{'fraction_non_alphanumeric': 0.04229390681003584, 'fraction_numerical': 0.016487455197132617, 'mean_word_length': 4.965811965811966, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Selective recording of the canine hypoglossal nerve using a multicontact flat interface nerve electrode

A flat-interface nerve electrode (FINE) is presented as a potential solution for using multifascicle nerve recordings as part of a closed-loop control system. To investigate the ability of this electrode to achieve selective recordings at physiological signal-to-noise ratio (SNR), a finite-element model (FEM) of a beagle hypoglossal nerve with an implanted FINE was constructed. Action potentials (AP) were generated at various SNR levels and the performance of the electrode was assessed with a selectivity index (0/spl les/SI/spl les/1; ability of the electrode to distinguish two active sources). Computer simulations yielded a selective range (0.05/spl les/SI/spl les/0.76) that was 1) related to the interfiber distance and 2) used to predict the minimum interfiber distance (0.23 mm/spl les/d/spl les/1.42 mm) for selective recording at each SNR. The SI was further evaluated using recorded compound APs elicited from electrically activating the branches of the beagle hypoglossal nerve. For all experiments (n=7), the selectivity (SI=0.45/spl plusmn/0.16) was within the range predicted by the FEM. This study suggests that the FINE can record the activity from a multifasciculated nerve and, more importantly, distinguish neural signals from pairs of fascicles at physiologic SNR.