A Large-Scale Model of the Functioning Brain

Modeling the Brain Neurons are pretty complicated cells. They display an endless variety of shapes that sprout highly variable numbers of axons and dendrites; they sport time- and voltage-dependent ion channels along with an impressive array of neurotransmitter receptors; and they connect intimately with near neighbors as well as former neighbors who have since moved away. Simulating a sizeable chunk of brain tissue has recently become achievable, thanks to advances in computer hardware and software. Eliasmith et al. (p. 1202; see the Perspective by Machens) present their million-neuron model of the brain and show that it can recognize numerals, remember lists of digits, and write down those lists—tasks that seem effortless for a human but that encompass the triad of perception, cognition, and behavior. Two-and-a-half million model neurons recognize images, learn via reinforcement, and display fluid intelligence. A central challenge for cognitive and systems neuroscience is to relate the incredibly complex behavior of animals to the equally complex activity of their brains. Recently described, large-scale neural models have not bridged this gap between neural activity and biological function. In this work, we present a 2.5-million-neuron model of the brain (called “Spaun”) that bridges this gap by exhibiting many different behaviors. The model is presented only with visual image sequences, and it draws all of its responses with a physically modeled arm. Although simplified, the model captures many aspects of neuroanatomy, neurophysiology, and psychological behavior, which we demonstrate via eight diverse tasks.