The man had a normal job and is a married father of two children.
Lionel Feuillet, Henry Dufour and Jean Pelletier. Brain of a white-collar worker. The Lancet, Volume 370, Issue 9583, 21 July 2007-27 July 2007, Page 262.
A patient who had been in a “minimally conscious state” for six years regained responsiveness after stimulation via electrodes implanted in the thalamus. Now he can “name objects on request, make precise hand gestures, and chew food without the aid of a feeding tube”.
This study provides fMRI evidence that, after forgetting some memories, the brain has to work less hard.
This isn’t news but is rather an interesting thing I learned today. There is a family with an inherited form of frontotemporal dementia. In this family, the onset of dementia occurred between 57-63 years of age. A study was done which did psychological tests on members of this family. It was found that young people (younger than 35) who carried the gene for the disorder had measurable frontal-executive dysfunction (whereas controls, young people in the same family who did not carry the gene, did not have dysfunction).
A set of 6 subjects with bilateral damage to the ventromedial prefrontal cortex (VMPC) answered ethical questions in a way more consistent with utilitarian ethical philosophy than the control subjects. For example, they would be more willing to kill someone by pushing them off a bridge if that would save 5 other people. This supports the view that social emotions underly ethical judgments.
Michael Koenigs, Liane Young, Ralph Adolphs, Daniel Tranel, Fiery Cushman, Marc Hauser and Antonio Damasio.Damage to the prefrontal cortex increases utilitarian moral judgements. Nature. Published online 21 March 2007
Entrepreneur-turned-cognitive neuroscientist Jeff Hawkins is distributing a “research release” of their experimental code base implementing his idea of hierarchical temporal memory described in his book, “On Intelligence”. Hawkins drew inspiration for the model from his own reading about the structure and function of the human neocortex and believes that it represents the foundation for developing intelligent machines.
Jeff explains this surprising move to open source the code for the Numenta Platform for Intelligent Computing (NuPIC) on the Numenta web site:
Why are we making NuPIC available now?
We have been contacted by dozens of researchers and scientists who are excited about HTM and by our work at Numenta. These people are anxious to work on HTM, are willing to be pioneers, and are willing to accept the uncertainty associated with a new technology. We are making our tools available so that these sophisticated developers can start building a community around HTM technology. NuPIC has been under development for 18 months, is pretty solid, and is well documented – including several examples to make it easy to get started – so we’re ready to open up to more developers, even while knowing that we do not yet have benchmarking data, and we cannot make guarantees about applicability to specific problems.
Here’s why Hawkins thinks that HTMs are new.
We have been covering Hawkins’ work for a while now. See these previous posts for more background info.
Neurodudes is actively soliciting code reviews of the newly released software. Is NuPIC the next big thing, or are you left feeling cold? Post your thoughts yourself using the instructions on the right-hand column, or let us know at contactus -AT- neurodudes.com!
In September, 2006, I described my “new brain/mind theory” here and received some challenging criticism from Eric Thomson and Mike S. (see below). To meet these challenges, I prepared a reduced model discussed in a web page linked to a paper in .pdf form. Since my approach is based on little-known thermodynamics, I have also written about mechanical metaphors that may be helpful in explaining my ideas.
HOW DOES THE BRAIN CONTROL BEHAVIOR?
HOW CAN TECHNOLOGY EMULATE BIOLOGICAL INTELLIGENCE?
The conference is aimed at researchers and students of computational neuroscience, cognitive science, neural networks, neuromorphic engineering, and artificial intelligence. It includes invited lectures and contributed lectures and posters by experts on the biology and technology of how the brain and other intelligent systems adapt to a changing world. The conference is particularly interested in exploring how the brain and biologically-inspired algorithms and systems in engineering and technology can learn. Single-track oral and poster sessions enable all presented work to be highly visible. Three-hour poster sessions with no conflicting events will be held on two of the conference days. Posters will be up all day, and can also be viewed during breaks in the talk schedule.
ELEVENTH INTERNATIONAL CONFERENCE
ON COGNITIVE AND NEURAL SYSTEMS
May 16 – 19, 2007
Boston University
677 Beacon Street
Boston, Massachusetts 02215 USA
http://www.cns.bu.edu/meetings/
Sponsored by the Boston University
Center for Adaptive Systems and
Department of Cognitive and Neural Systems (http://www.cns.bu.edu/)
with financial support from the National Science Foundation (http://cns.bu.edu/CELEST/)
Is science just about facts, or are theories and conceptualizations important too? Should we worry about having good theories, or do the facts pretty much give us everything we need to know. This article, entitled “Facts, concepts, and theories: The shape of psychology’s epistemic triangle“, discusses this issue for the field of Psychology, though its contents are also applicable to Neuroscience and AI.
The October 6th issue of Science is a special issue devoted to computational neuroscience. From the introduction to the special issue:
Computational neuroscience is now a mature field of research. In areas ranging from molecules to the highest brain functions, scientists use mathematical models and computer simulations to study and predict the behavior of the nervous system. Simulations are essential because the present experimental systems are too complex to allow collection of all the data. Modeling has become so powerful these days that there is no longer a one-way flow of scientific information. There is considerable intellectual exchange between modelers and experimentalists. The results produced in the simulation lab often lead to testable predictions and thus challenge other researchers to design new experiments or reanalyze their data as they try to confirm or falsify the hypotheses put forward. For this issue of Science, we invited leading computational neuroscientists, each of whom works at a different organizational level, to review the latest attempts of mathematical and computational modeling and to give us an outlook on what the future might hold in store.
Of particular interest is a review article by Randall O’Reilly on biologically based computational models. He focuses on models of the pre-frontal cortex.