The exact anatomical localization of right hemisphere lesions that lead to left spatial neglect is still debated. The effect of confounding factors such as acute diaschisis and hypoperfusion, visual field defects, and lesion size may account for conflicting results that have been reported in the literature. Here, we present a comprehensive anatomical investigation of the gray- and white matter lesion correlates of left spatial neglect, which was run in a sample 58 patients with subacute or chronic vascular strokes in the territory of the right middle cerebral artery. Standard voxel-based correlates confirmed the role played by lesions in the posterior parietal cortex (supramarginal gyrus, angular gyrus, and temporal-parietal junction), in the frontal cortex (frontal eye field, middle and inferior frontal gyrus), and in the underlying parietal-frontal white matter. Using a new diffusion tensor imaging-based atlas of the human brain, we were able to run, for the first time, a detailed analysis of the lesion involvement of subcortical white matter pathways. The results of this analysis revealed that, among the different pathways linking parietal with frontal areas, damage to the second branch of the superior longitudinal fasciculus (SLF II) was the best predictor of left spatial neglect. The group study also revealed a subsample of patients with neglect due to focal lesion in the lateral-dorsal portion of the thalamus, which connects the premotor cortex with the inferior parietal lobule. The relevance of fronto-parietal disconnection was further supported by complete in vivo tractography dissection of white matter pathways in 2 patients, one with and the other without signs of neglect. These 2 patients were studied both in the acute phase and 1 year after stroke and were perfectly matched for age, handedness, stroke onset, lesion size, and for cortical lesion involvement. Taken together, the results of the present study support the hypothesis that anatomical disconnections leading to a functional breakdown of parietal-frontal networks are an important pathophysiological factor leading to chronic left spatial neglect. Here, we propose that different loci of SLF disconnection on the rostro-caudal axis can also be associated with disconnection of short-range white matter pathways within the frontal or parietal areas. Such different local disconnection patterns can play a role in the important clinical variability of the neglect syndrome.

Anticipating a potential benefit and how difficult it will be to obtain it are valuable skills in a constantly changing environment. In the human brain, the anticipation of reward is encoded by the Anterior Cingulate Cortex (ACC) and Striatum. Naturally, potential rewards have an incentive quality, resulting in a motivational effect improving performance. Recently it has been proposed that an upcoming task requiring effort induces a similar anticipation mechanism as reward, relying on the same cortico-limbic network. However, this overlapping anticipatory activity for reward and effort has only been investigated in a perceptual task. Whether this generalizes to high-level cognitive tasks remains to be investigated. To this end, an fMRI experiment was designed to investigate anticipation of reward and effort in cognitive tasks. A mental arithmetic task was implemented, manipulating effort (difficulty), reward, and delay in reward delivery to control for temporal confounds. The goal was to test for the motivational effect induced by the expectation of bigger reward and higher effort. The results showed that the activation elicited by an upcoming difficult task overlapped with higher reward prospect in the ACC and in the striatum, thus highlighting a pivotal role of this circuit in sustaining motivated behavior.

Voluntary orienting of visual attention is conventionally measured in tasks with predictive central cues followed by frequent valid targets at the cued location and by infrequent invalid targets at the uncued location. This implies that invalid targets entail both spatial reorienting of attention and breaching of the expected spatial congruency between cues and targets. Here, we used event-related functional magnetic resonance imaging (fMRI) to separate the neural correlates of the spatial and expectancy components of both endogenous orienting and stimulus-driven reorienting of attention. We found that during endogenous orienting with predictive cues, there was a significant deactivation of the right Temporal-Parietal Junction (TPJ). We also discovered that the lack of an equivalent deactivation with nonpredictive cues was matched to drop in attentional costs and preservation of attentional benefits. The right TPJ showed equivalent responses to invalid targets following predictive and nonpredictive cues. On the contrary, infrequent-unexpected invalid targets following predictive cues specifically activated the right Middle and Inferior Frontal Gyrus (MFG-IFG). Additional comparisons with spatially neutral trials demonstrated that, independently of cue predictiveness, valid targets activate the left TPJ, whereas invalid targets activate both the left and right TPJs. These findings show that the selective right TPJ activation that is found in the comparison between invalid and valid trials results from the reciprocal cancelling of the different activations that in the left TPJ are related to the processing of valid and invalid targets. We propose that left and right TPJs provide "matching and mismatching to attentional template" signals. These signals enable reorienting of attention and play a crucial role in the updating of the statistical contingency between cues and targets.

Optimal decision-making is based on integrating information from several dimensions of decisional space (e.g., reward expectation, cost estimation, effort exertion). Despite considerable empirical and theoretical efforts, the computational and neural bases of such multidimensional integration have remained largely elusive. Here we propose that the current theoretical stalemate may be broken by considering the computational properties of a cortical-subcortical circuit involving the dorsal anterior cingulate cortex (dACC) and the brainstem neuromodulatory nuclei: ventral tegmental area (VTA) and locus coeruleus (LC). From this perspective, the dACC optimizes decisions about stimuli and actions, and using the same computational machinery, it also modulates cortical functions (meta-learning), via neuromodulatory control (VTA and LC). We implemented this theory in a novel neuro-computational model–the Reinforcement Meta Learner (RML). We outline how the RML captures critical empirical findings from an unprecedented range of theoretical domains, and parsimoniously integrates various previous proposals on dACC functioning.