Stability,　the　ability　to　automatically　extract　and　produce　the　efficient　and　accurate　results　of　a　defined　problem　without　making　epistemic　assumptions,　is　discussed　here　as　a　possible　memory　system　for　understanding　complex　cognitive　functions　of　the　arithmetical　learning.　Stability　is　of　top　priority　because　it　may　typify　organization　of　granule　(knowledge-based　information　unit)　structure.　Memory　efficiencies　are　that　they　depend　on　both　linguistic　factors　and　exposure　to　arithmetic　training　during　granule　formation　or　consolidation,　supporting　the　idea　of　analog　coding　of　numerical　representations.　Neuroimaging　studies　suggest　that　the　parietal　lobe　as　a　potential　substrate　for　a　domain-specific　representation　of　numeric　quantities　and　associative　memory　mechanisms　in　stability,　and　results　from　these　studies　indicate　that　there　may　be　the　organization　of　number-related　processes　of　stability　in　the　parietal　lobe.　Stability　seems　to　depend　on　the　automatic　information-processing　system＇s　response　to　experiential　knowledge　combining　granularity　(degree　of　detail　or　precision),　maturational　constraints,　spatial　factors　(mental　number　line)　and　linguistic　factors,　making　it　an　ideal　candidate　for　understanding　how　these　interactions　play　out　in　the　cognitive　arithmetic　system.　©　(2014)　Trans　Tech　Publications,　Switzerland.