Biology subjects

Lockwood, P.

Publications and source records attributed to Lockwood, P..

5 recordsLinked to original sources

bioRxiv2026

Preserved self-other integration during social decision making among individuals with elevated autistic traits

Autistic people can find social interactions difficult to navigate, traditionally attributed to difficulties in taking others perspectives. However, we have a limited understanding of how autistic people integrate self and other information efficiently during social decision-making. We conducted four highly powered experiments (total N = 1,621) to determine whether autistic traits affect two aspects of self-other integration during social decision making: self-bias and social basis function use. Using Bayesian analyses, we found strong support for the absence of a relationship between autistic traits and either aspect of social decision making, even after controlling for potential confounds (BF01 = 32.13 for self-bias, BF01 = 7.04 for social basis function use). Our results indicate that variations along autistic traits do not impact how people prioritise self-relevant information (self-bias) or utilize compressed social patterns of interaction (social basis function use) to guide their decisions about oneself and other people. These findings nuance the conceptualisation of social-cognitive processes across autistic traits while highlighting the need for large samples to validate null effects.

neuroscience↗

bioRxiv2021

Distinct neural representations for prosocial and self-benefitting effort

Prosocial behaviours - actions that benefit others - are central to individual and societal well-being. Most prosocial acts are effortful. Yet, how the brain encodes effort costs when actions benefit others is unknown. Here, using a combination of multivariate representational similarity analysis and model-based univariate analysis during fMRI, we reveal how the costs of prosocial efforts are processed. Strikingly, we identified a unique neural signature of effort in the anterior cingulate gyrus for prosocial acts both when choosing to help others and when exerting force for their benefit. This pattern was absent for similar self-benefitting behaviour and correlated with individual levels of empathy. In contrast, the ventral tegmental area and the ventral insula signalled subjective value preferentially when choosing whether to exert effort to benefit oneself. These findings demonstrate partially distinct brain areas guide the evaluation and exertion of effort costs when acts are prosocial or self-benefitting.

neuroscience↗

bioRxiv2021

Oxytocin modulates neurocomputational mechanisms underlying prosocial reinforcement learning

Humans often act in the best interests of others. However, how we learn which actions result in good outcomes for other people and the neurochemical systems that support this prosocial learning remain poorly understood. Using computational models of reinforcement learning, functional magnetic resonance imaging and dynamic causal modelling, we examined how different doses of intranasal oxytocin, a neuropeptide linked to social cognition, impact how people learn to benefit others (prosocial learning) and whether this influence could be dissociated from how we learn to benefit ourselves (self-oriented learning). We show that a low dose of oxytocin prevented decreases in prosocial performance over time, despite no impact on self-oriented learning. Critically, oxytocin produced dose-dependent changes in the encoding of prediction errors (PE) in the midbrain-subgenual anterior cingulate cortex (sgACC) pathway specifically during prosocial learning. Our findings reveal a new role of oxytocin in prosocial learning by modulating computations of PEs in the midbrain-sgACC pathway.

neuroscience↗

bioRxiv2020

Ageing disrupts reinforcement learning whilst learning to help others is preserved

Reinforcement learning is a fundamental mechanism displayed by many species. However, adaptive behaviour depends not only on learning about actions and outcomes that affect ourselves, but also those that affect others. Here, using computational reinforcement learning models, we tested whether young (age 18-36) and older (age 60-80, total n=152) adults can learn to gain rewards for themselves, another person (prosocial), or neither individual (control). Detailed model comparison showed that a model with separate learning rates for each recipient best explained behaviour. Young adults were faster to learn when their actions benefitted themselves, compared to helping others. Strikingly, compared to younger adults, older adults showed preserved prosocial learning rates but reduced self-relevant learning rates. Moreover, psychopathic traits were lower in older adults and negatively correlated with prosocial learning. These findings suggest learning how to benefit others is preserved across the lifespan with implications for reinforcement learning and theories of healthy ageing.

neuroscience↗

bioRxiv2019

Neural signatures of model-free learning when avoiding harm to self and other

Moral behaviour requires learning how our actions help or harm others. Theoretical accounts of learning propose a key division between model-free algorithms that efficiently cache outcome values in actions and model-based algorithms that prospectively map actions to outcomes, a distinction that may be critical for moral learning. Here, we tested the engagement of these learning mechanisms and their neural basis as participants learned to avoid painful electric shocks for themselves and a stranger. We found that model-free learning was prioritized when avoiding harm to others compared to oneself. Model-free prediction errors for others relative to self were tracked in the thalamus/caudate at the time of the outcome. At the time of choice, a signature of model-free moral learning was associated with responses in subgenual anterior cingulate cortex (sgACC), and resisting this model-free influence was predicted by stronger connectivity between sgACC and dorsolateral prefrontal cortex. Finally, multiple behavioural and neural correlates of model-free moral learning varied with individual differences in moral judgment. Our findings suggest moral learning favours efficiency over flexibility and is underpinned by specific neural mechanisms.

neuroscience↗