Following up on MC's posts about the significant insights in the history of neuroscience, I'll now take Neurevolution for a short jaunt into neuroscience's potential future. In light of recent advances in technologies and methodologies applicable to neuroscience research, the National Science Foundation last summer released a document on the "Grand Challenges of Neuroscience". These …
Monthly Archives: April 2007
History’s Top Insights Into Brain Computation
This post is the culmination of a month-long chronicling of the major brain computation insights of all time. Some important insights were certainly left out, so feel free to add comments with your favorites. Below you will find all 26 insights listed with links to their entries. At the end is the summary of the …
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History’s Top Brain Computation Insights: Day 26
26) Some complex object categories, such as faces, have dedicated areas of cortex for processing them, but are also represented in a distributed fashion (Kanwisher – 1997, Haxby – 2001) Early in her career Nancy Kanwisher used functional MRI (fMRI) to seek modules for perceptual and semantic processing. She was fortunate enough to discover what …
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History’s Top Brain Computation Insights: Day 25
25) The dopamine system implements a reward prediction error algorithm (Schultz – 1996, Sutton – 1988) It used to be that the main thing anyone "knew" about the dopamine system was that it is important for motor control. Parkinson's disease, which visibly manifests itself as motor tremors, is caused by disruption of the dopamine …
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Fair Use and Legal Intimidation in Science
Shelley Batts’s Retrospectacle neuroscience blog recently got hit with a legal threat from journal publisher Wiley for posting some graphs from a recently published article. This request amounts to underhanded legal intimidation as using these graphs clearly falls under fair use. Shelley had clearly cited the source of the graph and accurately reported the results. …
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History’s Top Brain Computation Insights: Day 24
24) Cognitive control processes are distributed within a network of distinct regions (Goldman-Rakic – 1988, Posner – 1990, Wager & Smith 2004, Cole & Schneider – 2007) Researchers investigating eye movements and attention recorded from different parts of the primate brain and found several regions showing very similar neural activity. Goldman-Rakic proposed the existence of …
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History’s Top Brain Computation Insights: Day 23
23) Motor cortex is organized by movement direction (Schwartz & Georgopoulos – 1986, Schwartz – 2001) Penfield had shown that motor cortex is organized in a somatotopic map. However, it was unclear how individual neurons are organized. What does each neuron’s activity represent? The final location of a movement, or the direction of that movement? …
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History’s Top Brain Computation Insights: Day 22
22) Recurrent connectivity in neural networks can elicit learning and reproduction of temporal sequences (Jordan – 1986, Elman – 1990, Schneider – 1991) Powerful learning algorithms such as Hebbian learning, self-organizing maps, and backpropagation of error illustrated how categorization and stimulus-response mapping might be learned in the brain. However, it remained unclear how sequences and …
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History’s Top Brain Computation Insights: Day 21
21) Parallel and distributed processing across many neuron-like units can lead to complex behaviors (Rumelhart & McClelland – 1986, O'Reilly – 1996) Pitts & McCullochprovided amazing insight into how brain computations take place. However, their two-layer perceptrons were limited. For instance, they could not implement the logic gate XOR (i.e., 'one but not both'). An …
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History’s Top Brain Computation Insights: Day 20
20) Spike-timing dependent plasticity: Getting the brain from correlation to causation (Levy – 1983, Sakmann – 1994, Bi & Poo – 1998, Dan – 2002) Hebb's original proposal was worded as such: "When an axon of cell A is near enough to excite a cell B and repeatedly or persistently takes part in firing it, …
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History’s Top Brain Computation Insights: Day 19
19) Neural networks can self-organize via competition (Grossberg – 1978, Kohonen – 1981) Hubel and Wiesel's work with the development of cortical columns (see previous post) hinted at it, but it wasn't until Grossberg and Kohonen built computational architectures explicitly exploring competition that its importance was made clear. Grossberg was the first to illustrate the …
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History’s Top Brain Computation Insights: Day 18
18) Behavior exists on a continuum between controlled and automatic processing (Schneider & Shiffrin – 1977) During the 1970s those studying the cognitive computations underlying visual search were at an impasse. One group of researchers claimed that visual search was a flat search function (i.e., adding more distracters doesn't increase search time), while another group …
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History’s Top Brain Computation Insights: Day 17
17) Reverbatory activity in lateral prefrontal cortex maintains memories and attention over short periods (Fuster – 1971, Jacobsen – 1936, Goldman-Rakic – 2000) Patient H.M., with his lack of long term memory but largely intact working (short-term) memory, illustrated a dissociation between these two forms of memory. While long-term memory seemed to rely on hippocampus …
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History’s Top Brain Computation Insights: Day 16
16) Critical periods of cortical development via competition (Hubel & Wiesel – 1970) Hubel & Wiesel showed that the ocular dominance columns they had discovered in cortex (see previous post) are organized during a critical period of development. Keeping one eye of an animal shut during the first few months of life made that animal …
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History’s Top Brain Computation Insights: Day 15
15) Consciousness depends on cortical communication; the cortical hemispheres are functionally specialized (Sperry & Gazzaniga – 1969) It is quite difficult to localize the epileptic origin in some seizure patients. Rather than removing the gray matter of origin, neurosurgeons sometimes remove white matter to restrict the seizure to one part of the brain. One particularly …
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