Synaptic integration gradients in single cortical pyramidal cell dendrites

Cortical pyramidal neurons receive thousands of synaptic inputs arriving at different dendritic locations with varying degrees of temporal synchrony. It is not known if different locations along single cortical dendrites integrate excitatory inputs in different ways. Here we have used two-photon glutamate uncaging and compartmental modeling to reveal a gradient of nonlinear synaptic integration in basal and apical oblique dendrites of cortical pyramidal neurons. Excitatory inputs to the proximal dendrite sum linearly and require precise temporal coincidence for effective summation, whereas distal inputs are amplified with high gain and integrated over broader time windows. This allows distal inputs to overcome their electrotonic disadvantage, and become surprisingly more effective than proximal inputs at influencing action potential output. Thus, single dendritic branches can already exhibit nonuniform synaptic integration, with the computational strategy shifting from temporal coding to rate coding along the dendrite.     

The time window for generation of dendritic spikes by coincidence of action potentials and EPSPs is layer specific in somatosensory cortex

The precise timing of events in the brain has consequences for intracellular processes, synaptic plasticity, integration and network behaviour. Pyramidal neurons, the most widespread excitatory neuron of the neocortex have multiple spike initiation zones, which interact via dendritic and somatic spikes actively propagating in all directions within the dendritic tree. For these neurons, therefore, both the location and timing of synaptic inputs are critical. The time window for which the backpropagating action potential can influence dendritic spike generation has been extensively studied in layer 5 neocortical pyramidal neurons of rat somatosensory cortex. Here, we re-examine this coincidence detection window for pyramidal cell types across the rat somatosensory cortex in layers 2/3, 5 and 6. We find that the time-window for optimal interaction is widest and shifted in layer 5 pyramidal neurons relative to cells in layers 6 and 2/3. Inputs arriving at the same time and locations will therefore differentially affect spike-timing dependent processes in the different classes of pyramidal neurons.     

Do neocortical pyramidal neurons display stochastic resonance?

Neocortical pyramidal neurons in vivo are subject to an intense synaptic background activity that has a significant impact on various electrophysiological properties and dendritic integration. Using detailed biophysical models of a morphologically reconstructed neocortical pyramidal neuron, in which synaptic background activity was simulated according to recent measurements in cat parietal cortex in vivo, we show that the responsiveness of the cell to additional periodic subthreshold stimuli can be significantly enhanced through mechanisms similar to stochastic resonance. We compare several paradigms leading to stochastic resonance-like behavior, such as varying the strength or the correlation in the background activity. A new type of resonance-like behavior was obtained when the correlation was varied, in which case the responsiveness is sensitive to the statistics rather than the strength of the noise. We suggest that this type of resonance may be relevant to information processing in the cerebral cortex.     

Glutamate-Bound NMDARs Arising from In Vivo-like Network Activity Extend Spatio-temporal Integration in a L5 Cortical Pyramidal Cell Model

In vivo, cortical pyramidal cells are bombarded by asynchronous synaptic input arising from ongoing network activity. However, little is known about how such ‘background’ synaptic input interacts with nonlinear dendritic mechanisms. We have modified an existing model of a layer 5 (L5) pyramidal cell to explore how dendritic integration in the apical dendritic tuft could be altered by the levels of network activity observed in vivo. Here we show that asynchronous background excitatory input increases neuronal gain and extends both temporal and spatial integration of stimulus-evoked synaptic input onto the dendritic tuft. Addition of fast and slow inhibitory synaptic conductances, with properties similar to those from dendritic targeting interneurons, that provided a ‘balanced’ background configuration, partially counteracted these effects, suggesting that inhibition can tune spatio-temporal integration in the tuft. Excitatory background input lowered the threshold for NMDA receptor-mediated dendritic spikes, extended their duration and increased the probability of additional regenerative events occurring in neighbouring branches. These effects were also observed in a passive model where all the non-synaptic voltage-gated conductances were removed. Our results show that glutamate-bound NMDA receptors arising from ongoing network activity can provide a powerful spatially distributed nonlinear dendritic conductance. This may enable L5 pyramidal cells to change their integrative properties as a function of local network activity, potentially allowing both clustered and spatially distributed synaptic inputs to be integrated over extended timescales.     

Physiology of Layer 5 Pyramidal Neurons in Mouse Primary Visual Cortex: Coincidence Detection through Bursting

L5 pyramidal neurons are the only neocortical cell type with dendrites reaching all six layers of cortex, casting them as one of the main integrators in the cortical column. What is the nature and mode of computation performed in mouse primary visual cortex (V1) given the physiology of L5 pyramidal neurons? First, we experimentally establish active properties of the dendrites of L5 pyramidal neurons of mouse V1 using patch-clamp recordings. Using a detailed multi-compartmental model, we show this physiological setup to be well suited for coincidence detection between basal and apical tuft inputs by controlling the frequency of spike output. We further show how direct inhibition of calcium channels in the dendrites modulates such coincidence detection. To establish the singe-cell computation that this biophysics supports, we show that the combination of frequency-modulation of somatic output by tuft input and (simulated) calcium-channel blockage functionally acts as a composite sigmoidal function. Finally, we explore how this computation provides a mechanism whereby dendritic spiking contributes to orientation tuning in pyramidal neurons.     

Hippocampal Feedforward Inhibition Focuses Excitatory Synaptic Signals into Distinct Dendritic Compartments

Feedforward inhibition controls the time window for synaptic integration and ensures temporal precision in cortical circuits. There is little information whether feedforward inhibition affects neurons uniformly, or whether it contributes to computational refinement within the dendritic tree. Here we demonstrate that feedforward inhibition crucially shapes the integration of synaptic signals in pyramidal cell dendrites. Using voltage-sensitive dye imaging we studied the transmembrane voltage patterns in CA1 pyramidal neurons after Schaffer collateral stimulation in acute brain slices from mice. We observed a high degree of variability in the excitation-inhibition ratio between different branches of the dendritic tree. Many dendritic segments showed no depolarizing signal at all, especially the basal dendrites that received predominantly inhibitory signals. Application of the GABA_A receptor antagonist bicuculline resulted in the spread of depolarizing signals throughout the dendritic tree. Tetanic stimulation of Schaffer collateral inputs induced significant alterations in the patterns of excitation/inhibition, indicating that they are modified by synaptic plasticity. In summary, we show that feedforward inhibition restricts the occurrence of depolarizing signals within the dendritic tree of CA1 pyramidal neurons and thus refines signal integration spatially.     

Spike timing and reliability in cortical pyramidal neurons: effects of EPSC kinetics, input synchronization and background noise on spike timing

In vivo studies have shown that neurons in the neocortex can generate action potentials at high temporal precision. The mechanisms controlling timing and reliability of action potential generation in neocortical neurons, however, are still poorly understood. Here we investigated the temporal precision and reliability of spike firing in cortical layer V pyramidal cells at near-threshold membrane potentials. Timing and reliability of spike responses were a function of EPSC kinetics, temporal jitter of population excitatory inputs, and of background synaptic noise. We used somatic current injection to mimic population synaptic input events and measured spike probability and spike time precision (STP), the latter defined as the time window (Deltat) holding 80% of response spikes. EPSC rise and decay times were varied over the known physiological spectrum. At spike threshold level, EPSC decay time had a stronger influence on STP than rise time. Generally, STP was highest (6 ms) triggered spikes at lower temporal precision (>or=6.58 ms). We found an overall linear relationship between STP and spike delay. The difference in STP between fast and slow compound EPSCs could be reduced by incrementing the amplitude of slow compound EPSCs. The introduction of a temporal jitter to compound EPSCs had a comparatively small effect on STP, with a tenfold increase in jitter resulting in only a five fold decrease in STP. In the presence of simulated synaptic background activity, precisely timed spikes could still be induced by fast EPSCs, but not by slow EPSCs.     

LOTOS-based two-photon calcium imaging of dendritic spines in vivo

Neurons in the mammalian brain receive thousands of synaptic inputs on their dendrites. In many types of neurons, such as cortical pyramidal neurons, excitatory synapses are formed on fine dendritic protrusions called spines. Usually, an individual spine forms a single synaptic contact with an afferent axon. In this protocol, we describe a recently established experimental procedure for measuring intracellular calcium signals from dendritic spines in cortical neurons in vivo by using a combination of two-photon microscopy and whole-cell patch-clamp recordings. We have used mice as an experimental model system, but the protocol may be readily adapted to other species. This method involves data acquisition at high frame rates and low-excitation laser power, and is termed low-power temporal oversampling (LOTOS). Because of its high sensitivity of fluorescence detection and reduced phototoxicity, LOTOS allows for prolonged and stable calcium imaging in vivo. Key aspects of the protocol, which can be completed in 5-6 h, include the use of a variant of high-speed two-photon imaging, refined surgery procedures and optimized tissue stabilization.     

Gain modulation from background synaptic input

Gain modulation is a prominent feature of neuronal activity recorded in behaving animals, but the mechanism by which it occurs is unknown. By introducing a barrage of excitatory and inhibitory synaptic conductances that mimics conditions encountered in vivo into pyramidal neurons in slices of rat somatosensory cortex, we show that the gain of a neuronal response to excitatory drive can be modulated by varying the level of "background" synaptic input. Simultaneously increasing both excitatory and inhibitory background firing rates in a balanced manner results in a divisive gain modulation of the neuronal response without appreciable signal-independent increases in firing rate or spike-train variability. These results suggest that, within active cortical circuits, the overall level of synaptic input to a neuron acts as a gain control signal that modulates responsiveness to excitatory drive.     

Encoding of spatio-temporal input characteristics by a CA1 pyramidal neuron model

The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing. For long delays, the average firing frequency of the model response discriminates spatially clustered from diffused inputs to the distal dendritic tree. For short delays, the onset latency and inter-spike-interval succession of model responses can accurately classify input signals as temporally close or distant and spatially clustered or diffused across different stimulation protocols. These findings suggest that a CA1 pyramidal neuron may be capable of encoding and transmitting presynaptic spatiotemporal information about the activity of the entorhinal cortex-hippocampal network to higher brain regions via the selective use of either a temporal or a rate code.     

Notch Signaling Activation Promotes Seizure Activity in Temporal Lobe Epilepsy

Notch signaling in the nervous system is often regarded as a developmental pathway. However, recent studies have suggested that Notch is associated with neuronal discharges. Here, focusing on temporal lobe epilepsy, we found that Notch signaling was activated in the kainic acid (KA)-induced epilepsy model and in human epileptogenic tissues. Using an acute model of seizures, we showed that DAPT, an inhibitor of Notch, inhibited ictal activity. In contrast, pretreatment with exogenous Jagged1 to elevate Notch signaling before KA application had proconvulsant effects. In vivo, we demonstrated that the impacts of activated Notch signaling on seizures can in part be attributed to the regulatory role of Notch signaling on excitatory synaptic activity in CA1 pyramidal neurons. In vitro, we found that DAPT treatment impaired synaptic vesicle endocytosis in cultured hippocampal neurons. Taken together, our findings suggest a correlation between aberrant Notch signaling and epileptic seizures. Notch signaling is up-regulated in response to seizure activity, and its activation further promotes neuronal excitation of CA1 pyramidal neurons in acute seizures.     

A behavioral role for dendritic integration: HCN1 channels constrain spatial memory and plasticity at inputs to distal dendrites of CA1 pyramidal neurons

The importance of long-term synaptic plasticity as a cellular substrate for learning and memory is well established. By contrast, little is known about how learning and memory are regulated by voltage-gated ion channels that integrate synaptic information. We investigated this question using mice with general or forebrain-restricted knockout of the HCN1 gene, which we find encodes a major component of the hyperpolarization-activated inward current (Ih) and is an important determinant of dendritic integration in hippocampal CA1 pyramidal cells. Deletion of HCN1 from forebrain neurons enhances hippocampal-dependent learning and memory, augments the power of theta oscillations, and enhances long-term potentiation (LTP) at the direct perforant path input to the distal dendrites of CA1 pyramidal neurons, but has little effect on LTP at the more proximal Schaffer collateral inputs. We suggest that HCN1 channels constrain learning and memory by regulating dendritic integration of distal synaptic inputs to pyramidal cells.     

In vivo analysis of inhibitory synaptic inputs and rebounds in deep cerebellar nuclear neurons

Neuronal function depends on the properties of the synaptic inputs the neuron receive and on its intrinsic responsive properties. However, the conditions for synaptic integration and activation of intrinsic responses may to a large extent depend on the level of background synaptic input. In this respect, the deep cerebellar nuclear (DCN) neurons are of particular interest: they feature a massive background synaptic input and an intrinsic, postinhibitory rebound depolarization with profound effects on the synaptic integration. Using in vivo whole cell patch clamp recordings from DCN cells in the cat, we find that the background of Purkinje cell input provides a tonic inhibitory synaptic noise in the DCN cell. Under these conditions, individual Purkinje cells appear to have a near negligible influence on the DCN cell and clear-cut rebounds are difficult to induce. Peripheral input that drives the simple spike output of the afferent PCs to the DCN cell generates a relatively strong DCN cell inhibition, but do not induce rebounds. In contrast, synchronized climbing fiber activation, which leads to a synchronized input from a large number of Purkinje cells, can induce profound rebound responses. In light of what is known about climbing fiber activation under behaviour, the present findings suggest that DCN cell rebound responses may be an unusual event. Our results also suggest that cortical modulation of DCN cell output require a substantial co-modulation of a large proportion of the PCs that innervate the cell, which is a possible rationale for the existence of the cerebellar microcomplex.     

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.     

Non-associative Potentiation of Perisomatic Inhibition Alters the Temporal Coding of Neocortical Layer 5 Pyramidal Neurons

In the neocortex, the coexistence of temporally locked excitation and inhibition governs complex network activity underlying cognitive functions, and is believed to be altered in several brain diseases. Here we show that this equilibrium can be unlocked by increased activity of layer 5 pyramidal neurons of the mouse neocortex. Somatic depolarization or short bursts of action potentials of layer 5 pyramidal neurons induced a selective long-term potentiation of GABAergic synapses (LTPi) without affecting glutamatergic inputs. Remarkably, LTPi was selective for perisomatic inhibition from parvalbumin basket cells, leaving dendritic inhibition intact. It relied on retrograde signaling of nitric oxide, which persistently altered presynaptic GABA release and diffused to inhibitory synapses impinging on adjacent pyramidal neurons. LTPi reduced the time window of synaptic summation and increased the temporal precision of spike generation. Thus, increases in single cortical pyramidal neuron activity can induce an interneuron-selective GABAergic plasticity effectively altering the computation of temporally coded information.     

Dense inhibitory connectivity in neocortex

The connectivity diagram of neocortical circuits is still unknown, and there are conflicting data as to whether cortical neurons are wired specifically or not. To investigate the basic structure of cortical microcircuits, we use a two-photon photostimulation technique that enables the systematic mapping of synaptic connections with single-cell resolution. We map the inhibitory connectivity between upper layers somatostatin-positive GABAergic interneurons and pyramidal cells in mouse frontal cortex. Most, and sometimes all, inhibitory neurons are locally connected to every sampled pyramidal cell. This dense inhibitory connectivity is found at both young and mature developmental ages. Inhibitory innervation of neighboring pyramidal cells is similar, regardless of whether they are connected among themselves or not. We conclude that local inhibitory connectivity is promiscuous, does not form subnetworks, and can approach the theoretical limit of a completely connected synaptic matrix.     

A major role for intracortical circuits in the strength and tuning of odor-evoked excitation in olfactory cortex

In primary sensory cortices, there are two main sources of excitation: afferent sensory input relayed from the periphery and recurrent intracortical input. Untangling the functional roles of these two excitatory pathways is fundamental for understanding how cortical neurons process sensory stimuli. Odor representations in the primary olfactory (piriform) cortex depend on excitatory sensory afferents from the olfactory bulb. However, piriform cortex pyramidal cells also receive dense intracortical excitatory connections, and the relative contribution of these two pathways to odor responses is unclear. Using a combination of in vivo whole-cell voltage-clamp recording and selective synaptic silencing, we show that the recruitment of intracortical input, rather than olfactory bulb input, largely determines the strength of odor-evoked excitatory synaptic transmission in rat piriform cortical neurons. Furthermore, we find that intracortical synapses dominate odor-evoked excitatory transmission in broadly tuned neurons, whereas bulbar synapses dominate excitatory synaptic responses in more narrowly tuned neurons.     

Enhancement of spike-timing precision by autaptic transmission in neocortical inhibitory interneurons

In vivo studies suggest that precise firing of neurons is important for correct sensory representation. Principal neocortical neurons fire imprecisely when repeatedly activated by fixed sensory stimuli or current depolarizations. Here we show that in contrast to pyramidal neurons, firing in neocortical GABAergic fast-spiking (FS) interneurons is quite precise. FS interneurons are self-innervated by powerful GABAergic autaptic connections reliably activated after each spike, suggesting that autapses strongly regulate FS-cell spike timing. Indeed, blockade of autaptic transmission degraded temporal precision in multiple ways. Under these conditions, realistic dynamic-clamp hyperpolarizing autapses restored precision of spike timing, even in the presence of synaptic noise. Furthermore, firing precision was increased in pyramidal neurons by artificial GABAergic autaptic conductances, suggesting that tightly coupled synaptic feedback inhibition regulates spike timing in principal cells. Thus, well-timed inhibition, whether autaptic or synaptic, facilitates precise spike timing and promotes synchronized cortical network oscillations relevant to several behaviors.     

Short-Term Synaptic Plasticity Orchestrates the Response of Pyramidal Cells and Interneurons to Population Bursts

The synaptic drive from neuronal populations varies considerably over short time scales. Such changes in the pre-synaptic rate trigger many temporal processes absent under steady-state conditions. This paper examines the differential impact of pyramidal cell population bursts on post-synaptic pyramidal cells receiving depressing synapses, and on a class of interneuron that receives facilitating synapses. In experiment a significant shift of the order of one hundred milliseconds is seen between the response of these two cell classes to the same population burst. It is demonstrated here that such a temporal differentiation of the response can be explained by the synaptic and membrane properties without recourse to elaborate cortical wiring schemes. Experimental data is first used to construct models of the two types of dynamic synaptic response. A population-based approach is then followed to examine analytically the temporal synaptic filtering effects of the population burst for the two post-synaptic targets. The peak-to-peak delays seen in experiment can be captured by the model for experimentally realistic parameter ranges. It is further shown that the temporal separation of the response is communicated in the outgoing action potentials of the two post-synaptic cells: pyramidal cells fire at the beginning of the burst and the class of interneuron receiving facilitating synapses fires at the end of the burst. The functional role of such delays in the temporal organisation of activity in the cortical microcircuit is discussed.