A strict correlation between dendritic and somatic plateau depolarizations in the rat prefrontal cortex pyramidal neurons

Optogenetic stimulation shapes dendritic trees of infragranular cortical pyramidal cells

Spontaneous or experimentally evoked activity can lead to changes in length and/or branching of neocortical pyramidal cell dendrites. For instance, an early postnatal overexpression of certain AMPA or kainate glutamate receptor subunits leads to larger amplitudes of depolarizing events driven by spontaneous activity, and this increases apical dendritic complexity. Whether stimulation frequency has a role is less clear. In this study, we report that the expression of channelrhodopsin2-eYFP was followed by a 5-day optogenetic stimulation from DIV 5-10 or 11-15 in organotypic cultures of rat visual cortex-evoked dendritic remodeling. Stimulation at 0.05 Hz, at a frequency range of spontaneous calcium oscillations known to occur in the early postnatal neocortex in vivo until eye opening, had no effect. Stimulation with 0.5 Hz, a frequency at which the cortex in vivo adopts after eye opening, unexpectedly caused shorter and somewhat less branched apical dendrites of infragranular pyramidal neurons. The outcome resembles the remodeling of corticothalamic and callosal projection neurons of layers VI and V, which in the adult have apical dendrites no longer terminating in layer I. Exposure to 2.5 Hz, a frequency not occurring naturally during the time windows, evoked dendritic damage. The results suggested that optogenetic stimulation at a biologically meaningful frequency for the selected developmental stage can influence dendrite growth, but contrary to expectation, the optogenetic stimulation decreased dendritic growth.

Sequence learning, prediction, and replay in networks of spiking neurons

Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) algorithm realizes these forms of computation. It learns sequences in an unsupervised and continuous manner using local learning rules, permits a context specific prediction of future sequence elements, and generates mismatch signals in case the predictions are not met. While the HTM algorithm accounts for a number of biological features such as topographic receptive fields, nonlinear dendritic processing, and sparse connectivity, it is based on abstract discrete-time neuron and synapse dynamics, as well as on plasticity mechanisms that can only partly be related to known biological mechanisms. Here, we devise a continuous-time implementation of the temporal-memory (TM) component of the HTM algorithm, which is based on a recurrent network of spiking neurons with biophysically interpretable variables and parameters. The model learns high-order sequences by means of a structural Hebbian synaptic plasticity mechanism supplemented with a rate-based homeostatic control. In combination with nonlinear dendritic input integration and local inhibitory feedback, this type of plasticity leads to the dynamic self-organization of narrow sequence-specific subnetworks. These subnetworks provide the substrate for a faithful propagation of sparse, synchronous activity, and, thereby, for a robust, context specific prediction of future sequence elements as well as for the autonomous replay of previously learned sequences. By strengthening the link to biology, our implementation facilitates the evaluation of the TM hypothesis based on experimentally accessible quantities. The continuous-time implementation of the TM algorithm permits, in particular, an investigation of the role of sequence timing for sequence learning, prediction and replay. We demonstrate this aspect by studying the effect of the sequence speed on the sequence learning performance and on the speed of autonomous sequence replay.

Essentially all data processed by mammals and many other living organisms is sequential. This holds true for all types of sensory input data as well as motor output activity. Being able to form memories of such sequential data, to predict future sequence elements, and to replay learned sequences is a necessary prerequisite for survival. It has been hypothesized that sequence learning, prediction and replay constitute the fundamental computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) constitutes an abstract powerful algorithm implementing this form of computation and has been proposed to serve as a model of neocortical processing. In this study, we are reformulating this algorithm in terms of known biological ingredients and mechanisms to foster the verifiability of the HTM hypothesis based on electrophysiological and behavioral data. The proposed model learns continuously in an unsupervised manner by biologically plausible, local plasticity mechanisms, and successfully predicts and replays complex sequences. Apart from establishing contact to biology, the study sheds light on the mechanisms determining at what speed we can process sequences and provides an explanation of fast sequence replay observed in the hippocampus and in the neocortex.

Local dendritic balance enables learning of efficient representations in networks of spiking neurons

How can neural networks learn to efficiently represent complex and high-dimensional inputs via local plasticity mechanisms? Classical models of representation learning assume that feedforward weights are learned via pairwise Hebbian-like plasticity. Here, we show that pairwise Hebbian-like plasticity works only under unrealistic requirements on neural dynamics and input statistics. To overcome these limitations, we derive from first principles a learning scheme based on voltage-dependent synaptic plasticity rules. Here, recurrent connections learn to locally balance feedforward input in individual dendritic compartments and thereby can modulate synaptic plasticity to learn efficient representations. We demonstrate in simulations that this learning scheme works robustly even for complex high-dimensional inputs and with inhibitory transmission delays, where Hebbian-like plasticity fails. Our results draw a direct connection between dendritic excitatory-inhibitory balance and voltage-dependent synaptic plasticity as observed in vivo and suggest that both are crucial for representation learning.

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.

Active Dendrites and Local Field Potentials: Biophysical Mechanisms and Computational Explorations

Neurons and glial cells are endowed with membranes that express a rich repertoire of ion channels, transporters, and receptors. The constant flux of ions across the neuronal and glial membranes results in voltage fluctuations that can be recorded from the extracellular matrix. The high frequency components of this voltage signal contain information about the spiking activity, reflecting the output from the neurons surrounding the recording location. The low frequency components of the signal, referred to as the local field potential (LFP), have been traditionally thought to provide information about the synaptic inputs that impinge on the large dendritic trees of various neurons. In this review, we discuss recent computational and experimental studies pointing to a critical role of several active dendritic mechanisms that can influence the genesis and the location-dependent spectro-temporal dynamics of LFPs, spanning different brain regions. We strongly emphasize the need to account for the several fast and slow dendritic events and associated active mechanisms - including gradients in their expression profiles, inter- and intra-cellular spatio-temporal interactions spanning neurons and glia, heterogeneities and degeneracy across scales, neuromodulatory influences, and activitydependent plasticity - towards gaining important insights about the origins of LFP under different behavioral states in health and disease. We provide simple but essential guidelines on how to model LFPs taking into account these dendritic mechanisms, with detailed methodology on how to account for various heterogeneities and electrophysiological properties of neurons and synapses while studying LFPs.

Neurophysiological basis of the N400 deflection, from Mismatch Negativity to Semantic Prediction Potentials and late positive components

The first theoretical model on the neurophysiological basis of the N400: the deflection reflects layer I dendritic plateaus on a preparatory state of synaptic integration that precedes layer V somatic burst firing for conscious identification of the higher-order features of the stimulus (a late positive shift). Plateaus ensue from apical disinhibition by vasoactive intestinal polypeptide-positive interneurons (VIPs) through suppression of Martinotti cells, opening the gates for glutamatergic feedback to trigger dendritic regenerative potentials. Cholinergic transients contribute to these dynamics directly, holding a central role in the N400 deflection. The stereotypical timing of the (frontal) glutamatergic feedback and the accompanying cholinergic transients account for the enigmatic "invariability" of the peak latency in the face of a gamut of different stimuli and paradigms. The theoretical postulations presented here may bring about unprecedented level of detail for the N400 deflection to be used in the study of schizophrenia, Alzheimer's disease and other higher-order pathologies. The substrates of a late positive component, the Mismatch Negativity and the Semantic Prediction Potentials are also surveyed.

Subthreshold basis for reward-predictive persistent activity in mouse prefrontal cortex

Nervous systems maintain information internally using persistent activity changes. The mechanisms by which this activity arises are incompletely understood. We study prefrontal cortex (PFC) in mice performing behaviors in which stimuli predicted rewards at different delays with different probabilities. We measure membrane potential (V_m) from pyramidal neurons across layers. Reward-predictive persistent firing increases arise due to sustained increases in mean and variance of V_m and are terminated by reward or via centrally generated mechanisms based on reward expectation. Other neurons show persistent decreases in firing rates, maintained by persistent hyperpolarization that is robust to intracellular perturbation. Persistent activity is layer (L)- and cell-type-specific. Neurons with persistent depolarization are primarily located in upper L5, whereas those with persistent hyperpolarization are mostly found in lower L5. L2/3 neurons do not show persistent activity. Thus, reward-predictive persistent activity in PFC is spatially organized and conveys information about internal state via synaptic mechanisms.

Kim et al. show sustained changes in membrane potential and firing rates in mouse frontal cortex leading up to an expected reward. These dynamics rely on underlying changes in mean and variance, directly testing prior theoretical studies. Neurons showing increased and decreased activity changes are located in different cortical layers.

Local glutamate-mediated dendritic plateau potentials change the state of the cortical pyramidal neuron

Dendritic spikes in thin dendritic branches (basal and oblique dendrites) are traditionally inferred from spikelets measured in the cell body. Here, we used laser-spot voltage-sensitive dye imaging in cortical pyramidal neurons (rat brain slices) to investigate the voltage waveforms of dendritic potentials occurring in response to spatially restricted glutamatergic inputs. Local dendritic potentials lasted 200-500 ms and propagated to the cell body, where they caused sustained 10- to 20-mV depolarizations. Plateau potentials propagating from dendrite to soma and action potentials propagating from soma to dendrite created complex voltage waveforms in the middle of the thin basal dendrite, comprised of local sodium spikelets, local plateau potentials, and backpropagating action potentials, superimposed on each other. Our model replicated these voltage waveforms across a gradient of glutamatergic stimulation intensities. The model then predicted that somatic input resistance (Rin) and membrane time constant (tau) may be reduced during dendritic plateau potential. We then tested these model predictions in real neurons and found that the model correctly predicted the direction of Rin and tau change but not the magnitude. In summary, dendritic plateau potentials occurring in basal and oblique branches put pyramidal neurons into an activated neuronal state ("prepared state"), characterized by depolarized membrane potential and smaller but faster membrane responses. The prepared state provides a time window of 200-500 ms, during which cortical neurons are particularly excitable and capable of following afferent inputs. At the network level, this predicts that sets of cells with simultaneous plateaus would provide cellular substrate for the formation of functional neuronal ensembles.NEW & NOTEWORTHY In cortical pyramidal neurons, we recorded glutamate-mediated dendritic plateau potentials with voltage imaging and created a computer model that recreated experimental measures from dendrite and cell body. Our model made new predictions, which were then tested in experiments. Plateau potentials profoundly change neuronal state: a plateau potential triggered in one basal dendrite depolarizes the soma and shortens membrane time constant, making the cell more susceptible to firing triggered by other afferent inputs.

Local Postsynaptic Signaling on Slow Time Scales in Reciprocal Olfactory Bulb Granule Cell Spines Matches Asynchronous Release

In the vertebrate olfactory bulb (OB), axonless granule cells (GC) mediate self- and lateral inhibitory interactions between mitral/tufted cells via reciprocal dendrodendritic synapses. Locally triggered release of GABA from the large reciprocal GC spines occurs on both fast and slow time scales, possibly enabling parallel processing during olfactory perception. Here we investigate local mechanisms for asynchronous spine output. To reveal the temporal and spatial characteristics of postsynaptic ion transients, we imaged spine and adjacent dendrite Ca2 +- and Na+-signals with minimal exogenous buffering by the respective fluorescent indicator dyes upon two-photon uncaging of DNI-glutamate in OB slices from juvenile rats. Both postsynaptic fluorescence signals decayed slowly, with average half durations in the spine head of t1 / 2_Δ[Ca2 +]i ∼500 ms and t1 / 2_Δ[Na+]i ∼1,000 ms. We also analyzed the kinetics of already existing data of postsynaptic spine Ca2 +-signals in response to glomerular stimulation in OB slices from adult mice, either WT or animals with partial GC glutamate receptor deletions (NMDAR: GluN1 subunit; AMPAR: GluA2 subunit). In a large subset of spines the fluorescence signal had a protracted rise time (average time to peak ∼400 ms, range 20 to >1,000 ms). This slow rise was independent of Ca2 + entry via NMDARs, since similarly slow signals occurred in ΔGluN1 GCs. Additional Ca2 + entry in ΔGluA2 GCs (with AMPARs rendered Ca2 +-permeable), however, resulted in larger ΔF/Fs that rose yet more slowly. Thus GC spines appear to dispose of several local mechanisms to promote asynchronous GABA release, which are reflected in the time course of mitral/tufted cell recurrent inhibition.

GluN2B but Not GluN2A for Basal Dendritic Growth of Cortical Pyramidal Neurons

NMDA receptors are important players for neuronal differentiation. We previously reported that antagonizing NMDA receptors with APV blocked the growth-promoting effects evoked by the overexpression of specific calcium-permeable or flip-spliced AMPA receptor subunits and of type I transmembrane AMPA receptor regulatory proteins which both exclusively modify apical dendritic length and branching of cortical pyramidal neurons. These findings led us to characterize the role of GluN2B and GluN2A for dendritogenesis using organotypic cultures of rat visual cortex. Antagonizing GluN2B with ifenprodil and Ro25-6981 strongly impaired basal dendritic growth of supra- and infragranular pyramidal cells at DIV 5–10, but no longer at DIV 15–20. Growth recovered after washout, and protein blots revealed an increase of synaptic GluN2B-containing receptors as indicated by a enhanced phosphorylation of the tyrosine 1472 residue. Antagonizing GluN2A with TCN201 and NVP-AAM077 was ineffective at both ages. Dendrite growth of non-pyramidal interneurons was not altered. We attempted to overexpress GluN2A and GluN2B. However, although the constructs delivered currents in HEK cells, there were neither effects on dendrite morphology nor an enhanced sensitivity to NMDA. Further, co-expressing GluN1-1a and GluN2B did not alter dendritic growth. Visualization of overexpressed, tagged GluN2 proteins was successful after immunofluorescence for the tag which delivered rather weak staining in HEK cells as well as in neurons. This suggested that the level of overexpression is too weak to modify dendrite growth. In summary, endogenous GluN2B, but not GluN2A is important for pyramidal cell basal dendritic growth during an early postnatal time window.

Sparse coding with a somato-dendritic rule

Cortical neurons are silent most of the time: sparse activity enables low-energy computation in the brain, and promises to do the same in neuromorphic hardware. Beyond power efficiency, sparse codes have favourable properties for associative learning, as they can store more information than local codes but are easier to read out than dense codes. Auto-encoders with a sparse constraint can learn sparse codes, and so can single-layer networks that combine recurrent inhibition with unsupervised Hebbian learning. But the latter usually require fast homeostatic plasticity, which could lead to catastrophic forgetting in embodied agents that learn continuously. Here we set out to explore whether plasticity at recurrent inhibitory synapses could take up that role instead, regulating both the population sparseness and the firing rates of individual neurons. We put the idea to the test in a network that employs compartmentalised inputs to solve the task: rate-based dendritic compartments integrate the feedforward input, while spiking integrate-and-fire somas compete through recurrent inhibition. A somato-dendritic learning rule allows somatic inhibition to modulate nonlinear Hebbian learning in the dendrites. Trained on MNIST digits and natural images, the network discovers independent components that form a sparse encoding of the input and support linear decoding. These findings confirm that intrinsic homeostatic plasticity is not strictly required for regulating sparseness: inhibitory synaptic plasticity can have the same effect. Our work illustrates the usefulness of compartmentalised inputs, and makes the case for moving beyond point neuron models in artificial spiking neural networks.

Synergy of Glutamatergic and Cholinergic Modulation Induces Plateau Potentials in Hippocampal OLM Interneurons

Oriens-lacunosum moleculare (OLM) cells are hippocampal inhibitory interneurons that are implicated in the regulation of information flow in the CA1 circuit, inhibiting cortical inputs to distal pyramidal cell dendrites, whilst disinhibiting CA3 inputs to pyramidal cells. OLM cells express metabotropic cholinergic (mAChR) and glutamatergic (mGluR) receptors, so modulation of these cells via these receptors may contribute to switching between functional modes of the hippocampus. Using a transgenic mouse line to identify OLM cells, we found that both mAChR and mGluR activation caused the cells to exhibit long-lasting depolarizing plateau potentials following evoked spike trains. Both mAChR- and mGluR-induced plateau potentials were eliminated by blocking transient receptor potential (TRP) channels, and were dependent on intracellular calcium concentration and calcium entry. Pharmacological tests indicated that Group I mGluRs are responsible for the glutamatergic induction of plateaus. There was also a pronounced synergy between the cholinergic and glutamatergic modulation, plateau potentials being generated by agonists applied together at concentrations too low to elicit any change when applied individually. This synergy could enable OLM cells to function as coincidence detectors of different neuromodulatory systems, leading to their enhanced and prolonged activation and a functional change in information flow within the hippocampus.

Can NMDA Spikes Dictate Computations of Local Networks and Behavior?

Intelligence is the ability to learn appropriate responses to stimuli and the capacity to master new skills. Synaptic integration at the dendritic level is thought to be essential for this ability through linear and non-linear processing, by allowing neurons to be tuned to relevant information and to maximize adaptive behavior. Showing that dendrites are able to generate local computations that influence how animals perceive the world, form a new memory or learn a new skill was a break-through in neuroscience, since in the past they were seen as passive elements of the neurons, just funneling information to the soma. Here, we provide an overview of the role of dendritic integration in improving the neuronal network and behavioral performance. We focus on how NMDA spikes are generated and their role in neuronal computation for optimal behavioral output based on recent in vivo studies on rodents.

How Dendrites Affect Online Recognition Memory

In order to record the stream of autobiographical information that defines our unique personal history, our brains must form durable memories from single brief exposures to the patterned stimuli that impinge on them continuously throughout life. However, little is known about the computational strategies or neural mechanisms that underlie the brain's ability to perform this type of "online" learning. Based on increasing evidence that dendrites act as both signaling and learning units in the brain, we developed an analytical model that relates online recognition memory capacity to roughly a dozen dendritic, network, pattern, and task-related parameters. We used the model to determine what dendrite size maximizes storage capacity under varying assumptions about pattern density and noise level. We show that over a several-fold range of both of these parameters, and over multiple orders-of-magnitude of memory size, capacity is maximized when dendrites contain a few hundred synapses-roughly the natural number found in memory-related areas of the brain. Thus, in comparison to entire neurons, dendrites increase storage capacity by providing a larger number of better-sized learning units. Our model provides the first normative theory that explains how dendrites increase the brain's capacity for online learning; predicts which combinations of parameter settings we should expect to find in the brain under normal operating conditions; leads to novel interpretations of an array of existing experimental results; and provides a tool for understanding which changes associated with neurological disorders, aging, or stress are most likely to produce memory deficits-knowledge that could eventually help in the design of improved clinical treatments for memory loss.

Autonomous patch-clamp robot for functional characterization of neurons in vivo: development and application to mouse visual cortex

Patch clamping is the gold standard measurement technique for cell-type characterization in vivo, but it has low throughput, is difficult to scale, and requires highly skilled operation. We developed an autonomous robot that can acquire multiple consecutive patch-clamp recordings in vivo. In practice, 40 pipettes loaded into a carousel are sequentially filled and inserted into the brain, localized to a cell, used for patch clamping, and disposed. Automated visual stimulation and electrophysiology software enables functional cell-type classification of whole cell-patched cells, as we show for 37 cells in the anesthetized mouse in visual cortex (V1) layer 5. We achieved 9% yield, with 5.3 min per attempt over hundreds of trials. The highly variable and low-yield nature of in vivo patch-clamp recordings will benefit from such a standardized, automated, quantitative approach, allowing development of optimal algorithms and enabling scaling required for large-scale studies and integration with complementary techniques. NEW & NOTEWORTHY In vivo patch-clamp is the gold standard for intracellular recordings, but it is a very manual and highly skilled technique. The robot in this work demonstrates the most automated in vivo patch-clamp experiment to date, by enabling production of multiple, serial intracellular recordings without human intervention. The robot automates pipette filling, wire threading, pipette positioning, neuron hunting, break-in, delivering sensory stimulus, and recording quality control, enabling in vivo cell-type characterization.

Conditional Bistability, a Generic Cellular Mnemonic Mechanism for Robust and Flexible Working Memory Computations

Persistent neural activity, the substrate of working memory, is thought to emerge from synaptic reverberation within recurrent networks. However, reverberation models do not robustly explain the fundamental dynamics of persistent activity, including high-spiking irregularity, large intertrial variability, and state transitions. While cellular bistability may contribute to persistent activity, its rigidity appears incompatible with persistent activity labile characteristics. Here, we unravel in a cellular model a form of spike-mediated conditional bistability that is robust and generic. and provides a rich repertoire of mnemonic computations. Under asynchronous synaptic inputs of the awakened state, conditional bistability generates spiking/bursting episodes, accounting for the irregularity, variability, and state transitions characterizing persistent activity. This mechanism has likely been overlooked because of the subthreshold input it requires, and we predict how to assess it experimentally. Our results suggest a reexamination of the role of intrinsic properties in the collective network dynamics responsible for flexible working memory.SIGNIFICANCE STATEMENT This study unravels a novel form of intrinsic neuronal property: conditional bistability. We show that, thanks to its conditional character, conditional bistability favors the emergence of flexible and robust forms of persistent activity in PFC neural networks, in opposition to previously studied classical forms of absolute bistability. Specifically, we demonstrate for the first time that conditional bistability (1) is a generic biophysical spike-dependent mechanism of layer V pyramidal neurons in the PFC and that (2) it accounts for essential neurodynamical features for the organization and flexibility of PFC persistent activity (the large irregularity and intertrial variability of the discharge and its organization under discrete stable states), which remain unexplained in a robust fashion by current models.

Embedded ensemble encoding hypothesis: The role of the "Prepared" cell

We here reconsider current theories of neural ensembles in the context of recent discoveries about neuronal dendritic physiology. The key physiological observation is that the dendritic plateau potential produces sustained depolarization of the cell body (amplitude 10-20 mV, duration 200-500 ms). Our central hypothesis is that synaptically-evoked dendritic plateau potentials lead to a prepared state of a neuron that favors spike generation. The plateau both depolarizes the cell toward spike threshold, and provides faster response to inputs through a shortened membrane time constant. As a result, the speed of synaptic-to-action potential (AP) transfer is faster during the plateau phase. Our hypothesis relates the changes from "resting" to "depolarized" neuronal state to changes in ensemble dynamics and in network information flow. The plateau provides the Prepared state (sustained depolarization of the cell body) with a time window of 200-500 ms. During this time, a neuron can tune into ongoing network activity and synchronize spiking with other neurons to provide a coordinated Active state (robust firing of somatic APs), which would permit "binding" of signals through coordination of neural activity across a population. The transient Active ensemble of neurons is embedded in the longer-lasting Prepared ensemble of neurons. We hypothesize that "embedded ensemble encoding" may be an important organizing principle in networks of neurons.

Dopamine D2 Receptors Modulate Pyramidal Neurons in Mouse Medial Prefrontal Cortex through a Stimulatory G-Protein Pathway

Dopaminergic modulation of prefrontal cortex (PFC) is thought to play key roles in many cognitive functions and to be disrupted in pathological conditions, such as schizophrenia. We have previously described a phenomenon whereby dopamine D2 receptor (D2R) activation elicits afterdepolarizations (ADPs) in subcortically projecting (SC) pyramidal neurons within L5 of the PFC. These D2R-induced ADPs only occur following synaptic input, which activates NMDARs, even when the delay between the synaptic input and ADPs is relatively long (e.g., several hundred milliseconds). Here, we use a combination of electrophysiological, optogenetic, pharmacological, transgenic, and chemogenetic approaches to elucidate cellular mechanisms underlying this phenomenon in male and female mice. We find that knocking out D2Rs eliminates the ADP in a cell-autonomous fashion, confirming that this ADP depends on D2Rs. Hyperpolarizing current injection, but not AMPA receptor blockade, prevents synaptic stimulation from facilitating D2R-induced ADPs, suggesting that this phenomenon depends on the recruitment of voltage-dependent currents (e.g., NMDAR-mediated Ca²⁺ influx) by synaptic input. Finally, the D2R-induced ADP is blocked by inhibitors of cAMP/PKA signaling, insensitive to pertussis toxin or β-arrestin knock-out, and mimicked by G_s-DREADD stimulation, suggesting that D2R activation elicits the ADP by stimulating cAMP/PKA signaling. These results show that this unusual physiological phenomenon, in which D2Rs enhance cellular excitability in a manner that depends on synaptic input, is mediated at the cellular level through the recruitment of signaling pathways associated with G_s, rather than the G_i/o-associated mechanisms that have classically been ascribed to D2Rs.SIGNIFICANCE STATEMENT Dopamine D2 receptors (D2Rs) in the prefrontal cortex (PFC) are thought to play important roles in behaviors, including working memory and cognitive flexibility. Variation in D2Rs has also been implicated in schizophrenia, Tourette syndrome, and bipolar disorder. Recently, we described a new mechanism through which D2R activation can enhance the excitability of pyramidal neurons in the PFC. Here, we explore the underlying cellular mechanisms. Surprisingly, although D2Rs are classically assumed to signal through G_i/o-coupled G-proteins and/or scaffolding proteins, such as β-arrestin, we find that the effects of D2Rs on prefrontal pyramidal neurons are actually mediated by pathways associated with G_s-mediated signaling. Furthermore, we show how, via this D2R-dependent phenomenon, synaptic input can enhance the excitability of prefrontal neurons over timescales on the order of seconds. These results elucidate cellular mechanisms underlying a novel signaling pathway downstream of D2Rs that may contribute to prefrontal function under normal and pathological conditions.

Contribution of extrasynaptic N-methyl-D-aspartate and adenosine A1 receptors in the generation of dendritic glutamate-mediated plateau potentials

Thin basal dendrites can strongly influence neuronal output via generation of dendritic spikes. It was recently postulated that glial processes actively support dendritic spikes by either ceasing glutamate uptake or by actively releasing glutamate and adenosine triphosphate (ATP). We used calcium imaging to study the role of NR2C/D-containing N-methyl-d-aspartate (NMDA) receptors and adenosine A1 receptors in the generation of dendritic NMDA spikes and plateau potentials in basal dendrites of layer 5 pyramidal neurons in the mouse prefrontal cortex. We found that NR2C/D glutamate receptor subunits contribute to the amplitude of synaptically evoked NMDA spikes. Dendritic calcium signals associated with glutamate-evoked dendritic plateau potentials were significantly shortened upon application of the NR2C/D receptor antagonist PPDA, suggesting that NR2C/D receptors prolong the duration of calcium influx during dendritic spiking. In contrast to NR2C/D receptors, adenosine A1 receptors act to abbreviate dendritic and somatic signals via the activation of dendritic K(+) current. This current is characterized as a slow-activating outward-rectifying voltage- and adenosine-gated current, insensitive to 4-aminopyridine but sensitive to TEA. Our data support the hypothesis that the release of glutamate and ATP from neurons or glia contribute to initiation, maintenance and termination of local dendritic glutamate-mediated regenerative potentials.

Effects of Neural Morphology and Input Distribution on Synaptic Processing by Global and Focal NMDA-Spikes

Cortical neurons can respond to glutamatergic stimulation with regenerative N-Methyl-D-aspartic acid (NMDA)-spikes. NMDA-spikes were initially thought to depend on clustered synaptic activation. Recent work had shown however a new variety of a global NMDA-spike, which can be generated by randomly distributed inputs. Very little is known about the factors that influence the generation of these global NMDA-spikes, as well the potentially distinct rules of synaptic integration and the computational significance conferred by the two types of NMDA-spikes. Here I show that the input resistance (R_IN) plays a major role in influencing spike initiation; while the classical, focal NMDA-spike depended upon the local (dendritic) R_IN, the threshold of global NMDA-spike generation was set by the somatic R_IN. As cellular morphology can exert a large influence on R_IN, morphologically distinct neuron types can have dissimilar rules for NMDA-spikes generation. For example, cortical neurons in superficial layers were found to be generally prone to global NMDA-spike generation. In contrast, electric properties of cortical layer 5b cells clearly favor focal NMDA-spikes. These differences can translate into diverse synaptic integration rules for the different classes of cortical cells; simulated superficial layers neurons were found to exhibit strong synaptic interactions between different dendritic branches, giving rise to a single integrative compartment mediated by the global NMDA-spike. In these cells, efficiency of postsynaptic activation was relatively little dependent on synaptic distribution. By contrast, layer 5b neurons were capable of true multi-unit computation involving independent integrative compartments formed by clustered synaptic input which could trigger focal NMDA-spikes. In a sharp contrast to superficial layers neurons, randomly distributed synaptic inputs were not very effective in driving firing the layer 5b cells, indicating a possibility for different computation performed by these important cortical neurons.

Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States

Oscillations between high and low values of the membrane potential (UP and DOWN states respectively) are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon’s implications for computation.

Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs) of the exponential integrate and fire (EIF) model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike’s preceding ISI. As we show, the EIF’s exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron’s ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states.

Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods.

Finally, we explain how spike-based random sampling relates to existing computational theories about UP states during slow wave sleep and present possible extensions of the model in the context of spike-frequency adaptation.

Distinctive receptive field and physiological properties of a wide-field amacrine cell in the macaque monkey retina

At early stages of visual processing, receptive fields are typically described as subtending local regions of space and thus performing computations on a narrow spatial scale. Nevertheless, stimulation well outside of the classical receptive field can exert clear and significant effects on visual processing. Given the distances over which they occur, the retinal mechanisms responsible for these long-range effects would certainly require signal propagation via active membrane properties. Here the physiology of a wide-field amacrine cell-the wiry cell-in macaque monkey retina is explored, revealing receptive fields that represent a striking departure from the classic structure. A single wiry cell integrates signals over wide regions of retina, 5-10 times larger than the classic receptive fields of most retinal ganglion cells. Wiry cells integrate signals over space much more effectively than predicted from passive signal propagation, and spatial integration is strongly attenuated during blockade of NMDA spikes but integration is insensitive to blockade of NaV channels with TTX. Thus these cells appear well suited for contributing to the long-range interactions of visual signals that characterize many aspects of visual perception.

NMDA receptors are the basis for persistent network activity in neocortex slices

During behavioral quiescence the neocortex generates spontaneous slow oscillations that consist of Up and Down states. Up states are short epochs of persistent activity, but their underlying source is unclear. In neocortex slices of adult mice, we monitored several cellular and network variables during the transition between a traditional buffer, which does not cause Up states, and a lower-divalent cation buffer, which leads to the generation of Up states. We found that the resting membrane potential and input resistance of cortical cells did not change with the development of Up states. The synaptic efficacy of excitatory postsynaptic potentials mediated by non-NMDA receptors was slightly reduced, but this is unlikely to facilitate the generation of Up states. On the other hand, we identified two variables that are associated with the generation of Up states: an enhancement of the intrinsic firing excitability of cortical cells and an enhancement of NMDA-mediated responses evoked by electrical or optogenetic stimulation. The fact that blocking NMDA receptors abolishes Up states indicates that the enhancement in intrinsic firing excitability alone is insufficient to generate Up states. NMDA receptors have a crucial role in the generation of Up states in neocortex slices.

Neocortical focus: experimental view

All brain normal or pathological activities occur in one of the states of vigilance: wake, slow-wave sleep, or REM sleep. Neocortical seizures preferentially occur during slow-wave sleep. We provide a description of neuronal behavior and mechanisms mediating such a behavior within neocortex taking place in natural states of vigilance as well as during seizures pointing to similarities and differences exhibited during sleep and seizures. A concept of epileptic focus is described using a model of cortical undercut, because in that model, the borders of the focus are well defined. In this model, as in other models of acquired epilepsy, the main factor altering excitability is deafferentation, which upregulates neuronal excitability that promotes generation of seizures. Periods of disfacilitation recorded during slow-wave sleep further upregulate neuronal excitability. It appears that the state of neurons and neuronal network in the epileptic focus produced by deafferentation are such that seizures cannot be generated there. Instead, seizures always start around the perimeter of the undercut cortex. Therefore, we define these areas as the seizure focus. In this zone, neuronal connectivity and excitability are moderately enhanced, lowering the threshold for seizure generation.

Mechanisms of Functional Hypoconnectivity in the Medial Prefrontal Cortex of Mecp2 Null Mice

Frontal cortical dysfunction is thought to contribute to cognitive and behavioral features of autism spectrum disorders; however, underlying mechanisms are poorly understood. The present study sought to define how loss of Mecp2, the gene mutated in Rett syndrome (RTT), disrupts function in the murine medial prefrontal cortex (mPFC) using acute brain slices and behavioral testing. Compared with wildtype, pyramidal neurons in the Mecp2 null mPFC exhibit significant reductions in excitatory postsynaptic currents, the duration of excitatory UP-states, evoked population activity, and the ratio of NMDA:AMPA currents, as well as an increase in the relative fraction of NR2B currents. These functional changes are associated with reductions in the density of excitatory dendritic spines, the ratio of vesicular glutamate to GABA transporters and GluN1 expression. In contrast to recent reports on circuit defects in other brain regions, we observed no effect of Mecp2 loss on inhibitory synaptic currents or expression of the inhibitory marker parvalbumin. Consistent with mPFC hypofunction, Mecp2 nulls exhibit respiratory dysregulation in response to behavioral arousal. Our data highlight functional hypoconnectivity in the mPFC as a potential substrate for behavioral disruption in RTT and other disorders associated with reduced expression of Mecp2 in frontal cortical regions.

Acetylcholine excites neocortical pyramidal neurons via nicotinic receptors

The neuromodulator acetylcholine (ACh) shapes neocortical function during sensory perception, motor control, arousal, attention, learning, and memory. Here we investigate the mechanisms by which ACh affects neocortical pyramidal neurons in adult mice. Stimulation of cholinergic axons activated muscarinic and nicotinic ACh receptors on pyramidal neurons in all cortical layers and in multiple cortical areas. Nicotinic receptor activation evoked short-latency, depolarizing postsynaptic potentials (PSPs) in many pyramidal neurons. Nicotinic receptor-mediated PSPs promoted spiking of pyramidal neurons. The duration of the increase in spiking was membrane potential dependent, with nicotinic receptor activation triggering persistent spiking lasting many seconds in neurons close to threshold. Persistent spiking was blocked by intracellular BAPTA, indicating that nicotinic ACh receptor activation evoked persistent spiking via a long-lasting calcium-activated depolarizing current. We compared nicotinic PSPs in primary motor cortex (M1), prefrontal cortex (PFC), and visual cortex. The laminar pattern of nicotinic excitation was not uniform but was broadly similar across areas, with stronger modulation in deep than superficial layers. Superimposed on this broad pattern were local differences, with nicotinic PSPs being particularly large and common in layer 5 of M1 but not layer 5 of PFC or primary visual cortex (V1). Hence, in addition to modulating the excitability of pyramidal neurons in all layers via muscarinic receptors, synaptically released ACh preferentially increases the activity of deep-layer neocortical pyramidal neurons via nicotinic receptors, thereby adding laminar selectivity to the widespread enhancement of excitability mediated by muscarinic ACh receptors.

NMDA spike/plateau potentials in dendrites of thalamocortical neurons

Dendritic NMDA spike/plateau potentials, first discovered in cortical pyramidal neurons, provide supralinear integration of synaptic inputs on thin and distal dendrites, thereby increasing the impact of these inputs on the soma. The more specific functional role of these potentials has been difficult to clarify, partly due to the complex circuitry of cortical neurons. Thalamocortical (TC) neurons in the dorsal lateral geniculate nucleus participate in simpler circuits. They receive their primary afferent input from retina and send their output to visual cortex. Cortex, in turn, regulates this output through massive feedback to distal dendrites of the TC neurons. The TC neurons can operate in two modes related to behavioral states: burst mode prevailing during sleep, when T-type calcium bursts largely disrupt the transfer of signals from retina to cortex, and tonic mode, which provides reliable transfer of retinal signals to cortex during wakefulness. We studied dendritic potentials in TC neurons with combined two-photon calcium imaging and whole-cell recording of responses to local dendritic glutamate iontophoresis in acute brain slices from mice. We found that NMDA spike/plateaus can be elicited locally at distal dendrites of TC neurons. We suggest that these dendritic potentials have important functions in the cortical regulation of thalamocortical transmission. NMDA spike/plateaus can induce shifts in the functional mode from burst to tonic by blockade of T-type calcium conductances. Moreover, in tonic mode, they can facilitate the transfer of retinal signals to cortex by depolarization of TC neurons.

Spiny neurons of amygdala, striatum, and cortex use dendritic plateau potentials to detect network UP states

Spiny neurons of amygdala, striatum, and cerebral cortex share four interesting features: (1) they are the most abundant cell type within their respective brain area, (2) covered by thousands of thorny protrusions (dendritic spines), (3) possess high levels of dendritic NMDA conductances, and (4) experience sustained somatic depolarizations in vivo and in vitro (UP states). In all spiny neurons of the forebrain, adequate glutamatergic inputs generate dendritic plateau potentials (“dendritic UP states”) characterized by (i) fast rise, (ii) plateau phase lasting several hundred milliseconds, and (iii) abrupt decline at the end of the plateau phase. The dendritic plateau potential propagates toward the cell body decrementally to induce a long-lasting (longer than 100 ms, most often 200–800 ms) steady depolarization (∼20 mV amplitude), which resembles a neuronal UP state. Based on voltage-sensitive dye imaging, the plateau depolarization in the soma is precisely time-locked to the regenerative plateau potential taking place in the dendrite. The somatic plateau rises after the onset of the dendritic voltage transient and collapses with the breakdown of the dendritic plateau depolarization. We hypothesize that neuronal UP states in vivo reflect the occurrence of dendritic plateau potentials (dendritic UP states). We propose that the somatic voltage waveform during a neuronal UP state is determined by dendritic plateau potentials. A mammalian spiny neuron uses dendritic plateau potentials to detect and transform coherent network activity into a ubiquitous neuronal UP state. The biophysical properties of dendritic plateau potentials allow neurons to quickly attune to the ongoing network activity, as well as secure the stable amplitudes of successive UP states.

An Augmented Two-Layer Model Captures Nonlinear Analog Spatial Integration Effects in Pyramidal Neuron Dendrites

In pursuit of the goal to understand and eventually reproduce the diverse functions of the brain, a key challenge lies in reverse engineering the peculiar biology-based "technology" that underlies the brain's remarkable ability to process and store information. The basic building block of the nervous system is the nerve cell, or "neuron," yet after more than 100 years of neurophysiological study and 60 years of modeling, the information processing functions of individual neurons, and the parameters that allow them to engage in so many different types of computation (sensory, motor, mnemonic, executive, etc.) remain poorly understood. In this paper, we review both historical and recent findings that have led to our current understanding of the analog spatial processing capabilities of dendrites, the major input structures of neurons, with a focus on the principal cell type of the neocortex and hippocampus, the pyramidal neuron (PN). We encapsulate our current understanding of PN dendritic integration in an abstract layered model whose spatially sensitive branch-subunits compute multidimensional sigmoidal functions. Unlike the 1-D sigmoids found in conventional neural network models, multidimensional sigmoids allow the cell to implement a rich spectrum of nonlinear modulation effects directly within their dendritic trees.

Synaptic cooperativity regulates persistent network activity in neocortex

During behavioral quiescence, the neocortex generates spontaneous slow oscillations, which may consist of up-states and down-states. Up-states are short epochs of persistent activity that resemble the activated neocortex during arousal and cognition. Neural activity in neocortical pathways can trigger up-states, but the variables that control their occurrence are poorly understood. We used thalamocortical slices from adult mice to explore the role of thalamocortical and intracortical synaptic cooperativity (the number of coincident afferents) in driving up-states. Cooperativity was adjusted by varying the intensity of electrical or blue-light stimuli in pathways that express channelrhodopsin-2. We found that optogenetics greatly improves the study of thalamocortical pathways in slices because it produces thalamocortical responses that resemble those observed in vivo. The results indicate that more synaptic cooperativity, caused by either thalamocortical or intracortical fast AMPA-receptor excitation, leads to more robust inhibition of up-states because it drives stronger feedforward inhibition. Conversely, during strong synaptic cooperativity that suppresses up-states, blocking fast excitation, and as a result the feedforward inhibition it drives, unmasks up-states entirely mediated by slow NMDA-receptor excitation. Regardless of the pathway's origin, cooperativity mediated by fast excitation is inversely related to the ability of excitatory synaptic pathways to trigger up-states in neocortex.

Control of layer 5 pyramidal cell spiking by oscillatory inhibition in the distal apical dendrites: a computational modeling study

The distal apical dendrites of layer 5 pyramidal neurons receive cortico-cortical and thalamocortical top-down and feedback inputs, as well as local recurrent inputs. A prominent source of recurrent inhibition in the neocortical circuit is somatostatin-positive Martinotti cells, which preferentially target distal apical dendrites of pyramidal cells. These electrically coupled cells can fire synchronously at various frequencies, including over a relatively slow range (5∼30 Hz), thereby imposing oscillatory inhibition on the pyramidal apical tuft dendrites. We examined how such distal oscillatory inhibition influences the firing of a biophysically detailed layer 5 pyramidal neuron model, which reproduced the spatiotemporal properties of sodium, calcium, and N-methyl-D-aspartate receptor spikes found experimentally. We found that oscillatory synchronization strongly influences the impact of distal inhibition on the pyramidal cell firing. Whereas asynchronous inhibition largely cancels out the facilitatory effects of distal excitatory inputs, inhibition oscillating synchronously at around 10∼20 Hz allows distal excitation to drive axosomatic firing, as if distal inhibition were absent. Underlying this is a switch from relatively infrequent burst firing to single spike firing at every period of the inhibitory oscillation. This phenomenon depends on hyperpolarization-activated cation current-dependent membrane potential resonance in the dendrite, but also, in a novel manner, on a cooperative amplification of this resonance by N-methyl-D-aspartate-receptor-driven dendritic action potentials. Our results point to a surprising dependence of the effect of recurrent inhibition by Martinotti cells on their oscillatory synchronization, which may control not only the local circuit activity, but also how it is transmitted to and decoded by downstream circuits.

Dopaminergic regulation of dendritic calcium: fast multisite calcium imaging

Optimal dopamine tone is required for the normal cortical function; however it is still unclear how cortical-dopamine-release affects information processing in individual cortical neurons. Thousands of glutamatergic inputs impinge onto elaborate dendritic trees of neocortical pyramidal neurons. In the process of ensuing synaptic integration (information processing), a variety of calcium transients are generated in remote dendritic compartments. In order to understand the cellular mechanisms of dopaminergic modulation it is important to know whether and how dopaminergic signals affect dendritic calcium transients. In this chapter, we describe a relatively inexpensive method for monitoring dendritic calcium fluctuations at multiple loci across the pyramidal dendritic tree, at the same moment of time (simultaneously). The experiments have been designed to measure the amplitude, time course and spatial extent of action potential-associated dendritic calcium transients before and after application of dopaminergic drugs. In the examples provided here the dendritic calcium transients were evoked by triggering the somatic action potentials (backpropagation-evoked), and puffs of exogenous dopamine were applied locally onto selected dendritic branches.

Extrasynaptic glutamate receptor activation as cellular bases for dynamic range compression in pyramidal neurons

Repetitive synaptic stimulation overcomes the ability of astrocytic processes to clear glutamate from the extracellular space, allowing some dendritic segments to become submerged in a pool of glutamate, for a brief period of time. This dynamic arrangement activates extrasynaptic NMDA receptors located on dendritic shafts. We used voltage-sensitive and calcium-sensitive dyes to probe dendritic function in this glutamate-rich location. An excess of glutamate in the extrasynaptic space was achieved either by repetitive synaptic stimulation or by glutamate iontophoresis onto the dendrites of pyramidal neurons. Two successive activations of synaptic inputs produced a typical NMDA spike, whereas five successive synaptic inputs produced characteristic plateau potentials, reminiscent of cortical UP states. While NMDA spikes were coupled with brief calcium transients highly restricted to the glutamate input site, the dendritic plateau potentials were accompanied by calcium influx along the entire dendritic branch. Once initiated, the glutamate-mediated dendritic plateau potentials could not be interrupted by negative voltage pulses. Activation of extrasynaptic NMDA receptors in cellular compartments void of spines is sufficient to initiate and support plateau potentials. The only requirement for sustained depolarizing events is a surplus of free glutamate near a group of extrasynaptic receptors. Highly non-linear dendritic spikes (plateau potentials) are summed in a highly sublinear fashion at the soma, revealing the cellular bases of signal compression in cortical circuits. Extrasynaptic NMDA receptors provide pyramidal neurons with a function analogous to a dynamic range compression in audio engineering. They limit or reduce the volume of “loud sounds” (i.e., strong glutamatergic inputs) and amplify “quiet sounds” (i.e., glutamatergic inputs that barely cross the dendritic threshold for local spike initiation). Our data also explain why consecutive cortical UP states have uniform amplitudes in a given neuron.

Glutamate spillover promotes the generation of NMDA spikes

NMDA spikes are prominent in the basal dendrites of cortical pyramidal neurons and greatly expand their ability to integrate synaptic inputs. Calcium (Ca) signals during these spikes are important for synaptic plasticity and fundamentally depend on activation of NMDA receptors. However, the factors that shape the activation of these receptors and the initiation of NMDA spikes remain unclear. Here we examine the properties of NMDA spikes in the basal dendrites of layer 5 pyramidal neurons in the mouse prefrontal cortex. Using two-photon imaging, we demonstrate that NMDA spikes evoke large Ca signals in both postsynaptic spines and nearby dendrites. We find that the dendrite Ca signals depend on NMDA and AMPA receptors but not sodium (Na) or Ca channels. Using voltage-clamp recordings, we show that activation of dendrite NMDA receptors is enhanced by concerted synaptic activity. Blocking glutamate reuptake further increases activation of these receptors and promotes the initiation of NMDA spikes. We conclude that glutamate spillover and recruitment of extrasynaptic receptors contribute to the initiation of NMDA spikes. These results have important implications for how synaptic activity generates both electrical and biochemical signals in dendrites and spines.

Dendritic slow dynamics enables localized cortical activity to switch between mobile and immobile modes with noisy background input

Mounting lines of evidence suggest the significant computational ability of a single neuron empowered by active dendritic dynamics. This motivates us to study what functionality can be acquired by a network of such neurons. The present paper studies how such rich single-neuron dendritic dynamics affects the network dynamics, a question which has scarcely been specifically studied to date. We simulate neurons with active dendrites networked locally like cortical pyramidal neurons, and find that naturally arising localized activity--called a bump--can be in two distinct modes, mobile or immobile. The mode can be switched back and forth by transient input to the cortical network. Interestingly, this functionality arises only if each neuron is equipped with the observed slow dendritic dynamics and with in vivo-like noisy background input. If the bump activity is considered to indicate a point of attention in the sensory areas or to indicate a representation of memory in the storage areas of the cortex, this would imply that the flexible mode switching would be of great potential use for the brain as an information processing device. We derive these conclusions using a natural extension of the conventional field model, which is defined by combining two distinct fields, one representing the somatic population and the other representing the dendritic population. With this tool, we analyze the spatial distribution of the degree of after-spike adaptation and explain how we can understand the presence of the two distinct modes and switching between the modes. We also discuss the possible functional impact of this mode-switching ability.

The decade of the dendritic NMDA spike

In the field of cortical cellular physiology, much effort has been invested in understanding thick apical dendrites of pyramidal neurons and the regenerative sodium and calcium spikes that take place in the apical trunk. Here we focus on thin dendrites of pyramidal cells (basal, oblique, and tuft dendrites), and we discuss one relatively novel form of an electrical signal ("NMDA spike") that is specific for these branches. Basal, oblique, and apical tuft dendrites receive a high density of glutamatergic synaptic contacts. Synchronous activation of 10-50 neighboring glutamatergic synapses triggers a local dendritic regenerative potential, NMDA spike/plateau, which is characterized by significant local amplitude (40-50 mV) and an extraordinary duration (up to several hundred milliseconds). The NMDA plateau potential, when it is initiated in an apical tuft dendrite, is able to maintain a good portion of that tuft in a sustained depolarized state. However, if NMDA-dominated plateau potentials originate in proximal segments of basal dendrites, they regularly bring the neuronal cell body into a sustained depolarized state, which resembles a cortical Up state. At each dendritic initiation site (basal, oblique, and tuft) an NMDA spike creates favorable conditions for causal interactions of active synaptic inputs, including the spatial or temporal binding of information, as well as processes of short-term and long-term synaptic modifications (e.g., long-term potentiation or long-term depression). Because of their strong amplitudes and durations, local dendritic NMDA spikes make up the cellular substrate for multisite independent subunit computations that enrich the computational power and repertoire of cortical pyramidal cells. We propose that NMDA spikes are likely to play significant roles in cortical information processing in awake animals (spatiotemporal binding, working memory) and during slow-wave sleep (neuronal Up states, consolidation of memories).

Brief dopaminergic stimulations produce transient physiological changes in prefrontal pyramidal neurons

In response to food reward and other pertinent events, midbrain dopaminergic neurons fire short bursts of action potentials causing a phasic release of dopamine in the prefrontal cortex (rapid and transient increases in cortical dopamine concentration). Here we apply short (2s) iontophoretic pulses of glutamate, GABA, dopamine and dopaminergic agonists locally, onto layer 5 pyramidal neurons in brain slices of the rat medial prefrontal cortex (PFC). Unlike glutamate and GABA, brief dopaminergic pulses had negligible effects on the resting membrane potential. However, dopamine altered action potential firing in an extremely rapid (<1s) and transient (<5 min) manner, as every neuron returned to baseline in less than 5-min post-application. The physiological responses to dopamine differed markedly among individual neurons. Pyramidal neurons with a preponderance of D1-like receptor signaling respond to dopamine with a severe depression in action potential firing rate, while pyramidal neurons dominated by the D2 signaling pathway respond to dopamine with an instantaneous increase in spike production. Increasing levels of dopamine concentrations around the cell body resulted in a dose dependent response, which resembles an "inverted U curve" (Vijayraghavan S, Wang M, Birnbaum SG, Williams GV, Arnsten AF (2007) Inverted-U dopamine D1 receptor actions on prefrontal neurons engaged in working memory. Nat Neurosci 10:376-384), but this effect can easily be caused by an iontophoresis current artifact. Our present data imply that one population of PFC pyramidal neurons receiving direct synaptic contacts from midbrain dopaminergic neurons would stall during the 0.5s of the phasic dopamine burst. The spillover dopamine, on the other hand, would act as a positive stimulator of cortical excitability (30% increase) to all D2-receptor carrying pyramidal cells, for the next 40s.

Parallel computational subunits in dentate granule cells generate multiple place fields

A fundamental question in understanding neuronal computations is how dendritic events influence the output of the neuron. Different forms of integration of neighbouring and distributed synaptic inputs, isolated dendritic spikes and local regulation of synaptic efficacy suggest that individual dendritic branches may function as independent computational subunits. In the present paper, we study how these local computations influence the output of the neuron. Using a simple cascade model, we demonstrate that triggering somatic firing by a relatively small dendritic branch requires the amplification of local events by dendritic spiking and synaptic plasticity. The moderately branching dendritic tree of granule cells seems optimal for this computation since larger dendritic trees favor local plasticity by isolating dendritic compartments, while reliable detection of individual dendritic spikes in the soma requires a low branch number. Finally, we demonstrate that these parallel dendritic computations could contribute to the generation of multiple independent place fields of hippocampal granule cells.

Neurons were originally divided into three morphologically distinct compartments: the dendrites receive the synaptic input, the soma integrates it and communicates the output of the cell to other neurons via the axon. Although several lines of evidence challenged this oversimplified view, neurons are still considered to be the basic information processing units of the nervous system as their output reflects the computations performed by the entire dendritic tree. In the present study, the authors build a simplified computational model and calculate that, in certain neurons, relatively small dendritic branches are able to independently trigger somatic firing. Therefore, in these cells, an action potential mirrors the activity of a small dendritic subunit rather than the input arriving to the whole dendritic tree. These neurons can be regarded as a network of a few independent integrator units connected to a common output unit. The authors demonstrate that a moderately branched dendritic tree of hippocampal granule cells may be optimized for these parallel computations. Finally the authors show that these parallel dendritic computations could explain some aspects of the location dependent activity of hippocampal granule cells.

Possible dendritic contribution to unimodal numerosity tuning and weber-fechner law-dependent numerical cognition

Humans and animals are known to share an ability to estimate or compare the numerosity of visual stimuli, and this ability is considered to be supported by the cortical neurons that have unimodal tuning for numerosity, referred to as the numerosity detector neurons. How such unimodal numerosity tuning is shaped through plasticity mechanisms is unknown. Here, I propose a testable hypothetical mechanism based on recently revealed features of the neuronal dendrite, namely, cooperative plasticity induction and nonlinear input integration at nearby dendritic sites, on the basis of the existing proposal that individual visual stimuli are represented as similar localized activities regardless of the size or the shape in a cortical region in the dorsal visual pathway. Intriguingly, the proposed mechanism naturally explains a prominent feature of the numerosity detector neurons, namely, the broadening of the tuning curve in proportion to the preferred numerosity, which is considered to underlie the known Weber-Fechner law-dependent accuracy of numerosity estimation and comparison. The simulated tuning curves are less sharp than reality, however, and together with the evidence from human imaging studies that numerical representation is a distributed phenomenon, it may not be likely that the proposed mechanism operates by itself. Rather, the proposed mechanism might facilitate the formation of hierarchical circuitry proposed in the previous studies, which includes neurons with monotonic numerosity tuning as well as those with sharp unimodal tuning, by serving as an efficient initial condition.

Rapid neocortical dynamics: cellular and network mechanisms

The highly interconnected local and large-scale networks of the neocortical sheet rapidly and dynamically modulate their functional connectivity according to behavioral demands. This basic operating principle of the neocortex is mediated by the continuously changing flow of excitatory and inhibitory synaptic barrages that not only control participation of neurons in networks but also define the networks themselves. The rapid control of neuronal responsiveness via synaptic bombardment is a fundamental property of cortical dynamics that may provide the basis of diverse behaviors, including sensory perception, motor integration, working memory, and attention.

Combining voltage and calcium imaging from neuronal dendrites

The ability to monitor membrane potential (V(m)) and calcium (Ca(2+)) transients at multiple locations on the same neuron can facilitate further progress in our understanding of neuronal function. Here we describe a method to combine V(m) and Ca(2+) imaging using styryl voltage sensitive dyes and Fura type UV-excitable Ca(2+) indicators. In all cases V(m) optical signals are linear with membrane potential changes, but the calibration of optical signals on an absolute scale is presently possible only in some neurons. The interpretation of Ca(2+) optical signals depends on the indicator Ca(2+) buffering capacity relative to the cell endogenous buffering capacity. In hippocampal CA1 pyramidal neurons, loaded with JPW-3028 and 300 microM Bis-Fura-2, V(m) optical signals cannot be calibrated and the physiological Ca(2+) dynamics are compromised by the presence of the indicator. Nevertheless, at each individual site, relative changes in V (m) and Ca(2+) fluorescence signals under different conditions can provide meaningful new information on local dendritic integration. In cerebellar Purkinje neurons, loaded with JPW-1114 and 1 mM Fura-FF, V(m) optical signals can be calibrated in terms of mV and Ca(2+) optical signals quantitatively reveal the physiological changes in free Ca(2+). Using these two examples, the method is explained in detail.

Spatiotemporally Graded NMDA Spike/Plateau Potentials in Basal Dendrites of Neocortical Pyramidal Neurons

Glutamatergic inputs clustered over ∼20–40 μm can elicit local N-methyl-d-aspartate (NMDA) spike/plateau potentials in terminal dendrites of cortical pyramidal neurons, inspiring the notion that a single terminal dendrite can function as a decision-making computational subunit. A typical terminal basal dendrite is ∼100–200 μm long: could it function as multiple decision-making subunits? We test this by sequential focal stimulation of multiple sites along terminal basal dendrites of layer 5 pyramidal neurons in rat somatosensory cortical brain slices, using iontophoresis or uncaging of brief glutamate pulses. There was an approximately sevenfold spatial gradient in average spike/plateau amplitude measured at the soma, from ∼3 mV for distal inputs to ∼23 mV for proximal inputs. Spike/plateaus were NMDA receptor (NMDAR) conductance-dominated at all locations. Large Ca2+ transients accompanied spike/plateaus over a ∼10- to 40-μm zone around the input site; smaller Ca2+ transients extended approximately uniformly to the dendritic tip. Spike/plateau duration grew with increasing glutamate and depolarization; high Ca2+ zone size grew with spike/plateau duration. The minimum high Ca2+ zone half-width (just above NMDA spike threshold) increased from distal (∼10 μm) to proximal locations (∼25 μm), as did the NMDA spike glutamate threshold. Depolarization reduced glutamate thresholds. Simulations exploring multi-site interactions based on this demonstrate that if appropriately timed and localized inputs occur in vivo, a single basal dendrite could correspond to a cascade of multiple co-operating dynamic decision-making subunits able to retain information for hundreds of milliseconds, with increasing influence on neural output from distal to proximal. Dendritic NMDA spike/plateaus are thus well-suited to support graded persistent firing.

Dynamics of action potential backpropagation in basal dendrites of prefrontal cortical pyramidal neurons

Basal dendrites of neocortical pyramidal neurons are relatively short and directly attached to the cell body. This allows electrical signals arising in basal dendrites to strongly influence the neuronal output. Likewise, somatic action potentials (APs) should readily propagate back into the basilar dendritic tree to influence synaptic plasticity. Two recent studies, however, determined that sodium APs are severely attenuated in basal dendrites of cortical pyramidal cells, so that they completely fail in distal dendritic segments. Here we used the latest improvements in the voltage-sensitive dye imaging technique (Zhou et al., 2007) to study AP backpropagation in basal dendrites of layer 5 pyramidal neurons of the rat prefrontal cortex. With a signal-to-noise ratio of > 15 and minimal temporal averaging (only four sweeps) we were able to sample AP waveforms from the very last segments of individual dendritic branches (dendritic tips). We found that in short- (< 150 microm) and medium (150-200 microm in length)-range basal dendrites APs backpropagated with modest changes in AP half-width or AP rise-time. The lack of substantial changes in AP shape and dynamics of rise is inconsistent with the AP-failure model. The lack of substantial amplitude boosting of the third AP in the high-frequency burst also suggests that in short- and medium-range basal dendrites backpropagating APs were not severely attenuated. Our results show that the AP-failure concept does not apply in all basal dendrites of the rat prefrontal cortex. The majority of synaptic contacts in the basilar dendritic tree actually received significant AP-associated electrical and calcium transients.

Persistent neural activity in the prefrontal cortex: a mechanism by which BDNF regulates working memory?

Working memory is the ability to maintain representations of task-relevant information for short periods of time to guide subsequent actions or make decisions. Neurons of the prefrontal cortex exhibit persistent firing during the delay period of working memory tasks. Despite extensive studies, the mechanisms underlying this persistent neural activity remain largely obscure. The neurotransmitter systems of dopamine, NMDA, and GABA have been implicated, but further investigations are necessary to establish their precise roles and relationships. Recent research has suggested a new component: brain-derived neurotrophic factor (BDNF) and its high-affinity receptor, TrkB. We review the research on persistent activity and suggest that BDNF/TrkB signaling in a distinct class of interneurons plays an important role in organizing persistent neural activity at the single-neuron and network levels.

Voltage and calcium transients in basal dendrites of the rat prefrontal cortex

Higher cortical functions (perception, cognition, learning and memory) are in large part based on the integration of electrical and calcium signals that takes place in thin dendritic branches of neocortical pyramidal cells (synaptic integration). The mechanisms underlying the synaptic integration in thin basal dendrites are largely unexplored. We use a recently developed technique, multisite voltage-calcium imaging, to compare voltage and calcium transients from multiple locations along individual dendritic branches. Our results reveal characteristic electrical transients (plateau potentials) that trigger and shape dendritic calcium dynamics and calcium distribution during suprathreshold glutamatergic synaptic input. We regularly observed three classes of voltage-calcium interactions occurring simultaneously in three different zones of the same dendritic branch: (1) proximal to the input site, (2) at the input site, and (3) distal to the input site. One hundred micrometers away from the synaptic input site, both proximally and distally, dendritic calcium transients are in tight temporal correlation with the dendritic plateau potential. However, on the same dendrite, at the location of excitatory input, calcium transients outlast local dendritic plateau potentials by severalfold. These Ca2+ plateaus (duration 0.5-2 s) are spatially restricted to the synaptic input site, where they cause a brief down-regulation of dendritic excitability. Ca2+ plateaus are not mediated by Ca2+ release from intracellular stores, but rather by an NMDA-dependent small-amplitude depolarization, which persists after the collapse of the dendritic plateau potential. These unique features of dendritic voltage and calcium distributions may provide distinct zones for simultaneous long-term (bidirectional) modulation of synaptic contacts along the same basal branch.