Mapping and modeling age-related changes in intrinsic neural timescales
Abstract Intrinsic timescales of brain regions exhibit heterogeneity, escalating with hierarchical levels, and are crucial for the temporal integration of external stimuli. Aging, often associated with cognitive decline, involves progressive neuronal and synaptic loss, reshaping brain structure and...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
|
| Series: | Communications Biology |
| Online Access: | https://doi.org/10.1038/s42003-025-07517-x |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1823861748413759488 |
|---|---|
| author | Kaichao Wu Leonardo L. Gollo |
| author_facet | Kaichao Wu Leonardo L. Gollo |
| author_sort | Kaichao Wu |
| collection | DOAJ |
| description | Abstract Intrinsic timescales of brain regions exhibit heterogeneity, escalating with hierarchical levels, and are crucial for the temporal integration of external stimuli. Aging, often associated with cognitive decline, involves progressive neuronal and synaptic loss, reshaping brain structure and dynamics. However, the impact of these structural changes on temporal coding in the aging brain remains unclear. We mapped intrinsic timescales and gray matter volume (GMV) using magnetic resonance imaging (MRI) in young and elderly adults. We found shorter intrinsic timescales across multiple large-scale functional networks in the elderly cohort, and a significant positive association between intrinsic timescales and GMV. Additionally, age-related decline in performance on visual discrimination tasks was linked to a reduction in intrinsic timescales in the cuneus. To explain these age-related shifts, we developed an age-dependent spiking neuron network model. In younger subjects, brain regions were near a critical branching regime, while regions in elderly subjects had fewer neurons and synapses, pushing the dynamics toward a subcritical regime. The model accurately reproduced the empirical results, showing longer intrinsic timescales in young adults due to critical slowing down. Our findings reveal how age-related structural brain changes may drive alterations in brain dynamics, offering testable predictions and informing possible interventions targeting cognitive decline. |
| format | Article |
| id | doaj-art-a881303277d844a18d70da1c1ab6cf25 |
| institution | Kabale University |
| issn | 2399-3642 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Biology |
| spelling | doaj-art-a881303277d844a18d70da1c1ab6cf252025-02-09T12:50:28ZengNature PortfolioCommunications Biology2399-36422025-02-018111610.1038/s42003-025-07517-xMapping and modeling age-related changes in intrinsic neural timescalesKaichao Wu0Leonardo L. Gollo1Brain Networks and Modelling Laboratory and The Turner Institute for Brain and Mental Health, Monash UniversityBrain Networks and Modelling Laboratory and The Turner Institute for Brain and Mental Health, Monash UniversityAbstract Intrinsic timescales of brain regions exhibit heterogeneity, escalating with hierarchical levels, and are crucial for the temporal integration of external stimuli. Aging, often associated with cognitive decline, involves progressive neuronal and synaptic loss, reshaping brain structure and dynamics. However, the impact of these structural changes on temporal coding in the aging brain remains unclear. We mapped intrinsic timescales and gray matter volume (GMV) using magnetic resonance imaging (MRI) in young and elderly adults. We found shorter intrinsic timescales across multiple large-scale functional networks in the elderly cohort, and a significant positive association between intrinsic timescales and GMV. Additionally, age-related decline in performance on visual discrimination tasks was linked to a reduction in intrinsic timescales in the cuneus. To explain these age-related shifts, we developed an age-dependent spiking neuron network model. In younger subjects, brain regions were near a critical branching regime, while regions in elderly subjects had fewer neurons and synapses, pushing the dynamics toward a subcritical regime. The model accurately reproduced the empirical results, showing longer intrinsic timescales in young adults due to critical slowing down. Our findings reveal how age-related structural brain changes may drive alterations in brain dynamics, offering testable predictions and informing possible interventions targeting cognitive decline.https://doi.org/10.1038/s42003-025-07517-x |
| spellingShingle | Kaichao Wu Leonardo L. Gollo Mapping and modeling age-related changes in intrinsic neural timescales Communications Biology |
| title | Mapping and modeling age-related changes in intrinsic neural timescales |
| title_full | Mapping and modeling age-related changes in intrinsic neural timescales |
| title_fullStr | Mapping and modeling age-related changes in intrinsic neural timescales |
| title_full_unstemmed | Mapping and modeling age-related changes in intrinsic neural timescales |
| title_short | Mapping and modeling age-related changes in intrinsic neural timescales |
| title_sort | mapping and modeling age related changes in intrinsic neural timescales |
| url | https://doi.org/10.1038/s42003-025-07517-x |
| work_keys_str_mv | AT kaichaowu mappingandmodelingagerelatedchangesinintrinsicneuraltimescales AT leonardolgollo mappingandmodelingagerelatedchangesinintrinsicneuraltimescales |