Convolutional Neural Network Classification of Topographic Electroencephalographic Maps on Alcoholism.

Alcohol use is a leading risk factor for substantial health loss, disability, and death. Thus, there is a general interest in developing computational tools to classify electroencephalographic (EEG) signals in alcoholism, but there are a limited number of studies on convolutional neural network (CNN) classification of alcoholism using topographic EEG signals. We produced an original dataset recorded from Brazilian subjects performing a language recognition task. Then, we transformed the Event-Related Potentials (ERPs) into topographic maps by using the ERP's statistical parameters across time, and used a CNN network to classify the topographic dataset. We tested the effect of the size of the dataset in the accuracy of the CNNs and proposed a data augmentation approach to increase the size of the topographic dataset to improve the accuracies. Our results encourage the use of CNNs to classify abnormal topographic EEG patterns associated with alcohol abuse.

Stochastic reaction-diffusion modeling of calcium dynamics in 3D dendritic spines of Purkinje cells.

Calcium (Ca2+) is a second messenger assumed to control changes in synaptic strength in the form of both long-term depression and long-term potentiation at Purkinje cell dendritic spine synapses via inositol trisphosphate (IP3)-induced Ca2+ release. These Ca2+ transients happen in response to stimuli from parallel fibers (PFs) from granule cells and climbing fibers (CFs) from the inferior olivary nucleus. These events occur at low numbers of free Ca2+, requiring stochastic single-particle methods when modeling them. We use the stochastic particle simulation program MCell to simulate Ca2+ transients within a three-dimensional Purkinje cell dendritic spine. The model spine includes the endoplasmic reticulum, several Ca2+ transporters, and endogenous buffer molecules. Our simulations successfully reproduce properties of Ca2+ transients in different dynamical situations. We test two different models of the IP3 receptor (IP3R). The model with nonlinear concentration response of binding of activating Ca2+ reproduces experimental results better than the model with linear response because of the filtering of noise. Our results also suggest that Ca2+-dependent inhibition of the IP3R needs to be slow to reproduce experimental results. Simulations suggest the experimentally observed optimal timing window of CF stimuli arises from the relative timing of CF influx of Ca2+ and IP3 production sensitizing IP3R for Ca2+-induced Ca2+ release. We also model ataxia, a loss of fine motor control assumed to be the result of malfunctioning information transmission at the granule to Purkinje cell synapse, resulting in a decrease or loss of Ca2+ transients. Finally, we propose possible ways of recovering Ca2+ transients under ataxia.

3D Modeling of Dendritic Spines with Synaptic Plasticity.

Computational modeling of diffusion and reaction of chemical species in a three-dimensional (3D) geometry is a fundamental method to understand the mechanisms of synaptic plasticity in dendritic spines. In this protocol, the detailed 3D structure of the dendrites and dendritic spines is modeled with meshes on the software Blender with CellBlender. The synaptic and extrasynaptic regions are defined on the mesh. Next, the synaptic receptor and synaptic anchor molecules are defined with their diffusion constants. Finally, the chemical reactions between synaptic receptors and synaptic anchors are included and the computational model is solved numerically with the software MCell. This method describes the spatiotemporal path of every single molecule in a 3D geometrical structure. Thus, it is very useful to study the trafficking of synaptic receptors in and out of the dendritic spines during the occurrence of synaptic plasticity. A limitation of this method is that the high number of molecules slows the speed of the simulations. Modeling of dendritic spines with this method allows the study of homosynaptic potentiation and depression within single spines and heterosynaptic plasticity between neighbor dendritic spines.

Mild myelin disruption elicits early alteration in behavior and proliferation in the subventricular zone.

Myelin, the insulating sheath around axons, supports axon function. An important question is the impact of mild myelin disruption. In the absence of the myelin protein proteolipid protein (PLP1), myelin is generated but with age, axonal function/maintenance is disrupted. Axon disruption occurs in Plp1-null mice as early as 2 months in cortical projection neurons. High-volume cellular quantification techniques revealed a region-specific increase in oligodendrocyte density in the olfactory bulb and rostral corpus callosum that increased during adulthood. A distinct proliferative response of progenitor cells was observed in the subventricular zone (SVZ), while the number and proliferation of parenchymal oligodendrocyte progenitor cells was unchanged. This SVZ proliferative response occurred prior to evidence of axonal disruption. Thus, a novel SVZ response contributes to the region-specific increase in oligodendrocytes in Plp1-null mice. Young adult Plp1-null mice exhibited subtle but substantial behavioral alterations, indicative of an early impact of mild myelin disruption.

Mirror Neurons Modeled Through Spike-Timing-Dependent Plasticity are Affected by Channelopathies Associated with Autism Spectrum Disorder.

Mirror neurons fire action potentials both when the agent performs a certain behavior and watches someone performing a similar action. Here, we present an original mirror neuron model based on the spike-timing-dependent plasticity (STDP) between two morpho-electrical models of neocortical pyramidal neurons. Both neurons fired spontaneously with basal firing rate that follows a Poisson distribution, and the STDP between them was modeled by the triplet algorithm. Our simulation results demonstrated that STDP is sufficient for the rise of mirror neuron function between the pairs of neocortical neurons. This is a proof of concept that pairs of neocortical neurons associating sensory inputs to motor outputs could operate like mirror neurons. In addition, we used the mirror neuron model to investigate whether channelopathies associated with autism spectrum disorder could impair the modeled mirror function. Our simulation results showed that impaired hyperpolarization-activated cationic currents (Ih) affected the mirror function between the pairs of neocortical neurons coupled by STDP.

Modelling intracellular competition for calcium: kinetic and thermodynamic control of different molecular modes of signal decoding.

Frequently, a common chemical entity triggers opposite cellular processes, which implies that the components of signalling networks must detect signals not only through their chemical natures, but also through their dynamic properties. To gain insights on the mechanisms of discrimination of the dynamic properties of cellular signals, we developed a computational stochastic model and investigated how three calcium ion (Ca(2+))-dependent enzymes (adenylyl cyclase (AC), phosphodiesterase 1 (PDE1), and calcineurin (CaN)) differentially detect Ca(2+) transients in a hippocampal dendritic spine. The balance among AC, PDE1 and CaN might determine the occurrence of opposite Ca(2+)-induced forms of synaptic plasticity, long-term potentiation (LTP) and long-term depression (LTD). CaN is essential for LTD. AC and PDE1 regulate, indirectly, protein kinase A, which counteracts CaN during LTP. Stimulations of AC, PDE1 and CaN with artificial and physiological Ca(2+) signals demonstrated that AC and CaN have Ca(2+) requirements modulated dynamically by different properties of the signals used to stimulate them, because their interactions with Ca(2+) often occur under kinetic control. Contrarily, PDE1 responds to the immediate amplitude of different Ca(2+) transients and usually with the same Ca(2+) requirements observed under steady state. Therefore, AC, PDE1 and CaN decode different dynamic properties of Ca(2+) signals.

Electrical responses of three classes of granule cells of the olfactory bulb to synaptic inputs in different dendritic locations.

This work consists of a computational study of the electrical responses of three classes of granule cells of the olfactory bulb to synaptic activation in different dendritic locations. The constructed models were based on morphologically detailed compartmental reconstructions of three granule cell classes of the olfactory bulb with active dendrites described by Bhalla and Bower (1993, pp. 1948-1965) and dendritic spine distributions described by Woolf et al. (1991, pp. 1837-1854). The computational studies with the model neurons showed that different quantities of spines have to be activated in each dendritic region to induce an action potential, which always was originated in the active terminal dendrites, independently of the location of the stimuli, and the morphology of the dendritic tree. These model predictions might have important computational implications in the context of olfactory bulb circuits.

Excitation of rat cerebellar Golgi cells by ethanol: further characterization of the mechanism.

BACKGROUND: Studies with rodents suggest that acute ethanol exposure impairs information flow through the cerebellar cortex, in part, by increasing GABAergic input to granule cells. Experiments suggest that an increase in the excitability of specialized GABAergic interneurons that regulate granule cell activity (i.e., Golgi cells [GoCs]) contributes to this effect. In GoCs, ethanol increases spontaneous action potential firing frequency, decreases the afterhyperpolarization amplitude, and depolarizes the membrane potential. Studies suggest that these effects could be mediated by inhibition of the Na(+)/K(+) ATPase. The purpose of this study was to characterize the potential role of other GoC conductances in the mechanism of action of ethanol. METHODS: Computer modeling techniques and patch-clamp electrophysiological recordings with acute slices from rat cerebella were used for these studies. RESULTS: Computer modeling suggested that modulation of subthreshold Na(+) channels, hyperpolarization-activated currents, and several K(+) conductances could explain some but not all actions of ethanol on GoCs. Electrophysiological studies did not find evidence consistent with a contribution of these conductances. Quinidine, a nonselective blocker of several types of channels (including several K(+) channels) that also antagonizes the Na(+)/K(+) ATPase, reduced the effect of ethanol on GoC firing. CONCLUSIONS: These findings further support that ethanol increases GoC excitability via modulation of the Na(+)/K(+) ATPase and suggest that a quinidine-sensitive K(+) channel may also play a role in the mechanism of action of ethanol.

Robustness effect of gap junctions between Golgi cells on cerebellar cortex oscillations.

BACKGROUND: Previous one-dimensional network modeling of the cerebellar granular layer has been successfully linked with a range of cerebellar cortex oscillations observed in vivo. However, the recent discovery of gap junctions between Golgi cells (GoCs), which may cause oscillations by themselves, has raised the question of how gap-junction coupling affects GoC and granular-layer oscillations. To investigate this question, we developed a novel two-dimensional computational model of the GoC-granule cell (GC) circuit with and without gap junctions between GoCs. RESULTS: Isolated GoCs coupled by gap junctions had a strong tendency to generate spontaneous oscillations without affecting their mean firing frequencies in response to distributed mossy fiber input. Conversely, when GoCs were synaptically connected in the granular layer, gap junctions increased the power of the oscillations, but the oscillations were primarily driven by the synaptic feedback loop between GoCs and GCs, and the gap junctions did not change oscillation frequency or the mean firing rate of either GoCs or GCs. CONCLUSION: Our modeling results suggest that gap junctions between GoCs increase the robustness of cerebellar cortex oscillations that are primarily driven by the feedback loop between GoCs and GCs. The robustness effect of gap junctions on synaptically driven oscillations observed in our model may be a general mechanism, also present in other regions of the brain.

A biophysical model of vertebrate olfactory epithelium and bulb exhibiting gap junction dependent odor-evoked spatiotemporal patterns of activity.

This work describes a biophysical model of the initial stages of vertebrate olfactory system containing structures representing the olfactory epithelium and bulb. Its main novelty is the introduction of gap junctions connecting neurons both in the epithelium and bulb, and of biologically detailed dendrodendritic synapses between granule and mitral cells in the bulb. The model was used to simulate the effect of an odor presentation on the neural activity pattern in the epithelium and bulb. During the time for which an odor is presented with a constant concentration, there are spatiotemporal patterns in the epithelium and bulb generated by the couplings due to the gap junctions and/or dendrodendritic synapses. A study varying the strength of the gap junction coupling shows that the spatiotemporal patterns, both in the epithelium and bulb, are dependent of the coupling strength. It is also shown that the olfactory bulb's spatiotemporal pattern depends on the existence of the dendrodendritic connections between mitral and granule cells. If these spatiotemporal patterns really exist in the early processing stages of the olfactory system they may be used for odor coding and the gap junctions and dendrodendritic synapses might have a role on it.