Variability of single trial brain activation predicts fluctuations in reaction time
Brain activation stability is crucial to understanding attention lapses. EEG methods could provide excellent markers to assess neuronal response variability with respect to temporal (intertrial coherence) and spatial variability (topographic consistency) as well as variations in activation intensity...
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| Main Authors: | , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
March 2015
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| In: |
Biological psychology
Year: 2015, Volume: 106, Pages: 50-60 |
| ISSN: | 1873-6246 |
| DOI: | 10.1016/j.biopsycho.2015.01.013 |
| Online Access: | Verlag, Volltext: http://dx.doi.org/10.1016/j.biopsycho.2015.01.013 Verlag, Volltext: http://www.sciencedirect.com/science/article/pii/S0301051115000241 
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| Author Notes: | Stephan Bender, Tobias Banaschewski, Veit Roessner, Christoph Klein, Marcella Rietschel, Bernd Feige, Daniel Brandeis, Manfred Laucht |
| Summary: | Brain activation stability is crucial to understanding attention lapses. EEG methods could provide excellent markers to assess neuronal response variability with respect to temporal (intertrial coherence) and spatial variability (topographic consistency) as well as variations in activation intensity (low frequency variability of single trial global field power). We calculated intertrial coherence, topographic consistency and low frequency amplitude variability during target P300 in a continuous performance test in 263 15-year-olds from a cohort with psychosocial and biological risk factors. Topographic consistency and low frequency amplitude variability predicted reaction time fluctuations (RTSD) in a linear model. Higher RTSD was only associated with higher psychosocial adversity in the presence of the homozygous 6R-10R dopamine transporter haplotype. We propose that topographic variability of single trial P300 reflects noise as well as variability in evoked cortical activation patterns. Dopaminergic neuromodulation interacted with environmental and biological risk factors to predict behavioural reaction time variability. |
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| Item Description: | Gesehen am 20.09.2017 |
| Physical Description: | Online Resource |
| ISSN: | 1873-6246 |
| DOI: | 10.1016/j.biopsycho.2015.01.013 |