Learning spatial hearing via innate mechanisms
Fig 4
Effects of cue disruptions and re-calibration mechanisms.
Response of the Teacher circuit (top row) and DNN Student (middle row without bootstrapping; bottom row with bootstrapping). The left column shows the original ILD response curve of the Teacher (top) and the good performance of the Student (bottom) before any acoustic cues are disrupted. The three right columns show the effects after three different types of disruptions to the acoustic cues. A symmetrical shift (left column, symmetrical bilateral hearing loss) leaves the ILD sensitivity curves (top row) of the Teacher unchanged. A symmetrical scaling (middle column, symmetrical bilateral auditory compression disruption) stretches the response curve along the ILD axis but doesn’t change the bias (preference for left/right). An asymmetrical scaling (right column, asymmetrical unilateral hearing loss), changes the bias of the LSO curve, although this can be restored with two labeled data points (green curve). In contrast, the DNN Student is much more sensitive to any disruptions in acoustic cues. The Student prediction is initially disrupted with high errors (middle row), but after recalibration (relearning using the Teacher) good performance is restored for the symmetrical disruptions (which do not change the bias). In the case of the asymmetrical disruption (right column), performance is restored after recalibration of the Teacher (green curve, bottom row).