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.

A calcium-based plasticity model for predicting long-term potentiation and depression in the neocortex.

Pyramidal cells (PCs) form the backbone of the layered structure of the neocortex, and plasticity of their synapses is thought to underlie learning in the brain. However, such long-term synaptic changes have been experimentally characterized between only a few types of PCs, posing a significant barrier for studying neocortical learning mechanisms. Here we introduce a model of synaptic plasticity based on data-constrained postsynaptic calcium dynamics, and show in a neocortical microcircuit model that a single parameter set is sufficient to unify the available experimental findings on long-term potentiation (LTP) and long-term depression (LTD) of PC connections.

HippoUnit: A software tool for the automated testing and systematic comparison of detailed models of hippocampal neurons based on electrophysiological data.

Anatomically and biophysically detailed data-driven neuronal models have become widely used tools for understanding and predicting the behavior and function of neurons. Due to the increasing availability of experimental data from anatomical and electrophysiological measurements as well as the growing number of computational and software tools that enable accurate neuronal modeling, there are now a large number of different models of many cell types available in the literature. These models were usually built to capture a few important or interesting properties of the given neuron type, and it is often unknown how they would behave outside their original context.

GABA-mediated tonic inhibition differentially modulates gain in functional subtypes of cortical interneurons.

The binding of GABA (γ-aminobutyric acid) to extrasynaptic GABA receptors generates tonic inhibition that acts as a powerful modulator of cortical network activity. Despite GABA being present throughout the extracellular space of the brain, previous work has shown that GABA may differentially modulate the excitability of neuron subtypes according to variation in chloride gradient. Here, using biophysically detailed neuron models, we predict that tonic inhibition can differentially modulate the excitability of neuron subtypes according to variation in electrophysiological properties.

Experimentally-constrained biophysical models of tonic and burst firing modes in thalamocortical neurons.

Somatosensory thalamocortical (TC) neurons from the ventrobasal (VB) thalamus are central components in the flow of sensory information between the periphery and the cerebral cortex, and participate in the dynamic regulation of thalamocortical states including wakefulness and sleep. This property is reflected at the cellular level by the ability to generate action potentials in two distinct firing modes, called tonic firing and low-threshold bursting. Although the general properties of TC neurons are known, we still lack a detailed characterization of their morphological and electrical properties in the VB thalamus.

The physiological variability of channel density in hippocampal CA1 pyramidal cells and interneurons explored using a unified data-driven modeling workflow.

Every neuron is part of a network, exerting its function by transforming multiple spatiotemporal synaptic input patterns into a single spiking output. This function is specified by the particular shape and passive electrical properties of the neuronal membrane, and the composition and spatial distribution of ion channels across its processes. For a variety of physiological or pathological reasons, the intrinsic input/output function may change during a neuron's lifetime.

BluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience.

At many scales in neuroscience, appropriate mathematical models take the form of complex dynamical systems. Parameterizing such models to conform to the multitude of available experimental constraints is a global non-linear optimisation problem with a complex fitness landscape, requiring numerical techniques to find suitable approximate solutions. Stochastic optimisation approaches, such as evolutionary algorithms, have been shown to be effective, but often the setting up of such optimisations and the choice of a specific search algorithm and its parameters is non-trivial, requiring domain-specific expertise.

At the Edge of Chaos: How Cerebellar Granular Layer Network Dynamics Can Provide the Basis for Temporal Filters.

Models of the cerebellar microcircuit often assume that input signals from the mossy-fibers are expanded and recoded to provide a foundation from which the Purkinje cells can synthesize output filters to implement specific input-signal transformations. Details of this process are however unclear. While previous work has shown that recurrent granule cell inhibition could in principle generate a wide variety of random outputs suitable for coding signal onsets, the more general application for temporally varying signals has yet to be demonstrated.

Reconstruction and Simulation of Neocortical Microcircuitry.

Unlabelled: We present a first-draft digital reconstruction of the microcircuitry of somatosensory cortex of juvenile rat. The reconstruction uses cellular and synaptic organizing principles to algorithmically reconstruct detailed anatomy and physiology from sparse experimental data. An objective anatomical method defines a neocortical volume of 0.

Model cerebellar granule cells can faithfully transmit modulated firing rate signals.

A crucial assumption of many high-level system models of the cerebellum is that information in the granular layer is encoded in a linear manner. However, granule cells are known for their non-linear and resonant synaptic and intrinsic properties that could potentially impede linear signal transmission. In this modeling study we analyse how electrophysiological granule cell properties and spike sampling influence information coded by firing rate modulation, assuming no signal-related, i.

The role of regularity and synchrony of cerebellar Purkinje cells for pathological nystagmus.

Previous theories assumed that the beneficial effect of the potassium channel blocker 4-aminopyridine (4-AP) for patients suffering from downbeat nystagmus (DBN) or episodic ataxia type 2 (EA2) is due to an increase of excitability of cerebellar Purkinje cells (PC). Recent experimental results using therapeutic doses of 4-AP with a mouse model of EA2 challenged the theory showing that 4-AP does not change the firing rate of PC but their regularity. Based on a mathematical model of the ocular motor and cerebellar circuitry, we show that changes in regularity have no effect without synchrony in PC firing.

Cellular and network contributions to vestibular signal processing: impact of ion conductances, synaptic inhibition, and noise.

Head motion-related sensory signals are transformed by second-order vestibular neurons (2°VNs) into appropriate commands for retinal image stabilization during body motion. In frogs, these 2°VNs form two distinct subpopulations that have either tonic or highly phasic intrinsic properties, essentially compatible with low-pass and bandpass filter characteristics, respectively. In the present study, physiological data on cellular properties of 2°VNs of the grass frog (Rana temporaria) have been used to construct conductance-based spiking cellular models that were fine-tuned by fitting to recorded spike-frequency data.

Functional organization of vestibular commissural connections in frog.

Central vestibular neurons receive substantial inputs from the contralateral labyrinth through inhibitory and excitatory brainstem commissural pathways. The functional organization of these pathways was studied by a multi-methodological approach in isolated frog whole brains. Retrogradely labeled vestibular commissural neurons were primarily located in the superior vestibular nucleus in rhombomeres 2/3 and the medial and descending vestibular nucleus in rhombomeres 5-7.

Modeling of intrinsic and synaptic properties to reveal the cellular and network contribution for vestibular signal processing.

Computational modeling of cellular and network properties of central vestibular neurons is necessary for understanding the mechanisms of sensory-motor transformation for gaze stabilization. As a first step to mathematically describe vestibular signal processing, the available physiological data of the synaptic and intrinsic properties of frog second-order vestibular neurons (2 degrees VN) were used to create a model that combines cellular and network parameters. With this approach it is now possible to reveal the particular contributions of intrinsic membrane versus emerging network properties in shaping labyrinthine afferent-evoked synaptic responses in 2 degrees VN, to simulate perturbations, and to generate hypotheses that are testable in empiric experiments.

Frequency-Domain Analysis of Intrinsic Neuronal Properties using High-Resistant Electrodes.

Intrinsic cellular properties of neurons in culture or slices are usually studied by the whole cell clamp method using low-resistant patch pipettes. These electrodes allow detailed analyses with standard electrophysiological methods such as current- or voltage-clamp. However, in these preparations large parts of the network and dendritic structures may be removed, thus preventing an adequate study of synaptic signal processing.

Differential dynamic processing of afferent signals in frog tonic and phasic second-order vestibular neurons.

The sensory-motor transformation of the large dynamic spectrum of head-motion-related signals occurs in separate vestibulo-ocular pathways. Synaptic responses of tonic and phasic second-order vestibular neurons were recorded in isolated frog brains after stimulation of individual labyrinthine nerve branches with trains of single electrical pulses. The timing of the single pulses was adapted from spike discharge patterns of frog semicircular canal nerve afferents during sinusoidal head rotation.

Modelling drug modulation of nystagmus.

A better understanding of the neural and functional mechanisms underlying drug-induced changes in pathological nystagmus is likely to improve medical treatment. A treatment option for downbeat nystagmus (DBN), a common form of acquired fixation nystagmus that often occurs with cerebellar degeneration, is low doses of the potassium channel blocker 4-aminopyridine (4-AP). The upward ocular drift in DBN has a spontaneous and a vertical gaze-evoked component.