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\begin{table}[h]
\caption[]{{\bf Network with 700 DGCs (expansion factor from EC to dentate gyrus of about~5) compared to the case with $N_{DGC}=100$ as in the main text.} All other network parameters are unchanged. Each network is pretrained with digits 3 and 4. Note that only a subset of neurons responsive to digit 3 (or 4) get active (firing rate $>1$ Hz) for a given pattern 3 (or 4).  Classification performance is evaluated over all test patterns from the trained digits. Top: after pretraining; bottom:  late phase, after adding patterns from digit '5'. Either all unresponsive cells (Figure 4 - figure supplement 1), or only a fraction of these (Figure 4 - figure supplement 2), have been replaced by newborn model cells. For the network with 700 DGCs, about $16 - 18\%$ of DGCs are activated upon presentation of a digit 3 or 4 or 5 (about $112-126$ model DGCs). If  119 newborn DGCs are plastic during presentation of the novel digit 5 (middle column), these can become selective for prototypes of digit 5 (Figure 4 - figure supplement 2) yielding a good classification performance while keeping 156 unresponsive DGCs available for future tasks. If only 35 newborn DGCs are available, classification performance is lower (right column).}
\centering
\begin{tabular}{p{4.7cm}p{1.3cm}|p{2.5cm}|p{2.5cm}p{2.5cm}p{2.5cm}}
   & & \multicolumn{1}{c|}{$N_{DGC} = 100$} & \multicolumn{3}{c}{$N_{DGC} = 700$} \\[5pt]
\hline
 & & & \\
   \parbox{6cm}{Percentage [in \%] (and absolute number) of unresponsive neurons at the end of pretraining } & & \multicolumn{1}{c|}{21 (21 DGCs)} & \multicolumn{3}{c}{$\sim$39 (275 DGCs)} \\[30pt]
   
   \multirow{2}{*}{\parbox{4.5cm}{Percentage [in \%] (and absolute number) of selective neurons at the end of pretraining}}
   & Digit 3 & \multicolumn{1}{c|}{40 (40 DGCs)} & \multicolumn{3}{c}{$\sim$30 (212 DGCs)}\\
   & Digit 4 & \multicolumn{1}{c|}{39 (39 DGCs)} & \multicolumn{3}{c}{$\sim$30 (213 DGCs)}\\[45pt]
  
    \multirow{2}{*}{\parbox{4.5cm}{Percentage of active neurons per  test pattern at the end of pretraining ($\mu \pm \sigma$ [\%])}}
    & Digit 3 & \multicolumn{1}{c|}{$22.70 \pm 4.56 $} & \multicolumn{3}{c}{$16.55 \pm 2.49$} \\
    & Digit 4 & \multicolumn{1}{c|}{$22.09 \pm 3.91 $} & \multicolumn{3}{c}{$16.23 \pm 2.42$} \\[45pt]
    
     \parbox{6cm}{Classification performance at the end of pretraining [\%]} &  & \multicolumn{1}{c|}{$99.25$} & \multicolumn{3}{c}{$99.55$} \\[20pt]
   \hline
   & & & \\
   \parbox{6cm}{Percentage  [in \%] (and absolute number) of newborn model DGCs } & & \multicolumn{1}{c|}{21 (21 DGCs)} & \multicolumn{1}{c}{$\sim$39 (275 DGCs)} & \multicolumn{1}{c}{17 (119 DGCs)}& \multicolumn{1}{c}{5 (35 DGCs)} \\[25pt]
 
   \multirow{2}{*}{\parbox{4.5cm}{Percentage of active neurons per test pattern at the end of the late phase of maturation ($\mu \pm \sigma$ [\%])}}
    & Digit 3 & \multicolumn{1}{c|}{$24.16 \pm 4.87 $} & \multicolumn{1}{c}{$17.56 \pm 2.73$} & \multicolumn{1}{c}{$17.09 \pm 2.65$}  & \multicolumn{1}{c}{$16.67 \pm 2.53$} \\
    & Digit 4 & \multicolumn{1}{c|}{$22.84 \pm 4.21 $} & \multicolumn{1}{c}{$16.56 \pm 2.57$} & \multicolumn{1}{c}{$16.44 \pm 2.54$} &  \multicolumn{1}{c}{$16.30 \pm 2.45$} \\
    & Digit 5 & \multicolumn{1}{c|}{$21.98 \pm 4.52 $} & \multicolumn{1}{c}{$16.62 \pm 2.85$} & \multicolumn{1}{c}{$16.96 \pm 2.65$} & \multicolumn{1}{c}{$17.78 \pm 2.56$} \\[30pt]
   
   \parbox{6cm}{Classification performance at the end of the late phase of maturation [\%]} & & \multicolumn{1}{c|}{$94.56$} & \multicolumn{1}{c}{$96.32$} & \multicolumn{1}{c}{$ 95.49 $} & \multicolumn{1}{c}{$90.88$} \\
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