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.