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Vidal JP, Danet L, Péran P, Pariente J, Bach Cuadra M, Zahr NM, Barbeau EJ, Saranathan M. Robust thalamic nuclei segmentation from T1-weighted MRI using polynomial intensity transformation. Brain Struct Funct 2024; 229:1087-1101. [PMID: 38546872 PMCID: PMC11147736 DOI: 10.1007/s00429-024-02777-5] [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: 12/22/2023] [Accepted: 02/19/2024] [Indexed: 04/09/2024]
Abstract
Accurate segmentation of thalamic nuclei, crucial for understanding their role in healthy cognition and in pathologies, is challenging to achieve on standard T1-weighted (T1w) magnetic resonance imaging (MRI) due to poor image contrast. White-matter-nulled (WMn) MRI sequences improve intrathalamic contrast but are not part of clinical protocols or extant databases. In this study, we introduce histogram-based polynomial synthesis (HIPS), a fast preprocessing transform step that synthesizes WMn-like image contrast from standard T1w MRI using a polynomial approximation for intensity transformation. HIPS was incorporated into THalamus Optimized Multi-Atlas Segmentation (THOMAS) pipeline, a method developed and optimized for WMn MRI. HIPS-THOMAS was compared to a convolutional neural network (CNN)-based segmentation method and THOMAS modified for the use of T1w images (T1w-THOMAS). The robustness and accuracy of the three methods were tested across different image contrasts (MPRAGE, SPGR, and MP2RAGE), scanner manufacturers (PHILIPS, GE, and Siemens), and field strengths (3 T and 7 T). HIPS-transformed images improved intra-thalamic contrast and thalamic boundaries, and HIPS-THOMAS yielded significantly higher mean Dice coefficients and reduced volume errors compared to both the CNN method and T1w-THOMAS. Finally, all three methods were compared using the frequently travelling human phantom MRI dataset for inter- and intra-scanner variability, with HIPS displaying the least inter-scanner variability and performing comparably with T1w-THOMAS for intra-scanner variability. In conclusion, our findings highlight the efficacy and robustness of HIPS in enhancing thalamic nuclei segmentation from standard T1w MRI.
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Affiliation(s)
- Julie P Vidal
- CNRS, CerCo (Brain and Cognition Research Center), Paul Sabatier University, Toulouse, France
- INSERM, ToNiC (Toulouse NeuroImaging Center), Paul Sabatier University, Toulouse, France
| | - Lola Danet
- INSERM, ToNiC (Toulouse NeuroImaging Center), Paul Sabatier University, Toulouse, France
- Neurology Department, Purpan Hospital, Toulouse University Hospital Center, Toulouse, France
| | - Patrice Péran
- INSERM, ToNiC (Toulouse NeuroImaging Center), Paul Sabatier University, Toulouse, France
| | - Jérémie Pariente
- INSERM, ToNiC (Toulouse NeuroImaging Center), Paul Sabatier University, Toulouse, France
- Neurology Department, Purpan Hospital, Toulouse University Hospital Center, Toulouse, France
| | - Meritxell Bach Cuadra
- CIBM Center for Biomedical Imaging, Radiology Department, Lausanne University and University Hospital, Lausanne, Switzerland
| | - Natalie M Zahr
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Emmanuel J Barbeau
- CNRS, CerCo (Brain and Cognition Research Center), Paul Sabatier University, Toulouse, France
| | - Manojkumar Saranathan
- Department of Radiology, University of Massachusetts Chan Medical School, Worcester, MA, USA.
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Young T, Kumar VJ, Saranathan M. Normative modeling of thalamic nuclear volumes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.06.24303871. [PMID: 38496426 PMCID: PMC10942522 DOI: 10.1101/2024.03.06.24303871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Thalamic nuclei have been implicated in neurodegenerative and neuropsychiatric disorders. Normative models for thalamic nuclear volumes have not been proposed thus far. The aim of this work was to establish normative models of thalamic nuclear volumes and subsequently investigate changes in thalamic nuclei in cognitive and psychiatric disorders. Volumes of the bilateral thalami and 12 nuclear regions were generated from T1 MRI data using a novel segmentation method (HIPS-THOMAS) in healthy control subjects (n=2374) and non-control subjects (n=695) with early and late mild cognitive impairment (EMCI, LMCI), Alzheimer's disease (AD), Early psychosis and Schizophrenia, Bipolar disorder, and Attention deficit hyperactivity disorder. Three different normative modelling methods were evaluated while controlling for sex, intracranial volume, and site. Z-scores and extreme z-score deviations were calculated and compared across phenotypes. GAMLSS models performed the best. Statistically significant shifts in z-score distributions consistent with atrophy were observed for most phenotypes. Shifts of progressively increasing magnitude were observed bilaterally from EMCI to AD with larger shifts in the left thalamic regions. Heterogeneous shifts were observed in psychiatric diagnoses with a predilection for the right thalamic regions. Here we present the first normative models of thalamic nuclear volumes and highlight their utility in evaluating heterogenous disorders such as Schizophrenia.
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Affiliation(s)
- Taylor Young
- Department of Psychiatry, University of Massachusetts Chan Medical School, Worcester, MA
- Department of Neurology, University of Massachusetts Chan Medical School, Worcester, MA
| | | | - Manojkumar Saranathan
- Department of Radiology, University of Massachusetts Chan Medical School, Worcester, MA
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Shah SN, Dounavi ME, Malhotra PA, Lawlor B, Naci L, Koychev I, Ritchie CW, Ritchie K, O’Brien JT. Dementia risk and thalamic nuclei volumetry in healthy midlife adults: the PREVENT Dementia study. Brain Commun 2024; 6:fcae046. [PMID: 38444908 PMCID: PMC10914447 DOI: 10.1093/braincomms/fcae046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 12/31/2023] [Accepted: 02/13/2024] [Indexed: 03/07/2024] Open
Abstract
A reduction in the volume of the thalamus and its nuclei has been reported in Alzheimer's disease, mild cognitive impairment and asymptomatic individuals with risk factors for early-onset Alzheimer's disease. Some studies have reported thalamic atrophy to occur prior to hippocampal atrophy, suggesting thalamic pathology may be an early sign of cognitive decline. We aimed to investigate volumetric differences in thalamic nuclei in middle-aged, cognitively unimpaired people with respect to dementia family history and apolipoprotein ε4 allele carriership and the relationship with cognition. Seven hundred participants aged 40-59 years were recruited into the PREVENT Dementia study. Individuals were stratified according to dementia risk (approximately half with and without parental dementia history). The subnuclei of the thalamus of 645 participants were segmented on T1-weighted 3 T MRI scans using FreeSurfer 7.1.0. Thalamic nuclei were grouped into six regions: (i) anterior, (ii) lateral, (iii) ventral, (iv) intralaminar, (v) medial and (vi) posterior. Cognitive performance was evaluated using the computerized assessment of the information-processing battery. Robust linear regression was used to analyse differences in thalamic nuclei volumes and their association with cognitive performance, with age, sex, total intracranial volume and years of education as covariates and false discovery rate correction for multiple comparisons. We did not find significant volumetric differences in the thalamus or its subregions, which survived false discovery rate correction, with respect to first-degree family history of dementia or apolipoprotein ε4 allele status. Greater age was associated with smaller volumes of thalamic subregions, except for the medial thalamus, but only in those without a dementia family history. A larger volume of the mediodorsal medial nucleus (Pfalse discovery rate = 0.019) was associated with a faster processing speed in those without a dementia family history. Larger volumes of the thalamus (P = 0.016) and posterior thalamus (Pfalse discovery rate = 0.022) were associated with significantly worse performance in the immediate recall test in apolipoprotein ε4 allele carriers. We did not find significant volumetric differences in thalamic subregions in relation to dementia risk but did identify an interaction between dementia family history and age. Larger medial thalamic nuclei may exert a protective effect on cognitive performance in individuals without a dementia family history but have little effect on those with a dementia family history. Larger volumes of posterior thalamic nuclei were associated with worse recall in apolipoprotein ε4 carriers. Our results could represent initial dysregulation in the disease process; further study is needed with functional imaging and longitudinal analysis.
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Affiliation(s)
- Sita N Shah
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK
| | - Maria-Eleni Dounavi
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK
| | - Paresh A Malhotra
- Department of Brain Sciences, Imperial College London, London W12 0NN, UK
- UK Dementia Research Institute Care Research and Technology Centre, Imperial College London and the University of Surrey, London SW7 2AZ, UK
| | - Brian Lawlor
- Trinity College Institute of Neuroscience, School of Psychology, Trinity College Dublin, Dublin D02 PX31, Ireland
- Global Brain Health Institute, Trinity College Dublin, Dublin D02 X9W9, Ireland
| | - Lorina Naci
- Trinity College Institute of Neuroscience, School of Psychology, Trinity College Dublin, Dublin D02 PX31, Ireland
- Global Brain Health Institute, Trinity College Dublin, Dublin D02 X9W9, Ireland
| | - Ivan Koychev
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
| | - Craig W Ritchie
- Centre for Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Karen Ritchie
- Institute de Neurosciences de Montpellier, INSERM, Montpellier 34093, France
| | - John T O’Brien
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge CB2 0QQ, UK
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Dönmezler S, Sönmez D, Yılbaş B, Öztürk Hİ, İskender G, Kurt İ. Thalamic nuclei volume differences in schizophrenia patients and healthy controls using probabilistic mapping: A comparative analysis. Schizophr Res 2024; 264:266-271. [PMID: 38198878 DOI: 10.1016/j.schres.2024.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 12/13/2023] [Accepted: 01/01/2024] [Indexed: 01/12/2024]
Abstract
AIM We aimed to investigate potential discrepancies in the volume of thalamic nuclei between individuals with schizophrenia and healthy controls. METHODS The imaging data for this study were obtained from the MCICShare data repository within SchizConnect. We employed probabilistic mapping technique developed by Iglesias et al. (2018). The analytical component entailed volumetric segmentation of the thalamus using the FreeSurfer image analysis suite. Our analysis focused on evaluating the differences in the volumes of various thalamic nuclei groups within the thalami, specifically the anterior, intralaminar, medial, posterior, lateral, and ventral groups in both the right and left thalami, between schizophrenia patients and healthy controls. We employed MANCOVA to analyse these dependent variables (volumes of 12 distinct thalamic nuclei groups), with diagnosis (SCZ vs. HCs) as the main explanatory variable, while controlling for covariates such as eTIV and age. RESULTS The assumptions of MANCOVA, including the homogeneity of covariance matrices, were met. Specific univariate tests for the right thalamus revealed significant differences in the medial (F[1, 200] = 26.360, p < 0.001), and the ventral groups (F[1, 200] = 4.793, p = 0.030). For the left thalamus, the medial (F[1, 200] = 22.527, p < 0.001); posterior (F[1, 200] = 8.227, p = 0.005), lateral (F[1, 200] = 7.004, p = 0.009), and ventral groups (F[1, 200] = 9.309, p = 0.003) showed significant differences. CONCLUSION These findings suggest that particular thalamic nuclei groups in both the right and left thalami may be most affected in schizophrenia, with more pronounced differences observed in the left thalamic nuclei. FUNDINGS The authors received no financial support for the research.
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Affiliation(s)
- Süleyman Dönmezler
- Sanko University, School of Medicine, Department of Psychiatry, Gaziantep, Turkey.
| | - Doğuş Sönmez
- Bakirkoy Training and Research Hospital for Psychiatry, Neurology and Neurosurgery, Department of Psychiatry, Istanbul, Turkey
| | - Barış Yılbaş
- Sanko University, School of Medicine, Department of Psychiatry, Gaziantep, Turkey
| | - Halil İbrahim Öztürk
- Sanko University, School of Medicine, Department of Psychiatry, Gaziantep, Turkey
| | - Gizem İskender
- Istanbul Prof. Dr. Cemil Tascioglu City Hospital, Department of Psychiatry, Istanbul, Turkey
| | - İmren Kurt
- Başakşehir Çam and Sakura City Hospital, Department of Psychiatry, Istanbul, Turkey
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Zhuo J, Raghavan P, Shao M, Roys S, Liang X, Tchoquessi RLN, Rhodes CS, Badjatia N, Prince JL, Gullapalli RP. Automatic Quantification of Enlarged Perivascular Space in Patients With Traumatic Brain Injury Using Super-Resolution of T2-Weighted Images. J Neurotrauma 2024; 41:407-419. [PMID: 37950721 PMCID: PMC10837035 DOI: 10.1089/neu.2023.0082] [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] [Indexed: 11/13/2023] Open
Abstract
The perivascular space (PVS) is important to brain waste clearance and brain metabolic homeostasis. Enlarged PVS (ePVS) becomes visible on magnetic resonance imaging (MRI) and is best appreciated on T2-weighted (T2w) images. However, quantification of ePVS is challenging because standard-of-care T1-weighted (T1w) and T2w images are often obtained via two-dimensional (2D) acquisition, whereas accurate quantification of ePVS normally requires high-resolution volumetric three-dimensional (3D) T1w and T2w images. The purpose of this study was to investigate the use of a deep-learning-based super-resolution (SR) technique to improve ePVS quantification from 2D T2w images for application in patients with traumatic brain injury (TBI). We prospectively recruited 26 volunteers (age: 31 ± 12 years, 12 male/14 female) where both 2D T2w and 3D T2w images were acquired along with 3D T1w images to validate the ePVS quantification using SR T2w images. We then applied the SR method to retrospectively acquired 2D T2w images in 41 patients with chronic TBI (age: 41 ± 16 years, 32 male/9 female). ePVS volumes were automatically quantified within the whole-brain white matter and major brain lobes (temporal, parietal, frontal, occipital) in all subjects. Pittsburgh Sleep Quality Index (PSQI) scores were obtained on all patients with TBI. Compared with the silver standard (3D T2w), in the validation study, the SR T2w provided similar whole-brain white matter ePVS volume (r = 0.98, p < 0.0001), and similar age-related ePVS burden increase (r = 0.80, p < 0.0001). In the patient study, patients with TBI with poor sleep showed a higher age-related ePVS burden increase than those with good sleep. Sleep status is a significant interaction factor in the whole brain (p = 0.047) and the frontal lobe (p = 0.027). We demonstrate that images produced by SR of 2D T2w images can be automatically analyzed to produce results comparable to those obtained by 3D T2 volumes. Reliable age-related ePVS burden across the whole-brain white matter was observed in all subjects. Poor sleep, affecting the glymphatic function, may contribute to the accelerated increase of ePVS burden following TBI.
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Affiliation(s)
- Jiachen Zhuo
- Center for Advanced Imaging Research, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Department of Diagnostic Radiology and Nuclear Medicine, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Prashant Raghavan
- Department of Diagnostic Radiology and Nuclear Medicine, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Muhan Shao
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Steven Roys
- Center for Advanced Imaging Research, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Department of Diagnostic Radiology and Nuclear Medicine, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Xiao Liang
- Center for Advanced Imaging Research, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Department of Diagnostic Radiology and Nuclear Medicine, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Rosy Linda Njonkou Tchoquessi
- Center for Advanced Imaging Research, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Department of Diagnostic Radiology and Nuclear Medicine, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Chandler Sours Rhodes
- National Intrepid Center of Excellence, Walter Reed National Military Medical Cent5r, Bethesda, Maryland, USA
| | - Neeraj Badjatia
- Department of Neurology, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Jerry L. Prince
- National Intrepid Center of Excellence, Walter Reed National Military Medical Cent5r, Bethesda, Maryland, USA
| | - Rao P. Gullapalli
- Center for Advanced Imaging Research, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
- Department of Diagnostic Radiology and Nuclear Medicine, Neurosurgery, and Anesthesiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
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Vidal JP, Danet L, Péran P, Pariente J, Cuadra MB, Zahr NM, Barbeau EJ, Saranathan M. Robust thalamic nuclei segmentation from T1-weighted MRI using polynomial intensity transformation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.30.24301606. [PMID: 38352493 PMCID: PMC10862991 DOI: 10.1101/2024.01.30.24301606] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Accurate segmentation of thalamic nuclei, crucial for understanding their role in healthy cognition and in pathologies, is challenging to achieve on standard T1-weighted (T1w) magnetic resonance imaging (MRI) due to poor image contrast. White-matter-nulled (WMn) MRI sequences improve intrathalamic contrast but are not part of clinical protocols or extant databases. In this study, we introduce histogram-based polynomial synthesis (HIPS), a fast preprocessing transform step that synthesizes WMn-like image contrast from standard T1w MRI using a polynomial approximation for intensity transformation. HIPS was incorporated into THalamus Optimized Multi-Atlas Segmentation (THOMAS) pipeline, a method developed and optimized for WMn MRI. HIPS-THOMAS was compared to a convolutional neural network (CNN)-based segmentation method and THOMAS modified for T1w images (T1w-THOMAS). The robustness and accuracy of the three methods were tested across different image contrasts (MPRAGE, SPGR, and MP2RAGE), scanner manufacturers (PHILIPS, GE, and Siemens), and field strengths (3T and 7T). HIPS-transformed images improved intra-thalamic contrast and thalamic boundaries, and HIPS-THOMAS yielded significantly higher mean Dice coefficients and reduced volume errors compared to both the CNN method and T1w-THOMAS. Finally, all three methods were compared using the frequently travelling human phantom MRI dataset for inter- and intra-scanner variability, with HIPS displaying the least inter-scanner variability and performing comparably with T1w-THOMAS for intra-scanner variability. In conclusion, our findings highlight the efficacy and robustness of HIPS in enhancing thalamic nuclei segmentation from standard T1w MRI.
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7
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Chauvin RJ, Newbold DJ, Nielsen AN, Miller RL, Krimmel SR, Metoki A, Wang A, Van AN, Montez DF, Marek S, Suljic V, Baden NJ, Ramirez-Perez N, Scheidter KM, Monk JS, Whiting FI, Adeyemo B, Snyder AZ, Kay BP, Raichle ME, Laumann TO, Gordon EM, Dosenbach NU. Disuse-driven plasticity in the human thalamus and putamen. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.07.566031. [PMID: 37987000 PMCID: PMC10659348 DOI: 10.1101/2023.11.07.566031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Motor adaptation in cortico-striato-thalamo-cortical loops has been studied mainly in animals using invasive electrophysiology. Here, we leverage functional neuroimaging in humans to study motor circuit plasticity in the human subcortex. We employed an experimental paradigm that combined two weeks of upper-extremity immobilization with daily resting-state and motor task fMRI before, during, and after the casting period. We previously showed that limb disuse leads to decreased functional connectivity (FC) of the contralateral somatomotor cortex (SM1) with the ipsilateral somatomotor cortex, increased FC with the cingulo-opercular network (CON) as well as the emergence of high amplitude, fMRI signal pulses localized in the contralateral SM1, supplementary motor area and the cerebellum. From our prior observations, it remains unclear whether the disuse plasticity affects the thalamus and striatum. We extended our analysis to include these subcortical regions and found that both exhibit strengthened cortical FC and spontaneous fMRI signal pulses induced by limb disuse. The dorsal posterior putamen and the central thalamus, mainly CM, VLP and VIM nuclei, showed disuse pulses and FC changes that lined up with fmri task activations from the Human connectome project motor system localizer, acquired before casting for each participant. Our findings provide a novel understanding of the role of the cortico-striato-thalamo-cortical loops in human motor plasticity and a potential link with the physiology of sleep regulation. Additionally, similarities with FC observation from Parkinson Disease (PD) questions a pathophysiological link with limb disuse.
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Affiliation(s)
- Roselyne J. Chauvin
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Dillan J. Newbold
- Department of Neurology, New York University Grossman School of Medicine, New York, New York 10016, USA
| | - Ashley N. Nielsen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Ryland L. Miller
- Basque Center on Cognition, Brain and Language, Donostia, Gipuzkoa, Spain
| | - Samuel R. Krimmel
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Athanasia Metoki
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Anxu Wang
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Biomedical Engineering, Washington University in St. Louis, MO 63130
| | - Andrew N. Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Division of Computation and Data Science, Washington University School of Medicine, St. Louis, MO 63110
| | - David F. Montez
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Scott Marek
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Vahdeta Suljic
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Noah J. Baden
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | | | - Kristen M. Scheidter
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Julia S. Monk
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Forrest I. Whiting
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Abraham Z. Snyder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Benjamin P. Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Marcus E. Raichle
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St Louis, MO, USA
| | - Timothy O. Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Evan M. Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Nico U.F. Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Biomedical Engineering, Washington University in St. Louis, MO 63130
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110
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Krimmel SR, Laumann TO, Chauvin RJ, Hershey T, Roland JL, Shimony JS, Willie JT, Norris SA, Marek S, Van AN, Monk J, Scheidter KM, Whiting F, Ramirez-Perez N, Metoki A, Wang A, Kay BP, Nahman-Averbuch H, Fair DA, Lynch CJ, Raichle ME, Gordon EM, Dosenbach NUF. The brainstem's red nucleus was evolutionarily upgraded to support goal-directed action. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.30.573730. [PMID: 38260662 PMCID: PMC10802246 DOI: 10.1101/2023.12.30.573730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
The red nucleus is a large brainstem structure that coordinates limb movement for locomotion in quadrupedal animals (Basile et al., 2021). The humans red nucleus has a different pattern of anatomical connectivity compared to quadrupeds, suggesting a unique purpose (Hatschek, 1907). Previously the function of the human red nucleus remained unclear at least partly due to methodological limitations with brainstem functional neuroimaging (Sclocco et al., 2018). Here, we used our most advanced resting-state functional connectivity (RSFC) based precision functional mapping (PFM) in highly sampled individuals (n = 5) and large group-averaged datasets (combined N ~ 45,000), to precisely examine red nucleus functional connectivity. Notably, red nucleus functional connectivity to motor-effector networks (somatomotor hand, foot, and mouth) was minimal. Instead, red nucleus functional connectivity along the central sulcus was specific to regions of the recently discovered somato-cognitive action network (SCAN; (Gordon et al., 2023)). Outside of primary motor cortex, red nucleus connectivity was strongest to the cingulo-opercular (CON) and salience networks, involved in action/cognitive control (Dosenbach et al., 2007; Newbold et al., 2021) and reward/motivated behavior (Seeley, 2019), respectively. Functional connectivity to these two networks was organized into discrete dorsal-medial and ventral-lateral zones. Red nucleus functional connectivity to the thalamus recapitulated known structural connectivity of the dento-rubral thalamic tract (DRTT) and could prove clinically useful in functionally targeting the ventral intermediate (VIM) nucleus. In total, our results indicate that far from being a 'motor' structure, the red nucleus is better understood as a brainstem nucleus for implementing goal-directed behavior, integrating behavioral valence and action plans.
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Affiliation(s)
- Samuel R Krimmel
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Roselyne J Chauvin
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Tamara Hershey
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychological & Brain Sciences, Washington University, St. Louis, Missouri, USA
| | - Jarod L Roland
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jon T Willie
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, New York, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, Missouri
| | - Scott A Norris
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Scott Marek
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri
| | - Julia Monk
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Kristen M Scheidter
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Forrest Whiting
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Nadeshka Ramirez-Perez
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Athanasia Metoki
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Anxu Wang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Division of Computation and Data Science, Washington University, St. Louis, Missouri, USA
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Hadas Nahman-Averbuch
- Washington University Pain Center, Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Damien A Fair
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota, USA
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota, USA
- Institute of Child Development, University of Minnesota, Minneapolis, Minnesota, USA
| | - Charles J Lynch
- Department of Psychiatry, Weill Cornell Medicine, New York, New York, USA
| | - Marcus E Raichle
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychological & Brain Sciences, Washington University, St. Louis, Missouri, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, Missouri
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri
| | - Evan M Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Psychological & Brain Sciences, Washington University, St. Louis, Missouri, USA
- Department of Biomedical Engineering, Washington University, St. Louis, Missouri
- Program in Occupational Therapy, Washington University, St. Louis, Missouri, USA
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri, USA
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