Two Separate Brain Networks for Predicting Trainability and Tracking Training-Related Plasticity in Working Dogs
Functional brain connectivity based on resting-state functional magnetic resonance imaging (fMRI) has been shown to be correlated with human personality and behavior. In this study, we sought to know whether capabilities and traits in dogs can be predicted from their resting-state connectivity, as i...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-04-01
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| Series: | Animals |
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| Online Access: | https://www.mdpi.com/2076-2615/14/7/1082 |
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| author | Gopikrishna Deshpande Sinan Zhao Paul Waggoner Ronald Beyers Edward Morrison Nguyen Huynh Vitaly Vodyanoy Thomas S. Denney Jeffrey S. Katz |
| author_facet | Gopikrishna Deshpande Sinan Zhao Paul Waggoner Ronald Beyers Edward Morrison Nguyen Huynh Vitaly Vodyanoy Thomas S. Denney Jeffrey S. Katz |
| author_sort | Gopikrishna Deshpande |
| collection | DOAJ |
| description | Functional brain connectivity based on resting-state functional magnetic resonance imaging (fMRI) has been shown to be correlated with human personality and behavior. In this study, we sought to know whether capabilities and traits in dogs can be predicted from their resting-state connectivity, as in humans. We trained awake dogs to keep their head still inside a 3T MRI scanner while resting-state fMRI data was acquired. Canine behavior was characterized by an integrated behavioral score capturing their hunting, retrieving, and environmental soundness. Functional scans and behavioral measures were acquired at three different time points across detector dog training. The first time point (TP1) was prior to the dogs entering formal working detector dog training. The second time point (TP2) was soon after formal detector dog training. The third time point (TP3) was three months’ post detector dog training while the dogs were engaged in a program of maintenance training for detection work. We hypothesized that the correlation between resting-state FC in the dog brain and behavior measures would significantly change during their detection training process (from TP1 to TP2) and would maintain for the subsequent several months of detection work (from TP2 to TP3). To further study the resting-state FC features that can predict the success of training, dogs at TP1 were divided into a successful group and a non-successful group. We observed a core brain network which showed relatively stable (with respect to time) patterns of interaction that were significantly stronger in successful detector dogs compared to failures and whose connectivity strength at the first time point predicted whether a given dog was eventually successful in becoming a detector dog. A second ontologically based flexible peripheral network was observed whose changes in connectivity strength with detection training tracked corresponding changes in behavior over the training program. Comparing dog and human brains, the functional connectivity between the brain stem and the frontal cortex in dogs corresponded to that between the locus coeruleus and left middle frontal gyrus in humans, suggestive of a shared mechanism for learning and retrieval of odors. Overall, the findings point toward the influence of phylogeny and ontogeny in dogs producing two dissociable functional neural networks. |
| first_indexed | 2024-04-24T10:51:20Z |
| format | Article |
| id | doaj.art-b24387a6862841ab9f18eb864f22195a |
| institution | Directory Open Access Journal |
| issn | 2076-2615 |
| language | English |
| last_indexed | 2024-04-24T10:51:20Z |
| publishDate | 2024-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Animals |
| spelling | doaj.art-b24387a6862841ab9f18eb864f22195a2024-04-12T13:14:19ZengMDPI AGAnimals2076-26152024-04-01147108210.3390/ani14071082Two Separate Brain Networks for Predicting Trainability and Tracking Training-Related Plasticity in Working DogsGopikrishna Deshpande0Sinan Zhao1Paul Waggoner2Ronald Beyers3Edward Morrison4Nguyen Huynh5Vitaly Vodyanoy6Thomas S. Denney7Jeffrey S. Katz8Auburn University Neuroimaging Center, Department of Electrical & Computer Engineering, Auburn University, Auburn, AL 36849, USAAuburn University Neuroimaging Center, Department of Electrical & Computer Engineering, Auburn University, Auburn, AL 36849, USACanine Performance Sciences Program, College of Veterinary Medicine, Auburn University, Auburn, AL 36849, USAAuburn University Neuroimaging Center, Department of Electrical & Computer Engineering, Auburn University, Auburn, AL 36849, USADepartment of Anatomy, Physiology & Pharmacology, Auburn University, Auburn, AL 36849, USAAuburn University Neuroimaging Center, Department of Electrical & Computer Engineering, Auburn University, Auburn, AL 36849, USADepartment of Anatomy, Physiology & Pharmacology, Auburn University, Auburn, AL 36849, USAAuburn University Neuroimaging Center, Department of Electrical & Computer Engineering, Auburn University, Auburn, AL 36849, USAAuburn University Neuroimaging Center, Department of Electrical & Computer Engineering, Auburn University, Auburn, AL 36849, USAFunctional brain connectivity based on resting-state functional magnetic resonance imaging (fMRI) has been shown to be correlated with human personality and behavior. In this study, we sought to know whether capabilities and traits in dogs can be predicted from their resting-state connectivity, as in humans. We trained awake dogs to keep their head still inside a 3T MRI scanner while resting-state fMRI data was acquired. Canine behavior was characterized by an integrated behavioral score capturing their hunting, retrieving, and environmental soundness. Functional scans and behavioral measures were acquired at three different time points across detector dog training. The first time point (TP1) was prior to the dogs entering formal working detector dog training. The second time point (TP2) was soon after formal detector dog training. The third time point (TP3) was three months’ post detector dog training while the dogs were engaged in a program of maintenance training for detection work. We hypothesized that the correlation between resting-state FC in the dog brain and behavior measures would significantly change during their detection training process (from TP1 to TP2) and would maintain for the subsequent several months of detection work (from TP2 to TP3). To further study the resting-state FC features that can predict the success of training, dogs at TP1 were divided into a successful group and a non-successful group. We observed a core brain network which showed relatively stable (with respect to time) patterns of interaction that were significantly stronger in successful detector dogs compared to failures and whose connectivity strength at the first time point predicted whether a given dog was eventually successful in becoming a detector dog. A second ontologically based flexible peripheral network was observed whose changes in connectivity strength with detection training tracked corresponding changes in behavior over the training program. Comparing dog and human brains, the functional connectivity between the brain stem and the frontal cortex in dogs corresponded to that between the locus coeruleus and left middle frontal gyrus in humans, suggestive of a shared mechanism for learning and retrieval of odors. Overall, the findings point toward the influence of phylogeny and ontogeny in dogs producing two dissociable functional neural networks.https://www.mdpi.com/2076-2615/14/7/1082caninedogresting statefunctional MRIfunctional connectivitycomparative biology |
| spellingShingle | Gopikrishna Deshpande Sinan Zhao Paul Waggoner Ronald Beyers Edward Morrison Nguyen Huynh Vitaly Vodyanoy Thomas S. Denney Jeffrey S. Katz Two Separate Brain Networks for Predicting Trainability and Tracking Training-Related Plasticity in Working Dogs Animals canine dog resting state functional MRI functional connectivity comparative biology |
| title | Two Separate Brain Networks for Predicting Trainability and Tracking Training-Related Plasticity in Working Dogs |
| title_full | Two Separate Brain Networks for Predicting Trainability and Tracking Training-Related Plasticity in Working Dogs |
| title_fullStr | Two Separate Brain Networks for Predicting Trainability and Tracking Training-Related Plasticity in Working Dogs |
| title_full_unstemmed | Two Separate Brain Networks for Predicting Trainability and Tracking Training-Related Plasticity in Working Dogs |
| title_short | Two Separate Brain Networks for Predicting Trainability and Tracking Training-Related Plasticity in Working Dogs |
| title_sort | two separate brain networks for predicting trainability and tracking training related plasticity in working dogs |
| topic | canine dog resting state functional MRI functional connectivity comparative biology |
| url | https://www.mdpi.com/2076-2615/14/7/1082 |
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