Circuits that contain the Current : I A, slow

(Slowly inactivating "delay" current I K(D))
Re-display model names without descriptions
    Models   Description
1. A multilayer cortical model to study seizure propagation across microdomains (Basu et al. 2015)
A realistic neural network was used to simulate a region of neocortex to obtain extracellular LFPs from ‘virtual micro-electrodes’ and produce test data for comparison with multisite microelectrode recordings. A model was implemented in the GENESIS neurosimulator. A simulated region of cortex was represented by layers 2/3, 5/6 (interneurons and pyramidal cells) and layer 4 stelate cells, spaced at 25 µm in each horizontal direction. Pyramidal cells received AMPA and NMDA inputs from neighboring cells at the basal and apical dendrites. The LFP data was generated by simulating 16-site electrode array with the help of ‘efield’ objects arranged at the predetermined positions with respect to the surface of the simulated network. The LFP for the model is derived from a weighted average of the current sources summed over all cellular compartments. Cell models were taken from from Traub et al. (2005) J Neurophysiol 93(4):2194-232.
2. A network model of tail withdrawal in Aplysia (White et al 1993)
The contributions of monosynaptic and polysynaptic circuitry to the tail-withdrawal reflex in the marine mollusk Aplysia californica were assessed by the use of physiologically based neural network models. Effects of monosynaptic circuitry were examined by the use of a two-layer network model with four sensory neurons in the input layer and one motor neuron in the output layer. Results of these simulations indicated that the monosynaptic circuit could not account fully for long-duration responses of tail motor neurons elicited by tail stimulation. A three-layer network model was constructed by interposing a layer of two excitatory interneurons between the input and output layers of the two-layer network model. The three-layer model could account for long-duration responses in motor neurons. Sensory neurons are a known site of plasticity in Aplysia. Synaptic plasticity at more than one locus modified dramatically the input-output relationship of the three-layer network model. This feature gave the model redundancy in its plastic properties and points to the possibility of distributed memory in the circuitry mediating withdrawal reflexes in Aplysia. Please see paper for more results and details.
3. A single column thalamocortical network model (Traub et al 2005)
To better understand population phenomena in thalamocortical neuronal ensembles, we have constructed a preliminary network model with 3,560 multicompartment neurons (containing soma, branching dendrites, and a portion of axon). Types of neurons included superficial pyramids (with regular spiking [RS] and fast rhythmic bursting [FRB] firing behaviors); RS spiny stellates; fast spiking (FS) interneurons, with basket-type and axoaxonic types of connectivity, and located in superficial and deep cortical layers; low threshold spiking (LTS) interneurons, that contacted principal cell dendrites; deep pyramids, that could have RS or intrinsic bursting (IB) firing behaviors, and endowed either with non-tufted apical dendrites or with long tufted apical dendrites; thalamocortical relay (TCR) cells; and nucleus reticularis (nRT) cells. To the extent possible, both electrophysiology and synaptic connectivity were based on published data, although many arbitrary choices were necessary.
4. Alpha rhythm in vitro visual cortex (Traub et al 2020)
The paper describes an experimental model of the alpha rhythm generated by layer 4 pyramidal neurons in a visual cortex slice. The simulation model is derived from that of Traub et al. (2005) J Neurophysiol, developed for thalamocortical oscillations.
5. Burst induced synaptic plasticity in Apysia sensorimotor neurons (Phares et al 2003)
The Aplysia sensorimotor synapse is a key site of plasticity for several simple forms of learning. Intracellular stimulation of sensory neurons to fire a burst of action potentials at 10 Hz for 1 sec led to significant homosynaptic depression of postsynaptic responses. During the burst, the steady-state depressed phase of the postsynaptic response, which was only 20% of the initial EPSP of the burst, still contributed to firing the motor neuron. To explore the functional contribution of transient homosynaptic depression to the response of the motor neuron, computer simulations of the sensorimotor synapse with and without depression were compared. Depression allowed the motor neuron to produce graded responses over a wide range of presynaptic input strength. Thus, synaptic depression increased the dynamic range of the sensorimotor synapse and can, in principle, have a profound effect on information processing. Please see paper for results and details.
6. Collection of simulated data from a thalamocortical network model (Glabska, Chintaluri, Wojcik 2017)
"A major challenge in experimental data analysis is the validation of analytical methods in a fully controlled scenario where the justification of the interpretation can be made directly and not just by plausibility. ... One solution is to use simulations of realistic models to generate ground truth data. In neuroscience, creating such data requires plausible models of neural activity, access to high performance computers, expertise and time to prepare and run the simulations, and to process the output. To facilitate such validation tests of analytical methods we provide rich data sets including intracellular voltage traces, transmembrane currents, morphologies, and spike times. ... The data were generated using the largest publicly available multicompartmental model of thalamocortical network (Traub et al. 2005), with activity evoked by different thalamic stimuli."
7. Dynamic cortical interlaminar interactions (Carracedo et al. 2013)
"... Here we demonstrate the mechanism underlying a purely neocortical delta rhythm generator and show a remarkable laminar, cell subtype and local subcircuit delineation between delta and nested theta rhythms. We show that spike timing during delta-nested theta rhythms controls an iterative, reciprocal interaction between deep and superficial cortical layers resembling the unsupervised learning processes proposed for laminar neural networks by Hinton and colleagues ... and mimicking the alternating cortical dynamics of sensory and memory processing during wakefulness."
8. Electrodecrements in in vitro model of infantile spasms (Traub et al 2020)
The code is an extension of the thalamocortical model of Traub et al. (2005) J Neurophysiol. It is here applied to an in vitro model of the electrodecremental response seen in the EEG of children with infantile spasms (West syndrome)
9. Microcircuits of L5 thick tufted pyramidal cells (Hay & Segev 2015)
"... We simulated detailed conductance-based models of TTCs (Layer 5 thick tufted pyramidal cells) forming recurrent microcircuits that were interconnected as found experimentally; the network was embedded in a realistic background synaptic activity. ... Our findings indicate that dendritic nonlinearities are pivotal in controlling the gain and the computational functions of TTCs microcircuits, which serve as a dominant output source for the neocortex. "
10. Multiscale model of excitotoxicity in PD (Muddapu and Chakravarthy 2020)
Parkinson's disease (PD) is a neurodegenerative disorder caused by loss of dopaminergic neurons in Substantia Nigra pars compacta (SNc). Although the exact cause of cell death is not clear, the hypothesis that metabolic deficiency is a key factor has been gaining attention in recent years. In the present study, we investigate this hypothesis using a multi-scale computational model of the subsystem of the basal ganglia comprising Subthalamic Nucleus (STN), Globus Pallidus externa (GPe) and SNc. The proposed model is a multiscale model in that interactions among the three nuclei are simulated using more abstract Izhikevich neuron models, while the molecular pathways involved in cell death of SNc neurons are simulated in terms of detailed chemical kinetics. Simulation results obtained from the proposed model showed that energy deficiencies occurring at cellular and network levels could precipitate the excitotoxic loss of SNc neurons in PD. At the subcellular level, the models show how calcium elevation leads to apoptosis of SNc neurons. The therapeutic effects of several neuroprotective interventions are also simulated in the model. From neuroprotective studies, it was clear that glutamate inhibition and apoptotic signal blocker therapies were able to halt the progression of SNc cell loss when compared to other therapeutic interventions, which only slows down the progression of SNc cell loss.
11. Single compartment Dorsal Lateral Medium Spiny Neuron w/ NMDA and AMPA (Biddell and Johnson 2013)
A biophysical single compartment model of the dorsal lateral striatum medium spiny neuron is presented here. The model is an implementation then adaptation of a previously described model (Mahon et al. 2002). The model has been adapted to include NMDA and AMPA receptor models that have been fit to dorsal lateral striatal neurons. The receptor models allow for excitation by other neuron models.
12. The microcircuits of striatum in silico (Hjorth et al 2020)
"Our aim is to reconstruct a full-scale mouse striatal cellular level model to provide a framework to integrate and interpret striatal data. We represent the main striatal neuronal subtypes, the two types of projection neurons (dSPNs and iSPNs) giving rise to the direct and indirect pathways, the fast-spiking interneurons, the low threshold spiking interneurons, and the cholinergic interneurons as detailed compartmental models, with properties close to their biological counterparts. Both intrastriatal and afferent synaptic inputs (cortex, thalamus, dopamine system) are optimized against existing data, including short-term plasticity. This model platform will be used to generate new hypotheses on striatal function or network dynamic phenomena."
13. The origin of different spike and wave-like events (Hall et al 2017)
Acute In vitro models have revealed a great deal of information about mechanisms underlying many types of epileptiform activity. However, few examples exist that shed light on spike and wave (SpW) patterns of pathological activity. SpW are seen in many epilepsy syndromes, both generalised and focal, and manifest across the entire age spectrum. They are heterogeneous in terms of their severity, symptom burden and apparent anatomical origin (thalamic, neocortical or both), but any relationship between this heterogeneity and underlying pathology remains elusive. Here we demonstrate that physiological delta frequency rhythms act as an effective substrate to permit modelling of SpW of cortical origin and may help to address this issue. ..."
14. Unbalanced peptidergic inhibition in superficial cortex underlies seizure activity (Hall et al 2015)
" ...Loss of tonic neuromodulatory excitation, mediated by nicotinic acetylcholine or serotonin (5HT3A) receptors, of 5HT3-immunopositive interneurons caused an increase in amplitude and slowing of the delta rhythm until each period became the "wave" component of the spike and wave discharge. As with the normal delta rhythm, the wave of a spike and wave discharge originated in cortical layer 5. In contrast, the "spike" component of the spike and wave discharge originated from a relative failure of fast inhibition in layers 2/3-switching pyramidal cell action potential outputs from single, sparse spiking during delta rhythms to brief, intense burst spiking, phase-locked to the field spike. The mechanisms underlying this loss of superficial layer fast inhibition, and a concomitant increase in slow inhibition, appeared to be precipitated by a loss of neuropeptide Y (NPY)-mediated local circuit inhibition and a subsequent increase in vasoactive intestinal peptide (VIP)-mediated disinhibition. Blockade of NPY Y1 receptors was sufficient to generate spike and wave discharges, whereas blockade of VIP receptors almost completely abolished this form of epileptiform activity. These data suggest that aberrant, activity-dependent neuropeptide corelease can have catastrophic effects on neocortical dynamics."

Re-display model names without descriptions