As such, we did not aim to exactly capture adaptation characteristics, but rather to capture strongly and weakly adapting cells as represented by the data here.
These models capture the frequency-current profiles of both strongly and weakly adapting cells.
There are two types of models, differing in some parameter values, to account for "strongly" and "weakly" adapting cell varieties.
For example, what would be the responses to time varying inputs and how the responses would differ between the strongly and weakly adapting cells?
Second paragraph of Weakly adapting models: "In addition, to obtain an appropriate rheobase current, we included a short in the applied current".
We found that for the two weakly adapting pyramidal cells, the slope of the linear least squares approximation of the f-I curves were 0.119 and 0.138 for the initial curves, and 0.013 and 0.044 for the final curves (values relating to experimental, data green and black in Figure 1 and Figure 4).
Following a similar methodology, we created two separate models for the weakly adapting pyramidal cells: the first better captures the cell's weak adaptation, especially for larger currents, but has a steep final slope, whereas the second captures the more gradual slope of the final f-I curve, but doesn't exhibit the cell's weak level of adaptation.
Nevertheless, the shortest latencies of the neurons that showed strong adaptation for a certain condition in the MGB were significantly longer than those of weakly adapting neurons for a certain condition, to both the deviant and standard stimuli.
Thus, we created pyramidal cell models based on the strongly adapting cells and the weakly adapting cells separately.
A series of depolarizing (10 pA) steps were used to precisely determine the rheobase currents, which were 62.0 pA and -12.1 pA for the two weakly adapting cells.
