Psycho-neuromuscular Literature Review
by Timothy Winey
Anxiety and the Yips - The Mayo Clinic (summary)
1. The Mayo Study
The Sports Medicine Center of the Mayo Clinic (MCSMC) in Rochester, Minnesota, studied the yips in golf (Smith et al., 2000; Mayo Clinic, 2000). The study focused on anxiety and neuromuscular movement disorders that have wide applicability to other sports. Previous researchers have classified yips as an occupational focal hand dystonia, a type of movement disorder apparently caused by degeneration of neural circuitry following decades of the same hand movement. The Mayo Clinic team departed from earlier researchers by assigning a prominent role in the etiology of the yips to psychological rather than neurological factors. They also opted for a behavioral definition of yips that does not distinguish between the contributions of anxiety and dystonia.
The team used four criteria to assess whether subjects were affected by the “yips:”
the golfer was previously a good putter, so the condition is acquired;
the yips are episodic (considered to be consistent with dystonia);
the yips have prompted the golfer to change putting technique in search of relief;
and the change in technique yielded at least temporary improvement in performance (Smith et al., 2000).
Actual physiological data during putting was gathered only from seven respondents, measuring heart rate (ECG), grip force (GF), and muscle activation patterns (EMG). Of these, only four self-reported as yips-affected. The four affected golfers exhibited higher heart rates, grip force, and EMG excitation than non-affected golfers. While the data allow dissociation of these four golfers from non-affected golfers in terms of the physiological signs, the physiological data fail to discriminate between effects due to anxiety versus neuromuscular dysfunction.
Practically speaking, it wouldn’t matter what caused the “yips” or even if there was 100% consensus on defining such a thing as “yips”, if a new putting paradigm could be demonstrated to return golfers to former putting skill levels or, better yet, improve upon them. It would be analogous to endlessly debating the causes of heart disease while a high risk population reversed angina by taking a vitamin supplement (already proven to be safe) without the scientific community being able to explain its precise mechanism of action.
Another study, conducted by Lewis and Linder also found that
decrements in performance could be alleviated through the use of a distractor (in this case, counting backward from 100) during real-time performance. Lewis and Linder suggested that attending to the distractor during on-line performance under pressure prevented participants from focusing attention inward on skill execution processes, thus alleviating the possibility of choking due to the "self-focus mediated misregulation" (p. 937) of performance. As can be seen from the literature just described, the notion that performance pressure induces self-focused attention, which in turn may lead to decrements in skill execution, is now a reasonably well-supported concept for proceduralized skills. In conclusion, the findings of the four experiments in the present study lend support to the notion that pressure-induced attention to the well-learned components of a complex, proceduralized skill disrupts execution.
Future research in this area is needed in order to illustrate the precise nature of the control structures that lead to decrements in performance under pressure. In addition, the generalizability of the present results to other task types and to different levels of practice must also be assessed. Further exploration of both the task and learning environments that mediate the pressure-performance relationship will serve to enhance our understanding of the choking under pressure phenomenon, which stands as an intriguing exception to the general rule that well-learned skills are robust and resistant to deterioration across a wide range of conditions.
It is asserted that the increased sensory awareness accompanying added weight provides a kind of “reassurance-distractor” for the golfer in the sense that it (the weight) provides enhanced (more ongoing) neuromuscular input about the indirect relationship of hands to putter head (relating to each other’s position, direction and velocity through the weight rather than directly), allowing the golfer to become less self-conscious about the grip/putter head relationship, helping to focus attention on “quality of stroke” rather than the instinctive “hitting” of the ball. It also allows for more detectable sensory input earlier in the putting stroke due to the added weight’s more pronounced pressure increases and decreases transmitting through the hands, allowing for finer adjustments to the stroke in a more instinctive and non-critical or excessively self-conscious way more ongoingly; that is to say, with a more real-time analysis and adjustment of the putting stroke, effectively shortening and amplifying the feedback loop of pressure variations in the grip, as the weight is lifted and dropped during the stroke.
Further investigation of potential relevant physiological factors such as grip force (GF), and muscle activation patterns (EMG) and their possible relationship to brainwave frequency variations correlating with differing techniques may be warrented.
Debra Crews and others (Linder et al., 1998), conducted a study on stress and putting, where the initial study consisted principally in taking a State-Trait Anxiety Inventory of golfers under simulated pressure. Ten college-student golfers with an average of 5.2 years of golfing experience and a mean scoring average of 90.1 strokes were tested. (Subsequently, Dr. Crews obtained EEG readings and prepared a composite image of golfer brains showing chokers and non-chokers.) The task was a trial of 20 five-foot putts for baseline, followed by a second trial of 20 putts on condition that the golfers who improved won $300 while golfers who performed worse than baseline would have to pay $100. Five did better, and five did worse (Linder et al., 1998; Abrahams, 2001).
The 1998 report simply concluded that anxiety was associated with performance decrement, and experience with pressure helps. (Linder et al., 1998) In the separate EEG study, Dr Crews compared EEG images of golfers in the trial and concluded that successful golfers had increased cortical activity just like unsuccessful golfers, but the activation was spread evenly over both hemispheres of the brain, whereas activation for unsuccessful golfers concentrated in the left (dominant) hemisphere (Abrahams, 2001).
Dr. Crews interpreted the increased left-brain EEG activity as anxiety-related and interpreted the successful golfer's brain pattern under pressure as the consequence of employment of right-brain processes that were better suited to "handle" the added pressure. In keeping with this analysis of handling pressure, Dr Crews teaches "right-brain" golf by encouraging golfers to use imagery, relaxation techniques, and target focus as ways to promote right-brain activation and therefore hemispheric balance.
So-called « Right Brain » golf may be an oversimplification. According to the eminent Harvard Psychiatrist Dr. Frederic Schiffer, author of the groundbreaking book, Of Two Minds (ISBN 0-684-85424-4), Stress is more accurately characterized as a manifestation of asymmetric storage of negative experience in either hemisphere, defining lower stress as a healthy communication between the stressed hemisphere (which could be either left or right) and the non-stressed hemisphere. Thus, an absence of stress may be more accurately characterized by inter-hemispheric synchrony rather than hemispheric dominance.
An overview of a study by Wright, J. et al, (2001), (reproduced below) summarizes their attempt to characterize brain activity by simplifying its behavior through representative models that do not become unmanageably complex as with traditional methods that, they assert, are unsuitable for mathematical analysis and hence, of limited utility.
Abstract.
Continuum models of cerebral cortex with parameters derived from physiological data, provide explanations of the cerebral rhythms, synchronous oscillation, and autonomous cortical activity in the gamma frequency range, and suggest possible mechanisms for dynamic self-organization in the brain.
Dispersion relations and derivations of power spectral response for the models, show that a low frequency resonant mode and associated traveling wave solutions of the models' equations of state can account for the predominant 1/f spectral content of the electroencephalogram (EEG). Large scale activity in the alpha, beta, and gamma bands, is accounted for by thalamocortical interaction, under regulation by diffuse cortical excitation. System impulse responses can be used to model Event-Related Potentials. Further classes of local resonance may be generated by rapid negative feedbacks at active synapses.
Activity in the gamma band around 40 Hz, associated with large amplitude oscillations of pulse density, appears at higher levels of cortical activation, and is unstable unless compensated by synaptic feedbacks. Control of cortical stability by synaptic feedbacks offers a partial account of the regulation of autonomous activity within the cortex.
Synchronous oscillation occurs between concurrently excited cortical sites, and can be explained by analysis of wave motion radiating from each of the co-active sites.
These models are suitable for the introduction of learning rules - most notably the coherent infomax rule.
1. Introduction.
The operation of the brain requires the coordinated interplay of billions of neurons via their synapto-dendritic couplings. The development of a concise mathematical description of this interplay is a major goal of neuroscience, but attempts to attain this goal encounter problems of a fundamental nature.
What are the essential cellular properties needed to account for the local cell pulse characteristics, and the macroscopic fields (notably the electroencephalogram (EEG)) emitted by the working brain? How are the observable pulses and fields related to information processing in the brain? Which are the essential features of the brain's gross anatomy which need to be taken into consideration? How do the dynamics of neurons interact with growth and other plastic modifications, to enable adaptive learning?
Accounts of interactions within populations of neurons have generally utilized neural network methods, in which the elementary units considered are the neurons (eg, Amit et al 1990; Arbib et al 1998; Traub et al 1996; Whittington et al 1995; Lumer et al 1997a,b; Wilson and Bower 1991). Despite their many virtues, such models are limited by the rapid increase in their numerical complexity as the scale and detail of simulation is increased. This complexity also generally makes them unsuited to mathematical analysis.
This paper describes the current attempts being made by our group to account for the dynamics of the brain in as simple a way as possible. We utilise continuum modeling methods pioneered in the works of Freeman (1975), Wilson and Cowan (1973), Nunez (1981, 1995) , Lopes da Silva (van Rotterdam et al 1982 and subsequent), Haken (eg, Jirsa and Haken 1996), Zhadin (1994) and others. Our work has been guided also by the following principles:
We have attempted to fit all simulations and analyses within a simplified conception of the brain's overall organization, with a view to achieving logically compatible models of brain dynamics at all spatial scales.
We assume that at microscopic scale neuronal interactions are highly nonlinear and discrete, yet at macroscopic scale observable fields such as the EEG emanate from a stochastic and essentially linear continuum. (Wright 1990; Wright and Liley 1996). This means that well established linear methods can be used to aid analysis of properties often initially demonstrated by numerical simulations.
Parameters (dendritic time constants, synaptic densities, etc.) compatible with independent physiological estimates (eg, Braitenberg and Schuz 1991, Thomson et al 1996, Thomson1997, Liley and Wright 1994, Rennie et al 2000a) are used to constrain model fitting to experimental data.
Drs. Eugene Peniston and Paul Kulkosky's (1989, 1990, 1991) pioneering work showed that training chronic alcoholics to increase the lower-frequency alpha and theta brain waves, while controlling the higher frequency beta waves, resulted in significantly less depression, less craving for alcohol and less relapse. (The alpha brain wave has been associated with a tranquil, serene state, while the theta wave corresponds to a deeper meditative state.)
The researchers' treatment protocol includes 6-8 weeks of thermal biofeedback and autogenic training, followed by 30 sessions of evoked images of personal change and alpha-theta EEG biofeedback. The sessions are performed twice a day, five days a week.
The results of the therapy have been nothing short of remarkable--80 percent short-term effectiveness, with ongoing studies tracking the long-term results. The training resulted not only in decreases in alcoholic behavior (relapse, cravings, etc.) but changes in a wide range of dysfunctional personality factors (Peniston & Kulkosky, 1990). The training even affected blood chemistry: serum Beta-endorphin levels increased in patients who completed alpha-theta brain wave training (Peniston & Kulkosky, 1989).
What accounts for these changes? The current theories behind alpha-theta brainwave training are documented in an excellent article by Jonathan D. Cowan, Ph.D. in the Megabrain Report: The Journal of Mind Technology (Vol. 2, No. 3). Cowan suggests that the power of the imagery instructions given prior to the EEG training, in which patients rehearse new intentions and positive alternatives, should not be underestimated. "These images of personal change are experienced in a relaxed state, followed closely by the effect induced by alpha-theta biofeedback, which is usually very pleasant. This forms an association between the images and pleasant effect which is repeated 30 times throughout the course of therapy.... The power of [the] ... training my be partly due to inputting images and suggestions in such a way that they bypass the conscious mind, thereby benefiting from the lack of interference from adult disbelief and disempowerment."
Brainwave frequencies can actually be induced by tricking the brain into tuning itself to a difference between two tones delivered to the ears, commonly termed binaural beat stimulation.
Science ushered in a new era in our ability to learn, be creative, remember, control our moods, reduce stress, resolve unwanted behavior patterns, and a host of other desirable ends, with the publishing of a remarkable paper by Dr. Gerald Oster of Mt. Sinai Medical Center in the October 1973 issue of Scientific American.
Oster's paper, entitled "Auditory Beats in the Brain", described how pulsation's called binaural beats occurred in the brain when tones of different frequencies were presented separately to each ear. As a result, the entire brain becomes entrained to the internal beat and begins to resonate to that frequency. In other words, Oster discovered a method for what is called "entrainment" of brain wave patterns. (1)
Simultaneously, Robert Monroe of the Monroe Institute of Applied Sciences was also investigating binaural beats. In thousands of experiments, using an EEG machine to monitor subject's electrical brain wave patterns, Monroe verified that he could indeed entrain brain wave patterns using binaural beats. In addition, he noted that the response did not only happen in the area of the brain responsible for hearing, or only in one hemisphere or the other, but rather the entire brain resonated, the wave forms of both hemispheres becoming identical in frequency, amplitude, phase, and coherence.
Many researchers have also verified this phenomenon. Language and speech pathologist Dr. Suzanne Evans Morris, Ph.D., says "Research supports the theory that different frequencies presented to each ear through stereo headphones...create a difference tone (or binaural beat) as the brain puts together the two tones it actually hears. Through EEG monitoring the difference tone is identified by a change in the electrical pattern produced by the brain. For example, frequencies of 200 Hz and 210 Hz produce a binaural beat frequency of 10 Hz. Monitoring of the brain's electricity (EEG) shows that the brain produces increased 10 Hz activity with equal frequency and amplitude of the wave form in both hemispheres." (2)
Research of Dr. Lester Fehmi, director of the Princeton Behavioral Medicine and Biofeedback Clinic and perhaps the foremost authority on hemispheric synchronization in the brain, also confirms that hemispheric synchronization and brain entrainment can be induced by binaural beats. (3)
Dr. Arthur Hastings, Ph.D., in a paper entitled "Tests of the Sleep Induction Technique" describes the effects of subjects listening to a cassette tape specially engineered to create binaural beats in the brain. In this case, the sounds on the tape were designed to slow the brain wave patterns from a normal waking "beta" brain wave pattern to a slower alpha pattern, then to a still slower theta pattern (the brain wave pattern of dreaming sleep), and finally to a delta pattern, the slowest of all, the brainwave pattern of dreamless sleep. Hastings says:
We were able to test the effects of the sleep tape on brain waves with an EEG machine through the courtesy of the researchers at the Langely-Porter Neuropsychiatric Institute, part of the University of California Medical School in San Francisco. Dr Joe Kaniya, Director of the Psychophysiology of Consciousness Laboratory, monitored the brain-wave frequencies of one subject as he listened to the sleep tape.
The chart recording showed a typical sleep onset pattern: initial alpha waves, then a slowing of the brain waves with sleep spindles, and finally a pattern of stage 2 and 3 sleep brain waves in the low theta range...the patterns in the various stages suggested that the tape was influencing the subject's state. (4)
Dr. Bill D. Schul also refers to this brain entrainment phenomenon:
...[P]hased sine waves at discernible sound frequencies, when blended to create 'beat' frequencies within the ranges of electrical brain waves found at the various stages of human sleep, will create a frequency following response (FFR) within the EEG pattern of the individual listening to such audio waveforms. The FFR in turn evokes physiological and mental states in direct relationship to the original stimulus. With the availability of this tool, it be- comes possible to develop and hold the subject into any of the various stages of sleep, from light Alpha relaxation through Theta into Delta and in REM (dreaming)." His conclusion was that "Binaural beat-frequency stimulation creates a sustaining FFR that is synchronous in both amplitude and frequency between the brain hemispheres.(5)
F. Holmes Atwater describes the neurophysics of the binaural beat brain entrainment process:
Within the sound processing centers of the brain, pulse stimulation provides relevant information to the higher centers of the brain. In the case of a wave form phase difference the electron pulse rate in one part of a sound-processing center is greater than in another. The differences in electron pulse stimulation within the sound processing centers of the brain are an anomaly. This anomaly (the difference in electron pulse stimulation) comes and goes as the two different frequency wave forms mesh in and out of phase. As a result of these constantly increasing and decreasing differences in electron pulse stimulation, an amplitude modulated standing wave (the binaural beat) is generated within the sound processing centers of the brain itself. It is this standing wave which acts to entrain brain waves.
Atwater further states, "A conventional binaural beat generates two amplitude modulated standing waves, one in each hemisphere's olivary nucleus. Such binaural beats will entrain both hemispheres to the same frequency, establishing equivalent electromagnetic environments and maximizing interhemispheric neural communication."(6)
The ability to entrain brain wave patterns opens up an exciting world of possibilities. Many neuroscience researchers have expressed their excitement.
"It's difficult to try to responsibly convey some sense of excitement about what's going on," said UCLA neurophysiologist John Kiebeskind. "You find yourself sounding like people you don't respect. You try to be more conservative and not say such wild and intriguing things, but damn! The field is wild and intriguing. It's hard to avoid talking that way...We are at a frontier, and it's a terribly exciting time to be in this line of work."(7)
Neurochemist Candace Pert of the National Institute of Mental Health had this to say: "There's a revolution going on. There used to be two systems of knowledge: hard science ã chemistry, physics, biophysics -- on the one hand, and, on the other, a system of knowledge that included ethology, psychology and psychiatry. And now it's as if a lightning bolt had connected the two. It's all one system -- neuroscience...The present era in neuroscience is comparable to the time when Louis Pasteur first found out that germs cause disease." (8)
David Krech, University of California at Berkeley psychologist predicted almost twenty-five years ago: "I foresee the day when we shall have the means, and therefore, inevitably, the temptation, to manipulate the behavior and intellectual functioning of all people through environmental and biochemical manipulation of the brain." (9)
That day may very well be here now, and the gentle altering of brain wave patterns using sound may be the easiest, most potent, and safest way to do it. Centerpointe Research Institute currently uses a sound technology called Holosync® to entrain brain wave patterns, giving us the ability to influence and/or create tranquility, pain control, creativity, euphoria, excitement, focused attention, relief from stress, enhanced learning ability, enhanced problem solving ability, increased memory, accelerated healing, behavior modification, and improvements in mental and emotional health.
Michael Hutchison in his book Megabrain Power sums up this revolution in neuroscience:
...[N]ew breakthroughs in neuroscience and microelectronics have permitted scientists to 'map' the electrical and chemical activity of the brain in action. Scientists have used the new technology to monitor the brains of those meditators, artists, and other rare individuals who are able to enter peak domains at will and to map their brain activity during those peak states.
Their first findings were that those peak states are not mysterious and unpredictable phenomena, but are very clearly linked to very specific patterns of brain activity. These include dramatic changes in brain wave activity, hemispheric symmetry, and rapid alterations in the levels of various neurochemicals. If we could learn to produce these patterns of brain activity, they reasoned, we should be able to produce the peak states they are associated with.
...They found that by using types of mechanical stimulation, such as...precise combinations of pulsating sound waves...they could actually produce those same 'peak state' brain patterns in ordinary people... (10)
If Schiffer is right about brain hemispheric asymmetry as a model for « stored stress » or negativity, and the increased cortical inter-hemispheric communication as evidence for improving mental health, then a simplified model proposed by Wright et al, should be able to demonstrate and even predict, improvements in interhemishpheric communication as evidence for, absence, or reduction, of stress. Alpha/theta biofeedback training is well documented as has been used to some substantial benefit in areas such drug and alcohol abuse, smoking cessation, asthma, chronic pain, muscle tension, cardiac arrhythmias, migraine headaches, tension headaches, hypertension, muscle reeducation, chronic pain syndromes and many others.
It may be useful to induce brainwave frequencies (using binaural beats) associated with relaxed, alert states (alpha, theta) as measured with EEG to see what effect, if any, they have on the well known physiological measures of stressful « yippy » putting.
The Brain Wave Frequencies of Health
by Jean Charles Genet, Director of The National Center for Integrative Medicine and The National Research Center for Chronic Fatigue
The ability of the brain to enter and maintain certain frequencies while sleeping may determine the level of health a person experiences.
Individuals suffering from the symptoms of Chronic Fatigue (waking up tired, stressed, experiencing symptomatic pain, depression, confused thinking, memory loss, headaches, nervous stomach, or having sleeping disorders, etc.) were solicited by the National Research Center for Chronic Fatigue in Denver, Colorado.
Patients were measured by electroencephalographic (EEG) brain wave recordings. It was revealed that certain frequencies could not be maintained. Although, as with any group, the response to one measured frequency is different from one person to the next, the overall response from those tested showed seven frequencies to be consistently weaker.
These seven frequencies seemed to be guide posts within the subconscious that lead the brain into and out of specific functions necessary for the nightly reconstructive process of the body to occur while in the sleep cycle. The weakness or inability to reach and maintain these frequencies related directly to the specific symptom or ailment experienced.
Reduction in Levels of Exhaustion
Those who suffer from Chronic Fatigue exhaust very easily. When moved to 4HZ these individuals showed marked improvement in the length of time between the occurrence of exhaustion after certain exercises were completed.
Solutions to Problems
At 7.5 HZ subjects who before suffered from confused thinking reported an ease at finding solutions to troublesome problems after a re-evaluation was conducted.
Less Effect From Symptoms
Those individuals whose ailments have manifested into the fourth stage of Chronic Fatigue, where some form of disease is apparent, experienced a release from the negative sensation of their symptoms when moved into 1.5HZ.
References
- Beilock, S., Carr, T. (2001). « On the Fragility of Skilled Performance: What Governs Choking Under Pressure? »
- Departments of Psychology and Kinesiology
- Michigan State University, Journal of Experimental Psychology: General.
- Wright, J., et al (2001) “Toward an Integrated Continuum Model of Cerebral Dynamics: The Cerebral Rhythms, Synchronous Oscillation and Cortical Stability.” BioSystems 63 (71-88).
- Schiffer, F. (1998). « Of Two Minds : The Revolutionary Science of Dual-Brain Psychology ». The Free Press, ISBN 0-684-85424-4.
- Dr. P.D. Hurrion, Dr. R.D. Hurrion and Ms. C. Gough.
- Quintic Consultancy Ltd, PO Box 2939, Coventry, West Midlands, CV7 7WH, UK.
- Bright, J.E.H., Freedman, O. (1998). Differences between implicit and explicit acquisition of a complex motor skill under pressure: an examination of some evidence. British Journal of Psychology May 1998 v89 n2 p249(15)
3D Shape - Its Unique Place in Visual Perception (PDF)
Images, Perception and Psychophysics (PDF)
The Physiology of the Senses - Transformations for Perception and Action (PDF)
Visual Perception & Psychophysics (PDF)
For a good overview of motion perception and some demonstrations go to:
www.lifesci.sussex.ac.uk/home/George_Mather/Motion
