344

24

The Nervous System

24.4

Neurocomputation

Microelectrodes have long been used to investigate brain tissues. ¹⁰ Following

the famous demonstration of the interfacing of living neurons with conventional

semiconductor-based electronic circuits, ¹¹ it was hoped that vast computing power

could be unleashed by artificial networks of living neurons, artificial in the sense that

their connexions would be specified by a human circuit designer. ¹² Despite progress,

the trend in neural computation is to work with mathematical models run on com-

puters, with practical interest in such areas as natural language processing, image

recognition, robotics and healthcare. Significant developments in deep learning are

convolutional neural networks (CNNs) and recurrent neural networks (RNNs). CNNs

are specifically designed to process data represented by a grid-like structure (e.g.,

images). Features are extracted using a series of filters, and the features are then

used to detect or classify objects in the image. In contrast, RNNs are designed for

processing sequential data, such as time series (e.g., audio or video), or text.

Problem. Program a general purpose computer to act as a neural network for iden-

tifying objects according to their essential attributes.

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10 See, e.g., Jánossy et al. (1990); Jánossy et al. (1991); Obien et al. (2015).

11 Zeck and Fromherz (2001).

12 See Suzuki et al. (2004) and Forró Cs et al. (2018) for a flavour of this endeavour.