### The Computational Limits to the Cognitive Power of
the Neuroidal Tabula Rasa

**Author: Jirí Wiedermann**.

**Source: ***Lecture Notes in Artificial Intelligence* Vol. 1720,
1999, 63 - 76.

**Abstract.**
The neuroidal tabula rasa (NTR) as a hypothetical device which is capable of
performing tasks related to cognitive processes in the brain was introduced
by L.G. Valiant in 1994. Neuroidal nets represent a computational model of
the NTR. Their basic computational element is a kind of a programmable neuron
called neuroid. Essentially it is a combination of a standard threshold
element with a mechanism that allows modification of the neuroid's computational
behaviour. This is done by changing its state and the settings of its weights
and of threshold in the course of computation. The computational power of an
NTR crucially depends both on the functional properties of the underlying update
mechanism that allows changing of neuroidal parameters and on the universe of
allowable weights. We will define instances of neuroids for which the
computational power of the respective finite-size
NTR ranges from that of finite automata, through Turing machines, upto that of a
certain restricted type of BSS machines that possess super-Turing computational
power. The latter two results are surprising since similar results were
known to hold only for certain kinds of analog neural networks.

©Copyright 1999 Springer-Verlag