Back

Lifetime physical activity and network attack tolerance contribute to the preservation of motor function in Parkinson's disease

Asendorf, A. L.; Guerra, E.; Dzialas, V.; Bankwinkler, M.; Theis, H.; Hagemann, N.; Moellenhoff, K.; van Eimeren, T.; Hoenig, M.

2025-03-17 neuroscience
10.1101/2025.03.14.643226 bioRxiv
Show abstract

We tested whether network resilience, quantified by network attack tolerance (NAT), is associated with dopamine terminal (DaT) integrity, motor function and lifetime factors in Parkinsons disease (PD). Data from 22 PD patients and 39 healthy controls included information on lifetime physical activity (PA), cognitive/motor performance, putaminal DaT integrity, and resting-state fMRI. NAT was assessed at global and subnetwork level by calculating global efficiency upon iterative node removal. Generalized linear-mixed-effects models were used to test the effects of PA, education, and dopamine integrity on NAT. Next, the moderating effect of lifetime factors on the association between NAT and motor function were assessed, controlling for DaT integrity. Greater putaminal DaT integrity was linked to higher somatomotor NAT. Higher global and somatomotor NAT supported motor function, especially in patients with moderate lifetime PA. Lifestyle factors may thus serve network-specific attack tolerance, thereby promoting motor preservation in PD, independent of dopaminergic impairment.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Scientific Reports
○ 3612 papers in training set
Top 3%
11.9%
Similar papers in this journal
2
Brain Communications
◐ 166 papers in training set
Top 0.2%
11.0%
Similar papers in this journal
3
npj Parkinson's Disease
○ 105 papers in training set
Top 0.3%
9.8%
Similar papers in this journal
4
Movement Disorders
○ 71 papers in training set
Top 0.2%
6.3%
Similar papers in this journal
5
Human Brain Mapping
○ 329 papers in training set
Top 1%
4.9%
Similar papers in this journal
6
NeuroImage: Clinical
○ 144 papers in training set
Top 0.6%
4.9%
7
Brain
◐ 168 papers in training set
Top 0.9%
4.0%
50% of probability mass above
8
Neurobiology of Disease
○ 148 papers in training set
Top 1%
3.2%
9
NeuroImage
○ 903 papers in training set
Top 4%
2.4%
10
Parkinsonism & Related Disorders
○ 25 papers in training set
Top 0.2%
1.9%
11
Translational Psychiatry
○ 260 papers in training set
Top 2%
1.9%
12
Communications Biology
○ 993 papers in training set
Top 14%
1.7%
13
Brain and Behavior
○ 43 papers in training set
Top 0.5%
1.7%
14
Network Neuroscience
● 126 papers in training set
Top 0.9%
1.7%
15
Frontiers in Human Neuroscience
○ 77 papers in training set
Top 0.9%
1.7%
16
Experimental Neurology
○ 61 papers in training set
Top 0.8%
1.5%
17
Progress in Neurobiology
○ 47 papers in training set
Top 0.3%
1.5%
18
Molecular Psychiatry
○ 282 papers in training set
Top 4%
1.5%
19
Frontiers in Aging Neuroscience
○ 74 papers in training set
Top 1.0%
1.4%
20
PLOS ONE
● 5266 papers in training set
Top 50%
1.3%
21
Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
○ 71 papers in training set
Top 1%
1.1%
22
Nature Communications
○ 5641 papers in training set
Top 50%
1.1%
23
European Journal of Neuroscience
○ 189 papers in training set
Top 3%
1.1%
24
eLife
● 5828 papers in training set
Top 59%
1.1%
25
Journal of Neurology
○ 28 papers in training set
Top 0.7%
1.1%
26
Annals of Neurology
○ 64 papers in training set
Top 1%
0.9%
27
Neurobiology of Aging
○ 107 papers in training set
Top 1%
0.9%
28
Frontiers in Neuroscience
○ 256 papers in training set
Top 6%
0.8%
29
eBioMedicine
○ 183 papers in training set
Top 8%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.