Abstract
A computational architecture modeling the relation between perception and action is proposed. Basic brain processes representing synaptic plasticity are first abstracted through asynchronous communication protocols and implemented as virtual microcircuits. These are used in turn to build mesoscale circuits embodying parallel cognitive processes. Encoding these circuits into symbolic expressions gives finally rise to neuro-inspired programs that are compiled into pseudo-code to be interpreted by a virtual machine. Quantitative evaluation measures are given by the modification of synapse weights over time. This approach is illustrated by models of simple forms of behaviors exhibiting cognition up to the third level of animal awareness. As a potential benefit, symbolic models of emergent psychological mechanisms could lead to the discovery of the learning processes involved in the development of cognition. The executable specifications of an experimental platform allowing for the reproduction of simulated experiments are given in “Appendix”.
Highlights
Necessity of a multilevel approach to cognitionFrom a functional perspective, the brain can be seen as a kind of computing machine relating input and output in a significant manner defining behaviors
Our overall methodology can be described in the following terms: (a) mesoscale circuits must be first induced from observed behaviors in comparative zoology (b) these mesoscale circuits are compiled into virtual code to be interpreted by a virtual machine running on top of microcircuits implementing synaptic plasticity (or more precisely, by a virtual machine executing virtual code designed to implement synaptic plasticity (c) by definition, such a virtual machine constitutes an interface which allows for defining mesoscale circuits independently of the way the underlying layers i.e., the microcircuits, are implemented
The concept of a virtual machine that we use here allows for interpreting virtual object code L compiled from source code S, as in the case of the Java virtual machine interpreting Java byte code obtained from the compilation of Java source code
Summary
Necessity of a multilevel approach to cognitionFrom a functional perspective, the brain can be seen as a kind of computing machine relating input and output in a significant manner defining behaviors. Enough, the usual way to simulate a brain today still follows pioneering work dating back from about the same time i.e., that of McCulloch and Pitts (1943) defining finitestate automata that implement a threshold logic, Hodgkin and Huxley (1952) using differential equations to simulate the electrical processes surrounding neurons, and Rall (1964) taking into account the dendritic trees to define neuronal input–output relations. In these approaches, the brain is considered solely as a physical substrate. To the way algorithms running on a computer do represent computation, one may ask: could symbolic programs intended to represent cognition be implemented on top of a simulated brain substrate?
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
