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Updated: Apr 17, 2026

Training Dogs for Awake, Unrestrained Functional Magnetic Resonance Imaging
Published on: October 13, 2019
Cognitive domains in the dog: independence of working memory from object learning, selective attention, and motor
Brian M Zanghi1, Joseph Araujo, Norton W Milgram
1Nestlé Purina Petcare Research, One Checkerboard Square, St Louis, MO, 63164, USA, Brian.Zanghi@rd.nestle.com.
Abstract:
Cognition in dogs, like in humans, is not a unitary process. Some functions, such as simple discrimination learning, are relatively insensitive to age; others, such as visuospatial learning can provide behavioral biomarkers of age. The present experiment sought to further establish the relationship between various cognitive domains, namely visuospatial memory, object discrimination learning (ODL), and selective attention (SA). In addition, we also set up a task to assess motor learning (ML). Thirty-six beagles (9-16 years) performed a variable delay non-matching to position (vDNMP) task using two objects with 20- and 90-s delay and were divided into three groups based on a combined score (HMP = 88-93 % accuracy [N = 12]; MMP = 79-86 % accuracy [N = 12]; LMP = 61-78 % accuracy [N = 12]). Variable object oddity task was used to measure ODL (correct or incorrect object) and SA (0-3 incorrect distractor objects with same [SA-same] or different [SA-diff] correct object as ODL). ML involved reaching various distances (0-15 cm). Age did not differ between memory groups (mean 11.6 years). ODL (ANOVA P = 0.43), or SA-same and SA-different (ANOVA P = 0.96), performance did not differ between the three vDNMP groups, although mean errors during ODL was numerically higher for LMP dogs. Errors increased (P < 0.001) for all dogs with increasing number of distractor objects during both SA tasks. vDNMP groups remained different (ANOVA P < 0.001) when re-tested with vDNMP task 42 days later. Maximum ML distance did not differ between vDNMP groups (ANOVA P = 0.96). Impaired short-term memory performance in aged dogs does not appear to predict performance of cognitive domains associated with object learning, SA, or maximum ML distance.
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