neurodudes

This paper describes some stuff that UCLA is doing with their neuroengineering program. Of particular interest is an ongoing project to develop networks of miniature wireless computers (”motes”) to support wireless MEA recording and stimulation (within section B, ” Improving Headstages for BCI Systems”).

The system is being built with Mica nodes, which are mesh-networking sensor motes about the size of a U.S. quarter, but I’m not sure if they are using mesh networking in this project. More details here.

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Riken tournament video

You win by producing alpha waves. Unfortunately, a Mindball set is a little expensive. Perhaps OpenEEG is the way to go? Here’s another build-your-own-EEG guide. Google also finds various people’s experiences trying to build their own EEGs according to these guides. Are there any other build-your-own EEG guides out there? Post a comment and let us know.

Also, I hope that all the homemade EEG folks know about OpenStim, and vice versa.

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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

Transcranial magnetic stimulation (TMS) is a popular technology for stimulating human cortical neurons, due to its safety, noninvasiveness, and efficacy. A TMS device is just a little coil of wire, through which 10,000 Amps of current is cranked during a period of only a few hundred microseconds; the resultant rapidly-changing magnetic field induces eddy currents in the brain. Depending on the protocol used, TMS can drive/inhibit a region of cortex corresponding to roughly a cubic centimeter or two, and is being explored for the treatment of depression, the reduction of auditory hallucinations during schizophrenia, and the alleviation of tinnitus and migraines. Thousands of papers on medicine and psychology have been written using this tool.

Yet the device itself is expensive and rare — they can run from $20,000 to $50,000 or even more, despite the fact that they are, in essence, a coil, a switch, a bank of capacitors, and a power supply. Much of the art lies in making the devices safe and fail-proof. Is it possible to hack/engineer a system that is safe, fault-tolerant, efficacious, and inexpensive? And furthermore, can we facilitate a community that will devise such devices, and share information about protocols and approaches to brain hacking?

This past August at Foo Camp, a hackers’ conference in Northern California, a group of people got together and set out to do just that. We are designing a safe, noninvasive, modular, and “open source” brain stimulator that will open up the field of circuit modulation to a wider audience. Members of the group include therapists and mental health professionals, engineers, programmers, and others interested in either the development of such devices, or the sharing of information on this front. Key to the design is safety — we want to make sure that the devices we create are as safe as devices on the market. Also, all the information is released under the Creative Commons “Attribution and Sharealike” license. This is a new model for “open source” medical device development — which may move it beyond the domain of simply creating “cool toys,” and to creating real devices.

You can find out more information, or contribute to the project, or learn from the project, at
http://transcenmentalism.org/OpenStim/

-Ed

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/

The July 13 issue of Nature included some neural prosthetics papers, one of which was the paper reporting 9 months of stimulation of Matthew Nagle, a tetraplegic who received the first trial of the 96-electrode BrainGate implant in his right precentral gyrus (motor cortex (MI) for arm). The authors were Leigh R. Hochberg, Mijail D. Serruya, Gerhard M. Friehs, Jon A. Mukand, Maryam Saleh, Abraham H. Caplan, Almut Branner, David Chen, Richard D. Penn and John P. Donoghue.

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Im a molecular/cellular neurobiologist. I do however, have a deep interst in neural prosthetics, bionics research. Is there a place for me in this field?

ScienceDaily: Semiconductor Brain: Nerve Tissue Interfaced With A Computer Chip

From the article:

16384 transistors on an area of one square millimeter record the neural activity in the brain.

Hmmm, that sounds like a lot of transistors… what kind of voltage sensing resolution can a device like that provide? Well, that works out to 1.6 transistors per 10 square microns, which is arguably the relevant area for a neuron. Although these are extracellular signals, this high-resolution tool is going to have quite a large impact.

From the abstract:

We report on the recording of electrical activity in cultured hippocampal slices by a multi-transistor array (MTA) with 16384 elements. Time-resolved imaging is achieved with a resolution of 7.8 µm on an area of 1 mm2 at 2 kHz. A read-out of fewer elements allows an enhanced time resolution. Individual transistor signals are caused by local evoked field potentials. They agree with micropipette measurements in amplitude and shape. The spatial continuity of the records provides time-resolved images of evoked field potentials and allows the detection of functional correlations over large distances. As examples, fast propagating waves of presynaptic action potentials are recorded as well as patterns of excitatory postsynaptic potentials across and along cornu ammonis.

M. Hutzler, A. Lambacher, B. Eversmann, M. Jenkner, R. Thewes, and P. Fromherz: High- resolution multi-transistor array recording of electrical field potentials in cultured brain slices. Journal of Neuropyhsiology. Preprint online (May 10, 2006).

The original article (whichs seems to online in a preprint form) has excellent photos of the array (showing how it can cover a lot of a hippocampal slice), the tight correspondence between the transistor signal and a microelectrode field signal, and some cool readouts of the “whole hippocampus” with various blockers. I doubt anyone has ever been able to simultaneously do such fine scale electrophysiology on such a large portion of the mammalian brain ever before.

Technology Review: Emerging Technologies and their Impact

I don’t know too much about Zach Lynch, other than that he has a blog and refers to his company as the “neurotechnology market authority”, but there are some interesting tidbits from the TR interview:

TR: Research suggests that antidepressants are effective partly because they stimulate neurogenesis. So companies such as BrainCells, based in San Diego, CA, are screening compounds that promote growth of neural stem cells in the brain. They say these drugs could bring new therapies for depression and, eventually, neurodegenerative diseases.

ZL: It’s an exciting area, and the investment community is certainly interested. But the jury is still out.

TR: We’re also starting to see a new kind of therapy for brain-related illnesses — electrical stimulation. Various types of stimulation devices are now on the market to treat epilepsy, depression, and Parkinson’s disease. What are some of the near- and far-term technologies we’ll see with this kind of device?

ZL: We’re seeing explosive growth in this area because scientists are overcoming many of the hurdles in this area. One example is longer battery life, so devices don’t have to be surgically implanted every five years. Researchers are also developing much smaller devices. Advanced Bionics, for example, has a next-generation stimulator in trials for migraines.

In the neurodevice space, the obesity market is coming on strong. Several companies are working on this, including Medtronics and Leptos Biomedical. In obesity, even a small benefit is a breakthrough, because gastric bypass surgery [one of the most common treatments for morbid obesity] is so invasive.

In the next 10 years, I think we’ll start to see a combination of technologies, like maybe a brain stimulator that releases L-dopa [a treatment for Parkinson's disease]. Whether that’s viable is a whole other question, but that possibility is there because of the microelectronics revolution.

The real breakthrough will come from work on new electrodes. This will transform neurostimulator applications. With these technologies, you can create noninvasive devices and target very specific parts of the brain. It’s like going from a Model T to a Ferrari. Those technologies will present the real competition for drugs.

Neuron : Dynamics of Parietal Neural Activity during Spatial Cognitive Processing

Here’s John Lisman’s review of this paper (from Georgopoulos’s group)… I don’t think I can say it better than him:

If ever there was a paper that would bring tears to one’s eyes, this is it: a previously hidden mental process has now become subject to experimental study. The mental process is the covert movement of attention, the selective focussing of attention to subregions of the visual field, but without eye movement. The movements of covert attention were hypothesized based on psychophysics, but the authors can now follow it using a vector field derived from a population of neurons in the parietal cortex. The monkey has been trained to use covert attentional shifts to solve a maze task. The major finding is that the vector derived from the population of parietal cells follows in time the path through the maze, as the monkey solves the maze.

From the abstract:

We found that the direction of the followed path could be recovered from neuronal population activity.

Yet another scary but cool result…