ulus ▁and ▁the ▁A - C ▁context ▁pattern . ▁When ▁the ▁model ▁was ▁trained ▁concurrent ly ▁on ▁the ▁A - B ▁and ▁A - C ▁items ▁then ▁the ▁network ▁readily ▁learned ▁all ▁of ▁the ▁associations ▁correctly . ▁In ▁sequ ential ▁training ▁the ▁A - B ▁list ▁was ▁trained ▁first , ▁followed ▁by ▁the ▁A - C ▁list . ▁After ▁each ▁presentation ▁of ▁the ▁A - C ▁list , ▁performance ▁was ▁measured ▁for ▁both ▁the ▁A - B ▁and ▁A - C ▁lists . ▁They ▁found ▁that ▁the ▁amount ▁of ▁training ▁on ▁the ▁A - C ▁list ▁in ▁Bar nes ▁and ▁Under wood ▁study ▁that ▁lead ▁to ▁ 5 0 % ▁correct ▁responses , ▁lead ▁to ▁nearly ▁ 0 % ▁correct ▁responses ▁by ▁the ▁back prop ag ation ▁network . ▁Furthermore , ▁they ▁found ▁that ▁the ▁network ▁t ended ▁to ▁show ▁responses ▁that ▁looked ▁like ▁the ▁C ▁response ▁pattern ▁when ▁the ▁network ▁was ▁prompt ed ▁to ▁give ▁the ▁B ▁response ▁pattern . ▁This ▁indicated ▁that ▁the ▁A - C ▁list ▁apparently ▁had ▁over written ▁the ▁A - B ▁list . ▁This ▁could ▁be ▁li ken ed ▁to ▁learning ▁the ▁word ▁dog , ▁followed ▁by ▁learning ▁the ▁word ▁st ool ▁and ▁then ▁finding ▁that ▁you ▁cannot ▁recognize ▁the ▁word ▁cat ▁well ▁but ▁instead ▁think ▁of ▁the ▁word ▁st ool ▁when ▁presented ▁with ▁the ▁word ▁dog . ▁ ▁McC los key ▁and ▁C ohen ▁tried ▁to ▁reduce ▁inter ference ▁through ▁a ▁number ▁of ▁manip ulations ▁including ▁changing ▁the ▁number ▁of ▁hidden ▁units , ▁changing ▁the ▁value