Neuroengineering/OptogeneticMapping

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Introduction
Brain-Machine Interfaces
Optogenetic Mapping: Neurotechnology Renaissance
Ubiquious Computing and Augmented Reality
The Affective Turn: Emotional Branding, Neuromarketing, and the New, New Media
Concluding Thoughts

Optogenetic Mapping: Neurotechnology Renaissance



The techniques for recording neural ensembles developed by Nicolelis and discussed above are effective in decoding sensorimotor movements, and there are numerous medical applications for assisting paralyzed patients that can implement these methods. But they are not fine-grained enough to be able to map out the individual circuits involving thousands of neurons that encode a specific brain function, particularly higher cognitive functions. Problems of a similar nature are obstacles in the use of fMRI imaging—since fMRI relies on blood flow and oxygenation to particular areas of the brain, the results suffer from temporal lag—and EEG (electroencephalogram) methods. Recently a new and highly successful approach has been introduced, called optogenetic mapping. Developed by Karl Diesseroth and Ed Boyden in 2006 this method operates by using a light stimulus to modulate electrical activity of populations of cortical neurons. Through a piece of genetic engineering, cortical neurons can be made to express Channelrhodopsin-2. Blue light from a laser will open ChR-2’s sodium channel, triggering a massive influx of sodium ions into the neuron and making it fire an action potential. Conversely Boyden and his team discovered that by inserting the gene for expressing Halorhodopsin, another protein capable of light activation, and exposing the neuron to yellow light, it would stop firing. Here you had a pair of On-Off switches that were extremely precise and could be operated in a highly controlled manner in a volume of neurons one cubic millimeter by simply injecting a small amount of virus used for the transfection. By stimulating those cells with a laser, the researchers could control the activity of specific nerve circuits with millisecond precision and study the effects. They later discovered that by also inserting the gene for expressing Green Fluorescing Protein, GFP, it would serve to indicate that the neuron expressing Channelrhodopsin-2 has fired. By using different promoters, different cell types could be selected and studied. By switching on and off the blue and yellow laser light that could be passed to the tissue through microfiber optic cables, it could be determined which functional groups of cells are involved in a bodily action. These new methods using light to activate or silence specific neurons in the brain, are now being widely utilized by researchers to reveal insights into how to control neural circuits to achieve therapeutically useful changes in brain dynamics.(For a demo, see: Optogenetics: Controlling the Brain with Light] According to Ed Boyden, “We are entering a neurotechnology renaissance, in which the toolbox for understanding the brain and engineering its functions is expanding in both scope and power at an unprecedented rate.” (Boyden, Brain Coprocessor) For Boyden and other neuroengineers the new tools for imaging and mapping brain circuits, such as those provided by optogenetics and two-photon microscopy, Diffusion Tensor Imaging and computer tractography are beginning to reveal principles governing how best to control a circuit—revealing the neural targets and control strategies that most efficaciously lead to a goal brain state or behavioral effect, and thus pointing the way to new therapeutic strategies and ultimately the development of implantable neuromorphic chips capable of intervening therapeutically into processes such as epilepsy or Parkinson’s disease. Miniature, implantable brain coprocessors, Boyden argues, might be able to support new kinds of personalized medicine, for example continuously adapting a neural control strategy to the goals, state, environment, and history of an individual patient; and in the not-distant future, the computational module of a brain coprocessor may be powerful enough to assist in high-level human cognition or complex decision-making.

Summary

Let me summarize the developments in Brain Machine Interfaces relevant to our interrogation of constructions of the future. First there have some important changes in how we understand the brain. Foremost is the emphasis on brain and neural plasticity. One of the key points in the discussion above is the ability of the brain to reshape the body schema to include new prosthetic devices such as robotic arms and legs operating over the internet as parts of the body. An astonishing feature of the Nicolelis experiments discussed above, for instance, is that as Aurora adjusts to operating the brain-machine interface by thought alone, not using her natural arm movements to operate the joystick, the neural firings in her brain adapt and optimize around controlling the robot arm. The ease and rapidity with which this happens is impressive, amazing really. Another feature I have wanted to emphasize is the point that through the BMIs we have presented, it is imaginable for two or more animals in the loop to share brain states as part of a collective, cooperative, agent mind. The imagination runs wild in thinking about possible scenarios of where this might lead in an internet-enabled ubiquitous computing environment. The final point we have made is that with new experimental techniques of optogenetics and new imaging modalities such as two-photon laser scanning microscopy, researchers are beginning to be able to map out the detailed circuitry not just of sensorimotor function but soon even higher-ordered cognitive functions central to mental activity. An example of this is the work of the David Tank Lab at Princeton on mapping the circuitry of the hippocampus in order to understand the dynamics of short term memory(Harvey, 2009). The ability to intervene within, control, and possibly modify the functioning of specific neural circuits is just over the horizon. According to Edward Boyden (MIT), David Tank (Princeton), Karl Diesseroth (Stanford) and other neuroengineers, the era of brain coprocessors is within reach (for outstanding coverage of these rapid ongoing developments see the BrainWindows blog: http://brainwindows.wordpress.com/2009/11/09/three-cheers-for-gcamp/).


The discussion thus far has centered on brain-machine interfaces and future imagined brain coprocessors as therapeutic, rehabilitative tools and devices for brain reading and mind control for augmenting human mental abilities through fairly invasive surgical means. But some of the features of these imagined brain coprocessors may already be silently being installed through non-surgically invasive means. In the next sections I want to explore developments from the fields of ubiquitous computing, social media and marketing in progress that for all practical purposes are neurotechnologies of the future. (More: Augmented Reality Interfaces)

References

Boyden, Edward S., Feng Zhang, Ernst Bamberg, Georg Nagel, and Karl Deisseroth. "Millisecond-Timescale, Genetically Targeted Optical Control of Neural Activity." Nature Neuroscience 8, no. 9 (2005): 1263-68.

Sporns, Olaf, Giulio Tononi, and Rolf Kötter. "The Human Connectome: A Structural Description of the Human Brain." PLoS Computational Biology 1, no. 4 (2005): e42.

Deisseroth, Karl, Guoping Feng, Ania K. Majewska, Gero Miesenböck, Alice Ting, and Mark J. Schnitzer. "Next-Generation Optical Technologies for Illuminating Genetically Targeted Brain Circuits." Journal of Neuroscience 26, no. 41 (2006): 10380-86.

Zhang, Feng, Li-Ping Wang, Martin Brauner, Jana F. Liewald, Kenneth Kay, Natalie Watzke, Phillip G. Wood, Ernst Bamberg, Georg Nagel, Alexander Gottschalk, and Karl Deisseroth. "Multimodal Fast Optical Interrogation of Neural Circuitry." Nature 446, no. 7136 (2007): 633-39.

Boyden, Edward S, Brian Allen, and Doug Fritz. "Brain Coprocessors." Technology Review September 23 (2010).

Harvey, Christopher D., Forrest Collman, Daniel A. Dombeck, and David W. Tank. "Intracellular Dynamics of Hippocampal Place Cells During Virtual Navigation." Nature 461, no. 7266 (2009): 941-46.

O'Doherty, Joseph E, Mikhail Lebedev, Timothy L Hanson, Nathan Fitzsimmons, and Miguel A.L Nicolelis. "A Brain-Machine Interface Instructed by Direct Intracortical Microstimulation." Frontiers in Integrative Neuroscience 3 (2009).

Boyden, E. S. "The Birth of Optogenetics." The Scientist, July 1 (2011): Cover Story.

Gradinaru, Viviana, Murtaza Mogri, Kimberly R. Thompson, Jaimie M. Henderson, and Karl Deisseroth. "Optical Deconstruction of Parkinsonian Neural Circuitry." Science 324, no. 5925 (2009): 354-59.

Moritz, Grosse-Wentrup, and et al. "Using Brain–Computer Interfaces to Induce Neural Plasticity and Restore Function." Journal of Neural Engineering 8, no. 2 (2011): 025004.

Berger, Theodore W. , Robert E. Hampson, Anushka Goonawardena, Samuel A. Deadwyler, Dong Song, and Vasilis Z. Marmarelis. "A Cortical Neural Prosthesis for Restoring and Enhancing Memory." Journal of Neural Engineering 8, no. 4 (2011): 046017.

Wentz, Christian T. , Jacob G Bernstein, Patrick Monahan, Alexander Guerra, Alex Rodriguez, and Edward S Boyden. "A Wirelessly Powered and Controlled Device for Optical Neural Control of Freely-Behaving Animals." Journal of Neural Engineering 8 (2011).

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