Windowed Correlation: A Suitable Tool for Providing Dynamic fMRI-Based Functional Connectivity Neurofeedback on Task Difficulty
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{"title"=>"Windowed correlation: A suitable tool for providing dynamic fMRI-based functional connectivity neurofeedback on task difficulty", "type"=>"journal", "authors"=>[{"first_name"=>"Anna", "last_name"=>"Zilverstand", "scopus_author_id"=>"35231916700"}, {"first_name"=>"Bettina", "last_name"=>"Sorger", "scopus_author_id"=>"23393624800"}, {"first_name"=>"Jan", "last_name"=>"Zimmermann", "scopus_author_id"=>"36338277400"}, {"first_name"=>"Amanda", "last_name"=>"Kaas", "scopus_author_id"=>"12798577100"}, {"first_name"=>"Rainer", "last_name"=>"Goebel", "scopus_author_id"=>"7102516398"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84899415802", "pmid"=>"24465794", "sgr"=>"84899415802", "doi"=>"10.1371/journal.pone.0085929", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "issn"=>"19326203", "pui"=>"372852924"}, "id"=>"8e59967f-fd6c-3c9f-b583-dbc58023f8cc", "abstract"=>"The goal of neurofeedback training is to provide participants with relevant information on their ongoing brain processes in order to enable them to change these processes in a meaningful way. Under the assumption of an intrinsic brain-behavior link, neurofeedback can be a tool to guide a participant towards a desired behavioral state, such as a healthier state in the case of patients. Current research in clinical neuroscience regarding the most robust indicators of pathological brain processes in psychiatric and neurological disorders indicates that fMRI-based functional connectivity measures may be among the most important biomarkers of disease. The present study therefore investigated the general potential of providing fMRI neurofeedback based on functional correlations, computed from short-window time course data at the level of single task periods. The ability to detect subtle changes in task performance with block-wise functional connectivity measures was evaluated based on imaging data from healthy participants performing a simple motor task, which was systematically varied along two task dimensions representing two different aspects of task difficulty. The results demonstrate that fMRI-based functional connectivity measures may provide a better indicator for an increase in overall (motor) task difficulty than activation level-based measures. Windowed functional correlations thus seem to provide relevant and unique information regarding ongoing brain processes, which is not captured equally well by standard activation level-based neurofeedback measures. Functional connectivity markers, therefore, may indeed provide a valuable tool to enhance and monitor learning within an fMRI neurofeedback setup.", "link"=>"http://www.mendeley.com/research/windowed-correlation-suitable-tool-providing-dynamic-fmribased-functional-connectivity-neurofeedback", "reader_count"=>77, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>3, "Researcher"=>19, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>28, "Student > Postgraduate"=>1, "Student > Master"=>11, "Other"=>2, "Student > Bachelor"=>5, "Lecturer"=>1, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>3, "Researcher"=>19, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>28, "Student > Postgraduate"=>1, "Student > Master"=>11, "Other"=>2, "Student > Bachelor"=>5, "Lecturer"=>1, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>9, "Agricultural and Biological Sciences"=>4, "Chemical Engineering"=>1, "Computer Science"=>2, "Economics, Econometrics and Finance"=>1, "Engineering"=>11, "Biochemistry, Genetics and Molecular Biology"=>1, "Medicine and Dentistry"=>9, "Neuroscience"=>14, "Sports and Recreations"=>1, "Physics and Astronomy"=>4, "Psychology"=>19, "Social Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>9}, "Social Sciences"=>{"Social Sciences"=>1}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>4}, "Psychology"=>{"Psychology"=>19}, "Unspecified"=>{"Unspecified"=>9}, "Chemical Engineering"=>{"Chemical Engineering"=>1}, "Engineering"=>{"Engineering"=>11}, "Neuroscience"=>{"Neuroscience"=>14}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>4}, "Computer Science"=>{"Computer Science"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}}, "reader_count_by_country"=>{"Netherlands"=>1, "United States"=>3, "Finland"=>1, "United Kingdom"=>1, "Italy"=>1, "Chile"=>1, "Portugal"=>2, "Germany"=>2}, "group_count"=>2}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1351210"], "description"=>"<p>The individually selected regions of interest in the left and right primary motor cortices (M1) of the five participants are projected onto an average of all participants’ anatomical brain images in panel <b>A</b> (z = 51, Talairach space), and onto the individual anatomical brain images in panel <b>B</b>. In Panel <b>C</b> the BOLD responses from left M1 (averaged across all tasks) are depicted for all participants (mean ± individual SE). The time windows used to compute the block-wise correlations are superimposed on the BOLD responses. Panel <b>D</b> displays the average activation level (group mean ± group SE) during each of the sixteen experimental conditions (four different tapping sequences performed at four different speeds) in right and left M1 (group mean ± group SE), while panel E shows the results (group mean ± group SE) from the correlation analysis of the same regions of interest. From unimanual to bimanual finger tapping the average activation level increased, as expected, in the right, but not left primary motor cortex (left M1: <i>unimanual</i> 1.4%, <i>synchronous</i> 1.3%, <i>alternating</i> 1.2%, <i>unbalanced</i> 1.2%; right M1: <i>unimanual</i> −0.2%, <i>synchronous</i> 1.3%, <i>alternating</i> 1.2%, <i>unbalanced</i> 0.9%). This effect was reflected in the steady-state task and overall task connectivity (26-s full task window: <i>unimanual</i>: 0.02, <i>synchronous</i> 0.75, <i>alternating</i> 0.73, <i>unbalanced</i> 0.73; 12-s steady-state task window: <i>unimanual</i>: 0.24, <i>synchronous</i> 0.42 <i>alternating</i> 0.47, <i>unbalanced</i> 0.47,), but not visible during rest connectivity (<i>unimanual</i> 0.40, <i>synchronous</i> 0.49 <i>alternating</i> 0.48, <i>unbalanced</i> 0.48). Additionally, all task derived measures were modulated by finger tapping speed. For the activation level derived measures, this effect was most pronounced when the performed tapping sequence was easy. During steady-state connectivity the modulation by finger tapping was strongest during <i>unimanual</i>, <i>alternating</i> and <i>unbalanced</i> tapping, and for the overall task connectivity the modulation by finger tapping speed was most pronounced as tapping sequences became most difficult (<i>alternating</i> and <i>unbalanced</i> tapping).</p>", "links"=>[], "tags"=>["neuroscience", "neuroimaging", "fmri", "psychology", "behavior", "Adjustment (psychology)", "Human performance", "Cognitive psychology", "learning", "therapies", "psychotherapy", "Experimental psychology", "neuropsychology", "region-of-interest"], "article_id"=>903977, "categories"=>["Biological Sciences", "Sociology"], "users"=>["Anna Zilverstand", "Bettina Sorger", "Jan Zimmermann", "Amanda Kaas", "Rainer Goebel"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085929.g005", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Within_participant_region_of_interest_results_/903977", "title"=>"Within-participant region-of-interest results.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-20 02:57:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1351207"], "description"=>"<p>The task-dependent modulation of the group-level overall task connectivity (26-s full task window, depicted on the left) and the steady-state task connectivity (12-s steady-state task window, shown on the right) are visualized schematically for the investigated functional network (M1 = primary motor cortex, dPMC = dorsal premotor cortex, SMA = supplementary motor area, V5 = visual motion area). The upper row shows the significant difference in functional connectivity between unimanual and bimanual tapping. The second row depicts the significant linear increase of functional connection with increasing demand on bimanual coordination during bimanual tapping. The third row shows how connectivity significantly increased with increasing tapping speed. The bottom row depicts the significant interaction effects between demand on bimanual coordination and tapping speed. While the effects were weaker during steady-state in comparison to overall task connectivity, the task-dependent modulations were qualitatively very similar independent of the time window used. Only one connection, the connection between the two primary motor cortices, showed all effects independent of the time window used. This connection also showed the highest average correlation in the functional network (the thickness of the depicted connections equals the average correlation across all experimental conditions).</p>", "links"=>[], "tags"=>["neuroscience", "neuroimaging", "fmri", "psychology", "behavior", "Adjustment (psychology)", "Human performance", "Cognitive psychology", "learning", "therapies", "psychotherapy", "Experimental psychology", "neuropsychology"], "article_id"=>903974, "categories"=>["Biological Sciences", "Sociology"], "users"=>["Anna Zilverstand", "Bettina Sorger", "Jan Zimmermann", "Amanda Kaas", "Rainer Goebel"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085929.g004", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Group_level_functional_network_results_/903974", "title"=>"Group-level functional network results.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-20 02:57:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1351197"], "description"=>"<p>All fMRI-based measures were derived from a network of a priori selected regions of interest (M1 = primary motor cortex, dPMC = dorsal premotor cortex, SMA = supplementary motor area, V5 = visual motion area), which are depicted schematically in panel <b>A</b>. The time windows (grey boxes) used in the functional connectivity analysis are superimposed on the schematic BOLD responses of the two regions of interest (solid and dotted line) in panel <b>B</b>.</p>", "links"=>[], "tags"=>["neuroscience", "neuroimaging", "fmri", "psychology", "behavior", "Adjustment (psychology)", "Human performance", "Cognitive psychology", "learning", "therapies", "psychotherapy", "Experimental psychology", "neuropsychology"], "article_id"=>903971, "categories"=>["Biological Sciences", "Sociology"], "users"=>["Anna Zilverstand", "Bettina Sorger", "Jan Zimmermann", "Amanda Kaas", "Rainer Goebel"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085929.g002", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Schematic_representation_of_functional_network_/903971", "title"=>"Schematic representation of functional network.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-20 02:57:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1351221"], "description"=>"<p>The criterion validity for detecting performed tapping speed was calculated by correlating the block-wise brain measures with the block-wise finger tapping speed. These brain-behavior correlations are presented for all participants for each of the three different bimanual tapping tasks separately as well as averaged (bold with asterisk = significant results).</p>", "links"=>[], "tags"=>["neuroscience", "neuroimaging", "fmri", "psychology", "behavior", "Adjustment (psychology)", "Human performance", "Cognitive psychology", "learning", "therapies", "psychotherapy", "Experimental psychology", "neuropsychology", "tapping"], "article_id"=>903988, "categories"=>["Biological Sciences", "Sociology"], "users"=>["Anna Zilverstand", "Bettina Sorger", "Jan Zimmermann", "Amanda Kaas", "Rainer Goebel"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085929.t003", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Correlation_with_finger_tapping_speed_/903988", "title"=>"Correlation with finger tapping speed.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-01-20 02:57:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1351196"], "description"=>"<p>The participants performed four different types of tapping sequences, which were selected to increase demand on bimanual coordination gradually: 1) <i>unimanual</i>: moving only the right index finger, 2) <i>bimanual synchronous</i>: moving both index fingers in synchrony, 3) <i>bimanual alternating</i>: moving both index fingers at the same pace in an alternating fashion, and 4) <i>bimanual unbalanced</i>: moving the left index finger in synchrony with the right index finger, but at half of the pace. Each of these tapping sequences was performed at four different tapping speeds for the right index finger (1, 2, 3, and 4 Hz), which resulted in 16 different experimental conditions. Task difficulty increased along both manipulated task dimensions.</p>", "links"=>[], "tags"=>["neuroscience", "neuroimaging", "fmri", "psychology", "behavior", "Adjustment (psychology)", "Human performance", "Cognitive psychology", "learning", "therapies", "psychotherapy", "Experimental psychology", "neuropsychology"], "article_id"=>903970, "categories"=>["Biological Sciences", "Sociology"], "users"=>["Anna Zilverstand", "Bettina Sorger", "Jan Zimmermann", "Amanda Kaas", "Rainer Goebel"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085929.g001", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Experimental_Design_/903970", "title"=>"Experimental Design.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-20 02:57:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1351215"], "description"=>"<p>The sensitivity and specificity in detecting if a task was uni- or bimanually performed was computed using a simple threshold approach. The results for the block-wise activation-level measures from right M1 (panel <b>A</b>), and the 26-s full task correlations (panel <b>B</b>), and the 12-s steady-state task correlations (panel <b>C</b>) are presented for two participants. Each dot represents one block. Significant results are marked with an asterisk. Activation level based and overall task connectivity measures both performed well in making this binary decision, while steady-state connectivity measures performed more poorly, but still above chance level (50%) in three of five participants (see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085929#pone-0085929-t002\" target=\"_blank\">table 2</a>).</p>", "links"=>[], "tags"=>["neuroscience", "neuroimaging", "fmri", "psychology", "behavior", "Adjustment (psychology)", "Human performance", "Cognitive psychology", "learning", "therapies", "psychotherapy", "Experimental psychology", "neuropsychology", "specificity", "detecting", "bimanual"], "article_id"=>903982, "categories"=>["Biological Sciences", "Sociology"], "users"=>["Anna Zilverstand", "Bettina Sorger", "Jan Zimmermann", "Amanda Kaas", "Rainer Goebel"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085929.g006", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sensitivity_and_specificity_in_detecting_bimanual_tapping_/903982", "title"=>"Sensitivity and specificity in detecting bimanual tapping.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-20 02:57:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1351224"], "description"=>"<p>The Talairach coordinates of the functionally defined regions of interest are listed for each individual participant. The Talairach coordinates for the group average and coordinates reported by a meta-analysis of 38 finger tapping studies <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085929#pone.0085929-Witt1\" target=\"_blank\">[44]</a> are shown for comparison. M1 = primary motor cortex, SMA = supplementary motor area, dPMC = dorsal premotor cortex, V5 = visual motion area.</p>", "links"=>[], "tags"=>["neuroscience", "neuroimaging", "fmri", "psychology", "behavior", "Adjustment (psychology)", "Human performance", "Cognitive psychology", "learning", "therapies", "psychotherapy", "Experimental psychology", "neuropsychology"], "article_id"=>903991, "categories"=>["Biological Sciences", "Sociology"], "users"=>["Anna Zilverstand", "Bettina Sorger", "Jan Zimmermann", "Amanda Kaas", "Rainer Goebel"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085929.t001", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Individual_regions_of_interest_/903991", "title"=>"Individual regions-of-interest.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-01-20 02:57:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1351223"], "description"=>"<p>The sensitivity and specificity (sensitivity/specificity) in detecting if a task was performed with only the right index finger (<i>unimanual</i>), or with both index fingers (<i>bimanual</i>) was computed for all participants using a simple threshold approach (bold with asterisk = significant results).</p>", "links"=>[], "tags"=>["neuroscience", "neuroimaging", "fmri", "psychology", "behavior", "Adjustment (psychology)", "Human performance", "Cognitive psychology", "learning", "therapies", "psychotherapy", "Experimental psychology", "neuropsychology", "specificity", "detecting", "bimanual"], "article_id"=>903990, "categories"=>["Biological Sciences", "Sociology"], "users"=>["Anna Zilverstand", "Bettina Sorger", "Jan Zimmermann", "Amanda Kaas", "Rainer Goebel"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085929.t002", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sensitivity_and_specificity_in_detecting_bimanual_tapping_/903990", "title"=>"Sensitivity and specificity in detecting bimanual tapping.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-01-20 02:57:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1351198"], "description"=>"<p>The behavioral results showed a significant linear increase of tapping speed consistent with the experimental manipulation for all participants. The actual tapping speed of the right index finger from all individuals (S01-05, mean ± individual SE), as well as the average (AVG) is plotted dependent on the required speed in panel <b>A</b>. Second, there was a significant linear increase of error rate with increasing demand on bimanual coordination (from left to right) in all participants. In panel <b>B</b> the individual error rate (S01-05, mean ± individual SE), and average (AVG) is plotted for the four performed tapping sequences.</p>", "links"=>[], "tags"=>["neuroscience", "neuroimaging", "fmri", "psychology", "behavior", "Adjustment (psychology)", "Human performance", "Cognitive psychology", "learning", "therapies", "psychotherapy", "Experimental psychology", "neuropsychology"], "article_id"=>903972, "categories"=>["Biological Sciences", "Sociology"], "users"=>["Anna Zilverstand", "Bettina Sorger", "Jan Zimmermann", "Amanda Kaas", "Rainer Goebel"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085929.g003", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Behavioral_results_/903972", "title"=>"Behavioral results.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-20 02:57:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/1351219"], "description"=>"<p>The criterion validity for detecting performed tapping speed was calculated by correlating the block-wise brain measures with the block-wise behavioral performance measures. The results from one representative participant are depicted for <i>bimanual synchronous</i> tapping (upper row) and <i>bimanual unbalanced</i> tapping (lower row). The correlation between finger tapping speed and the block-wise activation-level measures from left M1 (panel <b>A</b>), the 26-s full task block-wise correlations (panel <b>B</b>), and the 12-s steady-state task correlations (panel <b>C</b>) are shown. Each dot represents one block, with the regression line indicating the average strength of the brain-behavior correlation. Significant results are marked with an asterisk. The steady-state connectivity measures were modulated by finger tapping speed during the most difficult <i>unbalanced</i> tapping task, but not during the easier <i>synchronous</i> tapping task. The same effect is visible but less pronounced for the overall task connectivity measures, and much weaker for the activation-level based measures. The connectivity measures thus indicate overall task difficulty best, showing the strongest increase from low to high overall task difficulty.</p>", "links"=>[], "tags"=>["neuroscience", "neuroimaging", "fmri", "psychology", "behavior", "Adjustment (psychology)", "Human performance", "Cognitive psychology", "learning", "therapies", "psychotherapy", "Experimental psychology", "neuropsychology", "tapping"], "article_id"=>903986, "categories"=>["Biological Sciences", "Sociology"], "users"=>["Anna Zilverstand", "Bettina Sorger", "Jan Zimmermann", "Amanda Kaas", "Rainer Goebel"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0085929.g007", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Correlation_with_finger_tapping_speed_/903986", "title"=>"Correlation with finger tapping speed.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-20 02:57:19"}

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Relative Metric

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