cal ing ▁A ▁neural ▁network ▁that ▁under go es ▁pl astic ▁changes ▁between ▁syn aps es ▁must ▁initi ate ▁normal ization ▁mechan isms ▁in ▁order ▁to ▁combat ▁un rest rained ▁pot enti ation ▁or ▁de pression . ▁One ▁mechanism ▁ass ures ▁that ▁the ▁average ▁firing ▁rate ▁of ▁these ▁neur ons ▁is ▁kept ▁at ▁a ▁reasonable ▁rate ▁through ▁syn apt ic ▁scaling . ▁In ▁this ▁process , ▁input ▁levels ▁are ▁changed ▁in ▁cells ▁to ▁maintain ▁average ▁firing ▁rate . ▁For ▁example , ▁in hib itory ▁syn aps es ▁are ▁strength ened ▁or ▁exc itat ory ▁syn aps es ▁are ▁weak ened ▁to ▁normal ize ▁the ▁neural ▁network ▁and ▁allow ▁single ▁neur ons ▁to ▁reg ulate ▁their ▁firing ▁rate . ▁Another ▁mechanism ▁is ▁the ▁cell - wide ▁red ist ribution ▁of ▁syn apt ic ▁weight . ▁This ▁mechanism ▁conser ves ▁the ▁total ▁syn apt ic ▁weight ▁across ▁the ▁cell ▁by ▁introdu cing ▁competition ▁between ▁syn aps es . ▁Thus , ▁normal izing ▁a ▁single ▁neur on ▁after ▁pl astic ity . ▁During ▁development , ▁cells ▁can ▁be ▁ref ined ▁when ▁some ▁syn aps es ▁are ▁preserved ▁and ▁others ▁are ▁disc arded ▁to ▁normal ize ▁total ▁syn apt ic ▁weight . ▁In ▁this ▁way , ▁home ost asis ▁is ▁conser ved ▁in ▁cells ▁that ▁are ▁under going ▁pl astic ity ▁and ▁normal ▁operation ▁of ▁learning ▁networks ▁is ▁also ▁preserved , ▁allowing ▁new ▁information ▁to ▁be ▁learned . ▁ ▁References ▁ ▁Category : Memory ▁processes ▁Category : Ne uro pl astic ity ▁Category : Ne uro log