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Music increases frontal EEG coherence during verbal learning

Music increases frontal EEG coherence during verbal learning

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Music increases frontal EEG coherence during verbal learning

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  1. Music increases frontal EEG coherence during verbal learning David A. Peterson a,b,c,∗, Michael H. Thaut b,c a Department of Computer Science, Colorado State University b Program in Molecular, Cellular, and Integrative Neuroscience Colorado State University c Center for Biomedical Research in Music, Colorado State University Neuroscience Letters 412 (2007) 217-221 Ranelle Johnson

  2. Introduction (others said…) • Memory may be subserved by oscillations in recurrent networks within and between brain regions (in theory) • Increased multi band spectral power in the EEG during encoding is associated with successful subsequent word recall

  3. Introduction • In an earlier study… • verbal learning is associated with broadband increases in EEG power spectra • Music influences the topographic distribution of the increased spectral power • Present study… • examining spatial coherence in EEG measured during learning phase

  4. Independent Variable • Treatment Groups • Learning to recall in conventional speaking voice • Learning to recall while singing to melody

  5. Dependent Variable Theoretical Construct - verbal learning Operational Definition - Transition from not being able to recall to being able to recall a word that is repeatedly presented in the AVLT

  6. Dependent Variable • Theoretical Construct • Learning related changes in coherence (LRCC) • Operational Definition • Percent increase or decrease in coherence comparing “first recalled” words to the same words not recalled during the immediately preceding trial (all pairs of not learned/learned words)

  7. Hypothesis • Learning that persists over short- and long- delays will be associated with “learning related change in coherence” (LRCC) in frontal EEG

  8. Hypothesis • The temporally structured learning template provided by music will strengthen LRCC patterns in frontal EEG compared to conventional spoken learning.

  9. Subjects • 16 healthy right-handed volunteers • Normal hearing • No history- neurological or psychiatric conditions • Randomly assigned to one of two experimental conditions in a in between-subjects design • Age range • 18-26 (mean=19.8, SD=2.8) • 18-21 (mean=19.0, SD=1.0) • Each group contained 7 females

  10. Method • Rey’s Auditory Verbal Learning Test (AVLT) • 15 semantically unrelated words • Repeated in 5 learning trials • Subjects free recalled as many words as possible after each recall • 6th trial- distracter list, 20 minute visual

  11. Method Fig. 1. Rey’s Auditory Verbal Learning Test (AVLT) and the operational definitions of: • learning (thickest arrows, during the learning trials—e.g. words 2, 14, 15); • short-delay memory (medium thick arrows to M1—e.g. words 2, 15); • long-delay memory (thinnest arrows to M2—e.g. word 2).

  12. Method • Pre-recorded female voice (both conditions) • Music condition- sang simple, repetitive and unfamiliar melody • Made both groups’ list of words same durations (15sec)

  13. Method • Electroencephalogram (EEG) • Continuous EEG from continuous 32 scalp electrodes • Neuroscan’s QuickCap using low- and high- frequencies 1 and 100 Hz, 1kHz sampling frequency • Computed interelectrode coherence over 500 ms window 250ms after each word’s onset • For electrode pairs in theta, alpha, gamma frequency bands

  14. Analysis • Computed coherence for • left and right prefrontal areas, within and between • LRCC for each group- compared to no change using one-tailed t-test, alpha=.05 • LRCC between the two groups- compared using two-tailed t-test, alpha=.05 • Bonferroni adjustment by factor of 3 for multiple comparison

  15. Results (performance) • Both groups recalled about 6 more words on the last learned trial than on the first • mean=11 & 4.9 (spoken) • mean=9.7 & 4.3 (music) • Significant improvement in performance • t(16)= 9.6 & 6.3, p<0.0001 • Recall was not significantly different between spoken and musical groups on any trial • t(16)<1.4, p>0.1

  16. Results (spoken) Involves a mix of (+) & (-) LRCC None of LRCC values differed significantly from zero Except… Negative right frontal gamma LRCC t(42)=2.2, p=.03 and t(36)= 2.2, p=.03

  17. Results (musical) • Involved (+) LRCC within & between the hemispheres • Short-delays • Increased frontal coherence significant for left gamma, t(39)=2.6, p=.003 • Interhemispheric theta, t(39)=2.6, p=.01

  18. Results (musical) • Between Group Comparisons • Higher LRCC for music group in all 3 frequency bands • Music showed greater increase in theta coherence for short- & long- delay learning • t(81)=2.1, p=.04 (short- delay) • Music showed increase and spoken a decrease for right alpha coherence (both short- and long- delay) • t(66)=2.5, p=.01 (long delay learning) • Music showed greater increase (spoken decrease) in right gamma coherence in b/t groups for long- delay learning • t(66)=2.7, p=.009

  19. Results In each cell: .Values are mean coherence relative to previous unlearned trial (i.e. 100 is no change in coherence). Bold values indicates p < 0.05 in one-tailed T-test after Bonferroni correction. Highlighted values indicates p < 0.05 in between-group, two-tailed T-test after Bonferroni correction.

  20. Results Fig. 2. Learning-related change in coherence (LRCC). Left: LRCC for short-delay recall; right: LRCC for long-delay recall. Scale bar is percent change. Straight line and box overlays indicate absolute changes in LRCC greater than 5%: box for local quadrant LRCC, and line for interquadrant (interhemispheric) LRCC. Thin box (e.g. spoken group’s long-delay right frontal gamma LRCC) indicates a decrease of greater than 5%.

  21. Discussion • Music condition had increased frontal coherence whereas spoken condition had no significant change • Music group had stronger temporal synchronization in frontal areas

  22. Discussion • Lack of coherence in spoken condition may be due to form of measure • Spoken learning involves more focal changes • Musical learning shows more topographical broader network synchronization

  23. Discussion • Performance effect “nullified” • Transfer appropriate processing theory • Subjects asked to recall material in different way that it was encoded • Physiological results not due to differences in performance • Physiological results not due to different sensory processing (music vs. spoken stimuli) • Data for LRCC measured with recalled word compared to the same word not recalled in previous trial

  24. Discussion • How does music effect synchronization then? • Early attentional mechanism • Selective attention associated with greater coherence with multiple spatial skills • Music is known to form expectancy, listeners can predict musical aspects, this could increase coherence • Studies suggest that music related processing involves more widely distributed subcortical and cortical networks

  25. What do I think? • Uuuuuummmmm??? • I don’t know enough about the interpretations of EEG to really be able to criticize a whole lot… • But like they said, use more subjects • They could try testing performance by having the words sung back and see if it makes a difference on performance • I don’t understand how you can measure a not recalled word


  27. widely distributed Oh Toto, where are we? z, t, F = You're not in Kansas anymore, little girl!