Displaying the autonomic processing network in humans – a global tractography approach
Abstract: Regulation of the internal homeostasis is modulated by the central autonomic system. So far, the view of this system is determined by animal and human research focusing on cortical and subcortical grey substance regions. To provide an overview based on white matter architecture, we used a global tractography approach to reconstruct a network of tracts interconnecting brain regions that are known to be involved in autonomic processing. Diffusion weighted imaging data were obtained from subjects of the human connectome project (HCP) database. Resulting tracts are in good agreement with previous studies assuming a division of the central autonomic system into a cortical (CAN) and a subcortical network (SAN): the CAN consist of three subsystems that encompass all cerebral lobes and overlap within the insular cortex: a parieto-anterior-temporal pathway (PATP), an occipito-posterior-temporo-frontal pathway (OPTFP) and a limbic pathway. The SAN on the other hand connects the hypothalamus to the periaqueductal grey and locus coeruleus, before it branches into a dorsal and a lateral part that target autonomic nuclei in the rostral medulla oblongata. Our approach furthermore reveals how the CAN and SAN are interconnected: the hypothalamus can be considered as the interface-structure of the SAN, whereas the insula is the central hub of the CAN. The hypothalamus receives input from prefrontal cortical fields but is also connected to the ventral apex of the insular cortex. Thus, a holistic view of the central autonomic system could be created that may promote the understanding of autonomic signaling under physiological and pathophysiological conditions
- Sprache
-
Englisch
- Umfang
-
Online-Ressource
- Anmerkungen
-
NeuroImage. - 231 (2021) , 117852, ISSN: 1095-9572
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Ereignis
-
Veröffentlichung
- (wo)
-
Freiburg
- (wer)
-
Universität
- (wann)
-
2021
- DOI
-
10.1016/j.neuroimage.2021.117852
- URN
-
urn:nbn:de:bsz:25-freidok-1942044
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
12.03.2025, 23:07 MEZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Reisert, Marco
- Weiller, Cornelius
- Hosp, Jonas Aurel
- Universität
Entstanden
- 2021
Ähnliche Objekte (12)
Group integration techniques in pattern analysis : a kernel view
Approximation to pain‐signaling network in humans by means of migraine
Disentangling micro from mesostructure by diffusion MRI: a Bayesian approach
“The heart asks pleasure first” - conceptualizing psychiatric diseases as MAINTENANCE network dysfunctions through insights from slMFB DBS in depression and obsessive–compulsive disorder
There’s more to the picture than meets the eye : : Reply to: Letter to the editor of Acta Neurochirurgica: Blind men and the elephant - comment on “The dentato-rubro-thalamic tract as the potential common deep brain stimulation target for tremor of various origin: an observational case series”
What does FEXI measure?
The dual-loop model for combining external and internal worlds in our brain
A deep learning approach for projection and body-side classification in musculoskeletal radiographs
Accuracy of automated segmentation and volumetry of acute intracerebral hemorrhage following minimally invasive surgery using a patch-based convolutional neural network in a small dataset
Multiclass datasets expand neural network utility: an example on ankle radiographs
Autonomic function after myocardial infarction : an epidemiological approach
Effect of surface-partial-volume correction and adaptive threshold on segmentation of uroliths in computed tomography
Group integration techniques in pattern analysis : a kernel view
Approximation to pain‐signaling network in humans by means of migraine
Disentangling micro from mesostructure by diffusion MRI: a Bayesian approach
“The heart asks pleasure first” - conceptualizing psychiatric diseases as MAINTENANCE network dysfunctions through insights from slMFB DBS in depression and obsessive–compulsive disorder
There’s more to the picture than meets the eye : : Reply to: Letter to the editor of Acta Neurochirurgica: Blind men and the elephant - comment on “The dentato-rubro-thalamic tract as the potential common deep brain stimulation target for tremor of various origin: an observational case series”
What does FEXI measure?
The dual-loop model for combining external and internal worlds in our brain
A deep learning approach for projection and body-side classification in musculoskeletal radiographs
Accuracy of automated segmentation and volumetry of acute intracerebral hemorrhage following minimally invasive surgery using a patch-based convolutional neural network in a small dataset
Multiclass datasets expand neural network utility: an example on ankle radiographs
Autonomic function after myocardial infarction : an epidemiological approach
Effect of surface-partial-volume correction and adaptive threshold on segmentation of uroliths in computed tomography
Group integration techniques in pattern analysis : a kernel view
Approximation to pain‐signaling network in humans by means of migraine
Disentangling micro from mesostructure by diffusion MRI: a Bayesian approach
“The heart asks pleasure first” - conceptualizing psychiatric diseases as MAINTENANCE network dysfunctions through insights from slMFB DBS in depression and obsessive–compulsive disorder
There’s more to the picture than meets the eye : : Reply to: Letter to the editor of Acta Neurochirurgica: Blind men and the elephant - comment on “The dentato-rubro-thalamic tract as the potential common deep brain stimulation target for tremor of various origin: an observational case series”
What does FEXI measure?
The dual-loop model for combining external and internal worlds in our brain
A deep learning approach for projection and body-side classification in musculoskeletal radiographs
Accuracy of automated segmentation and volumetry of acute intracerebral hemorrhage following minimally invasive surgery using a patch-based convolutional neural network in a small dataset
Multiclass datasets expand neural network utility: an example on ankle radiographs
Autonomic function after myocardial infarction : an epidemiological approach