In 1994, Powers presented to the first European workshop on PCT a design for what he called an “Artificial Cerebellum” (AC) that could serve as an Output Function for any control loop at any level of the hierarchy (available at http://www.pctweb.org/Powers_cerebellum.pdf. It did not matter whether the AC was usd at a peripheral perceptual control level or at the very highest (cognitive?) level. The AC compensated for the spectral characteristics of the entire control loop, thereby both speeding the output when the loop characteristic was not flat, and therefore producing a certain amount of predictability, improving control whether of actin in the evironment or imaginative thought (though Powers was not so explicit in its range of usefulness).
A few days ago I ran across a paper published 20 years later in 2014 entitled “The cerebellum for jocks and nerds alike” at https://www.frontiersin.org/articles/10.3389/fnsys.2014.00113/full. Here’s the abstract, which I think sounds as though it coud have been an abstract for Powrs’ AC presentation, apart from discussing nural spikes instea of neural current.
Historically the cerebellum has been implicated in the control of movement. However, the cerebellum’s role in non-motor functions, including cognitive and emotional processes, has also received increasing attention. Starting from the premise that the uniform architecture of the cerebellum underlies a common mode of information processing, this review examines recent electrophysiological findings on the motor signals encoded in the cerebellar cortex and then relates these signals to observations in the non-motor domain. Simple spike firing of individual Purkinje cells encodes performance errors, both predicting upcoming errors as well as providing feedback about those errors. Further, this dual temporal encoding of prediction and feedback involves a change in the sign of the simple spike modulation. Therefore, Purkinje cell simple spike firing both predicts and responds to feedback about a specific parameter, consistent with computing sensory prediction errors in which the predictions about the consequences of a motor command are compared with the feedback resulting from the motor command execution. These new findings are in contrast with the historical view that complex spikes encode errors. Evaluation of the kinematic coding in the simple spike discharge shows the same dual temporal encoding, suggesting this is a common mode of signal processing in the cerebellar cortex. Decoding analyses show the considerable accuracy of the predictions provided by Purkinje cells across a range of times. Further, individual Purkinje cells encode linearly and independently a multitude of signals, both kinematic and performance errors. Therefore, the cerebellar cortex’s capacity to make associations across different sensory, motor and non-motor signals is large. The results from studying how Purkinje cells encode movement signals suggest that the cerebellar cortex circuitry can support associative learning, sequencing, working memory, and forward internal models in non-motor domains.