Partial Least Squares (PLS) methods for neuroimaging: A tutorial and review

Krishnan, Anjali; Williams, Lynne J.; McIntosh, Anthony R.; Abdi, Hervé

doi:10.1016/j.neuroimage.2010.07.034

Cited by 1,085 publications

(1,072 citation statements)

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“…Comparing the eigenvalues to a null distribution obtained using surrogate data avoids making parametric assumption about the noise. This approach is similar to how significant latent dimensions are estimated in PLS (Krishnan et al, 2011;McIntosh et al, 1996) and in other fields studying time series (e.g. Bjornsson and Venegas, 1997).…”

Section: Comparing Hc Subjects and Rrms Patientsmentioning

confidence: 94%

“…Singular value decomposition 1 (SVD) has also been applied to uncover patterns of relations between brain activity and experimental conditions, behavior or the activity of other voxels in a seed region, in a method called Partial Least Squares (PLS) (Krishnan et al, 2011;McIntosh et al, 1996). The right singular vectors contain patterns of voxels that are associated with e.g.…”

Section: Introductionmentioning

confidence: 99%

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Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest

et al. 2013

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Functional connectivity (FC) as measured by correlation between fMRI BOLD time courses of distinct brain regions has revealed meaningful organization of spontaneous fluctuations in the resting brain. However, an increasing amount of evidence points to non-stationarity of FC; i.e., FC dynamically changes over time reflecting additional and rich information about brain organization, but representing new challenges for analysis and interpretation. Here, we propose a data-driven approach based on principal component analysis (PCA) to reveal hidden patterns of coherent FC dynamics across multiple subjects. We demonstrate the feasibility and relevance of this new approach by examining the differences in dynamic FC between 13 healthy control subjects and 15 minimally disabled relapse-remitting multiple sclerosis patients. We estimated whole-brain dynamic FC of regionally-averaged BOLD activity using sliding time windows. We then used PCA to identify FC patterns, termed "eigenconnectivities", that reflect meaningful patterns in FC fluctuations. We then assessed the contributions of these patterns to the dynamic FC at any given time point and identified a network of connections centered on the default-mode network with altered contribution in patients. Our results complement traditional stationary analyses, and reveal novel insights into brain connectivity dynamics and their modulation in a neurodegenerative disease.© 2013 Elsevier Inc. All rights reserved. IntroductionSpontaneous fluctuations of the functional MRI (fMRI) bloodoxygen-level-dependent (BOLD) signal are not random but temporally coherent between distinct brain regions. While these fluctuations were long considered as "noise", Biswal et al. (1995) showed that fluctuations of motor areas were correlated even in the absence of a motor task. Several other networks of coherent BOLD activity between remote brain regions have since been identified, including visual, auditory, language and attention networks, and a network called the "default mode network" (DMN) which reduces its activity during attentiondemanding tasks. These networks of regions with coherent activity during rest are consistent across subjects and closely resemble the brain's functional organization of evoked responses (Damoiseaux et al., 2006;Fox and Raichle, 2007;Laird et al., 2011;Smith et al., 2009). Coherent BOLD activity persists during sleep and in anesthetized monkeys, suggesting that it reflects a fundamental property of the brain's functional organization (Larson-Prior et al., 2009;Vincent et al., 2007).Coherent BOLD activity, known as "functional connectivity" (FC), is modulated by learning (Bassett et al., 2011), cognitive and affective states (Cribben et al., 2012;Ekman et al., 2012;Eryilmaz et al., 2011;Richiardi et al., 2011;Shirer et al., 2012) and also spontaneously Chang and Glover, 2010; Kitzbichler et al., 2009). Chang andGlover (2010) showed that FC between the posterior cingulate cortex, a key region of the default mode network, and various other brain regions was highly dy...

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Section: Comparing Hc Subjects and Rrms Patientsmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest

et al. 2013

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“…Most of these methods are based on correlations or covariance between regional measures of activity obtained with fMRI (or some other neuroimaging technique), and range from relatively simple assessments of correlations between the time courses of two or more brain regions 105 , to more complex multivariate approaches that assess brain-wide patterns of connectivity, such as independent component analysis 116 , or partial least squares 198,199 . Another approach is that of graph theory 200 , which uses the number of correlations that characterize various regions to identify areas with large numbers of connections (hubs) and to cluster together subgroups of regions with strong connectivity inside larger collections of areas.…”

Section: Box 1 Measuring Activity In Brain Networkmentioning

confidence: 99%

The cognitive neuroscience of ageing

2012

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PrefaceThe availability of neuroimaging technology has spurred a marked increase in the human cognitive neuroscience literature, including the study of cognitive aging. Although there is a growing consensus that the aging brain retains considerable plasticity of function, currently measured primarily by means of functional magnetic resonance imaging, it is less clear how age differences in brain activity relate to cognitive performance. The field also is hampered by the complexity of the aging process itself and the large number of factors that are influenced by age. In this review, current trends and unresolved issues in the cognitive neuroscience of aging are discussed.

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“…We used partial least squares (PLS; Krishnan, Williams, McIntosh, & Abdi, 2011;Lobaugh, West, & McIntosh, 2001) to examine neuromagnetic brain activity across all 72 brain regions of interest as a function of age group and task. The term "partial least squares" refers to the computation of an optimal squares fit to part of a covariance structure that is attributable to the experimental manipulations or that relates to a given outcome measure.…”

Section: Pls Analysismentioning

confidence: 99%

Visual dominance and multisensory integration changes with age

2013

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Objects comprise of visual and auditory signatures that arrive through distinct sensory channels. Exposure to cross-modal events sets up expectations about what a given object most likely "sounds" like, and vice versa, thereby facilitating detection and recognition. Whereas episodic and working memory functions decline with age, the extent to which multisensory integration processes change with age remains an open question. In the present study, we examined whether multisensory integration processes play a compensatory role in normal aging. Magnetoencephalography recordings of semantically-related cross-modal and unimodal auditory and visual stimuli captured the spatiotemporal dynamics of multisensory responses in young and older adults. Whereas sensory-specific regions showed increased activity in response to cross-modal compared to unimodal stimuli 100 ms after stimulus onset in both age groups, posterior parietal and medial prefrontal regions responded preferentially to cross-modal stimuli between 150 and 300 ms in the older group only. Additionally, faster detection of cross-modal stimuli correlated with increased activity in inferior parietal and medial prefrontal regions 100 ms after stimulus onset in older compared to younger adults. Age-related differences in visual dominance were also observed with older adults exhibiting significantly larger multisensory facilitation effects relative to the auditory modality. Using structural equation modeling, we showed that age-related increases in parietal and medial prefrontal source activity predicted faster detection of cross-modal stimuli. Furthermore, the relationship between performance and source activity was mediated by age-related reductions in gray matter volume in those regions. Thus, we propose that multisensory integration processes change with age such that posterior parietal and medial prefrontal activity underlies the integrated response in older adults. AbstractObjects comprise of visual and auditory signatures that arrive through distinct sensory channels. Exposure to cross-modal events sets up expectations about what a given object most likely "sounds" like, and vice versa, thereby facilitating detection and recognition. Whereas episodic and working memory functions decline with age, the extent to which multisensory integration processes change with age remains an open question. In the present study, we examined whether multisensory integration processes play a compensatory role in normal aging. Magnetoencephalography recordings of semantically-related cross-modal and unimodal auditory and visual stimuli captured the spatiotemporal dynamics of multisensory responses in young and older adults. Whereas sensory-specific regions showed increased activity in response to cross-modal compared to unimodal stimuli 100ms after stimulus onset in both age groups, posterior parietal and medial prefrontal regions responded preferentially to cross-modal stimuli between 150 and 300ms in the older group only. Additionally, faster detection of cross-moda...

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Partial Least Squares (PLS) methods for neuroimaging: A tutorial and review

Cited by 1,085 publications

References 61 publications

Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest

Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest

The cognitive neuroscience of ageing

Visual dominance and multisensory integration changes with age

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