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. 2012 Feb 1:4:2.
doi: 10.3389/fnene.2012.00002. eCollection 2012.

Energetics based spike generation of a single neuron: simulation results and analysis

Nagarajan Venkateswaran  1 , Sudarshan Sekhar, Thiagarajan Thirupatchur Sanjayasarathy, Sharath Navalpakkam Krishnan, Dinesh Kannan Kabaleeswaran, Subbu Ramanathan, Narendran Narayanasamy, Sharan Srinivas Jagathrakshakan, S R Vignesh
Affiliations

Energetics based spike generation of a single neuron: simulation results and analysis

Nagarajan Venkateswaran et al. Front Neuroenergetics. .

Abstract

Existing current based models that capture spike activity, though useful in studying information processing capabilities of neurons, fail to throw light on their internal functioning. It is imperative to develop a model that captures the spike train of a neuron as a function of its intracellular parameters for non-invasive diagnosis of diseased neurons. This is the first ever article to present such an integrated model that quantifies the inter-dependency between spike activity and intracellular energetics. The generated spike trains from our integrated model will throw greater light on the intracellular energetics than existing current models. Now, an abnormality in the spike of a diseased neuron can be linked and hence effectively analyzed at the energetics level. The spectral analysis of the generated spike trains in a time-frequency domain will help identify abnormalities in the internals of a neuron. As a case study, the parameters of our model are tuned for Alzheimer's disease and its resultant spike trains are studied and presented. This massive initiative ultimately aims to encompass the entire molecular signaling pathways of the neuronal bioenergetics linking it to the voltage spike initiation and propagation; due to the lack of experimental data quantifying the inter dependencies among the parameters, the model at this stage adopts a particular level of functionality and is shown as an approach to study and perform disease modeling at the spike train and the mitochondrial bioenergetics level.

Keywords: ATP; Alzheimer’s disease; Krebs cycle; Petri nets; mitochondria; neuroenergetics; voltage spike; wavelet transformations.

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Figures

Figure 1
Figure 1
Simulation results using the energetics based single neuron simulator, for a pyramidal neuron over four stages of input under healthy conditions. (A) Difference in ionic concentration across the membrane (voltage spike; μM) vs timestamp. (B) Input neurotransmitters to the neuron (μM) vs timestamp corresponding to various input bands. (C) Krebs cycle activity (pyruvate consumed in μM per timestamp) vs timestamp. (D) Total intracellular ATP concentration (μM) vs timestamp.
Figure 2
Figure 2
Simulation results using the energetics based single neuron simulator, for a pyramidal neuron over four stages of input affected by Alzheimer’s disease. (A) Ionic concentration across the membrane (Voltage Spike; μM) vs timestamp. (B) Input neurotransmitters to the neuron (μM) vs Timestamp corresponding to various input bands. (C) Krebs cycle activity (NADH produced in μM/timestamp) vs timestamp. (D) Total intracellular ATP concentration (μM) vs timestamp.
Figure 3
Figure 3
Simulation results using the energetics based single neuron simulator, for a pyramidal neuron over four stages of input affected by a decrease in the rate of the electron transport chain. (A) Ionic concentration across the membrane (voltage spike; μM) vs timestamp. (B) Input neurotransmitters to the neuron (μM) vs timestamp corresponding to various input bands. (C) Krebs cycle activity (NADH produced in μM/timestamp) vs timestamp. (D) Total intracellular ATP concentration (μM) vs timestamp.
Figure 4
Figure 4
Simulation results using the energetics based single neuron simulator, for a pyramidal neuron over four stages of input affected by an increased formation of oxide ions. (A) Ionic concentration across the membrane (voltage spike; μM) vs timestamp. (B) Input neurotransmitters to the neuron (μM) vs timestamp corresponding to various input bands. (C) Krebs cycle activity (NADH produced in μM/timestamp) vs timestamp. (D) Total intracellular ATP concentration (μM) vs timestamp.
Figure 5
Figure 5
One dimensional wavelet transform (up to three frequency levels) of spike trains obtained from (A) energetics based simulation of a healthy pyramidal neuron. (B) Energetics based simulation of a pyramidal neuron affected by Alzheimer’s disease.
Figure 6
Figure 6
Petri nets based energetics model depicting the post-synapse and glial cells.
Figure 7
Figure 7
Transition probability matrix.
Figure 8
Figure 8
Petri nets based energetics model depicting the mitochondria.
Figure 9
Figure 9
Petri nets based energetics model depicting the pre synapse and spike generation.
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