▁connection ist ▁networks ▁like ▁the ▁standard ▁back prop ag ation ▁network ▁are ▁very ▁sensitive ▁to ▁new ▁information ▁and ▁can ▁general ize ▁on ▁new ▁inputs . ▁Back prop ag ation ▁models ▁can ▁be ▁considered ▁good ▁models ▁of ▁human ▁memory ▁in so far ▁as ▁they ▁mirror ▁the ▁human ▁ability ▁to ▁general ize ▁but ▁these ▁networks ▁often ▁exhib it ▁less ▁stability ▁than ▁human ▁memory . ▁Not ably , ▁these ▁back prop ag ation ▁networks ▁are ▁sus cept ible ▁to ▁cat ast roph ic ▁inter ference . ▁This ▁is ▁considered ▁an ▁issue ▁when ▁attempting ▁to ▁model ▁human ▁memory ▁because , ▁unlike ▁these ▁networks , ▁humans ▁typically ▁do ▁not ▁show ▁cat ast roph ic ▁forget ting . ▁Thus , ▁the ▁issue ▁of ▁cat ast roph ic ▁inter ference ▁must ▁be ▁er adic ated ▁from ▁these ▁back prop ag ation ▁models ▁in ▁order ▁to ▁enh ance ▁the ▁pla us ibility ▁as ▁models ▁of ▁human ▁memory . ▁ ▁History ▁of ▁cat ast roph ic ▁inter ference ▁ ▁The ▁term ▁cat ast roph ic ▁inter ference ▁was ▁originally ▁co ined ▁by ▁McC los key ▁and ▁C ohen ▁( 1 9 8 9 ) ▁but ▁was ▁also ▁brought ▁to ▁the ▁attention ▁of ▁the ▁scientific ▁community ▁by ▁research ▁from ▁Rat cl iff ▁( 1 9 9 0 ). ▁ ▁The ▁Se qu ential ▁Learning ▁Problem : ▁McC los key ▁and ▁C ohen ▁( 1 9 8 9 ) ▁ ▁McC los key ▁and ▁C ohen ▁( 1 9 8 9 ) ▁noted ▁the ▁problem ▁of ▁cat ast roph ic ▁inter ference ▁during ▁two