1
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Ohtake M, Abe K, Hasegawa M, Itokazu T, Selvakumar V, Matunis A, Stacy E, Froebrich E, Huynh N, Lee H, Kambe Y, Yamamoto T, Sato TK, Sato TR. Encoding of self-initiated actions in axon terminals of the mesocortical pathway. NEUROPHOTONICS 2024; 11:033408. [PMID: 38726349 PMCID: PMC11080647 DOI: 10.1117/1.nph.11.3.033408] [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: 12/05/2023] [Revised: 03/01/2024] [Accepted: 03/05/2024] [Indexed: 05/12/2024]
Abstract
Significance The initiation of goal-directed actions is a complex process involving the medial prefrontal cortex and dopaminergic inputs through the mesocortical pathway. However, it is unclear what information the mesocortical pathway conveys and how it impacts action initiation. In this study, we unveiled the indispensable role of mesocortical axon terminals in encoding the execution of movements in self-initiated actions. Aim To investigate the role of mesocortical axon terminals in encoding the execution of movements in self-initiated actions. Approach We designed a lever-press task in which mice internally determine the timing of the press, receiving a larger reward for longer waiting periods. Results Our study revealed that self-initiated actions depend on dopaminergic signaling mediated by D2 receptors, whereas sensory-triggered lever-press actions do not involve D2 signaling. Microprism-mediated two-photon calcium imaging further demonstrated ramping activity in mesocortical axon terminals approximately 0.5 s before the self-initiated lever press. Remarkably, the ramping patterns remained consistent whether the mice responded to cues immediately for a smaller reward or held their response for a larger reward. Conclusions We conclude that mesocortical dopamine axon terminals encode the timing of self-initiated actions, shedding light on a crucial aspect of the intricate neural mechanisms governing goal-directed behavior.
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Affiliation(s)
- Makoto Ohtake
- Medical University of South Carolina, Department of Neuroscience, Charleston, South Carolina, United States
- Yokohama City University, Department of Neurosurgery, Yokohama, Japan
| | - Kenta Abe
- Medical University of South Carolina, Department of Neuroscience, Charleston, South Carolina, United States
| | - Masashi Hasegawa
- Rutgers, The State University of New Jersey, Robert Wood Johnson Medical School, Center for Advanced Biotechnology and Medicine, Department of Neuroscience and Cell Biology, Piscataway, New Jersey, United States
| | - Takahide Itokazu
- Osaka University, Department of Neuro-Medical Science, Osaka, Japan
| | - Vihashini Selvakumar
- Medical University of South Carolina, Department of Neuroscience, Charleston, South Carolina, United States
| | - Ashley Matunis
- Medical University of South Carolina, Department of Neuroscience, Charleston, South Carolina, United States
- College of Charleston, Department of Biology, Charleston, South Carolina, United States
| | - Emma Stacy
- Medical University of South Carolina, Department of Neuroscience, Charleston, South Carolina, United States
- College of Charleston, Department of Biology, Charleston, South Carolina, United States
| | - Emily Froebrich
- Medical University of South Carolina, Department of Neuroscience, Charleston, South Carolina, United States
- College of Charleston, Department of Biology, Charleston, South Carolina, United States
| | - Nathan Huynh
- Kagoshima University, Department of Pharmacology, Kagoshima, Japan
| | - Haesuk Lee
- Kagoshima University, Department of Pharmacology, Kagoshima, Japan
| | - Yuki Kambe
- Kagoshima University, Department of Pharmacology, Kagoshima, Japan
| | - Tetsuya Yamamoto
- Yokohama City University, Department of Neurosurgery, Yokohama, Japan
| | - Tatsuo K. Sato
- Kagoshima University, Department of Pharmacology, Kagoshima, Japan
- FOREST, Japan Science and Technology Agency, Saitama, Japan
| | - Takashi R. Sato
- Medical University of South Carolina, Department of Neuroscience, Charleston, South Carolina, United States
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2
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Ambrad Giovannetti E, Rancz E. Behind mouse eyes: The function and control of eye movements in mice. Neurosci Biobehav Rev 2024; 161:105671. [PMID: 38604571 DOI: 10.1016/j.neubiorev.2024.105671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 03/12/2024] [Accepted: 04/08/2024] [Indexed: 04/13/2024]
Abstract
The mouse visual system has become the most popular model to study the cellular and circuit mechanisms of sensory processing. However, the importance of eye movements only started to be appreciated recently. Eye movements provide a basis for predictive sensing and deliver insights into various brain functions and dysfunctions. A plethora of knowledge on the central control of eye movements and their role in perception and behaviour arose from work on primates. However, an overview of various eye movements in mice and a comparison to primates is missing. Here, we review the eye movement types described to date in mice and compare them to those observed in primates. We discuss the central neuronal mechanisms for their generation and control. Furthermore, we review the mounting literature on eye movements in mice during head-fixed and freely moving behaviours. Finally, we highlight gaps in our understanding and suggest future directions for research.
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Affiliation(s)
| | - Ede Rancz
- INMED, INSERM, Aix-Marseille University, Marseille, France.
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3
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Vafaii H, Mandino F, Desrosiers-Grégoire G, O'Connor D, Markicevic M, Shen X, Ge X, Herman P, Hyder F, Papademetris X, Chakravarty M, Crair MC, Constable RT, Lake EMR, Pessoa L. Multimodal measures of spontaneous brain activity reveal both common and divergent patterns of cortical functional organization. Nat Commun 2024; 15:229. [PMID: 38172111 PMCID: PMC10764905 DOI: 10.1038/s41467-023-44363-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Accepted: 12/11/2023] [Indexed: 01/05/2024] Open
Abstract
Large-scale functional networks have been characterized in both rodent and human brains, typically by analyzing fMRI-BOLD signals. However, the relationship between fMRI-BOLD and underlying neural activity is complex and incompletely understood, which poses challenges to interpreting network organization obtained using this technique. Additionally, most work has assumed a disjoint functional network organization (i.e., brain regions belong to one and only one network). Here, we employ wide-field Ca2+ imaging simultaneously with fMRI-BOLD in mice expressing GCaMP6f in excitatory neurons. We determine cortical networks discovered by each modality using a mixed-membership algorithm to test the hypothesis that functional networks exhibit overlapping organization. We find that there is considerable network overlap (both modalities) in addition to disjoint organization. Our results show that multiple BOLD networks are detected via Ca2+ signals, and networks determined by low-frequency Ca2+ signals are only modestly more similar to BOLD networks. In addition, the principal gradient of functional connectivity is nearly identical for BOLD and Ca2+ signals. Despite similarities, important differences are also detected across modalities, such as in measures of functional connectivity strength and diversity. In conclusion, Ca2+ imaging uncovers overlapping functional cortical organization in the mouse that reflects several, but not all, properties observed with fMRI-BOLD signals.
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Affiliation(s)
- Hadi Vafaii
- Department of Physics, University of Maryland, College Park, MD, 20742, USA.
| | - Francesca Mandino
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Gabriel Desrosiers-Grégoire
- Computional Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC, H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, H3A 0G4, Canada
| | - David O'Connor
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
| | - Marija Markicevic
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xinxin Ge
- Department of Physiology, School of Medicine, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Peter Herman
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Fahmeed Hyder
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xenophon Papademetris
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
- Section of Biomedical Informatics & Data Science, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Mallar Chakravarty
- Computional Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC, H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, H3A 0G4, Canada
- Department of Psychiatry, McGill University, Montreal, QC, H3A 0G4, Canada
- Department of Biological and Biomedical Engineering, McGill University, Montreal, QC, H3A 0G4, Canada
| | - Michael C Crair
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA
- Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT, 06510, USA
| | - R Todd Constable
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Evelyn M R Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA.
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA.
| | - Luiz Pessoa
- Department of Psychology, University of Maryland, College Park, MD, 20742, USA.
- Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, 20742, USA.
- Maryland Neuroimaging Center, University of Maryland, College Park, MD, 20742, USA.
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4
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Vafaii H, Mandino F, Desrosiers-Grégoire G, O’Connor D, Shen X, Ge X, Herman P, Hyder F, Papademetris X, Chakravarty M, Crair MC, Constable RT, Lake EMR, Pessoa L. Multimodal measures of spontaneous brain activity reveal both common and divergent patterns of cortical functional organization. RESEARCH SQUARE 2023:rs.3.rs-2823802. [PMID: 37162818 PMCID: PMC10168440 DOI: 10.21203/rs.3.rs-2823802/v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Large-scale functional networks have been characterized in both rodent and human brains, typically by analyzing fMRI-BOLD signals. However, the relationship between fMRI-BOLD and underlying neural activity is complex and incompletely understood, which poses challenges to interpreting network organization obtained using this technique. Additionally, most work has assumed a disjoint functional network organization (i.e., brain regions belong to one and only one network). Here, we employed wide-field Ca2+ imaging simultaneously with fMRI-BOLD in mice expressing GCaMP6f in excitatory neurons. We determined cortical networks discovered by each modality using a mixed-membership algorithm to test the hypothesis that functional networks are overlapping rather than disjoint. Our results show that multiple BOLD networks are detected via Ca2+ signals; there is considerable network overlap (both modalities); networks determined by low-frequency Ca2+ signals are only modestly more similar to BOLD networks; and, despite similarities, important differences are detected across modalities (e.g., brain region "network diversity"). In conclusion, Ca2+ imaging uncovered overlapping functional cortical organization in the mouse that reflected several, but not all, properties observed with fMRI-BOLD signals.
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Affiliation(s)
- Hadi Vafaii
- Department of Physics, University of Maryland, College Park, MD, 20742, USA
| | - Francesca Mandino
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Gabriel Desrosiers-Grégoire
- Comp. Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health Univ. Institute, Montreal, QC, H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, H3A 0G4, Canada
| | - David O’Connor
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06511, USA
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xinxin Ge
- Department of Physiology, School of Medicine, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Peter Herman
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Fahmeed Hyder
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Xenophon Papademetris
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
| | - Mallar Chakravarty
- Comp. Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health Univ. Institute, Montreal, QC, H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, H3A 0G4, Canada
- Department of Psychiatry, McGill University, Montreal, QC, H3A 0G4, Canada
- Department of Biological and Biomedical Engineering, McGill University, Montreal, QC, H3A 0G4, Canada
| | - Michael C. Crair
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT, 06510, USA
- Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT, 06510, USA
| | - R. Todd Constable
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06511, USA
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Evelyn MR. Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Luiz Pessoa
- Department of Psychology, University of Maryland, College Park, MD, 20742, USA
- Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, 20742, USA
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5
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Osaki H, Kanaya M, Ueta Y, Miyata M. Distinct nociception processing in the dysgranular and barrel regions of the mouse somatosensory cortex. Nat Commun 2022; 13:3622. [PMID: 35768422 PMCID: PMC9243138 DOI: 10.1038/s41467-022-31272-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 06/07/2022] [Indexed: 11/23/2022] Open
Abstract
Nociception, a somatic discriminative aspect of pain, is, like touch, represented in the primary somatosensory cortex (S1), but the separation and interaction of the two modalities within S1 remain unclear. Here, we show spatially distinct tactile and nociceptive processing in the granular barrel field (BF) and adjacent dysgranular region (Dys) in mouse S1. Simultaneous recordings of the multiunit activity across subregions revealed that Dys neurons are more responsive to noxious input, whereas BF neurons prefer tactile input. At the single neuron level, nociceptive information is represented separately from the tactile information in Dys layer 2/3. In contrast, both modalities seem to converge on individual layer 5 neurons of each region, but to a different extent. Overall, these findings show layer-specific processing of nociceptive and tactile information between Dys and BF. We further demonstrated that Dys activity, but not BF activity, is critically involved in pain-like behavior. These findings provide new insights into the role of pain processing in S1. The processing of nociception in the somatosensory cortex (S1) has yet to be fully understood. Here, the authors demonstrate that the dysgranular region in S1 has an affinity for nociception and is critically involved in pain-like behavior.
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Affiliation(s)
- Hironobu Osaki
- Division of Neurophysiology, Department of Physiology, Graduate School of Medicine, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan. .,Laboratory of Functional Brain Circuit Construction, Graduate School of Brain Science, Doshisha University, Kyotanabe, Kyoto, Japan.
| | - Moeko Kanaya
- Division of Neurophysiology, Department of Physiology, Graduate School of Medicine, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan
| | - Yoshifumi Ueta
- Division of Neurophysiology, Department of Physiology, Graduate School of Medicine, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan
| | - Mariko Miyata
- Division of Neurophysiology, Department of Physiology, Graduate School of Medicine, Tokyo Women's Medical University, Shinjuku, Tokyo, Japan.
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6
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Leow YN, Zhou B, Sullivan HA, Barlowe AR, Wickersham IR, Sur M. Brain-wide mapping of inputs to the mouse lateral posterior (LP/Pulvinar) thalamus-anterior cingulate cortex network. J Comp Neurol 2022; 530:1992-2013. [PMID: 35383929 PMCID: PMC9167239 DOI: 10.1002/cne.25317] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 02/24/2022] [Accepted: 03/01/2022] [Indexed: 01/29/2023]
Abstract
The rodent homolog of the primate pulvinar, the lateral posterior (LP) thalamus, is extensively interconnected with multiple cortical areas. While these cortical interactions can span the entire LP, subdivisions of the LP are characterized by differential connections with specific cortical regions. In particular, the medial LP has reciprocal connections with frontoparietal cortical areas, including the anterior cingulate cortex (ACC). The ACC plays an integral role in top‐down sensory processing and attentional regulation, likely exerting some of these functions via the LP. However, little is known about how ACC and LP interact, and about the information potentially integrated in this reciprocal network. Here, we address this gap by employing a projection‐specific monosynaptic rabies tracing strategy to delineate brain‐wide inputs to bottom‐up LP→ACC and top‐down ACC→LP neurons. We find that LP→ACC neurons receive inputs from widespread cortical regions, including primary and higher order sensory and motor cortical areas. LP→ACC neurons also receive extensive subcortical inputs, particularly from the intermediate and deep layers of the superior colliculus (SC). Sensory inputs to ACC→LP neurons largely arise from visual cortical areas. In addition, ACC→LP neurons integrate cross‐hemispheric prefrontal cortex inputs as well as inputs from higher order medial cortex. Our brain‐wide anatomical mapping of inputs to the reciprocal LP‐ACC pathways provides a roadmap for understanding how LP and ACC communicate different sources of information to mediate attentional control and visuomotor functions.
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Affiliation(s)
- Yi Ning Leow
- Department of Brain and Cognitive Sciences, Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Blake Zhou
- Department of Brain and Cognitive Sciences, Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Heather A Sullivan
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Alexandria R Barlowe
- Department of Brain and Cognitive Sciences, Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Ian R Wickersham
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Mriganka Sur
- Department of Brain and Cognitive Sciences, Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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7
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Ishii D, Osaki H, Yozu A, Ishibashi K, Kawamura K, Yamamoto S, Miyata M, Kohno Y. Ipsilesional spatial bias after a focal cerebral infarction in the medial agranular cortex: A mouse model of unilateral spatial neglect. Behav Brain Res 2020; 401:113097. [PMID: 33385423 DOI: 10.1016/j.bbr.2020.113097] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 12/22/2020] [Accepted: 12/22/2020] [Indexed: 10/22/2022]
Abstract
Unilateral spatial neglect is a disorder of higher brain function that occurs after a brain injury, such as stroke, traumatic brain injury, brain tumor, and surgical procedures etc., and leads to failure to attend or respond to stimuli presented to the side contralateral to the lesioned cerebral hemisphere. Because patients with this condition often have other symptoms due to the presence of several brain lesions, it is difficult to evaluate the recovery mechanisms and effect of training on unilateral spatial neglect. In this study, a mouse model of unilateral spatial neglect was created to investigate whether the size of the lesion is related to the severity of ipsilesional spatial bias and the recovery process. Focal infarction was induced in the right medial agranular cortex (AGm) of mice via photothrombosis. After induction of cerebral infarction, ipsilesional spatial bias was evaluated for 9 consecutive days. The major findings were as follows: (1) unilateral local infarction of the AGm resulted in ipsilateral bias during internally guided decision-making; (2) the lesion size was correlated with the degree of impairment rather than slight differences in the lesion site; and (3) mice with anterior AGm lesions experienced lower recovery rates. These findings suggest that recovery from ipsilesional spatial bias requires neural plasticity within the anterior AGm. This conditional mouse model of ipsilesional spatial bias may be used to develop effective treatments for unilateral spatial neglect in humans.
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Affiliation(s)
- Daisuke Ishii
- Center for Medical Sciences, Ibaraki Prefectural University of Health Sciences, Ibaraki, Japan; Department of Cognitive Behavioral Physiology, Chiba University Graduate School of Medicine, Chiba, Japan.
| | - Hironobu Osaki
- Department of Physiology (Neurophysiology), School of Medicine, Tokyo Women's Medical University, Tokyo, Japan
| | - Arito Yozu
- Center for Medical Sciences, Ibaraki Prefectural University of Health Sciences, Ibaraki, Japan; Department of Precision Engineering, The University of Tokyo, Tokyo, Japan
| | - Kiyoshige Ishibashi
- Department of Physical Therapy, Ibaraki Prefectural University of Health Sciences Hospital, Ibaraki, Japan
| | - Kenta Kawamura
- Department of Physical Therapy, Ibaraki Prefectural University of Health Sciences, Ibaraki, Japan
| | - Satoshi Yamamoto
- Department of Physical Therapy, Ibaraki Prefectural University of Health Sciences, Ibaraki, Japan
| | - Mariko Miyata
- Department of Physiology (Neurophysiology), School of Medicine, Tokyo Women's Medical University, Tokyo, Japan
| | - Yutaka Kohno
- Center for Medical Sciences, Ibaraki Prefectural University of Health Sciences, Ibaraki, Japan
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8
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Yang JH, Kwan AC. Secondary motor cortex: Broadcasting and biasing animal's decisions through long-range circuits. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2020; 158:443-470. [PMID: 33785155 PMCID: PMC8190828 DOI: 10.1016/bs.irn.2020.11.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Medial secondary motor cortex (MOs or M2) constitutes the dorsal aspect of the rodent medial frontal cortex. We previously proposed that the function of MOs is to link antecedent conditions, including sensory stimuli and prior choices, to impending actions. In this review, we focus on the long-range pathways between MOs and other cortical and subcortical regions. We highlight three circuits: (1) connections with visual and auditory cortices that are essential for predictive coding of perceptual inputs; (2) connections with motor cortex and brainstem that are responsible for top-down, context-dependent modulation of movements; (3) connections with retrosplenial cortex, orbitofrontal cortex, and basal ganglia that facilitate reward-based learning. Together, these long-range circuits allow MOs to broadcast choice signals for feedback and to bias decision-making processes.
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Affiliation(s)
- Jen-Hau Yang
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Alex C Kwan
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States; Department of Neuroscience, Yale University School of Medicine, New Haven, CT, United States.
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9
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Hagihara KM, Ishikawa AW, Yoshimura Y, Tagawa Y, Ohki K. Long-Range Interhemispheric Projection Neurons Show Biased Response Properties and Fine-Scale Local Subnetworks in Mouse Visual Cortex. Cereb Cortex 2020; 31:1307-1315. [PMID: 33063102 DOI: 10.1093/cercor/bhaa297] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Revised: 08/20/2020] [Accepted: 09/08/2020] [Indexed: 12/24/2022] Open
Abstract
Integration of information processed separately in distributed brain regions is essential for brain functions. This integration is enabled by long-range projection neurons, and further, concerted interactions between long-range projections and local microcircuits are crucial. It is not well known, however, how this interaction is implemented in cortical circuits. Here, to decipher this logic, using callosal projection neurons (CPNs) in layer 2/3 of the mouse visual cortex as a model of long-range projections, we found that CPNs exhibited distinct response properties and fine-scale local connectivity patterns. In vivo 2-photon calcium imaging revealed that CPNs showed a higher ipsilateral (to their somata) eye preference, and that CPN pairs showed stronger signal/noise correlation than random pairs. Slice recordings showed CPNs were preferentially connected to CPNs, demonstrating the existence of projection target-dependent fine-scale subnetworks. Collectively, our results suggest that long-range projection target predicts response properties and local connectivity of cortical projection neurons.
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Affiliation(s)
- Kenta M Hagihara
- Department of Molecular Physiology, Kyushu University Graduate School of Medical Sciences, Fukuoka 812-8582, Japan.,Friedrich Miescher Institute for Biomedical Research, Basel 4058, Switzerland
| | - Ayako Wendy Ishikawa
- Division of Visual Information Processing, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki 444-8585, Japan.,Department of Physiological Sciences, The Graduate University for Advanced Studies, Okazaki 444-8585, Japan.,Keio University School of Medicine, Shinanomachi, Shinjuku-ku, 160-8582, Japan
| | - Yumiko Yoshimura
- Division of Visual Information Processing, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki 444-8585, Japan.,Department of Physiological Sciences, The Graduate University for Advanced Studies, Okazaki 444-8585, Japan
| | - Yoshiaki Tagawa
- Department of Biophysics, Kyoto University Graduate School of Science, Kyoto 606-8502, Japan.,Department of Physiology, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima 890-8544, Japan.,CREST, Japan Science and Technology Agency, Kawaguchi, Saitama 332-0012, Japan
| | - Kenichi Ohki
- Department of Molecular Physiology, Kyushu University Graduate School of Medical Sciences, Fukuoka 812-8582, Japan.,CREST, Japan Science and Technology Agency, Kawaguchi, Saitama 332-0012, Japan.,Department of Physiology, The University of Tokyo School of Medicine, Tokyo 113-0033, Japan.,International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo School of Medicine, Tokyo 113-0033, Japan.,Institute for AI and Beyond, The University of Tokyo School of Medicine, Tokyo 113-0033, Japan
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