The code snippet provided appears to be part of a computational neuroscience model focusing on certain aspects of neural activity, likely related to synaptic currents or membrane dynamics. The primary biological basis of this code can be inferred as follows:
Current Dynamics: The code intends to plot what it refers to as 'totCurr', which suggests it is dealing with total currents. In the context of neurons, these currents could represent ionic currents flowing through various channels in the neuronal membrane, influencing the neuron's membrane potential and, ultimately, neuronal firing.
Synaptic Activity or Ion Channel Conductance: The analysis in the code suggests it focuses on aspects of synaptic transmission or ion channel activity. Ionic currents, particularly sodium (Na+), potassium (K+), and calcium (Ca2+), play a critical role in neuronal excitability, and synaptic currents often stem from neurotransmitter-induced channel openings.
Gating Variables: The expression totCurr(:,3)./(totCurr(:,2)+totCurr(:,3)) bears resemblance to dynamic factors like gating variables in Hodgkin-Huxley-type models or synaptic conductance models. These variables often describe the proportion of ion channels in an open state relative to the total population, influencing the effective conductance.
Subplot (2, 1, 1): The first subplot is manipulating and visualizing the total currents with the ratio as an independent variable, suggesting an examination of how the proportion of certain currents (possibly excitatory versus inhibitory) impacts another variable (likely time or voltage). This could reflect the balance of synaptic excitation/inhibition or inward/outward ionic conductance affecting overall neuronal behavior.
Subplot (2, 1, 2): The second subplot plots normalized deviations of a quantity (potentially the neuron's membrane potential or some related signal) over its initial value. This aspect could relate to adaptation, plasticity, or other dynamic changes in response to the currents being studied.
This code represents visualization related to the dynamics of ionic currents or synaptic conductances in a neural model, allowing for examination of how these bioelectric phenomena contribute to neuronal function. The balancing of different current types, as well as their collective impact on membrane potential dynamics, is central to understanding how neurons encode, process, and transmit information.