TY - JOUR
T1 - Punishment insensitivity in humans is due to failures in instrumental contingency learning
AU - Jean-Richard-dit-Bressel, Philip
AU - Lee, Jessica C.
AU - Liew, Shi Xian
AU - Weidemann, Gabrielle
AU - Lovibond, Peter F.
AU - McNally, Gavan P.
PY - 2021
Y1 - 2021
N2 - Punishment maximises the probability of our individual survival by reducing behaviours that cause us harm, and also sustains trust and fairness in groups essential for social cohesion. However, some individuals are more sensitive to punishment than others and these differences in punishment sensitivity have been linked to a variety of decision-making deficits and psychopathologies. The mechanisms for why individuals differ in punishment sensitivity are poorly understood, although recent studies of conditioned punishment in rodents highlight a key role for punishment contingency detection (Jean-Richard-Dit-Bressel et al., 2019). Here, we applied a novel ‘Planets and Pirates’ conditioned punishment task in humans, allowing us to identify the mechanisms for why individuals differ in their sensitivity to punishment. We show that punishment sensitivity is bimodally distributed in a large sample of normal participants. Sensitive and insensitive individuals equally liked reward and showed similar rates of reward-seeking. They also equally disliked punishment and did not differ in their valuation of cues that signalled punishment. However, sensitive and insensitive individuals differed profoundly in their capacity to detect and learn volitional control over aversive outcomes. Punishment insensitive individuals did not learn the instrumental contingencies, so they could not withhold behaviour that caused punishment and could not generate appropriately selective behaviours to prevent impending punishment. These differences in punishment sensitivity could not be explained by individual differences in behavioural inhibition, impulsivity, or anxiety. This bimodal punishment sensitivity and these deficits in instrumental contingency learning are identical to those dictating punishment sensitivity in nonhuman animals, suggesting that they are general properties of aversive learning and decision-making.
AB - Punishment maximises the probability of our individual survival by reducing behaviours that cause us harm, and also sustains trust and fairness in groups essential for social cohesion. However, some individuals are more sensitive to punishment than others and these differences in punishment sensitivity have been linked to a variety of decision-making deficits and psychopathologies. The mechanisms for why individuals differ in punishment sensitivity are poorly understood, although recent studies of conditioned punishment in rodents highlight a key role for punishment contingency detection (Jean-Richard-Dit-Bressel et al., 2019). Here, we applied a novel ‘Planets and Pirates’ conditioned punishment task in humans, allowing us to identify the mechanisms for why individuals differ in their sensitivity to punishment. We show that punishment sensitivity is bimodally distributed in a large sample of normal participants. Sensitive and insensitive individuals equally liked reward and showed similar rates of reward-seeking. They also equally disliked punishment and did not differ in their valuation of cues that signalled punishment. However, sensitive and insensitive individuals differed profoundly in their capacity to detect and learn volitional control over aversive outcomes. Punishment insensitive individuals did not learn the instrumental contingencies, so they could not withhold behaviour that caused punishment and could not generate appropriately selective behaviours to prevent impending punishment. These differences in punishment sensitivity could not be explained by individual differences in behavioural inhibition, impulsivity, or anxiety. This bimodal punishment sensitivity and these deficits in instrumental contingency learning are identical to those dictating punishment sensitivity in nonhuman animals, suggesting that they are general properties of aversive learning and decision-making.
UR - https://hdl.handle.net/1959.7/uws:62883
U2 - 10.7554/eLife.69594
DO - 10.7554/eLife.69594
M3 - Article
SN - 2050-084X
VL - 10
JO - eLife
JF - eLife
M1 - e69594
ER -