high-sensitivity rod pathway to a much greater extent than that of the cone pathway.

Microcircuits composed of principal neuron and interneuron dendrites have an important role in shaping the representation of sensory information in the olfactory bulb. Here we establish the physiological features governing synaptic signaling in dendrodendritic microcircuits of olfactory bulb glomeruli. We show that dendritic gamma-aminobutyric acid (GABA) release from periglomerular neurons mediates inhibition of principal tufted cells, retrograde inhibition of sensory input and lateral signaling onto neighboring periglomerular cells. We find that L-type dendritic Ca(2+) spikes in periglomerular cells underlie dendrodendritic transmission by depolarizing periglomerular dendrites and activating P/Q type channels that trigger GABA release. Ca(2+) spikes in periglomerular cells are evoked by powerful excitatory inputs from a single principal cell, and glutamate release from the dendrites of single principal neurons activates a large ensemble of periglomerular cells.

Cyclic nucleotide-gated channels (CNGCs) on the dendritic cilia of olfactory receptor neurons (ORNs) are critical for sensory transduction in the olfactory system. Do CNGCs also play a role in the axons and/or nerve terminals of ORNs? We find that the cyclic nucleotides cAMP and cGMP can both facilitate and depress synaptic transmission between olfactory nerve fibers and their targets in olfactory bulb glomeruli. Cyclic nucleotides increase intracellular Ca 2+ in ORN terminals and enhance spontaneous transmitter release; at higher concentrations, cyclic nucleotides depress evoked transmission by altering olfactory nerve excitability. Cyclic nucleotides have no effect on transmission or nerve excitability, however, in mice lacking olfactory CNGCs. Taken together, our results identify a novel role for presynaptic CNGCs in modulating neurotransmission.

Parallel circuits throughout the CNS exhibit distinct sensitivities and responses to sensory stimuli. Ambiguities in the source and properties of signals elicited by physiological stimuli, however, frequently obscure the mechanisms underlying these distinctions. We found that differences in the degree to which activity in two classes of Off retinal ganglion cell (RGC) encode information about light stimuli near detection threshold were not due to obvious differences in the cells' intrinsic properties or the chemical synaptic input the cells received; indeed, differences in the cells' light responses were largely insensitive to block of fast ionotropic glutamate receptors. Instead, the distinct responses of the two types of RGCs likely reflect differences in light-evoked electrical synaptic input. These results highlight a surprising strategy by which the retina differentially processes and routes visual information and provide new insight into the circuits that underlie responses to stimuli near detection threshold.

Information about sensory stimuli is represented by spatiotemporal patterns of neural activity. The complexity of the central nervous system, however, frequently obscures the origin and properties of signals and noise that underlie these activity patterns. We minimized this constraint by examining mechanisms governing correlated activity in mouse retinal ganglion cells (RGCs) under conditions in which light-evoked responses traverse a specific circuit, the rod bipolar pathway. Signals and noise in this circuit produced correlated synaptic input to neighboring On and Off RGCs. Temporal modulation of light intensity did not alter the degree to which noise in the input to nearby RGCs was correlated, and action potential generation in individual RGCs was largely insensitive to differences in network noise generated by dynamic and static light stimuli. Together, these features enable noise in shared circuitry to diminish simultaneous action potential generation in neighboring On and Off RGCs under a variety of conditions.

Olfactory receptor neurons (ORNs) convey sensory information directly to the CNS via conventional glutamatergic synaptic contacts in olfactory bulb glomeruli. To better understand the process by which information contained in the odorant-evoked firing of ORNs is transmitted to the brain, we examined the properties of glutamate release from olfactory nerve (ON) terminals in slices of the rat olfactory bulb. We show that marked paired pulse depression is the same in simultaneously recorded periglomerular and tufted neurons, and that this form of short-term plasticity is attributable to a reduction of glutamate release from ON terminals. We used the progressive blockade of NMDA receptor (NMDAR) EPSCs by MK-801 [(5R,10S)-(+)-5-methyl-10,11-dihydro-5H-dibenzo[a,d]cyclohepten-5-10-imine hydrogen maleate] and stationary fluctuation analysis of AMPA receptor (AMPAR) EPSCs to determine the probability of release (Pr) of ON terminals; both approaches indicated that Pris unusually high (≥0.8). The low-affinity glutamate receptor antagonists γ-d-glutamylglycine andl-amino-5-phosphonovaleric acid blocked ON-evoked AMPAR- and NMDAR-mediated EPSCs, respectively, to the same extent under conditions of low and high Pr, suggesting that multivesicular release is not a feature of ON terminals. Although release from most synapses exhibits a highly nonlinear dependence on extracellular Ca2+, we find that the relationship between glutamate release and extracellular Ca2+at ON terminals is nearly linear. Our results suggest that ON terminals have specialized features that may contribute to the reliable transmission of sensory information from nose to brain.