Neuronal dynamics of the default mode network and anterior insular cortex: Intrinsic properties and modulation by salient stimuli

Autor: Tzu-Hao Harry Chao, Byeongwook Lee, Li-Ming Hsu, Domenic Hayden Cerri, Wei-Ting Zhang, Tzu-Wen Winnie Wang, Srikanth Ryali, Vinod Menon, Yen-Yu Ian Shih
Rok vydání: 2022
Předmět:
Popis: SummaryThe default mode network (DMN) is closely associated with self-referential mental functions and its dysfunction is implicated in many neuropsychiatric disorders. However, the neurophysiological properties and task-based functional organization of the rodent DMN are poorly understood, limiting its translational utility. Here, we combine fiber-photometry with fMRI and computational modeling to characterize dynamics of putative rodent DMN nodes and their interactions with the anterior insular cortex (AI) of the salience network. We reveal neuronal activity changes in AI and DMN nodes prior to fMRI-derived DMN activations and uncover cyclical transition patterns between spatiotemporal neuronal activity states. Finally, we demonstrate that salient oddball stimuli suppress the DMN and enhance AI neuronal activity, and that the AI causally inhibits the retrosplenial cortex, a prominent DMN node. These findings elucidate previously unknown properties regarding the neurobiological foundations of the rodent DMN and its modulation by salient stimuli, paving the way for future translational studies.HighlightsConcurrent measurement of neuronal (GCaMP) and fMRI signals in retrosplenial, cingulate, prelimbic, and anterior insula corticesGCaMP signals reveal neuronal antagonism between AI and fMRI-derived DMN activation and deactivationGCaMP signals reveal salient oddball stimuli-induced suppression of prelimbic, cingulate and retrosplenial cortices, and activation of anterior insular cortexAnterior insular cortex causally inhibits retrosplenial cortex during processing of salient oddball stimuliFindings delineate neurofunctional organization of the rodent DMN and provide a more informed model for translational studies
Databáze: OpenAIRE