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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _addToPoolingActivation(self, activeCells, overlaps):
 """ Adds overlaps from specified active cells to cells' pooling activation. @param activeCells: Indices of those cells winning the inhibition step @param overlaps: A current set of overlap values for each cell @return current pooling activation """

    self._poolingActivation[activeCells] = self._exciteFunction.excite(
      self._poolingActivation[activeCells], overlaps[activeCells])

    # increase pooling timers for all cells
    self._poolingTimer[self._poolingTimer >= 0] += 1

    # reset pooling timer for active cells
    self._poolingTimer[activeCells] = 0
    self._poolingActivationInitLevel[activeCells] = self._poolingActivation[activeCells]

    return self._poolingActivation