American Board of Sport Psychology by ktixcqlmc

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									The Electroencephalography of the
     Ideal Performance State


    Karla A. Kubitz, Ph.D., F.A.C.S.M.
           Dept. of Kinesiology
     Towson University, Towson, MD
Outline
   The research on the electroencephalography of
    the ideal performance state has become
    increasingly sophisticated.
      Hatfield et al. (1984)’s pioneering study
      Lawton et al. (1998)’s review of the literature
      Selected recent studies
   However, the adoption of statistical pattern
    recognition techniques could further increase the
    sophistication of these studies and our
    understanding of the ideal performance state.
      Gevins et al. (1998)’s study
      Preliminary data illustrating the application
        of statistical pattern recognition techniques
Hatfield, Landers, & Ray (1984)
                             Shooting EEG
   N=17 elite shooters
   Shooting condition (40
    shots)
   EEG activity (8-12 Hz;
    from -7.5 s)
   Alpha increased over
    time (in the left
    hemisphere) prior to
    shot
Lawton et al. (1998)
   Similarities among the      Differences between
    studies                      the studies
      Performance                 Task(s) performed
        condition/                 Surrounding
        sometimes control            conditions
        condition(s)               Psychophysiologic
      Focused on                    al measures
        psychophysiology
        of preperformance
        period
      Measure(s) of
        performance
    Lawton et al. (1998; cont.)
   Findings                       Recommendations
      Increases in EEG              Better psychological
       power (in the alpha             theories
       band; in the left             Better experimental
       hemisphere) during              designs
       the preperformance            More sophisticated
       period                          electrophysiology
      Preperformance                Multiple
       EEG influenced by               psychophysiological
       skill level                     measures
      Findings are                  Relationships
       typically interpreted           between physiology,
       as related to arousal,          psychology, and
       attention, and/or               performance
       self-talk
Psychological Theories & Experimental
Design
   Kerick et al. (2001); tested verbal-suppression
    hypothesis
   Hillman et al. (2000); compared executed and
    rejected shots
     Kerick et al. (2001)           Hold

   N=8 skilled marksman
   Shooting and control (i.e.,
    holding,dry-firing)
    conditions                     Dry fire
   Hold (maintain stable                     Shoot
    position); dry-fire (stable
    position plus shoot/ w/o
    aiming)
   11-13 Hz event-related
    alpha power (i.e., at 4       Shoot
    sites; from –9 s)
   T3 >T4 alpha power and
    T3<TF alpha slope during
    shooting but not control
    conditions
Hillman et al. (2000)
                                Alpha power
                                differences
   N = 7 skilled
    marksmen
   40 shots
   EEG during executed
                                          Rejected
    and rejected shots                    shots
    (from –4 s)             Beta power
                            differences
   EEG activity (8-13 Hz
    and 14-20 Hz)
   M = 16 rejected shots
   EEG alpha and beta
    power differed
    between executed and
    rejected shots
Sophisticated Electrophysiology
   Haufler et al. (2000); measured multiple sites and
    multiple ‘narrow’ frequency bands
   Deeny et al. (2003); examined EEG coherence
    Haufler et al. (2000)
   N=36 shooters (15 expert;
    21 novice)
   Shooting condition
    (Noptel Shooter Training
    System), ‘right-brain’
    task, and ‘left brain’ task
   EEG activity (8 sites; 6-7
    Hz, 9 Hz, 10-11 Hz, 18-22
    Hz, 36-44 Hz; from –6 s)
   Performance on shooting
    (but not control) tasks
    differed by skill level
   Power at all frequencies
    differed by skill level
    during shooting (E>N for      Higher theta in left
    lower; E<N for higher)        during shooting
Deeny et al. (2003)
   N=19 (10 expert
    marksmen; 9 skilled
    shooters)                  Experts

   EEG coherence (13
    sites; 8-10 Hz, 10-13
    Hz; and 13-22 Hz;–4 s)
   Experts had lower
    coherence (i.e.,
    between all left
    hemisphere sites and
    Fz; between all midline
    sites and T3; especially
    for the low alpha and
    low beta frequencies)
    than novices
Multiple Psychophysiological Measures
   Janelle et al. (2000); recorded EEG and eye
    movement
Janelle et al. (2000)          Alpha power

   25 rifle shooters (12
    expert; 13 nonexpert)          Experts
   Shooting condition (40
    shots; Noptel Shooter
    Training System)
   EEG activity (11 sites;
    8-13 and 14-20 Hz;
    from –6 s) and eye
    movement (5000 SU
    eye movement system)
   Performance and eye
    movement differed by
    skill level
   Alpha and beta power
    differed by skill level   Beta power
Relationships Between Physiological States,
Psychological States, and Performance
   Loze, Collins, & Holmes (2001)
   Konttinen, Lyytinen, & Viitasalo (1998);
    measured EEG and rifle stability
                                                  Alpha power in
    Loze, Collins, & Holmes (2001)                best shots

   N=6 shooters
   60 shot match; simulated    16
    competition                 14
                                12
   EEG alpha activity (T3,
    T4, Oz; from –6 s) from 5   10
                                8
    best and 5 worst shots
                                6
   EEG alpha power (at T3      4
    and T4) was greater in      2
    left than in right          0
    hemisphere                       Epoch1 Epoch2 Epoch3
   EEG alpha power                        Best   Worst

    increased across time (at
    Oz) prior to best and did
    the opposite prior to
    worst shots
    Konttinen, Lyytinen, & Viitasalo (1998)
   N=12 rifle shooters (6 elite;
    6 pre-elite)
   Shooting task (200 shots;
    Noptel Shooter Training
    System)                           Good stability
   EEG slow potentials               shots
    (frontal and central sites;
    from –6 s) and rifle barrel
    stability
   Performance, rifle barrel
    stability, frontal positivity,
    and central laterality
    differed by skill level
   Frontal positivity and
    central laterality related to
    rifle stability levels
Outline
   The research on the electroencephalography of
    the ideal performance state has become
    increasingly sophisticated.
      Hatfield et al. (1984; 1987)’s pioneering
        studies
      Lawton et al. (1998)’s review
      Selected recent studies
   However, the adoption of statistical pattern
    recognition techniques could further increase the
    sophistication of these studies and our
    understanding of the ideal performance state.
      Gevins et al. (1998)’s study
      Exploring Haufler et al. (2000)’s data
    Gevins et al. (1998)
   N=8 participants; working
    memory task (3 levels of
    difficulty)
   EEG activity (27 sites, 3
    bands), reaction times, and
    accuracy
   Statistical Pattern
    Recognition Techniques
      EEG data segments (4.5
        s windows) divided into
        testing and training
        subsets
      Power estimates for 4-7
        Hz, 8-12 Hz, and 13-30
        Hz
      Selected candidate
        features to submit to
        classification algorithm
Gevins et al. (1998; cont.)
   Submitted 10-20 candidate features to classifier
   Trained classifier to identify ‘best’ multivariate
    combination of features (i.e., the combination that
    best discriminates task difficulty)
   Tested resulting classifier on ability to classify
    ‘new’ EEG segments
   Theta and alpha features (at O and P sites) most
    heavily weighted in classification algorithms
   Trained on data from one day
      Tested on new data from same day (98%
        accuracy)
      Tested on data from another day (92%
        accuracy)
   Trained on data from spatial task/ tested on data
    from verbal task (94% accuracy)
   Trained on data from one group / tested on data
    from a new group (83% accuracy)
    Application of Statistical Pattern Recognition
    Techniques to Sport Performance Data
   Haufler et al. (2000)
   N=2 (1 expert; 1
    nonexpert) shooters                       Expert
   EEG data epoched
    around shot (-1500 to 0)
   Epochs divided into
    training and testing sets
   Classifier trained to
    distinguish between
    expert and novice
    shooter
   Classifier tested on
                                Nonexpert
    ability to classify ‘new’
    EEG samples
   73% accuracy
Outline
   The research on the electroencephalography of
    the ideal performance state has become
    increasingly sophisticated.
      Hatfield et al. (1984; 1987)’s pioneering
        studies
      Lawton et al. (1998)’s review
      Selected recent studies
   However, the adoption of statistical pattern
    recognition techniques could further increase the
    sophistication of these studies and our
    understanding of the ideal performance state.
      Gevins et al. (1998)’s study
      Exploring Haufler et al. (2000)’s data
The Electroencephalography of the
     Ideal Performance State

   http://www.towson.edu/~kubitz

								
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