1. |
|
|
2. |
- Vereb, D., et al.
(författare)
-
Age-related differences in the functional topography of the locus coeruleus and their implications for cognitive and affective functions
- 2023
-
Ingår i: eLife. - 2050-084X. ; 12
-
Tidskriftsartikel (refereegranskat)abstract
- The locus coeruleus (LC) is an important noradrenergic nucleus that has recently attracted a lot of attention because of its emerging role in cognitive and psychiatric disorders. Although previous histological studies have shown that the LC has heterogeneous connections and cellular features, no studies have yet assessed its functional topography in vivo, how this heterogeneity changes over aging, and whether it is associated with cognition and mood. Here, we employ a gradient-based approach to characterize the functional heterogeneity in the organization of the LC over aging using 3T resting-state fMRI in a population-based cohort aged from 18 to 88 years of age (Cambridge Centre for Ageing and Neuroscience cohort, n=618). We show that the LC exhibits a rostro-caudal functional gradient along its longitudinal axis, which was replicated in an independent dataset (Human Connectome Project [HCP] 7T dataset, n=184). Although the main rostro-caudal direction of this gradient was consistent across age groups, its spatial features varied with increasing age, emotional memory, and emotion regulation. More specifically, a loss of rostral-like connectivity, more clustered functional topography, and greater asymmetry between right and left LC gradients was associated with higher age and worse behavioral performance. Furthermore, participants with higher-than-normal Hospital Anxiety and Depression Scale (HADS) ratings exhibited alterations in the gradient as well, which manifested in greater asymmetry. These results provide an in vivo account of how the functional topography of the LC changes over aging, and imply that spatial features of this organization are relevant markers of LC-related behavioral measures and psychopathology.
|
|
3. |
|
|
4. |
- Hinault, T., et al.
(författare)
-
Age-related differences in network structure and dynamic synchrony of cognitive control
- 2021
-
Ingår i: NeuroImage. - : Elsevier BV. - 1095-9572 .- 1053-8119. ; 236
-
Tidskriftsartikel (refereegranskat)abstract
- Cognitive trajectories vary greatly across older individuals, and the neural mechanisms underlying these differences remain poorly understood. Here, we investigate the cognitive variability in older adults by linking the influence of white matter microstructure on the task-related organization of fast and effective communications between brain regions. Using diffusion tensor imaging and electroencephalography, we show that individual differences in white matter network organization are associated with network clustering and efficiency in the alpha and high-gamma bands, and that functional network dynamics partly explain individual differences in cognitive control performance in older adults. We show that older individuals with high versus low structural network clustering differ in task-related network dynamics and cognitive performance. These findings were corroborated by investigating magnetoencephalography networks in an independent dataset. This multimodal (fMRI and biological markers) brain connectivity framework of individual differences provides a holistic account of how differences in white matter microstructure underlie age-related variability in dynamic network organization and cognitive performance. Copyright © 2021. Published by Elsevier Inc.
|
|
5. |
|
|
6. |
|
|
7. |
- Veréb, D, et al.
(författare)
-
Age-related differences in the functional topography of the locus coeruleus: implications for cognitive and affective functions
- 2023
-
Ingår i: medRxiv : the preprint server for health sciences. - : Cold Spring Harbor Laboratory.
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- The locus coeruleus (LC) is an important noradrenergic nucleus that has recently attracted a lot of attention because of its emerging role in cognitive and psychiatric disorders. Although previous histological studies have shown that the LC has heterogeneous connections and cellular features, no studies have yet assessed its functional topography in vivo, how this heterogeneity changes over aging and whether it is associated with cognition and mood. Here we employ a gradient-based approach to characterize the functional heterogeneity in the organization of the LC over aging using 3T resting-state fMRI in a population-based cohort aged from 18 to 88 years old (Cambridge Centre for Ageing and Neuroscience cohort, n=618). We show that the LC exhibits a rostro-caudal functional gradient along its longitudinal axis, which was replicated in an independent dataset (Human Connectome Project 7T dataset, n=184). Although the main rostro-caudal direction of this gradient was consistent across age groups, its spatial features varied with increasing age, emotional memory and emotion regulation. More specifically, a loss of rostral-like connectivity, more clustered functional topography and greater asymmetry between right and left LC gradients was associated with higher age and worse behavioral performance. Furthermore, participants with higher-than-normal Hospital Anxiety and Depression Scale ratings exhibited alterations in the gradient as well, which manifested in greater asymmetry. These results provide an in vivo account of how the functional topography of the LC changes over aging, and imply that spatial features of this organization are relevant markers of LC-related behavioral measures and psychopathology.
|
|
8. |
- Canal-Garcia, A., et al.
(författare)
-
Multiplex Connectome Changes across the Alzheimer's Disease Spectrum Using Gray Matter and Amyloid Data
- 2022
-
Ingår i: Cerebral Cortex. - : Oxford University Press (OUP). - 1047-3211 .- 1460-2199. ; 32:16, s. 3501-3515
-
Tidskriftsartikel (refereegranskat)abstract
- The organization of the Alzheimer's disease (AD) connectome has been studied using graph theory using single neuroimaging modalities such as positron emission tomography (PET) or structural magnetic resonance imaging (MRI). Although these modalities measure distinct pathological processes that occur in different stages in AD, there is evidence that they are not independent from each other. Therefore, to capture their interaction, in this study we integrated amyloid PET and gray matter MRI data into a multiplex connectome and assessed the changes across different AD stages. We included 135 cognitively normal (CN) individuals without amyloid-beta pathology (A beta-) in addition to 67 CN, 179 patients with mild cognitive impairment (MCI) and 132 patients with AD dementia who all had A beta pathology (A beta+) from the Alzheimer's Disease Neuroimaging Initiative. We found widespread changes in the overlapping connectivity strength and the overlapping connections across A beta-positive groups. Moreover, there was a reorganization of the multiplex communities in MCI A beta + patients and changes in multiplex brain hubs in both MCI A beta + and AD A beta + groups. These findings offer a new insight into the interplay between amyloid-beta pathology and brain atrophy over the course of AD that moves beyond traditional graph theory analyses based on single brain networks.
|
|
9. |
- Lizano, Paulo, et al.
(författare)
-
Peripheral inflammatory subgroup differences in anterior Default Mode network and multiplex functional network topology are associated with cognition in psychosis
- 2023
-
Ingår i: BRAIN BEHAVIOR AND IMMUNITY. - 0889-1591 .- 1090-2139. ; 114, s. 3-15
-
Tidskriftsartikel (refereegranskat)abstract
- Introduction: High-inflammation subgroups of patients with psychosis demonstrate cognitive deficits and neuroanatomical alterations. Systemic inflammation assessed using IL-6 and C-reactive protein may alter func-tional connectivity within and between resting-state networks, but the cognitive and clinical implications of these alterations remain unknown. We aim to determine the relationships of elevated peripheral inflammation subgroups with resting-state functional networks and cognition in psychosis spectrum disorders. Methods: Serum and resting-state fMRI were collected from psychosis probands (schizophrenia, schizoaffective, psychotic bipolar disorder) and healthy controls (HC) from the B-SNIP1 (Chicago site) study who were stratified into inflammatory subgroups based on factor and cluster analyses of 13 cytokines (HC Low n = 32, Proband Low n = 65, Proband High n = 29). Nine resting-state networks derived from independent component analysis were used to assess functional and multilayer connectivity. Inter-network connectivity was measured using Fisher z -transformation of correlation coefficients. Network organization was assessed by investigating networks of positive and negative connections separately, as well as investigating multilayer networks using both positive and negative connections. Cognition was assessed using the Brief Assessment of Cognition in Schizophrenia. Linear regressions, Spearman correlations, permutations tests and multiple comparison corrections were used for analyses in R. Results: Anterior default mode network (DMNa) connectivity was significantly reduced in the Proband High compared to Proband Low (Cohen's d =-0.74, p = 0.002) and HC Low (d =-0.85, p = 0.0008) groups. Internetwork connectivity between the DMNa and the right-frontoparietal networks was lower in Proband High compared to Proband Low (d =-0.66, p = 0.004) group. Compared to Proband Low, the Proband High group had lower negative (d = 0.54, p = 0.021) and positive network (d = 0.49, p = 0.042) clustering coefficient, and lower multiplex network participation coefficient (d =-0.57, p = 0.014). Network findings in high inflammation subgroups correlate with worse verbal fluency, verbal memory, symbol coding, and overall cognition. Conclusion: These results expand on our understanding of the potential effects of peripheral inflammatory signatures and/or subgroups on network dysfunction in psychosis and how they relate to worse cognitive performance. Additionally, the novel multiplex approach taken in this study demonstrated how inflammation may disrupt the brain's ability to maintain healthy co-activation patterns between the resting-state networks while inhibiting certain connections between them.
|
|
10. |
- Mijalkov, M., et al.
(författare)
-
BRAPH: A graph theory software for the analysis of brain connectivity
- 2017
-
Ingår i: Plos One. - : Public Library of Science (PLoS). - 1932-6203. ; 12:8
-
Tidskriftsartikel (refereegranskat)abstract
- The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH-BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer's disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson's patients with mild cognitive impairment.
|
|