NMDA spikes mediate amplification of inputs in the rat piriform cortex

Glycine-gated extrasynaptic NMDARs activated during glutamate spillover drive burst firing in nigral dopamine neurons

Burst firing in substantia nigra pars compacta dopamine neurons is a critical biomarker temporally associated to movement initiation. This phasic change is generated by the tonic activation of NMDARs but the respective role of synaptic versus extrasynaptic NMDARs in the ignition of a burst and what is their level of activation remains unknown. Using ex vivo electrophysiological recordings from adolescent rats, we demonstrate that extrasynaptic NMDARs are the primary driver of burst firing. This pool of receptors is recruited during intense synaptic activity via spillover of glutamate and require the binding of NMDAR co-agonist glycine for full activation. Basal synaptic transmission activating only synaptic NMDARs with the support of D-serine is insufficient to generate a burst. Notably, both synaptic and extrasynaptic NMDARs share the same subunit composition but are regulated by distinct co-agonists. Location of NMDARs and regionalization of co-agonists but not NMDAR subunit composition underly burst generation and may serve as a guideline in understanding the physiological role of dopamine in signaling movement.

Computational functions of precisely balanced neuronal microcircuits in an olfactory memory network

Models of balanced autoassociative memory networks predict that specific inhibition is critical to store information in connectivity. To explore these predictions, we characterized and manipulated different subtypes of fast-spiking interneurons in the posterior telencephalic area Dp (pDp) of adult zebrafish, the homolog of the piriform cortex. Modeling of recurrent networks with assemblies showed that a precise balance of excitation and inhibition is important to prevent not only excessive firing rates ("runaway activity") but also the stochastic occurrence of high pattern correlations ("runaway correlations"). Consistent with model predictions, runaway correlations emerged in pDp when synaptic balance was perturbed by optogenetic manipulations of feedback inhibition but not feedforward inhibition. Runaway correlations were driven by sparse subsets of strongly active neurons rather than by a general broadening of tuning curves. These results are consistent with balanced neuronal assemblies in pDp and reveal novel computational functions of inhibitory microcircuits in an autoassociative network.

Discriminating neural ensemble patterns through dendritic computations in randomly connected feedforward networks

Co-active or temporally ordered neural ensembles are a signature of salient sensory, motor, and cognitive events. Local convergence of such patterned activity as synaptic clusters on dendrites could help single neurons harness the potential of dendritic nonlinearities to decode neural activity patterns. We combined theory and simulations to assess the likelihood of whether projections from neural ensembles could converge onto synaptic clusters even in networks with random connectivity. Using rat hippocampal and cortical network statistics, we show that clustered convergence of axons from three to four different co-active ensembles is likely even in randomly connected networks, leading to representation of arbitrary input combinations in at least 10 target neurons in a 100,000 population. In the presence of larger ensembles, spatiotemporally ordered convergence of three to five axons from temporally ordered ensembles is also likely. These active clusters result in higher neuronal activation in the presence of strong dendritic nonlinearities and low background activity. We mathematically and computationally demonstrate a tight interplay between network connectivity, spatiotemporal scales of subcellular electrical and chemical mechanisms, dendritic nonlinearities, and uncorrelated background activity. We suggest that dendritic clustered and sequence computation is pervasive, but its expression as somatic selectivity requires confluence of physiology, background activity, and connectomics.

Corticostriatal maldevelopment in the R6/2 mouse model of juvenile Huntington's disease

There is a growing consensus that brain development in Huntington's disease (HD) is abnormal, leading to the idea that HD is not only a neurodegenerative but also a neurodevelopmental disorder. Indeed, structural and functional abnormalities have been observed during brain development in both humans and animal models of HD. However, a concurrent study of cortical and striatal development in a genetic model of HD is still lacking. Here we report significant alterations of corticostriatal development in the R6/2 mouse model of juvenile HD. We examined wildtype (WT) and R6/2 mice at postnatal (P) days 7, 14, and 21. Morphological examination demonstrated early structural and cellular alterations reminiscent of malformations of cortical development, and ex vivo electrophysiological recordings of cortical pyramidal neurons (CPNs) demonstrated significant age- and genotype-dependent changes of intrinsic membrane and synaptic properties. In general, R6/2 CPNs had reduced cell membrane capacitance and increased input resistance (P7 and P14), along with reduced frequency of spontaneous excitatory and inhibitory synaptic events during early development (P7), suggesting delayed cortical maturation. This was confirmed by increased occurrence of GABAA receptor-mediated giant depolarizing potentials at P7. At P14, the rheobase of CPNs was significantly reduced, along with increased excitability. Altered membrane and synaptic properties of R6/2 CPNs recovered progressively, and by P21 they were similar to WT CPNs. In striatal medium-sized spiny neurons (MSNs), a different picture emerged. Intrinsic membrane properties were relatively normal throughout development, except for a transient increase in membrane capacitance at P14. The first alterations in MSNs synaptic activity were observed at P14 and consisted of significant deficits in GABAergic inputs, however, these also were normalized by P21. In contrast, excitatory inputs began to decrease at this age. We conclude that the developing HD brain is capable of compensating for early developmental abnormalities and that cortical alterations precede and are a main contributor of striatal changes. Addressing cortical maldevelopment could help prevent or delay disease manifestations.

Corticostriatal Maldevelopment in the R6/2 Mouse Model of Juvenile Huntington's Disease

There is a growing consensus that brain development in Huntington's disease (HD) is abnormal, leading to the idea that HD is not only a neurodegenerative but also a neurodevelopmental disorder. Indeed, structural and functional abnormalities have been observed during brain development in both humans and animal models of HD. However, a concurrent study of cortical and striatal development in a genetic model of HD is still lacking. Here we report significant alterations of corticostriatal development in the R6/2 mouse model of juvenile HD. We examined wildtype (WT) and R6/2 mice at postnatal (P) days 7, 14, and 21. Morphological examination demonstrated early structural and cellular alterations reminiscent of malformations of cortical development, and ex vivo electrophysiological recordings of cortical pyramidal neurons (CPNs) demonstrated significant age- and genotype-dependent changes of intrinsic membrane and synaptic properties. In general, R6/2 CPNs had reduced cell membrane capacitance and increased input resistance (P7 and P14), along with reduced frequency of spontaneous excitatory and inhibitory synaptic events during early development (P7), suggesting delayed cortical maturation. This was confirmed by increased occurrence of GABA A receptor-mediated giant depolarizing potentials at P7. At P14, the rheobase of CPNs was significantly reduced, along with increased excitability. Altered membrane and synaptic properties of R6/2 CPNs recovered progressively, and by P21 they were similar to WT CPNs. In striatal medium-sized spiny neurons (MSNs), a different picture emerged. Intrinsic membrane properties were relatively normal throughout development, except for a transient increase in membrane capacitance at P14. The first alterations in MSNs synaptic activity were observed at P14 and consisted of significant deficits in GABAergic inputs, however, these also were normalized by P21. In contrast, excitatory inputs began to decrease at this age. We conclude that the developing HD brain is capable of compensating for early developmental abnormalities and that cortical alterations precede and are a main contributor of striatal changes. Addressing cortical maldevelopment could help prevent or delay disease manifestations.

Distinct Olfactory Bulb-Cortex Neural Circuits Coordinate Cognitive Function in Parkinson's Disease

Cognitive dysfunction stands as a prevalent and consequential non-motor manifestation in Parkinson's disease (PD). Although dysfunction of the olfactory system has been recognized as an important predictor of cognitive decline, the exact mechanism by which aberrant olfactory circuits contribute to cognitive dysfunction in PD is unclear. Here, we provide the first evidence for abnormal functional connectivity across olfactory bulb (OB) and piriform cortex (PC) or entorhinal cortex (EC) by clinical fMRI, and dysfunction of neural coherence in the olfactory system in PD mice. Moreover, we discovered that 2 subpopulations of mitral/tufted (M/T) cells in OB projecting to anterior PC (aPC) and EC precisely mediated the process of cognitive memory respectively by neural coherence at specific frequencies in mice. In addition, the transcriptomic profiling analysis and functional genetic regulation analysis further revealed that biorientation defective 1 (Bod1) may play a pivotal role in encoding OBM/T-mediated cognitive function. We also verified that a new deep brain stimulation protocol in OB ameliorated the cognitive function of Bod1-deficient mice and PD mice. Together, aberrant coherent activity in the olfactory system can serve as a biomarker for assessing cognitive function and provide a candidate therapeutic target for the treatment of PD.

A dendritic mechanism for balancing synaptic flexibility and stability

Biological and artificial neural networks learn by modifying synaptic weights, but it is unclear how these systems retain previous knowledge and also acquire new information. Here, we show that cortical pyramidal neurons can solve this plasticity-versus-stability dilemma by differentially regulating synaptic plasticity at distinct dendritic compartments. Oblique dendrites of adult mouse layer 5 cortical pyramidal neurons selectively receive monosynaptic thalamic input, integrate linearly, and lack burst-timing synaptic potentiation. In contrast, basal dendrites, which do not receive thalamic input, exhibit conventional NMDA receptor (NMDAR)-mediated supralinear integration and synaptic potentiation. Congruently, spiny synapses on oblique branches show decreased structural plasticity in vivo. The selective decline in NMDAR activity and expression at synapses on oblique dendrites is controlled by a critical period of visual experience. Our results demonstrate a biological mechanism for how single neurons can safeguard a set of inputs from ongoing plasticity by altering synaptic properties at distinct dendritic domains.

Probing multiplexed basal dendritic computations using two-photon 3D holographic uncaging

Basal dendrites of layer 5 cortical pyramidal neurons exhibit Na+ and N-methyl-D-aspartate receptor (NMDAR) regenerative spikes and are uniquely poised to influence somatic output. Nevertheless, due to technical limitations, how multibranch basal dendritic integration shapes and enables multiplexed barcoding of synaptic streams remains poorly mapped. Here, we combine 3D two-photon holographic transmitter uncaging, whole-cell dynamic clamp, and biophysical modeling to reveal how synchronously activated synapses (distributed and clustered) across multiple basal dendritic branches are multiplexed under quiescent and in vivo-like conditions. While dendritic regenerative Na+ spikes promote millisecond somatic spike precision, distributed synaptic inputs and NMDAR spikes regulate gain. These concomitantly occurring dendritic nonlinearities enable multiplexed information transfer amid an ongoing noisy background, including under back-propagating voltage resets, by barcoding the axo-somatic spike structure. Our results unveil a multibranch dendritic integration framework in which dendritic nonlinearities are critical for multiplexing different spatial-temporal synaptic input patterns, enabling optimal feature binding.

Computational Modeling of Extrasynaptic NMDA Receptors: Insights into Dendritic Signal Amplification Mechanisms

Dendritic structures play a pivotal role in the computational processes occurring within neurons. Signal propagation along dendrites relies on both passive conduction and active processes related to voltage-dependent ion channels. Among these channels, extrasynaptic N-methyl-D-aspartate channels (exNMDA) emerge as a significant contributor. Prior studies have mainly concentrated on interactions between synapses and nearby exNMDA (100 nm-10 µm from synapse), activated by presynaptic membrane glutamate. This study concentrates on the correlation between synaptic inputs and distal exNMDA (>100 µm), organized in clusters that function as signal amplifiers. Employing a computational model of a dendrite, we elucidate the mechanism underlying signal amplification in exNMDA clusters. Our findings underscore the pivotal role of the optimal spatial positioning of the NMDA cluster in determining signal amplification efficiency. Additionally, we demonstrate that exNMDA subunits characterized by a large conduction decay constant. Specifically, NR2B subunits exhibit enhanced effectiveness in signal amplification compared to subunits with steeper conduction decay. This investigation extends our understanding of dendritic computational processes by emphasizing the significance of distant exNMDA clusters as potent signal amplifiers. The implications of our computational model shed light on the spatial considerations and subunit characteristics that govern the efficiency of signal amplification in dendritic structures, offering valuable insights for future studies in neurobiology and computational neuroscience.

ER-Ca2+ stores and the regulation of store-operated Ca2+ entry in neurons

Key components of endoplasmic reticulum (ER) Ca2+ release and store-operated Ca2+ entry (SOCE) are likely expressed in all metazoan cells. Due to the complexity of canonical Ca2+ entry mechanisms in neurons, the functional significance of ER-Ca2+ release and SOCE has been difficult to identify and establish. In this review we present evidence of how these two related mechanisms of Ca2+ signalling impact multiple aspects of neuronal physiology and discuss their interaction with the better understood classes of ion channels that are gated by either voltage changes or extracellular ligands in neurons. Given how a small imbalance in Ca2+ homeostasis can have strongly detrimental effects on neurons, leading to cell death, it is essential that neuronal SOCE is carefully regulated. We go on to discuss some mechanisms of SOCE regulation that have been identified in Drosophila and mammalian neurons. These include specific splice variants of stromal interaction molecules, different classes of membrane-interacting proteins and an ER-Ca2+ channel. So far these appear distinct from the mechanisms of SOCE regulation identified in non-excitable cells. Finally, we touch upon the significance of these studies in the context of certain human neurodegenerative diseases.

Endogenous cannabinoids in the piriform cortex tune olfactory perception

Sensory perception depends on interactions between external inputs transduced by peripheral sensory organs and internal network dynamics generated by central neuronal circuits. In the sensory cortex, desynchronized network states associate with high signal-to-noise ratio stimulus-evoked responses and heightened perception. Cannabinoid-type-1-receptors (CB1Rs) - which influence network coordination in the hippocampus - are present in anterior piriform cortex (aPC), a sensory paleocortex supporting olfactory perception. Yet, how CB1Rs shape aPC network activity and affect odor perception is unknown. Using pharmacological manipulations coupled with multi-electrode recordings or fiber photometry in the aPC of freely moving male mice, we show that systemic CB1R blockade as well as local drug infusion increases the amplitude of gamma oscillations in aPC, while simultaneously reducing the occurrence of synchronized population events involving aPC excitatory neurons. In animals exposed to odor sources, blockade of CB1Rs reduces correlation among aPC excitatory units and lowers behavioral olfactory detection thresholds. These results suggest that endogenous endocannabinoid signaling promotes synchronized population events and dampen gamma oscillations in the aPC which results in a reduced sensitivity to external sensory inputs.

Layer 1 neocortex: Gating and integrating multidimensional signals

Layer 1 (L1) of the neocortex acts as a nexus for the collection and processing of widespread information. By integrating ascending inputs with extensive top-down activity, this layer likely provides critical information regulating how the perception of sensory inputs is reconciled with expectation. This is accomplished by sorting, directing, and integrating the complex network of excitatory inputs that converge onto L1. These signals are combined with neuromodulatory afferents and gated by the wealth of inhibitory interneurons that either are embedded within L1 or send axons from other cortical layers. Together, these interactions dynamically calibrate information flow throughout the neocortex. This review will primarily focus on L1 within the primary sensory cortex and will use these insights to understand L1 in other cortical areas.

The impact of Hodgkin-Huxley models on dendritic research

For the past seven decades, the Hodgkin-Huxley (HH) formalism has been an invaluable tool in the arsenal of neuroscientists, allowing for robust and reproducible modelling of ionic conductances and the electrophysiological phenomena they underlie. Despite its apparent age, its role as a cornerstone of computational neuroscience has not waned. The discovery of dendritic regenerative events mediated by ionic and synaptic conductances has solidified the importance of HH-based models further, yielding new predictions concerning dendritic integration, synaptic plasticity and neuronal computation. These predictions are often validated through in vivo and in vitro experiments, advancing our understanding of the neuron as a biological system and emphasizing the importance of HH-based detailed computational models as an instrument of dendritic research. In this article, we discuss recent studies in which the HH formalism is used to shed new light on dendritic function and its role in neuronal phenomena.

Synapse-specific diversity of distinct postsynaptic GluN2 subtypes defines transmission strength in spinal lamina I

The unitary postsynaptic response to presynaptic quantal glutamate release is the fundamental basis of excitatory information transfer between neurons. The view, however, of individual glutamatergic synaptic connections in a population as homogenous, fixed-strength units of neural communication is becoming increasingly scrutinized. Here, we used minimal stimulation of individual glutamatergic afferent axons to evoke single synapse resolution postsynaptic responses from central sensory lamina I neurons in an ex vivo adult rat spinal slice preparation. We detected unitary events exhibiting a NMDA receptor component with distinct kinetic properties across synapses conferred by specific GluN2 subunit composition, indicative of GluN2 subtype-based postsynaptic heterogeneity. GluN2A, 2A and 2B, or 2B and 2D synaptic predominance functioned on distinct lamina I neuron types to narrowly, intermediately, or widely tune, respectively, the duration of evoked unitary depolarization events from resting membrane potential, which enabled individual synapses to grade differentially depolarizing steps during temporally patterned afferent input. Our results lead to a model wherein a core locus of proteomic complexity prevails at this central glutamatergic sensory synapse that involves distinct GluN2 subtype configurations. These findings have major implications for subthreshold integrative capacity and transmission strength in spinal lamina I and other CNS regions.

Cortical interneurons: fit for function and fit to function? Evidence from development and evolution

Cortical inhibitory interneurons form a broad spectrum of subtypes. This diversity suggests a division of labor, in which each cell type supports a distinct function. In the present era of optimisation-based algorithms, it is tempting to speculate that these functions were the evolutionary or developmental driving force for the spectrum of interneurons we see in the mature mammalian brain. In this study, we evaluated this hypothesis using the two most common interneuron types, parvalbumin (PV) and somatostatin (SST) expressing cells, as examples. PV and SST interneurons control the activity in the cell bodies and the apical dendrites of excitatory pyramidal cells, respectively, due to a combination of anatomical and synaptic properties. But was this compartment-specific inhibition indeed the function for which PV and SST cells originally evolved? Does the compartmental structure of pyramidal cells shape the diversification of PV and SST interneurons over development? To address these questions, we reviewed and reanalyzed publicly available data on the development and evolution of PV and SST interneurons on one hand, and pyramidal cell morphology on the other. These data speak against the idea that the compartment structure of pyramidal cells drove the diversification into PV and SST interneurons. In particular, pyramidal cells mature late, while interneurons are likely committed to a particular fate (PV vs. SST) during early development. Moreover, comparative anatomy and single cell RNA-sequencing data indicate that PV and SST cells, but not the compartment structure of pyramidal cells, existed in the last common ancestor of mammals and reptiles. Specifically, turtle and songbird SST cells also express the Elfn1 and Cbln4 genes that are thought to play a role in compartment-specific inhibition in mammals. PV and SST cells therefore evolved and developed the properties that allow them to provide compartment-specific inhibition before there was selective pressure for this function. This suggest that interneuron diversity originally resulted from a different evolutionary driving force and was only later co-opted for the compartment-specific inhibition it seems to serve in mammals today. Future experiments could further test this idea using our computational reconstruction of ancestral Elfn1 protein sequences.

Ultrafast simulation of large-scale neocortical microcircuitry with biophysically realistic neurons

Understanding the activity of the mammalian brain requires an integrative knowledge of circuits at distinct scales, ranging from ion channel gating to circuit connectomics. Computational models are regularly employed to understand how multiple parameters contribute synergistically to circuit behavior. However, traditional models of anatomically and biophysically realistic neurons are computationally demanding, especially when scaled to model local circuits. To overcome this limitation, we trained several artificial neural network (ANN) architectures to model the activity of realistic multicompartmental cortical neurons. We identified an ANN architecture that accurately predicted subthreshold activity and action potential firing. The ANN could correctly generalize to previously unobserved synaptic input, including in models containing nonlinear dendritic properties. When scaled, processing times were orders of magnitude faster compared with traditional approaches, allowing for rapid parameter-space mapping in a circuit model of Rett syndrome. Thus, we present a novel ANN approach allowing for rapid, detailed network experiments using inexpensive and commonly available computational resources.

Assessing Local and Branch-specific Activity in Dendrites

Dendrites are elaborate neural processes which integrate inputs from various sources in space and time. While decades of work have suggested an independent role for dendrites in driving nonlinear computations for the cell, only recently have technological advances enabled us to capture the variety of activity in dendrites and their coupling dynamics with the soma. Under certain circumstances, activity generated in a given dendritic branch remains isolated, such that the soma or even sister dendrites are not privy to these localized signals. Such branch-specific activity could radically increase the capacity and flexibility of coding for the cell as a whole. Here, we discuss these forms of localized and branch-specific activity, their functional relevance in plasticity and behavior, and their supporting biophysical and circuit-level mechanisms. We conclude by showcasing electrical and optical approaches in hippocampal area CA3, using original experimental data to discuss experimental and analytical methodology and key considerations to take when investigating the functional relevance of independent dendritic activity.

Fast and slow feedforward inhibitory circuits for cortical odor processing

Feedforward inhibitory circuits are key contributors to the complex interplay between excitation and inhibition in the brain. Little is known about the function of feedforward inhibition in the primary olfactory (piriform) cortex. Using in vivo two-photon-targeted patch clamping and calcium imaging in mice, we find that odors evoke strong excitation in two classes of interneurons – neurogliaform (NG) cells and horizontal (HZ) cells – that provide feedforward inhibition in layer 1 of the piriform cortex. NG cells fire much earlier than HZ cells following odor onset, a difference that can be attributed to the faster odor-driven excitatory synaptic drive that NG cells receive from the olfactory bulb. As a result, NG cells strongly but transiently inhibit odor-evoked excitation in layer 2 principal cells, whereas HZ cells provide more diffuse and prolonged feedforward inhibition. Our findings reveal unexpected complexity in the operation of inhibition in the piriform cortex.

Parallel processing in active dendrites during periods of intense spiking activity

A neuron's ability to perform parallel computations throughout its dendritic arbor substantially improves its computational capacity. However, during natural patterns of activity, the degree to which computations remain compartmentalized, especially in neurons with active dendritic trees, is not clear. Here, we examine how the direction of moving objects is computed across the bistratified dendritic arbors of ON-OFF direction-selective ganglion cells (DSGCs) in the mouse retina. We find that although local synaptic signals propagate efficiently throughout their dendritic trees, direction-selective computations in one part of the dendritic arbor have little effect on those being made elsewhere. Independent dendritic processing allows DSGCs to compute the direction of moving objects multiple times as they traverse their receptive fields, enabling them to rapidly detect changes in motion direction on a sub-receptive-field basis. These results demonstrate that the parallel processing capacity of neurons can be maintained even during periods of intense synaptic activity.

The guide to dendritic spikes of the mammalian cortex in vitro and in vivo

Half a century since their discovery by Llinás and colleagues, dendritic spikes have been observed in various neurons in different brain regions, from the neocortex and cerebellum to the basal ganglia. Dendrites exhibit a terrifically diverse but stereotypical repertoire of spikes, sometimes specific to subregions of the dendrite. Despite their prevalence, we only have a glimpse into their role in the behaving animal. This article aims to survey the full range of dendritic spikes found in excitatory and inhibitory neurons, compare them in vivo versus in vitro, and discuss new studies describing dendritic spikes in the human cortex. We focus on dendritic spikes in neocortical and hippocampal neurons and present a roadmap to identify and understand the broader role of dendritic spikes in single-cell computation.

Differential dendritic integration of long-range inputs in association cortex via subcellular changes in synaptic AMPA-to-NMDA receptor ratio

Synaptic NMDA receptors can produce powerful dendritic supralinearities that expand the computational repertoire of single neurons and their respective circuits. This form of supralinearity may represent a general principle for synaptic integration in thin dendrites. However, individual cortical neurons receive many diverse classes of input that may require distinct postsynaptic decoding schemes. Here, we show that sensory, motor, and thalamic inputs preferentially target basal, apical oblique, and distal tuft dendrites, respectively, in layer 5b pyramidal neurons of the mouse retrosplenial cortex, a visuospatial association area. These dendritic compartments exhibited differential expression of NMDA receptor-mediated supralinearity due to systematic changes in the AMPA-to-NMDA receptor ratio. Our results reveal a new schema for integration in cortical pyramidal neurons, in which dendrite-specific changes in synaptic receptors support input-localized decoding. This coexistence of multiple modes of dendritic integration in single neurons has important implications for synaptic plasticity and cortical computation.

Optimizing a Neuron for Reliable Dendritic Subunit Pooling

In certain biologically relevant computing scenarios, a neuron "pools" the outputs of multiple independent functional subunits, firing if any one of them crosses threshold. Recent studies suggest that active dendrites could provide the thresholding mechanism, so that both the thresholding and pooling operations could take place within a single neuron. A pooling neuron faces a difficult task, however. Dendrites can produce highly variable responses depending on the density and spatial patterning of their synaptic inputs, and bona fide dendritic firing may be very rare, making it difficult for a neuron to reliably detect when one of its many dendrites has "gone suprathreshold". Our goal has been to identify biological adaptations that optimize a neuron's performance at the binary subunit pooling (BSP) task. Katz et al. (2009) pointed to the importance of spine density gradients in shaping dendritic responses. In a similar vein, we used a compartmental model to study how a neuron's performance at the BSP task is affected by different spine density layouts and other biological variables. We found BSP performance was optimized when dendrites have (1) a decreasing spine density gradient (true for many types of pyramidal neurons); (2) low-to-medium resistance spine necks; (3) strong NMDA currents; (4) fast spiking Na+ channels; and (5) powerful hyperpolarizing inhibition. Our findings provide a normative account that links several neuronal properties within the context of a behaviorally relevant task, and thus provide new insights into nature's subtle strategies for optimizing the computing capabilities of neural tissue.

Plasticity of olfactory bulb inputs mediated by dendritic NMDA-spikes in rodent piriform cortex

The piriform cortex (PCx) is essential for learning of odor information. The current view postulates that odor learning in the PCx is mainly due to plasticity in intracortical (IC) synapses, while odor information from the olfactory bulb carried via the lateral olfactory tract (LOT) is ‘hardwired.’ Here, we revisit this notion by studying location- and pathway-dependent plasticity rules. We find that in contrast to the prevailing view, synaptic and optogenetically activated LOT synapses undergo strong and robust long-term potentiation (LTP) mediated by only a few local NMDA-spikes delivered at theta frequency, while global spike timing-dependent plasticity (STDP) protocols failed to induce LTP in these distal synapses. In contrast, IC synapses in apical and basal dendrites undergo plasticity with both NMDA-spikes and STDP protocols but to a smaller extent compared with LOT synapses. These results are consistent with a self-potentiating mechanism of odor information via NMDA-spikes that can form branch-specific memory traces of odors that can further associate with contextual IC information via STDP mechanisms to provide cognitive and emotional value to odors.

Dendritic Branch-constrained N-Methyl-d-Aspartate Receptor-mediated Spikes Drive Synaptic Plasticity in Hippocampal CA3 Pyramidal Cells

N-methyl-d-aspartate receptor-mediated ( spikes can be causally linked to the induction of synaptic long-term potentiation (LTP) in hippocampal and cortical pyramidal cells. However, it is unclear if they regulate plasticity at a local or global scale in the dendritic tree. Here, we used dendritic patch-clamp recordings and calcium imaging to investigate the integrative properties of single dendrites of hippocampal CA3 cells. We show that local hyperpolarization of a single dendritic segment prevents NMDA spikes, their associated calcium transients, as well as LTP in a branch-specific manner. This result provides direct, causal evidence that the single dendritic branch can operate as a functional unit in regulating CA3 pyramidal cell plasticity.

Local and Global Dynamics of Dendritic Activity in the Pyramidal Neuron

There has been increasing interest in the measurement and comparison of activity across compartments of the pyramidal neuron. Dendritic activity can occur both locally, on a single dendritic segment, or globally, involving multiple compartments of the single neuron. Little is known about how these dendritic dynamics shape and contribute to information processing and behavior. Although it has been difficult to characterize local and global activity in vivo due to the technical challenge of simultaneously recording from the entire dendritic arbor and soma, the rise of calcium imaging has driven the increased feasibility and interest of these experiments. However, the distinction between local and global activity made by calcium imaging requires careful consideration. In this review we describe local and global activity, discuss the difficulties and caveats of this distinction, and present the evidence of local and global activity in information processing and behavior.

Cell assembly formation and structure in a piriform cortex model

The piriform cortex is rich in recurrent excitatory synaptic connections between pyramidal neurons. We asked how such connections could shape cortical responses to olfactory lateral olfactory tract (LOT) inputs. For this, we constructed a computational network model of anterior piriform cortex with 2000 multicompartment, multiconductance neurons (500 semilunar, 1000 layer 2 and 500 layer 3 pyramids; 200 superficial interneurons of two types; 500 deep interneurons of three types; 500 LOT afferents), incorporating published and unpublished data. With a given distribution of LOT firing patterns, and increasing the strength of recurrent excitation, a small number of firing patterns were observed in pyramidal cell networks: first, sparse firings; then temporally and spatially concentrated epochs of action potentials, wherein each neuron fires one or two spikes; then more synchronized events, associated with bursts of action potentials in some pyramidal neurons. We suggest that one function of anterior piriform cortex is to transform ongoing streams of input spikes into temporally focused spike patterns, called here "cell assemblies", that are salient for downstream projection areas.

Antennal-lobe neurons in the moth Helicoverpa armigera: Morphological features of projection neurons, local interneurons, and centrifugal neurons

The relatively large primary olfactory center of the insect brain, the antennal lobe (AL), contains several heterogeneous neuronal types. These include projection neurons (PNs), providing olfactory information to higher‐order neuropils via parallel pathways, and local interneurons (LNs), which provide lateral processing within the AL. In addition, various types of centrifugal neurons (CNs) offer top‐down modulation onto the other AL neurons. By performing iontophoretic intracellular staining, we collected a large number of AL neurons in the moth, Helicoverpa armigera, to examine the distinct morphological features of PNs, LNs, and CNs. We characterize 190 AL neurons. These were allocated to 25 distinct neuronal types or sub‐types, which were reconstructed and placed into a reference brain. In addition to six PN types comprising 15 sub‐types, three LN and seven CN types were identified. High‐resolution confocal images allowed us to analyze AL innervations of the various reported neurons, which demonstrated that all PNs innervating ventroposterior glomeruli contact a protocerebral neuropil rarely targeted by other PNs, that is the posteriorlateral protocerebrum. We also discuss the functional roles of the distinct CNs, which included several previously uncharacterized types, likely involved in computations spanning from multisensory processing to olfactory feedback signalization into the AL.

Synaptic Organization of Anterior Olfactory Nucleus Inputs to Piriform Cortex

Odors activate distributed ensembles of neurons within the piriform cortex, forming cortical representations of odor thought to be essential to olfactory learning and behaviors. This odor response is driven by direct input from the olfactory bulb, but is also shaped by a dense network of associative or intracortical inputs to piriform, which may enhance or constrain the cortical odor representation. With optogenetic techniques, it is possible to functionally isolate defined inputs to piriform cortex and assess their potential to activate or inhibit piriform pyramidal neurons. The anterior olfactory nucleus (AON) receives direct input from the olfactory bulb and sends an associative projection to piriform cortex that has potential roles in the state-dependent processing of olfactory behaviors. Here, we provide a detailed functional assessment of the AON afferents to piriform in male and female C57Bl/6J mice. We confirm that the AON forms glutamatergic excitatory synapses onto piriform pyramidal neurons; and while these inputs are not as strong as piriform recurrent collaterals, they are less constrained by disynaptic inhibition. Moreover, AON-to-piriform synapses contain a substantial NMDAR-mediated current that prolongs the synaptic response at depolarized potentials. These properties of limited inhibition and slow NMDAR-mediated currents result in strong temporal summation of AON inputs within piriform pyramidal neurons, and suggest that the AON could powerfully enhance activation of piriform neurons in response to odor.SIGNIFICANCE STATEMENT Odor information is transmitted from olfactory receptors to olfactory bulb, and then to piriform cortex, where ensembles of activated neurons form neural representations of the odor. While these ensembles are driven by primary bulbar afferents, and shaped by intracortical recurrent connections, the potential for another early olfactory area, the anterior olfactory nucleus (AON), to contribute to piriform activity is not known. Here, we use optogenetic circuit-mapping methods to demonstrate that AON inputs can significantly activate piriform neurons, as they are coupled to NMDAR currents and to relatively modest disynaptic inhibition. The AON may enhance the piriform odor response, encouraging further study to determine the states or behaviors through which AON potentiates the cortical response to odor.

Circuit-Specific Dendritic Development in the Piriform Cortex

Dendritic geometry is largely determined during postnatal development and has a substantial impact on neural function. In sensory processing, postnatal development of the dendritic tree is affected by two dominant circuit motifs, ascending sensory feedforward inputs and descending and local recurrent connections. In the three-layered anterior piriform cortex (aPCx), neurons in the sublayers 2a and 2b display vertical segregation of these two circuit motifs. Here, we combined electrophysiology, detailed morphometry, and Ca²⁺ imaging in acute mouse brain slices and modeling to study circuit-specific aspects of dendritic development. We observed that determination of branching complexity, dendritic length increases, and pruning occurred in distinct developmental phases. Layer 2a and layer 2b neurons displayed developmental phase-specific differences between their apical and basal dendritic trees related to differences in circuit incorporation. We further identified functional candidate mechanisms for circuit-specific differences in postnatal dendritic growth in sublayers 2a and 2b at the mesoscale and microscale levels. Already in the first postnatal week, functional connectivity of layer 2a and layer 2b neurons during early spontaneous network activity scales with differences in basal dendritic growth. During the early critical period of sensory plasticity in the piriform cortex, our data are consistent with a model that proposes a role for dendritic NMDA-spikes in selecting branches for survival during developmental pruning in apical dendrites. The different stages of the morphologic and functional developmental pattern differences between layer 2a and layer 2b neurons demonstrate the complex interplay between dendritic development and circuit specificity.

Dendritic Spikes Expand the Range of Well Tolerated Population Noise Structures

The brain operates surprisingly well despite the noisy nature of individual neurons. The central mechanism for noise mitigation in the nervous system is thought to involve averaging over multiple noise-corrupted inputs. Subsequently, there has been considerable interest in identifying noise structures that can be integrated linearly in a way that preserves reliable signal encoding. By analyzing realistic synaptic integration in biophysically accurate neuronal models, I report a complementary denoising approach that is mediated by focal dendritic spikes. Dendritic spikes might seem to be unlikely candidates for noise reduction due to their miniscule integration compartments and poor averaging abilities. Nonetheless, the extra thresholding step introduced by dendritic spike generation increases neuronal tolerance for a broad category of noise structures, some of which cannot be resolved well with averaging. This property of active dendrites compensates for compartment size constraints and expands the repertoire of conditions that can be processed by neuronal populations.SIGNIFICANCE STATEMENT Noise, or random variability, is a prominent feature of the neuronal code and poses a fundamental challenge for information processing. To reconcile the surprisingly accurate output of the brain with the inherent noisiness of biological systems, previous work examined signal integration in idealized neurons. The notion that emerged from this body of work is that accurate signal representation relies largely on input averaging in neuronal dendrites. In contrast to the prevailing view, I show that denoising in simulated neurons with realistic morphology and biophysical properties follows a different strategy: dendritic spikes act as classifiers that assist in extracting information from a variety of noise structures that have been considered before to be particularly disruptive for reliable brain function.