Detection of silent cells, synchronization and modulatory activity in developing cellular networks.

Autor: Hjorth JJ; Department of Integrative Neurophysiology, Center for Neurogenomics & Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam, De Boelelaan 1085, 1081, HV, Amsterdam, the Netherlands., Dawitz J; Department of Integrative Neurophysiology, Center for Neurogenomics & Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam, De Boelelaan 1085, 1081, HV, Amsterdam, the Netherlands., Kroon T; Department of Integrative Neurophysiology, Center for Neurogenomics & Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam, De Boelelaan 1085, 1081, HV, Amsterdam, the Netherlands., Pires J; Department of Integrative Neurophysiology, Center for Neurogenomics & Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam, De Boelelaan 1085, 1081, HV, Amsterdam, the Netherlands., Dassen VJ; Department of Integrative Neurophysiology, Center for Neurogenomics & Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam, De Boelelaan 1085, 1081, HV, Amsterdam, the Netherlands., Berkhout JA; Department of Integrative Neurophysiology, Center for Neurogenomics & Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam, De Boelelaan 1085, 1081, HV, Amsterdam, the Netherlands., Emperador Melero J; Department of Functional Genomics, Center for Neurogenomics & Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam, De Boelelaan 1085, 1081, HV, Amsterdam, the Netherlands., Nadadhur AG; Department of Functional Genomics, Center for Neurogenomics & Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam, De Boelelaan 1085, 1081, HV, Amsterdam, the Netherlands., Alevra M; Department of Neurophysiology and Cellular Biophysics, University Medical Center Göttingen, Humboldtallee 23, 37073, Göttingen, Germany., Toonen RF; Department of Functional Genomics, Center for Neurogenomics & Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam, De Boelelaan 1085, 1081, HV, Amsterdam, the Netherlands., Heine VM; Department of Functional Genomics, Center for Neurogenomics & Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam, De Boelelaan 1085, 1081, HV, Amsterdam, the Netherlands.; Department of Pediatrics/Child Neurology, VU University Medical Center, De Boelelaan 1117, 1081, HV, Amsterdam, the Netherlands., Mansvelder HD; Department of Integrative Neurophysiology, Center for Neurogenomics & Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam, De Boelelaan 1085, 1081, HV, Amsterdam, the Netherlands., Meredith RM; Department of Integrative Neurophysiology, Center for Neurogenomics & Cognitive Research, Neuroscience Campus Amsterdam, VU University Amsterdam, De Boelelaan 1085, 1081, HV, Amsterdam, the Netherlands.
Jazyk: angličtina
Zdroj: Developmental neurobiology [Dev Neurobiol] 2016 Apr; Vol. 76 (4), pp. 357-74. Date of Electronic Publication: 2015 Jul 01.
DOI: 10.1002/dneu.22319
Abstrakt: Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell migration, to the refinement of synapses, topographic maps, and the mature composition of ion channels. These emergent activity patterns are not present in all cells simultaneously within the network and more immature "silent" cells, potentially correlated with the presence of silent synapses, are prominent in different networks during early developmental periods. Many current network analyses for detection of synchronous cellular activity utilize activity-based pixel correlations to identify cellular-based regions of interest (ROIs) and coincident cell activity. However, using activity-based correlations, these methods first underestimate or ignore the inactive silent cells within the developing network and second, are difficult to apply within cell-dense regions commonly found in developing brain networks. In addition, previous methods may ignore ROIs within a network that shows transient activity patterns comprising both inactive and active periods. We developed analysis software to semi-automatically detect cells within developing neuronal networks that were imaged using calcium-sensitive reporter dyes. Using an iterative threshold, modulation of activity was tracked within individual cells across the network. The distribution pattern of both inactive and active, including synchronous cells, could be determined based on distance measures to neighboring cells and according to different anatomical layers.
(© 2015 Wiley Periodicals, Inc.)
Databáze: MEDLINE
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