On the Influence of Reward on Action-Effect Binding

Ideomotor theory states that the formation of anticipatory representations about the perceptual consequences of an action [i.e., action-effect (A-E) binding] provides the functional basis of voluntary action control. A host of studies have demonstrated that A-E binding occurs fast and effortlessly, yet little is known about cognitive and affective factors that influence this learning process. In the present study, we sought to test whether the motivational value of an action modulates the acquisition of A-E associations. To this end, we linked specific actions with monetary incentives during the acquisition of novel A-E mappings. In a subsequent test phase, the degree of binding was assessed by presenting the former effect stimuli as task-irrelevant response primes in a forced-choice response task, absent reward. Binding, as indexed by response priming through the former action-effects, was only found for reward-related A-E mappings. Moreover, the degree to which reward associations modulated the binding strength was predicted by individuals’ trait sensitivity to reward. These observations indicate that the association of actions and their immediate outcomes depends on the motivational value of the action during learning, as well as on the motivational disposition of the individual. On a larger scale, these findings also highlight the link between ideomotor theories and reinforcement-learning theories, providing an interesting perspective for future research on anticipatory regulation of behavior

Goal-seeking compresses neural codes for space in the human hippocampus and orbitofrontal cortex

Humans can navigate flexibly to meet their goals. Here, we asked how the neural representation of allocentric space is distorted by goal-directed behavior. Participants navigated an agent to two successive goal locations in a grid world environment comprising four interlinked rooms, with a contextual cue indicating the conditional dependence of one goal location on another. Examining the neural geometry by which room and context were encoded in fMRI signals, we found that map-like representations of the environment emerged in both hippocampus and neocortex. Cognitive maps in hippocampus and orbitofrontal cortices were compressed so that locations cued as goals were coded together in neural state space, and these distortions predicted successful learning. This effect was captured by a computational model in which current and prospective locations are jointly encoded in a place code, providing a theory of how goals warp the neural representation of space in macroscopic neural signals

Neural coding for instruction-based task sets in human frontoparietal and visual cortex

Task preparation has traditionally been thought to rely upon persistent memory representations of instructions that permit their execution after delays. Accumulating evidence suggests, however, that accurate retention of task knowledge can be insufficient for successful performance. Here, we hypothesized that instructed facts would be organized into a task set, a temporary coding scheme that proactively tunes sensorimotor pathways based on instructions to enable highly efficient “reflex-like” performance. We devised a paradigm requiring either implementation or memorization of novel stimulus-response mapping instructions, and used multivoxel pattern analysis of neuroimaging data to compare neural coding of instructions during the pre-target phase. Although participants could retain instructions under both demands, we observed striking differences in their representation. To-be-memorized instructions could only be decoded from mid-occipital and posterior parietal cortices, consistent with previous work on visual short-term memory storage. By contrast, to-be- implemented instructions could also be decoded from frontoparietal “multiple- demand” regions, and dedicated visual areas, implicated in processing instructed stimuli. Neural specificity in the latter correlated with performance speed only when instructions were prepared, likely reflecting the pre-activation of instructed decision circuits. Together, these data illuminate how the brain proactively optimizes performance, and help dissociate neural mechanisms supporting task control and short- term memory storage

Prospective task knowledge improves working memory-guided behaviour

Working memory (WM) is the ability to keep information online for a forthcoming task. WM theories have tended to focus on how sensory information is maintained, and less on how WM content is used for guiding behaviour. Here we ask if WM is supported by a transformation of sensory memoranda into task-sets that are optimised for task-dependent responses. Thirty participants performed two different WM tasks; they remembered the tilt of oriented bars for either a rotation-discrimination task or a change-detection task. Task context was instructed either in advance (fixed task blocks) or at probe onset (mixed task blocks). If WM content is configured in a task-dependent format, performance should benefit from foreknowledge of the upcoming task. In line with this prediction, we found that WM accuracy was higher when participants had advance knowledge of the task context. Even if WM content can be configured as a task-set, perhaps only one item is optimised for guiding behaviour. If so, retro-cued prioritization may be supported by a transformation of the selected item from a sensory to a task-oriented code. We included a retro-cue on half of the trials to test the second hypothesis that task-foreknowledge enhances retro-cued prioritization. Interestingly, the benefits of task foreknowledge were independent of the benefits incurred by retro-cueing, indicating that attentional selection is sufficient for prioritization of WM content. Together, these results provide preliminary evidence that WM coding may be task-dependent, but neuroimaging studies are needed to elucidate the precise mechanisms by which task foreknowledge facilitates WM-guided behaviour

Co-Activation-Based Parcellation of the Lateral Prefrontal Cortex Delineates the Inferior Frontal Junction Area.

The inferior frontal junction (IFJ) area, a small region in the posterior lateral prefrontal cortex (LPFC), has received increasing interest in recent years due to its central involvement in the control of action, attention, and memory. Yet, both its function and anatomy remain controversial. Here, we employed a meta-analytic parcellation of the left LPFC to show that the IFJ can be isolated based on its specific functional connections. A seed region, oriented along the left inferior frontal sulcus (IFS), was subdivided via cluster analyses of voxel-wise whole-brain co-activation patterns. The ensuing clusters were characterized by their unique connections, the functional profiles of associated experiments, and an independent topic mapping approach. A cluster at the posterior end of the IFS matched previous descriptions of the IFJ in location and extent and could be distinguished from a more caudal cluster involved in motor control, a more ventral cluster involved in linguistic processing, and 3 more rostral clusters involved in other aspects of cognitive control. Overall, our findings highlight that the IFJ constitutes a core functional unit within the frontal lobe and delineate its borders. Implications for the IFJ's role in human cognition and the organizational principles of the frontal lobe are discussed

Neural Coding for Instruction-Based Task Sets in Human Frontoparietal and Visual Cortex

Task preparation has traditionally been thought to rely upon persistent memory representations of instructions that permit their execution after delays. Accumulating evidence suggests, however, that accurate retention of task knowledge can be insufficient for successful performance. Here, we hypothesized that instructed facts would be organized into a task set, a temporary coding scheme that proactively tunes sensorimotor pathways based on instructions to enable highly efficient “reflex-like” performance. We devised a paradigm requiring either implementation or memorization of novel stimulus-response mapping instructions, and used multivoxel pattern analysis of neuroimaging data to compare neural coding of instructions during the pre-target phase. Although participants could retain instructions under both demands, we observed striking differences in their representation. To-be-memorized instructions could only be decoded from mid-occipital and posterior parietal cortices, consistent with previous work on visual short-term memory storage. By contrast, to-be- implemented instructions could also be decoded from frontoparietal “multiple- demand” regions, and dedicated visual areas, implicated in processing instructed stimuli. Neural specificity in the latter correlated with performance speed only when instructions were prepared, likely reflecting the pre-activation of instructed decision circuits. Together, these data illuminate how the brain proactively optimizes performance, and help dissociate neural mechanisms supporting task control and short- term memory storage