Spatiotemporal Dynamics of Affective and Semantic Valence Among Women

The inter-related effects of alcohol use severity and sleep deficiency on semantic processing in young adults

BACKGROUND

Both alcohol misuse and sleep deficiency are associated with deficits in semantic processing. However, alcohol misuse and sleep deficiency are frequently comorbid and their inter-related effects on semantic processing as well as the underlying neural mechanisms remain to be investigated.

METHODS

We curated the Human Connectome Project data of 973 young adults (508 women) to examine the neural correlates of semantic processing in link with the severity of alcohol use and sleep deficiency. The latter were each evaluated using the first principal component (PC1) of principal component analysis of all drinking metrics and the Pittsburgh Sleep Quality Index (PSQI). We employed path modeling to elucidate the interplay among clinical, behavioral, and neural variables.

RESULTS

Among women, we observed a significant negative correlation between the left precentral gyrus (PCG) and PSQI scores. Mediation analysis revealed that the left PCG activity fully mediated the relationship between PSQI scores and word comprehension in language tasks. In women alone also, the right middle frontal gyrus (MFG) exhibited a significant negative correlation with PC1. The best path model illustrated the associations among PC1, PSQI scores, PCG activity, and MFG activation during semantic processing in women.

CONCLUSIONS

Alcohol misuse may lead to reduced MFG activation while sleep deficiency hinder semantic processing by suppressing PCG activity in women. The pathway model underscores the influence of sleep quality and alcohol consumption severity on semantic processing in women, suggesting that sex differences in these effects need to be further investigated.

The spread of affective and semantic valence representations across states

In many decision problems, outcomes are not reached after a single action but rather after a series of events or states. To optimize decisions over multiple states, representations of how good or bad the outcomes are, that is, the outcomes' valence, should spread across states. One mechanism for valence spreading is a temporal, state-independent process in which a single valence representation is updated when an outcome is experienced and fades away afterwards. Each state's valence is based on its temporal proximity to the experienced outcome. An alternative, state-dependent mechanism relies on the structure of transitions between states, updating a separate valence representation for each state according to its spatial distance from the outcomes. We examined how these mechanistic accounts shape the spread of two formats of valence representation, feelings (affective valence) and knowledge (semantic valence), between states. In two pre-registered experiments (N = 585), we used a novel task in which participants move in a four-state maze, one of which contains an outcome. The participants provide self-reports of affective and semantic valence throughout the maze and after finishing it. Results show that the affective representation of negative valence is more localized in state-space than the semantic representation. We also found evidence for the relative reliance of the affective valence on a temporal, state-independent mechanism and of the semantic valence on a structured, state-dependent mechanism. Our findings provide mechanistic accounts for the differences between affective and semantic valence representations and indicate how such representations may play a role in associative learning and decision-making.

Temporal dynamics of the semantic versus affective representations of valence during reversal learning

Valence, the representation of a stimulus in terms of good or bad, plays a central role in models of affect, value-based learning theories, and value-based decision-making models. Previous work used Unconditioned Stimulus (US) to support a theoretical division between two different types of valence representations for a stimulus: the semantic representation of valence, i.e., stored accumulated knowledge about the value of the stimulus, and the affective representation of valence, i.e., the valence of the affective response to this stimulus. The current work extended past research by using a neutral Conditioned Stimulus (CS) in the context of reversal learning, a type of associative learning. The impact of expected uncertainty (the variability of rewards) and unexpected uncertainty (reversal) on the evolving temporal dynamics of the two types of valence representations of the CS was tested in two experiments. Results show that in an environment presenting the two types of uncertainty, the adaptation process (learning rate) of the choices and of the semantic valence representation is slower than the adaptation of the affective valence representation. In contrast, in environments with only unexpected uncertainty (i.e., fixed rewards), there is no difference in the temporal dynamics of the two types of valence representations. Implications for models of affect, value-based learning theories, and value-based decision-making models are discussed.