Archive for the ‘Interdisciplinary concepts’ Category

Where are we with this whole free will thing?

Wednesday, December 12th, 2007

Haim Sompolinsky has written an excellent book chapter on the scientific view of free will and choice, pulling in good ideas from physics and neuroscience along with contemporary philosophical commentary.

I think this chapter might be helpful for neuroscientists outside of the lab. Often a dinner table discussion has moved to the idea of “quantum consciousness” or “quantum free will”. Often, someone will mention Roger Penrose, who has become something of a poster boy for this idea that quantum indeterminacy (eg. Heisenberg’s uncertainty principle) is one possible way that free will is really free. And then, people look around and say, “Well, you’re a neuroscientist. Do we have free will?” (And that’s when I take another big drink or bite while I figure out something semi-coherent to say.)

Sompolinsky does a nice job of evaluating such claims (in the end, he says we cannot rule out the possibility that the brain is an indeterministic system but it seems unlikely) and provides nice scientific insight. In his view, it is far more likely that the brain’s apparent randomness (eg. individual cell spike rasters vary across repeated presentations of the same stimulus) is more simply explained by thermal noise (think of varying channel gating properties) and chaotic brain dynamics. (Recall, a chaotic system is still deterministic; it simply exhibits aperiodic behavior due to exquisite sensitivity to initial conditions. It is difficult to predict the long-term behavior of chaotic systems. The more we know the initial conditions in detail, the better our prediction.) On the other hand, he argues that the relevant length and time scales for neurons (micrometers and milliseconds) are far larger by many orders of magnitude than those of quantum noise. Chaos might amplify such quantum events, but this is far from being the simplest, most parsimonious explanation. Given the current level of neuroscience understanding, this is almost idle speculation. Regardless of the (in)determinacy of the world, Sompolinsky effectively argues against any non-physical, purely mental (ie. dualistic) agent of causation.

Thus, in sum, the world and our brains might not be determined but, even given that, there’s no reason to believe we have any causative ability to change things in the sense of traditional free will. These observations seem right on the mark to me. I hope they bring some insight for others. Or at least a way to fend off the dinner-table-free-will-conversation barrage of questions.

Determining research trends from Neuroscience abstracts

Wednesday, October 17th, 2007

In this paper at arXiv, Yin et al. report on an analysis of the abstracts from the SfN meetings from 2001 to 2006. It sounds like their analysis uncovered several interesting trends: Two they mention in their abstract are that 60% of authors appear in only one year’s abstracts over the studied period, and that systems neuroscience seems to be on the rise relative to cellular and molecular neuroscience.

-John O’Leary

Age-dependent brainwashing in bees

Monday, July 23rd, 2007

Apparently, when not busy blowing our minds, bees occupy themselves by…

…brainwashing their youth

…and/or mysteriously disappearing from the face of the earth

Keeping an eye on species poised to take over the world,
Davie

Williams syndrome nytimes article

Monday, July 9th, 2007

http://www.nytimes.com/2007/07/08/magazine/08sociability-t.html

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WNYC’s Radio Lab is Back for Season 3

Monday, May 14th, 2007

Read on for a guest-posted ad for WNYC’s radio lab (http://www.radiolab.org)

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More on “Quad Nets” (new brain/mind theory)

Saturday, February 24th, 2007

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.

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So, How Do REAL Neuronal Networks Compute?

Tuesday, February 20th, 2007

What is the right level of biological realism to model neuronal systems in order to understand their computational properties? Some recent papers may help shed some light on the subject. Models of the computational properties of local networks of neurons are starting to come into their own. This year has already seen at least two articles published in experimentalist journals based on the same core of theoretical work.

To bring you up to speed, I need to remind you what is going on in the world of experimental neuroscience.

Experimentalists are now able to record the single-cell activities of a whole population of neurons simultaneously. From Briggman, Abarbanel, Kristan (2006):

By using multi-electrode arrays or optical imaging, investigators can now record from many individual neurons in various parts of nervous systems simultaneously while an animal performs sensory, motor or cognitive tasks. Given the large multidimensional datasets that are now routinely generated, it is often not obvious how to find meaningful results within the data.

This paper goes on to provide a nice overview on mathematical methods that researchers are using to grapple with the challenge of understanding the dynamics of the neural systems they are recording from. They make the case that conceptual progress needs to be made on the interpretation of the data these results yield. How can we understand what computations these neurons are collectively performing?

(Incidentally, this topic is being explored in a conference happening this week at the Los Alamos National Laboratory, which, according to one of the conference session chairs, is intended to help shape future directions for the lab. Hopefully there will be webcasts from this conference.)

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Cognitive and Neural Systems Conference in Boston

Friday, November 17th, 2006

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/)

Help Please: Future of Neural Engineering: From Job perspective

Tuesday, November 14th, 2006

Dear Members,
I am a prospective graduate student interested in taking up Neural Engineering under EE or Biomedical Engg for research. But I have a lot of concerns and need help from a person who knows about the field well.
1. I have studied VLSI, DSP, Image Processing, Wireless Communication, Control Systems and Embedded Systems as graduate and undergraduate courses and have some research interest in Neural Networks and Machine Learning(That’s how I got interested in Neural Engg and Prosthetics). Which of these subjects will be of help in Neural Engg/Prosthetics research. Which will be of most relevance. Please list them in the order of relevance(high->low).
2. What are the applications of the research ?
3. What is the research and JOB scope for this field? Are there any companies who recruit people with this specialisation? How is the job scene in academia? How many univs are doing research in this field in US? Please let me know about the career progression in academia, like how much time does it take to get full time academic position after PhD?
4. Especially, what are the applications of this research in Robotics?
5. What are the current problems and research themes in universities?
6. What imaging technologies are used in this research?

Though my queries may seem a bit ameteuristic, it is very important for me to get clarity on these doubts.
Hope my queries will be answered.
Thanking all of you in advance,
sudhi

Neuroengineering and the MIT TR35 innovators

Thursday, September 7th, 2006

Today MIT’s Technology Review magazine released its annual list of innovators under the age of 35 who were nominated for recognition. Interestingly, almost a full quarter are doing work relating to or impacting the field of neuroengineering — including ways to tag synapses with quantum dots, activate neurons remotely, improve machine vision, classify whole-brain states for prosthetic purposes, and make nanowire arrays.

http://www.technologyreview.com/TR35/