The　development　of　brain-inspired　neural　network　computing　synaptic　devices　based　on　organic　field-effect　transistors　(OFETs)　represents　a　pivotal　research　frontier　in　neuromorphic　computing　and　flexible　electronics.　These　devices　elucidate　fundamental　mechanistic　parallels　between　biological　neural　networks　and　artificial　systems,　facilitating　the　paradigm　shift　in　organic　electronics　from　passive　＂sensing＂　to　active　＂cognition＂.　This　technological　evolution　enables　loop　perception-computation-decision　architectures　while　unlocking　transformative　opportunities　in　intelligent　hardware　and　medical　technologies.　Such　pioneering　advancements　are　poised　to　redefine　the　global　semiconductor　industry　landscape　by　bridging　neuromorphic　engineering　with　next-generation　bioelectronic　applications,　ultimately　driving　the　convergence　of　adaptive　learning　systems　and　human-machine　symbiotic　interfaces.　A　low-voltage　(1　V)　C8-BTBT　optoelectronic　synaptic　array　(coefficient　of　variation　in　synaptic　weight　modulation:　8%)　emulated　human　visual　information　processing　under　distinct　cognitive　states:　dispersed-attention　mode　achieved　rapid　response　and　short-term　plasticity,　while　focused-attention　mode　enabled　noise　suppression　and　long-term　potentiation　via　carrier　trapping　modulation.　This　platform　advances　hardware-level　perception-computation　integration　for　biomimetic　vision　chips.