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Cai X, Xu H, Han C, Li P, Wang J, Zhang R, Tang R, Fang C, Yan K, Song Q, Liang C, Lu HD. Mesoscale functional connectivity in macaque visual areas. Neuroimage 2023; 271:120019. [PMID: 36914108 DOI: 10.1016/j.neuroimage.2023.120019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 03/07/2023] [Accepted: 03/10/2023] [Indexed: 03/13/2023] Open
Abstract
Studies of resting-state functional connectivity (rsFC) have provided rich insights into the structures and functions of the human brain. However, most rsFC studies have focused on large-scale brain connectivity. To explore rsFC at a finer scale, we used intrinsic signal optical imaging to image the ongoing activity of the anesthetized macaque visual cortex. Differential signals from functional domains were used to quantify network-specific fluctuations. In 30-60 min resting-state imaging, a series of coherent activation patterns were observed in all three visual areas we examined (V1, V2, and V4). These patterns matched the known functional maps (ocular dominance, orientation, color) obtained in visual stimulation conditions. These functional connectivity (FC) networks fluctuated independently over time and exhibited similar temporal characteristics. Coherent fluctuations, however, were observed from orientation FC networks in different areas and even across two hemispheres. Thus, FC in the macaque visual cortex was fully mapped both on a fine scale and over a long range. Hemodynamic signals can be used to explore mesoscale rsFC in a submillimeter resolution.
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Affiliation(s)
- Xingya Cai
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xin Jie Kou Wai Street, Beijing 100875, China
| | - Haoran Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xin Jie Kou Wai Street, Beijing 100875, China
| | - Chao Han
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xin Jie Kou Wai Street, Beijing 100875, China
| | - Peichao Li
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xin Jie Kou Wai Street, Beijing 100875, China
| | - Jiayu Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xin Jie Kou Wai Street, Beijing 100875, China
| | - Rui Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xin Jie Kou Wai Street, Beijing 100875, China
| | - Rendong Tang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xin Jie Kou Wai Street, Beijing 100875, China
| | - Chen Fang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xin Jie Kou Wai Street, Beijing 100875, China
| | - Kun Yan
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xin Jie Kou Wai Street, Beijing 100875, China
| | - Qianling Song
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xin Jie Kou Wai Street, Beijing 100875, China
| | - Chen Liang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xin Jie Kou Wai Street, Beijing 100875, China
| | - Haidong D Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xin Jie Kou Wai Street, Beijing 100875, China.
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Lu HD, Xie JL, Zhang LN, Zheng YY, Zhou XG. [Clinicopathological features of angioimmunoblastic T-cell lymphoma pattern Ⅰ]. Zhonghua Bing Li Xue Za Zhi 2022; 51:856-860. [PMID: 36097902 DOI: 10.3760/cma.j.cn112151-20211222-00925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Objective: To investigate the clinicopathological features of angioimmunoblastic T-cell lymphoma pattern Ⅰ (AITL Pattern Ⅰ). Methods: The clinicopathological data of 11 AITL Pattern Ⅰ cases that were diagnosed at the Beijing Friendship Hospital Affiliated to Capital Medical University (10 cases) and Beijing Lu Daopei Hospital (1 cases) from January 2019 to October 2021 were retrospectively collected. Immunophenotype, Epstein-Barr virus infection status and T cell receptor (TCR) clonality of the tumor cells were tested, and clinicopathological features of cases were analyzed. Results: Among the 11 AITL Pattern Ⅰ cases, the male to female ratio was 1.2∶1.0. The median age was 59 years (range 47-78 years). Seven cases had B symptoms, while eleven cases presented with systemic lymphadenopathy. According to Ann Arbor system staging, two cases were classified as stage Ⅰ-Ⅱ, and 9 cases as stage Ⅲ-Ⅳ. Hepatosplenomegaly was present in two cases (2/11), three cases (3/11) had skin rash and pruritus, and two cases (2/11) had pleural effusion. Previously, 6 cases (6/11) were diagnosed as reactive hyperplasia, 1 case (1/11) as EBV-associated lymphoproliferative disorder, and 4 cases (4/11) as hyperplasia of lymphoid tissue, which was unable to exclude lymphoma. Histologically, all the 11 cases showed hyperplastic follicles in the paracortical regions with well-formed germinal centers. The hyperplastic follicles showed ill-defined borders and attenuated mantle zones in 7 cases. Mantle zones completely disappeared in 4 cases. The follicles were surrounded by a thin layer of atypical lymphocytes with bright or faintly stained cytoplasm. In 2 cases, the clear cells were located between the germinal centers and the thin residual mantle cell layers, showing a circular growth pattern. The cells were medium in size, with irregular karyotype, coarse chromatin and indistinct nucleoli. Immunohistochemically, CD21 staining showed that the meshworks of follicular dendritic cells(FDC)were mainly confined to the follicles. There was a subtle expansion of the meshworks of FDC in 4 cases with ill-defined borders. The atypical cells surrounding the follicles expressed CD3 (11/11), CD4 (11/11), PD-1 (11/11), CXCL13 (6/11), ICOS (10/11) and CD10 (7/11). PD-1 staining showed a strong perifollicular pattern, and a small number of positive cells were scattered around the high endothelial veins in the interfollicular region. CXCL13, ICOS and CD10 showed similar distribution patterns. EBV-encoded small RNA probe (EBER) in situ hybridization showed that EBER positive B lymphocytes were scattered in the interfollicular region (5-20/HPF) in all cases. T cell receptor gene rearrangement was monoclonal in all cases. Conclusions: Diagnosing AITL Pattern Ⅰ may be challenging and requires comprehensive analysis of clinical manifestations, histological morphology, immunophenotype and gene rearrangement results.
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Affiliation(s)
- H D Lu
- Department of Pathology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - J L Xie
- Department of Pathology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - L N Zhang
- Department of Pathology, Beijing Lu Daopei Hospital, Beijing 100176, China
| | - Y Y Zheng
- Department of Pathology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - X G Zhou
- Department of Pathology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
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Shen L, Tian XJ, Liang RZ, Cheng Y, Kong XL, He F, Zhang C, Wang GA, Li SH, Lu HD, Sun SQ. [Clinical and imaging features of Chlamydia psittaci pneumonia: an analysis of 48 cases in China]. Zhonghua Jie He He Hu Xi Za Zhi 2021; 44:886-891. [PMID: 34565115 DOI: 10.3760/cma.j.cn112147-20210127-00082] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To explore the clinical characteristics, imaging findings, laboratory tests and treatment strategies for Chlamydia psittaci pneumonia. Methods: From January 1, 2019 to January 20, 2021, 48 cases of Psittacosis from 11 hospitals in China were diagnosed via metagenomic next-generation sequencing(mNGS). The data of all patients on occupational history, clinical manifestations, laboratory tests, chest computed tomography(CT)findings, treatment outcomes and prognosis were retrospectively analyzed. Results: Among the 48 patients, there were 29 males and 19 females, with a mean age of (57.1±10.3) years. Thirty patients had a confirmed history of exposure to poultry. The onset to admission interval was (6.5±3.2) days, and hospital stay was (12.4±4.8) days. Clinical manifestations included fever (100%, 48/48), relative bradycardia (71%, 34/48), cough (54.2%, 26/48), sputum (27.1%, 13/48), fatigue (16.7%, 8/48), headache and delirium (20.8%, 9/48), and gastrointestinal symptoms (16.7%, 8/48). Laboratory data showed that white blood cells were (8.0±3.8)×109/L, and the proportion of neutrophils increased in 44 patients. The level of C-reactive protein was (155.3±74.1)mg/L, and that of procalcitonin (PCT)in 59.5% of patients was more than 0.5 μg/L. Percentages of patients with increased lactate dehydrogenase and creatine kinase were 82.9% and 45.2%, respectively. Chest CT scans showed unilateral lung involvement in 34 cases(70.8%) and single lobe involvement in 27 cases(56.3%).The most common imaging change was consolidation, with 38 cases (79.2%) showing lobar consolidation. In terms of treatment, 25 patients were treated with fluoroquinolones alone, 6 patients with doxycycline alone, and 13 patients with combined treatment. The combined-treatment group and the doxycycline alone group were similar in the course of defervescence. The combined treatment group and the doxycycline alone group were both superior to the fluoroquinolones alone group. However, 11 patients were admitted to ICU, all of them received artificial ventilation, and 5 cases developed shock, and one died. Conclusions: Chlamydia psittaci pneumonia is an animal-derived infectious disease with unique features in clinical symptoms, laboratory tests and chest imaging. Appropriate treatment is able to significantly shorten the course of disease and improve the prognosis.
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Affiliation(s)
- L Shen
- Department of Pulmonary and Critical Care Medicine, Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou 310006, China
| | - X J Tian
- Department of Infectious Disease, the First People's Hospital of Xiaoshan District, Hangzhou 311201, China
| | - R Z Liang
- Department of Pulmonary and Critical Care Medicine, the First Hospital of Longyan Affiliated to Fujian Medical University, Longyan 364000, Fujian Province, China
| | - Y Cheng
- Department of Infectious Diseases, Hunan University of Traditional Medicine Affiliated Ningxiang People's Hospital, Ningxiang 410600, Hunan Province, China
| | - X L Kong
- Department of Pulmonary and Critical Care Medicine, Changsha First Hospital, Changsha 410005, China
| | - F He
- Department of Pulmonary and Critical Care Medicine, Affiliated Hangzhou Chest Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - C Zhang
- Institute of Respiratory Disease, China Three Gorges University, Yichang Central People's Hospital, Yichang 443003, Hubei Province, China
| | - G A Wang
- Department of Pulmonary and Critical Care Medicine, Ningbo Medical Center Li Huili Hospital, Ningbo 315040, China
| | - S H Li
- Department of Pulmonary Medicine, Hangzhou Ninth People's Hospital, Hangzhou 311225, China
| | - H D Lu
- Department of Respiratory and Critical Care, Huzhou Central Hospital, Huzhou 313000, Zhejiang Province, China
| | - S Q Sun
- Department of General Medicine, Nanjing Second Hospital, Nanjing 210003, China
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Gu S, Lu HD, Xie JW, Chen J, Fan XS, Xu J. [Computational pathology and its contributions to precision medicine]. Zhonghua Bing Li Xue Za Zhi 2021; 50:851-855. [PMID: 34344065 DOI: 10.3760/cma.j.cn112151-20201130-00878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- S Gu
- Institute for AI in Medicine & School of Automation, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - H D Lu
- Institute for AI in Medicine & School of Automation, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - J W Xie
- Institute for AI in Medicine & School of Automation, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - J Chen
- Department of Pathology, Nanjing Drum Tower Hospital, Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, China
| | - X S Fan
- Department of Pathology, Nanjing Drum Tower Hospital, Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, China
| | - J Xu
- Institute for AI in Medicine & School of Automation, Nanjing University of Information Science and Technology, Nanjing 210044, China
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Abstract
Human and nonhuman primates are good at identifying an object based on its motion, a task that is believed to be carried out by the ventral visual pathway. However, the neural mechanisms underlying such ability remains unclear. We trained macaque monkeys to do orientation discrimination for motion boundaries (MBs) and recorded neuronal response in area V2 with microelectrode arrays. We found 10.9% of V2 neurons exhibited robust orientation selectivity to MBs, and their responses correlated with monkeys' orientation-discrimination performances. Furthermore, the responses of V2 direction-selective neurons recorded at the same time showed correlated activity with MB neurons for particular MB stimuli, suggesting that these motion-sensitive neurons made specific functional contributions to MB discrimination tasks. Our findings support the view that V2 plays a critical role in MB analysis and may achieve this through a neural circuit within area V2.
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Affiliation(s)
- Heng Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Pengcheng Li
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jiaming Hu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xingya Cai
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qianling Song
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Haidong D Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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Abstract
Neurons in primate V4 exhibit various types of selectivity for contour shapes, including curves, angles, and simple shapes. How are these neurons organized in V4 remains unclear. Using intrinsic signal optical imaging and two-photon calcium imaging, we observed submillimeter functional domains in V4 that contained neurons preferring curved contours over rectilinear ones. These curvature domains had similar sizes and response amplitudes as orientation domains but tended to separate from these regions. Within the curvature domains, neurons that preferred circles or curve orientations clustered further into finer scale subdomains. Nevertheless, individual neurons also had a wide range of contour selectivity, and neighboring neurons exhibited a substantial diversity in shape tuning besides their common shape preferences. In strong contrast to V4, V1 and V2 did not have such contour-shape-related domains. These findings highlight the importance and complexity of curvature processing in visual object recognition and the key functional role of V4 in this process.
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Affiliation(s)
- Rendong Tang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/MGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qianling Song
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/MGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ying Li
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/MGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Rui Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/MGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xingya Cai
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/MGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Haidong D Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/MGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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Hu J, Ma H, Zhu S, Li P, Xu H, Fang Y, Chen M, Han C, Fang C, Cai X, Yan K, Lu HD. Visual Motion Processing in Macaque V2. Cell Rep 2020; 25:157-167.e5. [PMID: 30282025 DOI: 10.1016/j.celrep.2018.09.014] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Revised: 07/05/2018] [Accepted: 09/06/2018] [Indexed: 11/26/2022] Open
Abstract
In the primate visual system, direction-selective (DS) neurons are critical for visual motion perception. While DS neurons in the dorsal visual pathway have been well characterized, the response properties of DS neurons in other major visual areas are largely unexplored. Recent optical imaging studies in monkey visual cortex area 2 (V2) revealed clusters of DS neurons. This imaging method facilitates targeted recordings from these neurons. Using optical imaging and single-cell recording, we characterized detailed response properties of DS neurons in macaque V2. Compared with DS neurons in the dorsal areas (e.g., middle temporal area [MT]), V2 DS neurons have a smaller receptive field and a stronger antagonistic surround. They do not code speed or plaid motion but are sensitive to motion contrast. Our results suggest that V2 DS neurons play an important role in figure-ground segregation. The clusters of V2 DS neurons are likely specialized functional systems for detecting motion contrast.
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Affiliation(s)
- Jiaming Hu
- Institute of Neuroscience, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai 200031, China; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Interdisciplinary Institute of Neuroscience and Technology, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou 310027, China
| | - Heng Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Shude Zhu
- Institute of Neuroscience, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai 200031, China; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Peichao Li
- Institute of Neuroscience, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai 200031, China; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Haoran Xu
- Institute of Neuroscience, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai 200031, China; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Yang Fang
- Institute of Neuroscience, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai 200031, China; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Ming Chen
- Institute of Neuroscience, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai 200031, China; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Chao Han
- Institute of Neuroscience, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai 200031, China; State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Chen Fang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Xingya Cai
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Kun Yan
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Haidong D Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Interdisciplinary Institute of Neuroscience and Technology, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou 310027, China.
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Fang Y, Chen M, Xu H, Li P, Han C, Hu J, Zhu S, Ma H, Lu HD. An Orientation Map for Disparity-Defined Edges in Area V4. Cereb Cortex 2018; 29:666-679. [DOI: 10.1093/cercor/bhx348] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2017] [Indexed: 11/14/2022] Open
Affiliation(s)
- Yang Fang
- Institute of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai, China
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and the Collaborative Innovation Center for Brain Science, Beijing Normal University, Beijing, China
| | - Ming Chen
- Institute of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai, China
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and the Collaborative Innovation Center for Brain Science, Beijing Normal University, Beijing, China
| | - Haoran Xu
- Institute of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai, China
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and the Collaborative Innovation Center for Brain Science, Beijing Normal University, Beijing, China
| | - Peichao Li
- Institute of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai, China
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and the Collaborative Innovation Center for Brain Science, Beijing Normal University, Beijing, China
| | - Chao Han
- Institute of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai, China
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and the Collaborative Innovation Center for Brain Science, Beijing Normal University, Beijing, China
| | - Jiaming Hu
- Institute of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai, China
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and the Collaborative Innovation Center for Brain Science, Beijing Normal University, Beijing, China
| | - Shude Zhu
- Institute of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai, China
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and the Collaborative Innovation Center for Brain Science, Beijing Normal University, Beijing, China
| | - Heng Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and the Collaborative Innovation Center for Brain Science, Beijing Normal University, Beijing, China
| | - Haidong D Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, and the Collaborative Innovation Center for Brain Science, Beijing Normal University, Beijing, China
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Abstract
Stereoscopic vision depends on correct matching of corresponding features between the two eyes. It is unclear where the brain solves this binocular correspondence problem. Although our visual system is able to make correct global matches, there are many possible false matches between any two images. Here, we use optical imaging data of binocular disparity response in the visual cortex of awake and anesthetized monkeys to demonstrate that the second visual cortical area (V2) is the first cortical stage that correctly discards false matches and robustly encodes correct matches. Our findings indicate that a key transformation for achieving depth perception lies in early stages of extrastriate visual cortex and is achieved by population coding.
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Affiliation(s)
- Gang Chen
- Interdisciplinary Institute of Neuroscience and Technology, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou 310029, China;
- College of Biomedical Engineering and Instrument Science, Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou 310027, China
- School of Medicine, Zhejiang University, Hangzhou 310058, China
- College of Biomedical Engineering and Instrument Science, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou 310027, China
- Department of Psychology, Vanderbilt University, Nashville, TN 37203
| | - Haidong D Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Hisashi Tanigawa
- Interdisciplinary Institute of Neuroscience and Technology, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou 310029, China
- Department of Physiology, Niigata University, School of Medicine, Chuo-ku, Niigata 951-8510, Japan
| | - Anna W Roe
- Interdisciplinary Institute of Neuroscience and Technology, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou 310029, China
- College of Biomedical Engineering and Instrument Science, Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou 310027, China
- School of Medicine, Zhejiang University, Hangzhou 310058, China
- College of Biomedical Engineering and Instrument Science, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou 310027, China
- Department of Psychology, Vanderbilt University, Nashville, TN 37203
- Division of Neuroscience, Oregon National Primate Research Center, Oregon Health & Science University, Beaverton, OR 97006
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10
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Wang B, Ke W, Guang J, Chen G, Yin L, Deng S, He Q, Liu Y, He T, Zheng R, Jiang Y, Zhang X, Li T, Luan G, Lu HD, Zhang M, Zhang X, Shu Y. Firing Frequency Maxima of Fast-Spiking Neurons in Human, Monkey, and Mouse Neocortex. Front Cell Neurosci 2016; 10:239. [PMID: 27803650 PMCID: PMC5067378 DOI: 10.3389/fncel.2016.00239] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2016] [Accepted: 09/30/2016] [Indexed: 12/13/2022] Open
Abstract
Cortical fast-spiking (FS) neurons generate high-frequency action potentials (APs) without apparent frequency accommodation, thus providing fast and precise inhibition. However, the maximal firing frequency that they can reach, particularly in primate neocortex, remains unclear. Here, by recording in human, monkey, and mouse neocortical slices, we revealed that FS neurons in human association cortices (mostly temporal) could generate APs at a maximal mean frequency (Fmean) of 338 Hz and a maximal instantaneous frequency (Finst) of 453 Hz, and they increase with age. The maximal firing frequency of FS neurons in the association cortices (frontal and temporal) of monkey was even higher (Fmean 450 Hz, Finst 611 Hz), whereas in the association cortex (entorhinal) of mouse it was much lower (Fmean 215 Hz, Finst 342 Hz). Moreover, FS neurons in mouse primary visual cortex (V1) could fire at higher frequencies (Fmean 415 Hz, Finst 582 Hz) than those in association cortex. We further validated our in vitro data by examining spikes of putative FS neurons in behaving monkey and mouse. Together, our results demonstrate that the maximal firing frequency of FS neurons varies between species and cortical areas.
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Affiliation(s)
- Bo Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, School of Brain and Cognitive Sciences, The Collaborative Innovation Center for Brain Science, Beijing Normal UniversityBeijing, China; Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of SciencesShanghai, China
| | - Wei Ke
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, School of Brain and Cognitive Sciences, The Collaborative Innovation Center for Brain Science, Beijing Normal University Beijing, China
| | - Jing Guang
- Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences Shanghai, China
| | - Guang Chen
- Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences Shanghai, China
| | - Luping Yin
- Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences Shanghai, China
| | - Suixin Deng
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, School of Brain and Cognitive Sciences, The Collaborative Innovation Center for Brain Science, Beijing Normal University Beijing, China
| | - Quansheng He
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, School of Brain and Cognitive Sciences, The Collaborative Innovation Center for Brain Science, Beijing Normal University Beijing, China
| | - Yaping Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, School of Brain and Cognitive Sciences, The Collaborative Innovation Center for Brain Science, Beijing Normal University Beijing, China
| | - Ting He
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, School of Brain and Cognitive Sciences, The Collaborative Innovation Center for Brain Science, Beijing Normal University Beijing, China
| | - Rui Zheng
- Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences Shanghai, China
| | - Yanbo Jiang
- Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences Shanghai, China
| | - Xiaoxue Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, School of Brain and Cognitive Sciences, The Collaborative Innovation Center for Brain Science, Beijing Normal University Beijing, China
| | - Tianfu Li
- Department of Neurosurgery, Brain Institute, and Department of Neurology, Epilepsy Center, Beijing Sanbo Brain Hospital, Capital Medical University Beijing, China
| | - Guoming Luan
- Department of Neurosurgery, Brain Institute, and Department of Neurology, Epilepsy Center, Beijing Sanbo Brain Hospital, Capital Medical University Beijing, China
| | - Haidong D Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, School of Brain and Cognitive Sciences, The Collaborative Innovation Center for Brain Science, Beijing Normal University Beijing, China
| | - Mingsha Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, School of Brain and Cognitive Sciences, The Collaborative Innovation Center for Brain Science, Beijing Normal University Beijing, China
| | - Xiaohui Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, School of Brain and Cognitive Sciences, The Collaborative Innovation Center for Brain Science, Beijing Normal University Beijing, China
| | - Yousheng Shu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, School of Brain and Cognitive Sciences, The Collaborative Innovation Center for Brain Science, Beijing Normal University Beijing, China
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11
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Abstract
The ability to extract the shape of moving objects is fundamental to visual perception. However, where such computations are processed in the visual system is unknown. To address this question, we used intrinsic signal optical imaging in awake monkeys to examine cortical response to perceptual contours defined by motion contrast (motion boundaries, MBs). We found that MB stimuli elicit a robust orientation response in area V2. Orientation maps derived from subtraction of orthogonal MB stimuli aligned well with the orientation maps obtained with luminance gratings (LGs). In contrast, area V1 responded well to LGs, but exhibited a much weaker orientation response to MBs. We further show that V2 direction domains respond to motion contrast, which is required in the detection of MB in V2. These results suggest that V2 represents MB information, an important prerequisite for shape recognition and figure-ground segregation.
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Affiliation(s)
- Ming Chen
- Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Peichao Li
- Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Shude Zhu
- Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Chao Han
- Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Haoran Xu
- Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Yang Fang
- Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Jiaming Hu
- Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Anna W Roe
- Department of Psychology, Vanderbilt University, Nashville, TN 37203, USA
| | - Haidong D Lu
- Institute of Neuroscience and State Key Laboratory of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, and University of Chinese Academy of Sciences, Shanghai 200031, China.,State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
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12
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Rasch MJ, Chen M, Wu S, Lu HD, Roe AW. Quantitative inference of population response properties across eccentricity from motion-induced maps in macaque V1. J Neurophysiol 2012. [PMID: 23197457 DOI: 10.1152/jn.00673.2012] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Interpreting population responses in the primary visual cortex (V1) remains a challenge especially with the advent of techniques measuring activations of large cortical areas simultaneously with high precision. For successful interpretation, a quantitatively precise model prediction is of great importance. In this study, we investigate how accurate a spatiotemporal filter (STF) model predicts average response profiles to coherently drifting random dot motion obtained by optical imaging of intrinsic signals in V1 of anesthetized macaques. We establish that orientation difference maps, obtained by subtracting orthogonal axis-of-motion, invert with increasing drift speeds, consistent with the motion streak effect. Consistent with perception, the speed at which the map inverts (the critical speed) depends on cortical eccentricity and systematically increases from foveal to parafoveal. We report that critical speeds and response maps to drifting motion are excellently reproduced by the STF model. Our study thus suggests that the STF model is quantitatively accurate enough to be used as a first model of choice for interpreting responses obtained with intrinsic imaging methods in V1. We show further that this good quantitative correspondence opens the possibility to infer otherwise not easily accessible population receptive field properties from responses to complex stimuli, such as drifting random dot motions.
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Affiliation(s)
- Malte J Rasch
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal Univ, Beijing, China.
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13
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Abstract
In mammals, the perception of motion starts with direction-selective neurons in the visual cortex. Despite numerous studies in monkey primary and second visual cortex (V1 and V2), there has been no evidence of direction maps in these areas. In the present study, we used optical imaging methods to study the organization of motion response in macaque V1 and V2. In contrast to the findings in other mammals (e.g., cats and ferrets), we found no direction maps in macaque V1. Robust direction maps, however, were found in V2 thick/pale stripes and avoided thin stripes. In many cases direction maps were located within thick stripes and exhibited pinwheel or linear organizations. The presence of motion maps in V2 points to a newfound prominence of V2 in motion processing, for contributing to motion perception in the dorsal pathway and/or for motion cue-dependent form perception in the ventral pathway.
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Affiliation(s)
- Haidong D Lu
- Department of Psychology, Vanderbilt University, Nashville, TN 37240, USA.
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14
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Kaskan PM, Dillenburger BC, Lu HD, Roe AW, Kaas JH. Orientation and Direction-of-Motion Response in the Middle Temporal Visual Area (MT) of New World Owl Monkeys as Revealed by Intrinsic-Signal Optical Imaging. Front Neuroanat 2010; 4:23. [PMID: 20661299 PMCID: PMC2906256 DOI: 10.3389/fnana.2010.00023] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2010] [Accepted: 05/12/2010] [Indexed: 11/30/2022] Open
Abstract
Intrinsic-signal optical imaging was used to evaluate relationships of domains of neurons in middle temporal visual area (MT) selective for stimulus orientation and direction-of-motion. Maps of activation were elicited in MT of owl monkeys by gratings drifting back-and-forth, flashed stationary gratings and unidirectionally drifting fields of random dots. Drifting gratings, typically used to reveal orientation preference domains, contain a motion component that may be represented in MT. Consequently, this stimulus could activate groups of cells responsive to the motion of the grating, its orientation or a combination of both. Domains elicited from either moving or static gratings were remarkably similar, indicating that these groups of cells are responding to orientation, although they may also encode information about motion. To assess the relationship between domains defined by drifting oriented gratings and those responsive to direction-of-motion, the response to drifting fields of random dots was measured within domains defined from thresholded maps of activation elicited by the drifting gratings. The optical response elicited by drifting fields of random dots was maximal in a direction orthogonal to the map of orientation preference. Thus, neurons in domains selective for stimulus orientation are also selective for motion orthogonal to the preferred stimulus orientation.
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Affiliation(s)
- Peter M Kaskan
- Department of Psychology, Vanderbilt University Nashville, TN, USA
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15
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Lu HD, Chen G, Ts'o DY, Roe AW. A rapid topographic mapping and eye alignment method using optical imaging in Macaque visual cortex. Neuroimage 2008; 44:636-46. [PMID: 19013530 DOI: 10.1016/j.neuroimage.2008.10.007] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2007] [Revised: 06/10/2008] [Accepted: 10/06/2008] [Indexed: 10/21/2022] Open
Abstract
In optical imaging experiments, it is often advantageous to map the field of view and to converge the eyes without electrophysiological recording. This occurs when limited space precludes placement of an electrode or in chronic optical chambers in which one may not want to introduce an electrode each session or for determining eye position in studies of ocular disparity response in visual cortex of anesthetized animals. For these purposes, we have developed a spot imaging method that can be conducted rapidly and repeatedly throughout an experiment. Using small 0.2 degrees -0.5 degrees spots, the extent of the imaged field of view is mapped by imaging cortical response to single spots, placed at different positions (0.2 degrees steps) in either the horizontal or vertical axes. By shifting the relative positions of two spots, one presented to each eye, eye convergence can be assessed to within 0.1 degrees resolution. Once appropriate eye alignment is determined, stimuli for further optical imaging procedures (e.g. imaging random dot stimuli for study of disparity responses) can then be confidently placed. This procedure can be quickly repeated throughout the experiment to ensure maintained eye alignment.
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Affiliation(s)
- H D Lu
- Dept of Psychology, 301 Wilson Hall, Vanderbilt University, Nashville, TN 37212, USA
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16
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Kaskan PM, Lu HD, Dillenburger BC, Kaas JH, Roe AW. The organization of orientation-selective, luminance-change and binocular- preference domains in the second (V2) and third (V3) visual areas of New World owl monkeys as revealed by intrinsic signal optical imaging. ACTA ACUST UNITED AC 2008; 19:1394-407. [PMID: 18842661 DOI: 10.1093/cercor/bhn178] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Optical imaging was used to map patterns of visually evoked activation in the second (V2) and third (V3) visual areas of owl monkeys. Modular patterns of activation were produced in response to stimulation with oriented gratings, binocular versus monocular stimulation, and stimuli containing wide-field luminance changes. In V2, luminance-change domains tended to lie between domains selective for orientation. Regions preferentially activated by binocular stimulation co-registered with orientation-selective domains. Co-alignment of images with cytochrome oxidase (CO)-processed sections revealed functional correlates of 2 types of CO-dense regions in V2. Orientation-responsive domains and binocular domains were correlated with the locations of CO-thick stripes, and luminance-change domains were correlated with the locations of CO-thin stripes. In V3, orientation preference, luminance-change, and binocular preference domains were observed, but were more irregularly arranged than those in V2. Our data suggest that in owl monkey V2, consistent with that in macaque monkeys, modules for processing contours and binocularity exist in one type of compartment and that modules related to processing-surface features exist within a separate type of compartment.
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Affiliation(s)
- Peter M Kaskan
- Department of Psychology, Vanderbilt University, Nashville, TN 37203, USA.
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17
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Abstract
The perception of visual depth is determined by integration of spatial disparities of inputs from the two eyes. Single cells in visual cortex of monkeys are known to respond to specific binocular disparities; however, little is known about their functional organization. We now show, using intrinsic signal optical imaging and single-unit physiology, that, in the thick stripe compartments of the second visual area (V2), there is a clustered organization of Near cells and Far cells, and moreover, there are topographic maps for Near to Far disparities within V2. Our findings suggest that maps for visual disparity are calculated in V2, and demonstrate parallels in functional organization between the thin, pale, and thick stripes of V2.
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Affiliation(s)
- Gang Chen
- Department of Psychology, Vanderbilt University, Nashville, TN 37203, USA
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18
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Kaskan PM, Lu HD, Dillenburger BC, Roe AW, Kaas JH. Intrinsic-signal optical imaging reveals cryptic ocular dominance columns in primary visual cortex of new world owl monkeys. Front Neurosci 2007; 1:67-75. [PMID: 18974855 PMCID: PMC2518048 DOI: 10.3389/neuro.01.1.1.005.2007] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
A significant concept in neuroscience is that sensory areas of the neocortex have evolved the remarkable ability to represent a number of stimulus features within the confines of a global map of the sensory periphery. Modularity, the term often used to describe the inhomogeneous nature of the neocortex, is without a doubt an important organizational principle of early sensory areas, such as the primary visual cortex (V1). Ocular dominance columns, one type of module in V1, are found in many primate species as well as in carnivores. Yet, their variable presence in some New World monkey species and complete absence in other species has been enigmatic. Here, we demonstrate that optical imaging reveals the presence of ocular dominance columns in the superficial layers of V1 of owl monkeys (Aotus trivirgatus), even though the geniculate inputs related to each eye are highly overlapping in layer 4. The ocular dominance columns in owl monkeys revealed by optical imaging are circular in appearance. The distance between left eye centers and right eye centers is approximately 650 μm. We find no relationship between ocular dominance centers and other modular organizational features such as orientation pinwheels or the centers of the cytochrome oxidase blobs. These results are significant because they suggest that functional columns may exist in the absence of obvious differences in the distributions of activating inputs and ocular dominance columns may be more widely distributed across mammalian taxa than commonly suggested.
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Affiliation(s)
- Peter M Kaskan
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
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19
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Kaskan PM, Lu HD, Dillenburger BC, Roe AW, Kaas JH. Intrinsic-signal optical imaging reveals cryptic ocular dominance columns in primary visual cortex of New World owl monkeys. Front Neurosci 2007. [PMID: 18974855 PMCID: PMC2518048 DOI: 10.3389/neuro.01/1.1.005.2007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
A significant concept in neuroscience is that sensory areas of the neocortex have evolved the remarkable ability to represent a number of stimulus features within the confines of a global map of the sensory periphery. Modularity, the term often used to describe the inhomogeneous nature of the neocortex, is without a doubt an important organizational principle of early sensory areas, such as the primary visual cortex (V1). Ocular dominance columns, one type of module in V1, are found in many primate species as well as in carnivores. Yet, their variable presence in some New World monkey species and complete absence in other species has been enigmatic. Here, we demonstrate that optical imaging reveals the presence of ocular dominance columns in the superficial layers of V1 of owl monkeys (Aotus trivirgatus), even though the geniculate inputs related to each eye are highly overlapping in layer 4. The ocular dominance columns in owl monkeys revealed by optical imaging are circular in appearance. The distance between left eye centers and right eye centers is approximately 650 mum. We find no relationship between ocular dominance centers and other modular organizational features such as orientation pinwheels or the centers of the cytochrome oxidase blobs. These results are significant because they suggest that functional columns may exist in the absence of obvious differences in the distributions of activating inputs and ocular dominance columns may be more widely distributed across mammalian taxa than commonly suggested.
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Affiliation(s)
- Peter M. Kaskan
- Department of Psychology, Vanderbilt University, Nashville, TNUSA
| | - Haidong D. Lu
- Department of Psychology, Vanderbilt University, Nashville, TNUSA
| | | | - Anna W. Roe
- Department of Psychology, Vanderbilt University, Nashville, TNUSA
| | - Jon H. Kaas
- Department of Psychology, Vanderbilt University, Nashville, TNUSA,*Correspondence: Department of Psychology, Vanderbilt University, 301 Wilson Hall, 111 21st Avenue South, Nashville, TN 37203, USA
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20
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Abstract
Our studies on brightness information processing in Macaque monkey visual cortex suggest that the thin stripes in the secondary visual area (V2) are preferentially activated by brightness stimuli (such as full field luminance modulation and illusory edge-induced brightness modulation). To further examine this possibility, we used intrinsic signal optical imaging to examine contrast response of different functional domains in primary and secondary visual areas (V1 and V2). Color and orientation stimuli were used to map functional domains in V1 (color domains, orientation domains) and V2 (thin stripes, thick/pale stripes). To examine contrast response, sinusoidal gratings at different contrasts and spatial frequencies were presented. We find that, consistent with previous studies, the optical signal increased systematically with contrast level. Unlike single-unit responses, optical signals for both color domains and orientation domains in V1 exhibit linear contrast response functions, thereby providing a large dynamic range for V1 contrast response. In contrast to domains in V1, domains in V2 exhibit nonlinear responses, characterized by high gain at low contrasts, saturating at a mid-high contrast levels. At high contrasts, thin stripes exhibit increasing response, whereas thick/pale stripes saturate, consistent with a strong parvocellular input to thin stripes. These findings suggest that, with respect to contrast encoding, thin stripes have a larger dynamic range than thick/pale stripes and further support a role for thin stripes in processing of brightness information.
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Affiliation(s)
- Haidong D Lu
- Department of Psychology, Vanderbilt University, Nashville, TN 37203, USA.
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21
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Abstract
Several brightness illusions indicate that borders can affect the perception of surfaces dramatically. In the Cornsweet illusion, two equiluminant surfaces appear to be different in brightness because of the contrast border between them. Here, we report the existence of cells in monkey visual cortex that respond to such an "illusory" brightness. We find that luminance responsive cells are located in color-activated regions (cytochrome oxidase blobs and bridges) of primary visual cortex (V1), whereas Cornsweet responsive cells are found preferentially in the color-activated regions (thin stripes) of second visual area (V2). This colocalization of brightness and color processing within V1 and V2 suggests a segregation of contour and surface processing in early visual pathways and a hierarchy of brightness information processing from V1 to V2 in monkeys.
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Affiliation(s)
- Anna Wang Roe
- Department of Psychology, 301 Wilson Hall, Vanderbilt University, Nashville, TN 37203, USA.
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22
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Abstract
Tree shrews (Tupaia belangeri) are small diurnal mammals
capable of quick and agile navigation. Electroretinographic and
behavioral studies have indicated that tree shrews possess very good
temporal vision, but the neuronal mechanisms underlying that temporal
vision are not well understood. We used single-unit extracellular
recording techniques to characterize the temporal response properties
of individual retinal ganglion cell axons recorded from the optic
tract. A prominent characteristic of most cells was their sustained or
transient nature in responding to the flashing spot. Temporal
modulation sensitivity functions were obtained using a Gaussian spot
that was temporally modulated at different frequencies (2–60 Hz).
Sustained cells respond linearly to contrast. They showed an average
peak frequency of 6.9 Hz, a high-frequency cutoff at 31.3 Hz, and
low-pass filtering. Transient cells showed nonlinear response to
contrast. They had a peak frequency of 19.3 Hz, a high-frequency cutoff
at about 47.6 Hz, band-pass filtering, and higher overall sensitivity
than sustained cells. The responses of transient cells also showed a
phase advance of about 88 deg whereas the phase advance for sustained
cells was about 43 deg. Comparison with behavioral temporal modulation
sensitivity results suggested that transient retinal ganglion cells may
underlie detection for a wide range of temporal frequencies, with
sustained ganglion cells possibly mediating detection below 4 Hz. These
data suggest that two well-separated temporal channels exist at the
retinal ganglion cell level in the tree shrew retina, with the
transient channel playing a major role in temporal vision.
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Affiliation(s)
- Haidong D Lu
- Department of Psychological and Brain Sciences, University of Louisville, Louisville, KY 40292, USA
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23
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Xie XH, Lu HD, Wang L, Diao YC. [Integration of visual signals in the brain: mechanisms and functional significance of synchronous oscillation]. Sheng Li Ke Xue Jin Zhan 1997; 28:108-12. [PMID: 11038701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
How are the functions performed by one part of the nervous system integrated with those of others? One possible way is by synchronous oscillation. We have reviewed recent advances in visual system, where synchronous oscillations have been intensively observed and investigated. This article is concentrated on discussing theoretical reasoning, experimental evidence, possible mechanisms underlying the generation and the functional significance of visual synchronous oscillations. Predictions on several prosperous areas were also outlined.
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Affiliation(s)
- X H Xie
- Laboratory of Visual Information Processing, Academia Sinica, Beijing
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24
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Lu HD. [Some new technics in gynecology and obstetrics]. Zhonghua Hu Li Za Zhi 1984; 19:374-7. [PMID: 6399693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
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