Paul Fusella - Dynamic Systems Theory in Cognitive Science: Major Elements, Applications, and Debates Surrounding a Revolutionary Meta-Theory

Last week I posted an article that summarized some of the progress in dynamic systems theory and cognitive science over the last 20 years. This article takes up that same topic but examines some of the theoretical debates around the use and validity of dynamic systems theory (a good overview of DNS can be found here).

I am only posting the "Introduction" below, so follow the links to read the whole article (pdf).

Full Citation:
Fusella, PV. (2013). Dynamic Systems Theory in Cognitive Science: Major Elements, Applications, and Debates Surrounding a Revolutionary Meta-Theory. Dynamical Psychology. dynapsyc.org

Dynamic Systems Theory in Cognitive Science: Major Elements, Applications, and Debates Surrounding a Revolutionary Meta-Theory

Paul V. Fusella
January 15, 2013

Introduction

“It is the theory that decides what we can observe.” -Albert Einstein

Dynamic Systems Theory (DST) is a broad theoretical framework imported from the physical sciences and used in psychology and cognitive science in the past several decades that provides an alternative to the computational and information-processing approach that has governed main stream cognitive science since the dawn of the cognitive revolution in the mid-twentieth century (Beer, 2000; van Gelder & Port, 1995; van Gelder, 1998; Spivey, 2007). DST views all psychological processes and capacities as dynamic systems which are best described as complex, non-linear, self-organizing and emergent and whereby cognition develops over the life course and occurs over real-time as a probable description of many possible alternatives instead of linear-assembly-of-symbolic-processes (Spivey, 2007; van Gelder & Port, 1995). Psychological capacities are viewed as emerging as more complex unique forms from prior simpler states, moving from chaotic to more stable trajectories in a theoretical state-space that culminate in the manifestation of a specific thought in real-time or a developmental phenomenon over ontogenesis (Spivey, 2006, Thelen & Smith, 1994; van Geert, 1998). There is a sensitivity to initial conditions and a determination by multiple causality, whereby psychological phenomena, be it a developmental capacity or cognition more generally, are softly-assembled (Thelen & Smith, 2003).

This overarching and revolutionary view for cognitive science has been in the works for quite some time perhaps since the cybernetics movement in the mid-20th century but has become more popular in recent years and has been referred to by a number of different and related labels reflecting related ideas and ranging from chaos theory to complexity theory to nonlinear dynamical systems theory. These titles all refer to similar ideas but have subtle and nuanced differences. I choose to use the term dynamic systems theory because this is the term used by most cognitive scientists who subscribe to this viewpoint and who refer to their movement as the dynamical view in cognitive science and refer to themselves as dynamicists so I will continue with that tradition although the lexicon and conceptual hallmarks used are shared by all these related viewpoints.

Specifically, what I mean by the DST approach in cognitive science (and later to what I refer to as the Complexity Theory (CT) approach) is something also related to work in theoretical computer science and artificial intelligence and empirical and theoretical work done there that applies to some distinct intelligent systems but particularly what it can say about the human mind as an intelligent system. Siegelmann (1997, 2003), Bringsford (2004), Kempis (1991), and Penrose (1990) have described the quintessential hallmark of the DST approach of this particular form of intelligent system as being trans-Turing (or super-Turing) and which possesses hyper-computational capabilities; that is brains and other certain forms of intelligent systems perform processes that go above and beyond the Turing-limit with it’s symbolic-serial processing of the traditional digital computer metaphor that has hallmarked much of the work done in cognitive science and which has been motivated by the information-processing (or computational) perspective. By computationalism I am referring to what has been the dominate theoretical framework in cognitive science since its inception, which has been motivated by the development of the digital computer and principally the work of Alan Turing and the Turing machine, and which uses as a metaphor for the mind, a symbolic-algorithmic-serial-processing digital-computer that computes at or below the Turing-limit.

The argument made by most dynamicists is that DST is a more suitable theoretical framework for situating psychological phenomena because it has achieved success in accounting for other phenomena in the natural world as diverse as meteorological phenomena to kinematics of the human body. The brain and mind are part of the natural world so logically they too can be accounted for by the dynamical view and perhaps more completely and accurately than the traditional computational and information-processing approach with its use of the digital computer as the metaphor for mind. The mind is an abstraction for the neurological underpinnings in the brain and these are not machines they are biological organs made up of cells and organic molecules and they are part of the natural world and could arguably be better accounted for by a meta-theory that has been successful in capturing the diverse natural phenomena that dynamic systems theory has been able to do. I am echoing the argument made by the dynamicists and arguing for a paradigm shift in the sense that Kuhn (1962) described, specifically in cognitive science, as a move away-from the computational, toward a dynamical theoretical framework and paradigm with an recognition that the computations made by the human mind are trans-Turing (or super-Turing) and go above and beyond the Turing-limit of the traditional information-processing approach.

Adopting DST reconciles a lot of the debates in cognitive science surrounding the phenomena that is investigated from monism vs. dualism, nativism vs. empiricism, and subjectivity vs. objectivity, not to mention the various anomalies discovered as a result of adopting a computational viewpoint. DST reorganizes the way that phenomena are studied and conceptualized; where some such as Varela, Thompson, and Rosch (1991) have argued for first person methods in the study of consciousness utilizing methods from traditional Buddhist psychology and which reflects a post-positivist view of how science is conducted. However, others including Spivey (2007), Beer (2000), Thelen and Smith (1994), van Gelder and Port (1995), and Schoner (2008) continue to work empirically with a positivist empirical framework in studying various psychological capacities from a DST perspective and these are the mainstream in the field. Thus, be it the manner in which phenomena are empirically investigated or the manner in which theories are constructed, DST is beginning to be accepted as a viable alternative to the 20th century traditions of computationalism and positivism. DST provides an account of cognitive phenomena that is dynamical, embodied, completely situated and ecologically-grounded and the ways that cognitive scientists go about conducting research and theory building is likely to be influenced by these fundamental aspects to this meta-theory.

In this paper, I will set out to provide an overview of the dynamical approach in cognitive science reviewing the more important work that has been done in recent decades and especially at the turn of the 21rst century. I will focus on a review of two recent debates that were published recently: one in 1998 in the journal Behavioral and Brain Sciences and the other in 2012 in TopiCS in Cognitive Science where contributing scientists debate the legitimacy of the dynamical view. During the review of these debates I will touch on the different facets of DST including work done in embodied cognition and ecologically grounded cognitive phenomena and also work that has been done in applying DST to experiments in psycholinguistics wherein the role of the body, the context, and the environment are united in one framework that is guided by DST.

During this review of the work in the application of DST in cognitive science and reviewing the various formal debates that showed up in peer reviewed journals and discussing them critically, I will echo what others have proclaimed in the past and make the argument that DST is ultimately a more suitable theoretical framework for guiding empirical research and theory building in cognitive science and should at some point in the not so distant future, but especially for moving the field forward in this new century, replace the outdated computational and information-processing approach which appears to have run its course. DST has much promise in providing an overarching and unifying theoretical framework for the cognitive sciences but like anything new it is met with staunch criticisms and rejection. However, the more people that join this movement the more the basic principles embodied in the DST approach will become grounded in empirical evidence. I will begin to conclude the review with a recap of the major controversies that adopting DST provokes from its criticizers and will finish with my modest vision for the future role DST can play in reorganizing the way that science is conducted in the cognitive sciences building off the work that has been done in dynamical cognition from the beginning and reacting against and incorporating within it the good that came from the traditional approaches in cognitive science into the future of what this revolutionary meta-theory means for cognitive science.

Read the whole article (pdf).

Michael Graziano - Consciousness and the Attention Schema

This is Michael Graziano's talk at the Evolution and Function of Consciousness Summer School ("Turing Consciousness 2012") held at the University of Montreal as part of Alan Turing Year. More info below.

Michael Graziano - Consciousness and the Attention Schema

Abstract:

One possible explanation of awareness is that it is a construct of the social perceptual machinery. Humans have specialized neuronal machinery that allows us to be socially intelligent. The primary role for this machinery is to construct models of other people--minds thereby gaining some ability to predict the behavior of other individuals. In the present hypothesis, specific cortical machinery, notably in the superior temporal sulcus and the temporo-parietal junction, is used to build the construct of awareness and attribute it to other people. The same cortical machinery, in this hypothesis, is also used to attribute awareness to oneself. Damage to this cortical machinery can lead to disruptions in consciousness such as hemispatial neglect. In this theory, the value of the construct of awareness, and the value of attributing it to a person, is to gain a useful predictive model of that person--attentional processing. Attention is a style of information processing in the brain in which neuronal signals compete. One interrelated set of signals rises in strength at the expense of others, and thereby dominates the control of behavior. Awareness, in the present hypothesis, is a construct, a useful schema, that models the dynamics and essential properties of attention. To be aware of X is to construct a model of one--attentional focus on X. A brain concludes it is aware of X, and assigns a high degree of certainty to that conclusion, and reports that conclusion, because of an informational model that depicts awareness of X.

Reference Article:

Graziano, MSA, and Kastner, S. (2011) Human consciousness and its relationship to social neuroscience: A novel hypothesis. Cognitive Neuroscience, 2: 98-113. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3223025/

Here is the abstract and introduction to the paper - they raise the possibility that "awareness is a construct of the social machinery in the brain."

Human consciousness and its relationship to social neuroscience: A novel hypothesis

Michael S. A. Graziano and Sabine Kastner
Princeton University, Department of Psychology, Green Hall, Princeton NJ 08544

Abstract:

A common modern view of consciousness is that it is an emergent property of the brain, perhaps caused by neuronal complexity, and perhaps with no adaptive value. Exactly what emerges, how it emerges, and from what specific neuronal process, is in debate. One possible explanation of consciousness, proposed here, is that it is a construct of the social perceptual machinery. Humans have specialized neuronal machinery that allows us to be socially intelligent. The primary role for this machinery is to construct models of other people’s minds thereby gaining some ability to predict the behavior of other individuals. In the present hypothesis, awareness is a perceptual reconstruction of attentional state; and the machinery that computes information about other people’s awareness is the same machinery that computes information about our own awareness. The present article brings together a variety of lines of evidence including experiments on the neural basis of social perception, on hemispatial neglect, on the out-of-body experience, on mirror neurons, and on the mechanisms of decision-making, to explore the possibility that awareness is a construct of the social machinery in the brain.

“Men ought to know that from the brain, and from the brain only, arise our

pleasures, joys, laughter and jests, as well as our sorrows, pains, griefs and tears.

Through it, in particular, we think, see, hear, and distinguish the ugly from the

beautiful, the bad from the good, the pleasant from the unpleasant…”

~ Hippocrates, Fifth Century, BC.

Introduction

A common neuroscientific assumption about human consciousness is that it is an emergent property of information processing in the brain. Information is passed through neuronal networks, and by an unknown process consciousness of that information ensues. In such a view, a distinction is drawn between the information represented in the brain, that can be studied physiologically, and the as-yet unexplained property of being conscious of that information. In the present article a novel hypothesis is proposed that differs from these common intuitive notions. The hypothesis is summarized in the following five points.

First, when a person asserts “I am conscious of X,” whatever X may be, whether a color, a tactile sensation, a thought, or an emotion, the assertion depends on some system in the brain that must have computed the information, otherwise the information would be unavailable for report. Not only the information represented by X, visual information or auditory information for example, but also the essence of consciousness itself, the inner feeling attached to X, must be information or we would be unable to say that we have it. In this hypothesis, consciousness is not an emergent property, or a metaphysical emanation, but is itself information computed by an expert system. This first point raises the question of why the brain would contain an expert system that computes consciousness. The question is addressed in the following points.

Second, people routinely compute the state of awareness of other people. A fundamental part of social intelligence is the ability to compute information of the type, “Bill is aware of X.” In the present proposal, the awareness we attribute to another person is our reconstruction of that person’s attention. This social capability to reconstruct other people’s attentional state is probably dependent on a specific network of brain areas that evolved to process social information, though the exact neural instantiation of social intelligence is still in debate.

Third, in the present hypothesis, the same machinery that computes socially relevant information of the type, “Bill is aware of X,” also computes information of the type, “I am aware of X.” When we introspect about our own awareness, or make decisions about the presence or absence of our own awareness of this or that item, we rely on the same circuitry whose expertise is to compute information about other people’s awareness.

Fourth, awareness is best described as a perceptual model. It is not merely a cognitive or semantic proposition about ourselves that we can verbalize. Instead it is a rich informational model that includes, among other computed properties, a spatial structure. A commonly overlooked or entirely ignored component of social perception is spatial localization. Social perception is not merely about constructing a model of the thoughts and emotions of another person, but also about binding those mental attributes to a location. We do not merely reconstruct that Bill believes this, feels that, and is aware of the other, but we perceive those mental attributes as localized within and emanating from Bill. In the present hypothesis, through the use of the social perceptual machinery, we assign the property of awareness to a location within ourselves.

Fifth, because we have more complete and more continuous data on ourselves, the perceptual model of our own awareness is more detailed and closer to detection threshold than our perceptual models of other people’s awareness.

The purpose of the present article is to elaborate on the hypothesis summarized above and to review some existing evidence that is consistent with the hypothesis. None of the evidence discussed in this article is conclusive. Arguably, little conclusive evidence yet exists in the study of consciousness. Yet the evidence suggests some plausibility to the present hypothesis that consciousness is a perception and that the perceptual model is constructed by social circuitry.

The article is organized in the following manner. First the hypothesis is outlined in greater detail (Awareness as a product of social perception). Second, a summary of recent work on the neuronal basis of social perception is provided (Machinery for social perception and cognition). A series of sections then describes results from a variety of areas of study, including hemispatial neglect, cortical attentional processing, aspects of self perception including the out-of-body illusion, mirror neurons as a possible mechanism of social perception, and decision-making as a means of answering questions about one’s own awareness. In each case the evidence is interpreted in light of the present hypothesis. One possible advantage of the present hypothesis is that it may provide a general theoretical basis on which to understand and fit together a great range of otherwise disparate and incompatible data sets.

Read the whole interesting paper.

Terrence Deacon - Incomplete Nature: How Mind Emerged From Matter

Via Wonderfest: The Bay Area Beacon of Science, neuroscientist Terrence Deacon, who is chair of UC Berkeley's Anthropology Department, delivers an intriguing lecture of the emergence of mind - human consciousness - from matter. Years ago, I read and enjoyed, The Symbolic Species: The Co-evolution of Language and the Brain.

This lecture is based on his new book, Incomplete Nature: How Mind Emerged from Matter, which argues that "key elements of consciousness (feelings, meaning, and purpose, among others) emerge from specific CONSTRAINTS on the physical processes of a nervous system." His is definitely an emergent model of consciousness.


Incomplete Nature: How Mind Emerged From Matter from Wonderfest on FORA.tv

Terrence Deacon - Incomplete Nature: How Mind Emerged From Matter

What are such things as emotion, purpose, and meaning? In this presentation, Terrence Deacon, neuroscientist and chair of UC Berkeley's Anthropology Department, addresses such crucial questions in the study of consciousness.

Professor Deacon's talk will focus on the central idea of his new book, "Incomplete Nature," namely that key elements of consciousness (feelings, meaning, and purpose, among others) emerge from specific CONSTRAINTS on the physical processes of a nervous system.

As physicists work toward completing a theory of the universe and biologists unravel the molecular complexity of life, a glaring incompleteness in this scientific vision becomes apparent. The "Theory of Everything" that appears to be emerging includes everything but us: the feelings, meanings, consciousness, and purposes that make us (and many of our animal cousins) what we are. These most immediate and incontrovertible phenomena are left unexplained by the natural sciences because they lack the physical properties - such as mass, momentum, charge, and location - that are assumed to be necessary for something to have physical consequences in the world. This is an unacceptable omission. We need a "theory of everything" that does not leave it absurd that we exist.

Terrence Deacon

Professor Deacon's research has combined human evolutionary biology and neuroscience, with the aim of investigating the evolution of human cognition. His work extends from laboratory-based cellular-molecular neurobiology to the study of semiotic processes underlying animal and human communication, especially language. Many of these interests are explored in his 1997 book, The Symbolic Species: The Coevolution of Language and the Brain.

His neurobiological research is focused on determining the nature of the human divergence from typical primate brain anatomy, the cellular-molecular mechanisms producing this difference, and the correlations between these anatomical differences and special human cognitive abilities, particularly language. In pursuit of these questions he has used a variety of laboratory approaches including the tracing of axonal connections, quantitative analysis of regions of different species brains, and cross-species fetal neural transplantation. The goal is to identify elements of the developmental genetic mechanisms that distinguish human brains from other ape brains, to aid the study of the cognitive consequences of human brain evolution.

His theoretical interests include the study of evolution-like processes at many levels, including their role in embryonic development, neural signal processing, language change, and social processes, and how these different processes interact and depend on each other. Currently, his theoretical interests have focused on the problem of explaining emergent phenomena, such as characterize such apparently unprecedented transitions as the origin of life, the evolution of language, and the generation of conscious experience by brains. This is fueled by a career-long interest in the ideas of the late 19th-century American philosopher, Charles Sanders Peirce and his theory of semiosis. His new book, Incomplete Nature: How Mind Emerged from Matter, explores the relationship between thermodynamic, self-organizing, evolutionary and semiotic processes and provides a new technical conception of information that explains both its representational and normative properties.

Science News - Demystifying the Mind

Science News ran a cool series of articles throughout February and March on the science of the mind, the nature of consciousness, and what we known and don't know in this realm. Among the topics are consciousness as an emergent property of brain function and the reality of extended consciousness.

Aside from the first, short introductory article, I'm sharing the beginning of each one - follow the title links to read the whole piece.

Demystifying the Mind

A three-part series on the scientific struggle to explain the conscious self

By Science News Staff

Web edition : Monday, February 6th, 2012

Consciousness has posed a special challenge to scientists, but new ways of studying the brain may finally yield a deeper understanding. Science News describes the latest thinking on consciousness in this three-part special report.

The human brain is very good at figuring things out, except about itself.

Think about it. A brain capable of sophisticated reasoning has to be very complicated — so complicated that it would take an even more sophisticated brain to figure out how it works. But an even more sophisticated brain would be even harder to figure out. As the brain gets smarter and smarter, and thus more and more complex, it becomes ever more difficult to explain how it works. The brain can never catch up. Human brains are amazing devices, just not amazing enough to explain all of their amazing abilities.

In truth, the human brain has figured out a lot about how it works. Much of the molecular and cellular machinery underlying thinking and learning and memory, and even emotion, has been outlined in elaborate detail. But dissecting the machinery has not enabled scientists to say why the machine has a persistent sense of itself, how it generates the feeling of self-awareness (and even the awareness of that self-awareness) that people generally refer to as consciousness.

For millennia, philosophers have grappled with consciousness, trying to discern the distinction between mind and body or to show that such a distinction is illusory. But only in the present millennium have scientists engaged these arguments in a serious way, equipped with substantial scientific data.

Science News neurocience writer Laura Sanders has explored the latest efforts by consciousness researchers to demystify the mind and reports her findings in a three-part series. Her account describes how consciousness, long regarded by neuroscientists as a taboo topic, has finally emerged as a legitimate realm of scientific inquiry. Research results have begun accumulating, and theorists have begun transforming explanations of consciousness from philosophical speculations into quantitative concepts and equations.

A common thread connecting much consciousness theorizing is the role of information. Using the mathematics of information theory, scientists have begun to get a grip on possible ways of measuring consciousness, making it easier to identify and perhaps, someday, easier to create in a non-biological information-processing system. The prospect of a conscious computer may be terrifying to fans of the Terminator films (or, for older people, Colossus: The Forbin Project). But it would nevertheless be interesting to see if a conscious machine would be sufficiently sophisticated to figure out for itself how it works. —Tom Siegfried, Editor in Chief

* * * * * * *

Emblems of Awareness

Brain signatures lead scientists to the seat of consciousness

By Laura Sanders

February 11th, 2012; Vol.181 #3 (p. 22)

 

Michael Morgenstern

 

This article is part of Demystifying the Mind, a special report on the new science of consciousness. The next installments will appear in the February 25 and March 10 issues of Science News.

Humankind’s sharpest minds have figured out some of nature’s deepest secrets. Why the sun shines. How humans evolved from single-celled life. Why an apple falls to the ground. Humans have conceived and built giant telescopes that glimpse galaxies billions of light-years away and microscopes that illuminate the contours of a single atom. Yet the peculiar quality that enabled such flashes of scientific insight and grand achievements remains a mystery: consciousness.

Though in some ways deeply familiar, consciousness is at the same time foreign to those in its possession. Deciphering the cryptic machinations of the brain — and how they create a mind — poses one of the last great challenges facing the scientific world.

For a long time, the very question was considered to be in poor taste, acceptable for philosophical musing but outside the bounds of real science. Whispers of the C-word were met with scorn in polite scientific society.

Toward the end of the last century, though, sentiment shifted as some respectable scientists began saying the C-word out loud. Initially these discussions were tantalizing but hazy: Like kids parroting a dirty word without knowing what it means, scientists speculated on what consciousness is without any real data. After a while, though, researchers developed ways to turn their instruments inward to study the very thing that was doing the studying.

Today consciousness research has become a passion for many scientists, and not just for the thrill of saying a naughty word. A flood of data is sweeping brain scientists far beyond their intuitions, for the first time enabling meaningful evidence-based discussions about the nature of consciousness.

* * * * * * *

Self as Symbol

The loopy nature of consciousness trips up scientists studying themselves

By Tom Siegfried

February 11th, 2012; Vol.181 #3 (p. 28)

 

This essay is part of Demystifying the Mind, a special report on the new science of consciousness. The next installments will appear in the February 25 and March 10 issues of Science News.

When Francis Crick decided to embark on a scientific research career, he chose his specialty by applying the “gossip test.” He’d noticed that he liked to gossip about two especially hot topics in the 1940s — the molecular basis for heredity and the mysteries of the brain. He decided to tackle biology’s molecules first. By 1953, with collaborator James Watson (and aided by data from competitor Rosalind Franklin), Crick had identified the structure of the DNA molecule, establishing the foundation for modern genetics.

A quarter century later, he decided it was time to try the path not taken and turn his attention to the brain — in particular, the enigma of consciousness.

At first, Crick believed the mysteries of consciousness would be solved with a striking insight, similar to the way the DNA double helix structure explained heredity’s mechanisms. But after a while he realized that consciousness posed a much tougher problem. Understanding DNA was easier because it appeared in life’s history sooner; the double helix template for genetic replication marked the beginning of evolution as we know it. Consciousness, on the other hand, represented evolution’s pinnacle, the outcome of eons of ever growing complexity in biochemical information processing.

“The simplicity of the double helix … probably goes back to near the origin of life when things had to be simple,” Crick said in a 1998 interview. “It isn’t clear there will be a similar thing in the brain.”

In fact, it has become pretty clear that deciphering consciousness will definitely be more difficult than describing the dynamics of DNA.

* * * * * * *

Consciousness Emerges

Somewhere along a tangled path, sights, sounds and insights pop into awareness

By Laura Sanders

February 25th, 2012; Vol.181 #4 (p. 18)

 

Michael Morgenstern

 

Demystifying the Mind
This feature is the second installment in a three-part series on the scientific struggle to explain consciousness. To read the previous installment and see what’s in the next issue, click here. 


In one of science’s most iconic moments, Isaac Newton’s eye caught the red glint of an apple as it plunged toward the ground. He heard the leaves rustle in the light breeze and felt the warmth of the tea he was drinking at the time.

These sensory inputs streamed into his brain, where they met his vast stores of knowledge, his internal musings, his peculiar brand of curiosity and perhaps even a fond recollection of escaping the ground’s hold while climbing a tree as a boy. All at once, sights, sounds, emotions and memories converged to form a whole, rich experience in the garden that day.

It was this fortuitous experience — perfectly ripe for a big idea — that (legend has it) caused Newton to wonder why the apple fell not sideways or even upward, but straight down. Inspiration struck, ushering in a new understanding of gravity.

Newton gets the glory for figuring out that the same mysterious force pulls planets toward the sun and apples toward Earth, but how he did it hinges on an even deeper mystery: How his brain created a single, seamless experience from a chaotic flux of internal and external messages.

And that mystery isn’t confined to brains like Newton’s. In all conscious people, the brain somehow gives meaning to the external environment, allowing for thought, self-reflection and discovery. “It’s not that conscious experience is one little interesting phenomenon,” says neuroscientist Ralph Adolphs of Caltech. “It’s literally the whole world.”

* * * * * * *

Enriched with Information

New theory doesn’t limit consciousness to the brain

By Laura Sanders

March 10th, 2012; Vol.181 #5 (p. 22)

 

Michael Morgenstern

 

Demystifying the Mind
This feature is the final installment in a three-part series on the scientific struggle to explain consciousness. To read the entire series, click here.


As a scientist, Giulio Tononi’s goal is as lofty as it gets: He wants to understand how the brain generates consciousness. In his hunt, he and colleagues at the University of Wisconsin–Madison routinely use state-of-the-art brain scanners to produce torrents of information that stream into sophisticated computer programs describing various aspects of brain function.

But Tononi’s most profound insight didn’t spring from this huge cache of scientific data. It came instead from a moment of quiet reflection. When he stepped away from his scanners and data and the hustle of the lab and thought — deeply — about what it was like to be conscious, he realized something: Each split second of awareness is a unified, holistic experience, completely different from any experience before or after it.

From that observation alone, Tononi intuited a powerful new theory of consciousness, a theory based on the flow of information. He and others believe that mathematics — in particular, a set of equations describing how bits of data move through the brain — is the key to explaining how the mind knits together an experience.

Because of its clarity, this informational intuition has resonated with other researchers, inspiring a new way to see the consciousness problem. “This insight was very important to me,” says Anil Seth of the Sackler Centre for Consciousness Science at the University of Sussex in Brighton, England. “I thought, there’s something right about all this.”

TEDxUHowest - Fabien Pinckaers - Open source as a mature example of emergent collectives

Open Source is the future of cooperative learning, business, research, and community - nice talk.

Open source as a mature example of emergent collectives

Fabien Pinckaers is the founder and CEO of OpenERP, an open source business applications company. His talk is about how open source communities can leverage their cooperative business model to compete in a market that is crowded with commercial players. Open source collaboration gives an edge to innovative early market players.