Resting-State Networks of Awake Adolescent and Adult Squirrel Monkeys Using Ultra-High Field (9.4 T) Functional Magnetic Resonance Imaging
Resting-state networks (RSNs) are increasingly forwarded as candidate biomarkers for neuropsychiatric disorders. Such biomarkers may provide objective measures for evaluating novel therapeutic interventions in nonhuman primates often used in translational neuroimaging research. This study aimed to c...
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| Published in | eNeuro Vol. 11; no. 5; p. ENEURO.0173-23.2024 |
|---|---|
| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
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United States
Society for Neuroscience
01.05.2024
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| Online Access | Get full text |
| ISSN | 2373-2822 2373-2822 |
| DOI | 10.1523/ENEURO.0173-23.2024 |
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| Abstract | Resting-state networks (RSNs) are increasingly forwarded as candidate biomarkers for neuropsychiatric disorders. Such biomarkers may provide objective measures for evaluating novel therapeutic interventions in nonhuman primates often used in translational neuroimaging research. This study aimed to characterize the RSNs of awake squirrel monkeys and compare the characteristics of those networks in adolescent and adult subjects. Twenty-seven squirrel monkeys [
n
= 12 adolescents (6 male/6 female) ∼2.5 years and
n
= 15 adults (7 male/8 female) ∼9.5 years] were gradually acclimated to awake scanning procedures; whole-brain fMRI images were acquired with a 9.4 T scanner. Group-level independent component analysis (ICA; 30 ICs) with dual regression was used to detect and compare RSNs. Twenty ICs corresponding to physiologically meaningful networks representing a range of neural functions, including motor, sensory, reward, and cognitive processes, were identified in both adolescent and adult monkeys. The reproducibility of these RSNs was evaluated across several ICA model orders. Adults showed a trend for greater connectivity compared with adolescent subjects in two of the networks of interest: (1) in the right occipital region with the OFC network and (2) in the left temporal cortex, bilateral occipital cortex, and cerebellum with the posterior cingulate network. However, when age was entered into the above model, this trend for significance was lost. These results demonstrate that squirrel monkey RSNs are stable and consistent with RSNs previously identified in humans, rodents, and other nonhuman primate species. These data also identify several networks in adolescence that are conserved and others that may change into adulthood. |
|---|---|
| AbstractList | Resting state networks (RSNs) are increasingly forwarded as candidate biomarkers for neuropsychiatric disorders. Such biomarkers may provide objective measures for evaluating novel therapeutic interventions in nonhuman primates often used in translational neuroimaging research. This study aimed to characterize the RSNs of awake squirrel monkeys and compare the characteristics of those networks in adolescent and adult subjects. Twenty-seven squirrel monkeys (
=12 adolescents [6 male/6 female] ∼2.5 years and
=15 adults [7 male/8 female] ∼9.5 years) were gradually acclimated to awake scanning procedures; whole-brain fMRI images were acquired with a 9.4 Tesla scanner. Group level independent component (ICA) analysis (30 ICs) with dual regression was used to detect and compare RSNs. Twenty ICs corresponding to physiologically meaningful networks representing a range of neural functions, including motor, sensory, reward, and cognitive processes were identified in both adolescent and adult monkeys. The reproducibility of these RSNs was evaluated across several ICA model orders. Adults showed a trend for greater connectivity compared to adolescent subjects in two of the networks of interest: (1) in the right occipital region with the OFC network and (2) in the left temporal cortex, bilateral occipital cortex, and cerebellum with the posterior cingulate network. However, when age was entered into the above model, this trend for significance was lost. These results demonstrate that squirrel monkey RSNs are stable and consistent with RSNs previously identified in humans, rodents, and other nonhuman primate species. These data also identify several networks in adolescence that are conserved and others that may change into adulthood.
Functional magnetic resonance imaging procedures have revealed important information about how the brain is modified by experimental manipulations, disease states, and aging throughout the lifespan. Preclinical neuroimaging, especially in nonhuman primates, has become a frequently used means to answer targeted questions related to brain resting-state functional connectivity. The present study characterized resting state networks (RSNs) in adult and adolescent squirrel monkeys; twenty RSNs corresponding to networks representing a range of neural functions were identified. The RSNs identified here can be utilized in future studies examining the effects of experimental manipulations on brain connectivity in squirrel monkeys. These data also may be useful for comparative analysis with other primate species to provide an evolutionary perspective for understanding brain function and organization. Resting-state networks (RSNs) are increasingly forwarded as candidate biomarkers for neuropsychiatric disorders. Such biomarkers may provide objective measures for evaluating novel therapeutic interventions in nonhuman primates often used in translational neuroimaging research. This study aimed to characterize the RSNs of awake squirrel monkeys and compare the characteristics of those networks in adolescent and adult subjects. Twenty-seven squirrel monkeys [n = 12 adolescents (6 male/6 female) ∼2.5 years and n = 15 adults (7 male/8 female) ∼9.5 years] were gradually acclimated to awake scanning procedures; whole-brain fMRI images were acquired with a 9.4 T scanner. Group-level independent component analysis (ICA; 30 ICs) with dual regression was used to detect and compare RSNs. Twenty ICs corresponding to physiologically meaningful networks representing a range of neural functions, including motor, sensory, reward, and cognitive processes, were identified in both adolescent and adult monkeys. The reproducibility of these RSNs was evaluated across several ICA model orders. Adults showed a trend for greater connectivity compared with adolescent subjects in two of the networks of interest: (1) in the right occipital region with the OFC network and (2) in the left temporal cortex, bilateral occipital cortex, and cerebellum with the posterior cingulate network. However, when age was entered into the above model, this trend for significance was lost. These results demonstrate that squirrel monkey RSNs are stable and consistent with RSNs previously identified in humans, rodents, and other nonhuman primate species. These data also identify several networks in adolescence that are conserved and others that may change into adulthood. Resting-state networks (RSNs) are increasingly forwarded as candidate biomarkers for neuropsychiatric disorders. Such biomarkers may provide objective measures for evaluating novel therapeutic interventions in nonhuman primates often used in translational neuroimaging research. This study aimed to characterize the RSNs of awake squirrel monkeys and compare the characteristics of those networks in adolescent and adult subjects. Twenty-seven squirrel monkeys [ n = 12 adolescents (6 male/6 female) ∼2.5 years and n = 15 adults (7 male/8 female) ∼9.5 years] were gradually acclimated to awake scanning procedures; whole-brain fMRI images were acquired with a 9.4 T scanner. Group-level independent component analysis (ICA; 30 ICs) with dual regression was used to detect and compare RSNs. Twenty ICs corresponding to physiologically meaningful networks representing a range of neural functions, including motor, sensory, reward, and cognitive processes, were identified in both adolescent and adult monkeys. The reproducibility of these RSNs was evaluated across several ICA model orders. Adults showed a trend for greater connectivity compared with adolescent subjects in two of the networks of interest: (1) in the right occipital region with the OFC network and (2) in the left temporal cortex, bilateral occipital cortex, and cerebellum with the posterior cingulate network. However, when age was entered into the above model, this trend for significance was lost. These results demonstrate that squirrel monkey RSNs are stable and consistent with RSNs previously identified in humans, rodents, and other nonhuman primate species. These data also identify several networks in adolescence that are conserved and others that may change into adulthood. Resting-state networks (RSNs) are increasingly forwarded as candidate biomarkers for neuropsychiatric disorders. Such biomarkers may provide objective measures for evaluating novel therapeutic interventions in nonhuman primates often used in translational neuroimaging research. This study aimed to characterize the RSNs of awake squirrel monkeys and compare the characteristics of those networks in adolescent and adult subjects. Twenty-seven squirrel monkeys [n = 12 adolescents (6 male/6 female) ∼2.5 years and n = 15 adults (7 male/8 female) ∼9.5 years] were gradually acclimated to awake scanning procedures; whole-brain fMRI images were acquired with a 9.4 T scanner. Group-level independent component analysis (ICA; 30 ICs) with dual regression was used to detect and compare RSNs. Twenty ICs corresponding to physiologically meaningful networks representing a range of neural functions, including motor, sensory, reward, and cognitive processes, were identified in both adolescent and adult monkeys. The reproducibility of these RSNs was evaluated across several ICA model orders. Adults showed a trend for greater connectivity compared with adolescent subjects in two of the networks of interest: (1) in the right occipital region with the OFC network and (2) in the left temporal cortex, bilateral occipital cortex, and cerebellum with the posterior cingulate network. However, when age was entered into the above model, this trend for significance was lost. These results demonstrate that squirrel monkey RSNs are stable and consistent with RSNs previously identified in humans, rodents, and other nonhuman primate species. These data also identify several networks in adolescence that are conserved and others that may change into adulthood.Resting-state networks (RSNs) are increasingly forwarded as candidate biomarkers for neuropsychiatric disorders. Such biomarkers may provide objective measures for evaluating novel therapeutic interventions in nonhuman primates often used in translational neuroimaging research. This study aimed to characterize the RSNs of awake squirrel monkeys and compare the characteristics of those networks in adolescent and adult subjects. Twenty-seven squirrel monkeys [n = 12 adolescents (6 male/6 female) ∼2.5 years and n = 15 adults (7 male/8 female) ∼9.5 years] were gradually acclimated to awake scanning procedures; whole-brain fMRI images were acquired with a 9.4 T scanner. Group-level independent component analysis (ICA; 30 ICs) with dual regression was used to detect and compare RSNs. Twenty ICs corresponding to physiologically meaningful networks representing a range of neural functions, including motor, sensory, reward, and cognitive processes, were identified in both adolescent and adult monkeys. The reproducibility of these RSNs was evaluated across several ICA model orders. Adults showed a trend for greater connectivity compared with adolescent subjects in two of the networks of interest: (1) in the right occipital region with the OFC network and (2) in the left temporal cortex, bilateral occipital cortex, and cerebellum with the posterior cingulate network. However, when age was entered into the above model, this trend for significance was lost. These results demonstrate that squirrel monkey RSNs are stable and consistent with RSNs previously identified in humans, rodents, and other nonhuman primate species. These data also identify several networks in adolescence that are conserved and others that may change into adulthood. |
| Author | de Moura, Fernando B. Withey, Sarah L. Yassin, Walid Bergman, Jack Cao, Lei Kohut, Stephen J. Kangas, Brian D. |
| AuthorAffiliation | 4 McLean Imaging Center, McLean Hospital , Belmont, Massachusetts 02478 1 Behavioral Neuroimaging Laboratory, McLean Hospital , Belmont, Massachusetts 02478 2 Behavioral Biology Program, McLean Hospital , Belmont, Massachusetts 02478 3 Department of Psychiatry, Harvard Medical School , Boston, Massachusetts 02478 |
| AuthorAffiliation_xml | – name: 1 Behavioral Neuroimaging Laboratory, McLean Hospital , Belmont, Massachusetts 02478 – name: 4 McLean Imaging Center, McLean Hospital , Belmont, Massachusetts 02478 – name: 2 Behavioral Biology Program, McLean Hospital , Belmont, Massachusetts 02478 – name: 3 Department of Psychiatry, Harvard Medical School , Boston, Massachusetts 02478 |
| Author_xml | – sequence: 1 givenname: Walid surname: Yassin fullname: Yassin, Walid – sequence: 2 givenname: Fernando B. surname: de Moura fullname: de Moura, Fernando B. – sequence: 3 givenname: Sarah L. surname: Withey fullname: Withey, Sarah L. – sequence: 4 givenname: Lei surname: Cao fullname: Cao, Lei – sequence: 5 givenname: Brian D. surname: Kangas fullname: Kangas, Brian D. – sequence: 6 givenname: Jack surname: Bergman fullname: Bergman, Jack – sequence: 7 givenname: Stephen J. surname: Kohut fullname: Kohut, Stephen J. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38627065$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | Copyright © 2024 Yassine et al. Copyright © 2024 Yassin et al. Copyright © 2024 Yassin et al. 2024 |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 W.Y. and F.B.M. contributed equally to this work. This work was supported by the National Institute on Drug Abuse (NIDA) R01DA048150 (S.J.K.) and R01DA047575 (J.B./S.J.K./B.D.K.), Alkermes Pathways Research Awards grant (S.L.W.), T32DA015036 (F.B.M.), K01DA039306 (S.J.K.), and S10RR019356, and by the Counterdrug Technology Assessment Center, an office within the Office of National Drug Control Policy, via Contract No. DBK39-03-C-0075, awarded by the Army Contracting Agency. The content of the information does not necessarily reflect the position or the policy of the U.S. Government, and no official endorsement should be inferred. The authors declare no competing financial interests. We thank Jessi Stover, Samantha McGouldrick, Bryan Carlson, and Craig Stone for their efforts in acclimating subjects to awake MRI procedures, Kenroy Cayetano for engineering the experimental equipment used for these studies and providing the schematic for Figure 1, Bonnie Adams for assistance with MRI data acquisition, and Drs. Dionyssis Mintzopolous and Michael L. Rohan for developing the acquisition sequences used here. We acknowledge Dr. Lisa Nickerson from the Harvard Catalyst Biostatistics consulting program for helpful discussions about independent component analysis and presentation of results. Portions of this work were presented at the annual meeting of the Society for Neuroscience, 2021. Author contributions: W.Y., B.D.K., J.B., and S.J.K. designed Research; W.Y., F.B.M., S.L.W., and S.J.K. performed research; W.Y., F.B.M., S.L.W., L.C., and S.J.K. analyzed data; W.Y., F.B.M., S.L.W., L.C., B.D.K., J.B., and S.J.K. wrote the paper. |
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| References | 2024050610501313000_11.5.ENEURO.0173-23.2024.48 2024050610501313000_11.5.ENEURO.0173-23.2024.49 2024050610501313000_11.5.ENEURO.0173-23.2024.44 2024050610501313000_11.5.ENEURO.0173-23.2024.45 2024050610501313000_11.5.ENEURO.0173-23.2024.46 2024050610501313000_11.5.ENEURO.0173-23.2024.47 2024050610501313000_11.5.ENEURO.0173-23.2024.40 2024050610501313000_11.5.ENEURO.0173-23.2024.41 2024050610501313000_11.5.ENEURO.0173-23.2024.42 2024050610501313000_11.5.ENEURO.0173-23.2024.43 2024050610501313000_11.5.ENEURO.0173-23.2024.80 2024050610501313000_11.5.ENEURO.0173-23.2024.81 2024050610501313000_11.5.ENEURO.0173-23.2024.15 2024050610501313000_11.5.ENEURO.0173-23.2024.59 2024050610501313000_11.5.ENEURO.0173-23.2024.16 2024050610501313000_11.5.ENEURO.0173-23.2024.17 2024050610501313000_11.5.ENEURO.0173-23.2024.18 2024050610501313000_11.5.ENEURO.0173-23.2024.11 2024050610501313000_11.5.ENEURO.0173-23.2024.55 2024050610501313000_11.5.ENEURO.0173-23.2024.12 2024050610501313000_11.5.ENEURO.0173-23.2024.56 2024050610501313000_11.5.ENEURO.0173-23.2024.13 2024050610501313000_11.5.ENEURO.0173-23.2024.57 2024050610501313000_11.5.ENEURO.0173-23.2024.14 2024050610501313000_11.5.ENEURO.0173-23.2024.58 2024050610501313000_11.5.ENEURO.0173-23.2024.51 2024050610501313000_11.5.ENEURO.0173-23.2024.52 2024050610501313000_11.5.ENEURO.0173-23.2024.53 2024050610501313000_11.5.ENEURO.0173-23.2024.10 2024050610501313000_11.5.ENEURO.0173-23.2024.54 2024050610501313000_11.5.ENEURO.0173-23.2024.50 2024050610501313000_11.5.ENEURO.0173-23.2024.19 2024050610501313000_11.5.ENEURO.0173-23.2024.26 2024050610501313000_11.5.ENEURO.0173-23.2024.27 2024050610501313000_11.5.ENEURO.0173-23.2024.28 2024050610501313000_11.5.ENEURO.0173-23.2024.29 2024050610501313000_11.5.ENEURO.0173-23.2024.22 2024050610501313000_11.5.ENEURO.0173-23.2024.66 2024050610501313000_11.5.ENEURO.0173-23.2024.23 2024050610501313000_11.5.ENEURO.0173-23.2024.67 2024050610501313000_11.5.ENEURO.0173-23.2024.24 2024050610501313000_11.5.ENEURO.0173-23.2024.68 2024050610501313000_11.5.ENEURO.0173-23.2024.25 2024050610501313000_11.5.ENEURO.0173-23.2024.69 2024050610501313000_11.5.ENEURO.0173-23.2024.62 2024050610501313000_11.5.ENEURO.0173-23.2024.63 2024050610501313000_11.5.ENEURO.0173-23.2024.20 2024050610501313000_11.5.ENEURO.0173-23.2024.64 2024050610501313000_11.5.ENEURO.0173-23.2024.21 2024050610501313000_11.5.ENEURO.0173-23.2024.65 2024050610501313000_11.5.ENEURO.0173-23.2024.60 2024050610501313000_11.5.ENEURO.0173-23.2024.61 2024050610501313000_11.5.ENEURO.0173-23.2024.37 2024050610501313000_11.5.ENEURO.0173-23.2024.38 2024050610501313000_11.5.ENEURO.0173-23.2024.39 2024050610501313000_11.5.ENEURO.0173-23.2024.33 2024050610501313000_11.5.ENEURO.0173-23.2024.77 2024050610501313000_11.5.ENEURO.0173-23.2024.34 2024050610501313000_11.5.ENEURO.0173-23.2024.78 2024050610501313000_11.5.ENEURO.0173-23.2024.9 2024050610501313000_11.5.ENEURO.0173-23.2024.35 2024050610501313000_11.5.ENEURO.0173-23.2024.79 2024050610501313000_11.5.ENEURO.0173-23.2024.8 2024050610501313000_11.5.ENEURO.0173-23.2024.36 2024050610501313000_11.5.ENEURO.0173-23.2024.73 2024050610501313000_11.5.ENEURO.0173-23.2024.30 2024050610501313000_11.5.ENEURO.0173-23.2024.74 2024050610501313000_11.5.ENEURO.0173-23.2024.31 2024050610501313000_11.5.ENEURO.0173-23.2024.75 2024050610501313000_11.5.ENEURO.0173-23.2024.32 2024050610501313000_11.5.ENEURO.0173-23.2024.76 2024050610501313000_11.5.ENEURO.0173-23.2024.70 2024050610501313000_11.5.ENEURO.0173-23.2024.71 2024050610501313000_11.5.ENEURO.0173-23.2024.72 2024050610501313000_11.5.ENEURO.0173-23.2024.7 2024050610501313000_11.5.ENEURO.0173-23.2024.6 2024050610501313000_11.5.ENEURO.0173-23.2024.5 2024050610501313000_11.5.ENEURO.0173-23.2024.4 2024050610501313000_11.5.ENEURO.0173-23.2024.3 2024050610501313000_11.5.ENEURO.0173-23.2024.2 2024050610501313000_11.5.ENEURO.0173-23.2024.1 36711620 - bioRxiv. 2023 Jan 09 |
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| Snippet | Resting-state networks (RSNs) are increasingly forwarded as candidate biomarkers for neuropsychiatric disorders. Such biomarkers may provide objective measures... Resting state networks (RSNs) are increasingly forwarded as candidate biomarkers for neuropsychiatric disorders. Such biomarkers may provide objective measures... |
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| SubjectTerms | New Research |
| Title | Resting-State Networks of Awake Adolescent and Adult Squirrel Monkeys Using Ultra-High Field (9.4 T) Functional Magnetic Resonance Imaging |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/38627065 https://www.proquest.com/docview/3040320984 https://pubmed.ncbi.nlm.nih.gov/PMC11075123 |
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