This paper presents the in vivo performances of a resource-optimized digital action potential (AP) detector featuring an adaptive threshold based on a new Sigma-delta control loop. The proposed AP detector is optimized for utilizing low hardware resources, which makes it suitable for real-time implementation on most common low-power microcontroller units (MCC). The adaptive threshold is calculated using a digital control loop based on a Sigma-delta modulator that precisely estimates the standard deviation of the neuronal signal amplitude. The detector was demonstrated using a common MCC from MSP430 family, incorporated into a small wireless platform for combined optogenetics and neural recording. The system has been fully characterized experimentally within in vivo experiments on a freely-moving transgenic mouse expressing ChannelRhodospin (Thyl::ChR2-YFP line4). The results demonstrate that the proposed AP detector can be used to achieve overall data reduction ratios above 11 when transmitting only the detected APs. A comparison of the obtained results with other thresholding approaches shows that the proposed detector provides similar performances to those significantly more resource demanding approaches.