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Kaneko T, Matsumoto J, Lu W, Zhao X, Ueno-Nigh LR, Oishi T, Kimura K, Otsuka Y, Zheng A, Ikenaka K, Baba K, Mochizuki H, Nishijo H, Inoue KI, Takada M. Deciphering social traits and pathophysiological conditions from natural behaviors in common marmosets. Curr Biol 2024; 34:2854-2867.e5. [PMID: 38889723 DOI: 10.1016/j.cub.2024.05.033] [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] [Received: 04/16/2024] [Revised: 05/15/2024] [Accepted: 05/17/2024] [Indexed: 06/20/2024]
Abstract
Nonhuman primates (NHPs) are indispensable animal models by virtue of the continuity of behavioral repertoires across primates, including humans. However, behavioral assessment at the laboratory level has so far been limited. Employing the application of three-dimensional (3D) pose estimation and the optimal integration of subsequent analytic methodologies, we demonstrate that our artificial intelligence (AI)-based approach has successfully deciphered the ethological, cognitive, and pathological traits of common marmosets from their natural behaviors. By applying multiple deep neural networks trained with large-scale datasets, we established an evaluation system that could reconstruct and estimate the 3D poses of the marmosets, a small NHP that is suitable for analyzing complex natural behaviors in laboratory setups. We further developed downstream analytic methodologies to quantify a variety of behavioral parameters beyond motion kinematics. We revealed the distinct parental roles of male and female marmosets through automated detections of food-sharing behaviors using a spatial-temporal filter on 3D poses. Employing a recurrent neural network to analyze 3D pose time series data during social interactions, we additionally discovered that marmosets adjusted their behaviors based on others' internal state, which is not directly observable but can be inferred from the sequence of others' actions. Moreover, a fully unsupervised approach enabled us to detect progressively appearing symptomatic behaviors over a year in a Parkinson's disease model. The high-throughput and versatile nature of an AI-driven approach to analyze natural behaviors will open a new avenue for neuroscience research dealing with big-data analyses of social and pathophysiological behaviors in NHPs.
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Affiliation(s)
- Takaaki Kaneko
- Center for the Evolutionary Origins of Human Behavior, Kyoto University, Inuyama, Aichi 484-8506, Japan.
| | - Jumpei Matsumoto
- Department of System Emotional Science, Faculty of Medicine, University of Toyama, Toyama 930-0194, Japan; Research Center for Idling Brain Science, University of Toyama, Toyama 930-0194, Japan
| | - Wanyi Lu
- Center for the Evolutionary Origins of Human Behavior, Kyoto University, Inuyama, Aichi 484-8506, Japan
| | - Xincheng Zhao
- Center for the Evolutionary Origins of Human Behavior, Kyoto University, Inuyama, Aichi 484-8506, Japan
| | - Louie Richard Ueno-Nigh
- Center for the Evolutionary Origins of Human Behavior, Kyoto University, Inuyama, Aichi 484-8506, Japan
| | - Takao Oishi
- Center for the Evolutionary Origins of Human Behavior, Kyoto University, Inuyama, Aichi 484-8506, Japan
| | - Kei Kimura
- Center for the Evolutionary Origins of Human Behavior, Kyoto University, Inuyama, Aichi 484-8506, Japan
| | - Yukiko Otsuka
- Center for the Evolutionary Origins of Human Behavior, Kyoto University, Inuyama, Aichi 484-8506, Japan
| | - Andi Zheng
- Center for the Evolutionary Origins of Human Behavior, Kyoto University, Inuyama, Aichi 484-8506, Japan
| | - Kensuke Ikenaka
- Department of Neurology, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan
| | - Kousuke Baba
- Department of Neurology, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan
| | - Hideki Mochizuki
- Department of Neurology, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan
| | - Hisao Nishijo
- Department of System Emotional Science, Faculty of Medicine, University of Toyama, Toyama 930-0194, Japan; Research Center for Idling Brain Science, University of Toyama, Toyama 930-0194, Japan; Faculty of Human Sciences, University of East Asia, Shimonoseki, Yamaguchi 751-8503, Japan
| | - Ken-Ichi Inoue
- Center for the Evolutionary Origins of Human Behavior, Kyoto University, Inuyama, Aichi 484-8506, Japan
| | - Masahiko Takada
- Center for the Evolutionary Origins of Human Behavior, Kyoto University, Inuyama, Aichi 484-8506, Japan; Department of Neurology, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan.
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2
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Homanics GE. Exploratory studies of ethanol drinking in the white-tufted marmoset (Callithrix jacchus). Alcohol 2024; 120:99-107. [PMID: 38971210 DOI: 10.1016/j.alcohol.2024.07.001] [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: 05/16/2024] [Revised: 06/26/2024] [Accepted: 07/02/2024] [Indexed: 07/08/2024]
Abstract
The white-tufted marmoset is a small, nonhuman primate that is rapidly gaining popularity as a model organism, especially for neuroscience research. To date, little work in the alcohol research field has utilized the marmoset. As a step toward establishing the marmoset as a research model for alcohol experimentation, a series of exploratory studies were undertaken to characterize ethanol drinking behavior. A voluntary drinking paradigm was established whereby the common marmoset would consume pharmacologically relevant amounts of ethanol. To facilitate ethanol consumption, ethanol was mixed with a marshmallow flavored solution (hereafter called marshmallow juice) to mask the presumed adverse taste of ethanol. Using marshmallow juice flavored solutions, marmosets readily consumed ethanol up to 1 g/kg during 10 min binge-like drinking sessions or up to 5 g/kg during ∼4 h drinking sessions. Consumption of 1.0-1.5 g/kg during a 30 min session resulted in blood ethanol concentrations of 49-73 mg/dl, which are predicted to be pharmacologically relevant. In animals that were stably consuming ethanol in marshmallow juice, gradually reducing the concentration of the marshmallow juice flavoring resulted in markedly reduced ethanol consumption. Lastly, when offered a choice between ethanol in marshmallow juice and marshmallow juice alone, marmosets displayed a very strong preference for the marshmallow juice solution without ethanol. From these studies, it is concluded that marmosets will voluntarily consume ethanol if the taste is masked with a sweet solution such as marshmallow juice. These studies represent the first report of alcohol consumption and preference in the white-tufted marmoset.
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Affiliation(s)
- Gregg E Homanics
- Departments of Anesthesiology & Perioperative Medicine, Neurobiology, and Pharmacology & Chemical Biology, University of Pittsburgh School of Medicine, 3501 Fifth Ave, Pittsburgh, PA 15261, USA.
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Dureux A, Zanini A, Everling S. Mapping of facial and vocal processing in common marmosets with ultra-high field fMRI. Commun Biol 2024; 7:317. [PMID: 38480875 PMCID: PMC10937914 DOI: 10.1038/s42003-024-06002-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 03/01/2024] [Indexed: 03/17/2024] Open
Abstract
Primate communication relies on multimodal cues, such as vision and audition, to facilitate the exchange of intentions, enable social interactions, avoid predators, and foster group cohesion during daily activities. Understanding the integration of facial and vocal signals is pivotal to comprehend social interaction. In this study, we acquire whole-brain ultra-high field (9.4 T) fMRI data from awake marmosets (Callithrix jacchus) to explore brain responses to unimodal and combined facial and vocal stimuli. Our findings reveal that the multisensory condition not only intensifies activations in the occipito-temporal face patches and auditory voice patches but also engages a more extensive network that includes additional parietal, prefrontal and cingulate areas, compared to the summed responses of the unimodal conditions. By uncovering the neural network underlying multisensory audiovisual integration in marmosets, this study highlights the efficiency and adaptability of the marmoset brain in processing facial and vocal social signals, providing significant insights into primate social communication.
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Affiliation(s)
- Audrey Dureux
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, N6A 5K8, Canada.
| | - Alessandro Zanini
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, N6A 5K8, Canada
| | - Stefan Everling
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, N6A 5K8, Canada
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON, N6A 5K8, Canada
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Zhu L, Zheng D, Li R, Shen CJ, Cai R, Lyu C, Tang B, Sun H, Wang X, Ding Y, Xu B, Jia G, Li X, Gao L, Li XM. Induction of Anxiety-Like Phenotypes by Knockdown of Cannabinoid Type-1 Receptors in the Amygdala of Marmosets. Neurosci Bull 2023; 39:1669-1682. [PMID: 37368194 PMCID: PMC10603018 DOI: 10.1007/s12264-023-01081-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 03/08/2023] [Indexed: 06/28/2023] Open
Abstract
The amygdala is an important hub for regulating emotions and is involved in the pathophysiology of many mental diseases, such as depression and anxiety. Meanwhile, the endocannabinoid system plays a crucial role in regulating emotions and mainly functions through the cannabinoid type-1 receptor (CB1R), which is strongly expressed in the amygdala of non-human primates (NHPs). However, it remains largely unknown how the CB1Rs in the amygdala of NHPs regulate mental diseases. Here, we investigated the role of CB1R by knocking down the cannabinoid receptor 1 (CNR1) gene encoding CB1R in the amygdala of adult marmosets through regional delivery of AAV-SaCas9-gRNA. We found that CB1R knockdown in the amygdala induced anxiety-like behaviors, including disrupted night sleep, agitated psychomotor activity in new environments, and reduced social desire. Moreover, marmosets with CB1R-knockdown had up-regulated plasma cortisol levels. These results indicate that the knockdown of CB1Rs in the amygdala induces anxiety-like behaviors in marmosets, and this may be the mechanism underlying the regulation of anxiety by CB1Rs in the amygdala of NHPs.
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Affiliation(s)
- Lin Zhu
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Di Zheng
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Rui Li
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Chen-Jie Shen
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Ruolan Cai
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Chenfei Lyu
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Binliang Tang
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
- Rehabilitation Medicine Center, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 311399, China
| | - Hao Sun
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Xiaohui Wang
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Yu Ding
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Bin Xu
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Guoqiang Jia
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Xinjian Li
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Lixia Gao
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China.
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China.
| | - Xiao-Ming Li
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China.
- Center for Brain Science and Brain-Inspired Intelligence, Research Units for Emotion and Emotion Disorders, Chinese Academy of Medical Sciences, China/Guangdong-Hong Kong-Macao Greater Bay Area, Joint Institute for Genetics and Genome Medicine Between Zhejiang University and University of Toronto, Hangzhou, 310058, China.
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5
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Skibbe H, Rachmadi MF, Nakae K, Gutierrez CE, Hata J, Tsukada H, Poon C, Schlachter M, Doya K, Majka P, Rosa MGP, Okano H, Yamamori T, Ishii S, Reisert M, Watakabe A. The Brain/MINDS Marmoset Connectivity Resource: An open-access platform for cellular-level tracing and tractography in the primate brain. PLoS Biol 2023; 21:e3002158. [PMID: 37384809 DOI: 10.1371/journal.pbio.3002158] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 05/11/2023] [Indexed: 07/01/2023] Open
Abstract
The primate brain has unique anatomical characteristics, which translate into advanced cognitive, sensory, and motor abilities. Thus, it is important that we gain insight on its structure to provide a solid basis for models that will clarify function. Here, we report on the implementation and features of the Brain/MINDS Marmoset Connectivity Resource (BMCR), a new open-access platform that provides access to high-resolution anterograde neuronal tracer data in the marmoset brain, integrated to retrograde tracer and tractography data. Unlike other existing image explorers, the BMCR allows visualization of data from different individuals and modalities in a common reference space. This feature, allied to an unprecedented high resolution, enables analyses of features such as reciprocity, directionality, and spatial segregation of connections. The present release of the BMCR focuses on the prefrontal cortex (PFC), a uniquely developed region of the primate brain that is linked to advanced cognition, including the results of 52 anterograde and 164 retrograde tracer injections in the cortex of the marmoset. Moreover, the inclusion of tractography data from diffusion MRI allows systematic analyses of this noninvasive modality against gold-standard cellular connectivity data, enabling detection of false positives and negatives, which provide a basis for future development of tractography. This paper introduces the BMCR image preprocessing pipeline and resources, which include new tools for exploring and reviewing the data.
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Affiliation(s)
- Henrik Skibbe
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama, Japan
| | | | - Ken Nakae
- Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Aichi, Japan
| | - Carlos Enrique Gutierrez
- Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Onna Village, Japan
| | - Junichi Hata
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako, Saitama, Japan
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Hiromichi Tsukada
- Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Onna Village, Japan
- Center for Mathematical Science and Artificial Intelligence, Chubu University, Kasugai, Aichi, Japan
| | - Charissa Poon
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama, Japan
| | - Matthias Schlachter
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama, Japan
| | - Kenji Doya
- Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Onna Village, Japan
| | - Piotr Majka
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
- Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, Australia
- Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, Australia
| | - Marcello G P Rosa
- Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, Australia
- Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, Australia
| | - Hideyuki Okano
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako, Saitama, Japan
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Tetsuo Yamamori
- Laboratory of Haptic Perception and Cognitive Physiology, RIKEN Center for Brain Science, Wako, Saitama, Japan
- Department of Marmoset Biology and Medicine, Central Institute for Experimental Animals, Kawasaki, Japan
| | - Shin Ishii
- Department of Systems Science, Kyoto University, Kyoto, Japan
| | - Marco Reisert
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama, Japan
- Department of Stereotactic and Functional Neurosurgery, Medical Center of the University of Freiburg, Freiburg Im Breisgau, Germany
- Medical Faculty of the University of Freiburg, Freiburg Im Breisgau, Germany
- Department of Diagnostic and Interventional Radiology, Medical Physics, Medical Center-University of Freiburg, Freiburg Im Breisgau, Germany
| | - Akiya Watakabe
- Laboratory of Haptic Perception and Cognitive Physiology, RIKEN Center for Brain Science, Wako, Saitama, Japan
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Using Nonhuman Primate Models to Reverse-Engineer Prefrontal Circuit Failure Underlying Cognitive Deficits in Schizophrenia. Curr Top Behav Neurosci 2023; 63:315-362. [PMID: 36607528 DOI: 10.1007/7854_2022_407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
In this chapter, I review studies in nonhuman primates that emulate the circuit failure in prefrontal cortex responsible for working memory and cognitive control deficits in schizophrenia. These studies have characterized how synaptic malfunction, typically induced by blockade of NMDAR, disrupts neural function and computation in prefrontal networks to explain errors in cognitive tasks that are seen in schizophrenia. This work is finding causal relationships between pathogenic events of relevance to schizophrenia at vastly different levels of scale, from synapses, to neurons, local, circuits, distributed networks, computation, and behavior. Pharmacological manipulation, the dominant approach in primate models, has limited construct validity for schizophrenia pathogenesis, as the disease results from a complex interplay between environmental, developmental, and genetic factors. Genetic manipulation replicating schizophrenia risk is more advanced in rodent models. Nonetheless, gene manipulation in nonhuman primates is rapidly advancing, and primate developmental models have been established. Integration of large scale neural recording, genetic manipulation, and computational modeling in nonhuman primates holds considerable potential to provide a crucial schizophrenia model moving forward. Data generated by this approach is likely to fill several crucial gaps in our understanding of the causal sequence leading to schizophrenia in humans. This causal chain presents a vexing problem largely because it requires understanding how events at very different levels of scale relate to one another, from genes to circuits to cognition to social interactions. Nonhuman primate models excel here. They optimally enable discovery of causal relationships across levels of scale in the brain that are relevant to cognitive deficits in schizophrenia. The mechanistic understanding of prefrontal circuit failure they promise to provide may point the way to more effective therapeutic interventions to restore function to prefrontal networks in the disease.
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Golub EM, Conner B, Edwards M, Gilllis L, Lacreuse A. Potential trade-off between olfactory and visual discrimination learning in common marmosets (Callithrix jacchus): Implications for the assessment of age-related cognitive decline. Am J Primatol 2022; 84:e23427. [PMID: 35942572 PMCID: PMC9444974 DOI: 10.1002/ajp.23427] [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: 02/07/2022] [Revised: 06/17/2022] [Accepted: 07/23/2022] [Indexed: 11/09/2022]
Abstract
Olfactory dysfunction has been identified as an early biomarker for dementia risk but has rarely been assessed in nonhuman primate models of human aging. To better characterize common marmosets as such models, we assessed olfactory discrimination performance in a sample of 10 animals (5 females), aged 2.5-8.9 years old. The monkeys were proficient in the discrimination and reversal of visual stimuli but naïve to odor stimuli. For olfactory discrimination, the monkeys performed a series of six discriminations of increasing difficulty between two odor stimuli. We found no evidence for an age-related decline as both young and older individuals were able to perform the discriminations in roughly the same number of trials. In addition, the older monkeys had faster responses than the younger animals. However, we noted that when adjusted for age, the speed of acquisition of the first discrimination in the olfactory modality was inversely correlated to the speed of acquisition of their first discrimination of two visual stimuli months earlier. These results suggest that marmosets may compensate for sensory deficits in one modality with higher sensory performance in another. These data have broad implications for the assessment of age-related cognitive decline and the categorization of animals as impaired or nonimpaired.
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Affiliation(s)
| | - Bryce Conner
- Department of Psychological and Brain Sciences, University of Massachusetts Amherst MA
| | - Mélise Edwards
- Neuroscience and Behavior Program, University of Massachusetts Amherst MA
| | - Lacey Gilllis
- Department of Psychological and Brain Sciences, University of Massachusetts Amherst MA
| | - Agnès Lacreuse
- Department of Psychological and Brain Sciences, University of Massachusetts Amherst MA
- Neuroscience and Behavior Program, University of Massachusetts Amherst MA
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