Hyperpolarization-activated graded persistent activity in the prefrontal cortex

H-current modulation of cortical Up and Down states

Understanding the link between cellular processes and brain function remains a key challenge in neuroscience. One crucial aspect is the interplay between specific ion channels and network dynamics. This work reveals a role for h-current, a hyperpolarization-activated cationic current, in shaping cortical slow oscillations. Cortical slow oscillations are generated not only during slow wave sleep and deep anaesthesia, but also in association with disorders of consciousness and brain lesions. Cortical slow oscillations exhibit rhythmic periods of activity (Up states) alternating with silent periods (Down states). By progressively reducing h-current in both cortical slices and in a computational model, we observed Up states transformed into prolonged plateaus of sustained firing, while Down states were also significantly extended. This transformation led to a fivefold reduction in oscillation frequency. In a biophysical recurrent network model, we identified the cellular mechanisms underlying this transformation of network dynamics: an increased neuronal input resistance and membrane time constant, increasing neuronal responsiveness to even weak inputs. A partial block of h-current therefore resulted in a change in brain state. HCN (hyperpolarization-activated cyclic nucleotide-gated) channels, which generate h-current, are known targets for neuromodulation, suggesting potential pathways for dynamic control of brain rhythms. KEY POINTS: We investigated the role of h-current in shaping emergent cortical slow oscillation dynamics, specifically Up and Down states, in cortical slices. Blocking h-current transformed Up states into prolonged plateaus of sustained firing, lasting up to 4 s. Down states were also significantly elongated and the oscillatory frequency decreased. A biophysical model of the cortical network replicated these findings and allowed us to explore the underlying mechanisms. An increase in cellular input resistance and time constant led to a rise in network excitability, synaptic responsiveness and firing rates. Our results highlight the significant role of h-current in controlling cortical slow rhythmic patterns, making it a relevant target for neuromodulators regulating brain states.

Ferret as a model system for studying the anatomy and function of the prefrontal cortex: A systematic review

There is a lack of consensus on anatomical nomenclature, standards of documentation, and functional equivalence of the frontal cortex between species. There remains a major gap between human prefrontal function and interpretation of findings in the mouse brain that appears to lack several key prefrontal areas involved in cognition and psychiatric illnesses. The ferret is an emerging model organism that has gained traction as an intermediate model species for the study of top-down cognitive control and other higher-order brain functions. However, this research has yet to benefit from synthesis. Here, we provide a summary of all published research pertaining to the frontal and/or prefrontal cortex of the ferret across research scales. The targeted location within the ferret brain is summarized visually for each experiment, and the anatomical terminology used at time of publishing is compared to what would be the appropriate term to use presently. By doing so, we hope to improve clarity in the interpretation of both previous and future publications on the comparative study of frontal cortex.

Differential behaviors of calcium-induced calcium release in one dimensional dendrite by Nernst-Planck equation, cable model and pure diffusion model

The source and dynamics of calcium is the key factor that regulates dendritic integration. Apart from the voltage-gated and ligand-gated calcium influx, an important source of calcium is from inner store of endoplasmic reticulum with a regenerative process of calcium-induced calcium release (CICR). To trigger this process, inositol 1,4,5-trisphosphate (IP3) and calcium are needed to satisfy certain requirements. The aim of our paper is to investigate how the CICR depends on the dynamics of membrane potential. We utilize one dimensional dendritic model to calculate membrane potential by Nernst-Planck Equation (NPE) and cable model and Pure Diffusion (PD) model, computational simulations are carried out to inject the calcium influx by synaptic stimulation and to predict subsequent CICR and calcium wave propagation. Our results demonstrate that CICR initiation and calcium wave propagation have much difference between electro-diffusion process of NPE and cable model. We find that cable model has lower threshold of IP3 stimulation to trigger CICR but is more difficult for calcium propagation than NPE, PD model requires even higher threshold of IP3 to initiate CICR process and calcium duration is shorter than NPE; the regenerative calcium wave propagates with faster speed in NPE than that in cable model and in PD model. Our work addresses the important role of electro-diffusion dynamics of charged ions in regulating CICR process in dendritic structure; and provides theoretical predictions for neurological process which requires sustaining calcium for downstream signaling processes.

A brainstem integrator for self-location memory and positional homeostasis in zebrafish

To track and control self-location, animals integrate their movements through space. Representations of self-location are observed in the mammalian hippocampal formation, but it is unknown if positional representations exist in more ancient brain regions, how they arise from integrated self-motion, and by what pathways they control locomotion. Here, in a head-fixed, fictive-swimming, virtual-reality preparation, we exposed larval zebrafish to a variety of involuntary displacements. They tracked these displacements and, many seconds later, moved toward their earlier location through corrective swimming ("positional homeostasis"). Whole-brain functional imaging revealed a network in the medulla that stores a memory of location and induces an error signal in the inferior olive to drive future corrective swimming. Optogenetically manipulating medullary integrator cells evoked displacement-memory behavior. Ablating them, or downstream olivary neurons, abolished displacement corrections. These results reveal a multiregional hindbrain circuit in vertebrates that integrates self-motion and stores self-location to control locomotor behavior.

Comparative study between radiofrequency-induced and muscimol-induced inhibition of cultured networks of cortical neuron

Previous studies have shown that spontaneously active cultured networks of cortical neuron grown planar microelectrode arrays are sensitive to radiofrequency (RF) fields and exhibit an inhibitory response more pronounced as the exposure time and power increase. To better understand the mechanism behind the observed effects, we aimed at identifying similarities and differences between the inhibitory effect of RF fields (continuous wave, 1800 MHz) to the γ-aminobutyric acid type A (GABA_A) receptor agonist muscimol (MU). Inhibition of the network bursting activity in response to RF exposure became apparent at an SAR level of 28.6 W/kg and co-occurred with an elevation of the culture medium temperature of ~1°C. Exposure to RF fields preferentially inhibits bursting over spiking activity and exerts fewer constraints on neural network bursting synchrony, differentiating it from a pharmacological inhibition with MU. Network rebound excitation, a phenomenon relying on the intrinsic properties of cortical neurons, was observed following the removal of tonic hyperpolarization after washout of MU but not in response to cessation of RF exposure. This implies that hyperpolarization is not the main driving force mediating the inhibitory effects of RF fields. At the level of single neurons, network inhibition induced by MU and RF fields occurred with reduced action potential (AP) half-width. As changes in AP waveform strongly influence efficacy of synaptic transmission, the narrowing effect on AP seen under RF exposure might contribute to reducing network bursting activity. By pointing only to a partial overlap between the inhibitory hallmarks of these two forms of inhibition, our data suggest that the inhibitory mechanisms of the action of RF fields differ from the ones mediated by the activation of GABA_A receptors.

Active intrinsic conductances in recurrent networks allow for long-lasting transients and sustained activity with realistic firing rates as well as robust plasticity

Recurrent neural networks of spiking neurons can exhibit long lasting and even persistent activity. Such networks are often not robust and exhibit spike and firing rate statistics that are inconsistent with experimental observations. In order to overcome this problem most previous models had to assume that recurrent connections are dominated by slower NMDA type excitatory receptors. Usually, the single neurons within these networks are very simple leaky integrate and fire neurons or other low dimensional model neurons. However real neurons are much more complex, and exhibit a plethora of active conductances which are recruited both at the sub and supra threshold regimes. Here we show that by including a small number of additional active conductances we can produce recurrent networks that are both more robust and exhibit firing-rate statistics that are more consistent with experimental results. We show that this holds both for bi-stable recurrent networks, which are thought to underlie working memory and for slowly decaying networks which might underlie the estimation of interval timing. We also show that by including these conductances, such networks can be trained to using a simple learning rule to predict temporal intervals that are an order of magnitude larger than those that can be trained in networks of leaky integrate and fire neurons.

Ivabradine, the hyperpolarization-activated cyclic nucleotide-gated channel blocker, elicits relaxation of the human corpus cavernosum: a potential option for erectile dysfunction treatment

OBJECTIVE

To evaluate the effect of the I_f channel inhibitor, ivabradine on human corpus cavernosum (HCC) smooth muscle tone.

METHODS

HCC samples were obtained from erectile dysfunction(ED) patients (n = 12) undergoing penile prosthesis surgery. Concentration-response curves for ivabradine were exposed to various inhibitory and stimulatory agents. The relaxant and contractile responses to electrical field stimulation (EFS, 10 Hz and 80 Hz) were examined in the presence or absence of ivabradine (10 μM). HCN3 and HCN4 channel expression and localization were determined by Western blot and immunohistochemical analyses of HCC tissues.

RESULTS

Increasing ivabradine concentrations dependently reduced the maximal contractile responses of isolated HCC strips induced by KCl (59.5 ± 2.5%) and phenylephrine (84.0 ± 9.8%), which was not affected by nitric oxide synthase and soluble guanylyl cyclase inhibitors after phenylephrine-induced contraction. Nifedipine and tetraethylammonium inhibited the maximum relaxation to ivabradine by 75% and 39.3%, respectively. Fasudil and sildenafil increased the relaxation response to ivabradine without altering the maximum response. Pre-incubation with ivabradine significantly increased relaxant responses to EFS (p < 0.01) and reduced the contractile tension evoked by EFS (72.3%) (p < 0.001). Ivabradine incubation did not affect the expression and localization of HCN3 and HCN4 channels in the HCC smooth muscle cells.

CONCLUSIONS

Ivabradine exhibits a relaxant effect on HCC tissues, which is likely to be attributed to the blocking of L-type Ca²⁺ channels and the opening of K⁺ channels, independent of changes in the activation of the nitric oxide/cyclic guanosine monophosphate system. Inhibition of HCN channels localized in cavernosal smooth muscle cells may offer pharmacological benefits for patients with cardiovascular risk factors.

Refractory density model of cortical direction selectivity: Lagged-nonlagged, transient-sustained, and On-Off thalamic neuron-based mechanisms and intracortical amplification

A biophysically detailed description of the mechanisms of the primary vision is still being developed. We have incorporated a simplified, filter-based description of retino-thalamic visual signal processing into the detailed, conductance-based refractory density description of the neuronal population activity of the primary visual cortex. We compared four mechanisms of the direction selectivity (DS), three of them being based on asymmetrical projections of different types of thalamic neurons to the cortex, distinguishing between (i) lagged and nonlagged, (ii) transient and sustained, and (iii) On and Off neurons. The fourth mechanism implies a lack of subcortical bias and is an epiphenomenon of intracortical interactions between orientation columns. The simulations of the cortical response to moving gratings have verified that first three mechanisms provide DS to an extent compared with experimental data and that the biophysical model realistically reproduces characteristics of the visual cortex activity, such as membrane potential, firing rate, and synaptic conductances. The proposed model reveals the difference between the mechanisms of both the intact and the silenced cortex, favoring the second mechanism. In the fourth case, DS is weaker but significant; it completely vanishes in the silenced cortex.DS in the On-Off mechanism derives from the nonlinear interactions within the orientation map. Results of simulations can help to identify a prevailing mechanism of DS in V1. This is a step towards a comprehensive biophysical modeling of the primary visual system in the frameworks of the population rate coding concept.

A major mechanism that underlies tuning of cortical neurons to the direction of a moving stimulus is still debated. Considering the visual cortex structured with orientation-selective columns, we have realized and compared in our biophysically detailed mathematical model four hypothetical mechanisms of the direction selectivity (DS) known from experiments. The present model accomplishes our previous model that was tuned to experimental data on excitability in slices and reproduces orientation tuning effects in vivo. In simulations, we have found that the convergence of inputs from so-called transient and sustained (or lagged and nonlagged) thalamic neurons in the cortex provides an initial bias for DS, whereas cortical interactions amplify the tuning. In the absence of any bias, DS emerges as an epiphenomenon of the orientation map. In the case of a biased convergence of On- and Off- thalamic inputs, DS emerges with the help of the intracortical interactions on the orientation map, also. Thus, we have proposed a comprehensive description of the primary vision and revealed characteristic features of different mechanisms of DS in the visual cortex with columnar structure.

Dorsal prefrontal and premotor cortex of the ferret as defined by distinctive patterns of thalamo-cortical projections

Recent studies of the neurobiology of the dorsal frontal cortex (FC) of the ferret have illuminated its key role in the attention network, top-down cognitive control of sensory processing, and goal directed behavior. To elucidate the neuroanatomical regions of the dorsal FC, and delineate the boundary between premotor cortex (PMC) and dorsal prefrontal cortex (dPFC), we placed retrograde tracers in adult ferret dorsal FC anterior to primary motor cortex and analyzed thalamo-cortical connectivity. Cyto- and myeloarchitectural differences across dorsal FC and the distinctive projection patterns from thalamic nuclei, especially from the subnuclei of the medial dorsal (MD) nucleus and the ventral thalamic nuclear group, make it possible to clearly differentiate three separate dorsal FC fields anterior to primary motor cortex: polar dPFC (dPFCpol), dPFC, and PMC. Based on the thalamic connectivity, there is a striking similarity of the ferret's dorsal FC fields with other species. This possible homology opens up new questions for future comparative neuroanatomical and functional studies.

Clusters of cooperative ion channels enable a membrane-potential-based mechanism for short-term memory

Across biological systems, cooperativity between proteins enables fast actions, supra-linear responses, and long-lasting molecular switches. In the nervous system, however, the function of cooperative interactions between voltage-dependent ionic channels remains largely unknown. Based on mathematical modeling, we here demonstrate that clusters of strongly cooperative ion channels can plausibly form bistable conductances. Consequently, clusters are permanently switched on by neuronal spiking, switched off by strong hyperpolarization, and remain in their state for seconds after stimulation. The resulting short-term memory of the membrane potential allows to generate persistent firing when clusters of cooperative channels are present together with non-cooperative spike-generating conductances. Dynamic clamp experiments in rodent cortical neurons confirm that channel cooperativity can robustly induce graded persistent activity - a single-cell based, multistable mnemonic firing mode experimentally observed in several brain regions. We therefore propose that ion channel cooperativity constitutes an efficient cell-intrinsic implementation for short-term memories at the voltage level.

Parietal low beta rhythm provides a dynamical substrate for a working memory buffer

Working memory (WM) is a component of the brain's memory systems vital for interpretation of sequential sensory inputs and consequent decision making. Anatomically, WM is highly distributed over the prefrontal cortex (PFC) and the parietal cortex (PC). Here we present a biophysically detailed dynamical systems model for a WM buffer situated in the PC, making use of dynamical properties believed to be unique to this area. We show that the natural beta1 rhythm (12 to 20 Hz) of the PC provides a substrate for an episodic buffer that can synergistically combine executive commands (e.g., from PFC) and multimodal information into a flexible and updatable representation of recent sensory inputs. This representation is sensitive to distractors, it allows for a readout mechanism, and it can be readily terminated by executive input. The model provides a demonstration of how information can be usefully stored in the temporal patterns of activity in a neuronal network rather than just synaptic weights between the neurons in that network.

Chronic unpredictable stress promotes cell-specific plasticity in prefrontal cortex D1 and D2 pyramidal neurons

Exposure to unpredictable environmental stress is widely recognized as a major determinant for risk and severity in neuropsychiatric disorders such as major depressive disorder, anxiety, schizophrenia, and PTSD. The ability of ostensibly unrelated disorders to give rise to seemingly similar psychiatric phenotypes highlights a need to identify circuit-level concepts that could unify diverse factors under a common pathophysiology. Although difficult to disentangle a causative effect of stress from other factors on medial prefrontal cortex (PFC) dysfunction, a wealth of data from humans and rodents demonstrates that the PFC is a key target of stress. The present study sought to identify a model of chronic unpredictable stress (CUS) which induces affective behaviors in C57BL6J mice and once established, measure stress-related alterations in intrinsic excitability and synaptic regulation of mPFC layer 5/6 pyramidal neurons. Adult male mice received 2 weeks of 'less intense' stress or 2 or 4 weeks of 'more intense' CUS followed by sucrose preference for assessment of anhedonia, elevated plus maze for assessment of anxiety and forced swim test for assessment of depressive-like behaviors. Our findings indicate that more intense CUS exposure results in increased anhedonia, anxiety, and depressive behaviors, while the less intense stress results in no measured behavioral phenotypes. Once a behavioral model was established, mice were euthanized approximately 21 days post-stress for whole-cell patch clamp recordings from layer 5/6 pyramidal neurons in the prelimbic (PrL) and infralimbic (IL) cortices. No significant differences were initially observed in intrinsic cell excitability in either region. However, post-hoc analysis and subsequent confirmation using transgenic mice expressing tdtomato or eGFP under control of dopamine D1-or D2-type receptor showed that D1-expressing pyramidal neurons (D1-PYR) in the PrL exhibit reduced thresholds to fire an action potential (increased excitability) but impaired firing capacity at more depolarized potentials, whereas D2-expressing pyramidal neurons (D2-PYR) showed an overall reduction in excitability and spike firing frequency. Examination of synaptic transmission showed that D1-and D2-PYR exhibit differences in basal excitatory and inhibitory signaling under naïve conditions. In CUS mice, D1-PYR showed increased frequency of both miniature excitatory and inhibitory postsynaptic currents, whereas D2-PYR only showed a reduction in excitatory currents. These findings demonstrate that D1-and D2-PYR subpopulations differentially undergo stress-induced intrinsic and synaptic plasticity that may have functional implications for stress-related pathology, and that these adaptations may reflect unique differences in basal properties regulating output of these cells.

Detection of Activation Sequences in Spiking-Bursting Neurons by means of the Recognition of Intraburst Neural Signatures

Bursting activity is present in many cells of different nervous systems playing important roles in neural information processing. Multiple assemblies of bursting neurons act cooperatively to produce coordinated spatio-temporal patterns of sequential activity. A major goal in neuroscience is unveiling the mechanisms underlying neural information processing based on this sequential dynamics. Experimental findings have revealed the presence of precise cell-type-specific intraburst firing patterns in the activity of some bursting neurons. This characteristic neural signature coexists with the information encoded in other aspects of the spiking-bursting signals, and its functional meaning is still unknown. We investigate the ability of a neuron conductance-based model to detect specific presynaptic activation sequences taking advantage of intraburst fingerprints identifying the source of the signals building up a sequential pattern of activity. Our simulations point out that a reader neuron could use this information to contextualize incoming signals and accordingly compute a characteristic response by relying on precise phase relationships among the activity of different emitters. This would provide individual neurons enhanced capabilities to control and negotiate sequential dynamics. In this regard, we discuss the possible implications of the proposed contextualization mechanism for neural information processing.

Do TRPC channels support working memory? Comparing modulations of TRPC channels and working memory through G-protein coupled receptors and neuromodulators

Working memory is a crucial ability we use in daily life. However, the cellular mechanisms supporting working memory still remain largely unclear. A key component of working memory is persistent neural firing which is believed to serve short-term (hundreds of milliseconds up to tens of seconds) maintenance of necessary information. In this review, we will focus on the role of transient receptor potential canonical (TRPC) channels as a mechanism underlying persistent firing. Many years of in vitro work have been suggesting a crucial role of TRPC channels in working memory and temporal association tasks. If TRPC channels are indeed a central mechanism for working memory, manipulations which impair or facilitate working memory should have a similar effect on TRPC channel modulation. However, modulations of working memory and TRPC channels were never systematically compared, and it remains unanswered whether TRPC channels indeed contribute to working memory in vivo or not. In this article, we review the effects of G-protein coupled receptors (GPCR) and neuromodulators, including acetylcholine, noradrenalin, serotonin and dopamine, on working memory and TRPC channels. Based on comparisons, we argue that GPCR and downstream signaling pathways that activate TRPC, generally support working memory, while those that suppress TRPC channels impair it. However, depending on the channel types, areas, and systems tested, this is not the case in all studies. Further work to clarify involvement of specific TRPC channels in working memory tasks and how they are affected by neuromodulators is still necessary in the future.

Modulation of Ether-à-Go-Go Related Gene (ERG) Current Governs Intrinsic Persistent Activity in Rodent Neocortical Pyramidal Cells

While cholinergic receptor activation has long been known to dramatically enhance the excitability of cortical neurons, the cellular mechanisms responsible for this effect are not well understood. We used intracellular recordings in rat (both sexes) neocortical brain slices to assess the ionic mechanisms supporting persistent firing modes triggered by depolarizing stimuli following cholinergic receptor activation. We found multiple lines of evidence suggesting that a component of the underlying hyperexcitability associated with persistent firing reflects a reduction in the standing (leak) K⁺ current mediated by Ether-a-go-go-Related Gene (ERG) channels. Three chemically diverse ERG channel blockers (terfenadine, ErgToxin-1, and E-4031) abolished persistent firing and the underlying increase in input resistance in deep pyramidal cells in temporal and prefrontal association neocortex. Calcium accumulation during triggering stimuli appears to attenuate ERG currents, leading to membrane potential depolarization and increased input resistance, two critical elements generating persistent firing. Our results also suggest that ERG current normally governs cortical neuron responses to depolarizing stimuli by opposing prolonged discharges and by enhancing the poststimulus repolarization. The broad expression of ERG channels and the ability of ERG blocks to abolish persistent firing evoked by both synaptic and intracellular step stimuli suggest that modulation of ERG channels may underlie many forms of persistent activity observed in vivoSIGNIFICANCE STATEMENT Persistent activity, where spiking continues beyond the triggering stimulus, is a common phenomenon observed in many types of neurons. Identifying the mechanism underlying this elementary process of memory is a step forward in understanding higher cognitive function including short-term memory. Our results suggest that a reduction in the currents normally mediated by Ether-a-go-go-Related Gene (ERG) K⁺ channels contributes to persistent firing in neocortical pyramidal cells. ERG currents have been previously studied primarily in the heart; relatively little is known about ERG function in the brain, although mutations in ERG channels have recently been linked to schizophrenia. The present study is among the first to describe its role in neocortex in relation to biophysical correlates of memory function.

Persistent irregular activity is a result of rebound and coincident detection mechanisms: A computational study

Persistent irregular activity is defined as elevated irregular neural discharges in the brain in such a way that while the average network activity displays high frequency oscillations, the participating neurons display irregular and low frequency oscillations. This type of activity is observed in many brain regions like prefrontal cortex that plays a role in working memory. Previous studies have shown that large networks with sparse connections, networks with strong noise and persistent inhibition and networks with structured synaptic connections display persistent-irregular activity. However, experimental studies show that, not all brain regions obey these assumptions. In this study we show that a small network of excitatory-inhibitory neurons with random synaptic connections can reproduce persistent-irregular activity. In particular, the model shows that less than perfect rebound pattern in excitatory cells, coincident-sensitive inhibitory cells and sparse synaptic inhibition can account for persistent-irregular activity in an excitatory-inhibitory neural network with randomly assigned synaptic connections.

Multitarget Multiscale Simulation for Pharmacological Treatment of Dystonia in Motor Cortex

A large number of physiomic pathologies can produce hyperexcitability in cortex. Depending on severity, cortical hyperexcitability may manifest clinically as a hyperkinetic movement disorder or as epilpesy. We focus here on dystonia, a movement disorder that produces involuntary muscle contractions and involves pathology in multiple brain areas including basal ganglia, thalamus, cerebellum, and sensory and motor cortices. Most research in dystonia has focused on basal ganglia, while much pharmacological treatment is provided directly at muscles to prevent contraction. Motor cortex is another potential target for therapy that exhibits pathological dynamics in dystonia, including heightened activity and altered beta oscillations. We developed a multiscale model of primary motor cortex, ranging from molecular, up to cellular, and network levels, containing 1715 compartmental model neurons with multiple ion channels and intracellular molecular dynamics. We wired the model based on electrophysiological data obtained from mouse motor cortex circuit mapping experiments. We used the model to reproduce patterns of heightened activity seen in dystonia by applying independent random variations in parameters to identify pathological parameter sets. These models demonstrated degeneracy, meaning that there were many ways of obtaining the pathological syndrome. There was no single parameter alteration which would consistently distinguish pathological from physiological dynamics. At higher dimensions in parameter space, we were able to use support vector machines to distinguish the two patterns in different regions of space and thereby trace multitarget routes from dystonic to physiological dynamics. These results suggest the use of in silico models for discovery of multitarget drug cocktails.

Megamap: flexible representation of a large space embedded with nonspatial information by a hippocampal attractor network

The problem of how the hippocampus encodes both spatial and nonspatial information at the cellular network level remains largely unresolved. Spatial memory is widely modeled through the theoretical framework of attractor networks, but standard computational models can only represent spaces that are much smaller than the natural habitat of an animal. We propose that hippocampal networks are built on a basic unit called a "megamap," or a cognitive attractor map in which place cells are flexibly recombined to represent a large space. Its inherent flexibility gives the megamap a huge representational capacity and enables the hippocampus to simultaneously represent multiple learned memories and naturally carry nonspatial information at no additional cost. On the other hand, the megamap is dynamically stable, because the underlying network of place cells robustly encodes any location in a large environment given a weak or incomplete input signal from the upstream entorhinal cortex. Our results suggest a general computational strategy by which a hippocampal network enjoys the stability of attractor dynamics without sacrificing the flexibility needed to represent a complex, changing world.

Calcium regulation of HCN channels supports persistent activity in a multiscale model of neocortex

Neuronal persistent activity has been primarily assessed in terms of electrical mechanisms, without attention to the complex array of molecular events that also control cell excitability. We developed a multiscale neocortical model proceeding from the molecular to the network level to assess the contributions of calcium (Ca(2+)) regulation of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels in providing additional and complementary support of continuing activation in the network. The network contained 776 compartmental neurons arranged in the cortical layers, connected using synapses containing AMPA/NMDA/GABAA/GABAB receptors. Metabotropic glutamate receptors (mGluR) produced inositol triphosphate (IP3) which caused the release of Ca(2+) from endoplasmic reticulum (ER) stores, with reuptake by sarco/ER Ca(2+)-ATP-ase pumps (SERCA), and influence on HCN channels. Stimulus-induced depolarization led to Ca(2+) influx via NMDA and voltage-gated Ca(2+) channels (VGCCs). After a delay, mGluR activation led to ER Ca(2+) release via IP3 receptors. These factors increased HCN channel conductance and produced firing lasting for ∼1min. The model displayed inter-scale synergies among synaptic weights, excitation/inhibition balance, firing rates, membrane depolarization, Ca(2+) levels, regulation of HCN channels, and induction of persistent activity. The interaction between inhibition and Ca(2+) at the HCN channel nexus determined a limited range of inhibition strengths for which intracellular Ca(2+) could prepare population-specific persistent activity. Interactions between metabotropic and ionotropic inputs to the neuron demonstrated how multiple pathways could contribute in a complementary manner to persistent activity. Such redundancy and complementarity via multiple pathways is a critical feature of biological systems. Mediation of activation at different time scales, and through different pathways, would be expected to protect against disruption, in this case providing stability for persistent activity.

Neuronal calcium wave propagation varies with changes in endoplasmic reticulum parameters: a computer model

Calcium (Ca²⁺) waves provide a complement to neuronal electrical signaling, forming a key part of a neuron's second messenger system. We developed a reaction-diffusion model of an apical dendrite with diffusible inositol triphosphate (IP₃), diffusible Ca²⁺, IP₃ receptors (IP₃Rs), endoplasmic reticulum (ER) Ca²⁺ leak, and ER pump (SERCA) on ER. Ca²⁺ is released from ER stores via IP₃Rs upon binding of IP₃ and Ca²⁺. This results in Ca²⁺-induced-Ca²⁺-release (CICR) and increases Ca²⁺ spread. At least two modes of Ca²⁺ wave spread have been suggested: a continuous mode based on presumed relative homogeneity of ER within the cell and a pseudo-saltatory model where Ca²⁺ regeneration occurs at discrete points with diffusion between them. We compared the effects of three patterns of hypothesized IP₃R distribution: (1) continuous homogeneous ER, (2) hotspots with increased IP₃R density (IP₃R hotspots), and (3) areas of increased ER density (ER stacks). All three modes produced Ca²⁺ waves with velocities similar to those measured in vitro (approximately 50-90 μm /sec). Continuous ER showed high sensitivity to IP₃R density increases, with time to onset reduced and speed increased. Increases in SERCA density resulted in opposite effects. The measures were sensitive to changes in density and spacing of IP₃R hotspots and stacks. Increasing the apparent diffusion coefficient of Ca²⁺ substantially increased wave speed. An extended electrochemical model, including voltage-gated calcium channels and AMPA synapses, demonstrated that membrane priming via AMPA stimulation enhances subsequent Ca²⁺ wave amplitude and duration. Our modeling suggests that pharmacological targeting of IP₃Rs and SERCA could allow modulation of Ca²⁺ wave propagation in diseases where Ca²⁺ dysregulation has been implicated.

A simple biophysically plausible model for long time constants in single neurons

Recent work in computational neuroscience and cognitive psychology suggests that a set of cells that decay exponentially could be used to support memory for the time at which events took place. Analytically and through simulations on a biophysical model of an individual neuron, we demonstrate that exponentially decaying firing with a range of time constants up to minutes could be implemented using a simple combination of well-known neural mechanisms. In particular, we consider firing supported by calcium-controlled cation current. When the amount of calcium leaving the cell during an interspike interval is larger than the calcium influx during a spike, the overall decay in calcium concentration can be exponential, resulting in exponential decay of the firing rate. The time constant of the decay can be several orders of magnitude larger than the time constant of calcium clearance, and it could be controlled externally via a variety of biologically plausible ways. The ability to flexibly and rapidly control time constants could enable working memory of temporal history to be generalized to other variables in computing spatial and ordinal representations.

Dendritic nonlinearities reduce network size requirements and mediate ON and OFF states of persistent activity in a PFC microcircuit model

Technological advances have unraveled the existence of small clusters of co-active neurons in the neocortex. The functional implications of these microcircuits are in large part unexplored. Using a heavily constrained biophysical model of a L5 PFC microcircuit, we recently showed that these structures act as tunable modules of persistent activity, the cellular correlate of working memory. Here, we investigate the mechanisms that underlie persistent activity emergence (ON) and termination (OFF) and search for the minimum network size required for expressing these states within physiological regimes. We show that (a) NMDA-mediated dendritic spikes gate the induction of persistent firing in the microcircuit. (b) The minimum network size required for persistent activity induction is inversely proportional to the synaptic drive of each excitatory neuron. (c) Relaxation of connectivity and synaptic delay constraints eliminates the gating effect of NMDA spikes, albeit at a cost of much larger networks. (d) Persistent activity termination by increased inhibition depends on the strength of the synaptic input and is negatively modulated by dADP. (e) Slow synaptic mechanisms and network activity contain predictive information regarding the ability of a given stimulus to turn ON and/or OFF persistent firing in the microcircuit model. Overall, this study zooms out from dendrites to cell assemblies and suggests a tight interaction between dendritic non-linearities and network properties (size/connectivity) that may facilitate the short-memory function of the PFC.

Working memory, the ability to retain information for a short period of time, is a fundamental cognitive function that shapes behavior. The cellular correlate of working memory is the prolonged spiking (persistent) activity of neurons in the prefrontal cortex. Impairments of prefrontal cortex functionalities and working memory have been associated with a variety of cognitive disorders, such as schizophrenia, the attention deficit hyperactivity disorder, and drug addiction. Hence, understanding how neurons embedded in the local circuitry support and maintain persistent activity is of outmost importance. Our work uses a multi-level integrative approach spanning from the dendritic, to the neuronal and network levels to identify the key biophysical and anatomical mechanisms contributing to persistent activity, leading to a number of high impact findings: it predicts a tradeoff between dendritic regenerative events and the size of a network expressing persistent activity. It also proposes when and how the persistent state can be stabilized, opening new avenues for pharmacological interventions. Finally, it describes decoding mechanisms for upcoming ON/OFF state transitions, furthering our understanding of information processing in the PFC and shedding new light on the emergence of anticipatory behaviors.

Single neuron dynamics and computation

At the single neuron level, information processing involves the transformation of input spike trains into an appropriate output spike train. Building upon the classical view of a neuron as a threshold device, models have been developed in recent years that take into account the diverse electrophysiological make-up of neurons and accurately describe their input-output relations. Here, we review these recent advances and survey the computational roles that they have uncovered for various electrophysiological properties, for dendritic arbor anatomy as well as for short-term synaptic plasticity.

Signal processing by T-type calcium channel interactions in the cerebellum

T-type calcium channels of the Cav3 family are unique among voltage-gated calcium channels due to their low activation voltage, rapid inactivation, and small single channel conductance. These special properties allow Cav3 calcium channels to regulate neuronal processing in the subthreshold voltage range. Here, we review two different subthreshold ion channel interactions involving Cav3 channels and explore the ability of these interactions to expand the functional roles of Cav3 channels. In cerebellar Purkinje cells, Cav3 and intermediate conductance calcium-activated potassium (IKCa) channels form a novel complex which creates a low voltage-activated, transient outward current capable of suppressing temporal summation of excitatory postsynaptic potentials (EPSPs). In large diameter neurons of the deep cerebellar nuclei, Cav3-mediated calcium current (I T) and hyperpolarization-activated cation current (I H) are activated during trains of inhibitory postsynaptic potentials. These currents have distinct, and yet synergistic, roles in the subthreshold domain with I T generating a rebound burst and I H controlling first spike latency and rebound spike precision. However, by shortening the membrane time constant the membrane returns towards resting value at a faster rate, allowing I H to increase the efficacy of I T and increase the range of burst frequencies that can be generated. The net effect of Cav3 channels thus depends on the channels with which they are paired. When expressed in a complex with a KCa channel, Cav3 channels reduce excitability when processing excitatory inputs. If functionally coupled with an HCN channel, the depolarizing effect of Cav3 channels is accentuated, allowing for efficient inversion of inhibitory inputs to generate a rebound burst output. Therefore, signal processing relies not only on the activity of individual subtypes of channels but also on complex interactions between ion channels whether based on a physical complex or by indirect effects on membrane properties.

Prefrontal cortex HCN1 channels enable intrinsic persistent neural firing and executive memory function

In many cortical neurons, HCN1 channels are the major contributors to Ih, the hyperpolarization-activated current, which regulates the intrinsic properties of neurons and shapes their integration of synaptic inputs, paces rhythmic activity, and regulates synaptic plasticity. Here, we examine the physiological role of Ih in deep layer pyramidal neurons in mouse prefrontal cortex (PFC), focusing on persistent activity, a form of sustained firing thought to be important for the behavioral function of the PFC during working memory tasks. We find that HCN1 contributes to the intrinsic persistent firing that is induced by a brief depolarizing current stimulus in the presence of muscarinic agonists. Deletion of HCN1 or acute pharmacological blockade of Ih decreases the fraction of neurons capable of generating persistent firing. The reduction in persistent firing is caused by the membrane hyperpolarization that results from the deletion of HCN1 or Ih blockade, rather than a specific role of the hyperpolarization-activated current in generating persistent activity. In vivo recordings show that deletion of HCN1 has no effect on up states, periods of enhanced synaptic network activity. Parallel behavioral studies demonstrate that HCN1 contributes to the PFC-dependent resolution of proactive interference during working memory. These results thus provide genetic evidence demonstrating the importance of HCN1 to intrinsic persistent firing and the behavioral output of the PFC. The causal role of intrinsic persistent firing in PFC-mediated behavior remains an open question.

Ih tunes theta/gamma oscillations and cross-frequency coupling in an in silico CA3 model

channels are uniquely positioned to act as neuromodulatory control points for tuning hippocampal theta (4–12 Hz) and gamma (25 Hz) oscillations, oscillations which are thought to have importance for organization of information flow. contributes to neuronal membrane resonance and resting membrane potential, and is modulated by second messengers. We investigated oscillatory control using a multiscale computer model of hippocampal CA3, where each cell class (pyramidal, basket, and oriens-lacunosum moleculare cells), contained type-appropriate isoforms of . Our model demonstrated that modulation of pyramidal and basket allows tuning theta and gamma oscillation frequency and amplitude. Pyramidal also controlled cross-frequency coupling (CFC) and allowed shifting gamma generation towards particular phases of the theta cycle, effected via 's ability to set pyramidal excitability. Our model predicts that in vivo neuromodulatory control of allows flexibly controlling CFC and the timing of gamma discharges at particular theta phases.

Induction and modulation of persistent activity in a layer V PFC microcircuit model

Working memory refers to the temporary storage of information and is strongly associated with the prefrontal cortex (PFC). Persistent activity of cortical neurons, namely the activity that persists beyond the stimulus presentation, is considered the cellular correlate of working memory. Although past studies suggested that this type of activity is characteristic of large scale networks, recent experimental evidence imply that small, tightly interconnected clusters of neurons in the cortex may support similar functionalities. However, very little is known about the biophysical mechanisms giving rise to persistent activity in small-sized microcircuits in the PFC. Here, we present a detailed biophysically—yet morphologically simplified—microcircuit model of layer V PFC neurons that incorporates connectivity constraints and is validated against a multitude of experimental data. We show that (a) a small-sized network can exhibit persistent activity under realistic stimulus conditions. (b) Its emergence depends strongly on the interplay of dADP, NMDA, and GABA_B currents. (c) Although increases in stimulus duration increase the probability of persistent activity induction, variability in the stimulus firing frequency does not consistently influence it. (d) Modulation of ionic conductances (I_h, I_D, I_sAHP, I_caL, I_caN, I_caR) differentially controls persistent activity properties in a location dependent manner. These findings suggest that modulation of the microcircuit's firing characteristics is achieved primarily through changes in its intrinsic mechanism makeup, supporting the hypothesis of multiple bi-stable units in the PFC. Overall, the model generates a number of experimentally testable predictions that may lead to a better understanding of the biophysical mechanisms of persistent activity induction and modulation in the PFC.

Basal ganglia modulation of thalamocortical relay in Parkinson's disease and dystonia

Basal ganglia dysfunction has being implied in both Parkinson's disease and dystonia. While these disorders probably involve different cellular and circuit pathologies within and beyond basal ganglia, there may be some shared neurophysiological pathways. For example, pallidotomy and pallidal Deep Brain Stimulation (DBS) are used in symptomatic treatment of both disorders. Both conditions are marked by alterations of rhythmicity of neural activity throughout basal ganglia-thalamocortical circuits. Increased synchronized oscillatory activity in beta band is characteristic of Parkinson's disease, while different frequency bands, theta and alpha, are involved in dystonia. We compare the effect of the activity of GPi, the output nuclei of the basal ganglia, on information processing in the downstream neural circuits of thalamus in Parkinson's disease and dystonia. We use a data-driven computational approach, a computational model of the thalamocortical (TC) cell modulated by experimentally recorded data, to study the differences and similarities of thalamic dynamics in dystonia and Parkinson's disease. Our analysis shows no substantial differences in TC relay between the two conditions. Our results suggest that, similar to Parkinson's disease, a disruption of thalamic processing could also be involved in dystonia. Moreover, the degree to which TC relay fidelity is impaired is approximately the same in both conditions. While Parkinson's disease and dystonia may have different pathologies and differ in the oscillatory content of neural discharge, our results suggest that the effect of patterning of pallidal discharge is similar in both conditions. Furthermore, these results suggest that the mechanisms of GPi DBS in dystonia may involve improvement of TC relay fidelity.

Synaptic potentiation facilitates memory-like attractor dynamics in cultured in vitro hippocampal networks

Collective rhythmic dynamics from neurons is vital for cognitive functions such as memory formation but how neurons self-organize to produce such activity is not well understood. Attractor-based computational models have been successfully implemented as a theoretical framework for memory storage in networks of neurons. Additionally, activity-dependent modification of synaptic transmission is thought to be the physiological basis of learning and memory. The goal of this study is to demonstrate that using a pharmacological treatment that has been shown to increase synaptic strength within in vitro networks of hippocampal neurons follows the dynamical postulates theorized by attractor models. We use a grid of extracellular electrodes to study changes in network activity after this perturbation and show that there is a persistent increase in overall spiking and bursting activity after treatment. This increase in activity appears to recruit more “errant” spikes into bursts. Phase plots indicate a conserved activity pattern suggesting that a synaptic potentiation perturbation to the attractor leaves it unchanged. Lastly, we construct a computational model to demonstrate that these synaptic perturbations can account for the dynamical changes seen within the network.

Evidence for layer-specific differences in auditory corticocollicular neurons

Recent data suggest that there may be distinct processing streams emanating from auditory cortical layers 5 and 6 that influence the auditory midbrain. To determine whether these projections have different physiological properties, we injected rhodamine-tagged latex tracer beads into the inferior colliculus of >30-day-old mice to label these corticofugal cells. Whole-cell recordings were performed on 62 labeled cells to determine their basic electrophysiological properties and cells were filled with biocytin to determine their morphological characteristics. Layer 5 auditory corticocollicular cells have prominent I(h)-mediated sag and rebound currents, have relatively sluggish time constants, and can generate calcium-dependent rhythmic bursts. In contrast, layer 6 auditory corticocollicular cells are non-bursting, do not demonstrate sag or rebound currents and have short time constants. Quantitative analysis of morphology showed that layer 6 cells are smaller, have a horizontal orientation, and have very long dendrites (>500 μm) that branch profusely both near the soma distally near the pia. Layer 5 corticocollicular cells are large pyramidal cells with a long apical dendrite with most branching near the pial surface. The marked differences in physiological properties and dendritic arborization between neurons in layers 5 and 6 make it likely that each type plays a distinct role in controlling auditory information processing in the midbrain.

Constellation of HCN channels and cAMP regulating proteins in dendritic spines of the primate prefrontal cortex: potential substrate for working memory deficits in schizophrenia

Schizophrenia associates with impaired prefrontal cortical (PFC) function and alterations in cyclic AMP (cAMP) signaling pathways. These include genetic insults to disrupted-in-schizophrenia (DISC1) and phosphodiesterases (PDE4s) regulating cAMP hydrolysis, and increased dopamine D1 receptor (D1R) expression that elevates cAMP. We used immunoelectron microscopy to localize DISC1, PDE4A, PDE4B, and D1R in monkey PFC and to view spatial interactions with hyperpolarization-activated cyclic nucleotide-gated (HCN) channels that gate network inputs when opened by cAMP. Physiological interactions between PDE4s and HCN channels were tested in recordings of PFC neurons in monkeys performing a spatial working memory task. The study reveals a constellation of cAMP-related proteins (DISC1, PDE4A, and D1R) and HCN channels next to excitatory synapses and the spine neck in thin spines of superficial PFC, where working memory microcircuits interconnect and spine loss is most evident in schizophrenia. In contrast, channels in dendrites were distant from synapses and cAMP-related proteins, and were associated with endosomal trafficking. The data suggest that a cAMP signalplex is selectively positioned in the spines to gate PFC pyramidal cell microcircuits. Single-unit recordings confirmed physiological interactions between cAMP and HCN channels, consistent with gating actions. These data may explain why PFC networks are especially vulnerable to genetic insults that dysregulate cAMP signaling.

Attractor dynamics of spatially correlated neural activity in the limbic system

Attractor networks are a popular computational construct used to model different brain systems. These networks allow elegant computations that are thought to represent a number of aspects of brain function. Although there is good reason to believe that the brain displays attractor dynamics, it has proven difficult to test experimentally whether any particular attractor architecture resides in any particular brain circuit. We review models and experimental evidence for three systems in the rat brain that are presumed to be components of the rat's navigational and memory system. Head-direction cells have been modeled as a ring attractor, grid cells as a plane attractor, and place cells both as a plane attractor and as a point attractor. Whereas the models have proven to be extremely useful conceptual tools, the experimental evidence in their favor, although intriguing, is still mostly circumstantial.

A Scale-Invariant Internal Representation of Time

We propose a principled way to construct an internal representation of the temporal stimulus history leading up to the present moment. A set of leaky integrators performs a Laplace transform on the stimulus function, and a linear operator approximates the inversion of the Laplace transform. The result is a representation of stimulus history that retains information about the temporal sequence of stimuli. This procedure naturally represents more recent stimuli more accurately than less recent stimuli; the decrement in accuracy is precisely scale invariant. This procedure also yields time cells that fire at specific latencies following the stimulus with a scale-invariant temporal spread. Combined with a simple associative memory, this representation gives rise to a moment-to-moment prediction that is also scale invariant in time. We propose that this scale-invariant representation of temporal stimulus history could serve as an underlying representation accessible to higher-level behavioral and cognitive mechanisms. In order to illustrate the potential utility of this scale-invariant representation in a variety of fields, we sketch applications using minimal performance functions to problems in classical conditioning, interval timing, scale-invariant learning in autoshaping, and the persistence of the recency effect in episodic memory across timescales.

Persistent storage capability impairs decision making in a biophysical network model

Two long-standing questions in neuroscience concern the mechanisms underlying our abilities to make decisions and to store goal-relevant information in memory for seconds at a time. Recent experimental and theoretical advances suggest that NMDA receptors at intrinsic cortical synapses play an important role in both these functions. The long NMDA time constant is suggested to support persistent mnemonic activity by maintaining excitatory drive after the removal of a stimulus and to enable the slow integration of afferent information in the service of decisions. These findings have led to the hypothesis that the local circuit mechanisms underlying decisions must also furnish persistent storage of information. We use a local circuit cortical model of spiking neurons to test this hypothesis, controlling intrinsic drive by scaling NMDA conductance strength. Our simulations provide further evidence that persistent storage and decision making are supported by common mechanisms, but under biophysically realistic parameters, our model demonstrates that the processing requirements of persistent storage and decision making may be incompatible at the local circuit level. Parameters supporting persistent storage lead to strong dynamics that are at odds with slow integration, whereas weaker dynamics furnish the speed-accuracy trade-off common to psychometric data and decision theory.

Impact of infralimbic inputs on intercalated amygdala neurons: a biophysical modeling study

Intercalated (ITC) amygdala neurons regulate fear expression by controlling impulse traffic between the input (basolateral amygdala; BLA) and output (central nucleus; Ce) stations of the amygdala for conditioned fear responses. Previously, stimulation of the infralimbic (IL) cortex was found to reduce fear expression and the responsiveness of Ce neurons to BLA inputs. These effects were hypothesized to result from the activation of ITC cells projecting to Ce. However, ITC cells inhibit each other, leading to the question of how IL inputs could overcome the inter-ITC inhibition to regulate the responses of Ce neurons to aversive conditioned stimuli (CSs). To investigate this, we first developed a compartmental model of a single ITC cell that could reproduce their bistable electroresponsive properties, as observed experimentally. Next, we generated an ITC network that implemented the experimentally observed short-term synaptic plasticity of inhibitory inter-ITC connections. Model experiments showed that strongly adaptive CS-related BLA inputs elicited persistent responses in ITC cells despite the presence of inhibitory interconnections. The sustained CS-evoked activity of ITC cells resulted from an unusual slowly deinactivating K(+) current. Finally, over a wide range of stimulation strengths, brief IL activation caused a marked increase in the firing rate of ITC neurons, leading to a persistent decrease in Ce output, despite inter-ITC inhibition. Simulations revealed that this effect depended on the bistable properties and synaptic heterogeneity of ITC neurons. These results support the notion that IL inputs are in a strategic position to control extinction of conditioned fear via the activation of ITC neurons.

Single-cell persistent activity in anterodorsal thalamus

The anterodorsal nucleus of the thalamus contains a high percentage of head-direction cells whose activities are correlated with an animal's directional heading in the horizontal plane. The firing of head-direction cells could involve self-sustaining reverberating activity in a recurrent network, but the thalamus by itself lacks strong excitatory recurrent synaptic connections to sustain tonic reverberating activity. Here we examined whether a single thalamic neuron could sustain its own activity without synaptic input by recording from individual neurons from anterodorsal thalamus in brain slices with synaptic blockers. We found that the rebound firing induced by hyperpolarizing pulses often decayed slowly so that a thalamic neuron could keep on firing for many minutes after stimulation. The hyperpolarization-induced persistent firing rate was graded under repeated current injections, and could be enhanced by serotonin. The effect of depolarizing pulses was much weaker and only slightly accelerated the decay of the hyperpolarization-induced persistent firing. Our finding provides the first direct evidence for single-cell persistent activity in the thalamus, supporting the notion that cellular mechanisms at the slow time scale of minutes might potentially contribute to the operations of the head-direction system.

TRP channels and neural persistent activity

One of the integrative properties of the nervous system is its capability to, by transient motor commands or brief sensory stimuli, evoke persistent neuronal changes, mainly as a sustained, tonic action potential firing. This neural activity, named persistent activity, is found in a good number of brain regions and is thought to be a neural substrate for short-term storage and accumulation of sensory or motor information [1]. Examples of this persistent neural activity have been reported in prefrontal [2] and entorhinal [3] cortices, as part of the neural mechanisms involved in short-term working memory [4]. Interestingly, the general organization of the motor systems assumes the presence of bursts of short-lasting motor commands encoding movement characteristics such as velocity, duration, and amplitude, followed by a maintained tonic firing encoding the position at which the moving appendage should be maintained [5, 6]. Generation of qualitatively similar sustained discharges have also been found in spinal and supraspinal regions in relation to pain processing [7, 8]. Thus, persistent neural activity seems to be necessary for both behavioral (positions of fixation) and cognitive (working memory) processes. Persistent firing mechanisms have been proposed to involve the participation of a non-specific cationic current (CAN current) mainly mediated by activation of TRPC channels. Because the function and generation of persistent activity is still poorly understood, here we aimed to review and discuss the putative role of TRP-like channels on its generation and/or maintenance.

History-dependent excitability as a single-cell substrate of transient memory for information discrimination

Neurons react differently to incoming stimuli depending upon their previous history of stimulation. This property can be considered as a single-cell substrate for transient memory, or context-dependent information processing: depending upon the current context that the neuron "sees" through the subset of the network impinging on it in the immediate past, the same synaptic event can evoke a postsynaptic spike or just a subthreshold depolarization. We propose a formal definition of History-Dependent Excitability (HDE) as a measure of the propensity to firing in any moment in time, linking the subthreshold history-dependent dynamics with spike generation. This definition allows the quantitative assessment of the intrinsic memory for different single-neuron dynamics and input statistics. We illustrate the concept of HDE by considering two general dynamical mechanisms: the passive behavior of an Integrate and Fire (IF) neuron, and the inductive behavior of a Generalized Integrate and Fire (GIF) neuron with subthreshold damped oscillations. This framework allows us to characterize the sensitivity of different model neurons to the detailed temporal structure of incoming stimuli. While a neuron with intrinsic oscillations discriminates equally well between input trains with the same or different frequency, a passive neuron discriminates better between inputs with different frequencies. This suggests that passive neurons are better suited to rate-based computation, while neurons with subthreshold oscillations are advantageous in a temporal coding scheme. We also address the influence of intrinsic properties in single-cell processing as a function of input statistics, and show that intrinsic oscillations enhance discrimination sensitivity at high input rates. Finally, we discuss how the recognition of these cell-specific discrimination properties might further our understanding of neuronal network computations and their relationships to the distribution and functional connectivity of different neuronal types.

Modulation of firing rate by background synaptic noise statistics in rat visual cortical neurons

It has been shown previously that background synaptic noise modulates the response gain of neocortical neurons. However, the role of the statistical properties of the noise in modulating firing rate is not known. Here, the dependence of firing rate on the statistical properties of the excitatory to inhibitory balance (EI) in cortical pyramidal neurons was studied. Excitatory glutamatergic and inhibitory GABAergic synaptic conductances were simulated as two stochastic processes and injected into individual neurons in vitro through use of the dynamic-clamp system. Response gain was significantly modulated as a function of the statistical interactions between excitatory and inhibitory synaptic conductances. Firing rates were compared for noisy synaptic conductance steps by varying either the EI correlation or the relative delay between correlated E and I. When inhibitory synaptic conductances exhibited a short temporal delay (5 ms) relative to correlated excitatory synaptic conductances, the response gain was increased compared with noise with no temporal delay but with an equivalent degree of correlation. The dependence of neuronal firing rate on the EI delay of the noisy background synaptic conductance suggests that individual excitatory pyramidal neurons are sensitive to the EI balance of the synaptic conductance. Therefore the statistical EI interactions encoded within the synaptic subthreshold membrane fluctuations are able to modulate neuronal firing properties.

Spike integration and cellular memory in a rhythmic network from Na+/K+ pump current dynamics

The output of a neural circuit results from an interaction between the intrinsic properties of neurons within the circuit and the features of the synaptic connections between them. The plasticity of intrinsic properties has been primarily attributed to modification of ion channel function and/or number. In this study, we demonstrate a mechanism for intrinsic plasticity in rhythmically active Drosophila neurons that is not conductance-based. Larval motor neurons show a long lasting sodium-dependent afterhyperpolarization (AHP) following bursts of action potentials that is mediated by the electrogenic activity of Na⁺/K⁺ ATPase. This AHP persists for multiple seconds following volleys of action potentials and is able to function as a pattern-insensitive integrator of spike number that is independent of external calcium. This current also interacts with endogenous Shal K⁺ conductances to modulate spike timing for multiple seconds following rhythmic activity, providing a cellular memory of network activity on a behaviorally relevant time scale.

The modulation of orexin A on HCN currents of pyramidal neurons in mouse prelimbic cortex

The hyperpolarization-activated/cyclic nucleotide (HCN)-gated channels make important contributions to neural excitability. In prefrontal cortex, HCN channels are localized on the distal dendrites of layer V pyramidal neurons and decrease neural excitability when they are open. In the present study, using whole-cell voltage clamp recordings, the effect of an arousal peptide, orexin A, on HCN currents in layer V pyramidal neurons from mouse prelimbic cortex (PL), the homolog of the prefrontal cortex was investigated. The results demonstrated that orexin A suppressed HCN currents and shifted their activation curve to a more negative direction. This action of orexin A was blocked by SB334867, an orexin receptor 1 (OXR1) blocker and bisindolylmaleimide, a protein kinase C (PKC) inhibitor, indicating the involvement of OXR1 and PKC. The excitatory effect of orexin A on PL pyramidal neurons was enhanced when HCN currents were diminished, while attenuated when HCN currents were enlarged. In summary, orexin A inhibits HCN currents and enhances excitability of pyramidal neurons in PL, which may contribute to arousal and cognition.

The electrocortical effects of enflurane: experiment and theory

BACKGROUND

High concentrations of enflurane will induce a characteristic electroencephalogram pattern consisting of periods of suppression alternating with large short paroxysmal epileptiform discharges (PEDs). In this study, we compared a theoretical computer model of this activity with real local field potential (LFP) data obtained from anesthetized rats.

METHODS

After implantation of a high-density 8 x 8 electrode array in the visual cortex, the patterns of LFP and multiunit spike activity were recorded in rats during 0.5, 1.0, 1.5, and 2.0 minimum alveolar anesthetic concentration (MAC) enflurane anesthesia. These recordings were compared with computer simulations from a mean field model of neocortical dynamics. The neuronal effect of increasing enflurane concentration was simulated by prolonging the decay time constant of the inhibitory postsynaptic potential (IPSP). The amplitude of the excitatory postsynaptic potential (EPSP) was modulated, inverse to the neocortical firing rate.

RESULTS

In the anesthetized rats, increasing enflurane concentrations consistently caused the appearance of suppression pattern (>1.5 MAC) in the LFP recordings. The mean rate of multiunit spike activity decreased from 2.54/s (0.5 MAC) to 0.19/s (2.0 MAC). At high MAC, the majority of the multiunit action potential events became synchronous with the PED. In the theoretical model, prolongation of the IPSP decay time and activity-dependent EPSP modulation resulted in output that was similar in morphology to that obtained from the experimental data. The propensity for rhythmic seizure-like activity in the model could be determined by analysis of the eigenvalues of the equations.

CONCLUSION

It is possible to use a mean field theory of neocortical dynamics to replicate the PED pattern observed in LFPs in rats under enflurane anesthesia. This pattern requires a combination of a moderately increased total area under the IPSP, prolonged IPSP decay time, and also activity-dependent modulation of EPSP amplitude.

Graded information extraction by neural-network dynamics with multihysteretic neurons

A major goal in the study of neural networks is to create novel information-processing algorithms inferred from the real brain. Recent neurophysiological evidence of graded persistent activity suggests that the brain possesses neural mechanisms for retrieval of graded information, which could be described by the neural-network dynamics with attractors that are continuously dependent on the initial state. Theoretical studies have also demonstrated that model neurons with a multihysteretic response property can generate robust continuous attractors. Inspired by these lines of evidence, we proposed an algorithm given by the multihysteretic neuron-network dynamics, devised to retrieve graded information specific to a given topic (i.e., context, represented by the initial state). To demonstrate the validity of the proposed algorithm, we examined keyword extraction from documents, which is best fitted for evaluating the appropriateness of retrieval of graded information. The performance of keyword extraction by using our algorithm was significantly high (measured by the average precision of document retrieval, for which the appropriateness of keyword extraction is crucial) compared with standard document-retrieval methods. Moreover, our algorithm exhibited much higher performance than the neural-network dynamics with bistable neurons, which can also produce robust continuous attractors but only represent dichotomous information at the single-cell level. These findings indicate that the capability to manage graded information at the single-cell level was essential for obtaining a high performing algorithm.

Differences in intrinsic properties and local network connectivity of identified layer 5 and layer 6 adult mouse auditory corticothalamic neurons support a dual corticothalamic projection hypothesis

Intrinsic properties, morphology, and local network circuitry of identified layer 5 and layer 6 auditory corticothalamic neurons were compared. We injected fluorescent microspheres into the mouse auditory thalamus to prelabel corticothalamic neurons, then recorded and filled labeled layer 5 or layer 6 auditory cortical neurons in vitro. We observed low-threshold bursting in adult, but not juvenile, layer 5 corticothalamic neurons that was voltage and time dependent with nonlinear input-output properties, whereas adult layer 6 corticothalamic neurons demonstrated a regular spiking. Layer 5 corticothalamic neurons had larger somata, thicker apical dendrites and were more likely to have a layer 1 apical dendrite than layer 6 neurons. Using laser photostimulation, identified layer 5 corticothalamic neurons received excitatory input from a wide area of layers 2/3, 4, and 5 with widespread gamma-aminobutyric acidergic input from layer 2/3 and lower layer 5, whereas layer 6 corticothalamic neurons from the same cortical column received circumscribed excitatory input and discrete patches of inhibition derived from layer 6 of adjacent columns. These data demonstrate that layer 5 and layer 6 corticothalamic neurons receive unique sets of inputs and process them in different manners, supporting the hypothesis that layer-specific corticothalamic projections play distinct roles in information processing.

The response of cortical neurons to in vivo-like input current: theory and experiment : I. Noisy inputs with stationary statistics

The study of several aspects of the collective dynamics of interacting neurons can be highly simplified if one assumes that the statistics of the synaptic input is the same for a large population of similarly behaving neurons (mean field approach). In particular, under such an assumption, it is possible to determine and study all the equilibrium points of the network dynamics when the neuronal response to noisy, in vivo-like, synaptic currents is known. The response function can be computed analytically for simple integrate-and-fire neuron models and it can be measured directly in experiments in vitro. Here we review theoretical and experimental results about the neural response to noisy inputs with stationary statistics. These response functions are important to characterize the collective neural dynamics that are proposed to be the neural substrate of working memory, decision making and other cognitive functions. Applications to the case of time-varying inputs are reviewed in a companion paper (Giugliano et al. in Biol Cybern, 2008). We conclude that modified integrate-and-fire neuron models are good enough to reproduce faithfully many of the relevant dynamical aspects of the neuronal response measured in experiments on real neurons in vitro.