Dr. Frank Werblin at UC Berkeley has dedicated nearly his entire academic life to the study of the eye and visual processing. More recently Dr. Werblin has completed his model of the retinal processing system he has deemed “The Retinal Hypercircuit”. The Hypercircuit itself is made up of the five classical retina cell types: Photoreceptor, Horizontal, Bipolar, Amacrine and Retinal Ganglion Cells, but more recently, a collaborative effort has identified over 50 morphologically different cell types. Of this vast array of unique cell types the most variance falls in the morphology of the Amacrine cells, which offer horizontal properties in the Inner Plexiform Layer between the Bipolar and Ganglion Cells. Although the mechanics behind the Hypercirtuit are fascinating, what I find arguably more important is the output of the system, a topic which Werblin has indirectly stumbled upon, but which I believe could potentially lead to an incredibly progressive line of research.

Amacrine Cell Types

In his studies, Werblin has stumbled upon a couple novel properties of Ganglion Cell output which may hold more information about visual processing than meets the eye. First, he has discovered that the stream of visual information to the brain is actually not a “stream” at all, rather a set of discrete pieces of information sent at different times and with different inherent signal properties. Another finding was that each of the 12 morphologically distinct Ganglion Cells processes only a certain type of stimuli. Perhaps, as an example, one type of Ganglion Cell processes the signal that “something is looming” while another “something is moving to the right”. Although this organization is indeed the work of the Hypercircuit and is mind-blowingly complex, Werblin has shown that the signal leaving the each Retinal Ganglion Cell encodes a certain stimulus quality, discrete in time and purpose. There is a problem with this theory though: We actually perceive a “stream”!

In a recent e-mail correspondence with Dr. Werblin I asked whether there were certain signals that were processed more quickly than others. If you think about it this must be true. When someone jumps out of a bush at night and scares you, you are not at first aware that the person is wearing a red coat, rather that they are there, human and dangerous! This was indeed the response I received from Dr. Werblin. He said enthusiastically, “YES SOME MORE QUICKLY THAN OTHERS” and further that they are probably organized in an evolutionarily advantageous processing order. But again, there is a problem with this, we perceive stream…And not only that but another potent flaw in this discrete logic: If we were to be a constant delay between visual cues, say, we perceive “thereness” before we perceive “color” from birth to death that delay would be constantly growing. Hypothetically, if there were a 0.001ms difference between when we perceive “shape” and “color”, for every second of life we would be adding 0.001ms to the total gap between our perception of shape and color. Visually, we could represent this as two divergent graphs, each having a slope corresponding to the rate at which we perceive that discrete visual quality. As these graphs grow over time they are divergent which means that if our system worked in this simple discrete manner then by late life we would be perceiving the shape of a stimulus, only to receive the color information a day or so later.

Divergence of Visual Stiumulus Quality Arrival Time

So, in essence, it cannot be this simple, there must be something we are missing. Sadly, no research has ever been dedicated to answering this question so for now we can only guess and I think I have a solution that works.

Remember, the visual information is discrete in time and quality. The cut of visual information from the retina to the brain, or what actually makes the signals discrete, is done by a short eye movements called a Microsaccades which occur thousands of times per second. I believe, and again this is all speculation, that these Microsaccades have developed to sync up all of our visual data from all of the different Ganglion Cells. I think that they function to hold the feed of visual information until all of the visual qualities have been analyzed by their respective locations in the brain and the proper reactions have been then initiated. Once our brain has reacted to one of these discrete packages defined by microsaccadic borders our eyes can let up, the saccade can stop, and our eyes can again be soaked in a new set of electromagnetic data for analysis. If we could further analyze which qualities are encoded and sent by the retina in what order we may be able to extract information about downstream processing or evolutionary importance, but until then this idea may have to lie in the realm of mere hypothesis.

Again, I have to stress that this is speculation based on emergent data not intended for this use, but, as a closing remark I would like to mention one thing: When I posited this idea to Dr. Werblin himself he responded with simply, “MAKES SENSE!!!”. Further, for anyone interested in the more detailed workings of the hypercircuit, on The Werblin Lab’s website, which is linked just below, there is a visual walk-through detailing the entire logic and processes behind and within it.

Werblin Retinal Hypercircuit – Werblin Lab

For years, scientists have investigated cases of human brain damage as a means of further understanding the function of specific neural regions, but neuroanatomist, Dr. Jill Bolte Taylor, received the unique opportunity of experiencing this function-impeding damage firsthand. She awoke one morning to find herself having a stroke, and years later has recovered to share the event. Taylor’s unique experience sheds and interesting light on the underlying processes of our fascinating brains. Here is the video (via YouTube):

Sources:

Video Link – Ted.com

Background – DrJillTaylor.com

The world seems as though it is starting to move faster and faster, and thus the demand for information and information accessibility is drastically speeding up as well. Modern computers and related technologies, however, have done a remarkable job with both creating and keeping up with the ever growing demand for data and access people need to it. Perhaps one of the interesting innovations on the scene as of late is the emergence of a new form of information sharing and storing colloquially called “cloud computing”.

The term is probably familiar to many people, but the exact logistics of what the “cloud” is and how it works probably isn’t. On the whole, the “cloud” can most simply be thought of as a network over which computing software, resources and information can be simultaneous stored and shared (a perfect example of such a network being is Internet). While such an idea may seem to demolish the personal aspect of personal computing, the silver lining of the “cloud” is it’s ability to make common resources, such as software, “apps” and data readily available to everyone connected to the network from one (or a few) centralized sources. So, instead of…let’s say…Corporation Corp. needing to buy a new copy of Microsoft Office for every computer they have in their building, they can have the software supported on one central server that everyone in the building can be grated access to use. This goes the same for personal data as well; instead of needing to store everything on your computer’s hard drive, you can just upload it to a “cloud” network and have instant access to it everywhere you get internet service! The implications of this are pretty amazing when you consider how this could transform computing on a commercial level. However, one of the most interesting aspects (in my opinion) of the dawn of “cloud” computing comes in at the personal level, specifically the personal level invested in social networking.

Think about how many people you know that have a Facebook or a Twitter account, host their own blog or a Tumblr, have a Spotify or Pandora account. That’s a lot of people, and more importantly, that’s A LOT of data that each of those individuals has generated about themselves floating about on the internet! While the “cloud” may host hundreds of apps, programs and other services, it also hosts A LOT of information about everyone one of those people you just thought about, and about yourself as well most likely (talk about really living with your head in the “clouds”)! While this may seem innocuous enough, expect for those pictures from the Christmas party on your Facebook profile (“it’s okay, I untagged them!”), media entrepreneur and commentator Adam Ostrow has another very interesting take on the “you in the cloud”:

When you think about it, a lot of what Ostrow is getting at is very true (in a rather creepy, Matrix-y sort of way). There is so much data floating around about you, and specifically you, on the internet that it’s mind-boggling. From all the conversations saved on Facebook, to the constant updates on Twitter, the photos of favorite animals and TV shows on Tumblr, catchy songs played over and over again on Pandora…any way you look at it, the internet “knows” A LOT about you, what you do and what you like. Is is so far fetched to think that a program could be designed with a algorithm in place that could allow it to take all that data about you, integrate, and “predict” what you may tweet or post or play next? Personally, I say it isn’t…and, in fact, as programs and mods that Ostrow talked about show, it’s getting very close to being possible (on a basic level of course)!

But what if we could take this beyond the basic? What if this “digital self” strewn all across the internet could be compiled, fine tuned, and modified to create an “artificial self” that, as Ostrow suggests, lives on after you die or in general just lives as you would based off what it knows about you? Think about it, a holographic you (just like Will i Am…funky!) talking and interacting with people, spurting information about what you would probably do today, what LOL cats you thought were funny and could “re-post” to everyone around you, and your latest opinion on so and so’s new album (“you’ve probably never heard of them”). While this may all seem like a simple novelty today, I think this somewhat unsettling topic taps into an even greater implication: as basis for emergent artificial intelligence.

Our usual thoughts about A. I. probably trail off the realms where cybernetic skeletons hunt for future saviors of the human race, rogue computer programs toy with humans, or sassy pixels guide us to the next waypoint on a map. All in all, A. I. is usually consider something strictly robotic and that has to adhere to what the name suggests: the emergence of autonomous thought or “consciousness” from a purely synthetic construct. Indeed, world spanning endeavors such as the BlueBrain project propose to build a fully synthetic brain as a way to best study it’s mysterious functions and, more importantly, shed some light on the elusive topic of consciousness itself. But what if this “cloud” of information could serve as the rough start of something resembling what we want a robotic organism with a metal brain to be one day? While the thoughts of a “digital persona” may be restricted in the sense that it may not be able to “think” but only predict based off previously catalogued information, who is to say that it can’t get better at this? A tweak here and there (and years of work and research later) and we could have an algorithm that takes this compiled information and extrapolates it, compares it to information and exchanges you share with friends and loved ones and employers by accessing conversations, emails and pictures you shared with them all over the internet, adapting itself and getting better and better at predicting patterns that exist within your “internet autobiography”.

Indeed many simple adaptive learning programs already exist, such as the ones worked on by the CELEST lab here at BU for mimicking and modeling speech patterns and sounds, and at MIT’s Personal Robotics Group for modeling and learning fine motor control and movements (as seen in the facial expressions that can be seen modeled by their Nexi robot). Imagine taking that iSelf and integrating it with a machine that could walk and talk like a human being and let it start “predicting” things you would say based off all the information it can access about you, and learn to mimic your words, your likes, your “thoughts” better and better. It may not be HAL 9000 or Sonny, but in a way it is a certain form of artificial intelligence.

While the prospect of a truly text book artificial intelligence is probably still more feasible in the world of science fiction than science fact, the prospect of the “digital you” is very matter of fact in the real world today. Who knows, if programs and algorithms that compile and store information about you like My Next Tweet, and ifidie evolve and integrate more and more with the web, maybe one day we could see something truly new or “intelligent” evolve out of the data stream in a way no one ever thought possible. Perhaps the concept of a viable “artificial sentience” (fans of Jane in Orson Scott Card’s Speaker for the Dead represent!) is still just as far off…and then again maybe not. If anything though, it may be a good idea to take our heads out of the “cloud” from time to time and truly consider what programs are learning about us, and what information we want to leave for our “digital selves” to compile.

How Cloud Computing Works – How Stuff Works

Role of Expressive Behavior for Robots that Learn from People – Philosophical Transactions of the Royal British Society (Biological Sciences)

A Neural Theory of Speech Acquisition and Production – The Journal of Neurolinguistics

Transforming Robotics with Biologically Inspired Models – Live Science

You’re lying on a sandy beach on a hot sunny afternoon, enjoying a few hours of much needed laziness. As you open your eyes and confront the vastness of the ocean in front of you, light of 600nm wavelength hits your retina, kindling an impossibly long cascade of events in your brain: a molecule called retinal changes shape, neurons fire action potentials down the optic nerve, arrive at the lateral geniculate nucleus deep in the brain causing more action potentials in primary visual cortex in the back of your head, and so on ad infinitum. At some point, the mechanical wonder of 100 billion neurons working together produces something special: your experience of the color blue. What’s special is not that you can discriminate that color from others; nor that you are aware of it and paying attention to it. It is not notable that you can tell us about it, or assign a name to it. It’s that you have a subjective, qualitative experience of the color; there is something it is like to experience the color blue. Some philosophers call these experiences qualia – meaning “what kind” – but it is not important what kind of experience you are having, just that you are having one at all. Modern science hypothesizes that subjective experience is a product of the brain, but has no explanation for it.

The brain’s building blocks are neurons; their language is the action potential, an electrical impulse that relays information. Sensory molecules pick up information about the outside world and translate it into action potentials. The information is processed among many networks of neurons, and returns to the outside world via signals to muscles, which effect behavior. Somewhere between sensory molecules and muscles, the neurons organize to create systems for memory, attention, global access of information, self-awareness and language. How the brain achieves this feat is largely unknown, but neuroscientists are hard at work today trying to elucidate the mechanisms responsible. The philosopher David Chalmers calls these the “easy” problems of consciousness because science has the tools to ask questions about them and eventually solve them.

The easy problems have in common the fact that their explanation requires only a mechanism of their function; once we explain a mechanism by which neurons integrate information, for example, the problem of integration is solved. In contrast, experience, or the existence of qualia, is the “hard” problem of consciousness because it has no obvious function and is completely unmeasurable; science has no way of even proposing hypotheses about it.

Philosophical Zombies

Do you know that feeling you have when you fall in love? Most people describe it as something special, unexplainable, mysterious and wholly wonderful. Scientists will describe it in terms of molecules of oxytocin and vasopressin binding receptors on neurons in the midbrain. Surely love is not just a bunch of molecules running wild in your head? Yes and no. The molecules cause one to exhibit seriously strange behavior like not eating or sleeping, but out of their interactions emerges something more. That something is the feeling itself.

Physical rules and current neuroscientific evidence suggest that the brain should function as it does, but without producing feelings, sensations, or subjective experience; we should be philosophical zombies. Philosophical zombies are hypothetical beings that look and act exactly as humans do, but never actually have first-person qualitative experience of anything.

If a philosophical zombie met a nice girl, he would act as if he were in love. He would talk about his longing and joy, but he would not actually have that qualitative feeling of being in love. Even though they have brains just like ours, philosophical zombies are in essence robots – processing information, reporting mental states, having information of pains or emotions, having functional memory, but never actually having an experience of anything. There is nothing it is like to be a philosophical zombie; all processing goes on in the “subconscious.” This is exactly what science – in its current state – would predict. All cognitive processing should go on “in the dark,” without a conscious element.

Yet we obviously are not philosophical zombies. The processing that goes on in our brains is accompanied by a subjective experience. This experience is the most intimate thing you know – it’s almost impossible to imagine life without it – and for that reason, it is also the hardest thing to question or pinpoint in your own mind. Neuroscience hypothesizes that everything there is to your mind, including this subjective experience, is a product of physical events. But your experience itself is seemingly not physical; there is no thing, energy field, radiation or force that is your subjective experience that we currently know about. All we can measure are molecular events and electrical interactions among neurons. So where does experience come from and how can we study it?

Emergence

The answer may be found in the concept of emergence. From the interactions of a number of matching parts sometimes emerges a behavior or property that cannot be predicted from or reduced to the properties of the constituents. One such unexpected property comes from the simple behavior of individual ants, which produces a complex “society,” whose properties cannot be predicted from the behavior of individual ants. In fact, adding up the contributions of all individual ants does not produce an effect equal to the effect from the ant colony as a whole. Other examples of emergence include snowflakes, which assemble out of interactions among water molecules at low temperatures; temperature, which is based on molecular kinetics; the stock market, which has no central planning or regulation; human society; and subjective experience.

Subjective experience is an emergent property of the brain. As such, it cannot be predicted from our current knowledge of the brain, or reduced to its basal parts. Individual neurons are not aware of anything at all, but 100 billion of them working together are.

Modern neuroscientists aim to peek into the brain at higher and higher spatial and temporal resolutions with the goal of recording the electrical activities of vast numbers of neurons. Once they have recorded the activity, the thinking goes, the only remaining task will be to find out what the activity does. This logic is enticing, but falls short of a explaining the entirety of the brain’s features. One problem is that the entity that emerges – subjective experience – is qualitatively different from neurons and their activities, just as society emerges from interactions among individuals but is qualitatively different from individuals. Moreover, if we were to describe the activities of all individuals that comprise society, we would get no information about society; we would get noise from all the opposing actions. Likewise, if we describe the activities of all the neurons in the brain, all we get is activities of all the neurons in the brain.

An additional barrier is that subjective experience is closed off from outside observation. The contents of your experience are available only to you, and scientists have no way of collecting the data of experience directly. While some neuroscientists are satisfied with collecting first-person data via verbal (human subjects) or behavioral (animal subjects) reports, the fact is that as soon as the subject translates first-person experience into a report, the data becomes of third-person quality.

If aliens discovered earth, they would have no way of knowing that humans had anything going on between their ears beyond electricity and chemistry. This is why neuroscience is so exciting: the most magical machine in the universe is in your head, and we have the opportunity to find out what makes it so special. As neuroscience attracts increasing amounts of talent and funding, we must not forget the most mysterious, least tangible question about the brain.

This post originally appeared on guitchounts.com

A little self-education goes a long way. Let Richard Dawkins enlighten you (and if you’ve seen this already, it’s never a bad idea to brush up on the basics of life):

In the 2009 film Avatar, scientists exploring the planet Pandora used alien hybrid bodies called “avatars” that functioned through a mental connection established with their genetically-matched human counterparts.

While this kind of technology seems as science fictionally fantastic as only the movies can portray it, recent work in the neuro-scientific community may lead the world to think otherwise.  Neu­rol­o­gist Olaf Blanke, with the Brain Mind In­stitute at Ecole Poly­technique Fédérale de Lau­sanne in Switzer­land, led a Virtual-Reality (VR) experiment utilizing computerized “virtual humans” to gain a deeper understanding of the neurobiological basis for the knowledge of one’s location in space.  Interestingly, his team seems to have discovered that the sensation of possessing a body arises as part of our own conscious experience.

Blanke and his team had vol­unteers wear VR stereoscopic visors, or view projections on a large screen, while the researchers challenged them about fundamental aspects of self perception.  The scientists physically touched the subjects ei­ther in sync or out of sync with their dig­ital human “avatars” as they wandered through 3D environments, and even ‘immersed’ them into an avatar of the opposite sex.  They also changed the subject’s perspective from the first to the third-person point of view.  While such methods may seem a bit odd and even unorthodox, the response of the subjects to such testing was both highly positive and truly fascinating.  Indeed, as Blanke commented regarding his own observations: “They start think­ing that the avatar is their own body;  we cre­ated a partial out-of-body experience.  We were able to disas­sociate touch and vi­sion and make people think that their body was two me­tres in front of them”.

Throughout the experiement, subjects were fitted with  electrode-containing skullcaps to record the electrical activity produced by their brains.  The data collected by the electrodes and brain imaging scans (via fMRI) during the study demonstrated a height­ened response in the temporo-pa­ri­etal and frontal regions of the vol­unteer’s brains, areas classically considered responsible for integrating touch and vision.  These findings suggest that the subjects’ brains were successfully being tricked as they experienced their own “bodies” in virtual space.

Progression in the knowledge of self-awareness and virtual reality could lead to major advances in the fields of robotics, neuro-rehabilitation and even severe-pain treatment.  Imagine being able to temporarily “leave” the body as it heals after a serious injury!  Though we may never get to explore Pandora, the implications of such out of body “avatar” experiences could be enormous.

Scientists project humans into avatars – Financial Times

Scientists explore the meaning of self-consciousness – Irish Times

The real avatar – EurekAlert

Stuart Hameroff, MD, is an anesthesiologist and professor at the University of Arizona. In one of many articles and videos about consciousness on the Huffington Post, Hameroff describes how anesthesia can help explain consciousness.

If the brain produces consciousness (all aspects of the term), then it seems to follow that turning off the brain will also turn off consciousness. This is exactly how anesthetics work.

While most anesthetics are nonselective “dirty” drugs, they all produce loss of consciousness, amnesia, and immobility by either opening inhibitory ion channels or closing excitatory ion channels in neurons. The commonly used intravenous drug propofol, for example, acts by activating GABA receptors, the ubiquitous inhibitory channels in CNS interneurons. Brain off = consciousness off.

Hameroff does not subscribe to this. He argues that consciousness is an intrinsic part of the universe and that anesthetics simply disconnect it from the brain. He also thinks that by saying “quantum” a lot, he can scientifically prove the existence of the soul.

What’s scary is that Hameroff has “MD” and “Professor” next to his name. Will Joe the Plumber see through the misinformation?

Don’t take the HuffPost too seriously:

Consciousness and Anesthesia with Stuart Hameroff

Can Science Explain the Soul?

With one neuron missing, you probably won’t notice any perceptual change. But what if, one by one, all neurons in are MT went AWOL? You’d be stuck with an annoying inability to visually detect motion.

Now imagine that for every cell that our fancy ray gun hits, it replaces it with a magical transistor equivalent. These magical transistors have wires in place of each and every dendrite, a processing core, and some wires in place of axon(s). Naturally, the computational core analyzes the sum of all inputs and instructs the axon to “fire” accordingly. Given any set of inputs to the dendrite wires, the output of the axon wires is indistinguishable from that of the deceased neuron.

We can still imagine that with one neuron replaced with one magical transistor, there wouldn’t be any perceptual change. But what happens when more and more cells are replaced with transistors? Does perception change? Will our subject become blind to motion, as if area MT weren’t there? Or will motion detection be just as good as with the real neurons? I am tempted to vote in favor of “No change [we can believe in],” but have to remain skeptical: there is simply no direct evidence for either stance.

Ray guns aside, it is not hard to see that a computational model of a brain circuit may be a candidate replacement of real brain parts (this is especially true considering the computational success of the Blue Brain Project’s cortical column, which comprises 10,000 neurons and many more connections among them). For example, we can imagine thousands of electrodes in place of inputs to area MT that connect to a computer model (instead of to MT neurons); the model’s outputs are then connected, via other electrodes, to the real MT’s outputs, and ta-da!  Not so fast. This version of the upgrade doesn’t shed any more light on the problem than the first, but it does raise some questions: do the neurons in a circuit have to be connected in one specific way in order for the circuit to support perception? Or is it sufficient simply for the outputs of the substitute to match those of the real circuit, given any set of inputs? And, what if the whole brain were replaced with something that produced the same outputs (i.e. behavior) given a set of sensory inputs – would that “brain” still produce perception?