Extended Data Fig. 4: A Hebbian/anti-Hebbian network model of CA1 with both excitatory and inhibitory neurons exhibits similar representational drift as the network in Fig. 5 of the main text.

(a) A Hebbian/anti-Hebbian network with inhibitory neurons derived from a similarity matching objective. The derivation is given SI Section 3. (b) Upper: learned place fields tile a 1D linear track when sorted by their centroid positions (left), but continuously change over time (right). Lower: Representational similarity matrix \({{{\mathbf{Y}}}}^ \top {{{\mathbf{Y}}}}\) of position is stable over time. (c) Peak amplitude of an example place field during a simulation. (d) Due to the drift, the average autocorrelation coefficient of population vectors decays over time. Shading: mean ± SD, n = 200 places, population vectors consist of only excitatory neurons. (e) Despite the continuous reconfiguration of place cell ensembles, the fraction of cells with active place fields is stable over time. (f) Neurons whose RFs have larger average amplitude is more stable, as characterized by smaller D. (g) Probability distribution of centroid drifts of place cells at three different time intervals. (h) Same as Fig. 5k in main text. Drifts of RFs show distance-dependent correlations, quantified by the average Pearson correlation coefficient. Shading: mean ± SD, n = 20 repeats. Error bars: mean ± SD, n = 13 animals. Parameters used are in Supplementary Table 1 of SI.