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Shimaoka D, Wong YT, Rosa MG, Seow N, Price C. Naturalistic Movies and Encoding, Analysis Define Areal Borders in, Marmoset Third-Tier Visual Cortex. Prog Neurobiol 2024:102657. [PMID: 39103115 DOI: 10.1016/j.pneurobio.2024.102657] [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: 04/18/2024] [Revised: 06/24/2024] [Accepted: 07/30/2024] [Indexed: 08/07/2024]
Abstract
Accurate definition of the borders of cortical visual areas is essential for the study.of neuronal processes leading to perception. However, data used for definition of.areal boundaries have suffered from issues related to resolution, uniform.coverage, or suitability for objective analysis, leading to ambiguity. Here, we.present a novel approach that combines widefield optical imaging, presentation.of naturalistic movies, and encoding model analysis, to objectively define borders.in the primate extrastriate cortex. We applied this method to test conflicting.hypotheses about the third-tier visual cortex, where areal boundaries have.remained controversial. We demonstrate pronounced tuning preferences in the.third-tier areas, and an organizational structure in which the dorsomedial area.(DM) contains representations of both the upper and lower contralateral.quadrants, and is located immediate anterior to V2. High-density.electrophysiological recordings with a Neuropixels probe confirm these findings.Our encoding-model approach offers a powerful, objective way to disambiguate.areal boundaries….
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Affiliation(s)
- Daisuke Shimaoka
- Department of Physiology and Neuroscience Program, Biomedicine Discovery, Institute, Monash University, Clayton, Australia
| | - Yan Tat Wong
- Department of Physiology and Neuroscience Program, Biomedicine Discovery, Institute, Monash University, Clayton, Australia; Electrical and Computer Systems Engineering, Monash University, Clayton, Australia
| | - Marcello Gp Rosa
- Department of Physiology and Neuroscience Program, Biomedicine Discovery, Institute, Monash University, Clayton, Australia
| | - Nicholas Seow
- Department of Physiology and Neuroscience Program, Biomedicine Discovery, Institute, Monash University, Clayton, Australia; Electrical and Computer Systems Engineering, Monash University, Clayton, Australia
| | - Chiang Price
- Department of Physiology and Neuroscience Program, Biomedicine Discovery, Institute, Monash University, Clayton, Australia
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Ganglberger F, Kargl D, Töpfer M, Hernandez-Lallement J, Lawless N, Fernandez-Albert F, Haubensak W, Bühler K. BrainTACO: an explorable multi-scale multi-modal brain transcriptomic and connectivity data resource. Commun Biol 2024; 7:730. [PMID: 38877144 PMCID: PMC11178817 DOI: 10.1038/s42003-024-06355-7] [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: 04/27/2023] [Accepted: 05/20/2024] [Indexed: 06/16/2024] Open
Abstract
Exploring the relationships between genes and brain circuitry can be accelerated by joint analysis of heterogeneous datasets from 3D imaging data, anatomical data, as well as brain networks at varying scales, resolutions, and modalities. Generating an integrated view, beyond the individual resources' original purpose, requires the fusion of these data to a common space, and a visualization that bridges the gap across scales. However, despite ever expanding datasets, few platforms for integration and exploration of this heterogeneous data exist. To this end, we present the BrainTACO (Brain Transcriptomic And Connectivity Data) resource, a selection of heterogeneous, and multi-scale neurobiological data spatially mapped onto a common, hierarchical reference space, combined via a holistic data integration scheme. To access BrainTACO, we extended BrainTrawler, a web-based visual analytics framework for spatial neurobiological data, with comparative visualizations of multiple resources. This enables gene expression dissection of brain networks with, to the best of our knowledge, an unprecedented coverage and allows for the identification of potential genetic drivers of connectivity in both mice and humans that may contribute to the discovery of dysconnectivity phenotypes. Hence, BrainTACO reduces the need for time-consuming manual data aggregation often required for computational analyses in script-based toolboxes, and supports neuroscientists by directly leveraging the data instead of preparing it.
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Affiliation(s)
- Florian Ganglberger
- Biomedical Image Informatics, VRVis Research Center, Vienna, Austria
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma, Biberach an der Riss, Germany
| | - Dominic Kargl
- Department of Neuronal Cell Biology, Vienna Medical University, Vienna, Austria
| | - Markus Töpfer
- Biomedical Image Informatics, VRVis Research Center, Vienna, Austria
| | - Julien Hernandez-Lallement
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma, Biberach an der Riss, Germany
| | - Nathan Lawless
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma, Biberach an der Riss, Germany
| | - Francesc Fernandez-Albert
- Global Computational Biology and Digital Sciences, Boehringer Ingelheim Pharma, Biberach an der Riss, Germany
| | - Wulf Haubensak
- Department of Neuronal Cell Biology, Vienna Medical University, Vienna, Austria
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Vienna, Austria
| | - Katja Bühler
- Biomedical Image Informatics, VRVis Research Center, Vienna, Austria.
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Pedrosa LRR, Leal LCP, Muniz JAPC, Bastos CDO, Gomes BD, Krejcová LV. From imaging to precision: low cost and accurate determination of stereotactic coordinates for brain surgery Sapajus apella using MRI. Front Neurosci 2024; 18:1324669. [PMID: 38362021 PMCID: PMC10867132 DOI: 10.3389/fnins.2024.1324669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 01/17/2024] [Indexed: 02/17/2024] Open
Abstract
The capuchin monkey (Sapajus apella), a New World monkey species, exhibits prominent characteristics that make it an ideal model for neuroscience research. These characteristics include its phylogenetic traits, telencephalization coefficient, anatomical structures and pathways, genetic profile, immune responses, cognitive abilities, and complex behavioral repertoires. Traditionally, methodologies for stereotactic neurosurgery in research models have relied on the use of brain atlases. However, this approach can lead to errors due to the considerable variation in brain size and shape among individual monkeys. To address this issue, we developed a protocol for deriving individual coordinates for each monkey using a straightforward and relatively inexpensive method involving MRI imaging. Our protocol utilizes a specially designed, 3D-printed stereotactic head-holder that is safe to use with an MR magnet, non-invasive placement of fiducial markers, and post-processing with open-source software. This approach enhances MRI data visualization, improves anatomical targeting, and refines the design of neurosurgical experiments. Our technique could also prove beneficial in other areas of neuroscience research that require accurate calculation of stereotaxic coordinates. Furthermore, it could be useful for other nonhuman primate species for which brain atlases are typically unavailable.
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Affiliation(s)
| | - Leon C. P. Leal
- Institute of Biological Sciences, Federal University of Pará, Belém, Brazil
- National Primate Center, Institute Evandro Chagas, Ananindeua, Brazil
| | | | | | - Bruno D. Gomes
- Institute of Biological Sciences, Federal University of Pará, Belém, Brazil
| | - Lane V. Krejcová
- Institute of Biological Sciences, Federal University of Pará, Belém, Brazil
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Athey TL, Tward DJ, Mueller U, Younes L, Vogelstein JT, Miller MI. Preserving Derivative Information while Transforming Neuronal Curves. Neuroinformatics 2024; 22:63-74. [PMID: 38036915 PMCID: PMC10917852 DOI: 10.1007/s12021-023-09648-0] [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] [Accepted: 10/31/2023] [Indexed: 12/02/2023]
Abstract
The international neuroscience community is building the first comprehensive atlases of brain cell types to understand how the brain functions from a higher resolution, and more integrated perspective than ever before. In order to build these atlases, subsets of neurons (e.g. serotonergic neurons, prefrontal cortical neurons etc.) are traced in individual brain samples by placing points along dendrites and axons. Then, the traces are mapped to common coordinate systems by transforming the positions of their points, which neglects how the transformation bends the line segments in between. In this work, we apply the theory of jets to describe how to preserve derivatives of neuron traces up to any order. We provide a framework to compute possible error introduced by standard mapping methods, which involves the Jacobian of the mapping transformation. We show how our first order method improves mapping accuracy in both simulated and real neuron traces under random diffeomorphisms. Our method is freely available in our open-source Python package brainlit.
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Affiliation(s)
- Thomas L Athey
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
- Institute of Computational Medicine, Johns Hopkins University, Baltimore, MD, USA.
| | - Daniel J Tward
- Department of Computational Medicine, University of California at Los Angeles, Los Angeles, CA, USA
- Department of Neurology, University of California at Los Angeles, Los Angeles, CA, USA
| | - Ulrich Mueller
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA
| | - Laurent Younes
- Institute of Computational Medicine, Johns Hopkins University, Baltimore, MD, USA
- Department of Applied Mathematics & Statistics, Johns Hopkins University, Baltimore, MD, USA
- Center for Imaging Science, Johns Hopkins University, Baltimore, MD, USA
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, USA
| | - Joshua T Vogelstein
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Institute of Computational Medicine, Johns Hopkins University, Baltimore, MD, USA
- Center for Imaging Science, Johns Hopkins University, Baltimore, MD, USA
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, USA
| | - Michael I Miller
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Institute of Computational Medicine, Johns Hopkins University, Baltimore, MD, USA
- Center for Imaging Science, Johns Hopkins University, Baltimore, MD, USA
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD, USA
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Demirci N, Hoffman ME, Holland MA. Systematic cortical thickness and curvature patterns in primates. Neuroimage 2023; 278:120283. [PMID: 37516374 PMCID: PMC10443624 DOI: 10.1016/j.neuroimage.2023.120283] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 07/11/2023] [Accepted: 07/17/2023] [Indexed: 07/31/2023] Open
Abstract
Humans are known to have significant and consistent differences in thickness throughout the cortex, with thick outer gyral folds and thin inner sulcal folds. Our previous work has suggested a mechanical basis for this thickness pattern, with the forces generated during cortical folding leading to thick gyri and thin sulci, and shown that cortical thickness varies along a gyral-sulcal spectrum in humans. While other primate species are expected to exhibit similar patterns of cortical thickness, it is currently unknown how these patterns scale across different sizes, forms, and foldedness. Among primates, brains vary enormously from roughly the size of a grape to the size of a grapefruit, and from nearly smooth to dramatically folded; of these, human brains are the largest and most folded. These variations in size and form make comparative neuroanatomy a rich resource for investigating common trends that transcend differences between species. In this study, we examine 12 primate species in order to cover a wide range of sizes and forms, and investigate the scaling of their cortical thickness relative to the surface geometry. The 12 species were selected due to the public availability of either reconstructed surfaces and/or population templates. After obtaining or reconstructing 3D surfaces from publicly available neuroimaging data, we used our surface-based computational pipeline (https://github.com/mholla/curveball) to analyze patterns of cortical thickness and folding with respect to size (total surface area), geometry (i.e. curvature, shape, and sulcal depth), and foldedness (gyrification). In all 12 species, we found consistent cortical thickness variations along a gyral-sulcal spectrum, with convex shapes thicker than concave shapes and saddle shapes in between. Furthermore, we saw an increasing thickness difference between gyri and sulci as brain size increases. Our results suggest a systematic folding mechanism relating local cortical thickness to geometry. Finally, all of our reconstructed surfaces and morphometry data are available for future research in comparative neuroanatomy.
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Affiliation(s)
- Nagehan Demirci
- Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Mia E Hoffman
- Department of Mechanical Engineering, University of Washington, Seattle, WA 98195, USA; Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Maria A Holland
- Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN 46556, USA; Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA.
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Mahmoudian B, Dalal H, Lau J, Corrigan B, Abbas M, Barker K, Rankin A, Chen ECS, Peters T, Martinez-Trujillo JC. A method for chronic and semi-chronic microelectrode array implantation in deep brain structures using image guided neuronavigation. J Neurosci Methods 2023; 397:109948. [PMID: 37572883 DOI: 10.1016/j.jneumeth.2023.109948] [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: 05/16/2023] [Revised: 07/17/2023] [Accepted: 08/09/2023] [Indexed: 08/14/2023]
Abstract
BACKGROUND Accurate targeting of brain structures for in-vivo electrophysiological recordings is essential for basic as well as clinical neuroscience research. Although methodologies for precise targeting and recording from the cortical surface are abundant, such protocols are scarce for deep brain structures. NEW METHOD We have incorporated stable fiducial markers within a custom cranial cap for improved image-guided neuronavigation targeting of subcortical structures in macaque monkeys. Anchor bolt chambers allowed for a minimally invasive entrance into the brain for chronic recordings. A 3D-printed microdrive allowed for semi-chronic applications. RESULTS We achieved an average Euclidean targeting error of 1.6 mm and a radial error of 1.2 mm over three implantations in two animals. Chronic and semi-chronic implantations allowed for recording of extracellular neuronal activity, with single-neuron activity examples shown from one macaque monkey. COMPARISON WITH EXISTING METHOD(S) Traditional stereotactic methods ignore individual anatomical variability. Our targeting approach allows for a flexible, subject-specific surgical plan with targeting errors lower than what is reported in humans, and equal to or lower than animal models using similar methods. Utilizing an anchor bolt as a chamber reduced the craniotomy size needed for electrode implantation, compared to conventional large access chambers which are prone to infection. Installation of an in-house, 3D-printed, screw-to-mount mechanical microdrive is in contrast to existing semi-chronic methods requiring fabrication, assembly, and installation of complex parts. CONCLUSIONS Leveraging commercially available tools for implantation, our protocol decreases the risk of infection from open craniotomies, and improves the accuracy of chronic electrode implantations targeting deep brain structures in large animal models.
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Affiliation(s)
- Borna Mahmoudian
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Robarts Research Institute and Brain and Mind Institute, University of Western Ontario, 1151 Richmond St. N., London, ON N6A 5B7, Canada
| | - Hitarth Dalal
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Robarts Research Institute and Brain and Mind Institute, University of Western Ontario, 1151 Richmond St. N., London, ON N6A 5B7, Canada
| | - Jonathan Lau
- Department of Clinical Neurological Sciences, Division of Neurosurgery, London Health Sciences Centre, University of Western Ontario, 1151 Richmond St. N., London, ON N6A 5B7, Canada; School of Biomedical Engineering, University of Western Ontario, 1151 Richmond St. N., London, ON N6A 5B7, Canada; Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, 1151 Richmond St. N., London, ON N6A 5B7, Canada
| | - Benjamin Corrigan
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Robarts Research Institute and Brain and Mind Institute, University of Western Ontario, 1151 Richmond St. N., London, ON N6A 5B7, Canada
| | - Mohamad Abbas
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Robarts Research Institute and Brain and Mind Institute, University of Western Ontario, 1151 Richmond St. N., London, ON N6A 5B7, Canada; Department of Clinical Neurological Sciences, Division of Neurosurgery, London Health Sciences Centre, University of Western Ontario, 1151 Richmond St. N., London, ON N6A 5B7, Canada
| | | | - Adam Rankin
- Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, 1151 Richmond St. N., London, ON N6A 5B7, Canada
| | - Elvis C S Chen
- School of Biomedical Engineering, University of Western Ontario, 1151 Richmond St. N., London, ON N6A 5B7, Canada; Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, 1151 Richmond St. N., London, ON N6A 5B7, Canada; Department of Medical Biophysics, University of Western Ontario, 1151 Richmond St. N., London, ON N6A 5B7, Canada; Lawson Health Research Institute, 750 Base Line Road East Suite 300, London, ON N6C2R5, Canada; Department of Electrical and Computer Engineering, Thompson Engineering Building, University of Western Ontario, London, ON, N6A 5B9, Canada
| | - Terry Peters
- Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, 1151 Richmond St. N., London, ON N6A 5B7, Canada; Center for Functional and Metabolic Mapping, Robarts Research Institute, Department of Medical Biophysics and Brain and Mind Institute, University of Western Ontario, 1151 Richmond St. N., London, ON N6A 5B7, Canada
| | - Julio C Martinez-Trujillo
- Department of Physiology and Pharmacology, Schulich School of Medicine and Dentistry, Robarts Research Institute and Brain and Mind Institute, University of Western Ontario, 1151 Richmond St. N., London, ON N6A 5B7, Canada; Lawson Health Research Institute, 750 Base Line Road East Suite 300, London, ON N6C2R5, Canada.
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Cortical adaptation of the night monkey to a nocturnal niche environment: a comparative non-invasive T1w/T2w myelin study. Brain Struct Funct 2022:10.1007/s00429-022-02591-x. [PMID: 36399210 DOI: 10.1007/s00429-022-02591-x] [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: 05/31/2022] [Accepted: 10/25/2022] [Indexed: 11/21/2022]
Abstract
Night monkeys (Aotus) are the only genus of monkeys within the Simian lineage that successfully occupy a nocturnal environmental niche. Their behavior is supported by their sensory organs' distinctive morphological features; however, little is known about their evolutionary adaptations in sensory regions of the cerebral cortex. Here, we investigate this question by exploring the cortical organization of night monkeys using high-resolution in-vivo brain MRI and comparative cortical-surface T1w/T2w myeloarchitectonic mapping. Our results show that the night monkey cerebral cortex has a qualitatively similar but quantitatively different pattern of cortical myelin compared to the diurnal macaque and marmoset monkeys. T1w/T2w myelin and its gradient allowed us to parcellate high myelin areas, including the middle temporal complex (MT +) and auditory cortex, and a low-myelin area, Brodmann area 7 (BA7) in the three species, despite species differences in cortical convolutions. Relative to the total cortical-surface area, those of MT + and the auditory cortex are significantly larger in night monkeys than diurnal monkeys, whereas area BA7 occupies a similar fraction of the cortical sheet in all three species. We propose that the selective expansion of sensory areas dedicated to visual motion and auditory processing in night monkeys may reflect cortical adaptations to a nocturnal environment.
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