[Recovering the contents of consciousness in the noise of neuroimaging].
Andreas Kleinschmidt
Medecine sciences : M/S February 2011 DOI: 10.1051/medsci/2011272199 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Key points | Argues that standard event-related analyses of evoked neural activity neglect informative spatial and temporal variability, and that multivariate decoding of spatial patterns and study of temporal variability in ongoing activity have driven major advances in cognitive neuroscience, with implications beyond functional neuroimaging. |
Abstract
A classical approach in the neurosciences is to study neural activity modulations induced by a stimulus, a task, etc. This approach is anchored in a behaviourist culture and has proven informative within certain limits. The present paper shows that this approach nonetheless neglects aspects of neural activity that can also contribute important information about brain function. Over the last years, the contributions with the strongest impact on progress in cognitive neuroscience have used other approaches that exploit a spatial or temporal variability of neural activity that standard analyses consider as noise and hence do not take into account. By applying multi-variate analyses, spatial variability of evoked responses has permitted decoding sensory and cognitive representations in the brain. Temporal variability of ongoing neural activity influences how stimuli are perceived trial by trial as well as the associated evoked responses which points out the importance of spontaneous brain activity for cognition. We describe these two kind of approaches based on experiments using functional neuroimaging but the conclusions generalize to other techniques applied in the neurosciences.