1
|
Chan RW, Hamilton-Fletcher G, Edelman BJ, Faiq MA, Sajitha TA, Moeller S, Chan KC. NOise Reduction with DIstribution Corrected (NORDIC) principal component analysis improves brain activity detection across rodent and human functional MRI contexts. IMAGING NEUROSCIENCE (CAMBRIDGE, MASS.) 2024; 2:1-18. [PMID: 39463889 PMCID: PMC11506209 DOI: 10.1162/imag_a_00325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 09/11/2024] [Accepted: 09/12/2024] [Indexed: 10/29/2024]
Abstract
NOise Reduction with DIstribution Corrected (NORDIC) principal component analysis (PCA) has been shown to selectively suppress thermal noise and improve the temporal signal-to-noise ratio (tSNR) in human functional magnetic resonance imaging (fMRI). However, the feasibility to improve data quality for rodent fMRI using NORDIC PCA remains uncertain. NORDIC PCA may also be particularly beneficial for improving topological brain mapping, as conventional mapping requires precise spatiotemporal signals from large datasets (ideally ~1 hour acquisition) for individual representations. In this study, we evaluated the effects of NORDIC PCA compared with "Standard" processing in various rodent fMRI contexts that range from task-evoked optogenetic fMRI to resting-state fMRI. We also evaluated the effects of NORDIC PCA on human resting-state and retinotopic mapping fMRI via population receptive field (pRF) modeling. In rodent optogenetic fMRI, apart from doubling the tSNR, NORDIC PCA resulted in a larger number of activated voxels and a significant decrease in the variance of evoked brain responses without altering brain morphology. In rodent resting-state fMRI, we found that NORDIC PCA induced a nearly threefold increase in tSNR and preserved task-free relative cerebrovascular reactivity (rCVR) across cortical depth. NORDIC PCA further improved the detection of TGN020-induced aquaporin-4 inhibition on rCVR compared with Standard processing without NORDIC PCA. NORDIC PCA also increased the tSNR for both human resting-state and pRF fMRI, and for the latter also increased activation cluster sizes while retaining retinotopic organization. This suggests that NORDIC PCA preserves the spatiotemporal precision of fMRI signals needed for pRF analysis, and effectively captures small activity changes with high sensitivity. Taken together, these results broadly demonstrate the value of NORDIC PCA for the enhanced detection of neural dynamics across various rodent and human fMRI contexts. This can in turn play an important role in improving fMRI image quality and sensitivity for translational and preclinical neuroimaging research.
Collapse
Affiliation(s)
- Russell W. Chan
- Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY, United States
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, United States
- Tech4Health Institute, New York University Grossman School of Medicine, New York, NY, United States
- E-SENSE Innovation & Technology, Hong Kong, China
- Hong Kong Centre for Cerebro-cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Giles Hamilton-Fletcher
- Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY, United States
- Tech4Health Institute, New York University Grossman School of Medicine, New York, NY, United States
| | - Bradley J. Edelman
- Brain-Wide Circuits for Behavior Research Group, Max Planck Institute of Biological Intelligence, Planegg, Germany
- Emotion Research Department, Max Planck Institute of Psychiatry, Munich, Germany
| | - Muneeb A. Faiq
- Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY, United States
- Tech4Health Institute, New York University Grossman School of Medicine, New York, NY, United States
| | - Thajunnisa A. Sajitha
- Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY, United States
- Tech4Health Institute, New York University Grossman School of Medicine, New York, NY, United States
| | - Steen Moeller
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, United States
| | - Kevin C. Chan
- Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY, United States
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, United States
- Tech4Health Institute, New York University Grossman School of Medicine, New York, NY, United States
- Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
- Department of Biomedical Engineering, Tandon School of Engineering, New York University, New York, NY, United States
- Department of Ophthalmology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| |
Collapse
|
2
|
Zou Y, Tong C, Peng W, Qiu Y, Li J, Xia Y, Pei M, Zhang K, Li W, Xu M, Liang Z. Cell-type-specific optogenetic fMRI on basal forebrain reveals functional network basis of behavioral preference. Neuron 2024; 112:1342-1357.e6. [PMID: 38359827 DOI: 10.1016/j.neuron.2024.01.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 12/12/2023] [Accepted: 01/16/2024] [Indexed: 02/17/2024]
Abstract
The basal forebrain (BF) is a complex structure that plays key roles in regulating various brain functions. However, it remains unclear how cholinergic and non-cholinergic BF neurons modulate large-scale functional networks and their relevance in intrinsic and extrinsic behaviors. With an optimized awake mouse optogenetic fMRI approach, we revealed that optogenetic stimulation of four BF neuron types evoked distinct cell-type-specific whole-brain BOLD activations, which could be attributed to BF-originated low-dimensional structural networks. Additionally, optogenetic activation of VGLUT2, ChAT, and PV neurons in the BF modulated the preference for locomotion, exploration, and grooming, respectively. Furthermore, we uncovered the functional network basis of the above BF-modulated behavioral preference through a decoding model linking the BF-modulated BOLD activation, low-dimensional structural networks, and behavioral preference. To summarize, we decoded the functional network basis of differential behavioral preferences with cell-type-specific optogenetic fMRI on the BF and provided an avenue for investigating mouse behaviors from a whole-brain view.
Collapse
Affiliation(s)
- Yijuan Zou
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; International Center for Primate Brain Research, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 201602, China
| | - Chuanjun Tong
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; International Center for Primate Brain Research, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 201602, China
| | - Wanling Peng
- Songjiang Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200025, China
| | - Yue Qiu
- Cardiac Intensive Care Center, Zhongshan Hospital, Fudan University Shanghai, Shanghai 200032, China
| | - Jiangxue Li
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100101, China
| | - Ying Xia
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Mengchao Pei
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Kaiwei Zhang
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Weishuai Li
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Min Xu
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China.
| | - Zhifeng Liang
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; International Center for Primate Brain Research, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 201602, China.
| |
Collapse
|
3
|
Cerri DH, Albaugh DL, Walton LR, Katz B, Wang TW, Chao THH, Zhang W, Nonneman RJ, Jiang J, Lee SH, Etkin A, Hall CN, Stuber GD, Shih YYI. Distinct neurochemical influences on fMRI response polarity in the striatum. Nat Commun 2024; 15:1916. [PMID: 38429266 PMCID: PMC10907631 DOI: 10.1038/s41467-024-46088-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 02/13/2024] [Indexed: 03/03/2024] Open
Abstract
The striatum, known as the input nucleus of the basal ganglia, is extensively studied for its diverse behavioral roles. However, the relationship between its neuronal and vascular activity, vital for interpreting functional magnetic resonance imaging (fMRI) signals, has not received comprehensive examination within the striatum. Here, we demonstrate that optogenetic stimulation of dorsal striatal neurons or their afferents from various cortical and subcortical regions induces negative striatal fMRI responses in rats, manifesting as vasoconstriction. These responses occur even with heightened striatal neuronal activity, confirmed by electrophysiology and fiber-photometry. In parallel, midbrain dopaminergic neuron optogenetic modulation, coupled with electrochemical measurements, establishes a link between striatal vasodilation and dopamine release. Intriguingly, in vivo intra-striatal pharmacological manipulations during optogenetic stimulation highlight a critical role of opioidergic signaling in generating striatal vasoconstriction. This observation is substantiated by detecting striatal vasoconstriction in brain slices after synthetic opioid application. In humans, manipulations aimed at increasing striatal neuronal activity likewise elicit negative striatal fMRI responses. Our results emphasize the necessity of considering vasoactive neurotransmission alongside neuronal activity when interpreting fMRI signal.
Collapse
Affiliation(s)
- Domenic H Cerri
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Daniel L Albaugh
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Lindsay R Walton
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Brittany Katz
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tzu-Wen Wang
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tzu-Hao Harry Chao
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Weiting Zhang
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Randal J Nonneman
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jing Jiang
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Pediatrics, University of Iowa Carver College of Medicine, Iowa City, IA, USA
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
- Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Sung-Ho Lee
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amit Etkin
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Alto Neuroscience, Los Altos, CA, USA
| | - Catherine N Hall
- Sussex Neuroscience, University of Sussex, Falmer, United Kingdom
- School of Psychology, University of Sussex, Falmer, United Kingdom
| | - Garret D Stuber
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
- Department of Pharmacology, University of Washington, Seattle, WA, USA
| | - Yen-Yu Ian Shih
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| |
Collapse
|
4
|
Altahini S, Arnoux I, Stroh A. Optogenetics 2.0: challenges and solutions towards a quantitative probing of neural circuits. Biol Chem 2024; 405:43-54. [PMID: 37650383 DOI: 10.1515/hsz-2023-0194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 08/02/2023] [Indexed: 09/01/2023]
Abstract
To exploit the full potential of optogenetics, we need to titrate and tailor optogenetic methods to emulate naturalistic circuit function. For that, the following prerequisites need to be met: first, we need to target opsin expression not only to genetically defined neurons per se, but to specifically target a functional node. Second, we need to assess the scope of optogenetic modulation, i.e. the fraction of optogenetically modulated neurons. Third, we need to integrate optogenetic control in a closed loop setting. Fourth, we need to further safe and stable gene expression and light delivery to bring optogenetics to the clinics. Here, we review these concepts for the human and rodent brain.
Collapse
Affiliation(s)
- Saleh Altahini
- Leibniz Institute for Resilience Research, D-55122 Mainz, Germany
| | - Isabelle Arnoux
- Cerebral Physiopathology Laboratory, Center for Interdisciplinary Research in Biology, College de France, Centre national de la recherche scientifique, Institut national de la santé et de la recherche médicale, Université PSL, F-75005 Paris, France
| | - Albrecht Stroh
- Leibniz Institute for Resilience Research, D-55122 Mainz, Germany
- Institute of Pathophysiology, University Medical Center Mainz, D-55128 Mainz, Germany
| |
Collapse
|
5
|
Chao THH, Lee B, Hsu LM, Cerri DH, Zhang WT, Wang TWW, Ryali S, Menon V, Shih YYI. Neuronal dynamics of the default mode network and anterior insular cortex: Intrinsic properties and modulation by salient stimuli. SCIENCE ADVANCES 2023; 9:eade5732. [PMID: 36791185 PMCID: PMC9931216 DOI: 10.1126/sciadv.ade5732] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 01/19/2023] [Indexed: 05/26/2023]
Abstract
The default mode network (DMN) is critical for self-referential mental processes, 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 functional magnetic resonance imaging (fMRI) and computational modeling to characterize dynamics of putative rat DMN nodes and their interactions with the anterior insular cortex (AI) of the salience network. Our analysis revealed neuronal activity changes in AI and DMN nodes preceding fMRI-derived DMN activations and cyclical transitions between brain network states. Furthermore, 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 the neurophysiological foundations of the rodent DMN, its spatiotemporal dynamical properties, and modulation by salient stimuli, paving the way for future translational studies.
Collapse
Affiliation(s)
- Tzu-Hao Harry Chao
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Byeongwook Lee
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Li-Ming Hsu
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Domenic Hayden Cerri
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Wei-Ting Zhang
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tzu-Wen Winnie Wang
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Srikanth Ryali
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Vinod Menon
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
- Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| |
Collapse
|