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Electrophysiological evidences demonstrating differences in brain functions between nonmusicians and musicians.

Zhang L, Peng W, Chen J, Hu L - Sci Rep (2015)

Bottom Line: However, evidence demonstrating that long-term music training modulates higher brain functions is surprisingly rare.We observed that compared to nonmusicians, musicians have (1) larger high-frequency steady-state responses, which reflect the auditory information processing within the sensory system, and (2) smaller low-frequency vertex potentials, which reflect higher cognitive information processing within the novelty/saliency detection system.Therefore, we speculate that long-term music training facilitates "bottom-up" auditory information processing in the sensory system and enhances "top-down" cognitive inhibition of the novelty/saliency detection system.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Cognition and Personality (Ministry of Education) and School of Psychology, Southwest University, Chongqing, China.

ABSTRACT
Long-term music training can improve sensorimotor skills, as playing a musical instrument requires the functional integration of information related to multimodal sensory perception and motor execution. This functional integration often leads to functional reorganization of cerebral cortices, including auditory, visual, and motor areas. Moreover, music appreciation can modulate emotions (e.g., stress relief), and long-term music training can enhance a musician's self-control and self-evaluation ability. Therefore, the neural processing of music can also be related to certain higher brain cognitive functions. However, evidence demonstrating that long-term music training modulates higher brain functions is surprisingly rare. Here, we aimed to comprehensively explore the neural changes induced by long-term music training by assessing the differences of transient and quasi-steady-state auditory-evoked potentials between nonmusicians and musicians. We observed that compared to nonmusicians, musicians have (1) larger high-frequency steady-state responses, which reflect the auditory information processing within the sensory system, and (2) smaller low-frequency vertex potentials, which reflect higher cognitive information processing within the novelty/saliency detection system. Therefore, we speculate that long-term music training facilitates "bottom-up" auditory information processing in the sensory system and enhances "top-down" cognitive inhibition of the novelty/saliency detection system.

No MeSH data available.


Related in: MedlinePlus

The comparison of time-frequency distributions (TFDs) elicited by transient auditory stimuli between nonmusicians and musicians.Top panel: Being elicited by transient auditory stimuli, TFDs of auditory-induced responses (single trial), auditory-evoked responses (average), and phase-locking values (PLVs) (group-level average; FCz-A1A2) are displayed from top to bottom for nonmusicians (left) and musicians (right) respectively. x axis, latency (ms); y axis, frequency (Hz). The region-of-interests (ROIs), outlined in purple curves, had (1) significantly different TFD values than those within the pre-stimulus interval and (2) significantly different TFD values between nonmusicians and musicians. Bottom left panel: The scalp topographies, measured from the corresponding ROIs of evoked TFDs (ROI1) and PLVs (ROI2), are respectively displayed in the upper and lower parts for nonmusicians (left) and musicians (right). Bottom right panel: Statistical t values and corresponding  distributions within the ROIs of evoked TFDs (ROI1) and PLVs (ROI2) are displayed in the upper and lower parts respectively. Null distributions were generated from 5000 random permutations from all datasets. Statistical t values are indicated by vertical red lines. Within ROI1, permutation tests showed that the t value of the comparison of evoked TFDs between nonmusicians and musicians was significantly different from chance level (P = 0.002). Within ROI2, permutation tests showed that the t value of the PLV comparison between nonmusicians and musicians was significantly different from chance level (P < 0.001).
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f3: The comparison of time-frequency distributions (TFDs) elicited by transient auditory stimuli between nonmusicians and musicians.Top panel: Being elicited by transient auditory stimuli, TFDs of auditory-induced responses (single trial), auditory-evoked responses (average), and phase-locking values (PLVs) (group-level average; FCz-A1A2) are displayed from top to bottom for nonmusicians (left) and musicians (right) respectively. x axis, latency (ms); y axis, frequency (Hz). The region-of-interests (ROIs), outlined in purple curves, had (1) significantly different TFD values than those within the pre-stimulus interval and (2) significantly different TFD values between nonmusicians and musicians. Bottom left panel: The scalp topographies, measured from the corresponding ROIs of evoked TFDs (ROI1) and PLVs (ROI2), are respectively displayed in the upper and lower parts for nonmusicians (left) and musicians (right). Bottom right panel: Statistical t values and corresponding distributions within the ROIs of evoked TFDs (ROI1) and PLVs (ROI2) are displayed in the upper and lower parts respectively. Null distributions were generated from 5000 random permutations from all datasets. Statistical t values are indicated by vertical red lines. Within ROI1, permutation tests showed that the t value of the comparison of evoked TFDs between nonmusicians and musicians was significantly different from chance level (P = 0.002). Within ROI2, permutation tests showed that the t value of the PLV comparison between nonmusicians and musicians was significantly different from chance level (P < 0.001).

Mentions: The top panel of Fig. 3 shows the group-level average baseline-corrected time-frequency distributions (TFDs) obtained from single-trial AEPs (auditory-induced responses) and single-subject average AEPs (auditory-evoked responses), as well as group-level average PLVs (FCz-A1A2; from top to bottom) for nonmusicians and musicians. Being elicited by transient auditory stimuli, all TFDs contained clear responses located at 0–300 ms and 1–20 Hz, as well as at 0–100 ms and 30–100 Hz. These two time-frequency responses, which were phase-locked to auditory stimuli (showed in phase locking values, PLVs), corresponded to late-latency and early/middle-latency AEPs respectively in the time domain (Fig. 2). Region of interest (ROI) based statistical analysis revealed that the time-frequency regions showed significant differences of both evoked TFDs (ROI1) and PLVs (ROI2) between post-stimulus responses and pre-stimulus responses as well as between nonmusicians and musicians at around 0–300 ms and 1–20 Hz (i.e., late-latency AEPs; Fig. 3, top panel; marked in purple). There were similar scalp topographies of evoked TFDs between nonmusicians and musicians within ROI1 (maximal at fronto-central region, Fig. 3, upper part of the bottom panel); however, permutation testing (5000 times) indicated that the measured magnitudes were significantly larger for nonmusicians than musicians (0.35 ± 0.22 μV2 vs. 0.14 ± 0.07 μV2; P = 0.002). Within ROI2 (Fig. 3, lower part of the bottom panel), permutation testing indicated that the measured PLVs were significantly larger for nonmusicians than for musicians (0.33 ± 0.08 vs. 0.22 ± 0.05; P < 0.001).


Electrophysiological evidences demonstrating differences in brain functions between nonmusicians and musicians.

Zhang L, Peng W, Chen J, Hu L - Sci Rep (2015)

The comparison of time-frequency distributions (TFDs) elicited by transient auditory stimuli between nonmusicians and musicians.Top panel: Being elicited by transient auditory stimuli, TFDs of auditory-induced responses (single trial), auditory-evoked responses (average), and phase-locking values (PLVs) (group-level average; FCz-A1A2) are displayed from top to bottom for nonmusicians (left) and musicians (right) respectively. x axis, latency (ms); y axis, frequency (Hz). The region-of-interests (ROIs), outlined in purple curves, had (1) significantly different TFD values than those within the pre-stimulus interval and (2) significantly different TFD values between nonmusicians and musicians. Bottom left panel: The scalp topographies, measured from the corresponding ROIs of evoked TFDs (ROI1) and PLVs (ROI2), are respectively displayed in the upper and lower parts for nonmusicians (left) and musicians (right). Bottom right panel: Statistical t values and corresponding  distributions within the ROIs of evoked TFDs (ROI1) and PLVs (ROI2) are displayed in the upper and lower parts respectively. Null distributions were generated from 5000 random permutations from all datasets. Statistical t values are indicated by vertical red lines. Within ROI1, permutation tests showed that the t value of the comparison of evoked TFDs between nonmusicians and musicians was significantly different from chance level (P = 0.002). Within ROI2, permutation tests showed that the t value of the PLV comparison between nonmusicians and musicians was significantly different from chance level (P < 0.001).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4559803&req=5

f3: The comparison of time-frequency distributions (TFDs) elicited by transient auditory stimuli between nonmusicians and musicians.Top panel: Being elicited by transient auditory stimuli, TFDs of auditory-induced responses (single trial), auditory-evoked responses (average), and phase-locking values (PLVs) (group-level average; FCz-A1A2) are displayed from top to bottom for nonmusicians (left) and musicians (right) respectively. x axis, latency (ms); y axis, frequency (Hz). The region-of-interests (ROIs), outlined in purple curves, had (1) significantly different TFD values than those within the pre-stimulus interval and (2) significantly different TFD values between nonmusicians and musicians. Bottom left panel: The scalp topographies, measured from the corresponding ROIs of evoked TFDs (ROI1) and PLVs (ROI2), are respectively displayed in the upper and lower parts for nonmusicians (left) and musicians (right). Bottom right panel: Statistical t values and corresponding distributions within the ROIs of evoked TFDs (ROI1) and PLVs (ROI2) are displayed in the upper and lower parts respectively. Null distributions were generated from 5000 random permutations from all datasets. Statistical t values are indicated by vertical red lines. Within ROI1, permutation tests showed that the t value of the comparison of evoked TFDs between nonmusicians and musicians was significantly different from chance level (P = 0.002). Within ROI2, permutation tests showed that the t value of the PLV comparison between nonmusicians and musicians was significantly different from chance level (P < 0.001).
Mentions: The top panel of Fig. 3 shows the group-level average baseline-corrected time-frequency distributions (TFDs) obtained from single-trial AEPs (auditory-induced responses) and single-subject average AEPs (auditory-evoked responses), as well as group-level average PLVs (FCz-A1A2; from top to bottom) for nonmusicians and musicians. Being elicited by transient auditory stimuli, all TFDs contained clear responses located at 0–300 ms and 1–20 Hz, as well as at 0–100 ms and 30–100 Hz. These two time-frequency responses, which were phase-locked to auditory stimuli (showed in phase locking values, PLVs), corresponded to late-latency and early/middle-latency AEPs respectively in the time domain (Fig. 2). Region of interest (ROI) based statistical analysis revealed that the time-frequency regions showed significant differences of both evoked TFDs (ROI1) and PLVs (ROI2) between post-stimulus responses and pre-stimulus responses as well as between nonmusicians and musicians at around 0–300 ms and 1–20 Hz (i.e., late-latency AEPs; Fig. 3, top panel; marked in purple). There were similar scalp topographies of evoked TFDs between nonmusicians and musicians within ROI1 (maximal at fronto-central region, Fig. 3, upper part of the bottom panel); however, permutation testing (5000 times) indicated that the measured magnitudes were significantly larger for nonmusicians than musicians (0.35 ± 0.22 μV2 vs. 0.14 ± 0.07 μV2; P = 0.002). Within ROI2 (Fig. 3, lower part of the bottom panel), permutation testing indicated that the measured PLVs were significantly larger for nonmusicians than for musicians (0.33 ± 0.08 vs. 0.22 ± 0.05; P < 0.001).

Bottom Line: However, evidence demonstrating that long-term music training modulates higher brain functions is surprisingly rare.We observed that compared to nonmusicians, musicians have (1) larger high-frequency steady-state responses, which reflect the auditory information processing within the sensory system, and (2) smaller low-frequency vertex potentials, which reflect higher cognitive information processing within the novelty/saliency detection system.Therefore, we speculate that long-term music training facilitates "bottom-up" auditory information processing in the sensory system and enhances "top-down" cognitive inhibition of the novelty/saliency detection system.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Cognition and Personality (Ministry of Education) and School of Psychology, Southwest University, Chongqing, China.

ABSTRACT
Long-term music training can improve sensorimotor skills, as playing a musical instrument requires the functional integration of information related to multimodal sensory perception and motor execution. This functional integration often leads to functional reorganization of cerebral cortices, including auditory, visual, and motor areas. Moreover, music appreciation can modulate emotions (e.g., stress relief), and long-term music training can enhance a musician's self-control and self-evaluation ability. Therefore, the neural processing of music can also be related to certain higher brain cognitive functions. However, evidence demonstrating that long-term music training modulates higher brain functions is surprisingly rare. Here, we aimed to comprehensively explore the neural changes induced by long-term music training by assessing the differences of transient and quasi-steady-state auditory-evoked potentials between nonmusicians and musicians. We observed that compared to nonmusicians, musicians have (1) larger high-frequency steady-state responses, which reflect the auditory information processing within the sensory system, and (2) smaller low-frequency vertex potentials, which reflect higher cognitive information processing within the novelty/saliency detection system. Therefore, we speculate that long-term music training facilitates "bottom-up" auditory information processing in the sensory system and enhances "top-down" cognitive inhibition of the novelty/saliency detection system.

No MeSH data available.


Related in: MedlinePlus