The pursuit of goal-directed behaviour requires the integration of cognitive systems, particularly attention and motivation. Understanding how these systems converge within motor circuits has significant implications for systems neuroscience and clinical applications, including neurorehabilitation strategies for patients with movement disorders. Spatial attention, classically studied through Posner's cueing paradigm (Posner, 1980), enables efficient processing of environmental stimuli, whereas motivation provides the drive to engage with relevant targets. Reward-based incentives have been shown to powerfully influence visual selective attention, biasing neural resources towards behaviourally significant stimuli (Chelazzi et al., 2013). However how motivation shapes the relationship between attention and motor preparation at the neural level remains poorly understood. The dorsal premotor cortex (PMd) presents an ideal model for investigating this tripartite interaction. As a critical node for motor planning, the PMd receives converging inputs from both reward-processing regions and attention networks, positioning it as a potential integrator of these signals. In the research article ‘Motivational sharpening of the interaction between spatial attention and motor control: insights from the monkey dorsal premotor cortex’, Di Bello et al. (2025) present evidence that the PMd not only prepares movements but can dynamically encode target location in a manner that depends on both reward incentives and task demands. Di Bello et al. (2025) used two variations of a Posner-style cueing task in two adult male rhesus monkeys, allowing simultaneous examination of behavioural and neural responses (Di Bello et al., 2025). In both experiments, a coloured spatial cue from a touchscreen monitor indicated both the probable target location (80% validity) and the reward magnitude (3 versus 12 drops of juice depending on colour shown). The two tasks differed in their motor and attentional requirements. Experiment 1 involved simple target detection, requiring a motor response on every trial. Experiment 2 employed a Go/NoGo paradigm, where monkeys had to identify the target shape before deciding whether to respond, thus demanding both refined motor control and sustained visual attention. Neural recordings were obtained from 96-channel Utah arrays implanted in the left PMd, contralateral to the responding arm. The authors used time-resolved neural decoding with a regularized optimal linear estimator to track how target location information evolved across trial conditions. This multiunit activity approach enabled population-level analysis of neurons. Simultaneously the temporal dynamics, essential for understanding rapid sensorimotor transformations, were preserved. Behavioural results revealed distinct patterns across experiments. Both tasks showed the expected validity effect, with faster reaction times for valid trials (where the target appeared at the cued location) versus invalid trials (where it appeared on the opposite side), confirming successful attentional deployment. In Experiment 1, linear mixed-effects modelling revealed a main effect of reward in both monkeys, with high-reward trials producing faster responses. However no significant interaction was observed between reward and validity. In contrast, Experiment 2 revealed a significant interaction between reward and validity in both monkeys. High reward accelerated responses in valid trials, but this effect was attenuated or absent in invalid trials. These findings suggest that motivation specifically enhanced focused attention under conditions requiring executive motor control. Notably false alarm rates did not differ between reward conditions in Experiment 2, indicating that monkeys maintained inhibitory control even when higher rewards were at stake. The neural findings complemented these behavioural patterns. Using time-resolved decoding, the authors assessed how accurately the target's location (left or right) could be predicted from PMd population activity at each moment in a trial, where higher accuracy reflects a stronger spatial signal. In Experiment 1, reward did not significantly modulate this decoding accuracy around target onset (the moment the peripheral stimulus appeared). In contrast Experiment 2 revealed enhanced target location encoding in high-reward conditions in both monkeys, with this enhancement emerging around target presentation and, in one monkey, even before target onset. These findings suggest that when task demands require flexible motor control, the PMd more tightly couples reward signals with spatial representations. The effect of invalid cues on neural coding differed between tasks. Invalid targets, which require a rapid shift in attention away from the expected location, caused transient perturbations (drops in decoding accuracy relative to valid targets) in both experiments. However the direction of reward modulation was opposite. In Experiment 1 perturbations were more pronounced under low-reward conditions. In Experiment 2 perturbations were greater in high-reward conditions, with significant main effects of reward and trial type as well as their interaction. The authors interpret this as evidence that reward heightens the attentional focus on cued locations during demanding tasks, making reorientation more costly. A control analysis demonstrated that the target location code was functionally linked to movement execution: decoding accuracy remained high during reaching movements in Go trials but dropped sharply near the expected movement time in NoGo trials (where no movement was required), confirming the motor relevance of this neural signal. This study provides mechanistic insights into how the premotor cortex orchestrates goal-directed behaviour. The findings challenge purely motor-centric views of PMd function and reveal PMd's sensitivity to motivational context and task demands. For systems neuroscience these results suggest that theories of attention and motor interaction, such as the OPTIMAL framework (Wulf & Lewthwaite, 2016), may need to incorporate the dynamic, task-dependent nature of these relationships rather than treating motivation and attention as independent modulators. The clinical relevance of these findings merits consideration. Understanding how motivation modulates motor circuits could inform neurorehabilitation strategies, particularly for conditions affecting premotor regions. Neurosurgical approaches targeting the premotor cortex, whether for tumour resection or brain-machine interface implantation, may benefit from recognising how motivational state influences neural representations during motor planning. Furthermore disorders characterised by motivational deficits, such as Parkinson's disease or apathy syndromes, may involve disrupted reward and attention coupling in these circuits. Future studies could extend this work by examining whether similar principles apply to other premotor regions or to prefrontal areas more directly involved in executive control. Investigation in freely moving animals would help determine whether the reward-dependent modulation observed here, under constrained head-fixed conditions, generalises to the richer sensorimotor demands of natural behaviour. Additionally the two monkeys in this study demonstrated distinct proportions of reward- and cue-selective units, which may raise the question on whether individual variability in PMd composition contributes to differences in how motivation shapes attention–motor coupling. Finally extending these findings to different effectors, such as eye movements, and to more demanding task designs, would clarify whether the motivational sharpening reported here reflects a general principle of premotor function or is specific to the reaching and task conditions tested. Di Bello et al. (2025) advance our understanding of premotor cortex function by demonstrating that motivation does not simply hasten motor responses but specifically sharpens the interaction between attention and motor control depending on task requirements. Motivation enhances inhibition of unwanted movement, just as it promotes desired movement. As neural recording and decoding techniques continue to evolve, studies like this illuminate the computational role of motor cortical areas, revealing them not as passive executors of movements, but as active integrators of cognitive and motivational signals that shape how we interact with our environment. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. All authors report no competing interests. All authors have reviewed and approved the final version of the manuscript. All authors listed meet the criteria for authorship, and no qualified contributors have been omitted. None
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