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Miyashita Y. Cortical Layer-Dependent Signaling in Cognition: Three Computational Modes of the Canonical Circuit. Annu Rev Neurosci 2024; 47:211-234. [PMID: 39115926 DOI: 10.1146/annurev-neuro-081623-091311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/10/2024]
Abstract
The cerebral cortex performs computations via numerous six-layer modules. The operational dynamics of these modules were studied primarily in early sensory cortices using bottom-up computation for response selectivity as a model, which has been recently revolutionized by genetic approaches in mice. However, cognitive processes such as recall and imagery require top-down generative computation. The question of whether the layered module operates similarly in top-down generative processing as in bottom-up sensory processing has become testable by advances in the layer identification of recorded neurons in behaving monkeys. This review examines recent advances in laminar signaling in these two computations, using predictive coding computation as a common reference, and shows that each of these computations recruits distinct laminar circuits, particularly in layer 5, depending on the cognitive demands. These findings highlight many open questions, including how different interareal feedback pathways, originating from and terminating at different layers, convey distinct functional signals.
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Affiliation(s)
- Yasushi Miyashita
- Department of Physiology, The University of Tokyo School of Medicine, Tokyo, Japan;
- Juntendo University Graduate School of Medicine, Tokyo, Japan
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Liu Z, Li A, Gong H, Yang X, Luo Q, Feng Z, Li X. The cytoarchitectonic landscape revealed by deep learning method facilitated precise positioning in mouse neocortex. Cereb Cortex 2024; 34:bhae229. [PMID: 38836835 DOI: 10.1093/cercor/bhae229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 05/13/2024] [Accepted: 05/23/2024] [Indexed: 06/06/2024] Open
Abstract
Neocortex is a complex structure with different cortical sublayers and regions. However, the precise positioning of cortical regions can be challenging due to the absence of distinct landmarks without special preparation. To address this challenge, we developed a cytoarchitectonic landmark identification pipeline. The fluorescence micro-optical sectioning tomography method was employed to image the whole mouse brain stained by general fluorescent nucleotide dye. A fast 3D convolution network was subsequently utilized to segment neuronal somas in entire neocortex. By approach, the cortical cytoarchitectonic profile and the neuronal morphology were analyzed in 3D, eliminating the influence of section angle. And the distribution maps were generated that visualized the number of neurons across diverse morphological types, revealing the cytoarchitectonic landscape which characterizes the landmarks of cortical regions, especially the typical signal pattern of barrel cortex. Furthermore, the cortical regions of various ages were aligned using the generated cytoarchitectonic landmarks suggesting the structural changes of barrel cortex during the aging process. Moreover, we observed the spatiotemporally gradient distributions of spindly neurons, concentrated in the deep layer of primary visual area, with their proportion decreased over time. These findings could improve structural understanding of neocortex, paving the way for further exploration with this method.
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Affiliation(s)
- Zhixiang Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, No. 1037 Luoyu Road, Wuhan 430070, China
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, No. 1037 Luoyu Road, Wuhan 430070, China
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, No. 58 Renmin Road, Haikou 570228, China
- HUST-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, No. 388 Ruoshui Road, Suzhou 215000, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, No. 1037 Luoyu Road, Wuhan 430070, China
- HUST-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, No. 388 Ruoshui Road, Suzhou 215000, China
| | - Xiaoquan Yang
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, No. 58 Renmin Road, Haikou 570228, China
- HUST-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, No. 388 Ruoshui Road, Suzhou 215000, China
| | - Qingming Luo
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, No. 58 Renmin Road, Haikou 570228, China
| | - Zhao Feng
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, No. 58 Renmin Road, Haikou 570228, China
- HUST-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, No. 388 Ruoshui Road, Suzhou 215000, China
| | - Xiangning Li
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, No. 58 Renmin Road, Haikou 570228, China
- HUST-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, No. 388 Ruoshui Road, Suzhou 215000, China
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Packer JM, Bray CE, Beckman NB, Wangler LM, Davis AC, Goodman EJ, Klingele NE, Godbout JP. Impaired cortical neuronal homeostasis and cognition after diffuse traumatic brain injury are dependent on microglia and type I interferon responses. Glia 2024; 72:300-321. [PMID: 37937831 PMCID: PMC10764078 DOI: 10.1002/glia.24475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 09/14/2023] [Accepted: 09/20/2023] [Indexed: 11/09/2023]
Abstract
Neuropsychiatric complications including depression and cognitive decline develop in the years after traumatic brain injury (TBI), negatively affecting quality of life. Microglial and type 1 interferon (IFN-I) responses are associated with the transition from acute to chronic neuroinflammation after diffuse TBI in mice. Thus, the purpose of this study was to determine if impaired neuronal homeostasis and increased IFN-I responses intersected after TBI to cause cognitive impairment. Here, the RNA profile of neurons and microglia after TBI (single nucleus RNA-sequencing) with or without microglia depletion (CSF1R antagonist) was assessed 7 dpi. There was a TBI-dependent suppression of cortical neuronal homeostasis with reductions in CREB signaling, synaptogenesis, and synaptic migration and increases in RhoGDI and PTEN signaling (Ingenuity Pathway Analysis). Microglial depletion reversed 50% of TBI-induced gene changes in cortical neurons depending on subtype. Moreover, the microglial RNA signature 7 dpi was associated with increased stimulator of interferon genes (STING) activation and IFN-I responses. Therefore, we sought to reduce IFN-I signaling after TBI using STING knockout mice and a STING antagonist, chloroquine (CQ). TBI-associated cognitive deficits in novel object location and recognition (NOL/NOR) tasks at 7 and 30 dpi were STING dependent. In addition, TBI-induced STING expression, microglial morphological restructuring, inflammatory (Tnf, Cd68, Ccl2) and IFN-related (Irf3, Irf7, Ifi27) gene expression in the cortex were attenuated in STINGKO mice. CQ also reversed TBI-induced cognitive deficits and reduced TBI-induced inflammatory (Tnf, Cd68, Ccl2) and IFN (Irf7, Sting) cortical gene expression. Collectively, reducing IFN-I signaling after TBI with STING-dependent interventions attenuated the prolonged microglial activation and cognitive impairment.
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Affiliation(s)
- Jonathan M Packer
- Department of Neuroscience, The Ohio State University, Columbus, Ohio, USA
- Institute for Behavioral Medicine Research, The Ohio State University, Columbus, Ohio, USA
| | - Chelsea E Bray
- College of Medicine, The Ohio State University, Columbus, United States
| | - Nicolas B Beckman
- Institute for Behavioral Medicine Research, The Ohio State University, Columbus, Ohio, USA
| | - Lynde M Wangler
- Department of Neuroscience, The Ohio State University, Columbus, Ohio, USA
- Institute for Behavioral Medicine Research, The Ohio State University, Columbus, Ohio, USA
| | - Amara C Davis
- Department of Neuroscience, The Ohio State University, Columbus, Ohio, USA
- Institute for Behavioral Medicine Research, The Ohio State University, Columbus, Ohio, USA
| | - Ethan J Goodman
- Department of Neuroscience, The Ohio State University, Columbus, Ohio, USA
- Institute for Behavioral Medicine Research, The Ohio State University, Columbus, Ohio, USA
| | - Nathaniel E Klingele
- Institute for Behavioral Medicine Research, The Ohio State University, Columbus, Ohio, USA
| | - Jonathan P Godbout
- Department of Neuroscience, The Ohio State University, Columbus, Ohio, USA
- Institute for Behavioral Medicine Research, The Ohio State University, Columbus, Ohio, USA
- College of Medicine, The Ohio State University, Columbus, United States
- Chronic Brain Injury Program, The Ohio State University, Columbus, Ohio, USA
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Petanjek Z, Banovac I, Sedmak D, Hladnik A. Dendritic Spines: Synaptogenesis and Synaptic Pruning for the Developmental Organization of Brain Circuits. ADVANCES IN NEUROBIOLOGY 2023; 34:143-221. [PMID: 37962796 DOI: 10.1007/978-3-031-36159-3_4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Synaptic overproduction and elimination is a regular developmental event in the mammalian brain. In the cerebral cortex, synaptic overproduction is almost exclusively correlated with glutamatergic synapses located on dendritic spines. Therefore, analysis of changes in spine density on different parts of the dendritic tree in identified classes of principal neurons could provide insight into developmental reorganization of specific microcircuits.The activity-dependent stabilization and selective elimination of the initially overproduced synapses is a major mechanism for generating diversity of neural connections beyond their genetic determination. The largest number of overproduced synapses was found in the monkey and human cerebral cortex. The highest (exceeding adult values by two- to threefold) and most protracted overproduction (up to third decade of life) was described for associative layer IIIC pyramidal neurons in the human dorsolateral prefrontal cortex.Therefore, the highest proportion and extraordinarily extended phase of synaptic spine overproduction is a hallmark of neural circuitry in human higher-order associative areas. This indicates that microcircuits processing the most complex human cognitive functions have the highest level of developmental plasticity. This finding is the backbone for understanding the effect of environmental impact on the development of the most complex, human-specific cognitive and emotional capacities, and on the late onset of human-specific neuropsychiatric disorders, such as autism and schizophrenia.
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Affiliation(s)
- Zdravko Petanjek
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia.
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia.
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia.
| | - Ivan Banovac
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Dora Sedmak
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Ana Hladnik
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
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Barbas H, Zikopoulos B, John YJ. The inevitable inequality of cortical columns. Front Syst Neurosci 2022; 16:921468. [PMID: 36203745 PMCID: PMC9532056 DOI: 10.3389/fnsys.2022.921468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 09/01/2022] [Indexed: 11/13/2022] Open
Abstract
The idea of columns as an organizing cortical unit emerged from physiologic studies in the sensory systems. Connectional studies and molecular markers pointed to widespread presence of modular label that necessitated revision of the classical concept of columns. The general principle of cortical systematic variation in laminar structure is at the core of cortical organization. Systematic variation can be traced to the phylogenetically ancient limbic cortices, which have the simplest laminar structure, and continues through eulaminate cortices that show sequential elaboration of their six layers. Connections are governed by relational rules, whereby columns or modules with a vertical organization represent the feedforward mode of communication from earlier- to later processing cortices. Conversely, feedback connections are laminar-based and connect later- with earlier processing areas; both patterns are established in development. Based on studies in primates, the columnar/modular pattern of communication appears to be newer in evolution, while the broadly based laminar pattern represents an older system. The graded variation of cortices entails a rich variety of patterns of connections into modules, layers, and mixed arrangements as the laminar and modular patterns of communication intersect in the cortex. This framework suggests an ordered architecture poised to facilitate seamless recruitment of areas in behavior, in patterns that are affected in diseases of developmental origin.
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Affiliation(s)
- Helen Barbas
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, MA, United States
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
- Graduate Program in Neuroscience, Boston University and School of Medicine, Boston, MA, United States
- *Correspondence: Helen Barbas,
| | - Basilis Zikopoulos
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
- Graduate Program in Neuroscience, Boston University and School of Medicine, Boston, MA, United States
- Human Systems Neuroscience Laboratory, Department of Health Sciences, Boston University, Boston, MA, United States
| | - Yohan J. John
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, MA, United States
- Graduate Program in Neuroscience, Boston University and School of Medicine, Boston, MA, United States
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Miyamoto K, Setsuie R, Miyashita Y. Conversion of concept-specific decision confidence into integrative introspection in primates. Cell Rep 2022; 38:110581. [PMID: 35354028 DOI: 10.1016/j.celrep.2022.110581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 12/21/2021] [Accepted: 03/07/2022] [Indexed: 11/26/2022] Open
Abstract
Introspection based on the integration of uncertain evidence is critical for acting upon abstract thinking and imagining future scenarios. However, it is unknown how confidence read-outs from multiple sources of different concepts are integrated, especially considering the relationships among the concepts. In this study, monkeys performed wagering based on an estimation of their performance in a preceding mnemonic decision. We found that the longer the response times for post-decision wagering, the more relieved the impairments having been caused by frontal disruption. This suggests the existence of a time-consuming compensatory metacognitive process. We found posterior inferior parietal lobe (pIPL) as its candidate, which was not coding the wagering per se (i.e., just high bet or low bet), but became more active when monkeys successfully chose the optimal bet option based on mnemonic decision performance. Thereafter, the pIPL prompts dorsal anterior cingulate cortex to carry the chosen wagering option. Our findings suggest a role for the pIPL in metacognitive concept integration.
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Affiliation(s)
- Kentaro Miyamoto
- Department of Physiology, The University of Tokyo School of Medicine, Bunkyo-ku, Tokyo 113-0033, Japan; Juntendo University, Graduate School of Medicine, Bunkyo-ku, Tokyo 113-8421, Japan; Department of Experimental Psychology, University of Oxford, Oxford, OXON OX1 3TA, UK; Laboratory for Imagination and Executive Functions, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan.
| | - Rieko Setsuie
- Department of Physiology, The University of Tokyo School of Medicine, Bunkyo-ku, Tokyo 113-0033, Japan; Juntendo University, Graduate School of Medicine, Bunkyo-ku, Tokyo 113-8421, Japan; Laboratory for Cognition Circuit Dynamics, RIKEN Center for Brain Science, Wako-shi, Saitama 351-0198, Japan; Brain Functional Dynamics Collaboration Laboratory, RIKEN Center for Brain Science, Wako-shi, Saitama 351-0198, Japan
| | - Yasushi Miyashita
- Department of Physiology, The University of Tokyo School of Medicine, Bunkyo-ku, Tokyo 113-0033, Japan; Juntendo University, Graduate School of Medicine, Bunkyo-ku, Tokyo 113-8421, Japan; Laboratory for Cognition Circuit Dynamics, RIKEN Center for Brain Science, Wako-shi, Saitama 351-0198, Japan
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