The　development　of　optoelectronics　mimicking　the　functions　of　the　biological　nervous　system　is　important　to　artificial　intelligence.　This　work　demonstrates　an　optoelectronic,　artificial,　afferent-nerve　strategy　based　on　memory-electroluminescence　spikes,　which　can　realize　multiple　action-potentials　combination　through　a　single　optical　channel.　The　memory-electroluminescence　spikes　have　diverse　morphologies　due　to　their　history-dependent　characteristics　and　can　be　used　to　encode　distributed　sensor　signals.　As　the　key　to　successful　functioning　of　the　optoelectronic,　artificial　afferent　nerve,　a　driving　mode　for　light-emitting　diodes,　namely,　the　non-carrier　injection　mode,　is　proposed,　allowing　it　to　drive　nanoscale　light-emitting　diodes　to　generate　a　memory-electroluminescence　spikes　that　has　multiple　sub-peaks.　Moreover,　multiplexing　of　the　spikes　can　be　obtained　by　using　optical　signals　with　different　wavelengths,　allowing　for　a　large　signal　bandwidth,　and　the　multiple　action-potentials　transmission　process　in　afferent　nerves　can　be　demonstrated.　Finally,　sensor-position　recognition　with　the　bio-inspired　afferent　nerve　is　developed　and　shown　to　have　a　high　recognition　accuracy　of　98.88%.　This　work　demonstrates　a　strategy　for　mimicking　biological　afferent　nerves　and　offers　insights　into　the　construction　of　artificial　perception　systems.　In　this　work,　a　nanoscale　light-emitting　diode　with　memory-electroluminescence　is　demonstrated,　which　is　used　for　mimicking　the　generation　of　multiple　action-potentials　and　their　combinations　in　bio-inspired　afferent　nerves.