While Artificial Neural Networks have reached once unimaginable levels of performance, it is also broadly recognized that they lag far behind biological brains in important aspects (besides biological plausibility), such as interpretability and adaptability to new tasks as well as power and data usage. During the past two decades, the study of the animal brain has also progressed tremendously through powerful recording techniques and interpretation methodology --- in recent years assisted greatly by machine learning. However, this progress has not brought us closer to answering this field's own overarching interpretability question: how exactly does the activity of neurons and synapses result in high-level cognitive functions, especially in the human brain?
The Assembly Calculus (AC) is a novel framework intended to bridge the gap between the level of neuron and synapses, and that of cognition. AC is a computational system entailing a basic data item called an assembly, a stable set of neurons explained below; a set of operations that create and manipulate assemblies; and an execution model squarely based on basic tenets of neuroscience. Importantly, it allows the creation of biologically plausible, flexible and interpretable programs, enabling one to develop tangible hypotheses on how specific brain functions may work. To facilitate such experimentation, we present here a tool which in real-time allows the simulation, modification and visualization of this computational system, including several prepared examples.
Our tool is a web application which greatly aids in the creation and analysis of algorithms within the assembly calculus by allowing the user to both visualize neurons and their connections and also present a simple interface to dynamically modify and run code on assemblies. The interface can be accessed here: http://brain.cc.gatech.edu