. ▁( 1 9 9 5 ) ▁model , ▁the ▁final - storage ▁area ▁sends ▁internally ▁generated ▁representation ▁back ▁to ▁the ▁early ▁processing ▁area . ▁This ▁creates ▁a ▁rec urrent ▁network . ▁French ▁proposed ▁that ▁this ▁inter le aving ▁of ▁old ▁representations ▁with ▁new ▁representations ▁is ▁the ▁only ▁way ▁to ▁reduce ▁radical ▁forget ting . ▁Since ▁the ▁brain ▁would ▁most ▁likely ▁not ▁have ▁access ▁to ▁the ▁original ▁input ▁patterns , ▁the ▁patterns ▁that ▁would ▁be ▁fed ▁back ▁to ▁the ▁ne oc or tex ▁would ▁be ▁internally ▁generated ▁representations ▁called ▁pseud op at tern s . ▁ ▁These ▁pseud op at tern s ▁are ▁approxim ations ▁of ▁previous ▁inputs ▁and ▁they ▁can ▁be ▁inter le aved ▁with ▁the ▁learning ▁of ▁new ▁inputs . ▁The ▁use ▁of ▁these ▁pseud op at tern s ▁could ▁be ▁bi olog ically ▁pla us ible ▁as ▁par alle ls ▁between ▁the ▁cons olid ation ▁of ▁learning ▁that ▁occurs ▁during ▁sleep ▁and ▁the ▁use ▁of ▁inter le aved ▁pseud op at tern s . ▁Specifically , ▁they ▁both ▁serve ▁to ▁integrate ▁new ▁information ▁with ▁old ▁information ▁without ▁dis ruption ▁of ▁the ▁old ▁information . ▁When ▁given ▁an ▁input ▁( and ▁a ▁teacher ▁value ) ▁is ▁fed ▁into ▁the ▁pseudo - rec urrent ▁network ▁would ▁act ▁as ▁follows : ▁ ▁When ▁a ▁pattern ▁is ▁fed ▁from ▁the ▁environment ▁( a ▁real ▁input ), ▁the ▁information ▁travel s ▁both ▁to ▁the ▁early ▁processing ▁area ▁and ▁the ▁final ▁storage ▁area , ▁however ▁the ▁teacher ▁nodes ▁will ▁in hib it ▁the ▁output ▁from ▁the