Models that contain the Modeling Application : C or C++ program (web link to model) (Home Page)

(The model is written in the C or C++ language.)
Re-display model names without descriptions
    Models   Description
1.  A dynamic model of the canine ventricular myocyte (Hund, Rudy 2004)
The Hund-Rudy dynamic (HRd) model is based on data from the canine epicardial ventricular myocyte. Rate-dependent phenomena associated with ion channel kinetics, action potential properties and Ca2+ handling are simulated by the model. See paper for more and details.
2.  A Model of Selection between Stimulus and Place Strategy in a Hawkmoth (Balkenius et al. 2004)
"In behavioral experiments, the hawkmoth Deilephila elpenor can learn both the color and the position of artificial flowers. ... We show how a computational model can reproduce the behavior in the experimental situation. The aim of the model is to investigate which learning and behavior selection strategies are necessary to reproduce the behavior observed in the experiment. The model is based on behavioral data and the sensitivities of the moth photoreceptors. The model consists of a number of interacting behavior systems that are triggered by specific stimuli and control specific behaviors. The ability of the moth to learn the colors of different flowers and the adaptive processes involved in the choice between stimulus-approach and place-approach strategies are reproduced very accurately by the model. The model has implications both for further studies of the ecology of the animal and for robotic systems."
3.  Active dendritic integration in robust and precise grid cell firing (Schmidt-Hieber et al 2017)
"... Whether active dendrites contribute to the generation of the dual temporal and rate codes characteristic of grid cell output is unknown. We show that dendrites of medial entorhinal cortex neurons are highly excitable and exhibit a supralinear input–output function in vitro, while in vivo recordings reveal membrane potential signatures consistent with recruitment of active dendritic conductances. By incorporating these nonlinear dynamics into grid cell models, we show that they can sharpen the precision of the temporal code and enhance the robustness of the rate code, thereby supporting a stable, accurate representation of space under varying environmental conditions. Our results suggest that active dendrites may therefore constitute a key cellular mechanism for ensuring reliable spatial navigation."
4.  Auditory nerve spontaneous rate histograms (Jackson and Carney 2005)
Histograms of spontaneous rate estimates of auditory nerve are well reproduced by models with two or three spontaneous rates and long range dependence.
5.  Ca2+-activated I_CAN and synaptic depression promotes network-dependent oscil. (Rubin et al. 2009)
"... the preBotzinger complex... we present and analyze a mathematical model demonstrating an unconventional mechanism of rhythm generation in which glutamatergic synapses and the short-term depression of excitatory transmission play key rhythmogenic roles. Recurrent synaptic excitation triggers postsynaptic Ca2+- activated nonspecific cation current (ICAN) to initiate a network-wide burst. Robust depolarization due to ICAN also causes voltage-dependent spike inactivation, which diminishes recurrent excitation and thus attenuates postsynaptic Ca2+ accumulation. ..."
6.  Efficient simulation environment for modeling large-scale cortical processing (Richert et al. 2011)
"We have developed a spiking neural network simulator, which is both easy to use and computationally efficient, for the generation of large-scale computational neuroscience models. The simulator implements current or conductance based Izhikevich neuron networks, having spike-timing dependent plasticity and short-term plasticity. ..."
7.  Encoding and discrimination of vowel-like sounds (Tan and Carney 2005)
"The sensitivity of listeners to changes in the center frequency of vowel-like harmonic complexes as a function of the center frequency of the complex cannot be explained by changes in the level of the stimulus [Lyzenga and Horst, J. Acoust. Soc. Am. 98, 1943–1955 (1995)]. Rather, a complex pattern of sensitivity is seen; for a spectrum with a triangular envelope, the greatest sensitivity occurs when the center frequency falls between harmonics, whereas for a spectrum with a trapezoidal envelope, greatest sensitivity occurs when the center frequency is aligned with a harmonic. In this study, the thresholds of a population model of auditory-nerve (AN) fibers were quantitatively compared to these trends in psychophysical thresholds. Single-fiber and population model responses were evaluated in terms of both average discharge rate and the combination of rate and timing information. ..."
8.  Generating neuron geometries for detailed 3D simulations using AnaMorph (Morschel et al 2017)
"Generating realistic and complex computational domains for numerical simulations is often a challenging task. In neuroscientific research, more and more one-dimensional morphology data is becoming publicly available through databases. This data, however, only contains point and diameter information not suitable for detailed three-dimensional simulations. In this paper, we present a novel framework, AnaMorph, that automatically generates water-tight surface meshes from one-dimensional point-diameter files. These surface triangulations can be used to simulate the electrical and biochemical behavior of the underlying cell. ..."
9.  Inhibitory control by an integral feedback signal in prefrontal cortex (Miller and Wang 2006)
The prefrontal cortex (PFC) is known to be critical for inhibitory control of behavior, but the underlying mechanisms are unclear. Here, we propose that inhibitory control can be instantiated by an integral signal derived from working memory, another key function of the PFC. Specifically, we assume that an integrator converts excitatory input into a graded mnemonic activity that provides an inhibitory signal (integral feedback control) to upstream afferent neurons. We demonstrate this scenario in a neuronal-network model for a temporal discrimination task... See paper for details and more.
10.  Integrate and fire model code for spike-based coincidence-detection (Heinz et al. 2001, others)
Model code relevant to three papers; two on level discrimination and one on masked detection at low frequencies.
11.  Lobster STG pyloric network model with calcium sensor (Gunay & Prinz 2010) (Prinz et al. 2004)
This pyloric network model simulator is a C/C++ program that saves 384 different calcium sensor values that are candidates for activity sensors (Gunay and Prinz, 2010). The simulator was used to scan all of the 20 million pyloric network models that were previously collected in a database (Prinz et al, 2004).
12.  Long-term adaptation with power-law dynamics (Zilany et al. 2009)
... A model of rate adaptation at the synapse between inner hair cells and auditory-nerve (AN) fibers that includes both exponential and power-law dynamics is presented here. Exponentially adapting components with rapid and short-term time constants, which are mainly responsible for shaping onset responses, are followed by two parallel paths with power-law adaptation that provide slowly and rapidly adapting responses. ... The proposed model is capable of accurately predicting several sets of AN data, including amplitude-modulation transfer functions, long-term adaptation, forward masking, and adaptation to increments and decrements in the amplitude of an ongoing stimulus.
13.  Model of memory linking through memory allocation (Kastellakis et al. 2016)
Here, we present a simplified, biophysically inspired network model that incorporates multiple plasticity processes and explains linking of information at three different levels: (a) learning of a single associative memory (b) rescuing of a weak memory when paired with a strong one and (c) linking of multiple memories across time. By dissecting synaptic from intrinsic plasticity and neuron-wide from dendritically restricted protein capture, the model reveals a simple, unifying principle: Linked memories share synaptic clusters within the dendrites of overlapping populations of neurons
14.  Model of neural responses to amplitude-modulated tones (Nelson and Carney 2004)
"A phenomenological model with time-varying excitation and inhibition was developed to study possible neural mechanisms underlying changes in the representation of temporal envelopes along the auditory pathway. A modified version of an existing auditory-nerve model (Zhang et al., J. Acoust. Soc. Am. 109, 648–670 (2001) was used to provide inputs to higher hypothetical processing centers. Model responses were compared directly to published physiological data at three levels: the auditory nerve, ventral cochlear nucleus, and inferior colliculus. ..."
15.  Models for diotic and dichotic detection (Davidson et al. 2009)
Several psychophysical models for masked detection were evaluated using reproducible noises. The data were hit and false-alarm rates from three psychophysical studies of detection of 500-Hz tones in reproducible noise under diotic (N0S0) and dichotic (N0Spi) conditions with four stimulus bandwidths (50, 100, 115, and 2900 Hz). Diotic data were best predicted by an energy-based multiple-detector model that linearly combined stimulus energies at the outputs of several critical-band filters. The tone-plus-noise trials in the dichotic data were best predicted by models that linearly combined either the average values or the standard deviations of interaural time and level differences; however, these models offered no predictions for noise-alone responses. ...". The Breebart et al. 2001 and the Dau et al. 1996 models are supplied at the Carney lab web site.
16.  Multimodal stimuli learning in hawkmoths (Balkenius et al. 2008)
The moth Macroglossum stellatarum can learn the color and sometimes the odor of a rewarding food source. We present data from 20 different experiments with different combinations of blue and yellow artificial flowers and the two odors, honeysuckle and lavender. ... Three computational models were tested in the same experimental situations as the real moths and their predictions were compared with the experimental data. ... Neither the Rescorla–Wagner model nor a learning model with independent learning for each stimulus component were able to explain the experimental data. We present the new hawkmoth learning model, which assumes that the moth learns a template for the sensory attributes of the rewarding stimulus. This model produces behavior that closely matches that of the real moth in all 20 experiments.
17.  Neural mass model of spindle generation in the isolated thalamus (Schellenberger Costa et al. 2016)
The model generates different oscillatory patterns in the thalamus, including delta and spindle band oscillations.
18.  Neural mass model of the neocortex under sleep regulation (Costa et al 2016)
This model generates typical human EEG patterns of sleep stages N2/N3 as well as wakefulness and REM. It further contains a sleep regulatory component, that lets the model transition between those stages independently
19.  Neural mass model of the sleeping cortex (Weigenand et al 2014)
Generates typical EEG data of sleeping Humans for sleep stages N2/N3 as well as wakefulness
20.  Neural mass model of the sleeping thalamocortical system (Schellenberger Costa et al 2016)
This paper generates typical human EEG data of sleep stages N2/N3 as well as wakefulness and REM sleep.
21.  NEUROFIT: fitting HH models to voltage clamp data (Willms 2002)
Publicly available software for accurate fitting of Hodgkin-Huxley models to voltage-clamp data... The set of parameter values for the model determined by this software yield current traces that are substantially closer to the observed data than those determined from the usual fitting method. This improvement is due to the fact that the software fits all of the parameters simultaneously utilizing all of the data rather than fitting steady-state and time constant parameters disjointly using peak currents and portions of the rising and falling phases... The software also incorporates a linear pre-estimation procedure to help in determining reasonable initial values for the full non-linear algorithm. See references for details and more.
22.  Polychronization: Computation With Spikes (Izhikevich 2005)
"We present a minimal spiking network that can polychronize, that is, exhibit reproducible time-locked but not synchronous firing patterns with millisecond precision, as in synfire braids. The network consists of cortical spiking neurons with axonal conduction delays and spiketiming- dependent plasticity (STDP); a ready-to-use MATLAB code is included. It exhibits sleeplike oscillations, gamma (40 Hz) rhythms, conversion of firing rates to spike timings, and other interesting regimes. ... To our surprise, the number of coexisting polychronous groups far exceeds the number of neurons in the network, resulting in an unprecedented memory capacity of the system. ..."
23.  Predicting formant-frequency discrimination in noise (Tan and Carney 2006)
"To better understand how the auditory system extracts speech signals in the presence of noise, discrimination thresholds for the second formant frequency were predicted with simulations of auditory-nerve responses. These predictions employed either average-rate information or combined rate and timing information, and either populations of model fibers tuned across a wide range of frequencies or a subset of fibers tuned to a restricted frequency range. In general, combined temporal and rate information for a small population of model fibers tuned near the formant frequency was most successful in replicating the trends reported in behavioral data for formant-frequency discrimination. ..."
24.  Quantitative assessment of computational models for retinotopic map formation (Hjorth et al. 2015)
"Molecular and activity-based cues acting together are thought to guide retinal axons to their terminal sites in vertebrate optic tectum or superior colliculus (SC) to form an ordered map of connections. The details of mechanisms involved, and the degree to which they might interact, are still not well understood. We have developed a framework within which existing computational models can be assessed in an unbiased and quantitative manner against a set of experimental data curated from the mouse retinocollicular system. ..."
25.  Rat phrenic motor neuron (Amini et al 2004)
We have developed a model for the rat phrenic motor neuron (PMN) that robustly replicates many experimentally observed behaviors of PMNs in response to pharmacological, ionic, and electrical perturbations using a single set of parameters.
26.  Response properties of an integrate and fire model (Zhang and Carney 2005)
"A computational technique is described for calculation of the interspike interval and poststimulus time histograms for the responses of an integrate-and-fire model to arbitrary inputs. ... For stationary inputs, the regularity of the output was studied in detail for various model parameters. For nonstationary inputs, the effects of the model parameters on the output synchronization index were explored. ... these response properties have been reported for some cells in the ventral cochlear nucleus in the auditory brainstem. "
27.  Reverberatory bursts propagation and synchronization in developing cultured NNs (Huang et al 2016)
"Developing networks of neural systems can exhibit spontaneous, synchronous activities called neural bursts, which can be important in the organization of functional neural circuits. ... Using a propagation model we infer the spreading speed of the spiking activity, which increases as the culture ages. We perform computer simulations of the system using a physiological model of spiking networks in two spatial dimensions and find the parameters that reproduce the observed resynchronization of spiking in the bursts. An analysis of the simulated dynamics suggests that the depletion of synaptic resources causes the resynchronization. The spatial propagation dynamics of the simulations match well with observations over the course of a burst and point to an interplay of the synaptic efficacy and the noisy neural self-activation in producing the morphology of the bursts."
28.  Simple model of barrel-specific segregation in cortex (Lu et al 2006)
Mice with a loss-of-function mutation of calcium/calmodulin-activated adenylyl cyclase I (AC1) - barrelless mice - have strikingly abherrent cortical development: the thalamic afferents into the barrel cortex do not segregate into whisker-specific barrels. Our paper investigates the link between this mutation and the "barrelless" phenotype, and demonstrates that the loss-of-function mutation leads to deficits in presynaptic mechanisms at the thalamocortical synapse. How might presynaptic deficits disrupt whisker-specific segregation in the barrel cortex? We used a model to demonstrate one possibility: decrease in the release probability at the thalamocortical synapse (which is observed in the barrelless mutant) can influence the balance between LTP and LTD (in favor of LTD), which can disrupt whisker segregaton. Though how this occurs is easily explained with a conceptual model (described succinctly in the associated paper), we also produced a computational simulation of this phenomenon.
29.  Towards a virtual C. elegans (Palyanov et al. 2012)
"... Here we present a detailed demonstration of a virtual C. elegans aimed at integrating these data in the form of a 3D dynamic model operating in a simulated physical environment. Our current demonstration includes a realistic flexible worm body model, muscular system and a partially implemented ventral neural cord. Our virtual C. elegans demonstrates successful forward and backward locomotion when sending sinusoidal patterns of neuronal activity to groups of motor neurons. ..."
30.  Ventricular cell model (Guinea-pig-type) (Luo, Rudy 1991, +11 other papers!) (C++)
A mathematical model of the membrane action potential of the mammalian ventricular cell is introduced. The model is based, whenever possible, on recent single-cell and single-channel data and incorporates the possibility of changing extracellular potassium concentration [K]o. ... The results are consistent with recent experimental observations, and the model simulations relate these phenomena to the underlying ionic channel kinetics. See paper for more and details.
31.  Virtual Retina: biological retina simulator, with contrast gain control (Wohrer and Kornprobst 2009)
"We propose a new retina simulation software, called Virtual Retina, which transforms a video into spike trains. Our goal is twofold: Allow large scale simulations (up to 100,000 neurons) in reasonable processing times and keep a strong biological plausibility, taking into account implementation constraints. ... This software will be an evolutionary tool for neuroscientists that need realistic large-scale input spike trains in subsequent treatments, and for educational purposes."

Re-display model names without descriptions