Reward influences the allocation but not the availability of resources in visual working memory

Does value-based prioritization at working memory enhance long-term memory?

Research has demonstrated that individuals can direct their attention to valuable information in both working memory and long-term memory tasks with observable effects on performance. However, it is currently unclear whether prioritising an item for a working memory task automatically translates into a boost at long-term memory. This was examined in two experiments using relatively short (250 ms per item; Experiment 1) and longer (500 ms per item; Experiment 2) encoding times. Participants first completed a visual working memory task, in which they were presented with series of photographs of everyday objects. Following a brief delay (1,000 ms), they completed a four-alternative forced-choice test. Prior to encoding, participants were informed of the point values associated with each item. In some trials, the first item in the sequence was worth more points than the rest. In other trials, all items were equally valuable. After a filled delay, participants completed a surprise long-term memory task. At working memory, a value effect was reliably observed on recognition accuracy, along with some evidence of faster response times for high-value items. However, there was little consistent evidence of this effect automatically persisting into long-term memory. Thus, the benefits of attentional prioritization in working memory do not always translate into longer-term performance. More broadly, this provides further evidence that manipulations that enhance working memory performance do not necessarily enhance long-term memory.

Trying Harder: How Cognitive Effort Sculpts Neural Representations during Working Memory

While the exertion of mental effort improves performance on cognitive tasks, the neural mechanisms by which motivational factors impact cognition remain unknown. Here, we used fMRI to test how changes in cognitive effort, induced by changes in task difficulty, impact neural representations of working memory (WM). Participants (both sexes) were precued whether WM difficulty would be hard or easy. We hypothesized that hard trials demanded more effort as a later decision required finer mnemonic precision. Behaviorally, pupil size was larger and response times were slower on hard compared with easy trials suggesting our manipulation of effort succeeded. Neurally, we observed robust persistent activity during delay periods in the prefrontal cortex (PFC), especially during hard trials. Yet, details of the memoranda could not be decoded from patterns in prefrontal activity. In the patterns of activity in the visual cortex, however, we found strong decoding of memorized targets, where accuracy was higher on hard trials. To potentially link these across-region effects, we hypothesized that effort, carried by persistent activity in the PFC, impacts the quality of WM representations encoded in the visual cortex. Indeed, we found that the amplitude of delay period activity in the frontal cortex predicted decoded accuracy in the visual cortex on a trial-wise basis. These results indicate that effort-related feedback signals sculpt population activity in the visual cortex, improving mnemonic fidelity.

Working memory processes and intrinsic motivation: An EEG study

Processes typically encompassed by working memory (WM) include encoding, retention, and retrieval of information. Previous research has demonstrated that motivation can influence WM performance, although the specific WM processes affected by motivation are not yet fully understood. In this study, we investigated the effects of motivation on different WM processes, examining how task difficulty modulates these effects. We hypothesized that motivation level and personality traits of the participants (N = 48, 32 females; mean age = 21) would modulate the parietal alpha and frontal theta electroencephalography (EEG) correlates of WM encoding, retention, and retrieval phases of the Sternberg task. This effect was expected to be more pronounced under conditions of very high task difficulty. We found that increasing difficulty led to reduced accuracy and increased response time, but no significant relationship was found between motivation and accuracy. However, EEG data revealed that motivation influenced WM processes, as indicated by changes in alpha and theta oscillations. Specifically, higher levels of the Resilience trait-associated with mental toughness, hardiness, self-efficacy, achievement motivation, and low anxiety-were related to increased alpha desynchronization during encoding and retrieval. Increased scores of Subjective Motivation to perform well in the task were related to enhanced frontal midline theta during retention. Additionally, these effects were significantly stronger under conditions of high difficulty. These findings provide insights into the specific WM processes that are influenced by motivation, and underscore the importance of considering both task difficulty and intrinsic motivation in WM research.

Representation and computation in visual working memory

The ability to sustain internal representations of the sensory environment beyond immediate perception is a fundamental requirement of cognitive processing. In recent years, debates regarding the capacity and fidelity of the working memory (WM) system have advanced our understanding of the nature of these representations. In particular, there is growing recognition that WM representations are not merely imperfect copies of a perceived object or event. New experimental tools have revealed that observers possess richer information about the uncertainty in their memories and take advantage of environmental regularities to use limited memory resources optimally. Meanwhile, computational models of visuospatial WM formulated at different levels of implementation have converged on common principles relating capacity to variability and uncertainty. Here we review recent research on human WM from a computational perspective, including the neural mechanisms that support it.