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A confounding factor is head motion. Children move more than adults, older adults more than younger adults, and patients more than controls. Head motion varies considerably among individuals within the same population. Here we explored the influence of head motion on fcMRI estimates. Mean head displacement, maximum head displacement, the number of micro movements (> 0.1 mm), and head rotation were estimated in 1000 healthy, young adult subjects each scanned for two resting-state runs on matched 3T scanners. The majority of fcMRI variation across subjects was not linked to head motion. However, head motion had significant, systematic effects on fcMRI network measures. Head motion was associated with decreased functional coupling in the default and frontoparietal control networks — two networks characterized by coupling among distributed regions of association cortex. Other network measures increased with motion including estimates of local functional coupling and coupling between left and right motor regions — a region pair sometimes used as a control in studies to establish specificity. Comparisons between groups of individuals with subtly different levels of head motion yielded difference maps that could be mistaken for neuronal effects in other contexts. These effects are important to consider when interpreting variation between groups and across individuals.", "publicationTitle": "NeuroImage", "publisher": "", "place": "", "date": "January 2, 2012", "volume": "59", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "431-438", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1016/j.neuroimage.2011.07.044", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S1053811911008214", "accessDate": "2012-01-24T15:59:58Z", "PMID": "", "PMCID": "", "ISSN": "1053-8119", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "BOLD", "type": 1 }, { "tag": "Connectome", "type": 1 }, { "tag": "Functional MRI", "type": 1 }, { "tag": "Movement", "type": 1 }, { "tag": "Resting-state", "type": 1 } ], "collections": [ "TAMQU4EQ" ], "relations": {}, "dateAdded": "2012-01-24T15:59:58Z", "dateModified": "2012-01-24T15:59:58Z" } }, { "key": "U4R3XUJ8", "version": 1, "library": { "type": "group", "id": 24324, "name": "CONCH lab", "links": { "alternate": { "href": "https://www.zotero.org/groups/conch_lab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/24324/items/U4R3XUJ8", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/conch_lab/items/U4R3XUJ8", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/24324/items/GBQIP59S", "type": "application/json" } }, "meta": { "createdByUser": { "id": 269462, "username": "conorwild", "name": "Conor Wild", "links": { "alternate": { "href": "https://www.zotero.org/conorwild", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "U4R3XUJ8", "version": 1, "parentItem": "GBQIP59S", "itemType": "attachment", "linkMode": "imported_url", "title": "Power et al. - 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2012 - Spurious but systematic correlations in functional", "md5": "fa91514de231a216e8df0945e81887e7", "mtime": 1327416549239, "tags": [], "relations": {}, "dateAdded": "2012-01-24T14:49:07Z", "dateModified": "2012-01-24T14:49:49Z" } }, { "key": "GBQIP59S", "version": 1, "library": { "type": "group", "id": 24324, "name": "CONCH lab", "links": { "alternate": { "href": "https://www.zotero.org/groups/conch_lab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/24324/items/GBQIP59S", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/conch_lab/items/GBQIP59S", "type": "text/html" } }, "meta": { "createdByUser": { "id": 269462, "username": "conorwild", "name": "Conor Wild", "links": { "alternate": { "href": "https://www.zotero.org/conorwild", "type": "text/html" } } }, "creatorSummary": "Power et al.", "parsedDate": "2012-02-01", "numChildren": 2 }, "data": { "key": "GBQIP59S", "version": 1, "itemType": "journalArticle", "title": "Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion", "creators": [ { "creatorType": "author", "firstName": "Jonathan D.", "lastName": "Power" }, { "creatorType": "author", "firstName": "Kelly A.", "lastName": "Barnes" }, { "creatorType": "author", "firstName": "Abraham Z.", "lastName": "Snyder" }, { "creatorType": "author", "firstName": "Bradley L.", "lastName": "Schlaggar" }, { "creatorType": "author", "firstName": "Steven E.", "lastName": "Petersen" } ], "abstractNote": "Here, we demonstrate that subject motion produces substantial changes in the timecourses of resting state functional connectivity MRI (rs-fcMRI) data despite compensatory spatial registration and regression of motion estimates from the data. These changes cause systematic but spurious correlation structures throughout the brain. Specifically, many long-distance correlations are decreased by subject motion, whereas many short-distance correlations are increased. These changes in rs-fcMRI correlations do not arise from, nor are they adequately countered by, some common functional connectivity processing steps. Two indices of data quality are proposed, and a simple method to reduce motion-related effects in rs-fcMRI analyses is demonstrated that should be flexibly implementable across a variety of software platforms. We demonstrate how application of this technique impacts our own data, modifying previous conclusions about brain development. 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2011 - Post hoc Bayesian model selection.pdf", "accessDate": "2012-01-23T19:18:22Z", "url": "http://pdn.sciencedirect.com/science?_ob=MiamiImageURL&_cid=272508&_user=940030&_pii=S1053811911003417&_check=y&_origin=article&_zone=toolbar&_coverDate=15-Jun-2011&view=c&originContentFamily=serial&wchp=dGLbVlB-zSkWz&md5=375ea5b99be4e3e2b97c418af5eaa33e/1-s2.0-S1053811911003417-main.pdf", "note": "", "contentType": "application/pdf", "charset": "", "filename": "Friston and Penny - 2011 - Post hoc Bayesian model selection.pdf", "md5": "34eae918f43ea8f0ac5025b9cc185538", "mtime": 1327346303148, "tags": [], "relations": {}, "dateAdded": "2012-01-23T19:18:22Z", "dateModified": "2012-01-23T19:57:10Z" } }, { "key": "ZD8CCTEB", "version": 1, "library": { "type": "group", "id": 24324, "name": "CONCH lab", "links": { "alternate": { "href": "https://www.zotero.org/groups/conch_lab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/24324/items/ZD8CCTEB", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/conch_lab/items/ZD8CCTEB", "type": "text/html" } }, "meta": { "createdByUser": { "id": 269462, "username": "conorwild", "name": "Conor Wild", "links": { "alternate": { "href": "https://www.zotero.org/conorwild", "type": "text/html" } } }, "creatorSummary": "Friston", "numChildren": 2 }, "data": { "key": "ZD8CCTEB", "version": 1, "itemType": "journalArticle", "title": "The history of the future of the Bayesian brain", "creators": [ { "creatorType": "author", "firstName": "Karl", "lastName": "Friston" } ], "abstractNote": "The slight perversion of the original title of this piece (The Future of the Bayesian Brain) reflects my attempt to write prospectively about ‘Science and Stories’ over the past 20 years. I will meet this challenge by dealing with the future and then turning to its history. The future of the Bayesian brain (in neuroimaging) is clear: it is the application of dynamic causal modeling to understand how the brain conforms to the free energy principle. In this context, the Bayesian brain is a corollary of the free energy principle, which says that any self organizing system (like a brain or neuroimaging community) must maximize the evidence for its own existence, which means it must minimize its free energy using a model of its world. Dynamic causal modeling involves finding models of the brain that have the greatest evidence or the lowest free energy. In short, the future of imaging neuroscience is to refine models of the brain to minimize free energy, where the brain refines models of the world to minimize free energy. This endeavor itself minimizes free energy because our community is itself a self organizing system. I cannot imagine an alternative future that has the same beautiful self consistency as mine. Having dispensed with the future, we can now focus on the past, which is much more interesting:", "publicationTitle": "NeuroImage", "publisher": "", "place": "", "date": "", "volume": "", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1016/j.neuroimage.2011.10.004", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S1053811911011657", "accessDate": "2012-01-23T19:56:44Z", "PMID": "", "PMCID": "", "ISSN": "1053-8119", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Bayesian brain", "type": 1 }, { "tag": "Effective connectivity", "type": 1 }, { "tag": "Free energy", "type": 1 }, { "tag": "Functional integration", "type": 1 }, { "tag": "Generative models", "type": 1 }, { "tag": "Inference", "type": 1 }, { "tag": "Optimization", "type": 1 }, { "tag": "Predictive coding", "type": 1 } ], "collections": [ "TAMQU4EQ" ], "relations": {}, "dateAdded": "2012-01-23T19:56:44Z", "dateModified": "2012-01-23T19:57:03Z" } }, { "key": "PRNWP3CM", "version": 1, "library": { "type": "group", "id": 24324, "name": "CONCH lab", "links": { "alternate": { "href": "https://www.zotero.org/groups/conch_lab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/24324/items/PRNWP3CM", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/conch_lab/items/PRNWP3CM", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/24324/items/RFS9ZJCC", "type": "application/json" } }, "meta": { "createdByUser": { "id": 269462, "username": "conorwild", "name": "Conor Wild", "links": { "alternate": { "href": "https://www.zotero.org/conorwild", "type": "text/html" } } } }, "data": { "key": "PRNWP3CM", "version": 1, "parentItem": "RFS9ZJCC", "itemType": "attachment", "linkMode": "imported_url", "title": "ScienceDirect Snapshot", "accessDate": "2012-01-23T19:18:21Z", "url": "http://www.sciencedirect.com/science/article/pii/S1053811911003417", "note": "", "contentType": "", "charset": "", "filename": "Friston and Penny - 2011 - Post hoc Bayesian model selection", "md5": "31871ea11956e1553a0dbb211b8cf619", "mtime": 1327346303442, "tags": [], "relations": {}, "dateAdded": "2012-01-23T19:18:21Z", "dateModified": "2012-01-23T19:18:43Z" } }, { "key": "RFS9ZJCC", "version": 1, "library": { "type": "group", "id": 24324, "name": "CONCH lab", "links": { "alternate": { "href": "https://www.zotero.org/groups/conch_lab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/24324/items/RFS9ZJCC", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/conch_lab/items/RFS9ZJCC", "type": "text/html" } }, "meta": { "createdByUser": { "id": 269462, "username": "conorwild", "name": "Conor Wild", "links": { "alternate": { "href": "https://www.zotero.org/conorwild", "type": "text/html" } } }, "creatorSummary": "Friston and Penny", "parsedDate": "2011-06-15", "numChildren": 2 }, "data": { "key": "RFS9ZJCC", "version": 1, "itemType": "journalArticle", "title": "Post hoc Bayesian model selection", "creators": [ { "creatorType": "author", "firstName": "Karl", "lastName": "Friston" }, { "creatorType": "author", "firstName": "Will", "lastName": "Penny" } ], "abstractNote": "This note describes a Bayesian model selection or optimization procedure for post hoc inferences about reduced versions of a full model. The scheme provides the evidence (marginal likelihood) for any reduced model as a function of the posterior density over the parameters of the full model. It rests upon specifying models through priors on their parameters, under the assumption that the likelihood remains the same for all models considered. This provides a quick and efficient scheme for scoring arbitrarily large numbers of models, after inverting a single (full) model. In turn, this enables the selection among discrete models that are distinguished by the presence or absence of free parameters, where free parameters are effectively removed from the model using very precise shrinkage priors. An alternative application of this post hoc model selection considers continuous model spaces, defined in terms of hyperparameters (sufficient statistics) of the prior density over model parameters. In this instance, the prior (model) can be optimized with respect to its evidence. The expressions for model evidence become remarkably simple under the Laplace (Gaussian) approximation to the posterior density. Special cases of this scheme include Savage–Dickey density ratio tests for reduced models and automatic relevance determination in model optimization. We illustrate the approach using general linear models and a more complicated nonlinear state-space model.", "publicationTitle": "NeuroImage", "publisher": "", "place": "", "date": "June 15, 2011", "volume": "56", "issue": "4", "section": "", "partNumber": "", "partTitle": "", "pages": "2089-2099", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1016/j.neuroimage.2011.03.062", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S1053811911003417", "accessDate": "2012-01-23T19:18:18Z", "PMID": "", "PMCID": "", "ISSN": "1053-8119", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Automatic relevance determination", "type": 1 }, { "tag": "Bayesian model evidence", "type": 1 }, { "tag": "Hyperparameters", "type": 1 }, { "tag": "Model selection", "type": 1 }, { "tag": "Savage–Dickey density ratio", "type": 1 } ], "collections": [ "TAMQU4EQ" ], "relations": {}, "dateAdded": "2012-01-23T19:18:18Z", "dateModified": "2012-01-23T19:18:18Z" } }, { "key": "V8FSKD8A", "version": 1, "library": { "type": "group", "id": 24324, "name": "CONCH lab", "links": { "alternate": { "href": "https://www.zotero.org/groups/conch_lab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/24324/items/V8FSKD8A", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/conch_lab/items/V8FSKD8A", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/24324/items/9HNPD9MC", "type": "application/json" } }, "meta": { "createdByUser": { "id": 269462, "username": "conorwild", "name": "Conor Wild", "links": { "alternate": { "href": "https://www.zotero.org/conorwild", "type": "text/html" } } } }, "data": { "key": "V8FSKD8A", "version": 1, "parentItem": "9HNPD9MC", "itemType": "attachment", "linkMode": "imported_url", "title": "ScienceDirect Snapshot", "accessDate": "2012-01-23T19:10:38Z", "url": "http://www.sciencedirect.com/science/article/pii/S105381191001623X", "note": "", "contentType": "", "charset": "", "filename": "Friston et al. - 2011 - Network discovery with DCM", "md5": "888b84fdf4fcf20c24b4c72eef193607", "mtime": 1327345841506, "tags": [], "relations": {}, "dateAdded": "2012-01-23T19:10:38Z", "dateModified": "2012-01-23T19:11:22Z" } }, { "key": "9HNPD9MC", "version": 1, "library": { "type": "group", "id": 24324, "name": "CONCH lab", "links": { "alternate": { "href": "https://www.zotero.org/groups/conch_lab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/24324/items/9HNPD9MC", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/conch_lab/items/9HNPD9MC", "type": "text/html" } }, "meta": { "createdByUser": { "id": 269462, "username": "conorwild", "name": "Conor Wild", "links": { "alternate": { "href": "https://www.zotero.org/conorwild", "type": "text/html" } } }, "creatorSummary": "Friston et al.", "parsedDate": "2011-06-01", "numChildren": 2 }, "data": { "key": "9HNPD9MC", "version": 1, "itemType": "journalArticle", "title": "Network discovery with DCM", "creators": [ { "creatorType": "author", "firstName": "Karl J.", "lastName": "Friston" }, { "creatorType": "author", "firstName": "Baojuan", "lastName": "Li" }, { "creatorType": "author", "firstName": "Jean", "lastName": "Daunizeau" }, { "creatorType": "author", "firstName": "Klaas E.", "lastName": "Stephan" } ], "abstractNote": "This paper is about inferring or discovering the functional architecture of distributed systems using Dynamic Causal Modelling (DCM). We describe a scheme that recovers the (dynamic) Bayesian dependency graph (connections in a network) using observed network activity. This network discovery uses Bayesian model selection to identify the sparsity structure (absence of edges or connections) in a graph that best explains observed time-series. The implicit adjacency matrix specifies the form of the network (e.g., cyclic or acyclic) and its graph-theoretical attributes (e.g., degree distribution). The scheme is illustrated using functional magnetic resonance imaging (fMRI) time series to discover functional brain networks. Crucially, it can be applied to experimentally evoked responses (activation studies) or endogenous activity in task-free (resting state) fMRI studies. Unlike conventional approaches to network discovery, DCM permits the analysis of directed and cyclic graphs. Furthermore, it eschews (implausible) Markovian assumptions about the serial independence of random fluctuations. The scheme furnishes a network description of distributed activity in the brain that is optimal in the sense of having the greatest conditional probability, relative to other networks. The networks are characterised in terms of their connectivity or adjacency matrices and conditional distributions over the directed (and reciprocal) effective connectivity between connected nodes or regions. We envisage that this approach will provide a useful complement to current analyses of functional connectivity for both activation and resting-state studies.", "publicationTitle": "NeuroImage", "publisher": "", "place": "", "date": "June 1, 2011", "volume": "56", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "1202-1221", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1016/j.neuroimage.2010.12.039", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S105381191001623X", "accessDate": "2012-01-23T19:10:36Z", "PMID": "", "PMCID": "", "ISSN": "1053-8119", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Bayesian", "type": 1 }, { "tag": "Connectivity", "type": 1 }, { "tag": "Dynamic Causal Modelling", "type": 1 }, { "tag": "Generalised Filtering", "type": 1 }, { "tag": "Neuronal", "type": 1 }, { "tag": "Random differential equations", "type": 1 }, { "tag": "Resting-state", "type": 1 }, { "tag": "Stochastic", "type": 1 }, { "tag": "fMRI", "type": 1 } ], "collections": [ "TAMQU4EQ" ], "relations": {}, "dateAdded": "2012-01-23T19:10:36Z", "dateModified": "2012-01-23T19:10:36Z" } }, { "key": "5MCMT578", "version": 1, "library": { "type": "group", "id": 24324, "name": "CONCH lab", "links": { "alternate": { "href": "https://www.zotero.org/groups/conch_lab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/24324/items/5MCMT578", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/conch_lab/items/5MCMT578", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/24324/items/TVTIGPDX", "type": "application/json" } }, "meta": { "createdByUser": { "id": 269462, "username": "conorwild", "name": "Conor Wild", "links": { "alternate": { "href": "https://www.zotero.org/conorwild", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "5MCMT578", "version": 1, "parentItem": "TVTIGPDX", "itemType": "attachment", "linkMode": "imported_url", "title": "Valdes-Sosa et al. - Effective connectivity Influence, causality and b.pdf", "accessDate": "2011-04-21T16:27:19Z", "url": "http://www.sciencedirect.com/science?_ob=MImg&_imagekey=B6WNP-52JKSS6-1-W&_cdi=6968&_user=1025668&_pii=S1053811911003375&_origin=gateway&_coverDate=04%2F06%2F2011&_sk=999999999&view=c&wchp=dGLzVzb-zSkzV&md5=33cbc42ce7bb6448e1672f13c5c35e1b&ie=/sdarticle.pdf", "note": "", "contentType": "application/pdf", "charset": "", "filename": "Valdes-Sosa et al. - Effective connectivity Influence, causality and b.pdf", "md5": "30fde89b79f9061f0585dc51ad90ad71", "mtime": 1303403267000, "tags": [], "relations": {}, "dateAdded": "2011-04-21T16:27:47Z", "dateModified": "2011-04-21T16:28:27Z" } }, { "key": "TVTIGPDX", "version": 1, "library": { "type": "group", "id": 24324, "name": "CONCH lab", "links": { "alternate": { "href": "https://www.zotero.org/groups/conch_lab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/24324/items/TVTIGPDX", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/conch_lab/items/TVTIGPDX", "type": "text/html" } }, "meta": { "createdByUser": { "id": 269462, "username": "conorwild", "name": "Conor Wild", "links": { "alternate": { "href": "https://www.zotero.org/conorwild", "type": "text/html" } } }, "creatorSummary": "Valdes-Sosa et al.", "numChildren": 1 }, "data": { "key": "TVTIGPDX", "version": 1, "itemType": "journalArticle", "title": "Effective connectivity: Influence, causality and biophysical modeling", "creators": [ { "creatorType": "author", "firstName": "Pedro A.", "lastName": "Valdes-Sosa" }, { "creatorType": "author", "firstName": "Alard", "lastName": "Roebroeck" }, { "creatorType": "author", "firstName": "Jean", "lastName": "Daunizeau" }, { "creatorType": "author", "firstName": "Karl", "lastName": "Friston" } ], "abstractNote": "


This is the final paper in a Comments and Controversies series dedicated to \"The identification of interacting networks in the brain using fMRI: Model selection, causality and deconvolution\". We argue that discovering effective connectivity depends critically on state-space models with biophysically informed observation and state equations. These models have to be endowed with priors on unknown parameters and afford checks for model Identifiability. We consider the similarities and differences among Dynamic Causal Modeling, Granger Causal Modeling and other approaches. We establish links between past and current statistical causal modeling, in terms of Bayesian dependency graphs and Wiener-Akaike-Granger-Schweder influence measures. We show that some of the challenges faced in this field have promising solutions and speculate on future developments.

", "publicationTitle": "NeuroImage", "publisher": "", "place": "", "date": "", "volume": "In Press, Uncorrected Proof", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1016/j.neuroimage.2011.03.058", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/B6WNP-52JKSS6-1/2/245a53f406f642f2bf5a8e67670f1da3", "accessDate": "2011-04-21T16:27:18Z", "PMID": "", "PMCID": "", "ISSN": "1053-8119", "archive": "", "archiveLocation": "", "shortTitle": "Effective connectivity", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Dynamic Causal Modeling", "type": 1 }, { "tag": "EEG", "type": 1 }, { "tag": "Effective connectivity", "type": 1 }, { "tag": "Granger causality", "type": 1 }, { "tag": "fMRI", "type": 1 } ], "collections": [ "TAMQU4EQ" ], "relations": {}, "dateAdded": "2011-04-21T16:27:47Z", "dateModified": "2011-04-21T16:27:47Z" } }, { "key": "J5BT3XT5", "version": 1, "library": { "type": "group", "id": 24324, "name": "CONCH lab", "links": { "alternate": { "href": "https://www.zotero.org/groups/conch_lab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/24324/items/J5BT3XT5", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/conch_lab/items/J5BT3XT5", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/24324/items/AD3NDPKK", "type": "application/json" } }, "meta": { "createdByUser": { "id": 269462, "username": "conorwild", "name": "Conor Wild", "links": { "alternate": { "href": "https://www.zotero.org/conorwild", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "J5BT3XT5", "version": 1, "parentItem": "AD3NDPKK", "itemType": "attachment", "linkMode": "imported_file", "title": "Smith et al. - 2010 - Network modelling methods for FMRI.pdf", "accessDate": "", "url": "", "note": "", "contentType": "application/pdf", "charset": "", "filename": "Smith et al. - 2010 - Network modelling methods for FMRI.pdf", "md5": "308266f75d38df91d4103228554ac958", "mtime": 1303403150000, "tags": [], "relations": {}, "dateAdded": "2011-04-21T16:25:50Z", "dateModified": "2011-04-21T16:26:30Z" } }, { "key": "AD3NDPKK", "version": 1, "library": { "type": "group", "id": 24324, "name": "CONCH lab", "links": { "alternate": { "href": "https://www.zotero.org/groups/conch_lab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/24324/items/AD3NDPKK", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/conch_lab/items/AD3NDPKK", "type": "text/html" } }, "meta": { "createdByUser": { "id": 269462, "username": "conorwild", "name": "Conor Wild", "links": { "alternate": { "href": "https://www.zotero.org/conorwild", "type": "text/html" } } }, "creatorSummary": "Smith et al.", "parsedDate": "2010", "numChildren": 1 }, "data": { "key": "AD3NDPKK", "version": 1, "itemType": "journalArticle", "title": "Network modelling methods for FMRI", "creators": [ { "creatorType": "author", "firstName": "S. M", "lastName": "Smith" }, { "creatorType": "author", "firstName": "K. L", "lastName": "Miller" }, { "creatorType": "author", "firstName": "G.", "lastName": "Salimi-Khorshidi" }, { "creatorType": "author", "firstName": "M.", "lastName": "Webster" }, { "creatorType": "author", "firstName": "C. F", "lastName": "Beckmann" }, { "creatorType": "author", "firstName": "T. E", "lastName": "Nichols" }, { "creatorType": "author", "firstName": "J. D", "lastName": "Ramsey" }, { "creatorType": "author", "firstName": "M. W", "lastName": "Woolrich" } ], "abstractNote": "", "publicationTitle": "Neuroimage", "publisher": "", "place": "", "date": "2010", "volume": "", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "1053-8119", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Google Scholar", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [ "TAMQU4EQ" ], "relations": {}, "dateAdded": "2011-04-21T16:25:50Z", "dateModified": "2011-04-21T16:25:50Z" } }, { "key": "7IK4GPJB", "version": 1, "library": { "type": "group", "id": 24324, "name": "CONCH lab", "links": { "alternate": { "href": "https://www.zotero.org/groups/conch_lab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/24324/items/7IK4GPJB", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/conch_lab/items/7IK4GPJB", "type": "text/html" } }, "meta": { "createdByUser": { "id": 269462, "username": "conorwild", "name": "Conor Wild", "links": { "alternate": { "href": "https://www.zotero.org/conorwild", "type": "text/html" } } }, "creatorSummary": "Koch et al.", "parsedDate": "2002-05", "numChildren": 0 }, "data": { "key": "7IK4GPJB", "version": 1, "itemType": "journalArticle", "title": "An Investigation of Functional and Anatomical Connectivity Using Magnetic Resonance Imaging", "creators": [ { "creatorType": "author", "firstName": "Martin A.", "lastName": "Koch" }, { "creatorType": "author", "firstName": "David G.", "lastName": "Norris" }, { "creatorType": "author", "firstName": "Margret", "lastName": "Hund-Georgiadis" } ], "abstractNote": "This article examines functional and anatomical connectivity in healthy human subjects measured with magnetic resonance imaging methods. Anatomical connectivity in white matter is obtained from measurements of the diffusion tensor. A Monte-Carlo simulation determines the probability that a particle diffuses between two points, with the probability of a jump in a particular direction from a given voxel being based on the local value of the diffusion tensor components. Functional connectivity between grey matter pixels is assessed without recourse to a specific activation paradigm, by calculating the correlation coefficient between random fluctuations in the blood oxygenation level-dependent signal time course in different pixels. The methods are used to examine the anatomical and functional connectivities between crowns of adjacent gyri. A high functional connectivity was found between grey matter pixels, with white matter displaying only very low correlation. A comparison of the measurements of anatomical and functional connectivity found that there is no simple correlation between these measures, except that low values of functional connectivity were not found together with high values of anatomical connectivity. Furthermore pairs of regions situated around the central sulcus indicated a dependence of the two connectivity measures on each other. These results are in accordance with an interpretation that regions which are clearly directly linked by white matter fiber tracts should show high functional connectivity, but that the inverse need not be true as functional connectivity may also be indirectly mediated via more distant grey matter regions.", "publicationTitle": "NeuroImage", "publisher": "", "place": "", "date": "May 2002", "volume": "16", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "241-250", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1006/nimg.2001.1052", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/B6WNP-45N4MHG-P/2/ffffb761ca7d46b67016aadb8e595219", "accessDate": "2011-03-08T16:57:15Z", "PMID": "", "PMCID": "", "ISSN": "1053-8119", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "connectivity; 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Natural speech can be reproduced using as few as three time-varying sinusoids mimicking the corresponding speech formants. Untrained listeners are able to transcribe this [`]sine-wave' speech with a high degree of reliability. Coherent phonetic percepts generated by sine-wave speech occur despite an apparent lack of those cues on which low level auditory grouping processes are believed to operate. Consequently, it has been proposed that speech perception is governed by processes operating independently of those described by auditory scene analysis. This paper re-examines the evidence provided by previous perceptual studies of sine-wave speech and presents new data, from perceptual studies employing stimuli constructed from simultaneous sine-wave wave speech sources. These new studies suggest that in conditions that are closer to those of everyday listening, grouping cues have an important role in the formation of coherent speech percepts. In conjunction with these perceptual studies, results from automatic segregation and recognition tasks suggest that sine-wave speech contains sufficient low level, non speech-specific, structure to allow partial descriptions of sine-wave sources to be recovered from two-source mixtures. It is argued that these partial descriptions may be sufficient to account for the limited intelligibility observed in two-source sine-wave speech listening tests.", "publicationTitle": "Speech Communication", "publisher": "", "place": "", "date": "April 1999", "volume": "27", "issue": "3-4", "section": "", "partNumber": "", "partTitle": "", "pages": "159-174", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1016/S0167-6393(98)00081-8", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/B6V1C-3W49BY3-2/2/fb1682cb2d55e27168c2628bc745926f", "accessDate": "2010-09-29T00:03:23Z", "PMID": "", "PMCID": "", "ISSN": "0167-6393", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [ "TAMQU4EQ" ], "relations": {}, "dateAdded": "2010-09-29T00:03:23Z", "dateModified": "2010-09-29T00:03:23Z" } }, { "key": "EI7X3RQE", "version": 1, "library": { "type": "group", "id": 24324, "name": "CONCH lab", "links": { "alternate": { "href": "https://www.zotero.org/groups/conch_lab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/24324/items/EI7X3RQE", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/conch_lab/items/EI7X3RQE", "type": "text/html" } }, "meta": { "createdByUser": { "id": 269462, "username": "conorwild", "name": "Conor Wild", "links": { "alternate": { "href": "https://www.zotero.org/conorwild", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "EI7X3RQE", "version": 1, "itemType": "bookSection", "title": "", "creators": [], "abstractNote": "", "bookTitle": "", "series": "", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "", "publisher": "", "place": "", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "pages": "", "ISBN": "", "DOI": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2010-09-28T22:07:45Z", "dateModified": "2010-09-28T22:07:45Z" } }, { "key": "S4QJ2HHT", "version": 1, "library": { "type": "group", "id": 24324, "name": "CONCH lab", "links": { "alternate": { "href": "https://www.zotero.org/groups/conch_lab", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/24324/items/S4QJ2HHT", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/conch_lab/items/S4QJ2HHT", "type": "text/html" } }, "meta": { "createdByUser": { "id": 269462, "username": "conorwild", "name": "Conor Wild", "links": { "alternate": { "href": "https://www.zotero.org/conorwild", "type": "text/html" } } }, "creatorSummary": "Nootebloom et al.", "numChildren": 0 }, "data": { "key": "S4QJ2HHT", "version": 1, "itemType": "journalArticle", "title": "Contributions of Prosody to Speech Perception.", "creators": [ { "creatorType": "author", "firstName": "S G", "lastName": "Nootebloom" }, { "creatorType": "author", "firstName": "J P L", "lastName": "Brokx" }, { "creatorType": "author", "firstName": "J J", "lastName": "De Rooij" } ], "abstractNote": "", "publicationTitle": "", "publisher": "", "place": "", "date": "", "volume": "", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [ "TAMQU4EQ" ], "relations": {}, "dateAdded": "2010-09-28T22:06:29Z", "dateModified": "2010-09-28T22:07:23Z" } } ]