Regular Spiking Research Articles

Hippocampal Pyramidal Neurons Comprise Two Distinct Cell Types that Are Countermodulated by Metabotropic Receptors

Relating the function of neuronal cell types to information processing and behavior is a central goal of neuroscience. In the hippocampus, pyramidal cells in CA1 and the subiculum process sensory and motor cues to form a cognitive map encoding spatial, contextual, and emotional information, which they transmit throughout the brain. Do these cells constitute a single class or are there multiple cell types with specialized functions? Using unbiased cluster analysis, we show that there are two morphologically and electrophysiologically distinct principal cell types that carry hippocampal output. We show further that these two cell types are inversely modulated by the synergistic action of glutamate and acetylcholine acting on metabotropic receptors that are central to hippocampal function. Combined with prior connectivity studies, our results support a model of hippocampal processing in which the two pyramidal cell types are predominantly segregated into two parallel pathways that process distinct modalities of information.

Morphology, PKCδ expression, and synaptic responsiveness of different types of rat central lateral amygdala neurons

Recent findings implicate the central lateral amygdala (CeL) in conditioned fear. Indeed, CeL contains neurons exhibiting positive (CeL-On) or negative (CeL-Off) responses to fear-inducing conditioned stimuli (CSs). In mice, these cells differ in their expression of protein kinase Cδ (PKCδ) and physiological properties. CeL-Off cells are PKCδ(+) and late firing (LF), whereas CeL-On cells are PKCδ(-) and express a regular-spiking (RS) or low-threshold bursting (LTB) phenotype. However, the scarcity of LF cells in rats raises questions about the correspondence between the organization of CeL in mice and rats. Therefore, we studied the PKCδ expression, morphological properties, synaptic responsiveness, and fear conditioning-induced plasticity of rat CeL neurons. No PKCδ(+) LF cells were encountered, but ≈20-25% of RS and LTB neurons were PKCδ(+). Compared with RS neurons, a higher proportion of LTB cells projected to central medial amygdala (CeM) and they had fewer primary dendritic branches, yet the amplitude of excitatory postsynaptic potentials (EPSPs) evoked by lateral amygdala (LA) stimulation was similar in RS and LTB cells. In contrast, LA-evoked inhibitory postsynaptic potentials (IPSPs) had a higher amplitude in LTB than RS neurons. Finally, fear conditioning did not induce plasticity at LA inputs to RS or LTB neurons. These findings point to major species differences in the organization of CeL. Since rat LTB cells are subjected to stronger feedforward inhibition, they are more likely to exhibit inhibitory CS responses than RS cells. This is expected to cause a disinhibition of CeM fear output neurons and therefore an increase in fear expression.

Role of Ih in the firing pattern of mammalian cold thermoreceptor endings

Mammalian peripheral cold thermoreceptors respond to cooling of their sensory endings with an increase in firing rate and modification of their discharge pattern. We recently showed that cultured trigeminal cold-sensitive (CS) neurons express a prominent hyperpolarization-activated current (I(h)), mainly carried by HCN1 channels, supporting subthreshold resonance in the soma without participating in the response to acute cooling. However, peripheral pharmacological blockade of I(h), or characterization of HCN1(-/-) mice, reveals a deficit in acute cold detection. Here we investigated the role of I(h) in CS nerve endings, where cold sensory transduction actually takes place. Corneal CS nerve endings in mice show a rhythmic spiking activity at neutral skin temperature that switches to bursting mode when the temperature is lowered. I(h) blockers ZD7288 and ivabradine alter firing patterns of CS nerve endings, lengthening interspike intervals and inducing bursts at neutral skin temperature. We characterized the CS nerve endings from HCN1(-/-) mouse corneas and found that they behave similar to wild type, although with a lower slope in the firing frequency vs. temperature relationship, thus explaining the deficit in cold perception of HCN1(-/-) mice. The firing pattern of nerve endings from HCN1(-/-) mice was also affected by ZD7288, which we attribute to the presence of HCN2 channels in the place of HCN1. Mathematical modeling shows that the firing phenotype of CS nerve endings from HCN1(-/-) mice can be reproduced by replacing HCN1 channels with the slower HCN2 channels rather than by abolishing I(h). We propose that I(h) carried by HCN1 channels helps tune the frequency of the oscillation and the length of bursts underlying regular spiking in cold thermoreceptors, having important implications for neural coding of cold sensation.

Correlated discharges in the primate prefrontal cortex before and after working memory training

The correlation of discharges between single neurons can provide information about the computations and network properties of neuronal populations during the performance of cognitive tasks. In recent years, dynamic modulation of neuronal correlations by attention has been revealed during the execution of behavioral tasks. Much less is known about the influence of learning and performing a task itself. We therefore sought to quantify the correlated firing of simultaneously recorded pairs of neurons in the prefrontal cortex of naïve monkeys that were only required to fixate, and to examine how this correlation was altered after they had learned to perform a working memory task. We found that the trial-to-trial correlation of discharge rates between pairs of neurons (noise correlation) differed across neurons depending on their responsiveness and selectivity for stimuli, even before training in a working memory task. After monkeys had learned to perform the task, correlated firing decreased overall, although the effects varied according to the functional properties of the neurons. The greatest decreases were observed on comparison of populations of neurons that exhibited elevated firing rates during the trial events and those that had more similar spatial and temporal tuning. Greater decreases in noise correlation were also observed for pairs comprising one fast spiking neuron (putative interneuron) and one regular spiking neuron (putative pyramidal neuron) than pairs comprising regular spiking neurons only. Our results demonstrate that learning and performance of a cognitive task alters the correlation structure of neuronal firing in the prefrontal cortex.

Individual and collective properties of computationally efficient motoneuron models of types S and F with active dendrites

The input–output properties of motoneurons (MNs) and motor units (MUs) may be modulated by different physiological variables, including neuromodulators released by presynaptic neurons from the brainstem. Monoamines, such as serotonin and norepinephrine, act on MNs mainly by activating dendritic L-type Ca++ channels, generating a persistent inward current (PIC), which may change the input–output properties of the MU. If the firing properties of individual MNs and also the features of the force generated by the MUs can be changed, it follows that the descending monoaminergic systems may modulate the overall dynamics of motor control. The purpose of the present study is to investigate the effects of neuromodulation on the input–output properties of mathematically modeled type-specified MUs. Computationally efficient models are presented for S- and F-type mammalian MNs as well as a MN pool commanding muscle units of the Soleus muscle. The single models have a dendritic L-type Ca++ channel, generating a PIC, along with somatic currents that are responsible for spike-generating mechanisms and the afterhyperpolarization. The S-type active-dendrite (AD) MN model resulted highly excitable and discharged in a self-sustained manner after an excitatory input (bistability). An inhibitory activity turned off this self-sustained discharge. In addition, this low-threshold MN model showed a significant reduction in interspike interval (ISI) variability in comparison with an equivalent passive-dendrite (PD) MN model discharging at a similar mean rate. The frequency response gain from presynaptic spike train rate modulation to output spike train modulation had a clear valley from about 1–10Hz for the S-type AD MN model, whereas the PD model showed a gain increase instead. On the other hand, the frequency responses of PD and AD F-type models were similarly shaped, with the AD model having a higher gain at high frequencies. These results suggest that in motor behaviors where steady or low frequency activity is required, such as posture, PICs would aid low-threshold MNs to respond with regular spikes, reducing output variability, and would attenuate the effects of high-frequency input disturbances, helping maintain system steadiness. At the same time, high-threshold MNs being more responsive to high-frequency disturbances would contribute with the necessary activity to correct for postural deviations from a desired position. Simulation results from the neuromuscular model have shown that the PIC activation profoundly affects muscle force generation, with the neuromodulatory activity acting in the adjustment of the motor output. Both individual and collective results presented here expand the understanding of the versatility of monoaminergic neuromodulation in adjusting both the MN input–output coding and the control of force generation.

M-channels modulate the intrinsic excitability and synaptic responses of layer 2/3 pyramidal neurons in auditory cortex

Neurons in the auditory cortex are believed to utilize temporal patterns of neural activity to accurately process auditory information but the intrinsic neuronal mechanism underlying the control of auditory neural activity is not known. The slowly activating, persistent K+ channel, also called M-channel that belongs to the Kv7 family, is already known to be important in regulating subthreshold neural excitability and synaptic summation in neocortical and hippocampal pyramidal neurons. However, its functional role in the primary auditory cortex (A1) has never been characterized. In this study, we investigated the roles of M-channels on neuronal excitability, short-term plasticity, and synaptic summation of A1 layer 2/3 regular spiking pyramidal neurons with whole-cell current-clamp recordings in vitro. We found that blocking M-channels with a selective M-channel blocker, XE991, significantly increased neural excitability of A1 layer 2/3 pyramidal neurons. Furthermore, M-channels controled synaptic responses of intralaminar-evoked excitatory postsynaptic potentials (EPSPs); XE991 significantly increased EPSP amplitude, decreased the rate of short-term depression, and increased the synaptic summation. These results suggest that M-channels are involved in controlling spike output patterns and synaptic responses of A1 layer 2/3 pyramidal neurons, which would have important implications in auditory information processing.

Spike-Timing-Dependent Potentiation of Sensory Surround in the Somatosensory Cortex Is Facilitated by Deprivation-Mediated Disinhibition

Functional maps in the cerebral cortex reorganize in response to changes in experience, but the synaptic underpinnings remain uncertain. Here, we demonstrate that layer (L) 2/3 pyramidal cell synapses in mouse barrel cortex can be potentiated upon pairing of whisker-evoked postsynaptic potentials (PSPs) with action potentials (APs). This spike-timing-dependent long-term potentiation (STD-LTP) was only effective for PSPs evoked by deflections of a whisker in the neuron's receptive field center, and not its surround. Trimming of all except two whiskers rapidly opened the possibility to drive STD-LTP by the spared surround whisker. This facilitated STD-LTP was associated with a strong decrease in the surrounding whisker-evoked inhibitory conductance and partially occluded picrotoxin-mediated LTP facilitation. Taken together, our data demonstrate that sensory deprivation-mediated disinhibition facilitates STD-LTP from the sensory surround, which may promote correlation- and experience-dependent expansion of receptive fields.

Determinants of associative memory performance in spiking and non-spiking neural networks with different synaptic plasticity regimes

The majority of experimental studies of synaptic plasticity in the brain have focussed on modifiable connections between excitatory neurons. However, recent developments in the area of inhibitory synaptic plasticity are challenging the view that inhibitory interneurons provide a purely regulatory role [1]. One such example is the observation that endocannabinoid mediated plasticity in GABAergic synapses may be source and target specific (both in terms of identity and location of pre and postsynaptic neurons), allowing for the suppression of inhibition in specific cortical layers and cell types [2]. Moreover, it has recently been shown that inhibitory synaptic plasticity can help balance excitation and inhibition and support the storage and retrieval of memories in recurrent neural networks [3]. In the present study, we explore the effect of different types of synaptic plasticity and other neuronal characteristics on memory performance in neural networks with excitatory and inhibitory subpopulations. In an initial set of simulations, we investigate the performance of networks of perceptrons with a variety of permitted synaptic plasticity regimes. We then extend this work using similarly configured networks of Izhikevich neurons, and we study how the capacity of these networks is affected by synaptic parameters and neuronal firing patterns. The networks are trained using a modified version of the perceptron learning rule that enforces sign constraints, allowing model neurons to be labelled as excitatory or inhibitory. The retrieval of memories is tested by setting the initial state of the network to a corrupted version of the training pattern. In the non-spiking networks the network is allowed to settle into a steady state. In the networks of spiking neurons, we run the simulation for a fixed period of time and measure the performance by moving a sliding window across the firing trace to produce a set of firing vectors. These are compared to the uncorrupted training pattern and the firing vector with the highest similarity is selected. This process is carried out under increasing load (numbers of stored patterns) until the mean similarity across all tested patterns at a particular load p is < 95%. The effective capacity (the performance metric) is then said to be p – 1. Although a sufficient degree of synaptic plasticity in the networks is required for them to act as associative memories, we find that a lack of plasticity can be tolerated in subsets of synapses. In particular, networks without plasticity at inhibitory-to-inhibitory synapses still perform well, with an effective capacity that is influenced by the weight of the non-plastic connections. Moreover, in the networks of spiking neurons the performance is strongly dependent on synaptic parameters such as decay and scaling, the types of neurons used in the inhibitory and excitatory subpopulations (such as regular or fast spiking neurons), and the sparsity of the training patterns.

The role of voltage dependence of the NMDA receptor in cellular and network oscillation

Unraveling the mechanisms underlying oscillatory behavior is critical for understanding normal and pathological brain processes. Here we used electrophysiology in mouse neocortical slices and principles of nonlinear dynamics to demonstrate how an increase in the N-methyl-d-aspartic acid receptor (NMDAR) conductance can create a nonlinear whole-cell current-voltage (I-V) relationship which leads to changes in cellular stability. We discovered two behaviorally and morphologically distinct pyramidal cell populations. Under control conditions, both cell types responded to depolarizing current injection with regular spiking patterns. However, upon NMDAR activation, an intrinsic oscillatory (IO) cell type (n = 44) showed a nonlinear whole-cell I-V relationship, intrinsic voltage-dependent oscillations plus amplification of alternating input current, and these properties persisted after disabling action potential generation with tetrodotoxin (TTX). The other non-oscillatory (NO) neuronal population (n = 24) demonstrated none of these behaviors. Simultaneous intra- and extracellular recordings demonstrated the NMDAR's capacity to promote low-frequency seizure-like network oscillations via its effects on intrinsic neuronal properties. The two pyramidal cell types demonstrated different relationships with network oscillation--the IO cells were leaders that were activated early in the population activity cycle while the activation of the NO cell type was distributed across network bursts. The properties of IO neurons disappeared in a low-magnesium environment where the voltage dependence of the receptor is abolished; concurrently, the cellular contribution to network oscillation switched to synchronous firing. Thus, depending upon the efficacy of NMDAR in altering the linearity of the whole-cell I-V relationship, the two cell populations played different roles in sustaining network oscillation.

Predictive Features of Persistent Activity Emergence in Regular Spiking and Intrinsic Bursting Model Neurons

Proper functioning of working memory involves the expression of stimulus-selective persistent activity in pyramidal neurons of the prefrontal cortex (PFC), which refers to neural activity that persists for seconds beyond the end of the stimulus. The mechanisms which PFC pyramidal neurons use to discriminate between preferred vs. neutral inputs at the cellular level are largely unknown. Moreover, the presence of pyramidal cell subtypes with different firing patterns, such as regular spiking and intrinsic bursting, raises the question as to what their distinct role might be in persistent firing in the PFC. Here, we use a compartmental modeling approach to search for discriminatory features in the properties of incoming stimuli to a PFC pyramidal neuron and/or its response that signal which of these stimuli will result in persistent activity emergence. Furthermore, we use our modeling approach to study cell-type specific differences in persistent activity properties, via implementing a regular spiking (RS) and an intrinsic bursting (IB) model neuron. We identify synaptic location within the basal dendrites as a feature of stimulus selectivity. Specifically, persistent activity-inducing stimuli consist of activated synapses that are located more distally from the soma compared to non-inducing stimuli, in both model cells. In addition, the action potential (AP) latency and the first few inter-spike-intervals of the neuronal response can be used to reliably detect inducing vs. non-inducing inputs, suggesting a potential mechanism by which downstream neurons can rapidly decode the upcoming emergence of persistent activity. While the two model neurons did not differ in the coding features of persistent activity emergence, the properties of persistent activity, such as the firing pattern and the duration of temporally-restricted persistent activity were distinct. Collectively, our results pinpoint to specific features of the neuronal response to a given stimulus that code for its ability to induce persistent activity and predict differential roles of RS and IB neurons in persistent activity expression.

Electrophysiological and morphological properties of neurons in layer 5 of the rat postrhinal cortex.

The postrhinal (POR) cortex of the rat is homologous to the parahippocampal cortex of the primate based on connections and other criteria. POR provides the major visual and visuospatial input to the hippocampal formation, both directly to CA1 and indirectly through connections with the medial entorhinal cortex. Although the cortical and hippocampal connections of the POR cortex are well described, the physiology of POR neurons has not been studied. Here, we examined the electrical and morphological characteristics of layer 5 neurons from POR cortex of 14- to 16-day-old rats using an in vitro slice preparation. Neurons were subjectively classified as regular-spiking (RS), fast-spiking (FS), or low-threshold spiking (LTS) based on their electrophysiological properties and similarities with neurons in other regions of neocortex. Cells stained with biocytin included pyramidal cells and interneurons with bitufted or multipolar dendritic patterns. Similarity analysis using only physiological data yielded three clusters that corresponded to FS, LTS, and RS classes. The cluster corresponding to the FS class was composed entirely of multipolar nonpyramidal cells, and the cluster corresponding to the RS class was composed entirely of pyramidal cells. The third cluster, corresponding to the LTS class, was heterogeneous and included both multipolar and bitufted dendritic arbors as well as one pyramidal cell. We did not observe any intrinsically bursting pyramidal cells, which is similar to entorhinal cortex but unlike perirhinal cortex. We conclude that POR includes at least two major classes of neocortical inhibitory interneurons, but has a functionally restricted cohort of pyramidal cells.

Electrophysiological classes of layer 2/3 pyramidal cells in monkey prefrontal cortex

The activity of supragranular pyramidal neurons in the dorsolateral prefrontal cortex (DLPFC) neurons is hypothesized to be a key contributor to the cellular basis of working memory in primates. Therefore, the intrinsic membrane properties, a crucial determinant of a neuron's functional properties, are important for the role of DLPFC pyramidal neurons in working memory. The present study aimed to investigate the biophysical properties of pyramidal cells in layer 2/3 of monkey DLPFC to create an unbiased electrophysiological classification of these cells. Whole cell voltage recordings in the slice preparation were performed in 77 pyramidal cells, and 24 electrophysiological measures of their passive and active intrinsic membrane properties were analyzed. Based on the results of cluster analysis of 16 independent electrophysiological variables, 4 distinct electrophysiological classes of monkey pyramidal cells were determined. Two classes contain regular-spiking neurons with low and high excitability and constitute 52% of the pyramidal cells sampled. These subclasses of regular-spiking neurons mostly differ in their input resistance, minimum current that evoked firing, and current-to-frequency transduction properties. A third class of pyramidal cells includes low-threshold spiking cells (17%), which fire a burst of three-five spikes followed by regular firing at all suprathreshold current intensities. The last class consists of cells with an intermediate firing pattern (31%). These cells have two modes of firing response, regular spiking and bursting discharge, depending on the strength of stimulation and resting membrane potential. Our results show that diversity in the functional properties of DLPFC pyramidal cells may contribute to heterogeneous modes of information processing during working memory and other cognitive operations that engage the activity of cortical circuits in the superficial layers of the DLPFC.

Emergence of criticality in different topologies of networks of map-based neurons

KTz model is a three-dimensional map representing the action potential, a recovery and a slow variable, and exhibits the usual excitable cells behaviors (fast and regular spiking, bursting, etc). When we connect KTz’s units in different topologies with a probabilistic two-dimensional Chemical Synapse Map (CSM) we obtain spike avalanches, which is a number of connected neurons spiking one after another. The critical systems show a power law distribution of avalanches, and this is also a signature of Self-Organized Criticality (SOC). In vitro systems have shown neuronal avalanches. Comparisons between LFP recordings in monkeys performing a short term memory task and three subsampled SOC models are available in the literature, as well as in vivo data from rats and a cellular automaton model. These results are promising, and show close connection between critical models and neuronal activity. We simulate KTz neurons connected through CSM on different types of networks (square, scale-free, small world) and our preliminary results show criticality in the square lattice. Random topologies are under check, and they may be of close interest of the medical community, since they can be related to the development of some neural diseases.

Functional alterations in GABAergic fast-spiking interneurons in chronically injured epileptogenic neocortex

Progress toward developing effective prophylaxis and treatment of posttraumatic epilepsy depends on a detailed understanding of the basic underlying mechanisms. One important factor contributing to epileptogenesis is decreased efficacy of GABAergic inhibition. Here we tested the hypothesis that the output of neocortical fast-spiking (FS) interneurons onto postsynaptic targets would be decreased in the undercut (UC) model of chronic posttraumatic epileptogenesis. Using dual whole-cell recordings in layer IV barrel cortex, we found a marked increase in the failure rate and a very large reduction in the amplitude of unitary inhibitory postsynaptic currents (uIPSCs) from FS cells to excitatory regular spiking (RS) neurons and neighboring FS cells. Assessment of the paired pulse ratio and presumed quantal release showed that there was a significant, but relatively modest, decrease in synaptic release probability and a non-significant reduction in quantal size. A reduced density of boutons on axons of biocytin-filled UC FS cells, together with a higher coefficient of variation of uIPSC amplitude in RS cells, suggested that the number of functional synapses presynaptically formed by FS cells may be reduced. Given the marked reduction in synaptic strength, other defects in the presynaptic vesicle release machinery likely occur, as well.

Network activity and spike discharge oscillations in cortical slice cultures from neonatal rat

Network bursts and oscillations are forms of spontaneous activity in cortical circuits that have been described in vivo and in vitro. Searching for mechanisms involved in their generation, we investigated the collective network activity and spike discharge oscillations in cortical slice cultures of neonatal rats, combining multielectrode arrays with patch clamp recordings from individual neurons. The majority of these cultures showed spontaneous collective network activity [population bursts (PBs)] that could be described as neuronal avalanches. The largest of these PBs were followed by fast spike discharge oscillations in the beta to theta range, and sometimes additional repetitive PBs, together forming seizure-like episodes. During such episodes, all neurons showed sustained depolarization with increased spike rates. However, whereas regular-spiking (RS) and fast-spiking (FS) neurons fired during the PBs, only the FS neurons fired during the fast oscillations. Blockade of N-methyl-d-aspartate receptors reduced the depolarization and suppressed both the increased FS neuron firing and the oscillations. To investigate the generation of PBs, we studied the network responses to electrical stimulation. For most of the stimulation sites, the relationship between the stimulated inputs and the evoked PBs was linear. From a few stimulation sites, however, large PBs could be evoked with small inputs, indicating the activation of hub circuits. Taken together, our findings suggests that the oscillations originate from recurrent inhibition in local networks of depolarized inhibitory FS interneurons, whereas the PBs originate from recurrent excitation in networks of RS and FS neurons that is initiated in hub circuits.

Adaptation-induced plasticity and spike waveforms in cat visual cortex

Orientation-selective neurons shift their preferred orientation after being adapted to a nonpreferred orientation. These shifts of the peaks of tuning curves may be in the attractive or repulsive direction in relation to the adapter orientation. In anesthetized cats, we recorded evoked electrical responses from the visual cortex in a conventional manner. The recorded spikes in cortex may present two typical waveforms: regular spikes or fast spikes. However, there is no evidence whether the shapes of spikes are related to the attractive or repulsive shifts of orientation tuning curves of cells. Our results show that after adaptation the recorded cells with both attractive and repulsive shifts display one or the other shape of spike. However, the magnitude of shifts is systematically higher for regular spikes, which is attributed to putative pyramidal cells, whereas tuning curves for fast spikes have smaller magnitudes and are evoked by putative interneurons.

Short-Term Plasticity of Unitary Inhibitory-to-Inhibitory Synapses Depends on the Presynaptic Interneuron Subtype

Excitatory-to-inhibitory cortical synapses exhibit either short-term facilitation or depression, depending on the subtype identity of the postsynaptic interneuron, while the short-term plasticity (STP) of inhibitory-to-excitatory synapses depends on the presynaptic interneuron. However, the rules governing STP of inhibitory-to-inhibitory synapses have not yet been determined. We recorded 109 unitary connections made by the two major inhibitory interneuron subtypes in layer 4 of mouse somatosensory cortex, fast-spiking (FS) and somatostatin-containing (SOM) interneurons, on each other and on excitatory, regular-spiking (RS) neurons. In all pairs, we measured dynamic changes in the postsynaptic response to a 20 Hz train of presynaptic action potentials. In half of our dataset, we also measured kinetic properties of the unitary IPSC: latency, rise time, and decay time constant. We found a pronounced dependency of STP on the presynaptic, but not the postsynaptic, identity: FS interneurons made strongly depressing connections on FS, SOM, and RS targets, while in synapses made by SOM interneurons on FS and RS targets, weak early depression was followed by weak late facilitation. IPSC latency and rise time were also strongly dependent on the presynaptic interneuron subtype, being 1.5-2× slower in output synapses of SOM compared with FS interneurons. In contrast, the IPSC decay time constant depended only on the postsynaptic class, with 1.5× slower decay on excitatory compared with inhibitory targets. The properties of the inhibitory outputs of FS and SOM interneurons reciprocate the properties of their excitatory inputs and imply a dynamic spatiotemporal division of labor between these two major inhibitory subsystems.

Regular Spiking and Intrinsic Bursting Pyramidal Cells Show Orthogonal Forms of Experience-Dependent Plasticity in Layer V of Barrel Cortex

SummaryMost functional plasticity studies in the cortex have focused on layers (L) II/III and IV, whereas relatively little is known of LV. Structural measurements of dendritic spines in vivo suggest some specialization among LV cell subtypes. We therefore studied experience-dependent plasticity in the barrel cortex using intracellular recordings to distinguish regular spiking (RS) and intrinsic bursting (IB) subtypes. Postsynaptic potentials and suprathreshold responses in vivo revealed a remarkable dichotomy in RS and IB cell plasticity; spared whisker potentiation occurred in IB but not RS cells while deprived whisker depression occurred in RS but not IB cells. Similar RS/IB differences were found in the LII/III to V connections in brain slices. Modeling studies showed that subthreshold changes predicted the suprathreshold changes. These studies demonstrate the major functional partition of plasticity within a single cortical layer and reveal the LII/III to LV connection as a major excitatory locus of cortical plasticity.

A Contraction Argument for Two-Dimensional Spiking Neuron Models

A number of two-dimensional spiking neuron models that combine continuous dynamics with an instantaneous reset have been introduced in the literature. The models are capable of reproducing a variety of experimentally observed spiking patterns and also have the advantage of being mathematically tractable. Here an analysis of the transverse stability of orbits in the phase plane leads to sufficient conditions on the model parameters for regular spiking to occur. The application of this method is illustrated by three examples, taken from existing models in the neuroscience literature. In the first two examples the model has no equilibrium states, and regular spiking follows directly. In the third example there are equilibrium points, and some additional quantitative arguments are given to prove that regular spiking occurs.

A wavelet-based neural model to optimize and read out a temporal population code

It has been proposed that the dense excitatory local connectivity of the neo-cortex plays a specific role in the transformation of spatial stimulus information into a temporal representation or a temporal population code (TPC). TPC provides for a rapid, robust, and high-capacity encoding of salient stimulus features with respect to position, rotation, and distortion. The TPC hypothesis gives a functional interpretation to a core feature of the cortical anatomy: its dense local and sparse long-range connectivity. Thus far, the question of how the TPC encoding can be decoded in downstream areas has not been addressed. Here, we present a neural circuit that decodes the spectral properties of the TPC using a biologically plausible implementation of a Haar transform. We perform a systematic investigation of our model in a recognition task using a standardized stimulus set. We consider alternative implementations using either regular spiking or bursting neurons and a range of spectral bands. Our results show that our wavelet readout circuit provides for the robust decoding of the TPC and further compresses the code without loosing speed or quality of decoding. We show that in the TPC signal the relevant stimulus information is present in the frequencies around 100 Hz. Our results show that the TPC is constructed around a small number of coding components that can be well decoded by wavelet coefficients in a neuronal implementation. The solution to the TPC decoding problem proposed here suggests that cortical processing streams might well consist of sequential operations where spatio-temporal transformations at lower levels forming a compact stimulus encoding using TPC that are subsequently decoded back to a spatial representation using wavelet transforms. In addition, the results presented here show that different properties of the stimulus might be transmitted to further processing stages using different frequency components that are captured by appropriately tuned wavelet-based decoders.