Cognitive Mechanisms Underlying Prosocial Decision Making in Callous-Unemotional Traits.

Callous-unemotional (CU) traits are characterized by a lack of prosocial emotions, which has been demonstrated with prosocial behavior paradigms. While shaping our understanding of prosocial behavior in youth with CU traits, most of this work relies on outcomes that don't reliably capture cognitive processes during prosocial behavior. Examining prosocial cognitive processes can cue researchers into cognitive mechanisms underlying core impairments of CU traits. Drift diffusion modeling is a valuable tool for elucidating more precise outcomes of latent cognitive processes during forced choice tasks such as drift rate (information accumulation toward a decision boundary) and threshold separation (amount of information considered) as well as metrics outside of the decision-making processing including bias (starting point in decision process) and non-decision time (cognitive processes outside of choice). In a sample of 87 adolescents (12-14, 49% female) we applied diffusion modeling to a prosocial behavior task in which participants either accepted or rejected trials where a real monetary value was given to them and taken away from a charity (self-serving trial) or money was given to a charity and taken from them (donation trial). Results revealed that CU traits associated with information accumulation toward accepting self-serving trials. Exploratory sex differences suggested males trended toward rejecting donation trials and females considered more information during self-serving trials. CU trait associations were independent of conduct problems. Results suggest a unique cognitive profile that are differentiated by sex at higher CU traits when making prosocial decisions involving knowledge accumulation toward self-serving decisions.

Laminar segregation of sensory coding and behavioral readout in macaque V4.

Neurons in sensory areas of the neocortex are known to represent information both about sensory stimuli and behavioral state, but how these 2 disparate signals are integrated across cortical layers is poorly understood. To study this issue, we measured the coding of visual stimulus orientation and of behavioral state by neurons within superficial and deep layers of area V4 in monkeys while they covertly attended or prepared eye movements to visual stimuli. We show that whereas single neurons and neuronal populations in the superficial layers conveyed more information about the orientation of visual stimuli than neurons in deep layers, the opposite was true of information about the behavioral relevance of those stimuli. In particular, deep layer neurons encoded greater information about the direction of planned eye movements than superficial neurons. These results suggest a division of labor between cortical layers in the coding of visual input and visually guided behavior.

Symbol addition by monkeys provides evidence for normalized quantity coding.

Weber's law can be explained either by a compressive scaling of sensory response with stimulus magnitude or by a proportional scaling of response variability. These two mechanisms can be distinguished by asking how quantities are added or subtracted. We trained Rhesus monkeys to associate 26 distinct symbols with 0-25 drops of reward, and then tested how they combine, or add, symbolically represented reward magnitude. We found that they could combine symbolically represented magnitudes, and they transferred this ability to a novel symbol set, indicating that they were performing a calculation, not just memorizing the value of each combination. The way they combined pairs of symbols indicated neither a linear nor a compressed scale, but rather a dynamically shifting, relative scaling.