Brain Charts for the Rhesus Macaque

Poster No:


Submission Type:

Abstract Submission 


Samuel Alldritt1, Julian Ramirez1, Jakob Seidlitz2, Richard Bethlehem3, Karl-Heinz Nenning4, David Amaral5, Damien Fair6, Andrew Fox7, Alexandre Franco4, Jeff Bennett8, Ned Kalin9,10, Brian Russ4, Lena Dorfschmidt11, Aaron Alexander-Bloch2, Daniel Margulies12, Jonathan Smallwood13, Charles Schroeder14, Becker Guillaume15, Mar Sanchez16, Lucie Chalet17, Daniel Gale13, Zsofie Kovacs-Balint18, Jason Gallivan19, Joseph Nashed20, Clement Garin21, John Erdman22, Matthew Kuchan23, Martha Neuringer24, Viola Neudecker25, Oscar Miranda Dominguez26, Ansgar Brambrink25, Christopher Kroenke24, Christopher Petkov27, Jiaojing Wang28, Chris Klink29, Adam Messinger30, PRIME-DE Consortium1, Michael Milham1, Ting Xu1


1Child Mind Institute, New York, NY, 2University of Pennsylvania, Philadelphia, PA, 3Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom, 4Nathan Kline Institute, Orangeburg, NY, 5University of California Davis MIND Institute, Sacramento, CA, 6Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, 7University of California Davis, Davis, CA, 8California National Primate Research Center, Davis, CA, 9University of Wisconsin Madison, Madison, WI, 10Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, WI, 11The Children’s Hospital of Philadelphia, Philadelphia, PA, 12Université Paris Cité, CNRS, Integrative Neuroscience and Cognition Center, Paris, France, 13Department of Psychology, Queen’s University, Ontario, Canada, 14Nathan S. kline Institute for Psychiatric Research, Orangeburg, NY, 15Université de Lyon, Lyon, France, 16Emory National Primate Research Center, Atlanta, GA, 17Claude Bernard University Lyon 1, Villeurbanne, France, 18Emory University, Budapest, Hungary, 19Department of Psychology, Queens University, Ontario, Canada, 20Centre for Neuroscience Studies, Queen’s University, Ontario, Canada, 21Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 22Beckman Institute for Advanced Science and Technology, Champaign, IL, 23Abbott Laboratories, Columbus, OH, 24Oregon National Primate Research Center, Portland, OR, 25Columbia University, New York, NY, 26University of Minnesota, Minneapolis, MN, 27Newcastle University, Newcastle, United Kingdom, 28Kunming University of Science and Technology, Kunming, China, 29Netherlands Institute for Neuroscience Royal Netherlands Academy of Arts and Sciences, Meibergdreef, Netherlands, 30National Institute of Health, Baltimore, MD

First Author:

Samuel Alldritt  
Child Mind Institute
New York, NY


Julian Ramirez  
Child Mind Institute
New York, NY
Jakob Seidlitz  
University of Pennsylvania
Philadelphia, PA
Richard Bethlehem  
Autism Research Centre, Department of Psychiatry, University of Cambridge
Cambridge, United Kingdom
Karl-Heinz Nenning  
Nathan Kline Institute
Orangeburg, NY
David Amaral  
University of California Davis MIND Institute
Sacramento, CA
Damien Fair  
Masonic Institute for the Developing Brain, University of Minnesota Medical School
Minneapolis, MN
Andrew Fox  
University of California Davis
Davis, CA
Alexandre Franco  
Nathan Kline Institute
Orangeburg, NY
Jeff Bennett  
California National Primate Research Center
Davis, CA
Ned Kalin  
University of Wisconsin Madison|Department of Psychiatry, University of Wisconsin School of Medicine and Public Health
Madison, WI|Madison, WI
Brian Russ  
Nathan Kline Institute
Orangeburg, NY
Lena Dorfschmidt  
The Children’s Hospital of Philadelphia
Philadelphia, PA
Aaron Alexander-Bloch  
University of Pennsylvania
Philadelphia, PA
Daniel Margulies  
Université Paris Cité, CNRS, Integrative Neuroscience and Cognition Center
Paris, France
Jonathan Smallwood  
Department of Psychology, Queen’s University
Ontario, Canada
Charles Schroeder  
Nathan S. kline Institute for Psychiatric Research
Orangeburg, NY
Becker Guillaume  
Université de Lyon
Lyon, France
Mar Sanchez  
Emory National Primate Research Center
Atlanta, GA
Lucie Chalet  
Claude Bernard University Lyon 1
Villeurbanne, France
Daniel Gale  
Department of Psychology, Queen’s University
Ontario, Canada
Zsofie Kovacs-Balint, PhD  
Emory University
Budapest, Hungary
Jason Gallivan  
Department of Psychology, Queens University
Ontario, Canada
Joseph Nashed  
Centre for Neuroscience Studies, Queen’s University
Ontario, Canada
Clement Garin  
Department of Biomedical Engineering, Vanderbilt University
Nashville, TN
John Erdman  
Beckman Institute for Advanced Science and Technology
Champaign, IL
Matthew Kuchan  
Abbott Laboratories
Columbus, OH
Martha Neuringer  
Oregon National Primate Research Center
Portland, OR
Viola Neudecker  
Columbia University
New York, NY
Oscar Miranda Dominguez  
University of Minnesota
Minneapolis, MN
Ansgar Brambrink  
Columbia University
New York, NY
Christopher Kroenke  
Oregon National Primate Research Center
Portland, OR
Christopher Petkov  
Newcastle University
Newcastle, United Kingdom
Jiaojing Wang  
Kunming University of Science and Technology
Kunming, China
Chris Klink  
Netherlands Institute for Neuroscience Royal Netherlands Academy of Arts and Sciences
Meibergdreef, Netherlands
Adam Messinger  
National Institute of Health
Baltimore, MD
PRIME-DE Consortium  
Child Mind Institute
New York, NY
Michael Milham  
Child Mind Institute
New York, NY
Ting Xu  
Child Mind Institute
New York, NY


The rhesus macaque is one of the most widely used non-human primate (NHP) models for the human brain, due to resemblance in brain structure, function, and social behaviours. Notably, comparative developmental models of human and macaque provides opportunities to investigate neural plasticity, developmental trajectories, and pathological processes. Recently, analysis of multisite MRI datasets have successfully characterized human brain development across the lifespan [1]. However, due to multifaceted challenges in NHP studies, we lack comparative brain growth charts for macaques. This study aimed to establish reference standards for macaque brain development that facilitates the comparison of development phases across humans and macaques.


We studied a collaborative multisite collection of MRI data including the PRIMatE Data Exchange (PRIME-DE) consortium. Structural images were preprocessed through the 'nhp-abcd-bids-pipeline'[2-4], with customized templates for early developmental data (age < 0.3 yr), followed by visual inspections for quality assessment. Prenatal data was manually segmented [5]. A total of 1,522 scans (1024 macaques, 554 F, age: -.23 - 30.64 yr) across 23 sites were included in the analysis. We estimated global and regional volume, cortical thickness, and surface area and applied a GAMLSS, fitting nonlinear growth curves stratified by sex and site as a random effect. We identified the macaque developmental milestones (i.e. growth rates and peak age of trajectories) and transformed them to human surfaces for comparing the developmental phases between humans and macaques.


Overall, macaque trajectories demonstrate similar patterns in total volume of gray matter (GMV), white matter, and subcortical GM compared to humans. However, unlike humans, where GMV peaks in childhood (~6 yr), macaque GMV peaked earlier during infancy (~8 mon), followed by a plateau and gradual decline. Ventricular volume sharply decreases before birth, with a steady postnatal increase, followed by a slight increase towards the end of the lifespan. At the GMV peak age (Fig 1C), the growth rate in volume, area, and cortical thickness shows regional variations [6]. Except for the frontal pole, volumes in the lateral and medial frontal, middle temporal, and parahippocampal regions continue to increase, while the visual and parietal lobes show a reduction. Cortical thickness mirrors a similar pattern to volume, while surface area displays continued expansion in most brain regions, except for the visual cortex.

Figure 2 illustrates regional peak ages for volume, area, and thickness. Notably, volume and area share a similar peak age scale across regions, with a late peak age observed in the precentral gyrus and anterior cingular cortex (ACC). In contrast, thickness exhibits an earlier overall peak age. Upon comparing the human peak age with that of macaque transformed on the human surface (Fig 2C-D), a development delay was detected in the insular and ACC across all measures (Fig 2F), highlighting functional relationships including social cognition, autobiographical memory, and affective processing.
Supporting Image: Figure_1.jpg
Supporting Image: Figure_2.jpg


This study established normative brain development trajectories for macaque. Compared to human, macaque brain grows faster and plateaus earlier, particularly in regions with functional associations with social cognition, autobiographical memory, and affective processing. Our findings suggest neotenic changes in human brain development with prolonged periods of postnatal brain growth during childhood, which may facilitate cellular maturation, myelination, synaptic wiring, and pruning. Functionally these changes are important for the development of complex cognitive and social behaviours that are core features of human cognition. The normative brain charts offer a window into the brain development of nonhuman primates that provides a baseline from which we can gain an understanding of how human brain development shapes how we think and feel.

Lifespan Development:

Early life, Adolescence, Aging 1
Normal Brain Development: Fetus to Adolescence

Neuroanatomy, Physiology, Metabolism and Neurotransmission:

Cortical Anatomy and Brain Mapping 2
Normal Development


Open Data
White Matter

1|2Indicates the priority used for review

Provide references using author date format

[1] Bethlehem RAI, Seidlitz J, White SR, Vogel JW, Anderson KM, Adamson C, et al. Brain charts for the human lifespan. Nature. 2022;604: 525–533.

[2] Autio JA, Glasser MF, Ose T, Donahue CJ, Bastiani M, Ohno M, et al. Towards HCP-Style macaque connectomes: 24-Channel 3T multi-array coil, MRI sequences and preprocessing. Neuroimage. 2020;215: 116800.
[3] Donahue CJ, Sotiropoulos SN, Jbabdi S, Hernandez-Fernandez M, Behrens TE, Dyrby TB, et al. Using Diffusion Tractography to Predict Cortical Connection Strength and Distance: A Quantitative Comparison with Tracers in the Monkey. J Neurosci. 2016;36: 6758–6770.
[4] Glasser MF, Sotiropoulos SN, Wilson JA, Coalson TS, Fischl B, Andersson JL, et al. The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage. 2013;80: 105–124.
[6] Ryali S, Chen T, Supekar K, Menon V. A parcellation scheme based on von Mises-Fisher distributions and Markov random fields for segmenting brain regions using resting-state fMRI. Neuroimage. 2013;65: 83–96.

[7] Bezgin, Gleb, Vasily A. Vakorin, A. John van Opstal, Anthony R. McIntosh, and Rembrandt Bakker. 2012. “Hundreds of Brain Maps in One Atlas: Registering Coordinate-Independent Primate Neuro-Anatomical Data to a Standard Brain.” NeuroImage 62 (1): 67–76.

[8] Mesulam, M.-M. (Ed.). (2000). Principles of behavioral and cognitive neurology (2nd ed.). Oxford University Press.