Brain connectomics : time for a molecular imaging perspective?
(2023) In Trends in Cognitive Sciences 27(4). p.353-366- Abstract
In the past two decades brain connectomics has evolved into a major concept in neuroscience. However, the current perspective on brain connectivity and how it underpins brain function relies mainly on the hemodynamic signal of functional magnetic resonance imaging (MRI). Molecular imaging provides unique information inaccessible to MRI-based and electrophysiological techniques. Thus, positron emission tomography (PET) has been successfully applied to measure neural activity, neurotransmission, and proteinopathies in normal and pathological cognition. Here, we position molecular imaging within the brain connectivity framework from the perspective of timeliness, validity, reproducibility, and resolution. We encourage the neuroscientific... (More)
In the past two decades brain connectomics has evolved into a major concept in neuroscience. However, the current perspective on brain connectivity and how it underpins brain function relies mainly on the hemodynamic signal of functional magnetic resonance imaging (MRI). Molecular imaging provides unique information inaccessible to MRI-based and electrophysiological techniques. Thus, positron emission tomography (PET) has been successfully applied to measure neural activity, neurotransmission, and proteinopathies in normal and pathological cognition. Here, we position molecular imaging within the brain connectivity framework from the perspective of timeliness, validity, reproducibility, and resolution. We encourage the neuroscientific community to take an integrative approach whereby MRI-based, electrophysiological techniques, and molecular imaging contribute to our understanding of the brain connectome.
(Less)
- author
- organization
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- connectivity, electroencephalography, magnetic resonance imaging, networks, PET, positron emission tomography
- in
- Trends in Cognitive Sciences
- volume
- 27
- issue
- 4
- pages
- 353 - 366
- publisher
- Elsevier
- external identifiers
-
- pmid:36621368
- scopus:85146133588
- ISSN
- 1364-6613
- DOI
- 10.1016/j.tics.2022.11.015
- language
- English
- LU publication?
- yes
- id
- 59f1fb91-0b23-466e-955f-ced088c7d614
- date added to LUP
- 2023-02-16 14:54:26
- date last changed
- 2024-09-30 20:34:22
@article{59f1fb91-0b23-466e-955f-ced088c7d614, abstract = {{<p>In the past two decades brain connectomics has evolved into a major concept in neuroscience. However, the current perspective on brain connectivity and how it underpins brain function relies mainly on the hemodynamic signal of functional magnetic resonance imaging (MRI). Molecular imaging provides unique information inaccessible to MRI-based and electrophysiological techniques. Thus, positron emission tomography (PET) has been successfully applied to measure neural activity, neurotransmission, and proteinopathies in normal and pathological cognition. Here, we position molecular imaging within the brain connectivity framework from the perspective of timeliness, validity, reproducibility, and resolution. We encourage the neuroscientific community to take an integrative approach whereby MRI-based, electrophysiological techniques, and molecular imaging contribute to our understanding of the brain connectome.</p>}}, author = {{Sala, Arianna and Lizarraga, Aldana and Caminiti, Silvia Paola and Calhoun, Vince D. and Eickhoff, Simon B. and Habeck, Christian and Jamadar, Sharna D. and Perani, Daniela and Pereira, Joana B. and Veronese, Mattia and Yakushev, Igor}}, issn = {{1364-6613}}, keywords = {{connectivity; electroencephalography; magnetic resonance imaging; networks; PET; positron emission tomography}}, language = {{eng}}, number = {{4}}, pages = {{353--366}}, publisher = {{Elsevier}}, series = {{Trends in Cognitive Sciences}}, title = {{Brain connectomics : time for a molecular imaging perspective?}}, url = {{http://dx.doi.org/10.1016/j.tics.2022.11.015}}, doi = {{10.1016/j.tics.2022.11.015}}, volume = {{27}}, year = {{2023}}, }