Recognition and inhibition of dorsal horn nociceptive signals within a closed-loop system

We implemented an integrated system that can acquire neuronal signals from spinal cord dorsal horn neurons, wirelessly transmit the signals to a computer, and recognize the nociceptive signals from three different mechanical stimuli (brush, pressure and pinch). Positive peak detection method was chosen to distinguish between signal spikes. The inter spike intervals (ISIs) were calculated from the identified action potentials (APs) and fed into a numerical array called cluster. When the sum of the ISIs in the cluster reached a critical level, the program recognized the recorded signals as nociceptive inputs. The user has the flexibility to tune both the cluster size and critical threshold for individual´s need to reach optimization in pain signal recognition. The program was integrated with a wireless neurostimulator to form a feedback loop to recognize and inhibit nociceptive signals.