contributed;articles

Doi: 10.1145/1831407.1831425

metaphor for the central mystery of how the brain produces intelligent behavior and intelligence itself. They also provide experimental tools for information processing, effectively testing theories of the brain, particularly those involving aspects of intelligence (such as sensory perception). The contribution of computer science to neuroscience happens at multiple levels and is well recognized. Perhaps less obvious is that neuroscience is beginning to contribute powerful new ideas and approaches to artificial intelligence and computer science as well. Modern computational neuroscience models are no longer toy models but quantitatively detailed while beginning to compete with state-of-the-art computer-vision systems. Here, we explore how computational neuroscience could become a major source of new ideas and approaches in artificial intelligence.

Understanding the processing of information in our cortex is a significant part of understanding how the brain works and understanding intelligence itself. For example, vision is one of our most developed senses. Primates easily categorize images or parts of images, as in, say, an office scene or a face within a scene, identifying specific objects. Our visual capabilities are exceptional, and, despite decades of engineering, no computer algorithm is yet able to match the performance of the primate visual system.

Our visual cortex may serve as a proxy for the rest of the cortex and thus

BY thomaS SeRRe anD tomaSo PoGGio a neuromorphic approach to computer Vision

Neuroscience is beginning to inspire a new generation of seeing machines.

iF Ph YSicS wAS the science of the first half of the 20th century, biology was certainly the science of the second half. Neuroscience is now often cited as one of the key scientific focuses of the 21st century and has indeed grown rapidly in recent years, spanning a range of approaches, from molecular neurobiology to neuro-informatics and computational neuroscience. Computer science gave biology powerful new data-analysis tools that yielded bioinformatics and genomics, making possible the sequencing of the human genome. Similarly, computer science techniques are at the heart of brain imaging and other branches of neuroscience.

Computers are critical for the neurosciences, though at a much deeper level, representing the best

key insights

;;; the past century of neuroscience research has begun to answer fundamental questions ranging from the intricate inner workings of individual neurons to understanding the collective behavior of networks of millions of neurons.

;;; a key challenge for the visual cortex is how to deal with the poverty-of-stimulus problem.

;;; a major goal of the visual system is how to adapt to the statistics of its natural environment through visual experience and even evolution.