Spontaneous Activity Predicts Survival of Developing Cortical Neurons
Spontaneous activity plays a crucial role in brain development by coordinating the integration of immature neurons into emerging cortical networks. High levels and complex patterns of spontaneous activity are generally associated with low rates of apoptosis in the cortex. However, whether spontaneou...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-08-01
|
| Series: | Frontiers in Cell and Developmental Biology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fcell.2022.937761/full |
| _version_ | 1811308872621621248 |
|---|---|
| author | Davide Warm Davide Bassetti Jonas Schroer Heiko J. Luhmann Anne Sinning |
| author_facet | Davide Warm Davide Bassetti Jonas Schroer Heiko J. Luhmann Anne Sinning |
| author_sort | Davide Warm |
| collection | DOAJ |
| description | Spontaneous activity plays a crucial role in brain development by coordinating the integration of immature neurons into emerging cortical networks. High levels and complex patterns of spontaneous activity are generally associated with low rates of apoptosis in the cortex. However, whether spontaneous activity patterns directly encode for survival of individual cortical neurons during development remains an open question. Here, we longitudinally investigated spontaneous activity and apoptosis in developing cortical cultures, combining extracellular electrophysiology with calcium imaging. These experiments demonstrated that the early occurrence of calcium transients was strongly linked to neuronal survival. Silent neurons exhibited a higher probability of cell death, whereas high frequency spiking and burst behavior were almost exclusively detected in surviving neurons. In local neuronal clusters, activity of neighboring neurons exerted a pro-survival effect, whereas on the functional level, networks with a high modular topology were associated with lower cell death rates. Using machine learning algorithms, cell fate of individual neurons was predictable through the integration of spontaneous activity features. Our results indicate that high frequency spiking activity constrains apoptosis in single neurons through sustained calcium rises and thereby consolidates networks in which a high modular topology is reached during early development. |
| first_indexed | 2024-04-13T09:32:06Z |
| format | Article |
| id | doaj.art-58221a6d0e814bc0a5f52f537f2b107e |
| institution | Directory Open Access Journal |
| issn | 2296-634X |
| language | English |
| last_indexed | 2024-04-13T09:32:06Z |
| publishDate | 2022-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cell and Developmental Biology |
| spelling | doaj.art-58221a6d0e814bc0a5f52f537f2b107e2022-12-22T02:52:13ZengFrontiers Media S.A.Frontiers in Cell and Developmental Biology2296-634X2022-08-011010.3389/fcell.2022.937761937761Spontaneous Activity Predicts Survival of Developing Cortical NeuronsDavide WarmDavide BassettiJonas SchroerHeiko J. LuhmannAnne SinningSpontaneous activity plays a crucial role in brain development by coordinating the integration of immature neurons into emerging cortical networks. High levels and complex patterns of spontaneous activity are generally associated with low rates of apoptosis in the cortex. However, whether spontaneous activity patterns directly encode for survival of individual cortical neurons during development remains an open question. Here, we longitudinally investigated spontaneous activity and apoptosis in developing cortical cultures, combining extracellular electrophysiology with calcium imaging. These experiments demonstrated that the early occurrence of calcium transients was strongly linked to neuronal survival. Silent neurons exhibited a higher probability of cell death, whereas high frequency spiking and burst behavior were almost exclusively detected in surviving neurons. In local neuronal clusters, activity of neighboring neurons exerted a pro-survival effect, whereas on the functional level, networks with a high modular topology were associated with lower cell death rates. Using machine learning algorithms, cell fate of individual neurons was predictable through the integration of spontaneous activity features. Our results indicate that high frequency spiking activity constrains apoptosis in single neurons through sustained calcium rises and thereby consolidates networks in which a high modular topology is reached during early development.https://www.frontiersin.org/articles/10.3389/fcell.2022.937761/fulldevelopmentspontaneous activitycortical neuronsapoptosismachine learningMEA |
| spellingShingle | Davide Warm Davide Bassetti Jonas Schroer Heiko J. Luhmann Anne Sinning Spontaneous Activity Predicts Survival of Developing Cortical Neurons Frontiers in Cell and Developmental Biology development spontaneous activity cortical neurons apoptosis machine learning MEA |
| title | Spontaneous Activity Predicts Survival of Developing Cortical Neurons |
| title_full | Spontaneous Activity Predicts Survival of Developing Cortical Neurons |
| title_fullStr | Spontaneous Activity Predicts Survival of Developing Cortical Neurons |
| title_full_unstemmed | Spontaneous Activity Predicts Survival of Developing Cortical Neurons |
| title_short | Spontaneous Activity Predicts Survival of Developing Cortical Neurons |
| title_sort | spontaneous activity predicts survival of developing cortical neurons |
| topic | development spontaneous activity cortical neurons apoptosis machine learning MEA |
| url | https://www.frontiersin.org/articles/10.3389/fcell.2022.937761/full |
| work_keys_str_mv | AT davidewarm spontaneousactivitypredictssurvivalofdevelopingcorticalneurons AT davidebassetti spontaneousactivitypredictssurvivalofdevelopingcorticalneurons AT jonasschroer spontaneousactivitypredictssurvivalofdevelopingcorticalneurons AT heikojluhmann spontaneousactivitypredictssurvivalofdevelopingcorticalneurons AT annesinning spontaneousactivitypredictssurvivalofdevelopingcorticalneurons |