A Fast Fixed-Point Algorithm for Independent Component Analysis

Hyvärinen, Aapo; Oja, Erkki

doi:10.1162/neco.1997.9.7.1483

Cited by 2,993 publications

(1,728 citation statements)

References 6 publications

Supporting

Mentioning

1,699

Contrasting

Unclassified

Order By: Relevance

“…On the other hand, the classic sustained and transient types of neural signal (Leventhal and Hirsch, 1978;Henry, Mustari and Bullier, 1983;Mullikin, Jones and Palmer, 1984) are categorically distinct but are not mathematically orthogonal. The appropriate method for dissociating such signals is Independent Components Analysis (ICA; HyvÌrinen and Oja, 1997;McKeown et al, 1998;Calhoun et al, 2001;HyvÌrinen et al, 2002;Formisano et al, 2004), which identifies parametric clusters of components regardless of their degree of correlation. Although it cannot identify multiple components within a single voxel, the present application of ICA relies on the variation in the weights of multiple components across a set of voxels, to identify the relative contribution of the components to each voxel.…”

Section: Boldðtþ ¼ Gðnðtþþ ð3þmentioning

confidence: 99%

Independent components in stimulus-related BOLD signals and estimation of the underlying neural responses

2008

View full text Add to dashboard Cite

This is the published version of the paper.This version of the publication may differ from the final published version. Permanent repository link A R T I C L E I N F O A B S T R A C TArticle history: IntroductionFunctional magnetic-resonance imaging (fMRI) based on the blood oxygenation-level dependent (BOLD) signal is a powerful technique for studying the neural response in the cortex. Most previous work has been based on the assumption that the BOLD signal is a unitary response to a single form of stimulus S(t), usually in the form of a linear convolution of a hemodynamic response function (HRF) with the temporal waveform of the stimulus time sequence (Bandettini et al., 1993;Friston et al., 1994;Boynton et al., 1996). In most cases, it is assumed that the HRF incorporates both the cortical response to the stimulus and the hemodynamic response of the blood to the oxygen requirements of the cortical response. However, the situation may be much more complicated, with multiple components of neural response to the stimulus weighted differentially across the cortex (Zacks et al., 2001;d'Avossa et al., 2003;Bellgowan et al., 2003;Calhoun et al., 2004a;Fox et al., 2005), such that any one voxel contains contributions from more than one neural time course. If these time course variations are small relative to the BOLD temporal resolution, they may be negligible for an overall analysis of response strength, but the cited studies show non-negligible variations that require a more detailed analysis. For this reason, consistent with Friston et al. (1998Friston et al. ( , 2000, Buxton et al. (2004) and others, we restrict the term HRF to the dynamics of the blood response to the metabolic demands of the neural processing and consider the neural response to the stimulus as a separate process. This leads to the model of the BOLD mechanisms shown in Fig. 1.

show abstract

Section: Boldðtþ ¼ Gðnðtþþ ð3þmentioning

confidence: 99%

Independent components in stimulus-related BOLD signals and estimation of the underlying neural responses

2008

View full text Add to dashboard Cite

show abstract

“…We have used the same number of components for ICA, FDA, SHICA, and SHFDA as PCA and SHPCA, respectively. Here ICA is calculated using the FastICA algorithm (Hyvärinen, 1999) and FDA based on an algorithm by Belhumeur et al (1997). We use the nearest neighbor classifier for recognition.…”

Section: Experimental Results For Recognitionmentioning

confidence: 99%

Intrinsic generalization analysis of low dimensional representations

2003

View full text Add to dashboard Cite

Low dimensional representations of images impose equivalence relations in the image space; the induced equivalence class of an image is named as its intrinsic generalization. The intrinsic generalization of a representation provides a novel way to measure its generalization and leads to more fundamental insights than the commonly used recognition performance, which is heavily influenced by the choice of training and test data. We demonstrate the limitations of linear subspace representations by sampling their intrinsic generalization, and propose a nonlinear representation that overcomes these limitations. The proposed representation projects images nonlinearly into the marginal densities of their filter responses, followed by linear projections of the marginals. We use experiments on large datasets to show that the representations that have better intrinsic generalization also lead to better recognition performance. q

show abstract

“…DMN functional connectivity: rs-fMRI images were realigned, normalized to Montreal Neurological Institute space, and smoothed with a 6-mm full-width at half maximum isotropic Gaussian kernel with SPM8, to perform independent component analysis (ICA) with the Group ICA toolbox (Calhoun et al, 2001) (GIFT v3.0a, http://mialab.mrn.org/software/gift/index. html) and the FastICA approach (Hyvärinen et al, 1997). The estimated number of independent components was 39, a dimension determined using the minimum description length criteria.…”

Section: Mri Image Acquisition and Processingmentioning

confidence: 99%

Association of postoperative delirium with markers of neurodegeneration and brain amyloidosis: a pilot study

Rolandi

Cavedo

Pievani

et al. 2018

Neurobiology of Aging

View full text Add to dashboard Cite

a b s t r a c tThe aim of the study was to investigate the association between postoperative delirium (POD) and in vivo markers of Alzheimer's disease pathology in nondemented hip fracture surgery patients. POD was assessed with the Confusion Assessment Method. Amyloid load was quantified on 18 F-Flutemetamol positron emission tomography images as standardized uptake value ratio. Secondary outcome measures were gray matter volumes, white matter integrity, and functional connectivity at rest. All the patients with POD (PODþ, N ¼ 5) were amyloid negative (standardized uptake value ratio <0.59), whereas 6 out of 11 patients without POD (PODÀ) showed brain amyloid positivity. PODþ compared to PODÀ displayed: lower gray matter volumes in the amygdala (p ¼ 0.003), in the middle temporal gyrus and in the anterior cingulate cortex (p < 0.001), increased diffusivity in the genu of the corpus callosum and in the anterior corona radiata (p < 0.05), and higher functional connectivity within the default mode network (p < 0.001). POD patients showed altered gray and white matter integrity in the fronto-limbic regions in absence of brain amyloidosis. Based on this preliminary investigation, delirium pathophysiology might be independent of Alzheimer's disease. Future studies on larger samples are needed to confirm this hypothesis.

show abstract

A Fast Fixed-Point Algorithm for Independent Component Analysis

Cited by 2,993 publications

References 6 publications

Independent components in stimulus-related BOLD signals and estimation of the underlying neural responses

Independent components in stimulus-related BOLD signals and estimation of the underlying neural responses

Intrinsic generalization analysis of low dimensional representations

Association of postoperative delirium with markers of neurodegeneration and brain amyloidosis: a pilot study

Contact Info

Product

Resources

About