tag:blogger.com,1999:blog-14477956754656501862024-02-21T20:43:13.380-05:00Best before yesterdayWeblog of Christopher Harris, PhDChrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.comBlogger361125tag:blogger.com,1999:blog-1447795675465650186.post-38882865341916642142017-11-19T12:08:00.000-05:002017-11-19T12:08:48.003-05:00What's your robot into?<div dir="ltr" style="line-height: 1.38; margin-bottom: 0pt; margin-top: 0pt; text-align: justify;">
<span style="background-color: transparent; color: black; font-family: Calibri; font-size: 12pt; font-style: normal; font-variant: normal; font-weight: 400; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">In the Apple store yesterday, in the corner where they keep electronic learning toys and robots, I read this on a box: “Almost human”, “Cozmo doesn’t just learn - Cozmo plots and plans”, “Cozmo doesn’t just move - Cozmo gets curious and explores”. Cozmo is an $180 robot toy with image processing capabilities, expressive LED eyes, and a set of anthropomorphic behaviors. Ascribing mental states to it seems like an exaggeration - I don’t think Cozmo gets curious, just as I don’t think my phone gets hungry as its battery runs down - but what exactly does a robot or computer have to do before we can ascribe mental states to it without exaggerating? This question will get more and more relevant as AI and robotics continue to improve.</span></div>
<b id="docs-internal-guid-d2f14124-d532-44d8-70f4-7ddf16bf23bd" style="font-weight: normal;"><br /></b>
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<span style="background-color: transparent; color: black; font-family: Calibri; font-size: 12pt; font-style: normal; font-variant: normal; font-weight: 400; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">Contemporary philosophy and neuroscience offers two contradictory answers. “Functionalists” like Daniel Dennett argue that we are justified in ascribing mental states to a system whenever doing so helps us understand and predict its behavior. Proponents of more brain-based views such as integrated information theory (IIT) argue that mental states, or at least their subjective aspect, require a degree of information integration that we currently observe only in biological brains.</span></div>
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<span style="background-color: transparent; color: black; font-family: Calibri; font-size: 12pt; font-style: normal; font-variant: normal; font-weight: 400; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">IIT has the distinct advantage that it recognizes the possibility of mental states in immobile systems such as unresponsive patients and simulated brains - Dennett’s behavior-based account does not. But IIT is prone to zombies: if IIT is correct it should be possible to build robots that mimic the behavior of animals or human beings but lack subjective states simply because they use integrated circuits to process information rather than neurons. This could get confusing or downright ugly, because how should we treat a robot that expresses every sign of need, trust, pain or love, but (according to IIT) has no subjective experience whatsoever? Some might feel entirely justified in treating such robots terribly, Westworld style.</span></div>
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<span style="background-color: transparent; color: black; font-family: Calibri; font-size: 12pt; font-style: normal; font-variant: normal; font-weight: 400; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">Dear philosopher friends! Am I reading this right? Does Dennett accept that his intentional stance fails spectacularly as far as unresponsive patients are concerned? Would proponents of IIT agree that their framework may become the legal defense of the sexbot industry? What does a computer or robot have to do to deserve to be treated like a mind? Do we need to be less binary about whether or not a system is in a particular mental state? Perhaps my phone can get hungry after all, in its own way, or does that cheapen the concept of hunger? What do you think?</span></div>
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Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com0tag:blogger.com,1999:blog-1447795675465650186.post-11312975095685583312017-11-07T12:40:00.000-05:002017-11-07T12:40:37.565-05:00Brain Implants in the News<div dir="ltr" style="line-height: 1.38; margin-bottom: 0pt; margin-top: 0pt; text-align: justify;">
<span style="background-color: transparent; color: black; font-family: Calibri; font-size: 12pt; font-style: normal; font-variant: normal; font-weight: 400; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">In his October 27 article in the Wall Street Journal titled “<a href="https://www.wsj.com/articles/to-keep-up-with-ai-well-need-high-tech-brains-1509120930">To Keep Up With AI, We’ll Need High-Tech Brains</a>” Christof Koch, President and Chief Scientific Officer at the Allen Institute for Brain Science, argues for the development of high-resolution brain implants for everyone. His stated reason is that this will create a place for humans in a future where all basic tasks are performed by computers and robots, but he also hints at something grander, saying of the brain that “It is within our reach to enhance it, to reach for something immensely powerful we can barely discern”. </span><span style="font-family: Calibri; font-size: 12pt; white-space: pre-wrap;">Koch muses about implants that “could translate a vague thought into a precise and error-free piece of digital code, turning anyone into a programmer.” and about how “People could set their brains to keep their focus on a task for hours on end” (now that reminds me of something…).</span></div>
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<span style="background-color: transparent; color: black; font-family: Calibri; font-size: 12pt; font-style: normal; font-variant: normal; font-weight: 400; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">Enter John Horgan, foe of brain implants and writer at the Scientific American, where on November 1 he published "<a href="https://blogs.scientificamerican.com/cross-check/do-we-need-brain-implants-to-keep-up-with-robots/">Do We Need Brain Implants To Keep Up With Robots?</a>".</span><span style="background-color: transparent; color: black; font-family: Calibri; font-size: 12pt; font-style: normal; font-variant: normal; font-weight: 400; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;"> Horgan thinks the technology Koch describes is far in the future; because before we can develop effective brain implants, Horgan thinks we need to solve what he calls the “neural code”, i.e. understand how communication among millions of individual neurons gives rise to brain function. I think this is an error of thought. Complete understanding is a valuable thing but improvisation and learning by trial and error are workable courses of action too, especially in an age of AI. Many powerful brain enhancing implants could be in widespread use today if the process for placing electrodes inside the skull could be made safe, but Horgan doesn’t mention this essential (and in my mind only) obstacle to rapid growth in the use of brain implants. Good thing Elon Musk is <a href="https://en.wikipedia.org/wiki/Neuralink">on the case</a>.</span></div>
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<span style="font-family: Calibri; font-size: 12pt; white-space: pre-wrap;">PS. The neurorobot project is developing just fine, stay tuned :)</span></div>
Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com1tag:blogger.com,1999:blog-1447795675465650186.post-62081411183316271922016-06-12T10:53:00.002-04:002016-08-11T09:03:36.619-04:00Eyeball - A Minimal NeurorobotThis is my second post on personal neurorobotics. In the <a href="http://brainimplant.blogspot.com/2016/04/personal-neurorobotics.html">previous post</a> I outlined the case for brain-based robots as consumer products, especially in education. In this post I will describe a minimal personal neurorobot that I call Eyeball. Eyeball implements a causal loop that is fundamental to animal (and neurorobot) behavior: signals travel from the brain to motors, causing behavior and change in the outside world, which is perceived by the brain as visual or other sensory feedback.<br />
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Eyeball is a web-camera attached to a servo motor. Eyeball's brain consists of two spontaneously spiking neurons that run on a USB-connected computer (<a href="http://www.vertebot.com/code/eyeball.py">eyeball.py</a>, requires <a href="http://opencv.org/">OpenCV</a>, windows installation instructions <a href="http://mathalope.co.uk/2015/05/07/opencv-python-how-to-install-opencv-python-package-to-anaconda-windows/">here</a>). One of the neurons is a motor neuron: whenever it spikes the motor moves to a new position. This changes the field of view of the web-camera, which continuously sends video frames back to the brain. The second neuron is a sensory neuron that is maximally activated by a dark spot on a white background. The spikes of the sensory neuron inhibit the motor neuron. This means that when Eyeball encounters a dark spot on a white background it stops moving and fixates on it.</div>
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Eyeball is very cheap. Web-cameras and servos can be bought for less than $5 each. To send serial commands via USB from Python to Eyeball I use an FTDI chip, which can also be purchased for around $5. I used an Arduino board to convert the serial commands to the PWM format needed to control the servo but only because I don't yet know how to send PWM commands from Python directly. So in principle the device costs less than $20. (Of course, to be successful Eyeball would also need a nice-looking plastic case.)<br />
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Despite the low cost, Eyeball has all the components needed to emulate some interesting brain functions and behavior. Vision is perhaps the best understood of all brain functions, and brain-based models of visual object recognition such as <a href="http://maxlab.neuro.georgetown.edu/hmax.html">HMAX</a> are already used to give neurorobots vision, but only in academia - not yet for consumer-oriented educational applications. Given the ability to recognize objects, Eyeball could moreover be trained to orient towards and track some objects and avoid others, ideally using a realistic implementation of the tectum/superior colliculus and basal ganglia. A reward-button could be used to deliver a dopamine-reward, changing synaptic weights according to known learning rules and thus training the robot to show preference for some objects. Easy access to the web-camera's microphone and the computer's speakers opens the door for voice communication... etc... etc...<br />
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While even this very simple neurorobot opens up a lot of interesting possibilities for implementing and exploring mechanistic models of the brain, what we really want is a robot that has two eyes and can move around independently. This will be the topic of the next post.<br />
<br />Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com0tag:blogger.com,1999:blog-1447795675465650186.post-68782610228077785762016-04-26T08:30:00.001-04:002016-06-02T06:05:23.336-04:00Personal NeuroroboticsI've been exploring this idea for a few years now. It's time I start to document what I'm doing and ask for feedback. This is a summary, I'll go into detail in future posts.<br />
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Consider these trends:<br />
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<li>Mechanistic models of brains and brain functions are getting better and better</li>
<li>Smartphones and laptops are becoming powerful enough to run such models</li>
<li>Hardware is getting cheap enough to build robots that can see, hear, make sounds, move around and communicate wirelessly for less than $200</li>
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I believe these trends open up a market for autonomous robots whose control-systems emulate biological brains. Consumer robotics is already a rapidly growing phenomenon and <a href="http://journal.frontiersin.org/journal/neurorobotics">neurorobotics</a> is an expanding area of research but I have yet to see the two endeavors combined. Please let me know in the comments below if there's some product or project I've missed.<br />
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A first generation personal neurorobot might emulate the brain of a fish or lamprey. Done right, it would explore its environment, avoid obstacles, escape threats, pursue desired states and objects, and learn, both from experience and explicit training. While these are behaviors that conventional robots can be programmed to perform, the defining feature of a neurorobot is its realistic brain architecture and activity, which makes it ideal for exploring and teaching neuroscience. Here, all the robot's brain processes could run on a wirelessly connected smartphone or computer, and be available for observation, explanation and modification in real-time. Using reinforcement learning to train the robot would be particularly interesting.<br />
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I see two markets for personal neurorobots:<br />
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<li>Schools. Robots are already used in schools (e.g. <a href="http://www.firstinspires.org/">FIRST Robotics Competition</a>, <a href="https://education.lego.com/en-us">LEGO Education</a>). Neurorobots add the possibility of teaching neuroscience and behavior, which broadens the appeal substantially.</li>
<li>Enthusiasts. The popularity of neuroscience on the one hand and of consumer robotics on the other indicates that there would be a lot of interest in a project that combines both.</li>
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Importantly, the complexity of the brains and behavior of personal neurorobots could be increased year by year as new neuroscientific findings and models become available. Hopefully this can be an open process, with both individual enthusiasts and larger research teams working to make new brain circuits and capabilities available to the broader user-base. (The Human Brain Project is betting on a similar dynamic with their simulated robot testing environment, the <a href="http://www.neurorobotics.net/">Neurorobotics Platform</a>.) The long-term aim would be to emulate the brain functions of higher vertebrates, such as complex learning, communication, attachment, planning, language and play.<br />
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While I think this project needs the attention of experienced roboticists, programmers, educators and investors, I will do my best to demonstrate feasibility and promote the idea. In my spare time I've developed a prototype neurorobot that I call a vertebot, pictured above. The hardware works, although ideally a personal neurorobot should be a light off-the-shelf product, not a five-pound beast that's prone to burst into flames. My main challenge is the code. I'm only fluent in Matlab and this project requires a non-proprietary language. So I'm learning Python and I'll ask for help with that as I move forward. Currently I can just about make a single neuron spike (<a href="http://www.vertebot.com/code/single_neuron.py">single_neuron.py</a>). I've set up a website (<a href="http://www.vertebot.com/">www.vertebot.com</a>) where I'll put code and up-to-date information on the project. I'm also setting up a GitHub repo. All other observations and ideas I'll share here on the blog.<br />
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It's a big, sprawling project. I hope you'll find it interesting.<br />
<br />Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com0tag:blogger.com,1999:blog-1447795675465650186.post-41567384655716428522016-04-24T12:04:00.001-04:002016-04-24T13:38:27.380-04:00Best Podcasts 2016It's a great year in politics so let's start there. <a href="http://www.slate.com/articles/podcasts/gabfest.html" target="_blank">Slate's Political Gabfest</a> is still going strong. Co-host John Dickerson has moved up in the world of US politics, he now moderates presidential debates and interviews the candidates on CBS's <a href="http://www.cbsnews.com/face-the-nation/" target="_blank">Face the Nation</a> (don't miss his FTN Diary). However, the Gabfest faces formidable election coverage competition from the <a href="http://fivethirtyeight.com/tag/elections-podcast/" target="_blank">Five Thirty Eight elections podcast</a>, which has a great, geeky ambiance and a fresh, numbers-based approach to punditry. Vox's <a href="http://www.vox.com/the-weeds" target="_blank">The Weeds</a>, The Econonist's various podcasts, and shows like <a href="http://bloggingheads.tv/programs/glenn-show" target="_blank">The Glenn Show</a> on Bloggingheads TV do good analysis of news and society. BBC's <a href="http://www.bbc.co.uk/programmes/p002vsnk/episodes/downloads" target="_blank">Newshour</a> is still the go-to podcast for big complex stories like the Panama Papers.<br />
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Long-form interviews can be extraordinarily good when done right. <a href="http://www.wtfpod.com/" target="_blank">WTF with Marc Maron</a>, CNN's <a href="http://politics.uchicago.edu/pages/axefiles" target="_blank">The Axe Files</a> with David Axelrod, and The Ezra Klein Show frequently hit the mark.<br />
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<a href="http://verybadwizards.com/" target="_blank"><img border="0" height="233" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhXk0ngm_oy7mUViRKSXVmpeS0CyxVElaRlGaQqMVYbiPMlmEh31QOkBy7BurhsVp7YlJ-NGeslzjxtFtu-bAtllkND4-khPVXzDJfVjWoLMcsLXf0fMcGcfDkAJ1f40m-y_VacwlxfCVs/s320/VeryBadWizardArtwork%252Bwebsite.png" width="320" /></a></div>
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<a href="http://verybadwizards.com/" target="_blank">Very Bad Wizards</a> is the best podcast. Period. Social psychology, moral philosophy and great banter. I own the T-shirt. Repugnant. <a href="http://www.spacetimemind.com/" target="_blank">Space Time Mind</a>, another philosophy podcast was really picking up steam (the <a href="http://www.spacetimemind.com/blog/2015/2/15/episode-23-transhumanist-hot-tub-w-ken-williford" target="_blank">Transhumanist Hot Tub episode</a> is absolutely genius) but has been silent for months.<br />
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When it comes neuroscience, <a href="http://snrp.utsa.edu/Podcast/Podcast.html" target="_blank">Neuroscientists Talk Shop</a> wipes the floor with the competition. Try it (the episodes with <a href="http://snrp.utsa.edu/Podcast/Entries/2015/3/31_Anatol_Kreizer_PhD.html" target="_blank">Kreizer</a> and <a href="http://snrp.utsa.edu/Podcast/Entries/2015/2/5_Carmen_Canavier_PhD.html" target="_blank">Canavier</a> are two recent highlights) and then try something like Nature's <a href="http://www.nature.com/neurosci/neuropod/index.html" target="_blank">Neuropod</a> or the <a href="http://brainsciencepodcast.com/" target="_blank">Brain Science podcast</a> and decide for yourself. (That said, yesterday I discovered <a href="http://brainpodcast.com/" target="_blank">Brain Matters</a>, which looks like it could be really good. Fingers crossed.)<br />
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At the end if the week, relax with BBC's Friday Night Comedy podcast <a href="http://www.bbc.co.uk/programmes/b006r9yq" target="_blank">The News Quiz</a>. Sandi Toksvig left to host QI and has been gloriously replaced by Miles Jupp.<br />
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Finally technology. Leo Laporte is still king. <a href="https://twit.tv/shows/this-week-in-google" target="_blank">This Week in Google</a> is pretty much always very good. <a href="https://twit.tv/shows/security-now" target="_blank">Security Now</a>, <a href="https://twit.tv/shows/this-week-in-law" target="_blank">This Week in Law</a> and <a href="https://twit.tv/shows/this-week-in-tech" target="_blank">This Week in Tech</a> can be good if the topic and panel are. Non-TWiT podcasts worth keeping an eye on include Robohub's <a href="http://robohub.org/category/talk/robotspodcast/" target="_blank">Robots podcast</a>, the <a href="http://techcrunch.com/video/gillmor-gang/" target="_blank">Gillmor Gang</a>, and of course <a href="http://longnow.org/seminars/podcast/" target="_blank">Seminars About Long-Term Thinking</a>.<br />
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And don't forget <a href="http://www.bbc.co.uk/programmes/b006qykl" target="_blank">In Our Time</a>.<br />
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I use the paid-for version of <a href="https://play.google.com/store/apps/details?id=com.bambuna.podcastaddict" target="_blank">Podcast Addict</a> on Android.<br />
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Please let me know about any podcasts you think I would like.<br />
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Enjoy!<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjgQuVRpjM8NdereKB-OVsjC8DttC9NPItcouBB0H8D28FvW9QGxBMWh0X1k1WuY347s_g9IhVmPMJqPdY2OrnyJ65PueUQBQAfqJ8HKfhm-DAqGNybOBVH8yi16BxBkbkBCVDlZtnA34Y/s1600/Wernicke%2527s_area_-_lateral_view2.png" imageanchor="1"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjgQuVRpjM8NdereKB-OVsjC8DttC9NPItcouBB0H8D28FvW9QGxBMWh0X1k1WuY347s_g9IhVmPMJqPdY2OrnyJ65PueUQBQAfqJ8HKfhm-DAqGNybOBVH8yi16BxBkbkBCVDlZtnA34Y/s320/Wernicke%2527s_area_-_lateral_view2.png" width="320" /></a></div>
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Wernicke's Area, where podcast do their magic.</div>
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<span style="font-size: xx-small;">Polygon data were generated by Database Center for Life Science(DBCLS)<a class="external autonumber" href="http://dbcls.rois.ac.jp/en/" rel="nofollow">[2]</a>.
Polygon data are from BodyParts3D<a class="external autonumber" href="http://lifesciencedb.jp/ag/bp3d/download/index.jsp" rel="nofollow">[1]</a>, <a href="http://creativecommons.org/licenses/by-sa/2.1/jp/deed.en" title="Creative Commons Attribution-Share Alike 2.1 jp">CC BY-SA 2.1 jp</a>, https://commons.wikimedia.org/w/index.php?curid=32534031
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<br />Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com0tag:blogger.com,1999:blog-1447795675465650186.post-90730748737175036712013-03-24T14:55:00.001-04:002015-05-29T15:11:31.276-04:00Musing on the mind-brain problem<span style="color: #333333;"><i>Following a couple of recent conversations with friends and family I've written a short summary of my current views on the mind-brain problem. The dry jargon of scientific research reports is an obvious obstacle to a generally satisfying account of the conscious self, so I try to not be dry. This is just my current perspective, I'm not providing references and I reserve the right to be wrong.</i></span><br />
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<span style="color: #333333;">I think it's important not to think of the brain as 'just a bunch of cells', but rather as</span><span style="color: #333333;"> a hundred billion individual identities that want to live and grow</span><span style="color: #333333;">. The ancestors of the cells of the brain were <i>free agents</i>; swimming, creeping, crawling, swirling their way through the waters of ancient earth; feeding, resting, sensing, fighting, fleeing and multiplying. Now they're here, living together in this civilization we call brain; but they are still feral. In a very real way they rival and tussle every day to stay alive. The neurons of the brain do not grow old and die like other cells; you have almost entirely the same brain cells now as you had when you were a child. However, tens of thousands of them are wiped out every day - only the ones that form <i>important </i>constellations and alliances with other neurons receive 'neuromodulators' and grow; others shrivel and fade. </span><span style="color: #333333;">Neuromodulators, what Gerald Edelman called 'value systems', are essential to the life and growth that brain cells seek. And here is the essential fact: neuromodulators are released in the brain in response to <i>meaningful</i> events of various kinds, happenings internal or external that bear on the interests of the body, the person, the brain as a whole, or one of its neural communities. The brain cells, seeking neuromodulators, seeking life and growth, are therefore in constant electrical communication and structural flux, seeking to bring about, probe and explore the meaningful, important aspects of the reality in which they find themselves.</span><br />
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<span style="color: #333333;">What are these aspects of interest, of meaning, that allow neurons to survive and grow? What happenings attract the complexity and potential of a living human brain cell? To start with, every neuron is in constant electrical union with the sensing, moving body, and the neurons communicate and grow about this vital fact. The neurons share a common path through life, and so they explore and probe their shared memories constantly for nuggets of intrigue. Although their communities are often in tension as each continues the ancient will to live on and grow against the daily weeding out of the least relevant of them, they nevertheless share a common mouth, a common pair of hands and eyes, and the electrical urges of hunger, need, sleep and dreams reverberate across the neural fields </span><span style="color: #333333;">endlessly. How could they <i>not</i> share a sense of I in this circumstance? </span><span style="color: #333333;">From this seeking, seething</span><span style="color: #333333;">, astronomically complex swirl of electric neural energy, membrane and will to survive and grow emerges pleasure and frustration, I and not-I, hopes, plans, dreams and distinctions. The astounding communities and constellations of living, electrified tissue that constitute each of these core features of the human experience are there for us to explore, by any method we choose - introspective, statistical, fictional, spiritual, communal - and it is our tremendous fortune and grace to be alive just as the technology to express and understand all this is finally beginning to become available.</span><br />
<span style="color: #333333;"><br /></span><span style="color: #333333;">At the heart of it all then, is a dynamic, inventive, persevering civilization of cells, seeking nourishment, excitement, </span><span style="color: #333333;">love</span><span style="color: #333333;"> and force, in a never-ending myriad of ways. </span><span style="color: #333333;">This is what it is to be alive, a conscious human being; a near-instantaneous sharing of memory, will and rich experience among the one hundred billion little lives within that one skull. It is in their nature to seek, like their cousins still independent in the sea; but the cells of the brain seek in communication and structural union with other brain cells. The subject of this electrical conversation is and feels like you.</span><br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEinXNAnrlxz9loZEJPtYoXcT0S43EKBKC3nznsstEgm0yfKM8zGvAHk-SOtljK0DHEAOyLYkBECnYgfhTwaWbFlVgYnEaYE-nJLBSn4vQ09GSAMlMIfuPVmKCk_vihmcOMTRuBtX_SATVA/s1600/vv.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="544" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEinXNAnrlxz9loZEJPtYoXcT0S43EKBKC3nznsstEgm0yfKM8zGvAHk-SOtljK0DHEAOyLYkBECnYgfhTwaWbFlVgYnEaYE-nJLBSn4vQ09GSAMlMIfuPVmKCk_vihmcOMTRuBtX_SATVA/s640/vv.jpg" width="640" /></a></div>
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Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com0tag:blogger.com,1999:blog-1447795675465650186.post-77869323889089539282012-12-25T11:30:00.001-05:002012-12-25T19:57:49.058-05:00Coupled neural attractorsTowards the end of my PhD I made a second audiovisual rendering of feeding circuit data (the first is quite different and is available <a href="http://www.youtube.com/watch?v=g84z4n9idhc">here</a>)<br />
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<iframe allowfullscreen="allowfullscreen" frameborder="0" height="315" src="http://www.youtube.com/embed/IsdPVL-UZuc" width="560"></iframe>
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For those of you looking to do something similar, this blog post explains how it's done (mainly Matlab). Code and data are available here: <a href="http://www.iplant.eu/code/neuralAttractor.m">neuralAttractor.m</a>, <a href="http://www.iplant.eu/code/nineSpikeRates.txt">nineSpikeRates.txt</a>. Suggested improvements are welcome too.<br />
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<b>Data</b><br />
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The input data for the video is 1000 seconds of spike time data from nine neurons that has been converted into smooth normalized spike rates. The data was recorded from two bilateral triplets of motorneurons and one triplet of 'extra-CPG' neurons that adapt the feeding behavior of the six motorneurons to the availability of food (see <a href="http://dx.plos.org/10.1371/journal.pone.0042493">Harris et al. 2012</a> for details).<br />
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<span style="font-family: Courier New, Courier, monospace;">data = load('nineSpikeRates.txt');</span></blockquote>
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<b>Video</b><br />
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The video is made entirely in Matlab. Use this line to initialize and set the length of the movie<br />
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<span style="font-family: Courier New, Courier, monospace;">videoFrames = moviein(length(data)-10); </span></blockquote>
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Then, <span style="font-family: Courier New, Courier, monospace;">for t = 1:length(data)-10</span>, run<br />
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<span style="font-family: Courier New, Courier, monospace;">dataSegment = data(t:t+9, :);<br />figure(1)<br />plot3(dataSegment(:,1), dataSegment(:,2), dataSegment(:,3), 'o', 'Color', 'r', 'MarkerSize', 30);<br />hold on<br />plot3(dataSegment(:,4), dataSegment(:,5), dataSegment(:,6), 'o', 'Color', 'r', 'MarkerSize', 30);<br />plot3(dataSegment(:,7), dataSegment(:,8), dataSegment(:,9), 'o', 'Color', 'b', 'MarkerSize', 30);<br />axis([0 1 0 1 0 1])<br />grid on<br />videoFrames(t) = getframe(1);<br />close(1)</span></blockquote>
This creates and saves multiple 3D plots showing successive 10 second segments of neuron triplet activity.</div>
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Finally, to save the video, use this line</div>
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<span style="font-family: Courier New, Courier, monospace;">movie2avi(videoFrames, 'videoOut.avi', 'compression', 'none', 'FPS', 10);</span></blockquote>
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<b>Audio</b><br />
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To play music in Matlab I use the Java library JFugue. Download the library <i>jfugue-4.0.3.jar, </i>or whatever is the latest version, from <a href="http://www.jfugue.org/">jfugue.org</a>. Use the following lines to make the library available to Matlab. Note that the javaaddpath command doesn't like to be executed as part of a script - you may get an IMPORT error. To get around this you can run the javaaddpath line manually before you run the script (this is possibly a newbie error on my part).<br />
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<span style="font-family: Courier New, Courier, monospace;">javaaddpath('jfugue-4.0.3.jar')<br />import org.jfugue.Player<br />import java.io.File<br />player = Player()</span> </blockquote>
The JFugue player takes a single long string as input. Each note is represented by an integer between 0 and 127 enclosed in square brackets (JFugue in fact supports a very wide range of musical commands, like 'Cmaj'). For example, try:<br />
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<span style="font-family: Courier New, Courier, monospace;">notes = '[48] [50] [52] [53] [55] [57] [59] Cmaj'<br />player.play(notes)</span></blockquote>
JFugue can play several notes simultaneously. Each channel or 'voice' is indicated by V1, V2 etc. You can specify an instrument for each channel, e.g. I0 for piano, I24 for guitar etc. You'll also want to specify a tempo for the entire string, using T[<i>beats per minute</i>]. For example:<br />
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<span style="font-family: Courier New, Courier, monospace;">notes = 'T[120] V1 I0 [48] [50] [52] [53] [55] [57] [59] [60] V2 I24 [60] [59] [57] [55] [53] [52] [50] [48]'<br />player.play(notes)</span></blockquote>
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To generate the audio for this video I initialized the JFugue string <span style="font-family: Courier New, Courier, monospace;">notes = 'T[600] '</span> and ran the following <span style="font-family: Courier New, Courier, monospace;">for n = 1:3</span><br />
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<span style="font-family: Courier New, Courier, monospace;">notes = [notes horzcat('V', num2str(n), ' I11 ')];<br />for t = 10:length(data)<br /> note = round(mean(data(t,[1 2 3]*n)*30+30));<br /> if note > 30<br /> notes = [notes horzcat('[', num2str(note), '] ')];<br /> else<br /> notes = [notes 'R '];<br /> end<br />end</span></blockquote>
This takes the mean spike rate of each neuron triplet at each time step (<span style="font-family: Courier New, Courier, monospace;">t</span>) and converts it to a bracketed integer between 30 and 60 (a mid-pitch range) unless the spike rate is zero, in which case 'R ' is added, which JFugue interprets as a pause. <span style="font-family: Courier New, Courier, monospace;">t</span> starts from 10 here so that the sound played at each time step will correspond to the front of the 10 second segments of activity used to generate the video frames.<br />
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Use this to save your audio as a midi file<br />
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<span style="font-family: Courier New, Courier, monospace;">filePath = File('audioOut.mid')<br />player.saveMidi(notes, filePath)</span></blockquote>
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<b>Finalize</b><br />
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Now you need to merge video and audio. As far as I know there's no way to do this in Matlab. JFugue only outputs midi files and unfortunately Windows Movie Maker doesn't accept midi, so if that's what you're planning to use to merge you'll need to convert the midi to wav first. I use <a href="http://www.nch.com.au/switch/index.html">Switch Sound File Converter</a> for this. You may need to play around with the number of beats per minute at the head of the JFugue string to get audio that's the same duration as the video, especially if you're using many data points per second. If you play the YouTube movie above to the end you'll see that I didn't get this completely right.<br />
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An example of the video file I get after merging videoOut.avi with audioOut.wav (this is audioOut.mid converted to wav) in Windows Movie Maker is available <a href="http://www.iplant.eu/code/exampleAttractor.wmv">here</a>. Good luck.Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com1tag:blogger.com,1999:blog-1447795675465650186.post-56287912445375260682012-08-23T06:47:00.000-04:002012-08-23T16:33:54.771-04:00What is reward?So I recently passed my PhD viva and got a <a href="http://dx.plos.org/10.1371/journal.pone.0042493">paper</a> published (whoop whoop!). The titles of the two texts are <i>‘Multi-electrode analysis of pattern generation and its adaptation to <b>reward</b>’</i> and <i>‘Multi-neuronal refractory period adapts centrally generated behaviour to <b>reward</b>’</i>. That last word, and my use of it in the texts, caused a fair amount of trouble. I naïvely thought it would be OK to leave the term undefined, seeing as we’re still working out how the brain’s reward system operates. For example, the observation that midbrain dopamine neurons are sometimes activated by stimuli purely by virtue of those stimuli being new and unexpected (rather than appetizing, sexual etc) suggests that novelty itself might be thought of as a reward. And anyway we all have a fairly good intuitive understanding of what constitutes a reward, right? <i>Wrong</i>. I need to define reward.<br />
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Here’s what we ended up writing in the paper following extended skirmish with reviewers:<br />
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<i>"We will refer to… a ‘reward’ in the general meaning of a stimulus that promotes approach and consummatory behaviour rather than the more specific meaning of an unconditioned stimulus used as a positive reinforcer in a classical or operant long-term conditioning paradigm." (<a href="http://dx.plos.org/10.1371/journal.pone.0042493">Harris et al., 2012</a>)</i></blockquote>
I'd like to contrast this definition with Wolfram Schultz's, who writes:<br />
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<i>"A reward is any object or event that generates approach behavior and consumption, produces learning of such behavior, and is an outcome of decision making." (<a href="http://www.ncbi.nlm.nih.gov/pubmed/17600522">Schultz, 2007</a>)</i></blockquote>
Schultz's second condition, that rewards produce <b>learning </b>of approach behaviour and consumption, begs the question: does this refer to conditioning proper, in which memory persists long after the reward is removed, or does an effect on short-term memory suffice? For example, is a food object rewarding merely by virtue of inducing a high and sustained feeding rate, or must it also increase the probability that similar food objects be eaten in the future? This question has physiological consequences: both classical and operant conditioning require brief bursts of spikes in midbrain dopamine neurons (<a href="http://www.sciencemag.org/content/324/5930/1080.abstract">Tsai et al., 2009</a>; <a href="http://dx.plos.org/10.1371/journal.pone.0033612">Kim et al., 2012</a>), whereas the rate and intensity of ongoing behaviour, and the stability of working memory representations, are regulated by the tonic concentration of dopamine, which is set by the number of dopamine neurons engaged in slow pacemaker firing at any given moment (<a href="http://www.ncbi.nlm.nih.gov/pubmed/17031711">Niv et al., 2007</a>; <a href="http://www.ncbi.nlm.nih.gov/pubmed/15539374">Cools & Robbins, 2004</a>). In fact, Schultz's definition of reward <i>does</i> require persistent memory formation, i.e. bursts of dopamine. I disagree. I think a stimulus-induced increase in the rate and intensity of approach and consummatory behaviour can be thought of as a reward-response regardless of whether it produces lasting behavioural change. Yael Niv has for example argued convincingly that the average rate of reward over time modulates tonic background concentrations of dopamine, and thereby adapts the rate and intensity of foraging behaviour (<a href="http://www.ncbi.nlm.nih.gov/pubmed/17031711">Niv et al., 2007</a>). There are many indications that this extends also to non-food rewards. This view is also in accordance with Norman White's, who writes that rewards are stimuli that elicit approach behaviour whereas <i>reinforcers</i> induce memory consolidation (<a href="http://www.ncbi.nlm.nih.gov/pubmed/2682404">White, 1989</a>). Roy Wise similarly notes that 'priming' is an important effect of rewards, but one which does not find its way into long-term memory (<a href="http://www.scholarpedia.org/article/Reinforcement">Wise, 2009</a>).<br />
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Schultz's third condition, that rewards be the outcome of <b>decision making</b>, is also problematic. If this condition is taken to mean that a reward <i>must</i> be the consequence of an overt motor behaviour, as many people would argue, then two objections follow. First, cases of classical conditioning where a neutral stimulus is paired with for example food, producing a subsequent preference for the neutral stimulus, do not involve any overt motor behaviour or action and so cannot according to this definition be said to involve reward. This is in stark contrast to numerous papers that describe such experiments as '<a href="https://www.google.com/search?q=%22classical+reward+conditioning%22">classical reward conditioning</a>' and the food stimuli used as rewards. Second, say you give a hungry rat a food pellet, either at a randomly chosen time or as a consequence of the rat wandering into a pre-defined part of the cage. Do we really want to say that the pellet is a reward in the latter case but not in the former? Physiologically there will be no difference: the dopamine burst response and its effect on synaptic plasticity will be the same. Isn't it in fact the case that brains are <i>always </i>in the process of deciding how to act, and operate by responding to <i>correlations</i> between their own activity states (be they sensory- or motor-states) and varying concentrations of dopamine? Whether or not a reward is <i>in fact</i> the causal outcome of a decision is irrelevant from the perspective of the brain.<br />
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In light of all this, I would suggest the following new definition of reward:<br />
<blockquote class="tr_bq">
<i>A reward is an object or event that induces approach and consummatory behaviour, and produces short- or long-term learning of that behaviour.</i></blockquote>
The lack of reference to rewards necessarily being the outcome of overt decision making constitutes a deviation from the way the term reward is used in everyday language (for example, an unexpected tax-return is a reward according to this new definition), but not, I think, from the way many scientists use the term. One might argue that such stimuli should be referred to as '<i>non-contingent</i> rewards', but, at least in the case of the term 'reinforcement', this approach appears only to have complicated matters (<a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1284187/">Poling & Normand, 1999</a>). Maybe then, we should drop the term reward entirely, and use 'positive stimulus' instead? However, this term has the serious disadvantage of not being a verbal noun. That is, whereas everyone understands the noun 'reward' and the associated verb 'rewarding', there is no established understanding of the (compound) verb 'positively stimulating' that is associated with the (compound) noun 'positive stimulus'. If anything, 'positive' has optimistic or ethical connotations that would jar with the amoral and downright destructive topics often discussed in relation to reward, such as addiction. The term 'appetitive stimulus' (and 'appetitively stimulating') avoids this problem but implies a focus on satisfying bodily needs, particularly hunger, whereas the key property of reward is that it can apply to any desire or goal.<br />
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Have I missed something; some word with the same meaning as 'reward' but better able to match the physiology? Is it time to make up a new word? If not, then I would suggest we stick with reward, using the definition above, accepting it as a slight neologism. The lack of a requirement that a reward <i>necessarily</i> be a consequence of overt decision making or motor behaviour should be appropriately tempered by the understanding that in fact the vast majority of rewards <i>do</i> occur as a consequence of decision making and motor behaviour - specifically as the result of exploration, trial-and-error, or more complex goal-oriented behaviours.<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjkS0iJaj_893w3X0eX0JzGCcG3IU_Z3Nqc_iZhEKXn2jTXPnDu5TSQbGnCc_whte2xElmy73yS7N4JImDcXPjKm79pWx95Y0cvdCsbw_B1gtS3xkA_0abVjzeOI5tZE8ZbL-HmNI4HAwY/s1600/fym.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjkS0iJaj_893w3X0eX0JzGCcG3IU_Z3Nqc_iZhEKXn2jTXPnDu5TSQbGnCc_whte2xElmy73yS7N4JImDcXPjKm79pWx95Y0cvdCsbw_B1gtS3xkA_0abVjzeOI5tZE8ZbL-HmNI4HAwY/s1600/fym.jpg" /></a></div>
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And here we see the fuck yeah monkey upon his mountain of treats!</div>
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(The treats are all rewards provided the monkey has an appetite)</div>
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(h/t <a href="https://twitter.com/theeviluncle">Austen</a>)</div>
Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com5tag:blogger.com,1999:blog-1447795675465650186.post-73896067902362231642012-07-15T13:27:00.003-04:002012-07-15T14:56:03.829-04:00Finding reward in the zebrafish brainIt looks I'll be working a lot with the zebrafish model over the next couple of years, so I've been trying to get my head around its dopaminergic reward system. I was hoping for some clear homologies with the human/mammalian reward system, but the situation is more complex.
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Overall, fish and mammals have similar brain topologies. The fish forebrain pushes forward during development rather than wrapping itself around the lower brain regions as it does in mammals ('eversion' rather than 'evagination'). The fish pallium is nevertheless homologous to the mammalian cortex, with distinct sensory and motor regions, although in fish a disproportionate amount of visual processing takes place in the tectum, a homologue of the mammalian superior colliculus (<a href="http://www.ncbi.nlm.nih.gov/pubmed/12937346">Salas et al., 2003</a>). Likewise, the subpallium of fish corresponds to the mammalian basal nuclei, including the striatum, the key recipient of dopaminergic reward in the mammalian brain. So far so good; most forebrain structures involved in reward processing appear to be conserved among vertebrates, and cognitive abilities previously thought of as exclusive to 'higher' animals (i.e. birds and mammals) are now being studied also in fish (<a href="http://www.ncbi.nlm.nih.gov/pubmed/12937346">Salas et al., 2003</a>).
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<iframe allowfullscreen="" frameborder="0" height="360" mozallowfullscreen="" src="http://player.vimeo.com/video/35210047?title=0&byline=0&portrait=0&color=BDCCD4" style="background-color: white;" webkitallowfullscreen="" width="640"></iframe>
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However, the fish dopamine supply is all over the place, quite literally. Dopamine neurons are found throughout the zebrafish brain, <i>except for</i> the midbrain, where almost all mammalian dopamine neurons are located. A few dopaminergic clusters in the hypothalamic region project to the subpallium/striatum and were previously thought to be homologous to the mammalian mesolimbic dopamine system, but more recent research has debunked this view (<a href="http://www.ncbi.nlm.nih.gov/pubmed/21567980">Schweitzer et al., 2011</a>; <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3105308/">Tay et al., 2011</a>). There simply is no mesencephalic dopamine system in the zebrafish brain. Nevertheless, fish <i>are</i> capable of both classical and operant reward conditionning (<a href="http://rubenportugues.net/valente_et_al.pdf">Valente et al., 2011</a>), including dopamine-dependent place preference, and even intracranial self-stimulation (<a href="http://www.ncbi.nlm.nih.gov/pubmed/13872148">Boyd & Gardner, 1962</a>), so what gives?
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(Figure adapted from the <a href="http://www.ucl.ac.uk/zebrafish-group/zebrafishbrain/tutorial.php">Zebrafish Brain Atlas</a>)</div>
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As far as I can tell, dopaminergic reward mechanisms remain remarkably poorly understood in the zebrafish, despite intense research in recent years on the neurobiology and genetics of this model system. Most of the dopamine in the zebrafish subpallium/striatum appears to originate in local dopaminergic projections from neurons whose cell bodies are distributed throughout the subpallium/striatum (<a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3105308/">Tay et al., 2011</a>). These neurons look like plausible mediators of reward, but their input, physiology and function remains unknown(!). The function of the ascending dopaminergic fibres that project to the subpallium/striatum is also not known. Moreover, pretectal dopamine neurons arborize extensively in the tectum, suggesting a possible role in visually guided reward-seeking behaviour, such as hunting.
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Plenty of reward-related research to be done in other words, but what do we make of this? <a href="http://csjarchive.cogsci.rpi.edu/2006v30/1/s15516709HCOG0000_50/s15516709HCOG0000_50.pdf">Hills (2006)</a> argues that the evolution from anamniotes (fish and amphibians) to amniotes (reptiles, birds and mammals) involved a number of changes regarding dopamine and reward-processing, including:
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<br />
<ul>
<li>The number of cortical imputs to the striatum increased significantly</li>
<li>The number of dopaminergic inputs to the striatum increased significantly</li>
<li>The synaptic machinery that allows dopamine to modulate cortical input to the striatum expanded to include DARPP-32</li>
<li>The dopaminergic signal transitioned from representing the presence of food to representing the expectation of reward more generally</li>
</ul>
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As a consequence of these changes, Hills argues, amniotes were able to apply the neural mechanisms of foraging (e.g. 'area-restricted search', the ancestral function of dopamine, present even in worms and mollusks (<a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2967375/">Barron et al., 2010</a>)) to search for <i>any</i> kind of information or goal, whether internal or external to the brain; a profoundly powerful adaptation. In addition to the four changes suggested by Hills I would add:
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<br />
<ul>
<li>Dopaminergic cell clusters became centralized in the midbrain</li>
</ul>
<br />
This centralization, together with some specific adaptations, such as gap junctions connecting dopaminergic axons, allowed amniote brains to generate a single, scalar reward signal that adjusts dopamine concentrations homogenously throughout the forebrain.
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<br />
I think what I need to ask now is: how does the more ancient dopamine reward system of fish actually work; what forms of reward-processing is it capable of; and does its distributed anatomy offer any advantages to the animal or to attempts to understand the neural basis of reward-based cognition?
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<br />Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com2tag:blogger.com,1999:blog-1447795675465650186.post-81744915240623427002012-07-10T10:01:00.002-04:002012-07-10T10:01:46.606-04:00Back in StockholmSo.. my return to blogging ran into some snags. Had to publish a paper, write my thesis and leave the UK, all in a few months, ergo blogging never got enough juice. But that's all done now: the paper will appear in PLoS ONE shortly and the thesis grew to a reasonable 119 pages in the end. I'm back in Stockholm for the time being but assuming the thesis defence goes alright I'll be starting a postdoc in the US in October. In the meantime I've got loads of reading to do, the highlights of which I'll try to summarize here.<br />
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Until next time<br />
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<br />Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com0tag:blogger.com,1999:blog-1447795675465650186.post-67687010122276606692012-04-14T08:33:00.002-04:002012-04-14T17:34:56.640-04:00Top 10 podcasts<b><a href="http://bloggingheads.tv/">Bloggingheads</a> </b>| Hour long one-on-one, usually about current affairs. Updates 2-4 times a week. Look out for episodes with the founder, <a href="http://www.theatlantic.com/robert-wright/">Robert Wright</a>, they are excellent.<br />
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<b><a href="http://www.slate.com/articles/podcasts/gabfest.html">Slate's Political Gabfest</a></b>
| Every Friday. Editor of Slate Magazine David Plotz, with Emily Bazelon and John Dickerson. The number one podcast on US politics.</div>
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<b><a href="http://www.bbc.co.uk/radio4/features/in-our-time/">In Our Times</a></b> | From BBC Radio 4. Every Thursday morning Melvyn Bragg interviews three guests about anything from Edward Munch to Quantum Gravity. Undisputed master of the History of Ideas, only occasionally challenged by <a href="http://french-italian.stanford.edu/opinions/">Entitled Opinions</a>.
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<b><a href="http://twit.tv/twig">This Week in Google</a></b>
| Wednesdays. Great show. TWiT-founder <a href="https://plus.google.com/101261243957067319422/posts">Leo Laporte</a> discuss the current state of cloud computing Gina Trippani, Jeff Jarvis and a guest. The <a href="http://techcrunch.com/tag/gillmor-gang/">Gillmor Gang</a> covers the same beat with a different tone, less polished, tends to dig deeper, not always to great effect. <a href="http://twit.tv/show/this-week-in-tech">This Week In Tech</a>, the 2-hr flagship show of the TWiT network, available Monday mornings, is sometimes good but often has too much of the everything's-a-joke TWiT humour.</div>
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<b><a href="http://www.bbc.co.uk/podcasts/series/fricomedy">Friday Night Comedy</a></b> | BBC Radio 4 pokes fun at the news every Friday evening. The excellent News Quiz alternates with the less funny Now Show every couple of months (we're currently in a News Quiz phase).</div>
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<b><a href="http://www.bbc.co.uk/podcasts/series/globalnews">Global News</a></b>
| Also from the BBC. Updated twice daily except weekends, including at 2-3 in the morning, which means that the truly podcast-addicted can always start the day here. Somewhat obsessed with interviewing random people about whatever plight they're in.</div>
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<b><a href="http://itunes.apple.com/us/artist/the-economist/id272651214">The Economist</a></b>
| More current affairs. The 'All Audio' edition updates sporadically throughout the week whereas the 'Editor's Highlights' is a one hour block of readings from the latest issue of the magazine released every Friday.</div>
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<b><a href="http://twit.tv/tri">Triangulation</a></b>
| Near-weekly one hour show with Leo Laporte and Tom Merrit. Great stuff if the guest is good and fortunately they manage some seriously good guests, including Steve Martin, Kevin Kelly, Ray Kurzweil, Jeri Ellsworth, the list goes on, check the archive.</div>
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<b><a href="http://www.bbc.co.uk/podcasts/series/stw">Start the Week with Andrew Marr</a></b>
| Monday morning. Hit-and-miss, too much artistic sentiment but occasionally very good (Monday morning, you take what you can get). Nearly got bumped off the list by <a href="http://www.bbc.co.uk/podcasts/series/greatlives">Great Lives</a>, also from the BBC.</div>
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<b><a href="http://twit.tv/fc">FourCast</a></b>
| Futurism from the TWiT network, updated once or twice a month. Only just started listening to this. A bit too light-hearted for my taste but with <a href="http://ieet.org/index.php/IEET/csr">Changesurfer Radio</a> seemingly out of the loop a futurist has to get his fix somewhere. <a href="http://twit.tv/show/futures-in-biotech">Futures in Biotech</a>, also from the TWiT network, works too.<br />
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</div>Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com7tag:blogger.com,1999:blog-1447795675465650186.post-25750573019649135152012-04-04T05:27:00.000-04:002012-04-04T05:27:00.370-04:00Romo the smartphone robotI recently came across 'romo' - a smartphone robot by <a href="http://romotive.com/">Romotive</a> (a recent start-up funded through <a href="http://www.kickstarter.com/">Kickstarter</a>). I love it. I think it's important. As you can see it's a plastic, tank-like little platform, with a panel and a strap for attaching your smartphone (iPhone here but Android works too). Ingeniously the wheels are controlled by output from the audio jack. Different sine wave frequencies applied to the left or right stereo channel trigger forward and backward motion and left/right turns (<a href="http://romotive.com/blog/2012/01/hackers-welcomed-heres-our-protocol/">more info here</a>). The rest is up to the phone, with it's various input (e.g. camera, WiFi, power sensor) and output (e.g. screen, speaker, and now wheels) channels. And the price: $99 (£62).<br />
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From what I've seen so far most people seem to be enjoying remote-controlling their romo from another smartphone. I'm more interested in developing the robot's autonomic behaviour. The 'Darwin' family of brain-based robots for example (Edelman et al., 1992; <a href="http://vesicle.nsi.edu/nomad/darwinvii.html">link</a>) is controlled by a few tens of thousands of artificial brain cells and can explore its environment and see, approach, grab and evaluate objects in a laboratory setting. With the ability of a smartphone to run cloud apps (e.g. identification of objects using Google Goggles), generate and receive spoken commands (text-to-speech, speech-to-text) and reach a wide consumer and developer audience, interesting autonomous robotics suddenly seems tangible.<br />
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<iframe src="//www.viddler.com/embed/9c772b58/?f=1&offset=0&autoplay=0&disablebranding=0" frameborder="0" height="349" id="viddler-9c772b58" width="545"></iframe>Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com3tag:blogger.com,1999:blog-1447795675465650186.post-19195562219790981412012-03-27T15:25:00.002-04:002012-03-27T15:29:37.576-04:00Some papers on structural neurobiologyI've started reading up on structural neurobiology recently. <a href="http://www.nature.com/nmeth/journal/v9/n3/full/nmeth.1854.html">Ragan et al., 2012</a> describes a two-photon microscopy technique that can slice and scan a mouse brain at a resolution of 2 μm^3 in a week. Eight years earlier <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0020329">Denk and Horstmann (2004)</a> presented a similarly automated method for slicing and scanning neural tissue in an electron microscope (EM).<br />
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EM resolutions of about 20 nm^3 allow us to model the complex shapes of individual neurons and synapses. The only brain that has in fact been completely reconstructed in this way though is the tiny nervous system (~300 neurons) of <i>C. Elegans</i> (<a href="http://rstb.royalsocietypublishing.org/content/314/1165/1.abstract">White et al., 1986</a>). This is because reconstructing cell-shapes in 3D, neuron by neuron, from thousands and thousands of grainy images is a very tedious yet difficult job. One solution is to have multiple amateurs work on the same EM data and average their results (<a href="http://www.nature.com/neuro/journal/v14/n8/abs/nn.2868.html">Helmstaedter et al., 2011</a>). Another is to train computers to analyse the EM data for us (<a href="http://www.ncbi.nlm.nih.gov/pubmed/20801638">Jain et al., 2012</a>).<br />
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There are many reasons for developing high-resolution 3D models of brains (<a href="http://www.ncbi.nlm.nih.gov/pubmed/22353782">Denk et al., 2012</a>; <a href="http://www.ncbi.nlm.nih.gov/pubmed/18801435">Lichtman and Sanes, 2008</a>). If we want one day to have computer systems that replicate all the important functions of biological brains we need understand when and why anatomical detail matters. What if for example we assume that all axons and dendrites in a model are cylindrical, or that all synapses have the same geometry; would such simplifications severely disrupt network function? Seems the high-throughput tools we need to answer such questions are only just being made available.Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com1tag:blogger.com,1999:blog-1447795675465650186.post-56730544148560286482012-03-21T07:37:00.000-04:002012-03-21T07:37:03.020-04:00Barbados<div style="text-align: center;">
Decided to start blogging again. It's been a while (541 days). I'm still in Brighton. Got a little over two months left to finish my PhD. A lot has happened with the research, I'll write about it soon as our new paper is in press.</div>
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In the meantime, I just came back from Barbados, here are some pictures :)</div>
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I had a great time. Hadn't been on vacation for years and years.</div>Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com0tag:blogger.com,1999:blog-1447795675465650186.post-58924648351652201042010-09-27T07:08:00.004-04:002010-09-27T17:18:06.031-04:00Open neuroscience talk at the University of Sussex next Wednesday - by me :)I've been asked to give a talk to the <a href="http://alergic.pbworks.com/">Artificial Life Reading Group</a> (Alergic) at the University of Sussex next Wednesday (Oct 6). I'm gonna take the opportunity to articulate my understanding of brains as spiking attractor networks that seek operant control through dopamine-mediated reward learning. This is actually a simple mix of old ideas, but my model system - the buccal ganglia - and experimental technique - the multielectrode array - allows me to quantify and visualize the various components of the theory. I'll also have the opportunity to test some new thoughts on brain-computer interfacing.<br />
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<blockquote><b>Network dynamics, dopamine and operant control: lessons from the molluskan buccal ganglia</b></blockquote><blockquote>Time: Oct 6, 16:30-18:00</blockquote><blockquote>Abstract</blockquote><blockquote>Multielectrode array (MEA) analysis of molluskan nervous systems is an experimental technique recently developed at the University of Sussex (Harris et al., 2010). Here I discuss our current understanding of the molluskan buccal ganglia, with examples from the MEA work, and relate it to more general theories of network dynamics, pattern generation, dopamine-mediated reward and operant control. Variance in the neural pattern for feeding behaviour, which the buccal ganglia continue to generate in vitro, allows the brain to search for optimal feeding strategies in changing environments (Brezina et al., 2006) and can be considered a rudimentary form of free will (Brembs, in press). I argue that this ability to generate variable, reward-sensitive motor output is a central function of brains, and discuss experimental and computational approaches toward a better understanding of it.</blockquote><blockquote>References: Brembs (in press) Proc of the Royal Soc; Harris et al (2010) J Neurosci Methods 186(2):171-8; Brezina et al (2006) Neurocomputing 69(10-12):1120-1124.</blockquote><br />
The talk will be recorded and will hopefully be available on the <a href="http://www.youtube.com/user/iPlantChannel">iPlant channel</a> in a few weeks but please get in touch if you are in the UK and would like to attend the talk (and the enjoyable post-talk discussion in the bar). RSVP on Facebook <a href="http://www.facebook.com/event.php?eid=162507330429060">here</a>.Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com3tag:blogger.com,1999:blog-1447795675465650186.post-693794317827054102010-09-21T09:25:00.000-04:002010-09-21T09:25:46.757-04:00Sackler Centre for Consciousness Science - Facebook Page<iframe allowtransparency="true" frameborder="0" scrolling="no" src="http://www.facebook.com/plugins/likebox.php?href=http%3A%2F%2Fwww.facebook.com%2F%23%21%2Fpages%2FSackler-Centre-for-Consciousness-Science%2F113282278727167&width=292&connections=10&stream=true&header=true&height=587" style="border: none; height: 587px; overflow: hidden; width: 292px;"></iframe><br />
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I recently set up and will now manage the <a href="http://www.facebook.com/#!/pages/Sackler-Centre-for-Consciousness-Science/113282278727167">Facebook Page</a> of the Sackler Centre for Consciousness Science and the Neurodynamics and Consciousness Lab at the University of Sussex. These are interdiciplinary groups headed by Dr Anil Seth. There's also a <a href="http://twitter.com/sacklercentre">Twitter account</a>.<br />
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Part of the mission statement:<br />
<blockquote>How do conscious experience, subjectivity and free will arise from the brain and the body? Even in the late 20th century, consciousness was considered by many to be beyond the reach of science. Now, understanding the neural mechanisms underlying consciousness is recognized as a key objective for 21th century science. Powerful new combinations of functional brain imaging, computational modelling and basic neurobiology bring real hope that human ingenuity can resolve this central mystery of life. Practically, an enhanced understanding of consciousness will transform clinical approaches to a wide range of neurological and psychiatric disorders, from coma to insomnia, from depression and schizophrenia to autism and dementia...</blockquote>More info at the University website: <a href="http://www.sussex.ac.uk/sackler">http://www.sussex.ac.uk/sackler</a>Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com0tag:blogger.com,1999:blog-1447795675465650186.post-39770949344057598312010-09-11T13:08:00.001-04:002010-09-11T13:57:21.898-04:00Spontaneous and dopamine-driven brain activity<object height="385" width="640"><param name="movie" value="http://www.youtube.com/v/g84z4n9idhc?fs=1&hl=en_GB&color1=0x2b405b&color2=0x6b8ab6"></param><param name="allowFullScreen" value="true"></param><param name="allowscriptaccess" value="always"></param><embed src="http://www.youtube.com/v/g84z4n9idhc?fs=1&hl=en_GB&color1=0x2b405b&color2=0x6b8ab6" type="application/x-shockwave-flash" allowscriptaccess="always" allowfullscreen="true" width="640" height="385"></embed></object><br />
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Last weekend I started working on a video aimed at giving viewers a feel for the beauty and complexity of the network activity we record in the lab (see <a href="http://brainimplant.blogspot.com/2010/02/studying-formation-of-patterns-in.html">this</a> entry for details). The trigger for this was meeting a friend who was able to create for me the Java code necessary to run the spike rate data through <a href="http://www.jfugue.org/">JFugue</a>. My own attempts at this had <a href="http://www.youtube.com/watch?v=XC4tRtT5tWs">not</a> been completely successful. Simultaneously, Björn Brembs started posting a series of excellent and quite closely related videos over on <a href="http://www.youtube.com/user/brembs">his</a> YouTube channel, which kept me motivated (also, being able to point to videos from Bill Kristan's lab certainly helped convince my supervisors of the wisdom of the idea).<br />
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There will be more of these, at least I intend for there to be, because it was a lot of fun to make and there are a range of variations and improvements on the audiovisual presentation to explore, as well as a whole bunch of specific topics I'd like to address. But for now, this is it.Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com0tag:blogger.com,1999:blog-1447795675465650186.post-38602000508215263412010-08-21T08:32:00.003-04:002010-08-21T21:34:03.097-04:00Myers vs KurzweilIn a recent <a href="http://scienceblogs.com/pharyngula/2010/08/ray_kurzweil_does_not_understa.php">post</a>, PZ Myers aggressively critizises Ray Kurzweil's prediction that the human brain will be digitally simulated by 2029. Yesterday Kurzweil <a href="http://www.kurzweilai.net/ray-kurzweil-responds-to-ray-kurzweil-does-not-understand-the-brain">responded</a>, restating his belief that the complexity of the brain, though considerable, must not be overestimated. One of Ray's arguments is that the genetic blue-print for the brain is about 50 MB. <i>(Update: Myers has now </i><a href="http://scienceblogs.com/pharyngula/2010/08/kurzweil_still_doesnt_understa.php"><i>responded</i></a><i> to Kurzweil's reply.)</i><br />
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<img src="http://www.iplant.eu/blog/mk.PNG" /><br />
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I'm torn here. Intuitively I agree with Myers: the brain consists of biological tissue and therefore has a theoretically infinite complexity. Our understanding even of a single synapse is for example still very limited, as evidenced by entire <a href="http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1098-2396">journals</a> being dedicated to research on synapses. But there is of course a considerable degree of noise in the brain, suggesting a limit to useful complexity (<a href="http://people.pwf.cam.ac.uk/mds26/cogsci/files/Eliasmith---HowWeOughtToDescribeComputationInTheBrain.pdf">Eliasmith 2000</a>).<br />
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How much of the brain's complexity must we include in digital simulations for them to, say, pass the Turing test? This is where Kurzweil makes mistakes. Phrases and assertions like <i>"the cerebellum (which has been modeled, simulated and tested)"</i> and <i>"We have sufficiently high-resolution in-vivo brain scanners now that we can see how our brain creates our thoughts and see our thoughts create our brain"</i> do indeed indicate that, as Myers puts it, Kurzweil does not understand the brain, and only serve to remind us of Henry Markrams scathing (but accurate) <a href="http://nextbigfuture.com/2009/11/henry-markram-calls-ibm-cat-scale-brain.html">dismissal</a> of the IBM cat brain simulation.<br />
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The issue seems to be this: Kurzweil's successful predictions - the decoding of the human genome, the growth of the internet - concerned discrete systems, where units (base pairs decoded, computers connected) could be clearly defined and counted. Digital simulations of brains are growing exponentially in size and complexity, but we truly do not know <i>how </i>complex they need to be before they can be said to match their biological counterparts. Kurzweil needs to present a scientifically robust theory of brain function before neuroscientists will take his 2029 prediction seriously.Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com1tag:blogger.com,1999:blog-1447795675465650186.post-62058167374867969602010-07-03T11:00:00.007-04:002010-08-04T17:28:47.300-04:00New academic summary (update 4)I just finished writing a new 'academic objectives' blurb for my <a href="http://www.sussex.ac.uk/biology/profile192915.html">university</a>, <a href="http://www.mendeley.com/profiles/christopher-harris1/">Mendeley</a> and <a href="http://www.academia.edu/">Academia.edu</a> profiles. Constructive criticism warmly welcomed.<br />
<blockquote>I'm a DPhil (PhD) student in my final year at the University of Sussex (UK). I'm looking for a post-doctoral research position in the United States or Canada where I can continue working in electrophysiology and learn optogenetic techniques. I'm interested in how brains generate, select and maintain adaptive neural and behavioural activity. This process, particularly the often central role of dopamine-mediated reward-learning, is fascinating in its own right because it's intrinsic to how our lives develop, but its breakdown is also the hallmark of a wide range of psychiatric conditions in urgent need of effective medical treatment.</blockquote><blockquote>For my PhD I have developed a multielectrode technique to interface with a semi-intact invertebrate preparation and study the effects of sensory input, neuromodulators and electrical current on the brain's dynamic repertoire and adaptive output (Harris et al., 2010). Moving forward I want to learn techniques to interface with the mammalian brain and contribute to the development of models and technologies to help patients achieve adaptive neural and behavioural activity; control brain-computer interfaces for example or overcome maladaptive patterns of behaviour. I'm particularly interested in optogenetic photo-stimulation techniques, which have yet to reach clinical trials but already show extraordinary potential to address the theoretical and medical problems I want to work with, including dopamine-mediated reward-learning (e.g. Tsai et al., 2009; Bass et al., 2010).</blockquote><blockquote>References: Harris et al (2010) J Neurosci Methods 186:171-8. Tsai et al (2009) Science 324;5930:1080-4. Bass et al (in press) J Neurochem.</blockquote>Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com4tag:blogger.com,1999:blog-1447795675465650186.post-7831686434763115012010-07-01T07:17:00.000-04:002010-07-01T07:17:56.311-04:00A brain and a robot walk into a bar.. (MEA2010, day 3)Not surprisingly there are a few posters <a href="http://www.nmi.de/meameeting2010/">here</a> on two-way connections between robots and neurons cultured on multielectrode arrays (MEAs). One of them offer an open source software package to do it, called Cult2Robot. The authors use the software to let a culture of neurons on an MEA move a robot in four directions and avoid obstacles, all through a Bluetooth connection. Spike rates in the culture are monitored and whenever they cross a threshold at one of the four edges of the square MEA the robot goes in that direction. If the robot's sensors detect an object in any of the four directions, electrical stimulation is applied to neurons on the opposite site of the array, making them more prone to fire and bring the robot away from the obstacle.<div><br />
<div>It's a simple principle but it illustrates a point I've been <a href="http://brainimplant.blogspot.com/2010/03/brains-as-spiking-attractor-networks.html">trying</a> <a href="http://brainimplant.blogspot.com/2010/02/studying-formation-of-patterns-in.html">to</a> <a href="http://brainimplant.blogspot.com/2009/11/brembs-2006-brains-as-outputinput.html">formulate</a> for months:</div><div><ol><li>Activity in brains and neural networks can be understood as a fixed number of neurons with a spike rate 0-200 Hz (120.000 neurons in this particular culture) </li>
<li>Some patterns of activity result in defined actions (here supra-threshold activity along an MEA edge results in ipsilateral movement) </li>
<li>Some actions are adaptive, others maladaptive, depending on the circumstances </li>
<li>Given adaptive sensory- and/or reward-feedback, neurons change their activity to produce more adaptive output (here objects are avoided by stimulation of neurons with contralateral output)</li>
<li>The number of adaptive activity patterns a network can reliably assume in the context of changing sensory- and/or reward-feedback is a measure of its operant control (in brains we call this creativity, intelligence, self-discipline etc; as an infant learns new words, its operant control increases)</li>
<li>By using sensory- and/or reward-feedback protocols and good electrophysiological or brain imaging techniques we can map the dynamic range of activity states a brain or network can assume and explore/model the network properties that determine its degree of operant control</li>
</ol></div><div>A pressing question is how adaptive various networks can be. Could we for example program the MEA-culture-robot above to move not just in four directions but in the 360 directions of a circle? Could the network learn that certain spatial and/or temporal patterns of network output drive power-moves in the robot (like jumping, climbing or crawling) that scale difficult obstacles, the presence of which might be indicated by specific sensory feedback patterns? The link between specific obstacles and appropriate outputs could be strengthened by application of dopamine... you get the idea. Moreover, to make use of the rich and variable activity of neural networks, they should be given the ability to control the robot's actions along continuums like amplitude, duration, and correlation with other actions. And remember, its not just academic curiosity driving these explorations: a constant theme of this conference has been neural prostheses, and the ability of human brains to generate and respond to many arbitrary patterns of activity along continuums is exactly what gives them the ability to control and respond to brain computer interfaces that restore function and improve lives daily, all over the world, but which are still very immature and problematic.</div></div>Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com0tag:blogger.com,1999:blog-1447795675465650186.post-62664669924814687162010-06-30T07:27:00.001-04:002010-07-03T22:18:37.515-04:00MEA Meeting 2010, day twoI'm in Germany this week, in a sleepy little southern town called Reutlingen, attending the <a href="http://www.nmi.de/meameeting2010/">MEA2010 conference</a>. I'm here to present our most recent work, talk to other MEA nerds and berate Multi Channel Systems employees until they implement basic <a href="http://www.scholarpedia.org/article/Spike_sorting">spike sorting</a> in <a href="http://www.multichannelsystems.com/products-mea/product-details/products/269/mc-rack-2.html">MC_Rack</a>. MEA stands for multielectrode array; the focus of the conference is multi-unit electrophysiology, mostly neural networks cultured on titanium arrays in glass dishes, but the whole spectrum of techniques and analysis methods is represented: yesterday we saw analysis of data from an electrode net the size of a small hand that goes right on the top of the brain, more on that in a bit.<br />
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German is frustratingly close to my native Swedish and yet impossible to understand. Almost. Spielplatz must mean playground, speil sounding like a variant of spel (game in Swedish) and platz like plats (ground in this context, though it really means location). Spielplatz = gameground. In Swedish we say lekplats, lek meaning play. It doesn't help, I'm still a tourist, and the heat is just as bad here as in England. People at the conference are mostly from Europe and East Asia, many languages spoken in the hallways and a lot of poor English (Globish, according to <a href="http://www.bbc.co.uk/programmes/b00stlrh">yesterday's Start The Week</a>). There's maybe 200 people here in the big hall now, though it's still pretty early; leave it to the Germans to serve food and wine until 23:00 and then start talks at 8:30 the next morning. It's ok, my hotel is ten minutes away.<br />
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<div class="separator" style="clear: both; text-align: center;"></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg-z2oCOBEMgIRl2H8VcxACG5oQXl1ZM41Jxl_7FGwUapfbb-ljL10uR1ClvnvUGzInuoPwcCKTgZz6-v1PUqCE9jjB_rvGVaVttkZ5z8BvMj5_oYOwGpIYkkF099dwX6oR9H_5qW23FLc/s1600/Ecog1.png" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg-z2oCOBEMgIRl2H8VcxACG5oQXl1ZM41Jxl_7FGwUapfbb-ljL10uR1ClvnvUGzInuoPwcCKTgZz6-v1PUqCE9jjB_rvGVaVttkZ5z8BvMj5_oYOwGpIYkkF099dwX6oR9H_5qW23FLc/s400/Ecog1.png" width="400" /></a></div>The opening lecture yesterday was by <a href="http://www.ru.nl/neuroimaging/staff/neuronal_coherence/pascal_fries/">Pascal Fries</a> and entitled 'Unravelling the brain-wide web of attention'. It was very good. Fries looks like he could be 25 years old but is a Prof., a P.I. and an M.D. He was showing us evidence that objects are held in visual attention by selective synchronization of distributed but functionally relevant brain regions in the gamma (feed forward, Granger = 0.02) and beta (feed back) bands (and a mystery band at 30 Hz). The data was recorded using a large net of a few hundred 1 mm diameter electrodes placed at 2 mm distance across almost the entire right hemisphere of two monkeys trained to respond to some visual stimuli and ignore others. The stimuli was known to hit specific regions in visual cortex, and activity in these region was subsequently compared with activity across the brain, using the net. The degree of synchrony in the gamma band predicted fast reaction time, so I'm wondering if synchrony in the molluskan buccal ganglia predict feeding rate. In question time I asked him what his thinking was on the mechanism by which the network associated with one stimulus becomes able to entrain others. The answer: given sufficient dopamine and noradrenaline tone, the network will establish coherence by activating interneurons in target regions. Signal-to-noise.<br />
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I actually asked him two questions, and having finished answering the first question he appeared ready to move to another questioner before catching himself and exclaiming "Oh, right, the second stimulus.. eh I mean second question". It's ok man, no need to speak humaneese, we're all neuroscientists here. Anyway, I should pay attention to the talks. Great wireless at a conference is both a blessing and a curse. Mostly blessing though.Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com2tag:blogger.com,1999:blog-1447795675465650186.post-86380904676271497062010-06-20T06:34:00.000-04:002010-06-20T06:34:36.944-04:00Entitled Opinions update<blockquote>"Because to recognize oneself as a material being.. a number of human beings find that too disenchanting a view.. and if that's what it means to recognize myself, I'd rather continue to decieve myself" --Robert Harrison</blockquote><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg2YMBp0hn_ut5KfRX3h8E55JKs1Flpa5vmxc6c7mBuq-opVif8QcbRghEBTEFc3wl1wp7_RqtIa-7AXhR-TI4Hh78yl2_5nyQCMRDtClb_T0fV-plt1PCfiG-zMtqugTntSXGHuwb_KJI/s1600/robert.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg2YMBp0hn_ut5KfRX3h8E55JKs1Flpa5vmxc6c7mBuq-opVif8QcbRghEBTEFc3wl1wp7_RqtIa-7AXhR-TI4Hh78yl2_5nyQCMRDtClb_T0fV-plt1PCfiG-zMtqugTntSXGHuwb_KJI/s320/robert.jpg" width="304" /></a></div><br />
Despite somewhat unfortunate statements such as this, Robert Harrison's Stanford radio program/podcast 'Entitled Opinions' is still going strong. Recent highlights include a <a href="http://french-italian.stanford.edu/opinions/mancall.html">program</a> on Karl Marx, and a <a href="http://french-italian.stanford.edu/opinions/floyd.html">another</a>, with Harrison's brother Thomas, on Pink Floyd.<br />
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Silence must be heard!Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com0tag:blogger.com,1999:blog-1447795675465650186.post-13373508742044677402010-05-28T13:39:00.005-04:002010-12-31T10:59:43.468-05:00First run<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgN3sttxcQYtJ4UeknE9PIyjDZ_mY1kna-ceZjMGQ6OrJYOknJB40QGf4QEEUmiNOMUSNEJIV3ajeviEkVM16vpqlZRX6Tw7pgv_2eo6FdWFykY1eVnVdjnpotYwi00k1XXGZmKvSCvFVI/s1600/runner.jpg" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgN3sttxcQYtJ4UeknE9PIyjDZ_mY1kna-ceZjMGQ6OrJYOknJB40QGf4QEEUmiNOMUSNEJIV3ajeviEkVM16vpqlZRX6Tw7pgv_2eo6FdWFykY1eVnVdjnpotYwi00k1XXGZmKvSCvFVI/s320/runner.jpg" width="132" /></a></div>"I am still your body, you're just a brain!! You have no right..!"<br />
"A brain with electronic motivation", Meg whispered.<br />
"Fuck you!", her body shouted, in its own way, and ramped up lactic acid synthesis. Meg pressed on. It hurt, but the pain was part of her running, and she wanted to run. She'd been running non-stop for almost two hours on the big treadmill in the lab. The <a href="http://brainimplant.blogspot.com/2008/12/riding-bike.html">brain network</a> maintaining her posture, driving her legs, arms and lungs, was lean, mean and optimized. Pressure-sensors in her shoes <a href="http://www.iplant.eu/programming.html">triggered dopaminergic electrodes</a> in her brain with every step; honing, shaping, supporting and reinforcing the neuronal network and its muscle contractions. Interruption was impossible. Tiredness irrelevant. Even pain was part of the purpose, part of her strength, her will, her artificial motivation.<br />
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Lucy stood at the door, watching her. "It's time" she called.<br />
"Noo.." Meg groaned.<br />
"It's time", Lucy said again.<br />
"Fuck!" Meg shouted and punched the stop button on the treadmill. The treadmill started slowing down, and for a moment Meg found herself trying to keep it going, pressing her hands against the railing and pushing her feet against the rubber sheet, harder and harder, the network in her refusing to disassemble, even though the link was lost, the sensors in her shoes inactive.<br />
"Wow" she gasped, between strained gulps of air, and stopped. "Wow."<br />
She released the railing, jumped off the edge of the treadmill and stomped both feet hard against the floor, putting all her weight and strength into it. But the sensors were silent. She groaned again and collapsed on the floor.<br />
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Lucy watched her from the door.<br />
"You ok?" she asked?<br />
Meg rolled over on her back, spread-eagle, and lay panting, staring at the ceiling. "Wow."<br />
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<i>More iPlant fiction <a href="http://www.iplant.eu/fiction.html">here</a></i>Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com0tag:blogger.com,1999:blog-1447795675465650186.post-66013520342911345992010-05-28T13:17:00.000-04:002010-05-28T13:17:24.750-04:00DriftingYou're on a train, staring out the window at power lines, green planes and sky. Your mind wanders. You think of things that happened years ago, people still important in your life. You recall an exchange, you relive the feel of it; embarrassment, adoration, indifference, adventure, but context-dependent and with a specific, complex taste; you're watching rows of hedges, trees and sheep flash by, but in your mind's eye you see streets, places, a room where years ago someone close to you slept. The room most likely remains but you know nothing of the persons living there now; they never enter your mind in any way, why should they? Your friend lives elsewhere now, lives where the train is heading. For three hundred and thirty two seconds your brain attracts around those memories - the room, the bathroom, food and conversations you had there, films you watched - then stops, and you snap out of it, reach for your bottled water, and reconnect with your surroundings; with the people moving or sitting still around you. You don't know why your mind drifted to those particular memories, or what made it stop suddenly - or rather, you DO know, about <a href="http://brainimplant.blogspot.com/2010/03/brains-as-spiking-attractor-networks.html">quasi-stable patterns of brain activity</a>, maintained by dopamine and obvious given your destination - but why that PARTICULAR chain of thoughts and memories, and why the sudden stop? You imagine the dyanmics of your brain, imagine a brain-shaped animation of swirling electrical potential, action potentials, ever-changing, save for brief periods where stable configurations are reached that attract the swirling mass around a recognizable shape, a place, a thought, a memory, before loosing interest and drifting off. You look around again, search the environment for stability, attraction, dopamine. The woman next to you in black, with the clean features, the headphones, the short hair and the eyebrows. The landscape outside, darker now; houses, horses, a town. There's nothing there to keep you, and your mind begins to drift again. It makes you sad, restless, and you put the music back on.<br />
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<img src="http://www.iplant.eu/blog/Bild006.jpg" width="600" />Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com0tag:blogger.com,1999:blog-1447795675465650186.post-76838057668610274022010-05-21T11:32:00.002-04:002010-05-21T11:32:59.404-04:00Craig Venter unveils "synthetic life"<object height="326" width="446"><param name="movie" value="http://video.ted.com/assets/player/swf/EmbedPlayer.swf"></param><param name="allowFullScreen" value="true" /><param name="allowScriptAccess" value="always"/><param name="wmode" value="transparent"></param><param name="bgColor" value="#ffffff"></param><param name="flashvars" value="vu=http://video.ted.com/talks/podcast/CraigVenter_2010P.mp4&su=http://images.ted.com/images/ted/tedindex/embed-posters/CraigVenter-2010P.embed_thumbnail.jpg&vw=432&vh=240&ap=0&ti=863&introDuration=15330&adDuration=4000&postAdDuration=830&adKeys=talk=craig_venter_unveils_synthetic_life;year=2010;theme=to_boldly_go;theme=new_on_ted_com;theme=evolution_s_genius;theme=what_s_next_in_tech;theme=medicine_without_borders;theme=tales_of_invention;theme=inspired_by_nature;event=TED+in+the+Field;&preAdTag=tconf.ted/embed;tile=1;sz=512x288;" /><embed src="http://video.ted.com/assets/player/swf/EmbedPlayer.swf" pluginspace="http://www.macromedia.com/go/getflashplayer" type="application/x-shockwave-flash" wmode="transparent" bgColor="#ffffff" width="446" height="326" allowFullScreen="true" allowScriptAccess="always" flashvars="vu=http://video.ted.com/talks/podcast/CraigVenter_2010P.mp4&su=http://images.ted.com/images/ted/tedindex/embed-posters/CraigVenter-2010P.embed_thumbnail.jpg&vw=432&vh=240&ap=0&ti=863&introDuration=15330&adDuration=4000&postAdDuration=830&adKeys=talk=craig_venter_unveils_synthetic_life;year=2010;theme=to_boldly_go;theme=new_on_ted_com;theme=evolution_s_genius;theme=what_s_next_in_tech;theme=medicine_without_borders;theme=tales_of_invention;theme=inspired_by_nature;event=TED+in+the+Field;"></embed></object>Chrishttp://www.blogger.com/profile/16726301179207891280noreply@blogger.com0