Review Paper on how the Mind works

Walter Derzko wderzko at pathcom.com
Wed Dec 31 10:53:25 EST 1997

New clues on how the brain works.
Good review article discusses latest work on brain patterning  from recent
Dec 13th New Scientist
I see some interesting implications for optimizing learning and training.

Walter Derzko
Director Idea Lab
wderzko at pathcom.com
(416) 588-1122
[Archive: 13 December 1997]

                        Wild Minds

                    The idea of the brain as a computer
            has thoroughly seduced us. But, says John McCrone,
                 the old grey matter may be just too sloppy 
                         for such a neat metaphor

       STANDING by a pond at London Zoo, grabbing a moment to talk
       shop with an American colleague on what was supposed to be a
       family outing, Karl Friston tried to describe a new vision of the
       brain. Traditional thinking held that the brain was some kind of
       computer, crunching its way through billions of inputs each second,
       outputting consciousness. But said Friston, a theoretical
       neurobiologist at London's Institute of Neurology, it is more as if
       the arrival of those inputs provokes a widespread disturbance in the

       Look, Friston told his Harvard friend, the brain is like this pond.
       You throw in a pebble--the sensory input--and you get ripples.
       That's the neurons responding. Sure, the pattern says something
       about the way the pebble hit the surface. But the pond is already
       covered in ripples caused by other pebbles, so the pattern appears a
       little chaotic. And then once the ripples spread out far enough to
       begin bouncing off the sides, he continued, the shape of the pond
       begins to affect what is going on. The whole thing keeps evolving
       and becoming more complex. 

       Yes, replied his friend, nodding furiously, and as we throw more
       and more pebbles--or rather experiences--into the pond, we change
       the kind of patterns it produces, and even the shape of the pond
       itself. This system has a memory! 

       In the early 90s, in hundreds of private conversations like this,
       scientists were groping their way towards a fresh view of the
       brain--one based on the idea that mental states are dynamically
       evolved rather than clinically computed. Back then, the arguments
       were little more than hand-waving exercises. People were familiar
       with the new ideas about chaos, complexity and nonlinear systems
       coming out of places like the Santa Fe Institute, but unsure how
       they applied to the brain. Today, however, the dynamic revolution
       is beginning to roll. At workshops and meetings around the world,
       researchers like Friston are talking publicly about dynamic models
       of the brain, and the evidence to support the new theories that is
       beginning to fall into place. 

       A replacement for the brain-as-computer model certainly seems
       overdue. The textbook view has been that brain cells are simple
       logic gates, adding and subtracting input spikes until some
       level of charge is breached, at which point they convulse to produce
       a spike of their own. The all-or-nothing nature of a cell's firing
       promised to lift neurons clear of the usual soupy sloppiness of
       cellular processes, allowing the brain to carry out digitally crisp,
       noise-free calculations. 

       The task for researchers was simply to discover how the output of
       each cell encoded a message. In a chase likened to the hunt to crack
       the genetic code, neuroscientists became obsessed with finding the
       "neural code". They tried to discover whether the message was
       contained in the strength of a spike, the average number of spikes
       produced each second, or in the timing of the firing, with
       information carried only on those spikes which were synchronised
       with spikes from other cells (see "Dot dot dot, dash dash dash",
       New Scientist, 18 May 1996, p 40). 

       But the neurons have proved slippery customers. "For 30 years
       we've been going along quite nicely, with lots of expensive
       equipment, lots of expensive people and lots of papers being
       produced, but finally the answers aren't there. We can't even say
       what it is about the spike train of an individual neuron that
       says Rodney Douglas of the Institute of Neuroinformatics in Zurich.
       Much worse for the idea of a simple, crackable neural code are the
       smattering of recent findings which show that the output of any
       individual neuron also depends on what the brain happens to be
       thinking at the time. It's as if rather than the spikes combining to
       produce conscious awareness, consciousness is able to decide how
       the cells should spike. 

       The search for the neural code began in earnest in the 1960s with
       David Hubel and Torsten Wiesel's Nobel prizewinning
       demonstration that certain cells in the primary visual cortex--the
       first part of the higher brain to receive sensory input from the
       eyes--fired only in response to the sight of a line or edge, indeed,
       only to a line of the correct slope. The neurons represented every
       possible orientation of a line at each point of the visual field,
       were lined up in the brain like dots on a TV screen, creating a
       physical "map" of the input from the eye. 

       Other researchers soon showed that cells in different areas of the
       sensory cortex made maps of the frequencies of sound, and even,
       in the case of touch, of the contours of the body. In fact, the
       wrinkled surface of the cortex seemed to be a mosaic of mapping,
       with the primary sensory areas being the first rung of a hierarchy
       processing. The primary maps were reworked, as the message from
       one layer of cells, supposedly encoded in the neurons' spike trains,
       fed into the next. So, for example, about halfway up the visual
       hierarchy, cells might fire in response to movement in a certain
       direction and with a certain speed, or a certain shape of a certain
       colour. Sensory qualities began to emerge. At the very top of the
       hierarchy, neurons would react only to complete objects--say, the
       sight of a face or a hand. Each rung of the hierarchy was built on
       the digital clarity of the spike pattern of the neurons below,
       providing a way for the brain to compute a precise, conscious
       representation of the real world. That, at least, was the theory. 

       The problem was that most of the evidence for the theory came
       from studies of anaesthetised animals whose heads had been
       propped up in front of screens with their eyelids pinned back.
       When, in the late 1980s, researchers developed techniques that
       made it easier to record neural impulses from awake animals, the
       story of brain cells as simple switches, hard-wired to respond to
       line or that movement, changed dramatically. 

       Take an experiment reported in Nature last year by neuroscientists
       John Maunsell, at Baylor College of Medicine in Houston, Texas,
       and Stefan Treue of the University of Tübingen in Germany. They
       studied those neurons about halfway up the visual hierarchy that
       deal with motion, in monkeys trained to watch moving dots on a
       screen. When the monkeys did not have to follow any dot in
       particular, the motion cells simply burst into life each time they
       spotted a dot heading in their preferred direction. But as soon as
       monkeys were asked to concentrate on a single dot--they had been
       trained to do this without moving their heads or their eyes--the
       became picky. When the target dot came into view, the cells went
       wild, doubling their firing rate, while the response from the same
       neurons to non-target dots moving in the correct direction became

       It all makes good psychological sense. The cells turn the volume up
       in response to movement that is the focus of attention, and mute it
       in response to other movement. But it also raises the question of
       how the brain's mental state is managing to transmogrify the cell's
       spike pattern. 


       Neuroscientists dread any hint that something spooky might be
       going on. They try to slide past the problem of the brain's mental
       state interfering with the clarity of the long-sought neural code
       euphemisms such as "selective attention effects" or
       "state-dependent modulations". 

       Yet Maunsell admits that his findings strike to the heart of the
       that the brain works as an input-driven machine: "We are coming to
       the end of one generation of effort," he predicts. "The next
       generation is going to have to look at the whole system [and]
       understand the effect that plans, decisions and actions can have on
       what neurons do." 

       Maunsell and Treue are not the only ones who have been backed
       into a corner by their own data. A rash of similar findings is
       emerging from labs run by the likes of Robert Desimone at the
       National Institute of Mental Health near Washington DC and
       Richard Andersen at Caltech in Pasadena. One team of researchers
       has even found that cells right at the bottom of the visual
       hierarchy--those that take the "freshest" input from the eyes and
       might be expected to be least influenced by the brain's mental
       state--are also at its mercy. 

       David Leopold and Nikos Logothetis, both also at Baylor, reported
       in Nature last year the results of an experiment in which monkeys
       looked through stereoscopic displays so that each eye saw a
       different image--gratings angled in different directions. The brain
       makes sense of such a conflict by allowing the view of one eye to
       dominate: the monkey is consciously aware of seeing only a single

       According to the old view of the brain, the cortex cells that get
       input direct from the eyes shouldn't be involved in the mental
       jiggery-pokery that suppresses the image from one eye--it should
       happen higher up the hierarchy. Instead, Leopold and Logothetis
       found that the firing of about a fifth of cells in the primary
       cortex depended on which image the monkeys signalled they were
       seeing. Even at the lowest level, there was an attention effect. 

       Booming with the enthusiasm of an outsider who is beginning to be
       proved right, Scott Kelso, a dynamicist who studies the brain and
       behaviour at Florida Atlantic University in Boca Raton, claims that
       results like these will only make sense once the old notion of the
       brain processing encoded messages through nothing more than a
       hierarchy of inputs and outputs is abandoned. Instead, he says,
       neuroscience must make a fresh start and recognise that the brain is
       a dynamical system--an organ that evolves its patterns of activity
       rather than computes them. 

       The very word "dynamic" strikes fear into the hearts of many
       researchers, relying as it does on the maths of chaos and complexity
       theory. Jargon such as "metastability", "critical boundaries" and
       "loosely coupled attractors" litters the papers. Still, the
       of the dynamic view stress that a few simple ideas are key. 

       Bursting forth 

       First, says Kelso, stop thinking of neurons as if they are
       messages. Instead (to use another of the hydraulic metaphors
       favoured by dynamicists), the spike patterns of a cell are like a
       whorl erupting in moving water--a local expression of a much wider
       balance of forces. After all, it is no secret that most of the 5000
       input lines to the average brain cell are actually parts of feedback
       loops returning via neighbouring neurons, or those higher up the
       hierarchy. Barely a tenth of the connections come from sense
       organs or mapping levels lower in the hierarchy. Every neuron is
       plumbed into a sea of feedback. The signals coming up the chain
       may provide the seed of a response, but in the end, the cell's spike
       patterns evolve in concert with how the rest of the brain is
       to the stimulus. The spike pattern is less a crisp code and more the
       chatterings of a system forever moving towards an equilibrium. 

       This is good, as it means there is nothing spooky about how
       thoughts and intentions, that is mental states, shape the activity
of a
       neuron, and vice versa. But it does mean that levels of
       consciousness matter, especially if you are trying to make sense of
       a neuron's spike train. 

       When a cell is firing in relative isolation--for example, when an
       animal is unconscious--its response will be at its most hard-wired,
       simple sum of its sensory or lower inputs. Like a ringing phone, the
       neuron will announce that it has a message, but no one lifts the
       receiver to get the conversation going. But as the experiments with
       wide-awake monkeys show, as soon as a cell becomes drawn into
       some greater wave of processing, its firing appears far less
       hard-wired. Of course, it takes time for the wave to build up, which
       is why attention effects usually show up about a tenth of a second
       behind the first exposure to the focus of the attention. 

       The second crucial change needed in the thinking about neural
       processing, say the dynamicists, is to realise that the brain is
       in a state of tension, its circuits drawn tight like the surface of
       Friston's pond. Computer analogies suggest that the brain is a blank
       screen until cells fire to light up a picture. But almost every
       cell is constantly firing, a fact that has long troubled
       There is a steady tick-over of at least three or four spikes a
       even in an area of the brain that seems to be doing nothing. The
       temptation is to dismiss this activity as meaningless, just a
       of current. But dynamicists say the spikes bouncing around the
       brain's connections must be maintaining it at a certain level of
       giving each new input something to disturb in the first place. 

       Going a step further, they argue, this background firing presumably
       creates some meaning. But what? The brain stores memories as
       patterns of connections between cells--new experiences prompt the
       strengthening of old connections, or the growth of new ones. The
       tick-over firing echoing around the brain could be a defocused
       representation of everything you have ever learnt or known. When
       the brain processes new information, it is not a matter of lighting
       dark circuits but of driving a generalised, weakly defined state of
       representation towards a specific one. The brain is always on, it
       needs tuning in. 

       Hot spots 

       As the message of the dynamicists begins to sink in, neuroscientists
       are having to think again about the way they do experiments and
       analyse their data. The most obvious change, says Friston, is that
       researchers must allow enough time to get an accurate fix on what a
       cell is up to. Indeed, to truly understand a cell's firing pattern,
       need to know how far along its feedback trajectory it has gone. At
       the moment, neuroscientists tend to concentrate on a cell's first
       reaction to a stimulus rather than waiting another tenth of a second
       or so until the feedback has had long enough to focus what the cell
       is saying. 

       What's more, in a dynamic scheme, cells apparently saying nothing
       (that show no change in firing rate and therefore go unreported
       when the time comes to write up a research paper) are still
       important. "Rather than talking about a hunt for the neural code, we
       should be talking about a hunt for the metric--the right kind of
       spatiotemporal measure to give the full picture of how a cell's
       response evolves," Friston says. 

       Friston is as good as his word when it comes to his own interest in
       human brain scanning. The standard approach to scanner studies is
       to look for brain hot spots, the bits of the brain that have to work
       the hardest when a subject does some mental or physical task. Like
       20th-century phrenologists, researchers look for the brain bump that
       "does" hand movements or mental imagery. But if the brain really
       works by evolving patterns of connections, then it is how areas of
       the brain, even those that appear quite faint on a scan, join
       over time that tells the true story. 

       As part of a two-day symposium on dynamical neuroscience at this
       October's meeting of the Society for Neuroscience in New Orleans,
       Friston attempted to prove that the distinction between mapping
       brain hot spots and patterns of connections is not purely academic.
       He reported an analysis of brain scan data collected by
       magnetoencephalography, using a method of correlation that
       highlights increases and decreases in activity in different parts of
       brain that occur over the same period. It turned out that high
       activity in an area at the front of the brain called the prefrontal
       cortex, and low activity in an area towards the back called the
       parietal cortex, are tightly coupled just when the volunteer is
       deciding to make small hand movements. Usual methods of analysis
       would have missed the link. What's more, says Friston, it took a
       twentieth of a second or more for this coupling to appear, a clear
       sign that the connection had to evolve. 

       For now, however, dynamicists like Friston and Kelso are keeping a
       sense of perspective. They know that convincing mainstream
       neurobiologists to stop looking for machine-like order in a
       organ that thrives on the creative energy of chaos and feedback is
       going to take more than a few experiments and lots of enthusiasm.
       As Kelso said after the New Orleans symposium: "If we are serious
       about the brain as a self-organising system, then we need new tools,
       new concepts, a new language. Even the way we measure the brain
       has to be different." That process has started, and once it is
       complete, the dynamicists say, neuroscience's golden age of
       discovery will be ready to begin.

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