One　of　the　key　ideas　in　realizing　human-like　intelligence　is　to　understand　information-processing　mechanisms　in　the　human　brain.　Brain　Informatics　is　a　rapidly　expanding　interdisciplinary　field　to　systematically　utilize　brain-related　data,　information　and　knowledge　coming　from　the　entire　research　process　for　in-depth　brain　investigation.　In　the　past　few　years,　a　data-centric　conceptual　brain　model,　namely　Data-Brain,　has　been　proposed,　providing　the　foundation　for　the　systematic　Brain　Informatics　methodology.　The　Data-Brain　model　constitutes　a　conceptual　framework　and　detailed　guideline　for　managing　and　analyzing　brain　big　data.　The　development　of　Data-Brain　model　also　demands　the　support　from　advanced　technologies.　This　paper　presents　an　extensible　version　of　the　Data-Brain　with　advanced　computing　techniques　in　the　connected　world.　It　provides　a　global　understanding　of　how　multidisciplinary　techniques　work　together　to　tackle　brain　computing　challenges.　Particularly,　the　integrated　K-I-D　(Knowledge-Information-Data)　loop　is　proposed,　constructing　a　cycle　as　the　thinking　space　to　help　pursue　the　systematic　brain　investigation,　by　which　the　extensible　Data-Brain　model　continuously　iterates　and　evolves　through　the　never-ending　learning.　Such　synergistic　evolvement　will　power　future　progress　for　building　intelligence　systems　and　applications　connected　with　the　study　of　complex　human　brain.　©　2020　Elsevier　B.V.