Principal Component Regression Predicts Functional Responses across Individuals

Thirion, Bertrand; Varoquaux, Gaël; Grisel, Olivier; Poupon, Cyril; Pinel, Philippe

doi:10.1007/978-3-319-10470-6_92

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…The ARCHI tasks were developed at NeuroSpin in the framework of various neuroimaging projects. Hence, they have been extensively tested and validated by fMRI studies 25 , 26 , 34 , 35 . Data from each task were acquired in two runs, within the same session and using different phase-encoding directions (consult Section Imaging Data and Table 2 for details).…”

Section: Methodsmentioning

confidence: 99%

Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping

Pinho¹,

Amadon²,

Ruest³

et al. 2018

Sci Data

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129

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Functional Magnetic Resonance Imaging (fMRI) has furthered brain mapping on perceptual, motor, as well as higher-level cognitive functions. However, to date, no data collection has systematically addressed the functional mapping of cognitive mechanisms at a fine spatial scale. The Individual Brain Charting (IBC) project stands for a high-resolution multi-task fMRI dataset that intends to provide the objective basis toward a comprehensive functional atlas of the human brain. The data refer to a cohort of 12 participants performing many different tasks. The large amount of task-fMRI data on the same subjects yields a precise mapping of the underlying functions, free from both inter-subject and inter-site variability. The present article gives a detailed description of the first release of the IBC dataset. It comprises a dozen of tasks, addressing both low- and high- level cognitive functions. This openly available dataset is thus intended to become a reference for cognitive brain mapping.

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Section: Methodsmentioning

confidence: 99%

Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping

Pinho¹,

Amadon²,

Ruest³

et al. 2018

Sci Data

Self Cite

129

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“…After the removal of the global brain signal, the obtained hemodynamic responses were associated with the envelope modulation power using a searchlight approach (Kriegeskorte, 2006) and a machine learning algorithm based on principal component regression (Thirion, 2014). Specifically, for each stimulus category, a searchlight analysis was performed in the above-mentioned regions of interest to predict envelope features using principal components derived from brain activity (see Figure 2A).…”

Section: Reconstruction Of Envelope Features From Brain Activitymentioning

confidence: 99%

Auditory features modelling reveals sound envelope representation in striate cortex

Handjaras

Betta

Leo

et al. 2020

Preprint

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Primary visual cortex is no longer considered exclusively visual in its function. Proofs that its activity plays a role in multisensory processes have accrued. Here we provide evidence that, in absence of retinal input, V1 maps sound envelope information. We modeled amplitude changes occurring at typical speech envelope timescales of four hierarchically-organized categories of natural (or synthetically derived) sounds. Using functional magnetic resonance, we assessed whether sound amplitude variations were represented in striate cortex and, as a control, in the temporal cortex. Sound amplitude mapping in V1 occurred regardless of the semantic content, was dissociated from the spectral properties of sounds and was not restricted to speech material. As in the temporal cortex, a spatially organized representation of amplitude modulation frequencies emerged in V1. Our results demonstrate that human striate cortex is a locus of representation of sound attributes.

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Differences in Human Cortical Gene Expression Match the Temporal Properties of Large-Scale Functional Networks

et al. 2014

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We explore the relationships between the cortex functional organization and genetic expression (as provided by the Allen Human Brain Atlas). Previous work suggests that functional cortical networks (resting state and task based) are organized as two large networks (differentiated by their preferred information processing mode) shaped like two rings. The first ring–Visual-Sensorimotor-Auditory (VSA)–comprises visual, auditory, somatosensory, and motor cortices that process real time world interactions. The second ring–Parieto-Temporo-Frontal (PTF)–comprises parietal, temporal, and frontal regions with networks dedicated to cognitive functions, emotions, biological needs, and internally driven rhythms. We found–with correspondence analysis–that the patterns of expression of the 938 genes most differentially expressed across the cortex organized the cortex into two sets of regions that match the two rings. We confirmed this result using discriminant correspondence analysis by showing that the genetic profiles of cortical regions can reliably predict to what ring these regions belong. We found that several of the proteins–coded by genes that most differentiate the rings–were involved in neuronal information processing such as ionic channels and neurotransmitter release. The systematic study of families of genes revealed specific proteins within families preferentially expressed in each ring. The results showed strong congruence between the preferential expression of subsets of genes, temporal properties of the proteins they code, and the preferred processing modes of the rings. Ionic channels and release-related proteins more expressed in the VSA ring favor temporal precision of fast evoked neural transmission (Sodium channels SCNA1, SCNB1 potassium channel KCNA1, calcium channel CACNA2D2, Synaptotagmin SYT2, Complexin CPLX1, Synaptobrevin VAMP1). Conversely, genes expressed in the PTF ring favor slower, sustained, or rhythmic activation (Sodium channels SCNA3, SCNB3, SCN9A potassium channels KCNF1, KCNG1) and facilitate spontaneous transmitter release (calcium channel CACNA1H, Synaptotagmins SYT5, Complexin CPLX3, and synaptobrevin VAMP2).

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Principal Component Regression Predicts Functional Responses across Individuals

Cited by 3 publications

References 12 publications

Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping

Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping

Auditory features modelling reveals sound envelope representation in striate cortex

Differences in Human Cortical Gene Expression Match the Temporal Properties of Large-Scale Functional Networks

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