Investigating the Impact of Local Manipulations on Spontaneous and Evoked Brain Complexity Indices: A Large-Scale Computational Model
Brain complexity relies on the integrity of structural and functional brain networks, where specialized areas synergistically cooperate on a large scale. Local alterations within these areas can lead to widespread consequences, leading to a reduction in overall network complexity. Investigating the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/14/2/890 |
| _version_ | 1797340060640608256 |
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| author | Gianluca Gaglioti Thierry Ralph Nieus Marcello Massimini Simone Sarasso |
| author_facet | Gianluca Gaglioti Thierry Ralph Nieus Marcello Massimini Simone Sarasso |
| author_sort | Gianluca Gaglioti |
| collection | DOAJ |
| description | Brain complexity relies on the integrity of structural and functional brain networks, where specialized areas synergistically cooperate on a large scale. Local alterations within these areas can lead to widespread consequences, leading to a reduction in overall network complexity. Investigating the mechanisms governing this occurrence and exploring potential compensatory interventions is a pressing research focus. In this study, we employed a whole-brain in silico model to simulate the large-scale impact of local node alterations. These were assessed by network complexity metrics derived from both the model’s spontaneous activity (i.e., Lempel–Ziv complexity (LZc)) and its responses to simulated local perturbations (i.e., the Perturbational Complexity Index (PCI)). Compared to LZc, local node silencing of distinct brain regions induced large-scale alterations that were paralleled by a systematic drop of PCI. Specifically, while the intact model engaged in complex interactions closely resembling those obtained in empirical studies, it displayed reduced PCI values across all local manipulations. This approach also revealed the heterogeneous impact of different local manipulations on network alterations, emphasizing the importance of posterior hubs in sustaining brain complexity. This work marks an initial stride toward a comprehensive exploration of the mechanisms underlying the loss and recovery of brain complexity across different conditions. |
| first_indexed | 2024-03-08T09:57:29Z |
| format | Article |
| id | doaj.art-180ac70c9a1245ae9b734bd4e6678eda |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-08T09:57:29Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-180ac70c9a1245ae9b734bd4e6678eda2024-01-29T13:45:39ZengMDPI AGApplied Sciences2076-34172024-01-0114289010.3390/app14020890Investigating the Impact of Local Manipulations on Spontaneous and Evoked Brain Complexity Indices: A Large-Scale Computational ModelGianluca Gaglioti0Thierry Ralph Nieus1Marcello Massimini2Simone Sarasso3Department of Biomedical and Clinical Sciences, University of Milan, 20157 Milan, ItalyCore Facility Indaco, University of Milan, 20122 Milan, ItalyDepartment of Biomedical and Clinical Sciences, University of Milan, 20157 Milan, ItalyDepartment of Biomedical and Clinical Sciences, University of Milan, 20157 Milan, ItalyBrain complexity relies on the integrity of structural and functional brain networks, where specialized areas synergistically cooperate on a large scale. Local alterations within these areas can lead to widespread consequences, leading to a reduction in overall network complexity. Investigating the mechanisms governing this occurrence and exploring potential compensatory interventions is a pressing research focus. In this study, we employed a whole-brain in silico model to simulate the large-scale impact of local node alterations. These were assessed by network complexity metrics derived from both the model’s spontaneous activity (i.e., Lempel–Ziv complexity (LZc)) and its responses to simulated local perturbations (i.e., the Perturbational Complexity Index (PCI)). Compared to LZc, local node silencing of distinct brain regions induced large-scale alterations that were paralleled by a systematic drop of PCI. Specifically, while the intact model engaged in complex interactions closely resembling those obtained in empirical studies, it displayed reduced PCI values across all local manipulations. This approach also revealed the heterogeneous impact of different local manipulations on network alterations, emphasizing the importance of posterior hubs in sustaining brain complexity. This work marks an initial stride toward a comprehensive exploration of the mechanisms underlying the loss and recovery of brain complexity across different conditions.https://www.mdpi.com/2076-3417/14/2/890brain complexitywhole-brain modelingnode silencingperturbationsLempel–Ziv complexityPerturbational Complexity Index |
| spellingShingle | Gianluca Gaglioti Thierry Ralph Nieus Marcello Massimini Simone Sarasso Investigating the Impact of Local Manipulations on Spontaneous and Evoked Brain Complexity Indices: A Large-Scale Computational Model Applied Sciences brain complexity whole-brain modeling node silencing perturbations Lempel–Ziv complexity Perturbational Complexity Index |
| title | Investigating the Impact of Local Manipulations on Spontaneous and Evoked Brain Complexity Indices: A Large-Scale Computational Model |
| title_full | Investigating the Impact of Local Manipulations on Spontaneous and Evoked Brain Complexity Indices: A Large-Scale Computational Model |
| title_fullStr | Investigating the Impact of Local Manipulations on Spontaneous and Evoked Brain Complexity Indices: A Large-Scale Computational Model |
| title_full_unstemmed | Investigating the Impact of Local Manipulations on Spontaneous and Evoked Brain Complexity Indices: A Large-Scale Computational Model |
| title_short | Investigating the Impact of Local Manipulations on Spontaneous and Evoked Brain Complexity Indices: A Large-Scale Computational Model |
| title_sort | investigating the impact of local manipulations on spontaneous and evoked brain complexity indices a large scale computational model |
| topic | brain complexity whole-brain modeling node silencing perturbations Lempel–Ziv complexity Perturbational Complexity Index |
| url | https://www.mdpi.com/2076-3417/14/2/890 |
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