{'fraction_non_alphanumeric': 0.01726263871763255, 'fraction_numerical': 0.0, 'mean_word_length': 5.194656488549619, '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}}
An interpretation of cortical maps in echolocating bats.

Target parameters such as reflectivity, range, velocity, and angular position are represented by ordered maps of tuned cortical neurons in insectivorous bats. It is suggested that the response of each neuron in such a map is determined by a hypothesis test conditioned on a particular value of the mapped parameter. The excitation of each neuron is then interpreted as a sample value of a conditional log-likelihood ratio or a log-likelihood function. Interpolation between the samples, which is needed to find the parameter that maximizes the mapped function (e.g., the maximum likelihood parameter estimate), can be accomplished with overlapped tuning curves. An attempt to portray a sharp peak by a weighted sum of relatively broad neuronal tuning curves or interpolation functions results in excitatory center/inhibitory surround behavior. Facilitation or antifacilitation of neurons that are likely to be excited by succeeding observations can be used for sequential detection and tracking. Interpolation and pulse-to-pulse data storage capability are required to explain range jitter sensitivity and to allow for moving target indication in bat sonar. If a cortical map represents an ordered array of hypothesis tests, then many such tests are implemented in parallel when target parameters are unknown. Detection performance is then degraded relative to the idealized situation in which all parameters are specified. Performance in noise may thus appear to be much worse than that of an ideal detector, even if each hypothesis test is optimally implemented.