Electrophysiological evidences demonstrating differences in brain functions between nonmusicians and musicians

Zhang, Li; Peng, Weiwei; Chen, Jie; Hu, Li

doi:10.1038/srep13796

Cited by 10 publications

(9 citation statements)

References 50 publications

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“…Electrophysiological indices might be more sensitive to subtle group differences than behavioral measures (e.g. Schön & François, 2011; see also Zhang, Peng, Chen, & Hu, 2015) and performance on stop-signal and Stroop tasks are not necessarily correlated and have been argued to reflect different underlying processes (e.g., Khng & Lee, 2014;MacLeod, Dodd, Sheard, Wilson, & Bibi, 2003). In fact, a previous study showing musician advantages on Stroop-type tasks (Bialystok & DePape, 2009) did not actually report smaller interference effects for musicians, but rather faster responses to both incongruent and congruent stimuli in a conflict context.…”

Section: Discussionmentioning

confidence: 99%

Tuning the mind: Exploring the connections between musical ability and executive functions

et al. 2016

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A growing body of research suggests that musical experience and ability are related to a variety of cognitive abilities, including executive functioning (EF). However, it is not yet clear if these relationships are limited to specific components of EF, limited to auditory tasks, or reflect very general cognitive advantages. This study investigated the existence and generality of the relationship between musical ability and EFs by evaluating the musical experience and ability of a large group of participants and investigating whether this predicts individual differences on three different components of EF – inhibition, updating, and switching – in both auditory and visual modalities. Musical ability predicted better performance on both auditory and visual updating tasks, even when controlling for a variety of potential confounds (age, handedness, bilingualism, and socio-economic status). However, musical ability was not clearly related to inhibitory control and was unrelated to switching performance. These data thus show that cognitive advantages associated with musical ability are not limited to auditory processes, but are limited to specific aspects of EF. This supports a process-specific (but modality-general) relationship between musical ability and non-musical aspects of cognition.GRAMMY Foundatio

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Section: Discussionmentioning

confidence: 99%

Tuning the mind: Exploring the connections between musical ability and executive functions

et al. 2016

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“…For example, Alain et al (2007) reported finding smaller P2 amplitudes following training using speech sounds. More recently, Zhang et al (2015) also recorded smaller N1-P2 responses from musicians compared to non-musicians when they used click trains as the stimulus for evoked potential testing.…”

Section: Introductionmentioning

confidence: 99%

Effects of Long-Term Musical Training on Cortical Auditory Evoked Potentials

et al. 2017

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Objective Evidence suggests that musicians, as a group, have superior frequency resolution abilities when compared to non-musicians. It is possible to assess auditory discrimination using either behavioral or electrophysiologic methods. The purpose of this study was to determine if the auditory change complex (ACC) is sensitive enough to reflect the differences in spectral processing exhibited by musicians and non-musicians. Design Twenty individuals (10 musicians and 10 non-musicians) participated in this study. Pitch and spectral ripple discrimination were assessed using both behavioral and electrophysiologic methods. Behavioral measures were obtained using a standard three interval, forced choice procedure and the ACC was recorded and used as an objective (i.e. non-behavioral) measure of discrimination between two auditory signals. The same stimuli were used for both psychophysical and electrophysiologic testing. Results As a group, musicians were able to detect smaller changes in pitch than non-musicians. They also were able to detect a shift in the position of the peaks and valleys in a ripple noise stimulus at higher ripple densities than non-musicians. ACC responses recorded from musicians were larger than those recorded from non-musicians when the amplitude of the ACC response was normalized to the amplitude of the onset response in each stimulus pair. Visual detection thresholds derived from the evoked potential data were better for musicians than non-musicians regardless of whether the task was discrimination of musical pitch or detection of a change in the frequency spectrum of the rippled noise stimuli. Behavioral measures of discrimination were generally more sensitive than the electrophysiologic measures; however, the two metrics were correlated. Conclusions Perhaps as a result of extensive training, musicians are better able to discriminate spectrally complex acoustic signals than non-musicians. Those differences are evident not only in perceptual/behavioral tests, but also in electrophysiologic measures of neural response at the level of the auditory cortex. While these results are based on observations made from normal hearing listeners, they suggest that the ACC may provide a non-behavioral method of assessing auditory discrimination and as a result might prove useful in future studies that explore the efficacy of participation in a musically based, auditory training program perhaps geared toward pediatric and/or hearing-impaired listeners.

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“…In these studies, brain signals were recorded using an EEG headset while the subject listens to music [44,53,58,100,110,112,115,116,151,154,190,205,216,220,222,235,276,279]. Moreover, the subjects' emotions were recognized as displayed by EEG signals.…”

Section: Domain Description Referencesmentioning

confidence: 99%

Review and Classification of Emotion Recognition Based on EEG Brain-Computer Interface System Research: A Systematic Review

et al. 2017

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Abstract:Recent developments and studies in brain-computer interface (BCI) technologies have facilitated emotion detection and classification. Many BCI studies have sought to investigate, detect, and recognize participants' emotional affective states. The applied domains for these studies are varied, and include such fields as communication, education, entertainment, and medicine. To understand trends in electroencephalography (EEG)-based emotion recognition system research and to provide practitioners and researchers with insights into and future directions for emotion recognition systems, this study set out to review published articles on emotion detection, recognition, and classification. The study also reviews current and future trends and discusses how these trends may impact researchers and practitioners alike. We reviewed 285 articles, of which 160 were refereed journal articles that were published since the inception of affective computing research. The articles were classified based on a scheme consisting of two categories: research orientation and domains/applications. Our results show considerable growth of EEG-based emotion detection journal publications. This growth reflects an increased research interest in EEG-based emotion detection as a salient and legitimate research area. Such factors as the proliferation of wireless EEG devices, advances in computational intelligence techniques, and machine learning spurred this growth.

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Electrophysiological evidences demonstrating differences in brain functions between nonmusicians and musicians

Cited by 10 publications

References 50 publications

Tuning the mind: Exploring the connections between musical ability and executive functions

Tuning the mind: Exploring the connections between musical ability and executive functions

Effects of Long-Term Musical Training on Cortical Auditory Evoked Potentials

Review and Classification of Emotion Recognition Based on EEG Brain-Computer Interface System Research: A Systematic Review

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