Voltage-gated K+ channels in layer 5 neocortical pyramidal neurones from young rats: subtypes and gradients

GluN2C/D-containing NMDA receptors enhance temporal summation and increase sound-evoked and spontaneous firing in the inferior colliculus

Along the ascending auditory pathway, there is a broad shift from temporal coding, which is common in the lower auditory brainstem, to rate coding, which predominates in auditory cortex. This temporal-to-rate transition is particularly prominent in the inferior colliculus (IC), the midbrain hub of the auditory system, but the mechanisms that govern how individual IC neurons integrate information across time remain largely unknown. Here, we report the widespread expression of Glun2c and Glun2d mRNA in IC neurons. GluN2C/D-containing NMDA receptors are relatively insensitive to voltage-dependent Mg2+ block, and thus can conduct current at resting membrane potential. Using in situ hybridization and pharmacology, we show that VIP neurons in the IC express GluN2D-containing NMDA receptors that are activatable by commissural inputs from the contralateral IC. In addition, GluN2C/D-containing receptors have much slower kinetics than other NMDA receptors, and we found that GluN2D-containing receptors facilitate temporal summation of synaptic inputs in VIP neurons. In a model neuron, we show that a GluN2C/D-like conductance interacts with the passive membrane properties of the neuron to alter temporal and rate coding of stimulus trains. Consistent with this, we show in vivo that blocking GluN2C/D-containing receptors decreases both the spontaneous firing rate and the overall firing rate elicited by amplitude-modulated (AM) sounds in many IC neurons. These results suggest that GluN2C/D-containing NMDA receptors influence rate coding for auditory stimuli in the IC by facilitating the temporal integration of synaptic inputs.

Data-driven multiscale computational models of cortical and subcortical regions

Data-driven computational models of neurons, synapses, microcircuits, and mesocircuits have become essential tools in modern brain research. The goal of these multiscale models is to integrate and synthesize information from different levels of brain organization, from cellular properties, dendritic excitability, and synaptic dynamics to microcircuits, mesocircuits, and ultimately behavior. This article surveys recent advances in the genesis of data-driven computational models of mammalian neural networks in cortical and subcortical areas. I discuss the challenges and opportunities in developing data-driven multiscale models, including the need for interdisciplinary collaborations, the importance of model validation and comparison, and the potential impact on basic and translational neuroscience research. Finally, I highlight future directions and emerging technologies that will enable more comprehensive and predictive data-driven models of brain function and dysfunction.

Spontaneous slow wave oscillations in extracellular field potential recordings reflect the alternating dominance of excitation and inhibition

In the resting state, cortical neurons can fire action potentials spontaneously but synchronously (Up state), followed by a quiescent period (Down state) before the cycle repeats. Extracellular recordings in the infragranular layer of cortex with a micro-electrode display a negative deflection (depth-negative) during Up states and a positive deflection (depth-positive) during Down states. The resulting slow wave oscillation (SWO) has been studied extensively during sleep and under anaesthesia. However, recent research on the balanced nature of synaptic excitation and inhibition has highlighted our limited understanding of its genesis. Specifically, are excitation and inhibition balanced during SWOs? We analyse spontaneous local field potentials (LFPs) during SWOs recorded from anaesthetised rats via a multi-channel laminar micro-electrode and show that the Down state consists of two distinct synaptic states: a Dynamic Down state associated with depth-positive LFPs and a prominent dipole in the extracellular field, and a Static Down state with negligible (≈ 0 mV $ \approx 0{\mathrm{\;mV}}$ ) LFPs and a lack of dipoles extracellularly. We demonstrate that depth-negative and -positive LFPs are generated by a shift in the balance of synaptic excitation and inhibition from excitation dominance (depth-negative) to inhibition dominance (depth-positive) in the infragranular layer neurons. Thus, although excitation and inhibition co-tune overall, differences in their timing lead to an alternation of dominance, manifesting as SWOs. We further show that Up state initiation is significantly faster if the preceding Down state is dynamic rather than static. Our findings provide a coherent picture of the dependence of SWOs on synaptic activity. KEY POINTS: Cortical neurons can exhibit repeated cycles of spontaneous activity interleaved with periods of relative silence, a phenomenon known as 'slow wave oscillation' (SWO). During SWOs, recordings of local field potentials (LFPs) in the neocortex show depth-negative deflection during the active period (Up state) and depth-positive deflection during the silent period (Down state). Here we further classified the Down state into a dynamic phase and a static phase based on a novel method of classification and revealed non-random, stereotypical sequences of the three states occurring with significantly different transitional kinetics. Our results suggest that the positive and negative deflections in the LFP reflect the shift of the instantaneous balance between excitatory and inhibitory synaptic activity of the local cortical neurons. The differences in transitional kinetics may imply distinct synaptic mechanisms for Up state initiation. The study may provide a new approach for investigating spontaneous brain rhythms.

A universal workflow for creation, validation, and generalization of detailed neuronal models

Detailed single-neuron modeling is widely used to study neuronal functions. While cellular and functional diversity across the mammalian cortex is vast, most of the available computational tools focus on a limited set of specific features characteristic of a single neuron. Here, we present a generalized automated workflow for the creation of robust electrical models and illustrate its performance by building cell models for the rat somatosensory cortex. Each model is based on a 3D morphological reconstruction and a set of ionic mechanisms. We use an evolutionary algorithm to optimize neuronal parameters to match the electrophysiological features extracted from experimental data. Then we validate the optimized models against additional stimuli and assess their generalizability on a population of similar morphologies. Compared to the state-of-the-art canonical models, our models show 5-fold improved generalizability. This versatile approach can be used to build robust models of any neuronal type.

Simulations predict differing phase responses to excitation vs. inhibition in theta-resonant pyramidal neurons

Rhythmic activity is ubiquitous in neural systems, with theta-resonant pyramidal neurons integrating rhythmic inputs in many cortical structures. Impedance analysis has been widely used to examine frequency-dependent responses of neuronal membranes to rhythmic inputs, but it assumes that the neuronal membrane is a linear system, requiring the use of small signals to stay in a near-linear regime. However, postsynaptic potentials are often large and trigger nonlinear mechanisms (voltage-gated ion channels). The goals of this work were to 1) develop an analysis method to evaluate membrane responses in this nonlinear domain and 2) explore phase relationships between rhythmic stimuli and subthreshold and spiking membrane potential (Vmemb) responses in models of theta-resonant pyramidal neurons. Responses in these output regimes were asymmetrical, with different phase shifts during hyperpolarizing and depolarizing half-cycles. Suprathreshold theta-rhythmic stimuli produced nonstationary Vmemb responses. Sinusoidal inputs produced "phase retreat": action potentials occurred progressively later in cycles of the input stimulus, resulting from adaptation. Sinusoidal current with increasing amplitude over cycles produced "phase advance": action potentials occurred progressively earlier. Phase retreat, phase advance, and subthreshold phase shifts were modulated by multiple ion channel conductances. Our results suggest differential responses of cortical neurons depending on the frequency of oscillatory input, which will play a role in neuronal responses to shifts in network state. We hypothesize that intrinsic cellular properties complement network properties and contribute to in vivo phase-shift phenomena such as phase precession, seen in place and grid cells, and phase roll, also observed in hippocampal CA1 neurons.NEW & NOTEWORTHY We augmented electrical impedance analysis to characterize phase shifts between large-amplitude current stimuli and nonlinear, asymmetric membrane potential responses. We predict different frequency-dependent phase shifts in response excitation vs. inhibition, as well as shifts in spike timing over multiple input cycles, in theta-resonant pyramidal neurons. We hypothesize that these effects contribute to navigation-related phenomena such as phase precession and phase roll. Our neuron-level hypothesis complements, rather than falsifies, prior network-level explanations of these phenomena.

Overexpression of UCP4 in astrocytic mitochondria prevents multilevel dysfunctions in a mouse model of Alzheimer's disease

Alzheimer's disease (AD) is becoming increasingly prevalent worldwide. It represents one of the greatest medical challenges as no pharmacologic treatments are available to prevent disease progression. Astrocytes play crucial functions within neuronal circuits by providing metabolic and functional support, regulating interstitial solute composition, and modulating synaptic transmission. In addition to these physiological functions, growing evidence points to an essential role of astrocytes in neurodegenerative diseases like AD. Early-stage AD is associated with hypometabolism and oxidative stress. Contrary to neurons that are vulnerable to oxidative stress, astrocytes are particularly resistant to mitochondrial dysfunction and are therefore more resilient cells. In our study, we leveraged astrocytic mitochondrial uncoupling and examined neuronal function in the 3xTg AD mouse model. We overexpressed the mitochondrial uncoupling protein 4 (UCP4), which has been shown to improve neuronal survival in vitro. We found that this treatment efficiently prevented alterations of hippocampal metabolite levels observed in AD mice, along with hippocampal atrophy and reduction of basal dendrite arborization of subicular neurons. This approach also averted aberrant neuronal excitability observed in AD subicular neurons and preserved episodic-like memory in AD mice assessed in a spatial recognition task. These findings show that targeting astrocytes and their mitochondria is an effective strategy to prevent the decline of neurons facing AD-related stress at the early stages of the disease.

Thalamic control of sensory processing and spindles in a biophysical somatosensory thalamoreticular circuit model of wakefulness and sleep

Thalamoreticular circuitry plays a key role in arousal, attention, cognition, and sleep spindles, and is linked to several brain disorders. A detailed computational model of mouse somatosensory thalamus and thalamic reticular nucleus has been developed to capture the properties of over 14,000 neurons connected by 6 million synapses. The model recreates the biological connectivity of these neurons, and simulations of the model reproduce multiple experimental findings in different brain states. The model shows that inhibitory rebound produces frequency-selective enhancement of thalamic responses during wakefulness. We find that thalamic interactions are responsible for the characteristic waxing and waning of spindle oscillations. In addition, we find that changes in thalamic excitability control spindle frequency and their incidence. The model is made openly available to provide a new tool for studying the function and dysfunction of the thalamoreticular circuitry in various brain states.

NeuroML-DB: Sharing and characterizing data-driven neuroscience models described in NeuroML

As researchers develop computational models of neural systems with increasing sophistication and scale, it is often the case that fully de novo model development is impractical and inefficient. Thus arises a critical need to quickly find, evaluate, re-use, and build upon models and model components developed by other researchers. We introduce the NeuroML Database (NeuroML-DB.org), which has been developed to address this need and to complement other model sharing resources. NeuroML-DB stores over 1,500 previously published models of ion channels, cells, and networks that have been translated to the modular NeuroML model description language. The database also provides reciprocal links to other neuroscience model databases (ModelDB, Open Source Brain) as well as access to the original model publications (PubMed). These links along with Neuroscience Information Framework (NIF) search functionality provide deep integration with other neuroscience community modeling resources and greatly facilitate the task of finding suitable models for reuse. Serving as an intermediate language, NeuroML and its tooling ecosystem enable efficient translation of models to other popular simulator formats. The modular nature also enables efficient analysis of a large number of models and inspection of their properties. Search capabilities of the database, together with web-based, programmable online interfaces, allow the community of researchers to rapidly assess stored model electrophysiology, morphology, and computational complexity properties. We use these capabilities to perform a database-scale analysis of neuron and ion channel models and describe a novel tetrahedral structure formed by cell model clusters in the space of model properties and features. This analysis provides further information about model similarity to enrich database search.

Electrophysiology of Dendritic Spines: Information Processing, Dynamic Compartmentalization, and Synaptic Plasticity

For many years, synaptic transmission was considered as information transfer between presynaptic neuron and postsynaptic cell. At the synaptic level, it was thought that dendritic arbors were only receiving and integrating all information flow sent along to the soma, while axons were primarily responsible for point-to-point information transfer. However, it is important to highlight that dendritic spines play a crucial role as postsynaptic components in central nervous system (CNS) synapses, not only integrating and filtering signals to the soma but also facilitating diverse connections with axons from many different sources. The majority of excitatory connections from presynaptic axonal terminals occurs on postsynaptic spines, although a subset of GABAergic synapses also targets spine heads. Several studies have shown the vast heterogeneous morphological, biochemical, and functional features of dendritic spines related to synaptic processing. In this chapter (adding to the relevant data on the biophysics of spines described in Chap. 1 of this book), we address the up-to-date functional dendritic characteristics assessed through electrophysiological approaches, including backpropagating action potentials (bAPs) and synaptic potentials mediated in dendritic and spine compartmentalization, as well as describing the temporal and spatial dynamics of glutamate receptors in the spines related to synaptic plasticity.

Dendritic Excitability and Synaptic Plasticity In Vitro and In Vivo

Much of our understanding of dendritic and synaptic physiology comes from in vitro experimentation, where the afforded mechanical stability and convenience of applying drugs allowed patch-clamping based recording techniques to investigate ion channel distributions, their gating kinetics, and to uncover dendritic integrative and synaptic plasticity rules. However, with current efforts to study these questions in vivo, there is a great need to translate existing knowledge between in vitro and in vivo experimental conditions. In this review, we identify discrepancies between in vitro and in vivo ionic composition of extracellular media and discuss how changes in ionic composition alter dendritic excitability and plasticity induction. Here, we argue that under physiological in vivo ionic conditions, dendrites are expected to be more excitable and the threshold for synaptic plasticity induction to be lowered. Consequently, the plasticity rules described in vitro vary significantly from those implemented in vivo.

Computational Concepts for Reconstructing and Simulating Brain Tissue

It has previously been shown that it is possible to derive a new class of biophysically detailed brain tissue models when one computationally analyzes and exploits the interdependencies or the multi-modal and multi-scale organization of the brain. These reconstructions, sometimes referred to as digital twins, enable a spectrum of scientific investigations. Building such models has become possible because of increase in quantitative data but also advances in computational capabilities, algorithmic and methodological innovations. This chapter presents the computational science concepts that provide the foundation to the data-driven approach to reconstructing and simulating brain tissue as developed by the EPFL Blue Brain Project, which was originally applied to neocortical microcircuitry and extended to other brain regions. Accordingly, the chapter covers aspects such as a knowledge graph-based data organization and the importance of the concept of a dataset release. We illustrate algorithmic advances in finding suitable parameters for electrical models of neurons or how spatial constraints can be exploited for predicting synaptic connections. Furthermore, we explain how in silico experimentation with such models necessitates specific addressing schemes or requires strategies for an efficient simulation. The entire data-driven approach relies on the systematic validation of the model. We conclude by discussing complementary strategies that not only enable judging the fidelity of the model but also form the basis for its systematic refinements.

Kinetic and thermodynamic modeling of a voltage-gated sodium channel

Like all biological and chemical reactions, ion channel kinetics are highly sensitive to changes in temperature. Therefore, it is prudent to investigate channel dynamics at physiological temperatures. However, most ion channel investigations are performed at room temperature due to practical considerations, such as recording stability and technical limitations. This problem is especially severe for the fast voltage-gated sodium channel, whose activation kinetics are faster than the time constant of the standard patch-clamp amplifier at physiological temperatures. Thus, biologically detailed simulations of the action potential generation evenly scale the kinetic models of voltage-gated channels acquired at room temperature. To quantitatively study voltage-gated sodium channels' temperature sensitivity, we recorded sodium currents from nucleated patches extracted from the rat's layer five neocortical pyramidal neurons at several temperatures from 13.5 to 30 °C. We use these recordings to model the kinetics of the voltage-gated sodium channel as a function of temperature. We show that the temperature dependence of activation differs from that of inactivation. Furthermore, the data indicate that the sustained current has a different temperature dependence than the fast current. Our kinetic and thermodynamic analysis of the current provided a numerical model spanning the entire temperature range. This model reproduced vital features of channel activation and inactivation. Furthermore, the model also reproduced action potential dependence on temperature. Thus, we provide an essential building block for the generation of biologically detailed models of cortical neurons.

NeuroGPU: Accelerating multi-compartment, biophysically detailed neuron simulations on GPUs

BACKGROUND

The membrane potential of individual neurons depends on a large number of interacting biophysical processes operating on spatial-temporal scales spanning several orders of magnitude. The multi-scale nature of these processes dictates that accurate prediction of membrane potentials in specific neurons requires the utilization of detailed simulations. Unfortunately, constraining parameters within biologically detailed neuron models can be difficult, leading to poor model fits. This obstacle can be overcome partially by numerical optimization or detailed exploration of parameter space. However, these processes, which currently rely on central processing unit (CPU) computation, often incur orders of magnitude increases in computing time for marginal improvements in model behavior. As a result, model quality is often compromised to accommodate compute resources.

NEW METHOD

Here, we present a simulation environment, NeuroGPU, that takes advantage of the inherent parallelized structure of the graphics processing unit (GPU) to accelerate neuronal simulation.

RESULTS & COMPARISON WITH EXISTING METHODS

NeuroGPU can simulate most biologically detailed models 10-200 times faster than NEURON simulation running on a single core and 5 times faster than GPU simulators (CoreNEURON). NeuroGPU is designed for model parameter tuning and best performs when the GPU is fully utilized by running multiple (> 100) instances of the same model with different parameters. When using multiple GPUs, NeuroGPU can reach to a speed-up of 800 fold compared to single core simulations, especially when simulating the same model morphology with different parameters. We demonstrate the power of NeuoGPU through large-scale parameter exploration to reveal the response landscape of a neuron. Finally, we accelerate numerical optimization of biophysically detailed neuron models to achieve highly accurate fitting of models to simulation and experimental data.

CONCLUSIONS

Thus, NeuroGPU is the fastest available platform that enables rapid simulation of multi-compartment, biophysically detailed neuron models on commonly used computing systems accessible by many scientists.

Kv2.1 Potassium Channels Regulate Repetitive Burst Firing in Extratelencephalic Neocortical Pyramidal Neurons

Coincidence detection and cortical rhythmicity are both greatly influenced by neurons' propensity to fire bursts of action potentials. In the neocortex, repetitive burst firing can also initiate abnormal neocortical rhythmicity (including epilepsy). Bursts are generated by inward currents that underlie a fast afterdepolarization (fADP) but less is known about outward currents that regulate bursting. We tested whether Kv2 channels regulate the fADP and burst firing in labeled layer 5 PNs from motor cortex of the Thy1-h mouse. Kv2 block with guangxitoxin-1E (GTx) converted single spike responses evoked by dendritic stimulation into multispike bursts riding on an enhanced fADP. Immunohistochemistry revealed that Thy1-h PNs expressed Kv2.1 (not Kv2.2) channels perisomatically (not in the dendrites). In somatic macropatches, GTx-sensitive current was the largest component of outward current with biophysical properties well-suited for regulating bursting. GTx drove ~40% of Thy1 PNs stimulated with noisy somatic current steps to repetitive burst firing and shifted the maximal frequency-dependent gain. A network model showed that reduction of Kv2-like conductance in a small subset of neurons resulted in repetitive bursting and entrainment of the circuit to seizure-like rhythmic activity. Kv2 channels play a dominant role in regulating onset bursts and preventing repetitive bursting in Thy1 PNs.

Paradoxical hyperexcitability from NaV1.2 sodium channel loss in neocortical pyramidal cells

Loss-of-function variants in the gene SCN2A, which encodes the sodium channel NaV1.2, are strongly associated with autism spectrum disorder and intellectual disability. An estimated 20%-30% of children with these variants also suffer from epilepsy, with altered neuronal activity originating in neocortex, a region where NaV1.2 channels are expressed predominantly in excitatory pyramidal cells. This is paradoxical, as sodium channel loss in excitatory cells would be expected to dampen neocortical activity rather than promote seizure. Here, we examined pyramidal neurons lacking NaV1.2 channels and found that they were intrinsically hyperexcitable, firing high-frequency bursts of action potentials (APs) despite decrements in AP size and speed. Compartmental modeling and dynamic-clamp recordings revealed that NaV1.2 loss prevented potassium channels from properly repolarizing neurons between APs, increasing overall excitability by allowing neurons to reach threshold for subsequent APs more rapidly. This cell-intrinsic mechanism may, therefore, account for why SCN2A loss-of-function can paradoxically promote seizure.

Active dendrites enable strong but sparse inputs to determine orientation selectivity

The dendrites of neocortical pyramidal neurons are excitable. However, it is unknown how synaptic inputs engage nonlinear dendritic mechanisms during sensory processing in vivo, and how they in turn influence action potential output. Here, we provide a quantitative account of the relationship between synaptic inputs, nonlinear dendritic events, and action potential output. We developed a detailed pyramidal neuron model constrained by in vivo dendritic recordings. We drive this model with realistic input patterns constrained by sensory responses measured in vivo and connectivity measured in vitro. We show mechanistically that under realistic conditions, dendritic Na+ and NMDA spikes are the major determinants of neuronal output in vivo. We demonstrate that these dendritic spikes can be triggered by a surprisingly small number of strong synaptic inputs, in some cases even by single synapses. We predict that dendritic excitability allows the 1% strongest synaptic inputs of a neuron to control the tuning of its output. Active dendrites therefore allow smaller subcircuits consisting of only a few strongly connected neurons to achieve selectivity for specific sensory features.

Rethinking Single Neuron Electrical Compartmentalization: Dendritic Contributions to Network Computation In Vivo

Decades of experimental and theoretical work support a now well-established theory that active dendritic processing contributes to the computational power of individual neurons. This theory is based on the high degree of electrical compartmentalization observed in the dendrites of single neurons in ex vivo preparations. Compartmentalization allows dendrites to conduct semi-independent operations on their inputs before final integration and output at the axon, producing a "network-in-a-neuron." However, recent in vivo functional imaging experiments in mouse cortex have reported surprisingly little evidence for strong dendritic compartmentalization. In this review, we contextualize these new findings and discuss their impact on the future of the field. Specifically, we consider how highly coordinated, and thus less compartmentalized, activity in soma and dendrites can contribute to cortical computations including nonlinear mixed selectivity, prediction/expectation, multiplexing, and credit assignment.

A Minimal Biophysical Model of Neocortical Pyramidal Cells: Implications for Frontal Cortex Microcircuitry and Field Potential Generation

Ca²⁺ spikes initiated in the distal trunk of layer 5 pyramidal cells (PCs) underlie nonlinear dynamic changes in the gain of cellular response, critical for top-down control of cortical processing. Detailed models with many compartments and dozens of ionic channels can account for this Ca²⁺ spike-dependent gain and associated critical frequency. However, current models do not account for all known Ca²⁺-dependent features. Previous attempts to include more features have required increasing complexity, limiting their interpretability and utility for studying large population dynamics. We overcome these limitations in a minimal two-compartment biophysical model. In our model, a basal-dendrites/somatic compartment included fast-inactivating Na⁺ and delayed-rectifier K⁺ conductances, while an apical-dendrites/trunk compartment included persistent Na⁺, hyperpolarization-activated cation (I _h ), slow-inactivating K⁺, muscarinic K⁺, and Ca²⁺ L-type. The model replicated the Ca²⁺ spike morphology and its critical frequency plus three other defining features of layer 5 PC synaptic integration: linear frequency-current relationships, back-propagation-activated Ca²⁺ spike firing, and a shift in the critical frequency by blocking I _h Simulating 1000 synchronized layer 5 PCs, we reproduced the current source density patterns evoked by Ca²⁺ spikes and describe resulting medial-frontal EEG on a male macaque monkey. We reproduced changes in the current source density when I _h was blocked. Thus, a two-compartment model with five crucial ionic currents in the apical dendrites reproduces all features of these neurons. We discuss the utility of this minimal model to study the microcircuitry of agranular areas of the frontal lobe involved in cognitive control and responsible for event-related potentials, such as the error-related negativity.SIGNIFICANCE STATEMENT A minimal model of layer 5 pyramidal cells replicates all known features crucial for distal synaptic integration in these neurons. By redistributing voltage-gated and returning transmembrane currents in the model, we establish a theoretical framework for the investigation of cortical microcircuit contribution to intracranial local field potentials and EEG. This tractable model will enable biophysical evaluation of multiscale electrophysiological signatures and computational investigation of cortical processing.

Human Neocortical Neurosolver (HNN), a new software tool for interpreting the cellular and network origin of human MEG/EEG data

Magneto- and electro-encephalography (MEG/EEG) non-invasively record human brain activity with millisecond resolution providing reliable markers of healthy and disease states. Relating these macroscopic signals to underlying cellular- and circuit-level generators is a limitation that constrains using MEG/EEG to reveal novel principles of information processing or to translate findings into new therapies for neuropathology. To address this problem, we built Human Neocortical Neurosolver (HNN, https://hnn.brown.edu) software. HNN has a graphical user interface designed to help researchers and clinicians interpret the neural origins of MEG/EEG. HNN's core is a neocortical circuit model that accounts for biophysical origins of electrical currents generating MEG/EEG. Data can be directly compared to simulated signals and parameters easily manipulated to develop/test hypotheses on a signal's origin. Tutorials teach users to simulate commonly measured signals, including event related potentials and brain rhythms. HNN's ability to associate signals across scales makes it a unique tool for translational neuroscience research.

Deep Sequencing of Somatosensory Neurons Reveals Molecular Determinants of Intrinsic Physiological Properties

Dorsal root ganglion (DRG) sensory neuron subtypes defined by their in vivo properties display distinct intrinsic electrical properties. We used bulk RNA sequencing of genetically labeled neurons and electrophysiological analyses to define ion channel contributions to the intrinsic electrical properties of DRG neuron subtypes. The transcriptome profiles of eight DRG neuron subtypes revealed differentially expressed and functionally relevant genes, including voltage-gated ion channels. Guided by these data, electrophysiological analyses using pharmacological and genetic manipulations as well as computational modeling of DRG neuron subtypes were undertaken to assess the functions of select voltage-gated potassium channels (Kv1, Kv2, Kv3, and Kv4) in shaping action potential (AP) waveforms and firing patterns. Our findings show that the transcriptome profiles have predictive value for defining ion channel contributions to sensory neuron subtype-specific intrinsic physiological properties. The distinct ensembles of voltage-gated ion channels predicted to underlie the unique intrinsic physiological properties of eight DRG neuron subtypes are presented.

Transient Potassium Channels: Therapeutic Targets for Brain Disorders

Transient potassium current channels (I_A channels), which are expressed in most brain areas, have a central role in modulating feedforward and feedback inhibition along the dendroaxonic axis. Loss of the modulatory channels is tightly associated with a number of brain diseases such as Alzheimer’s disease, epilepsy, fragile X syndrome (FXS), Parkinson’s disease, chronic pain, tinnitus, and ataxia. However, the functional significance of I_A channels in these diseases has so far been underestimated. In this review, we discuss the distribution and function of I_A channels. Particularly, we posit that downregulation of I_A channels results in neuronal (mostly dendritic) hyperexcitability accompanied by the imbalanced excitation and inhibition ratio in the brain’s networks, eventually causing the brain diseases. Finally, we propose a potential therapeutic target: the enhanced action of I_A channels to counteract Ca²⁺-permeable channels including NMDA receptors could be harnessed to restore dendritic excitability, leading to a balanced neuronal state.

The Axon Initial Segment is the Dominant Contributor to the Neuron's Extracellular Electrical Potential Landscape

Extracellular voltage fields, produced by a neuron's action potentials, provide a widely used means for studying neuronal and neuronal-network function. The neuron's soma and dendrites are thought to drive the extracellular action potential (EAP) landscape, while the axon's contribution is usually considered less important. However, by recording voltages of single neurons in dissociated rat cortical cultures and Purkinje cells in acute mouse cerebellar slices through hundreds of densely packed electrodes, it is found, instead, that the axon initial segment dominates the measured EAP landscape, and, surprisingly, the soma only contributes to a minor extent. As expected, the recorded dominant signal has negative polarity (charge entering the cell) and initiates at the distal end. Interestingly, signals with positive polarity (charge exiting the cell) occur near some but not all dendritic branches and occur after a delay. Such basic knowledge about which neuronal compartments contribute to the extracellular voltage landscape is important for interpreting results from all electrical readout schemes. Finally, initiation of the electrical activity at the distal end of the axon initial segment (AIS) and subsequent spreading into the axon proper and backward through the proximal AIS toward the soma are confirmed. The corresponding extracellular waveforms across different neuronal compartments could be tracked.

Sodium and potassium conductances in principal neurons of the mouse piriform cortex: a quantitative description

KEY POINTS

The primary olfactory (or piriform) cortex is a promising model system for understanding how the cerebral cortex processes sensory information, although an investigation of the piriform cortex is hindered by a lack of detailed information about the intrinsic electrical properties of its component neurons. In the present study, we quantify the properties of voltage-dependent sodium currents and voltage- and calcium-dependent potassium currents in two important classes of excitatory neurons in the main input layer of the piriform cortex. We identify several classes of these currents and show that their properties are similar to those found in better-studied cortical regions. Our detailed quantitative descriptions of these currents will be valuable to computational neuroscientists who aim to build models that explain how the piriform cortex encodes odours.

ABSTRACT

The primary olfactory cortex (or piriform cortex, PC) is an anatomically simple palaeocortex that is increasingly used as a model system for investigating cortical sensory processing. However, little information is available on the intrinsic electrical conductances in neurons of the PC, hampering efforts to build realistic computational models of this cortex. In the present study, we used nucleated macropatches and whole-cell recordings to rigorously quantify the biophysical properties of voltage-gated sodium (Na_V ), voltage-gated potassium (K_V ) and calcium-activated potassium (K_Ca ) conductances in two major classes of glutamatergic neurons in layer 2 of the PC, semilunar (SL) cells and superficial pyramidal (SP) cells. We found that SL and SP cells both express a fast-inactivating Na_V current, two types of K_V current (A-type and delayed rectifier-type) and three types of K_Ca current (fast-, medium- and slow-afterhyperpolarization currents). The kinetic and voltage-dependent properties of the Na_V and K_V conductances were, with some exceptions, identical in SL and SP cells and similar to those found in neocortical pyramidal neurons. The K_Ca conductances were also similar across the different types of neurons. Our results are summarized in a series of empirical equations that should prove useful to computational neuroscientists seeking to model the PC. More broadly, our findings indicate that, at the level of single-cell electrical properties, this palaeocortex is not so different from the neocortex, vindicating efforts to use the PC as a model of cortical sensory processing in general.

A-type K+ channels impede supralinear summation of clustered glutamatergic inputs in layer 3 neocortical pyramidal neurons

A-type K⁺ channels restrain the spread of incoming signals in tufted and apical dendrites of pyramidal neurons resulting in strong compartmentalization. However, the exact subunit composition and functional significance of K⁺ channels expressed in small diameter proximal dendrites remain poorly understood. We focus on A-type K⁺ channels expressed in basal and oblique dendrites of cortical layer 3 pyramidal neurons, in ex vivo brain slices from young adult mice. Blocking putative Kv4 subunits with phrixotoxin-2 enhances depolarizing potentials elicited by uncaging RuBi-glutamate at single dendritic spines. A concentration of 4-aminopyridine reported to block Kv1 has no effect on such responses. 4-aminopyridine and phrixotoxin-2 increase supralinear summation of glutamatergic potentials evoked by synchronous activation of clustered spines. The effect of 4-aminopyridine on glutamate responses is simulated in a computational model where the dendritic A-type conductance is distributed homogeneously or in a linear density gradient. Thus, putative Kv4-containing channels depress excitatory inputs at single synapses. The additional recruitment of Kv1 subunits might require the synchronous activation of multiple inputs to regulate the gain of signal integration.

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We focus on A-type K+ channels expressed in oblique and basal dendrites.

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Putative Kv4 subunits depress excitatory signals generated by single spine excitation.

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Kv4 and Kv1 regulate supralinear signal integration at clustered dendritic spines.

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A computational model simulates Kv-mediated modulation of dendritic integration.

Voltage-Gated Sodium Channels in Neocortical Pyramidal Neurons Display Cole-Moore Activation Kinetics

Exploring the properties of action potentials is a crucial step toward a better understanding of the computational properties of single neurons and neural networks. The voltage-gated sodium channel is a key player in action potential generation. A comprehensive grasp of the gating mechanism of this channel can shed light on the biophysics of action potential generation. However, most models of voltage-gated sodium channels assume a concerted Hodgkin and Huxley kinetic gating scheme. However, it is not clear if Hodgkin and Huxley models are suitable for use in action potential simulations of central nervous system neurons. To resolve this, we investigated the activation kinetics of voltage-gated sodium channels. Here we performed high resolution voltage-clamp experiments from nucleated patches extracted from the soma of layer 5 (L5) cortical pyramidal neurons in rat brain slices. We show that the gating mechanism does not follow traditional Hodgkin and Huxley kinetics and that much of the channel voltage-dependence is probably due to rapid closed-closed transitions that lead to substantial onset latency reminiscent of the Cole-Moore effect observed in voltage-gated potassium conductances. Thus, the classical Hodgkin and Huxley description of sodium channel kinetics may be unsuitable for modeling the physiological role of this channel. Furthermore, our results reconcile between apparently contradicting studies sodium channel activation. Our findings may have key implications for the role of sodium channels in synaptic integration and action potential generation.

Potassium channels contribute to activity-dependent regulation of dendritic inhibition

GABAergic inhibition plays a critical role in the regulation of neuronal activity. In the neocortex, inhibitory interneurons that target the dendrites of pyramidal cells influence both electrical and biochemical postsynaptic signaling. Voltage-gated ion channels strongly shape dendritic excitability and the integration of excitatory inputs, but their contribution to GABAergic signaling is less well understood. By combining 2-photon calcium imaging and focal GABA uncaging, we show that voltage-gated potassium channels normally suppress the GABAergic inhibition of calcium signals evoked by back-propagating action potentials in dendritic spines and shafts of cortical pyramidal neurons. Moreover, the voltage-dependent inactivation of these channels leads to enhancement of dendritic calcium inhibition following somatic spiking. Computational modeling reveals that the enhancement of calcium inhibition involves an increase in action potential depolarization coupled with the nonlinear relationship between membrane voltage and calcium channel activation. Overall, our findings highlight the interaction between intrinsic and synaptic properties and reveal a novel mechanism for the activity-dependent regulation of GABAergic inhibition.

Functional roles of Kv1-mediated currents in genetically identified subtypes of pyramidal neurons in layer 5 of mouse somatosensory cortex

We used voltage-clamp recordings from somatic outside-out macropatches to determine the amplitude and biophysical properties of putative Kv1-mediated currents in layer 5 pyramidal neurons (PNs) from mice expressing EGFP under the control of promoters for etv1 or glt. We then used whole cell current-clamp recordings and Kv1-specific peptide blockers to test the hypothesis that Kv1 channels differentially regulate action potential (AP) voltage threshold, repolarization rate, and width as well as rheobase and repetitive firing in these two PN types. We found that Kv1-mediated currents make up a similar percentage of whole cell K⁺ current in both cell types, and only minor biophysical differences were observed between PN types or between currents sensitive to different Kv1 blockers. Putative Kv1 currents contributed to AP voltage threshold in both PN types, but AP width and rate of repolarization were only affected in etv1 PNs. Kv1 currents regulate rheobase, delay to the first AP, and firing rate similarly in both cell types, but the frequency-current slope was much more sensitive to Kv1 block in etv1 PNs. In both cell types, Kv1 block shifted the current required to elicit an onset doublet of action potentials to lower currents. Spike frequency adaptation was also affected differently by Kv1 block in the two PN types. Thus, despite similar expression levels and minimal differences in biophysical properties, Kv1 channels differentially regulate APs and repetitive firing in etv1 and glt PNs. This may reflect differences in subcellular localization of channel subtypes or differences in the other K⁺ channels expressed. NEW & NOTEWORTHY In two types of genetically identified layer 5 pyramidal neurons, α-dendrotoxin blocked approximately all of the putative Kv1 current (on average). We used outside-out macropatches and whole cell recordings at 33°C to show that despite similar expression levels and minimal differences in biophysical properties, Kv1 channels differentially regulate action potentials and repetitive firing in etv1 and glt pyramidal neurons. This may reflect differences in subcellular localization of channel subtypes or differences in the other K⁺ channels expressed.

Systematic generation of biophysically detailed models for diverse cortical neuron types

The cellular components of mammalian neocortical circuits are diverse, and capturing this diversity in computational models is challenging. Here we report an approach for generating biophysically detailed models of 170 individual neurons in the Allen Cell Types Database to link the systematic experimental characterization of cell types to the construction of cortical models. We build models from 3D morphologies and somatic electrophysiological responses measured in the same cells. Densities of active somatic conductances and additional parameters are optimized with a genetic algorithm to match electrophysiological features. We evaluate the models by applying additional stimuli and comparing model responses to experimental data. Applying this technique across a diverse set of neurons from adult mouse primary visual cortex, we verify that models preserve the distinctiveness of intrinsic properties between subsets of cells observed in experiments. The optimized models are accessible online alongside the experimental data. Code for optimization and simulation is also openly distributed.

A stepwise neuron model fitting procedure designed for recordings with high spatial resolution: Application to layer 5 pyramidal cells

BACKGROUND

Recent progress in electrophysiological and optical methods for neuronal recordings provides vast amounts of high-resolution data. In parallel, the development of computer technology has allowed simulation of ever-larger neuronal circuits. A challenge in taking advantage of these developments is the construction of single-cell and network models in a way that faithfully reproduces neuronal biophysics with subcellular level of details while keeping the simulation costs at an acceptable level.

NEW METHOD

In this work, we develop and apply an automated, stepwise method for fitting a neuron model to data with fine spatial resolution, such as that achievable with voltage sensitive dyes (VSDs) and Ca²⁺ imaging.

RESULT

We apply our method to simulated data from layer 5 pyramidal cells (L5PCs) and construct a model with reduced neuronal morphology. We connect the reduced-morphology neurons into a network and validate against simulated data from a high-resolution L5PC network model.

COMPARISON WITH EXISTING METHODS

Our approach combines features from several previously applied model-fitting strategies. The reduced-morphology neuron model obtained using our approach reliably reproduces the membrane-potential dynamics across the dendrites as predicted by the full-morphology model.

CONCLUSIONS

The network models produced using our method are cost-efficient and predict that interconnected L5PCs are able to amplify delta-range oscillatory inputs across a large range of network sizes and topologies, largely due to the medium after hyperpolarization mediated by the Ca²⁺-activated SK current.

The stochastic nature of action potential backpropagation in apical tuft dendrites

In cortical pyramidal neurons, backpropagating action potentials (bAPs) supply Ca²⁺ to synaptic contacts on dendrites. To determine whether the efficacy of AP backpropagation into apical tuft dendrites is stable over time, we performed dendritic Ca²⁺ and voltage imaging in rat brain slices. We found that the amplitude of bAP-Ca²⁺ in apical tuft branches was unstable, given that it varied from trial to trial (termed "bAP-Ca²⁺ flickering"). Small perturbations in dendritic physiology, such as spontaneous synaptic inputs, channel inactivation, or temperature-induced changes in channel kinetics, can cause bAP flickering. In the tuft branches, the density of Na⁺ and K⁺ channels was sufficient to support local initiation of fast spikelets by glutamate iontophoresis. We quantified the time delay between the somatic AP burst and the peak of dendritic Ca²⁺ transient in the apical tuft, because this delay is important for induction of spike-timing dependent plasticity. Depending on the frequency of the somatic AP triplets, Ca²⁺ signals peaked in the apical tuft 20-50 ms after the 1st AP in the soma. Interestingly, at low frequency (<20 Hz), the Ca²⁺ peaked sooner than at high frequency, because only the 1st AP invaded tuft. Activation of dendritic voltage-gated Ca²⁺ channels is sensitive to the duration of the dendritic voltage transient. In apical tuft branches, small changes in the duration of bAP voltage waveforms cause disproportionately large increases in dendritic Ca²⁺ influx (bAP-Ca²⁺ flickering). The stochastic nature of bAP-Ca²⁺ adds a new perspective on the mechanisms by which pyramidal neurons combine inputs arriving at different cortical layers.NEW & NOTEWORTHY The bAP-Ca²⁺ signal amplitudes in some apical tuft branches randomly vary from moment to moment. In repetitive measurements, successful AP invasions are followed by complete failures. Passive spread of voltage from the apical trunk into the tuft occasionally reaches the threshold for local Na⁺ spike, resulting in stronger Ca²⁺ influx. During a burst of three somatic APs, the peak of dendritic Ca²⁺ in the apical tuft occurs with a delay of 20-50 ms depending on AP frequency.

Is realistic neuronal modeling realistic?

Scientific models are abstractions that aim to explain natural phenomena. A successful model shows how a complex phenomenon arises from relatively simple principles while preserving major physical or biological rules and predicting novel experiments. A model should not be a facsimile of reality; it is an aid for understanding it. Contrary to this basic premise, with the 21st century has come a surge in computational efforts to model biological processes in great detail. Here we discuss the oxymoronic, realistic modeling of single neurons. This rapidly advancing field is driven by the discovery that some neurons don't merely sum their inputs and fire if the sum exceeds some threshold. Thus researchers have asked what are the computational abilities of single neurons and attempted to give answers using realistic models. We briefly review the state of the art of compartmental modeling highlighting recent progress and intrinsic flaws. We then attempt to address two fundamental questions. Practically, can we realistically model single neurons? Philosophically, should we realistically model single neurons? We use layer 5 neocortical pyramidal neurons as a test case to examine these issues. We subject three publically available models of layer 5 pyramidal neurons to three simple computational challenges. Based on their performance and a partial survey of published models, we conclude that current compartmental models are ad hoc, unrealistic models functioning poorly once they are stretched beyond the specific problems for which they were designed. We then attempt to plot possible paths for generating realistic single neuron models.

Roles of specific Kv channel types in repolarization of the action potential in genetically identified subclasses of pyramidal neurons in mouse neocortex

The action potential (AP) is a fundamental feature of excitable cells that serves as the basis for long-distance signaling in the nervous system. There is considerable diversity in the appearance of APs and the underlying repolarization mechanisms in different neuronal types (reviewed in Bean BP. Nat Rev Neurosci 8: 451-465, 2007), including among pyramidal cell subtypes. In the present work, we used specific pharmacological blockers to test for contributions of Kv1, Kv2, or Kv4 channels to repolarization of single APs in two genetically defined subpopulations of pyramidal cells in layer 5 of mouse somatosensory cortex (etv1 and glt) as well as pyramidal cells from layer 2/3. These three subtypes differ in AP properties (Groh A, Meyer HS, Schmidt EF, Heintz N, Sakmann B, Krieger P. Cereb Cortex 20: 826-836, 2010; Guan D, Armstrong WE, Foehring RC. J Neurophysiol 113: 2014-2032, 2015) as well as laminar position, morphology, and projection targets. We asked what the roles of Kv1, Kv2, and Kv4 channels are in AP repolarization and whether the underlying mechanisms are pyramidal cell subtype dependent. We found that Kv4 channels are critically involved in repolarizing neocortical pyramidal cells. There are also pyramidal cell subtype-specific differences in the role for Kv1 channels. Only Kv4 channels were involved in repolarizing the narrow APs of glt cells. In contrast, in etv1 cells and layer 2/3 cells, the broader APs are partially repolarized by Kv1 channels in addition to Kv4 channels. Consistent with their activation in the subthreshold range, Kv1 channels also regulate AP voltage threshold in all pyramidal cell subtypes.

The inhibitory effect of propofol on Kv2.1 potassium channel in rat parietal cortical neurons

Excessive K(+) efflux via activated voltage-gated K(+) channels can deplete intracellular K(+) and lead to long-lasting membrane depolarization which will promote neuronal apoptosis during ischemia/hypoxia injury. The Kv2.1 potassium channel was the major component of delayed rectifier potassium current (Ik) in pyramidal neurons in cortex and hippocampus. The neuronal protective effect of propofol has been proved. Delayed rectifier potassium current (Ik) has been shown to have close relationship with neuronal damage. The study was designed to test the inhibitory effect of propofol on Kv2.1 potassium channel in rat parietal cortical neurons. Whole-cell patch clamp recordings and Western blot analysis were used to investigate the electrophysiological function and protein expression of Kv2.1 in rat parietal cortical neurons after propofol treatment. We found that propofol concentration-dependently inhibited Ik in pyramidal neurons. Propofol also caused a downward shift of the I-V curve of Ik at 30μM concentration. Propofol significantly inhibited the expression of Kv2.1 protein level at 30μM, 50μM, 100μM concentration. In conclusion, our data showed that propofol could inhibit Ik, probably via depressing the expression of Kv2.1 protein in rat cerebral parietal cortical neurons.

Cell-Type Specific Channelopathies in the Prefrontal Cortex of the fmr1-/y Mouse Model of Fragile X Syndrome

Fragile X syndrome (FXS) is caused by transcriptional silencing of the fmr1 gene resulting in the loss of fragile X mental retardation protein (FMRP) expression. FXS patients display several behavioral phenotypes associated with prefrontal cortex (PFC) dysfunction. Voltage-gated ion channels, some of which are regulated by FMRP, heavily influence PFC neuron function. Although there is evidence for brain region-specific alterations to the function a single type of ion channel in FXS, it is unclear whether subtypes of principal neurons within a brain region are affected uniformly. We tested for alterations to ion channels critical in regulating neural excitability in two subtypes of prefrontal L5 pyramidal neurons. Using somatic and dendritic patch-clamp recordings, we provide evidence that the functional expression of h-channels (I_h) is down-regulated, whereas A-type K⁺ channel function is up-regulated in pyramidal tract-projecting (PT) neurons in the fmr1-/y mouse PFC. This is the opposite pattern of results from published findings from hippocampus where I_h is up-regulated and A-type K⁺ channel function is down-regulated. Additionally, we find that somatic Kv1-mediated current is down-regulated, resulting in increased excitability of fmr1-/y PT neurons. Importantly, these h- and K⁺ channel differences do not extend to neighboring intratelencephalic-projecting neurons. Thus, the absence of FMRP has divergent effects on the function of individual types of ion channels not only between brain regions, but also variable effects across cell types within the same brain region. Given the importance of ion channels in regulating neural circuits, these results suggest cell-type-specific phenotypes for the disease.

Anatomy and physiology of the thick-tufted layer 5 pyramidal neuron

The thick-tufted layer 5 (TTL5) pyramidal neuron is one of the most extensively studied neuron types in the mammalian neocortex and has become a benchmark for understanding information processing in excitatory neurons. By virtue of having the widest local axonal and dendritic arborization, the TTL5 neuron encompasses various local neocortical neurons and thereby defines the dimensions of neocortical microcircuitry. The TTL5 neuron integrates input across all neocortical layers and is the principal output pathway funneling information flow to subcortical structures. Several studies over the past decades have investigated the anatomy, physiology, synaptology, and pathophysiology of the TTL5 neuron. This review summarizes key discoveries and identifies potential avenues of research to facilitate an integrated and unifying understanding on the role of a central neuron in the neocortex.

Branch specific and spike-order specific action potential invasion in basal, oblique, and apical dendrites of cortical pyramidal neurons

In neocortical pyramidal neurons, action potentials (APs) propagate from the axon into the dendritic tree to influence distal synapses. Traditionally, AP backpropagation was studied in the thick apical trunk. Here, we used the principles of optical imaging developed by Cohen to investigate AP invasion into thin dendritic branches (basal, oblique, and tuft) of prefrontal cortical L5 pyramidal neurons. Multisite optical recordings from neighboring dendrites revealed a clear dichotomy between two seemingly equal dendritic branches belonging to the same cell ("sister branches"). We documented the variable efficacy of AP invasion in basal and oblique branches by revealing their AP voltage waveforms. Using fast multisite calcium imaging, we found that trains of APs are filtered differently between two apical tuft branches. Although one dendritic branch passes all spikes in an AP train, another branch belonging to the same neuron, same cortical layer, and same path distance from the cell body, experiences only one spike. Our data indicate that the vast differences in dendritic voltage and calcium transients, detected in dendrites of pyramidal neurons, arise from a nonuniform distribution of A-type [Formula: see text] conductance, an aggregate number of branch points in the path of the AP propagation and minute differences in dendritic diameter.

Subcellular localization of K+ channels in mammalian brain neurons: remarkable precision in the midst of extraordinary complexity

Potassium channels (KChs) are the most diverse ion channels, in part due to extensive combinatorial assembly of a large number of principal and auxiliary subunits into an assortment of KCh complexes. Their structural and functional diversity allows KChs to play diverse roles in neuronal function. Localization of KChs within specialized neuronal compartments defines their physiological role and also fundamentally impacts their activity, due to localized exposure to diverse cellular determinants of channel function. Recent studies in mammalian brain reveal an exquisite refinement of KCh subcellular localization. This includes axonal KChs at the initial segment, and near/within nodes of Ranvier and presynaptic terminals, dendritic KChs found at sites reflecting specific synaptic input, and KChs defining novel neuronal compartments. Painting the remarkable diversity of KChs onto the complex architecture of mammalian neurons creates an elegant picture of electrical signal processing underlying the sophisticated function of individual neuronal compartments, and ultimately neurotransmission and behavior.

Differential modulation of repetitive firing and synchronous network activity in neocortical interneurons by inhibition of A-type K(+) channels and Ih

GABAergic interneurons provide the main source of inhibition in the neocortex and are important in regulating neocortical network activity. In the presence 4-aminopyridine (4-AP), CNQX, and D-APV, large amplitude GABAA-receptor mediated depolarizing responses were observed in the neocortex. GABAergic networks are comprised of several types of interneurons, each with its own protein expression pattern, firing properties, and inhibitory role in network activity. Voltage-gated ion channels, especially A-type K(+) channels, differentially regulate passive membrane properties, action potential (AP) waveform, and repetitive firing properties in interneurons depending on their composition and localization. HCN channels are known modulators of pyramidal cell intrinsic excitability and excitatory network activity. Little information is available regarding how HCN channels functionally modulate excitability of individual interneurons and inhibitory networks. In this study, we examined the effect of 4-AP on intrinsic excitability of fast-spiking basket cells (FS-BCs) and Martinotti cells (MCs). 4-AP increased the duration of APs in both FS-BCs and MCs. The repetitive firing properties of MCs were differentially affected compared to FS-BCs. We also examined the effect of Ih inhibition on synchronous GABAergic depolarizations and synaptic integration of depolarizing IPSPs. ZD 7288 enhanced the amplitude and area of evoked GABAergic responses in both cell types. Similarly, the frequency and area of spontaneous GABAergic depolarizations in both FS-BCs and MCs were increased in presence of ZD 7288. Synaptic integration of IPSPs in MCs was significantly enhanced, but remained unaltered in FS-BCs. These results indicate that 4-AP differentially alters the firing properties of interneurons, suggesting MCs and FS-BCs may have unique roles in GABAergic network synchronization. Enhancement of GABAergic network synchronization by ZD 7288 suggests that HCN channels attenuate inhibitory network activity.

Dissecting mechanisms of brain aging by studying the intrinsic excitability of neurons

Several studies using vertebrate and invertebrate animal models have shown aging associated changes in brain function. Importantly, changes in soma size, loss or regression of dendrites and dendritic spines and alterations in the expression of neurotransmitter receptors in specific neurons were described. Despite this understanding, how aging impacts intrinsic properties of individual neurons or circuits that govern a defined behavior is yet to be determined. Here we discuss current understanding of specific electrophysiological changes in individual neurons and circuits during aging.

Density of voltage-gated potassium channels is a bifurcation parameter in pyramidal neurons

Several types of intrinsic dynamics have been identified in brain neurons. Type 1 excitability is characterized by a continuous frequency-stimulus relationship and, thus, an arbitrarily low frequency at threshold current. Conversely, Type 2 excitability is characterized by a discontinuous frequency-stimulus relationship and a nonzero threshold frequency. In previous theoretical work we showed that the density of Kv channels is a bifurcation parameter, such that increasing the Kv channel density in a neuron model transforms Type 1 excitability into Type 2 excitability. Here we test this finding experimentally, using the dynamic clamp technique on Type 1 pyramidal cells in rat cortex. We found that increasing the density of slow Kv channels leads to a shift from Type 1 to Type 2 threshold dynamics, i.e., a distinct onset frequency, subthreshold oscillations, and reduced latency to first spike. In addition, the action potential was resculptured, with a narrower spike width and more pronounced afterhyperpolarization. All changes could be captured with a two-dimensional model. It may seem paradoxical that an increase in slow K channel density can lead to a higher threshold firing frequency; however, this can be explained in terms of bifurcation theory. In contrast to previous work, we argue that an increased outward current leads to a change in dynamics in these neurons without a rectification of the current-voltage curve. These results demonstrate that the behavior of neurons is determined by the global interactions of their dynamical elements and not necessarily simply by individual types of ion channels.

A simulation study on the effects of dendritic morphology on layer V prefrontal pyramidal cell firing behavior

Pyramidal cells, the most abundant neurons in neocortex, exhibit significant structural variability across different brain areas and layers in different species. Moreover, in response to a somatic step current, these cells display a range of firing behaviors, the most common being (1) repetitive action potentials (Regular Spiking-RS), and (2) an initial cluster of 2-5 action potentials with short interspike interval (ISIs) followed by single spikes (Intrinsic Bursting-IB). A correlation between firing behavior and dendritic morphology has recently been reported. In this work we use computational modeling to investigate quantitatively the effects of the basal dendritic tree morphology on the firing behavior of 112 three-dimensional reconstructions of layer V PFC rat pyramidal cells. Particularly, we focus on how different morphological (diameter, total length, volume, and branch number) and passive [Mean Electrotonic Path length (MEP)] features of basal dendritic trees shape somatic firing when the spatial distribution of ionic mechanisms in the basal dendritic trees is uniform or non-uniform. Our results suggest that total length, volume and branch number are the best morphological parameters to discriminate the cells as RS or IB, regardless of the distribution of ionic mechanisms in basal trees. The discriminatory power of total length, volume, and branch number remains high in the presence of different apical dendrites. These results suggest that morphological variations in the basal dendritic trees of layer V pyramidal neurons in the PFC influence their firing patterns in a predictive manner and may in turn influence the information processing capabilities of these neurons.

Modulatory mechanisms and multiple functions of somatodendritic A-type K (+) channel auxiliary subunits

Auxiliary subunits are non-conducting, modulatory components of the multi-protein ion channel complexes that underlie normal neuronal signaling. They interact with the pore-forming α-subunits to modulate surface distribution, ion conductance, and channel gating properties. For the somatodendritic subthreshold A-type potassium (ISA) channel based on Kv4 α-subunits, two types of auxiliary subunits have been extensively studied: Kv channel-interacting proteins (KChIPs) and dipeptidyl peptidase-like proteins (DPLPs). KChIPs are cytoplasmic calcium-binding proteins that interact with intracellular portions of the Kv4 subunits, whereas DPLPs are type II transmembrane proteins that associate with the Kv4 channel core. Both KChIPs and DPLPs genes contain multiple start sites that are used by various neuronal populations to drive the differential expression of functionally distinct N-terminal variants. In turn, these N-terminal variants generate tremendous functional diversity across the nervous system. Here, we focus our review on (1) the molecular mechanism underlying the unique properties of different N-terminal variants, (2) the shaping of native ISA properties by the concerted actions of KChIPs and DPLP variants, and (3) the surprising ways that KChIPs and DPLPs coordinate the activity of multiple channels to fine-tune neuronal excitability. Unlocking the unique contributions of different auxiliary subunit N-terminal variants may provide an important opportunity to develop novel targeted therapeutics to treat numerous neurological disorders.

Deletion of the Kv2.1 delayed rectifier potassium channel leads to neuronal and behavioral hyperexcitability

The Kv2.1 delayed rectifier potassium channel exhibits high-level expression in both principal and inhibitory neurons throughout the central nervous system, including prominent expression in hippocampal neurons. Studies of in vitro preparations suggest that Kv2.1 is a key yet conditional regulator of intrinsic neuronal excitability, mediated by changes in Kv2.1 expression, localization and function via activity-dependent regulation of Kv2.1 phosphorylation. Here we identify neurological and behavioral deficits in mutant (Kv2.1(-/-) ) mice lacking this channel. Kv2.1(-/-) mice have grossly normal characteristics. No impairment in vision or motor coordination was apparent, although Kv2.1(-/-) mice exhibit reduced body weight. The anatomic structure and expression of related Kv channels in the brains of Kv2.1(-/-) mice appear unchanged. Delayed rectifier potassium current is diminished in hippocampal neurons cultured from Kv2.1(-/-) animals. Field recordings from hippocampal slices of Kv2.1(-/-) mice reveal hyperexcitability in response to the convulsant bicuculline, and epileptiform activity in response to stimulation. In Kv2.1(-/-) mice, long-term potentiation at the Schaffer collateral - CA1 synapse is decreased. Kv2.1(-/-) mice are strikingly hyperactive, and exhibit defects in spatial learning, failing to improve performance in a Morris Water Maze task. Kv2.1(-/-) mice are hypersensitive to the effects of the convulsants flurothyl and pilocarpine, consistent with a role for Kv2.1 as a conditional suppressor of neuronal activity. Although not prone to spontaneous seizures, Kv2.1(-/-) mice exhibit accelerated seizure progression. Together, these findings suggest homeostatic suppression of elevated neuronal activity by Kv2.1 plays a central role in regulating neuronal network function.

A quantitative description of dendritic conductances and its application to dendritic excitation in layer 5 pyramidal neurons

Postsynaptic integration is a complex function of passive membrane properties and nonlinear activation of voltage-gated channels. Some cortical neurons express many voltage-gated channels, with each displaying heterogeneous dendritic conductance gradients. This complexity has hindered the construction of experimentally based mechanistic models of cortical neurons. Here we show that it is possible to overcome this obstacle. We recorded the membrane potential from the soma and apical dendrite of layer 5 (L5) pyramidal neurons of the rat somatosensory cortex. A combined experimental and numerical parameter peeling procedure was implemented to optimize a detailed ionic mechanism for the generation and propagation of dendritic spikes in neocortical L5 pyramidal neurons. In the optimized model, the density of voltage-gated Ca(2+) channels decreased linearly from the soma, and leveled at the distal apical dendrite. The density of the small-conductance Ca(2+)-activated channel decreased along the apical dendrite, whereas the density of the large-conductance Ca(2+)-gated K(+) channel was uniform throughout the apical dendrite. The model predicted an ionic mechanism for the generation of a dendritic spike, the interaction of this spike with the backpropagating action potential, the mechanism responsible for the ability of the proximal apical dendrite to control the coupling between the axon and the dendrite, and the generation of NMDA spikes in the distal apical tuft. Moreover, in addition to faithfully predicting many experimental results recorded from the apical dendrite of L5 pyramidal neurons, the model validates a new methodology for mechanistic modeling of neurons in the CNS.

Voltage-gated potassium channels at the crossroads of neuronal function, ischemic tolerance, and neurodegeneration

Voltage-gated potassium (Kv) channels are widely expressed in the central and peripheral nervous system and are crucial mediators of neuronal excitability. Importantly, these channels also actively participate in cellular and molecular signaling pathways that regulate the life and death of neurons. Injury-mediated increased K(+) efflux through Kv2.1 channels promotes neuronal apoptosis, contributing to widespread neuronal loss in neurodegenerative disorders such as Alzheimer's disease and stroke. In contrast, some forms of neuronal activity can dramatically alter Kv2.1 channel phosphorylation levels and influence their localization. These changes are normally accompanied by modifications in channel voltage dependence, which may be neuroprotective within the context of ischemic injury. Kv1 and Kv7 channel dysfunction leads to neuronal hyperexcitability that critically contributes to the pathophysiology of human clinical disorders such as episodic ataxia and epilepsy. This review summarizes the neurotoxic, neuroprotective, and neuroregulatory roles of Kv channels and highlights the consequences of Kv channel dysfunction on neuronal physiology. The studies described in this review thus underscore the importance of normal Kv channel function in neurons and emphasize the therapeutic potential of targeting Kv channels in the treatment of a wide range of neurological diseases.

Layer-specific modulation of neuronal excitability by 660-nm laser irradiation in mouse neocortex

It has been reported that laser light irradiation (LLI) could regulate neuronal activities in the forebrain, but little is known if and how LLI in the red wavelength range affects neuronal excitability. Here, we investigated the effects of a continuous diode laser at 660 nm on intrinsic membrane properties and excitability of presumed pyramidal neurons in the thalamocortical input layer (layer 3/4) and in layer 5 of mouse primary auditory cortex using the whole-cell patch-clamp recording technique. In layer 3/4 neurons, 660-nm laser irradiation (LLI-660) at 20 mW for 5 min gradually increased resting membrane potentials, which reached a plateau after irradiation. Concomitantly, LLI-660 decreased onset latency of first action potentials (spikes) without changing spike threshold or peak amplitude, but increased inter-spike interval of initial bursting spike doublets and their peak amplitude ratio. None of these changes was observed in layer 5 neurons. Instead, LLI-660 at 20 mW rapidly reduced spike width ~5 % within 1 min of irradiation onset. The magnitude of this reduction did not change during 5 or 10 min irradiation, and returned quickly to at least baseline levels after turning the LLI off. Decreasing laser power to 10 mW reduced spike width to a lesser extent, suggesting laser power dependence of this phenomenon. These data suggest that LLI-660 regulates different aspects of neuronal excitability in cortical neurons in a layer-dependent manner possibly by affecting different voltage-gated ion channels.

The cognitive significance of resonating neurons in the cerebral cortex

Most neural fibers of the cerebral cortex engage in electric signaling, but one particular fiber, the apical dendrite of the pyramidal neuron, specializes in electric resonating. This dendrite extends upward from somas of pyramidal neurons, the most numerous neurons of the cortex. The apical dendrite is embedded in a recurrent corticothalamic circuit that induces surges of electric current to move repeatedly down the dendrite. Narrow bandwidths of surge frequency (resonating) enable cortical circuits to use specific carrier frequencies, which isolate the processing of those circuits from other circuits. Resonating greatly enhances the intensity and duration of electrical activity of a neuron over a narrow frequency range, which underlies attention in its various modes. Within the minicolumn, separation of the central resonating circuit from the surrounding signal processing network separates "having" subjective impressions from "thinking about" them. Resonating neurons in the insular cortex apparently underlie cognitive impressions of feelings.

Potassium channels control the interaction between active dendritic integration compartments in layer 5 cortical pyramidal neurons

Active dendritic synaptic integration enhances the computational power of neurons. Such nonlinear processing generates an object-localization signal in the apical dendritic tuft of layer 5B cortical pyramidal neurons during sensory-motor behavior. Here, we employ electrophysiological and optical approaches in brain slices and behaving animals to investigate how excitatory synaptic input to this distal dendritic compartment influences neuronal output. We find that active dendritic integration throughout the apical dendritic tuft is highly compartmentalized by voltage-gated potassium (KV) channels. A high density of both transient and sustained KV channels was observed in all apical dendritic compartments. These channels potently regulated the interaction between apical dendritic tuft, trunk, and axosomatic integration zones to control neuronal output in vitro as well as the engagement of dendritic nonlinear processing in vivo during sensory-motor behavior. Thus, KV channels dynamically tune the interaction between active dendritic integration compartments in layer 5B pyramidal neurons to shape behaviorally relevant neuronal computations.