101. Bottom-up sensory processing can decrease activity and functional connectivity in the default mode like network in rats
- Author
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Georgios A. Keliris, Disha Shah, Annemie Van der Linden, Rukun Hinz, Marleen Verhoye, Michael E. Belloy, Meriam Malekzadeh, Peeters Lmb, Stephan Missault, and Vanreusel
- Subjects
Elementary cognitive task ,medicine.diagnostic_test ,Sensory processing ,Computer science ,Functional connectivity ,medicine.medical_treatment ,medicine ,Stimulation ,Top-down and bottom-up design ,Stimulus (physiology) ,Functional magnetic resonance imaging ,Neuroscience ,Default mode network - Abstract
The default mode network is a large-scale brain network that is active during rest and internally focused states and deactivates as well as desynchronizes during externally oriented (top-down) attention demanding cognitive tasks. However, it is not sufficiently understood if unpredicted salient stimuli, able to trigger bottom-up attentional processes, could also result in similar reduction of activity and functional connectivity in the DMN. In this study, we investigated whether bottom-up sensory processing could influence the default mode like network (DMLN) in rats. DMLN activity was examined using block-design visual functional magnetic resonance imaging (fMRI) while its synchronization was investigated by comparing functional connectivity during a resting versus a continuously stimulated brain state by unpredicted light flashes. We demonstrated that activity in DMLN regions was decreased during visual stimulus blocks and increased during blanks. Furthermore, decreased inter-network functional connectivity between the DMLN and visual networks as well as decreased intra-network functional connectivity within the DMLN was observed during the continuous visual stimulation. These results suggest that triggering of bottom-up attention mechanisms in anesthetized rats can lead to a cascade similar to top-down orienting of attention in humans and is able to deactivate and desynchronize the DMLN.
- Published
- 2018