Neuronal Responses in Posterior Parietal Cortex during Learning of Implied Serial Order

Abstract

Monkeys are able to learn the implied ordering of pairs of images drawn from an ordered set, without ever seeing all of the images simultaneously and without explicit spatial or temporal cues. The learning of implied order differs from learning of explicit visual or motor sequences. We recorded the activity of parietal neurons in rhesus macaques while they learned 7-item TI lists when only 2 items were presented on each trial. Behavior and ensemble neuronal activity were significantly influenced by the ordinal relationship of the stimulus pairs, specifically symbolic distance (the difference in rank) and joint ranks (the sum of the ranks). Symbolic distance strongly predicted decision accuracy, and learning was consistently faster as symbolic distance increased. An effect of joint rank on performance was also found nested within the symbolic distance effect. Across the population of neurons, there was significant modulation of firing correlated with the relative ranks of the two stimuli presented on each trial. Neurons exhibited selectivity for stimulus rank during learning, but not before or after. The observed behavior during learning is best explained by a virtual workspace model, not by associative or reward mechanisms. The neural data support a role for posterior parietal cortex in representing several variables that contribute to serial learning, particularly information about the ordinal ranks of the stimuli presented during a given trial. Thus, parietal cortex appears to belong to a neural substrate for learning and representing abstract relationships in a virtual workspace.

Cortical grey matter mediates increases in model-based control and learning from positive feedback from adolescence to adulthood

“…We also find GMD in the parietal cortex, vmPFC and dlPFC to partially mediate age effects on positive feedback learning. The parietal cortex has been implicated in mapping the ordinal relationship among cues, a highly relevant feature when learning the relative rank order of task cues (Munoz et al, 2020). The vmPFC's relevance for feedback learning is also supported by work tying mPFC and mOFC to adaptive decision making and subjective value encoding (Rushworth et al, 2011) for positive (Kringelbach, 2005) and negative outcomes (Tom et al, 2007).…”

Emergent neural dynamics and geometry for generalization in a transitive inference task

“…Despite the long history of TI as a cognitive task, investigation of its neural basis in the brain is comparatively recent [57,[90][91][92][93][94]. Prior work implies that an approach seeking to identify biologically accurate neural implementations would benefit from two criteria:…”

“…Neural recordings in living subjects performing TI indicate that single neurons in the brain can encode variables relevant to TI, including symbolic distance [91,92]. It remains unclear what collective neural process or activity pattern implements the comparison operation-akin to a '>' operator-that generalizes transitivity to novel combinations of items.…”

Emergent neural dynamics and geometry for generalization in a transitive inference task

“…Despite the long history of TI as a cognitive task, investigation of its neural basis in the brain is relatively recent [52, 61, 62, 63, 64, 65]. Prior work implies that an approach seeking to identify biologically accurate neural implementations would benefit from three criteria:…”

“…Neural recordings in living subjects performing TI indicate that single neurons in the brain can encode variables relevant to TI, including symbolic distance [62, 63]. It remains unclear what collective neural process or activity pattern implements the comparison operation – akin to a ‘>‘ operator – that generalizes transitivity to novel combinations of items (test cases).…”