What's New in Neurofeedback

• Neuroscientists Discover Key to Spinal Cord Defects
• Modifying Neural Stem Cells Improves Therapeutic Efficacy
• Synesthetic Experiences are Real and Automatic
• Secrets of the Brain: Researchers Decipher Parts of the Neuronal Code
• Exposure to Young Triggers New Neuron Creation in Females Exhibiting Maternal Behavior
• New Clues Emerge for Understanding Morphine Addiction
• Progesterone as a Treatment Option for Traumatic Brain Injuries
• How the Brain Encodes Memories at Cellular Level
• Could Acetaminophen Ease Psychological Pain?
• Brain Training Can Help Improve Abilities in Older People

Links at http://www.sciencedaily.com/news/mind_brain

 

Jill approaches the edge of a field with an unopened package. As she nears the field, she realizes that she is about to die. She is in perfect health and no one is chasing her, but sure enough her dead body is found in the field later that day.

Why?

Consider the assumptions we make when reading this riddle. Jill, a woman or girl, nears some kind of field -- maybe a meadow or a baseball field -- and she carries a brown box or bag and knows she will die.... it is the assumptions we make, a single wrong assumption, that makes this statement a riddle, a mystery, and to solve this mystery we need to reconsider our assumptions and change one of them. Starting with the first assumption -- Jill, a common name for a woman, and let's assume this assumption is correct, approaches a field...what if it were a minefield? That would make sense. But what about the package? How is that relevant to our mystery? What if the package she held were a bomb? But then why mention a field at all. A good riddle requires all its parts to be part of the solution so carrying a ticking bomb has no bearing on approaching a field so it is not our answer. So we move on. Let's consider the assumption about the field... green grass.... flowers.... flat..... nothing very deadly here.... so let's move on to the next assumption. Let's reconceive not the field but her approach of it. Imagine that Jill nears a meadow not from the East or from the West but from directly above the flora, high above, because she is falling from the sky. Her approach is vertical, not the more common horizontal we assumed. With this change in our assumption, we understand what the unopened package must be: a parachute, undeployed, and her likely demise is now explained.

Here is another riddle: Jamie died in the mountains and Craig died at sea. Everyone was happy with Craig’s death but no one was pleased about Jamie’s.

Why?

Why should we be happy over Craig's death and sad about Jamie's? Was Craig a jerk of monumental proportions, and would that be enough to celebrate his death? Or do we need to reconsider our assumptions again.... Jamie, a man, maybe a woman, or kid, dies in the Rockies, say, and Craig, a man of similar age we suspect, though this assumption may be wrong, dies from falling overboard and drowning perhaps. These assumptions leave us still a-riddled. Let's consider death differently for awhile... and that fails to illuminate the riddle... and it takes awhile but eventually we focus away from thinking about the sea and the mountains and death and instead considering the names themselves, or better put, the process of naming and the variety of things we might give a proper name to. Are all Jamie's young men? Or might we name a pet Jamie? Or an automobile? Or a natural phenomenon? What other things do we attach names to? A quick listing in our heads will lead us to storms and we have our answer. When a hurricane dies at sea, no one is usually injured, but when a large storm crosses land and finally peters out in the mountains, it leaves a path of death and destruction in its wake. We all wish for hurricanes to die before they reach our shores.

Riddle number three: What is unique about this sequence?

8 5 4 9 1 7 6 3 2 0

Numbers have a curious existence. Every number relates to every other in fully discoverable ways. And these relationships rarely change, only becoming more rich with further discovery. Eight is always eternally twice four and one more than seven and one less than nine. It is a product of two times four and two times two times two. It can be broken down into one plus two plus five or six plus two. With numbers come mathematical operations, so looking at this sequence we might consider subtracting adjacent numbers and see if there is a pattern. Eight minus five is three, and five minus four is one, and four minus nine is negative five... so 3 1 -5 and so on... nothing unique here, just random numbers. We can do the same thing with multiplication, multiplying neighboring numbers until it proves fruitless and unremarkable. We can place all the numbers under one, making fractions, and we get 0.125, 0.200, 0.250, 0.111... and no discernable pattern emerges. So let's reconsider our assumptions.

Each numeral is a symbol and symbols have referents, things they stand in place of or point to. Here, 8 refers to eight which refers to a specific size or order in a sequence, but let's step back and think how we translate "8" into words. In English 8 is eight but in French it is huit and ocho in Spanish. If we rewrite the sequence above in Latin, with the help of Wikipedia, we get octo, quinque, quattuor, novem, and so on... we get nowhere, but do this in English -- Eight Five Four Nine One.... with Zero at the end -- and we have the digits in alphabetical order in our common tongue, and that is what is unique about this sequence.

Representation is central to problem-solving and we need to consider what is being represented in following riddle: What starts with the letter E, ends with the letter E, contains only one letter but it is not the letter E?

One solution to this riddle seems to be EYE, as EYE can be written as "I", a single letter, and that makes sense -- almost... as "EYE" is "EYE", not one letter but three! So we need to stretch our brain muscles and thing about representation. In the previous riddle, 8 could refer to a concept of size (eightness) or to another symbol, the word "eight." In this riddle we have to consider how a symbol may have two or more referents, two or more items they encompass. The word "letter" has a number of meanings and allowing it to shift meaning during the sentence will resolve the tension of this riddle. Letters are alphabetical manifestations, and they are also correspondence between parties using paper and envelopes, and here is our answer, the word "envelope" as it starts with the letter E, ends with the letter E, and contains only one letter within, one missive.

It is not the words themselves that create a riddle but our common representations which block proper representation of events or ideas. When we seek out alternative representations, less common conceptions, there is often no riddle to be had. As in this case, riddle #5, we find out that a man heading home encounters two masked men. He turns around to run away, but it is too late! What happened? A script of a robbery pops into our head, but this common idea is not right and we are left pondering what else may be going on. A robbery is too open, too unentertaining to be a riddle. After a bit of puzzling, our thoughts focus on masks and the various types that exist. Masks are worn by a variety of people and for a variety of reasons, not just thugs trying to hide their identity. The Lone Ranger wore a mask to hide his identity, but masks can also be worn for protection. Surgeons and dentists wear cloth masks to protect them from germs and catchers and umpires wear masks to protect them from stray baseballs. The latter fits our riddle... the man heading home has been tagged out.

Our mindsets, our dominant or common representation of events or ideas, can limit our understanding and make it hard for us to see the forest from the trees. A woman had two daughters born on the same hour of the same day of the same year but they were not twins. How could this be so? Just because two daughters are born together, this statement does not limit how many children were born to only two. The answer is that the woman had triplets, or more. Riddle solved. Now consider how Jane was able to hit a homerun over her backyard fence and the ball falls into the middle of a neighbor’s lake and as it’s her only ball she runs to the lake to retrieve the ball. She does this and not only does she not get wet, the ball is not wet despite the fact that the lake is very deep throughout. So how does she avoid getting herself or the ball wet?

This is hardly a riddle in upstate New York when asked on a cold winter's day.

Problems can be conceived as a present state that is not a desired (future) state. Often the way to go from here to there is to change one's representation of the elements and often we find the transition simple. Lakes are wet except when they are frozen. Identical infants are twins except when they are two-third of triplets. Mind sets are the biggest obstacles to problem-solving. Mental sets are entrenchment, categorization that overrides novel representations. In fact we tend to entrench our mental sets by ignoring data that discredits our ideas and highlight confirming evidence, a confirmation bias. Mindsets are forms of fixation, inability to see a problem from a fresh perspective. We have a tendency to think about familiar objects in familiar ways that may prevent using them in more creative ways (e.g., use shoe or book as doorstop), what is called functional fixedness.

There are two problem types, well structured and ill-structured. In well-structure problems there is a clear problem space and path to solution (e.g., area of triangle) but in a so-called ill-structured problem we have a vague problem space and an uncertain path to solution. The search for extraterrestrial intelligence is an ill-structured problem. How do we detect intelligence in other star systems? By the pollution they make in the radio-sphere? Or by checking out the composition of atmospheres in neighboring terrestrial systems?

There are also two general problem-solving techniques, algorithms and heuristics. An algorithm, the basis of computing, can be slow and plodding but it is always accurate, which means we need well-structured problems and total information to proceed to the end. For ill-structured problems we can throw a variety of algorithms at the elements of the problem, but we cannot guarantee success. I like to say I do algorithmic living as a parent to my child, locking doors, closing off electrical sockets, but when it comes to anything biological or social, we are all using heuristics. Heuristics are quick connections from starting point to goal, not always correct, but generally they work well. Heuristics do not need total information, which is more often the case than not in the real world. In most Presidential elections, the taller candidate wins as well as the person with the longer name, arule-of-thumb that predicts most of our elections, better than it should. One of the interesting comparisons of algorithms to heuristic comes from the movies. The homicidal computer in the film “2001: A Space Odyssey” was called the HAL-9000, with Hal being a contraction of Heuristic-ALgorithmic computer, a learning machine, using algorithms heuristically to solve problems (and failing, as Hal kills all of the crew but fails to kill Dave and end up having its power source disconnected).

When it comes to most problems, we can proceed by plodding through its solution space, trying one possible candidate solution after another, or we can leap through it with insight and abruptly land on the surprising solution. Plodding solutions can be visualized nicely by anagrams, a problem of letter rearrangements of common words. For instance, for the anagram "EWT" we can go through the plodding solution spaceand examine all possible rearrangements of these three letters... EWT, ETW, TEW, TWE, WTE... and finally WET, our answer, one of six possible arrangements. With a longer anagram like AABCEILNP, we can run through all possible combinations of the lettering, but it will take hours before we stumble across the answer... or we can leap through the solution space with insight or heuristics, and notice, for instance, how ABLE is part of this anagram. Remove ABLE from AABCEILNP and we are left with ACINP, and pulling out IN and rearranging these letters, we shortly arrive at INCAP which added to ABLE gives us INCAPABLE, the solution of this anagram.

There are two general classes of obstacles to problem-solving, structural and psychological. (Problem properties seem to come in pairs of two, like Noah's beasts.) Structural obstacles are those having to do with the nature or organization of information such as novelty, number of rules, complexity of rules, and counterintuitive rules. The more novel a problem, the harder it is to solve. The more rules, the harder to solve. The more complex, the harder to solve.

The game of chess was invented more than 1,400 years ago and originally consisted of four primary pieces (infantry, cavalry, elephants, and chariotry) which evolved into the modern pawn, knight, bishop, and rook, respectively. We added a queen and a king along the way, which gives us 6 pieces, each with its own movement and capture rules. Now a few general rules about the size of the playing board (8x8 grid), rules for victory and ties, rules about turn-taking, and a few quirky rules like starting pawns and castling rook and king, and we have a game that is to this day unsolved. Computers should eventually solve chess, as it is a finite problem space, but it is taking some time to do this. The size of the finite problem space is very large, about 10 raised to the 50th power or so of possible movement combinations of all possible games, so it may take 100 years or a 1,000, but eventually the game of chess will be solved like tic-tac-toe, wit no possible way of winning against a knowledgeable opponent (with his or her computer guiding or calling each move).

Despite its few rules, the complexity of chess arises from the fact that at each moment in the game a player can make as many as 218 possible moves, and a previous move gives birth to another round of 218 possible moves or so. Even when only a few possible moves are available instead of 218, it is the sequence from one move to the next to the next to the next that creates the large, almost infinite problem space. Exponential growth approaches the infinite but does not reach it.

Whereas chess consists of simple rules, consider the problem of drawing a chessboard on a computer screen. We have the complexity of the hardware running an operating system that controls a variety of computer screens manufactured with numerous specifications and controlled by an application that may call any number of functions to change the colors of the screen in order to draw the checkerboard pattern of a certain size. Mastering the complexity of rules involved in computers have made Microsoft, Apple, and Intel household names.

Finally, now consider counterintuitive rules, those strategies where doing what appears right is wrong. When a woman asks you if she looks good in an outfit, one might think we should look her over and appraise the outfit and her appearance, but as a husband or boyfriend, we soon learn that this behavioral strategy will fail. The counterintuitive rule is to ignore her appearance entirely, disregard any cues or evidence of appearing inelegant in wardrobe, and answer how beautiful she looks.

In addition to structural obstacles, we have numerous psychological obstacles to problem-solving, such as premature commitment to an idea or conclusion; that is, an inability to keep other hypotheses available for later consideration. We often fall into the trap of focusing on an incorrect summation of what is going on or likely to happen, to the exclusion of competing ideas or conceptions. When we gamble, we might think after winning a hand or two at poker or slots that we are on a hot streak and bet more and more money, ignoring the losses as they pile up. We also can suffer from overconfidence, being unrealistically confident in our predictions, especially about our ability to accomplish what we set out to do, and the previous example works to illustrate this issue as well.

We often rely on potentially faulty heuristics such as the availability heuristic, which is estimating the probability of an outcome based on how easy an outcome can be imagined. For instance, when asked which is more likely -- dying from a shark attack or dying from injuries sustained from falling airplane parts, most of us can readily imagine a shark attack and think of times when we read a reports in a newpaper or magazine about an attack off Hawaii or Bermuda but we never hear about blue ice falling from the skies nowadays (from planes purging their dirty toilet water from midair), so we would wrongly assume shark attacks are more frequent, whereas they happen 30 times less often than deaths from airplane parts falling from the sky. We also fall prey to the representativeness heuristic, judging things as being similar based on how closely they resemble each other, even when the resemblance is superficial. If I ask you to guess the profession of Lucy, a woman who wears her hair in bun, lives alone, dresses very conservatively, and loves to read, and give you two choices to choose from: Is she a librarian or a business woman? Most would answer she is more likely a librarian although there are far more businesswomen than woman librarians nowadays, 30 times more. Another faulty heuristics is the anchoring heuristic in which we anchor our guestimations by adjusting from earlier estimations provided to us rather than starting from scratch. If I say that I think a previously-owned Gulfstream jet would be listed for sale on eBay at $2 million, and ask you for your estimate of its likely price, psychologists have discovered that most people will make their estimate close to mine (unless they have specific knowledge). In this example, most would say $2.2 million or maybe $2.5 or $3 million. But if I started us off by estimating a used Gulfstream jet at $7 million dollars and now ask for your estimation, it is likely to be around my guess, much higher than from the previous scenario

Representation of information fixates our ways of thinking about an object or event. Mindsets blind us to solutions. Redefining a problem often solves the problem. When we consider the "War on Drugs" we define our problem with a metaphor full of attack and violence and casualties, with victors on one side, but when we consider the same issue in the context of the effects of poverty on mental health, our problem will be defined differently, and with different results. If we speak of invasions, we consider ourselves invaders, but if we consider the same event a police action, or a peacekeeping mission, or Bush-era liberation, and the goal and problems have changed. We can emphasize one mindset over another with our language -- George Orwell taught us this in his book 1984, which I describe in my article "Vulnerable to Vocabulary," http://start.eegspectrum.com/Newsletter/dec2004.htm#section5

Representation of information is the start of every problem, and re-representation of information is often the solution to our problems. In neurotherapy we have re-represented mental health problems in terms of energy regulation in order to resolve the problem in this domain, with the expectation that solving it in one domain -- normalizing EEG activity or increasing EEG flexibility -- will eliminate the mental health problem.

-DK

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