Radiology: functional MRI imaging of healthy adults at rest

Previous resting functional magnetic resonance (rsfMRI) studies have consistently shown that healthy young and old individuals can display different patterns of intrinsic functional connectivity, and this difference may mediate the negative effects
of aging on cognitive function.
Primary sensory networks (PSNs) play a key role in primary information processing, while networks such as attention networks (ANs), frontal networks (FPNs), default mode networks (DMNs), and edge networks play key
roles in higher-order cognitive control functions.
The intrinsic network changes associated with aging show patterns consistent with network development, which is known as the "last-in-first-out" theory
.
The theory holds that brain development shifts from PSN to higher-order cognitive control networks, but healthy aging begins with higher-order cognitive networks and maintains relatively intact primary functions
.
The "last-in-first-out" theory states that PSN and higher-order cognitive networks show different changes
with age.

In addition to isolation, the inner network is also extremely integrated in specific cognitive control tasks
.
A representative integration is the negative correlation between DMN and AN
.
To perform better on goal-directed tasks, the brain may integrate DMN and AN to complete the competitive process
between external goal-directed attention and internal mental processes.
A study on aging showed that DMN-AN had a smaller negative correlation, which may induce impairment
of working memory.

In addition, FPN, as a key switching node in cognitive control, is able to regulate the interaction between DMN and AN, which is age-sensitive
.
This raises the question of how the network interactions between DMN, AN, and FPN can change
temporally over the course of an adult's lifetime.

A study published in the journal Radiology promotes clinical interpretation of dynamic brain network changes
in complex aging processes by quantifying activation levels and obtaining clear definitions of CAPs with rsfMRI.

RSFMRI data from healthy participants in the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) database retrieved in this retrospective study (October 2010-September 2013) were used to generate CAP
by applying single-volume temporal clustering 。 Spatial clustering is then performed to capture dynamic coactivation and deactivation
within or between primary sensory networks and higher-order cognitive networks, including the default mode network [DMN], attention network [AN], and frontal network [FPN].
The linear relationship between dynamic metrics and age is shown
by Spearman partial correlation.

A total of 614 participants (mean age, 54 years± 18 [SD]; 311 women) were included in the assessment, ranging in age from 18 to 88 years
.
CAPs (Spearman correlation: r = -0.
98, P < .
001) were negatively correlated
with coactivation in aging (partial correlation: r = -0.
17, P < .
001) and deactivation (partial correlation: r = 0.
216, P < .
001).
。 CAPs, characterized by a negative correlation pattern between DMN and AN, occur with age (partial correlation: r = 0.
14, P = .
003) and stay (partial correlation: r = 0.
10, P = .
04) more
.
In addition, AN and DMN CAP transition more to AN and FPN CAP (partially related: r = 0.
17, P <.
001)
with age.

Figure Community Function Co-Activation Modes (CAPs).

(A) Z-scores
for six CAPs.
Each row displays a pair of CAPs with Spear-man associated r values
in the middle.
A = attention network, D = default mode network, F = frontoparietal network, P = primary sensory network
.
The symbol "+" indicates co-activation and the symbol "-" indicates inactivation
.
(B) Five network templates for 1024 regions of interest are derived from previous literature reports

The rest-state based functional magnetic resonance data presented in this study can be used to describe large-scale network changes associated with aging using co-activation mode (CAP) analysis, which can provide high temporal resolution
close to the volume of single-function magnetic resonance.
The results of this study suggest that adults spend less time on primary sensory networks and frontal network CAP with age, further leading to a compensatory increase
in the CAP of default mode networks and attention networks.
These findings provide new insights into framed aging-related network patterns and identify treatment target patterns
that can serve as markers of brain diseases and personalized neuromodulation.

Original source:

Tiantian Liu,Li Wang,Dingjie Suo,et al.
Resting-State Functional MRI of Healthy Adults: Temporal Dynamic Brain Coactivation Patterns.
DOI:10.
1148/radiol.
211762