Altered Resting-State Functional Connectivity Between Awake and Isoflurane Anesthetized Marmosets

Abstract

The common marmoset (Callithrix jacchus) is a New World primate that is becoming increasingly popular as a preclinical model. To assess functional connectivity (FC) across the marmoset brain, resting-state functional MRI (RS-fMRI) is often performed under isoflurane anesthesia to avoid the effects of motion, physiological stress, and training requirements. In marmosets, however, it remains unclear how isoflurane anesthesia affects patterns of FC. Here, we investigated the effects of isoflurane on FC when delivered with either medical air or 100% pure oxygen, two canonical methods of inhalant isoflurane anesthesia delivery. The results demonstrated that when delivered with either medical air or 100% oxygen, isoflurane globally decreased FC across resting-state networks that were identified in awake marmosets. Generally, although isoflurane globally decreased FC in resting-state networks, the spatial structure of the networks was preserved. Outside of the context of RS networks, we indexed pair-wise functional connectivity between regions across the brain and found that isoflurane substantially altered interhemispheric and thalamic FC. Taken together, these findings indicate that RS-fMRI under isoflurane anesthesia is useful to evaluate the global structure of functional networks, but may obfuscate important nodes of some network components when compared to data acquired in fully awake marmosets.

Cortico-subcortical functional connectivity profiles of resting-state networks in marmosets and humans

“…These RSNs were thresholded at z = 2.3 for visual purposes. Obtained RSNs were consistent with previously observed networks in marmosets (Belcher et al, 2013; Ghahremani et al, 2016; Hori et al, 2020b) such as default mode network (DMN) (Fig. 1A), attention network (ATN) (Fig.…”

“…Fourteen components identified as resting-state networks in the marmosets. These networks were labeled based on previous studies (Belcher et al, 2013; Hori et al, 2020b) as follows: (A) default mode network (DMN); (B) attention network (ATN); (C) salience network (SAN); (D) left primary visual network (pVIS-Lt); (E) right primary VIS (pVIS-Rt); (F) orbitofrontal network (ORN); (G)-(J) high-order VIS (hVIS1-4); (K)-(M) somatomotor networks ventral (SMNv), dorsal (SMNd), and medial (SMNm); (N) premotor network (PMN). Color bar represents the z-score of these correlation patterns thresholding at 2.3.…”

“…Resting-state functional magnetic resonance imaging (RS-fMRI) allows for circumvention of some of these challenges by allowing for non-invasive identification of robust and reproducible resting-state networks across different species (Damoiseaux et al, 2006; Fox and Raichle, 2007; Smith et al, 2013; Sporns, 2013). With recent advances in MRI hardware, we are now able to measure the functional networks/connectivities in awake marmosets (Belcher et al, 2013; Cléry et al, 2020; Hori et al, 2020b; Schaeffer et al, 2019c). Particularly, the marmoset’s small size is ideal for ultra-high field small-bore fMRI, affording high spatial resolution and signal-to-noise ratio (SNR) even in subcortical areas.…”

Using non-invasive neuroimaging to enhance the care, well-being and experimental outcomes of laboratory non-human primates (monkeys)

“…Functional interactions between distributed brain areas within specific neural networks give rise to coherent patterns of hemodynamic signals, measured as BOLD activity. Covariant relations of spontaneous BOLD signals in the resting state have been reported in humans ( Arcaro et al, 2015a ; Biswal et al, 1995 ; Fox et al, 2009 ; Power et al, 2011 ; Sporns and Honey, 2013 ) and awake NHPs ( Belcher et al, 2016 ; Ghahremani et al, 2017 ; Hori et al, 2020a ; Leopold et al, 2003 ; Liu et al, 2013 ; Logothetis, 2003b ; Silva, 2017 ; Wang et al, 2012 ) as well as in anesthetized NHPs ( Hori et al, 2020a , b ; Hutchison et al, 2012 ; Hutchison et al, 2013 ; Mantini et al, 2012a ; Vincent et al, 2007 ; Wu et al, 2016 ; Wu et al, 2017 ; Zhang et al, 2019 ). These studies have revealed that specialized cognitive and sensory networks retain their basic functional connectivity, even when not specifically engaged in task-relevant operations.…”

Interspecies activation correlations reveal functional correspondences between marmoset and human brain areas

“…Functional magnetic resonance imaging (fMRI) plays an important role in identifying the functional architecture of marmoset cortex (Belcher et al, 2013;Hori et al, 2020a;Schaeffer et al, 2019c) and in establishing brain homologies between primate species (Ghahremani et al, 2016;Hori et al, 2020b;Schaeffer et al, 2019c). In particular resting-state fMRI has been used (i) to identify homologous large-scale brain networks between marmosets and humans (Ghahremani et al, 2016;Hori et al, 2020a;Schaeffer et al, 2019c), (ii) to define functional boundaries based on intrinsic functional connectivity (Schaeffer et al, 2019b(Schaeffer et al, , 2019a, and (iii) to use functional connectivity "fingerprints" of brain areas to establish homologies between marmosets, rodents, and humans (Schaeffer et al, 2020a). Because resting state patterns are state-agnostic and spontaneous, however, this technique cannot be used to map the functional correspondences of interspecies BOLD fluctuations over time.…”