Scale-Free Brain-Wave Music from Simultaneously EEG and fMRI Recordings
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{"title"=>"Scale-Free Brain-Wave Music from Simultaneously EEG and fMRI Recordings", "type"=>"journal", "authors"=>[{"first_name"=>"Jing", "last_name"=>"Lu", "scopus_author_id"=>"56456789300"}, {"first_name"=>"Dan", "last_name"=>"Wu", "scopus_author_id"=>"57030953900"}, {"first_name"=>"Hua", "last_name"=>"Yang", "scopus_author_id"=>"55484495600"}, {"first_name"=>"Cheng", "last_name"=>"Luo", "scopus_author_id"=>"55695798400"}, {"first_name"=>"Chaoyi", "last_name"=>"Li", "scopus_author_id"=>"7501678463"}, {"first_name"=>"Dezhong", "last_name"=>"Yao", "scopus_author_id"=>"55558568500"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84869124023", "pui"=>"366053715", "doi"=>"10.1371/journal.pone.0049773", "isbn"=>"1932-6203", "sgr"=>"84869124023", "pmid"=>"23166768"}, "id"=>"0c7e0f6a-bf60-3b2c-86c3-04787b511dfe", "abstract"=>"In the past years, a few methods have been developed to translate human EEG to music. In 2009, PloS One 4 e5915, we developed a method to generate scale-free brainwave music where the amplitude of EEG was translated to music pitch according to the power law followed by both of them, the period of an EEG waveform is translated directly to the duration of a note, and the logarithm of the average power change of EEG is translated to music intensity according to the Fechner's law. In this work, we proposed to adopt simultaneously-recorded fMRI signal to control the intensity of the EEG music, thus an EEG-fMRI music is generated by combining two different and simultaneous brain signals. And most importantly, this approach further realized power law for music intensity as fMRI signal follows it. Thus the EEG-fMRI music makes a step ahead in reflecting the physiological process of the scale-free brain.", "link"=>"http://www.mendeley.com/research/scalefree-brainwave-music-simultaneously-eeg-fmri-recordings", "reader_count"=>99, "reader_count_by_academic_status"=>{"Unspecified"=>5, "Professor > Associate Professor"=>5, "Researcher"=>18, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>32, "Student > Postgraduate"=>4, "Student > Master"=>14, "Other"=>1, "Student > Bachelor"=>9, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>5}, "reader_count_by_user_role"=>{"Unspecified"=>5, "Professor > Associate Professor"=>5, "Researcher"=>18, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>32, "Student > Postgraduate"=>4, "Student > Master"=>14, "Other"=>1, "Student > Bachelor"=>9, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>5}, "reader_count_by_subject_area"=>{"Unspecified"=>9, "Agricultural and Biological Sciences"=>8, "Arts and Humanities"=>5, "Computer Science"=>11, "Earth and Planetary Sciences"=>1, "Engineering"=>17, "Environmental Science"=>1, "Mathematics"=>1, "Medicine and Dentistry"=>6, "Neuroscience"=>16, "Physics and Astronomy"=>4, "Psychology"=>18, "Social Sciences"=>2}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>6}, "Social Sciences"=>{"Social Sciences"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>4}, "Psychology"=>{"Psychology"=>18}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>9}, "Environmental Science"=>{"Environmental Science"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>5}, "Engineering"=>{"Engineering"=>17}, "Neuroscience"=>{"Neuroscience"=>16}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>8}, "Computer Science"=>{"Computer Science"=>11}}, "reader_count_by_country"=>{"Canada"=>1, "Cuba"=>1, "Austria"=>1, "United States"=>3, "Japan"=>2, "Finland"=>1, "United Kingdom"=>1, "Italy"=>3, "Chile"=>1, "Switzerland"=>1, "Spain"=>2}, "group_count"=>6}

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/543062"], "description"=>"<p>(a) and (d) the fMRI signals collected at MNI coordinate (15,−48, 60); (b) and (e) pieces of signals in (a) and (d) for the following music compositions; (c) and (f) 30 s simultaneous EEGs collected at scalp Cz, respectively for Subjects A and B.</p>", "links"=>[], "tags"=>["eeg", "fmri"], "article_id"=>213556, "categories"=>["Physiology", "Biotechnology", "Neuroscience"], "users"=>["Jing Lu", "Dan Wu", "Hua Yang", "Cheng Luo", "Chaoyi Li", "Dezhong Yao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0049773.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_EEG_and_fMRI_signals_/213556", "title"=>"The EEG and fMRI signals.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-14 00:59:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/543185"], "description"=>"<p>(a) Subject A, the left region alpha = 1.022, and the right region alpha = 0.195; (b) Subject B, the left region alpha = 0.878, and the right region alpha = 0.215. Here k is the window size, and F(k) is the fluctuation from the local trends in windows.</p>", "links"=>[], "tags"=>["detrended", "fluctuation", "scale-free"], "article_id"=>213675, "categories"=>["Physiology", "Biotechnology", "Neuroscience"], "users"=>["Jing Lu", "Dan Wu", "Hua Yang", "Cheng Luo", "Chaoyi Li", "Dezhong Yao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0049773.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_EEG_detrended_fluctuation_analysis_and_Scale_free_regions_/213675", "title"=>"EEG detrended fluctuation analysis and Scale-free regions.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-14 01:01:15"}
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  • {"files"=>["https://ndownloader.figshare.com/files/543421"], "description"=>"<p>Points indicate the original sample, the solid lines indicate the interpolated function.(a) and (b) for Subject A and B, respectively.</p>", "links"=>[], "tags"=>["interpolation", "fmri"], "article_id"=>213916, "categories"=>["Physiology", "Biotechnology", "Neuroscience"], "users"=>["Jing Lu", "Dan Wu", "Hua Yang", "Cheng Luo", "Chaoyi Li", "Dezhong Yao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0049773.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Fractal_Interpolation_of_the_fMRI_signals_/213916", "title"=>"Fractal Interpolation of the fMRI signals.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-14 01:05:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/543540"], "description"=>"<p>The amplitude, waveform period, and fMRI signal are mapped to pitch, duration and intensity, respectively. The mappings from amplitude to pitch and from fMRI signal to intensity are based the power law.</p>", "links"=>[], "tags"=>["rules", "eeg-fmri"], "article_id"=>214034, "categories"=>["Physiology", "Biotechnology", "Neuroscience"], "users"=>["Jing Lu", "Dan Wu", "Hua Yang", "Cheng Luo", "Chaoyi Li", "Dezhong Yao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0049773.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Composition_rules_of_EEG_fMRI_music_/214034", "title"=>"Composition rules of EEG-fMRI music.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-14 01:07:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/543601"], "description"=>"<p>Each column denotes a note, where the pitch (height of a column) is determined by <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049773#pone.0049773.e001\" target=\"_blank\">Equation (1)</a>, the duration (width of a column) is defined as the period of an EEG wave, and the intensity (color of a column) is determined by <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049773#pone.0049773.e016\" target=\"_blank\">Equation (5)</a>. (a) EEG music of Subject A with <i>b</i><sub>1</sub> = 96, <i>b</i><sub>2</sub> = 108, = 1.02, = 0.20; (b) EEG music of Subject B with <i>b</i><sub>1</sub> = 96, <i>b</i><sub>2</sub> = 108, = 0.88, = 0.21; (c) the relation between the pitch and intensity of the EEG music of Subject A with correlation coefficient = 0.427 (p<0.05); (d) the relation between the pitch and intensity of the EEG music of Subject B with correlation coefficient = 0.494(p<0.05).</p>", "links"=>[], "tags"=>["biotechnology", "physiology", "neuroscience"], "article_id"=>214098, "categories"=>["Physiology", "Biotechnology", "Neuroscience"], "users"=>["Jing Lu", "Dan Wu", "Hua Yang", "Cheng Luo", "Chaoyi Li", "Dezhong Yao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0049773.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_EEG_music_/214098", "title"=>"EEG music.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-14 01:08:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/543718"], "description"=>"<p>Each column denotes a note, where the pitch (height of a column) is determined by <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049773#pone.0049773.e001\" target=\"_blank\">Equation (1)</a>, the duration (width of a column) is defined as the period of the EEG wave, and the intensity (color of a column) is determined by fMRI signal. (a) EEG-fMRI music of Subject A; (b) EEG-fMRI music of Subject B. The parameters adopted here are the same with <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049773#pone-0049773-g006\" target=\"_blank\">Figure 6</a>; (c) The relation between the pitch and intensity of the EEG-fMRI music of Subject A with correlation coefficient = 0.0048 (p>0.05); (d) The relation between the pitch and intensity of the EEG-fMRI music of Subject B with correlation coefficient = 0.0095(p>0.05).</p>", "links"=>[], "tags"=>["biotechnology", "physiology", "neuroscience"], "article_id"=>214218, "categories"=>["Physiology", "Biotechnology", "Neuroscience"], "users"=>["Jing Lu", "Dan Wu", "Hua Yang", "Cheng Luo", "Chaoyi Li", "Dezhong Yao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0049773.g007"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_EEG_fMRI_music_/214218", "title"=>"EEG-fMRI music.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-14 01:10:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/543831"], "description"=>"<p>(a) Score of brain music of Subject A, (b) score of brain music of Subject B.</p>", "links"=>[], "tags"=>["eeg-fmri", "sibelius"], "article_id"=>214326, "categories"=>["Physiology", "Biotechnology", "Neuroscience"], "users"=>["Jing Lu", "Dan Wu", "Hua Yang", "Cheng Luo", "Chaoyi Li", "Dezhong Yao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0049773.g008"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Illustration_of_the_score_of_EEG_fMRI_music_Printed_by_Sibelius_4_0_/214326", "title"=>"Illustration of the score of EEG-fMRI music (Printed by Sibelius 4.0).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-14 01:12:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/543964"], "description"=>"<p>(a)–(b) DFA of EEG music note duration for subjects A and B, respectively. For Subject A, alpha = 0.109, for Subject B, alpha = 0.056. (c)–(d) DFA of EEG music note volume for subjects A and B, respectively. For Subject A, alpha = 0.123, for Subject B, alpha = 0.082. Here k is the window size, and F(k) is the fluctuation from the local trends in windows.</p>", "links"=>[], "tags"=>["fluctuation", "eeg-music", "duration"], "article_id"=>214457, "categories"=>["Physiology", "Biotechnology", "Neuroscience"], "users"=>["Jing Lu", "Dan Wu", "Hua Yang", "Cheng Luo", "Chaoyi Li", "Dezhong Yao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0049773.g009"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Detrended_fluctuation_analysis_of_EEG_music_duration_and_volume_/214457", "title"=>"Detrended fluctuation analysis of EEG-music duration and volume.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-14 01:14:17"}
  • {"files"=>["https://ndownloader.figshare.com/files/544096"], "description"=>"<p>(a) A piece of real music ‘Nocturnes’, composed by Mozart, (b) EEG-fMRI music and (c) EEG music.</p>", "links"=>[], "tags"=>["ranges"], "article_id"=>214595, "categories"=>["Physiology", "Biotechnology", "Neuroscience"], "users"=>["Jing Lu", "Dan Wu", "Hua Yang", "Cheng Luo", "Chaoyi Li", "Dezhong Yao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0049773.g010"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_envelope_variation_ranges_of_music_waveform_/214595", "title"=>"The envelope variation ranges of music waveform.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-14 01:16:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/544180"], "description"=>"<p>Intensity Variation recognition by 10 volunteers.</p>", "links"=>[], "tags"=>["10"], "article_id"=>214676, "categories"=>["Physiology", "Biotechnology", "Neuroscience"], "users"=>["Jing Lu", "Dan Wu", "Hua Yang", "Cheng Luo", "Chaoyi Li", "Dezhong Yao"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0049773.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Intensity_Variation_recognition_by_10_volunteers_/214676", "title"=>"Intensity Variation recognition by 10 volunteers.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-11-14 01:17:56"}

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Relative Metric

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