Ultra-high-order ICA: fine overlapping functional parcellations and spatiotemporal reconfiguration

AbstractOur recent findings show that functional organizations evolve spatially over time, highlighting the importance of considering within-subject spatial variations and dynamic functional parcellations in brain functional analyses. Meanwhile, a considerable level of multi-functionality suggests the need for overlapping brain parcellations. In this work, we used ultra-high-order ICA to identify fine overlapping functional dynamic parcellations of the brain. The preliminary result of this work was presented at the organization for human brain mapping workshop (OHBM 2019)1.

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Convergence of human brain mapping tools: Neuronavigated TMS Parameters and fMRI activity in the hand motor area

Human Brain Mapping ◽

10.1002/hbm.21272 ◽

2011 ◽

Vol 33 (5) ◽

pp. 1107-1123 ◽

Cited By ~ 34

Author(s):

Anna-Sophia Sarfeld ◽

Svenja Diekhoff ◽

Ling E. Wang ◽

Gianpiero Liuzzi ◽

Kamil Uludağ ◽

...

Keyword(s):

Human Brain ◽

Brain Mapping ◽

Motor Area ◽

Human Brain Mapping ◽

Hand Motor Area

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Adaptive Gaussian Markov random fields with applications in human brain mapping

Journal of the Royal Statistical Society Series C (Applied Statistics) ◽

10.1111/j.1467-9876.2007.00580.x ◽

2007 ◽

Vol 56 (3) ◽

pp. 327-345 ◽

Cited By ~ 21

Author(s):

A. Brezger ◽

L. Fahrmeir ◽

A. Hennerfeind

Keyword(s):

Human Brain ◽

Brain Mapping ◽

Random Fields ◽

Markov Random Fields ◽

Human Brain Mapping ◽

Gaussian Markov Random Fields ◽

Markov Random

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Astronomia nova to human brain mapping

Neural Networks ◽

10.1016/j.neunet.2006.09.007 ◽

2006 ◽

Vol 19 (9) ◽

pp. 1453-1454

Author(s):

Rik Vandenberghe

Keyword(s):

Human Brain ◽

Brain Mapping ◽

Human Brain Mapping

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Genome aging: somatic mutation in the brain links age-related decline with disease and nominates pathogenic mechanisms

Human Molecular Genetics ◽

10.1093/hmg/ddz191 ◽

2019 ◽

Vol 28 (R2) ◽

pp. R197-R206 ◽

Cited By ~ 10

Author(s):

Michael A Lodato ◽

Christopher A Walsh

Keyword(s):

Human Brain ◽

Somatic Mutation ◽

Somatic Mutations ◽

Late Onset ◽

Whole Genome ◽

Single Nucleotide Variants ◽

Single Nucleotide ◽

Age Related ◽

The Brain ◽

Over Time

AbstractAging is a mysterious process, not only controlled genetically but also subject to random damage that can accumulate over time. While DNA damage and subsequent mutation in somatic cells were first proposed as drivers of aging more than 60 years ago, whether and to what degree these processes shape the neuronal genome in the human brain could not be tested until recent technological breakthroughs related to single-cell whole-genome sequencing. Indeed, somatic single-nucleotide variants (SNVs) increase with age in the human brain, in a somewhat stochastic process that may nonetheless be controlled by underlying genetic programs. Evidence from the literature suggests that in addition to demonstrated increases in somatic SNVs during aging in normal brains, somatic mutation may also play a role in late-onset, sporadic neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s disease. In this review, we will discuss somatic mutation in the human brain, mechanisms by which somatic mutations occur and can be controlled, and how this process can impact human health.

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Plastic Maps: The New Brain Cartographies of the 21th-Century Neurosciences

Nuncius ◽

10.1163/18253911-03202008 ◽

2017 ◽

Vol 32 (2) ◽

pp. 472-500

Author(s):

Carmela Morabito

Keyword(s):

Brain Mapping ◽

Brain Regions ◽

Individual Experience ◽

Clinical Use ◽

Functional Architecture ◽

Early 19Th Century ◽

New Models ◽

Local Properties ◽

The Brain ◽

Over Time

Ever since the phrenological heads of the early 19th century, maps have translated into images our ideas, theories and models of the brain, making this organ at one and the same time scientific object and representation. Brain maps have always served as gateways for navigating and visualizing neuroscientific knowledge, and over time many different maps have been produced – firstly as tools to “read” and analyse the cerebral territory, then as instruments to produce new models of the brain. Over the last 150 years brain cartography has evolved from a way of identifying brain regions and localizing them for clinical use to an anatomical framework onto which information about local properties and functions can be integrated to provide a view of the brain’s structural and functional architecture. In this paper a historical and epistemological consideration of the topic is offered as a contribution to the understanding of contemporary brain mapping, based on the assumption that the brain continuously rewires itself in relation to individual experience.

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Z-Score EEG Biofeedback: Past, Present, and Future

Biofeedback ◽

10.5298/1081-5937-47.4.04 ◽

2019 ◽

Vol 47 (4) ◽

pp. 89-103

Author(s):

Robert W. Thatcher ◽

Joel F. Lubar ◽

J. Lucas Koberda

Keyword(s):

Human Brain ◽

Real Time ◽

Brain Mapping ◽

Three Dimensional ◽

Brain Network ◽

Eeg Biofeedback ◽

Reference Database ◽

Symptom Checklist ◽

Z Score ◽

Human Brain Mapping

Human electroencephalogram (EEG) biofeedback (neurofeedback) started in the 1940s using one EEG recording channel, then four channels in the 1990s, and in 2004, expanded to 19 channels using Low Resolution Electromagnetic Tomography (LORETA) of the microampere three-dimensional current sources of the EEG. In 2004–2006 the concept of a real-time comparison of the EEG to a healthy reference database was developed and tested using surface EEG z score neurofeedback based on a statistical bell curve called real-time z scores. The real-time or live normative reference database comparison was developed to help reduce the uncertainty of what threshold to select to activate a feedback signal and to unify all EEG measures to a single value (i.e., the distance from the mean of an age-matched reference sample). In 2009 LORETA z score neurofeedback further increased specificity by targeting brain network hubs referred to as Brodmann areas. A symptom checklist program to help link symptoms to dysregulation of brain networks based on fMRI and positron emission tomography (PET) and neurology was created in 2009. The symptom checklist and National Institutes of Health–based networks linking symptoms to brain networks grew out of the human brain mapping program started in 1990 that continues today. A goal is to increase specificity of EEG biofeedback by targeting brain network hubs and connections between hubs likely linked to the patient's symptoms. Developments first introduced in 2017 provide increased resolution of three-dimensional source localization with 12,700 voxels using swLORETA with the capacity to conduct cerebellar neurofeedback and neurofeedback of subcortical brain hubs such as the thalamus, amygdala, and habenula. Future applications of swLORETA z score neurofeedback represent another example of the transfer of knowledge gained by the human brain mapping initiatives to further aid in helping people with cognition problems as well as balance problems and parkinsonism. A brief review of the past, present, and future predictions of z score neurofeedback are discussed with special emphasis on new developments that point toward a bright and enlightened future in the field of EEG biofeedback.

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