Computational Modeling of Channelrhodopsin-2 Photocurrent Characteristics in Relation to Neural Signaling

Channelrhodopsins-2 (ChR2) are a class of light sensitive proteins that offer the ability to use light stimulation to regulate neural activity with millisecond precision. In order to address the limitations in the efficacy of the wild-type ChR2 (ChRwt) to achieve this objective, new variants of ChR2 that exhibit fast mono-exponential photocurrent decay characteristics have been recently developed and validated. In this paper, we investigate whether the framework of transition rate model with 4 states, primarily developed to mimic the bi-exponential photocurrent decay kinetics of ChRwt, as opposed to the low complexity 3 state model, is warranted to mimic the mono-exponential photocurrent decay kinetics of the newly developed fast ChR2 variants: ChETA (Gunaydin et al., Nature Neurosci, 13:387-392, 2010) and ChRET/TC (Berndt et al., PNAS, 108:7595-7600, 2011). We begin by estimating the parameters for the 3-state and 4-state models from experimental data on the photocurrent kinetics of ChRwt, ChETA and ChRET/TC. We then incorporate these models into a fast-spiking interneuron model (Wang and Buzsaki., J Neurosci, 16:6402-6413,1996) and a hippocampal pyramidal cell model (Golomb et al., J Neurophysiol, 96:1912-1926, 2006) and investigate the extent to which the experimentally observed neural response to various optostimulation protocols can be captured by these models. We demonstrate that for all ChR2 variants investigated, the 4 state model implementation is better able to capture neural response consistent with experiments across wide range of optostimulation protocol. We conclude by analytically investigating the conditions under which the characteristic specific to the 3-state model, namely the mono-exponential photocurrent decay of the newly developed variants of ChR2, can occurs in the framework of the 4-state model.Comment: 10 figure

A Low Dimensional Description of Globally Coupled Heterogeneous Neural Networks of Excitatory and Inhibitory Neurons

Neural networks consisting of globally coupled excitatory and inhibitory nonidentical neurons may exhibit a complex dynamic behavior including synchronization, multiclustered solutions in phase space, and oscillator death. We investigate the conditions under which these behaviors occur in a multidimensional parametric space defined by the connectivity strengths and dispersion of the neuronal membrane excitability. Using mode decomposition techniques, we further derive analytically a low dimensional description of the neural population dynamics and show that the various dynamic behaviors of the entire network can be well reproduced by this reduced system. Examples of networks of FitzHugh-Nagumo and Hindmarsh-Rose neurons are discussed in detail

NMDA receptors mediate stimulus-timing-dependent plasticity and neural synchrony in the dorsal cochlear nucleus

Auditory information relayed by auditory nerve fibers and somatosensory information relayed by granule cell parallel fibers converge on the fusiform cells (FCs) of the dorsal cochlear nucleus, the first brain station of the auditory pathway. In vitro, parallel fiber synapses on FCs exhibit spike-timing-dependent plasticity with Hebbian learning rules, partially mediated by the NMDA receptor (NMDAr). Well-timed bimodal auditory-somatosensory stimulation, in vivo equivalent of spike-timing-dependent plasticity, can induce stimulus-timing-dependent plasticity (StTDP) of the FCs spontaneous and tone-evoked firing rates. In healthy guinea pigs, the resulting distribution of StTDP learning rules across a FC neural population is dominated by a Hebbian profile while anti-Hebbian, suppressive and enhancing LRs are less frequent. In this study, we investigate in vivo, the NMDAr contribution to FC baseline activity and long term plasticity. We find that blocking the NMDAr decreases the synchronization of FC- spontaneous activity and mediates differential modulation of FC rate-level functions such that low, and high threshold units are more likely to increase, and decrease, respectively, their maximum amplitudes. Three significant alterations in mean learning-rule profiles were identified: transitions from an initial Hebbian profile towards (1) an anti-Hebbian and (2) a suppressive profile, and (3) transitions from an anti-Hebbian to a Hebbian profile. FC units preserving their learning rules showed instead, NMDAr-dependent plasticity to unimodal acoustic stimulation, with persistent depression of tone-evoked responses changing to persistent enhancement following the NMDAr antagonist. These results reveal a crucial role of the NMDAr in mediating FC baseline activity and long-term plasticity which have important implications for signal processing and auditory pathologies related to maladaptive plasticity of dorsal cochlear nucleus circuitry

Genesis of interictal spikes in the CA1: a computational investigation

Interictal spikes (IISs) are spontaneous high amplitude, short time duration <400 ms events often observed in electroencephalographs (EEG) of epileptic patients. In vitro analysis of resected mesial temporal lobe tissue from patients with refractory temporal lobe epilepsy has revealed the presence of IIS in the CA1 subfield. In this paper, we develop a biophysically relevant network model of the CA1 subfield and investigate how changes in the network properties influence the susceptibility of CA1 to exhibit an IIS. We present a novel template based approach to identify conditions under which synchronization of paroxysmal depolarization shift (PDS) events evoked in CA1 pyramidal (Py) cells can trigger an IIS. The results from this analysis are used to identify the synaptic parameters of a minimal network model that is capable of generating PDS in response to afferent synaptic input. The minimal network model parameters are then incorporated into a detailed network model of the CA1 subfield in order to address the following questions: (1) How does the formation of an IIS in the CA1 depend on the degree of sprouting (recurrent connections) between the CA1 Py cells and the fraction of CA3 Shaffer collateral (SC) connections onto the CA1 Py cells? and (2) Is synchronous afferent input from the SC essential for the CA1 to exhibit IIS? Our results suggest that the CA1 subfield with low recurrent connectivity (absence of sprouting), mimicking the topology of a normal brain, has a very low probability of producing an IIS except when a large fraction of CA1 neurons (>80%) receives a barrage of quasi-synchronous afferent input (input occurring within a temporal window of ≤24 ms) via the SC. However, as we increase the recurrent connectivity of the CA1 (P(sprout) > 40); mimicking sprouting in a pathological CA1 network, the CA1 can exhibit IIS even in the absence of a barrage of quasi-synchronous afferents from the SC (input occurring within temporal window >80 ms) and a low fraction of CA1 Py cells (≈30%) receiving SC input. Furthermore, we find that in the presence of Poisson distributed random input via SC, the CA1 network is able to generate spontaneous periodic IISs (≈3 Hz) for high degrees of recurrent Py connectivity (P(sprout) > 70). We investigate the conditions necessary for this phenomenon and find that spontaneous IISs closely depend on the degree of the network's intrinsic excitability

Zinc binding agonist effect on the recognition of the β-amyloid (4–10) epitope by anti-β-amyloid antibodies

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