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Memristor-based analogue computing for brain-inspired sound localization with in situ training.

ABSTRACT: The human nervous system senses the physical world in an analogue but efficient way. As a crucial ability of the human brain, sound localization is a representative analogue computing task and often employed in virtual auditory systems. Different from well-demonstrated classification applications, all output neurons in localization tasks contribute to the predicted direction, introducing much higher challenges for hardware demonstration with memristor arrays. In this work, with the proposed multi-threshold-update scheme, we experimentally demonstrate the in-situ learning ability of the sound localization function in a 1K analogue memristor array. The experimental and evaluation results reveal that the scheme improves the training accuracy by ∼45.7% compared to the existing method and reduces the energy consumption by ∼184× relative to the previous work. This work represents a significant advance towards memristor-based auditory localization system with low energy consumption and high performance.

SUBMITTER: Gao B

PROVIDER: S-EPMC9018844 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Memristor-based analogue computing for brain-inspired sound localization with in situ training.

Gao Bin B Zhou Ying Y Zhang Qingtian Q Zhang Shuanglin S Yao Peng P Xi Yue Y Liu Qi Q Zhao Meiran M Zhang Wenqiang W Liu Zhengwu Z Li Xinyi X Tang Jianshi J Qian He H Wu Huaqiang H

Nature communications 20220419 1

The human nervous system senses the physical world in an analogue but efficient way. As a crucial ability of the human brain, sound localization is a representative analogue computing task and often employed in virtual auditory systems. Different from well-demonstrated classification applications, all output neurons in localization tasks contribute to the predicted direction, introducing much higher challenges for hardware demonstration with memristor arrays. In this work, with the proposed mult ...[more]

PMID: 35440127

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Project description:Sound localization requires the integration in the brain of auditory spatial cues generated by interactions with the external ears, head and body. Perceptual learning studies have shown that the relative weighting of these cues can change in a context-dependent fashion if their relative reliability is altered. One factor that may influence this process is vision, which tends to dominate localization judgments when both modalities are present and induces a recalibration of auditory space if they become misaligned. It is not known, however, whether vision can alter the weighting of individual auditory localization cues. Using virtual acoustic space stimuli, we measured changes in subjects' sound localization biases and binaural localization cue weights after ?50 min of training on audiovisual tasks in which visual stimuli were either informative or not about the location of broadband sounds. Four different spatial configurations were used in which we varied the relative reliability of the binaural cues: interaural time differences (ITDs) and frequency-dependent interaural level differences (ILDs). In most subjects and experiments, ILDs were weighted more highly than ITDs before training. When visual cues were spatially uninformative, some subjects showed a reduction in auditory localization bias and the relative weighting of ILDs increased after training with congruent binaural cues. ILDs were also upweighted if they were paired with spatially-congruent visual cues, and the largest group-level improvements in sound localization accuracy occurred when both binaural cues were matched to visual stimuli. These data suggest that binaural cue reweighting reflects baseline differences in the relative weights of ILDs and ITDs, but is also shaped by the availability of congruent visual stimuli. Training subjects with consistently misaligned binaural and visual cues produced the ventriloquism aftereffect, i.e., a corresponding shift in auditory localization bias, without affecting the inter-subject variability in sound localization judgments or their binaural cue weights. Our results show that the relative weighting of different auditory localization cues can be changed by training in ways that depend on their reliability as well as the availability of visual spatial information, with the largest improvements in sound localization likely to result from training with fully congruent audiovisual information.

Dataset Information

Memristor-based analogue computing for brain-inspired sound localization with in situ training.

Publications

Memristor-based analogue computing for brain-inspired sound localization with in situ training.

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