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Generating and updating probabilistic models of the environment is a fundamental modus operandi of the human brain. Although crucial for various cognitive functions, the neural mechanisms of these inference processes remain to be elucidated. Here, we show the causal involvement of the right temporoparietal junction (rTPJ) in updating probabilistic beliefs and we provide new insights into the chronometry of the process by combining online transcranial magnetic stimulation (TMS) with computational modeling of behavioral responses. Female and male participants performed a modified location-cueing paradigm, where false information about the percentage of cue validity (%CV) was provided in half of the experimental blocks to prompt updating of prior expectations. Online double-pulse TMS over rTPJ 300 ms (but not 50 ms) after target appearance selectively decreased participants' updating of false prior beliefs concerning %CV, reflected in a decreased learning rate of a Rescorla-Wagner model. Online TMS over rTPJ also impacted on participants' explicit beliefs, causing them to overestimate %CV. These results confirm the involvement of rTPJ in updating of probabilistic beliefs, thereby advancing our understanding of this area's function during cognitive processing. SIGNIFICANCE STATEMENT Contemporary views propose that the brain maintains probabilistic models of the world to minimize surprise about sensory inputs. Here, we provide evidence that the right temporoparietal junction (rTPJ) is causally involved in this process. Because neuroimaging has suggested that rTPJ is implicated in divergent cognitive domains, the demonstration of an involvement in updating internal models provides a novel unifying explanation for these findings. We used computational modeling to characterize how participants change their beliefs after new observations. By interfering with rTPJ activity through online transcranial magnetic stimulation, we showed that participants were less able to update prior beliefs with TMS delivered at 300 ms after target onset., (Copyright © 2017 the authors 0270-6474/17/375419-10$15.00/0.)

Predictions about upcoming events influence how we perceive and respond to our environment. There is increasing evidence that predictions may be generated based upon previous observations following Bayesian principles, but little is known about the underlying cortical mechanisms and their specificity for different cognitive subsystems. The present study aimed at identifying common and distinct neural signatures of predictive processing in the spatial attentional and motor intentional system. Twenty-three female and male healthy human volunteers performed two probabilistic cueing tasks with either spatial or motor cues while lying in the fMRI scanner. In these tasks, the percentage of cue validity changed unpredictably over time. Trialwise estimates of cue predictability were derived from a Bayesian observer model of behavioral responses. These estimates were included as parametric regressors for analyzing the BOLD time series. Parametric effects of cue predictability in valid and invalid trials were considered to reflect belief updating by precision-weighted prediction errors. The brain areas exhibiting predictability-dependent effects dissociated between the spatial attention and motor intention task, with the right temporoparietal cortex being involved during spatial attention and the left angular gyrus and anterior cingulate cortex during motor intention. Connectivity analyses revealed that all three areas showed predictability-dependent coupling with the right hippocampus. These results suggest that precision-weighted prediction errors of stimulus locations and motor responses are encoded in distinct brain regions, but that crosstalk with the hippocampus may be necessary to integrate new trialwise outcomes in both cognitive systems. SIGNIFICANCE STATEMENT The brain is able to infer the environments' statistical structure and responds strongly to expectancy violations. In the spatial attentional domain, it has been shown that parts of the attentional networks are sensitive to the predictability of stimuli. It remains unknown, however, whether these effects are ubiquitous or if they are specific for different cognitive systems. The present study compared the influence of model-derived cue predictability on brain activity in the spatial attentional and motor intentional system. We identified areas with distinct predictability-dependent activation for spatial attention and motor intention, but also common connectivity changes of these regions with the hippocampus. These findings provide novel insights into the generality and specificity of predictive processing signatures in the human brain., (Copyright © 2017 the authors 0270-6474/17/375334-11$15.00/0.)

The deployment of visuospatial attention and the programming of saccades are governed by the inferred likelihood of events. In the present study, we combined computational modeling of psychophysical data with fMRI to characterize the computational and neural mechanisms underlying this flexible attentional control. Sixteen healthy human subjects performed a modified version of Posner's location-cueing paradigm in which the percentage of cue validity varied in time and the targets required saccadic responses. Trialwise estimates of the certainty (precision) of the prediction that the target would appear at the cued location were derived from a hierarchical Bayesian model fitted to individual trialwise saccadic response speeds. Trial-specific model parameters then entered analyses of fMRI data as parametric regressors. Moreover, dynamic causal modeling (DCM) was performed to identify the most likely functional architecture of the attentional reorienting network and its modulation by (Bayes-optimal) precision-dependent attention. While the frontal eye fields (FEFs), intraparietal sulcus, and temporoparietal junction (TPJ) of both hemispheres showed higher activity on invalid relative to valid trials, reorienting responses in right FEF, TPJ, and the putamen were significantly modulated by precision-dependent attention. Our DCM results suggested that the precision of predictability underlies the attentional modulation of the coupling of TPJ with FEF and the putamen. Our results shed new light on the computational architecture and neuronal network dynamics underlying the context-sensitive deployment of visuospatial attention., Significance Statement: Spatial attention and its neural correlates in the human brain have been studied extensively with the help of fMRI and cueing paradigms in which the location of targets is pre-cued on a trial-by-trial basis. One aspect that has so far been neglected concerns the question of how the brain forms attentional expectancies when no a priori probability information is available but needs to be inferred from observations. This study elucidates the computational and neural mechanisms under which probabilistic inference governs attentional deployment. Our results show that Bayesian belief updating explains changes in cortical connectivity; in that directional influences from the temporoparietal junction on the frontal eye fields and the putamen were modulated by (Bayes-optimal) updates., (Copyright © 2015 Vossel et al.)

The exact mechanisms whereby the cholinergic neurotransmitter system contributes to attentional processing remain poorly understood. Here, we applied computational modeling to psychophysical data (obtained from a spatial attention task) under a psychopharmacological challenge with the cholinesterase inhibitor galantamine (Reminyl). This allowed us to characterize the cholinergic modulation of selective attention formally, in terms of hierarchical Bayesian inference. In a placebo-controlled, within-subject, crossover design, 16 healthy human subjects performed a modified version of Posner's location-cueing task in which the proportion of validly and invalidly cued targets (percentage of cue validity, % CV) changed over time. Saccadic response speeds were used to estimate the parameters of a hierarchical Bayesian model to test whether cholinergic stimulation affected the trial-wise updating of probabilistic beliefs that underlie the allocation of attention or whether galantamine changed the mapping from those beliefs to subsequent eye movements. Behaviorally, galantamine led to a greater influence of probabilistic context (% CV) on response speed than placebo. Crucially, computational modeling suggested this effect was due to an increase in the rate of belief updating about cue validity (as opposed to the increased sensitivity of behavioral responses to those beliefs). We discuss these findings with respect to cholinergic effects on hierarchical cortical processing and in relation to the encoding of expected uncertainty or precision., (Copyright © 2014 the authors 0270-6474/14/3415735-08$15.00/0.)

The right intraparietal sulcus (rIPS) is a key region for the endogenous control of selective visual attention in the human brain. Previous studies suggest that the rIPS is especially involved in top-down control and spatial distribution of attention across both visual hemifields. We further explored these attentional functions using transcranial direct current stimulation (tDCS) of the rIPS to modulate behavioral performance in a partial report task. Performance was analyzed according to the theory of visual attention (TVA) (Bundesen, 1990), which provides a computational framework to investigate different parameters of visuo-attentional processing such as top-down control, attentional weighting, capacity of visual short term memory, and processing speed. We investigated the effects of different tDCS current strengths (1 mA and 2 mA) in two experiments: 1 mA tDCS (anodal, cathodal, sham) did not affect any of the TVA parameters, but cathodal 2 mA stimulation significantly enhanced top-down control as evidenced by a reduction of the α parameter of TVA, regardless of hemifield. This differential impact on the top-down control component of attentional processing suggests that the horizontal rIPS is mainly involved in attentional selection as none of the spatial or resource variables of TVA were altered. Furthermore, the data add evidence to previous work highlighting (1) the importance of using appropriate current strength in stimulation protocols, and (2) that the often reported inhibitory effect of cathodal stimulation in e.g., motor tasks might not extend to cognitive paradigms.

How the human brain reconstructs the three-dimensional (3D) world from two-dimensional (2D) retinal images has received a great deal of interest as has how we shift attention in 2D space. In contrast, it remains poorly understood how visuospatial attention is shifted in depth. In this fMRI study, by constructing a virtual 3D environment in the MR scanner and by presenting targets either close to or far from the participants in an adapted version of the Posner spatial-cueing paradigm, we investigated the behavioral and neural mechanisms underlying visuospatial orienting/reorienting in depth. At the behavioral level, although covering the same spatial distance, attentional reorienting to objects unexpectedly appearing closer to the observer and in the unattended hemispace was faster than reorienting to unexpected objects farther away. At the neural level, we found that in addition to the classical attentional reorienting system in the right temporoparietal junction, two additional brain networks were differentially involved in aspects of attentional reorienting in depth. First, bilateral premotor cortex reoriented visuospatial attention specifically along the third dimension of visual space (i.e., from close to far or vice versa), compared with attentional reorienting within the same depth plane. Second, a network of areas reminiscent of the human "default-mode network," including posterior cingulate cortex, orbital prefrontal cortex, and left angular gyrus, was involved in the neural interaction between depth and attentional orienting, by boosting attentional reorienting to unexpected objects appearing both closer to the observer and in the unattended hemispace.