The control of selective visuo-spatial attention is known to rely on multiple signals, including reward. While most attention control signals are well acknowledged to interact with each other, the case of reward has led to mixed findings supporting either its interaction with, or its independence from other signals. We addressed this issue using a 4-item search task that entailed spatially biased reward contingencies, with one of the four locations associated with high rewards for correct target discriminations. In different conditions, the target, a distractor or neither of them could be physically salient. Targets at the high-reward location did not enhance search performance. In contrast, and contrary to our initial expectations, salient distractors at the high-reward location interfered less with the discrimination of the task-relevant targets, reflecting gating mechanisms at the high-reward location. Exploratory analyses showed that, across participants, the degree of target and salient distractor gating at the high-reward location correlated with each other. In contrast to previous findings supporting attention capture by reward signals, we evidenced gating by reward.

Functional connectomics is a popular approach to investigate the neural underpinnings of developmental disorders of which attention deficit hyperactivity disorder (ADHD) is one of the most prevalent. Nonetheless, neuronal mechanisms driving the aberrant functional connectivity resulting in ADHD symptoms remain largely unclear. Whereas resting state activity reflecting intrinsic tonic background activity is only vaguely connected to behavioral effects, naturalistic neuroscience has provided means to measure phasic brain dynamics associated with overt manifestation of the symptoms. Here we collected functional magnetic resonance imaging (fMRI) data in three experimental conditions, an active virtual reality (VR) task where the participants execute goal-directed behaviors, a passive naturalistic Video Viewing task, and a standard Resting State condition. Thirty-nine children with ADHD and thirty-seven typically developing (TD) children participated in this preregistered study. Functional connectivity was examined with network-based statistics (NBS) and graph theoretical metrics. During the naturalistic VR task, the ADHD group showed weaker task performance and stronger functional connectivity than the TD group. Group differences in functional connectivity were observed in widespread brain networks: particularly subcortical areas showed hyperconnectivity in ADHD. More restricted group differences in functional connectivity were observed during the Video Viewing, and there were no group differences in functional connectivity in the Resting State condition. These observations were consistent across NBS and graph theoretical analyses, although NBS revealed more pronounced group differences. Furthermore, during the VR task and Video Viewing, functional connectivity in TD controls was associated with task performance during the measurement, while Resting State activity in TD controls was correlated with ADHD symptoms rated over six months. We conclude that overt expression of the symptoms is correlated with aberrant brain connectivity in ADHD. Furthermore, naturalistic paradigms where clinical markers can be coupled with simultaneously occurring brain activity may further increase the interpretability of psychiatric neuroimaging findings.

A fundamental limitation of fMRI based on the BOLD effect is its limited spatial specificity. This is because the BOLD signal reflects neurovascular coupling, leading to macrovascular changes that are not strictly limited to areas of increased neural activity. However, neuronal activation also induces microstructural changes within the brain parenchyma by modifying the diffusion of extracellular biological water. Therefore, diffusion-weighted imaging (DWI) has been applied in fMRI to overcome BOLD limits and better explain the mechanisms of functional activation, but the results obtained so far are not clear. This is because a DWI signal depends on many experimental variables: instrumental, physiological, and microstructural. Here, we hypothesize that the γ parameter of the fractional diffusion representation could be of particular interest for DW-fMRI applications, due to its proven dependence on local magnetic susceptibility and diffusion multi-compartmentalization. BOLD fMRI and DW-fMRI experiments were performed at 3T using an exemplar application to task-based activation of the human visual cortex. The results, corroborated by simulation, highlight that γ provides complementary information to conventional diffusion fMRI and γ can quantify cellular morphology changes and neurovascular regulation during neuronal activation with higher sensitivity and specificity than conventional BOLD fMRI and DW-fMRI.

Memory retrieval entails dynamic interactions between the medial temporal lobe and areas in the parietal and frontal cortices. Here, we tested the hypothesis that effective connectivity between the precuneus, in the medial parietal cortex, and the medial temporal cortex contributes to the subjective quality of remembering objects together with information about their rich spatio-temporal encoding context. During a 45 min encoding session, the participants were presented with pictures of objects while they actively explored a virtual town. The following day, under fMRI, participants were presented with images of objects and had to report whether: they recognized the object and could remember the place/time of encoding, the object was familiar only, or the object was new. The hippocampus/parahippocampus, the precuneus and the ventro-medial prefrontal cortex activated when the participants successfully recognized objects they had seen in the virtual town and reported that they could remember the place/time of these events. Analyses of effective connectivity showed that the influence exerted by the precuneus on the medial temporal cortex mediates this effect of episodic recollection. Our findings demonstrate the role of the inter-regional connectivity in mediating the subjective experience of remembering and underline the relevance of studying memory in contextually-rich conditions.

Visual attention can be guided by statistical regularities in the environment, that people implicitly learn from past experiences (statistical learning, SL). Moreover, a perceptually salient element can automatically capture attention, gaining processing priority through a bottom-up attentional control mechanism. The aim of our study was to investigate the dynamics of SL and if it shapes attentional target selection additively with salience processing, or whether these mechanisms interact, e.g. one gates the other. In a visual search task, we therefore manipulated target frequency (high vs. low) across locations while, in some trials, the target was salient in terms of colour. Additionally, halfway through the experiment, the high-frequency location changed to the opposite hemifield. EEG activity was simultaneously recorded, with a specific interest in two markers related to target selection and post-selection processing, respectively: N2pc and SPCN. Our results revealed that both SL and saliency significantly enhanced behavioural performance, but also interacted with each other, with an attenuated saliency effect at the high-frequency target location, and a smaller SL effect for salient targets. Concerning processing dynamics, the benefit of salience processing was more evident during the early stage of target selection and processing, as indexed by a larger N2pc and early-SPCN, whereas SL modulated the underlying neural activity particularly later on, as revealed by larger late-SPCN. Furthermore, we showed that SL was rapidly acquired and adjusted when the spatial imbalance changed. Overall, our findings suggest that SL is flexible to changes and, combined with salience processing, jointly contributes to establishing attentional priority.

The present study aims to investigate how the competition between visual elements is solved by top-down and/or statistical learning (SL) attentional control (AC) mechanisms when active together. We hypothesized that the "winner" element that will undergo further processing is selected either by one AC mechanism that prevails over the other, or by the joint activity of both mechanisms. To test these hypotheses, we conducted a visual search experiment that combined an endogenous cueing protocol (valid vs. neutral cue) and an imbalance of target frequency distribution across locations (high- vs. low-frequency location). The unique and combined effects of top-down control and SL mechanisms were measured on behaviour and amplitudes of three evoked-response potential (ERP) components (i.e., N2pc, P1, CNV) related to attentional processing. Our behavioural results showed better performance for validly cued targets and for targets in the high-frequency location. The two factors were found to interact, so that SL effects emerged only in the absence of top-down guidance. Whereas the CNV and P1 only displayed a main effect of cueing, for the N2pc we observed an interaction between cueing and SL, revealing a cueing effect for targets in the low-frequency condition, but not in the high-frequency condition. Thus, our data support the view that top-down control and SL work in a conjoint, integrated manner during target selection. In particular, SL mechanisms are reduced or even absent when a fully reliable top-down guidance of attention is at play.

Prospective Memory (PM) entails a set of executive processes primarily associated with the activation of frontal and parietal regions. Both the number of PM-targets to be monitored (i.e. task load) and the relationship between the type of PM-targets and the ongoing (ONG) task (i.e. task focality) can impact executive monitoring and PM performance. In the present imaging study, we manipulated load and focality of an event-based PM task to test the hypothesis that common resources engage in situations requiring high levels of cognitive control: that is, in high-load (i.e. monitor multiple PM-targets) and non-focal conditions (i.e. monitor at the same time letters' identity and color). We investigated monitoring-related and detection-related processes by assessing behavior and brain activity separately for ONG trials (monitoring) and PM-targets (detection). At the behavioral level, we found a significant interaction between load and focality during detection, with slowest reaction times for focal, high-load PM-targets. The imaging analyses of the detection phase revealed the activation of the left intraparietal sulcus in the high-load conditions. Both in the monitoring and the detection phases, we found overlapping effects of non-focality and low-load in the fusiform gyrus. Our results suggest that under low-load conditions, cognitive control operates via early selection mechanisms in the ventral occipito-temporal cortex. By contrast, high-load conditions entail control at later processing stages within the dorsal parietal cortex. We conclude that load and focality operate via different mechanisms, with the level of task load largely determining how cognitive control selects the most relevant information.

We examined the effect of combined top-down and bottom-up attentional control sources in easy and difficult visual search tasks. Applying a new analysis on previously acquired data, we focused on the sustained posterior contralateral negativity (SPCN) and the response-locked posterior contralateral negativity (RLpcN), to better understand processes following target selection. We used the signed-area approach to measure the negative area, where the signal was either locked to the target or the response onsets. We further split the RLpcN into an early and a late segment to capture the dynamics of selection and post-selection processes. In Experiment 1, participants reported the orientation of a uniquely tilted target. In Experiment 2, participants reported the position of a small gap within the uniquely tilted target. In both experiments, endogenous cues manipulated top-down attention (valid vs. neutral), and salient color singletons (either the target or a distractor) manipulated bottom-up attention. We hypothesized that the SPCN and the later segment of the RLpcN would be modulated by task difficulty and target salience, as they are associated with post-selection processes, such as response selection and working memory. The early segment of the RLpcN was hypothesized to be modulated by the cueing manipulation and presence of a salient distractor, as they affect target selection. An effect of distractor presence was observed on the early segment of the RLpcN, and our results further supported the hypotheses regarding the SPCN and the later segment of the RLpcN, providing novel insights into post-selection processes in visual search.

Attention selects behaviorally relevant inputs for in-depth processing. Beside the role of traditional signals related to goal-directed and stimulus-driven control, a debate exists regarding the mechanisms governing the effect of statistical regularities on attentional selection, and how these are integrated with other control signals. Using a visuo-spatial search task under fMRI, we tested the joint effects of statistical regularities and stimulus-driven salience. We found that both types of signals modulated occipital activity in a spatially specific manner. Salience acted primarily by reducing the attention bias towards the target location when associated with irrelevant distractors, while statistical regularities reduced this attention bias when the target was presented at a low probability location, particularly at the lower levels of the visual hierarchy. In addition, we found that both statistical regularities and salience activated the dorsal frontoparietal network. Additional exploratory analyses of functional connectivity revealed that only statistical regularities modulated the inter-regional coupling between the posterior parietal cortex and the occipital cortex. These results show that statistical regularities and salience signals are both spatially represented at the occipital level, but that their integration into attentional processing priorities relies on dissociable brain mechanisms.

Visual attention can be guided by statistical regularities in the environment that people implicitly learn from past experience. Moreover, a perceptually salient element is able to automatically capture attention gaining processing priority through a bottom-up attentional control (AC) mechanism, independently of the volitional goals of the observer. The aim of our study was to investigate the interaction between attentional biases developed through statistical learning (SL) and bottom-up signals, to directly test whether the former might shape the attentional selection/suppression of salient items or whether its effects are blocked by a prevalence of saliency signals. By using the same visual search task, we manipulated target frequency (high vs. low) across spatial locations while, in some trials, we introduced a salient stimulus that differed from all the other elements in the array in terms of colour. In Experiment 1 the salient item was an irrelevant distractor, whereas in Experiments 2 and 3 it was the target. In the latter experiment, we also recorded the EEG activity, focusing on N2pc, i.e. an ERP markers related to target selection. Our results revealed that both SL and target-related saliency signals significantly and independently enhanced behavioural performance for targets at high (vs. low) frequency locations and for salient (vs. non-salient) targets, respectively. Furthermore, the benefit of bottom-up AC was confirmed by a larger N2pc, albeit in this case the effect was only evident for salient targets at the low-frequency location. In contrast, when a saliency signal was associated to an irrelevant distractor, participants showed longer RTs compared to when the display was homogeneous, again without any behavioural interaction with SL effects. Overall our findings suggest that SL and bottom-up AC jointly (and mainly independently) contribute to establishing attentional priority for specific spatial locations

Eye movements and other rich data obtained in virtual reality (VR) environments resembling situations where symptoms are manifested could help in the objective detection of various symptoms in clinical conditions. In the present study, 37 children with attention deficit hyperactivity disorder and 36 typically developing controls (9–13 y.o) played a lifelike prospective memory game using head-mounted display with inbuilt 90 Hz eye tracker. Eye movement patterns had prominent group differences, but they were dispersed across the full performance time rather than associated with specific events or stimulus features. A support vector machine classifier trained on eye movement data showed excellent discrimination ability with 0.92 area under curve, which was significantly higher than for task performance measures or for eye movements obtained in a visual search task. We demonstrated that a naturalistic VR task combined with eye tracking allows accurate prediction of attention deficits, paving the way for precision diagnostics.

Visuospatial attention is strongly lateralized, with the right hemisphere commonly exhibiting stronger activation and connectivity patterns than the left hemisphere during attentive processes. However, whether such asymmetry influences inter-hemispheric information transfer and behavioral performance is not known. Here we used a region of interest (ROI) and network-based approach to determine steady-state fMRI functional connectivity (FC) in the whole cerebral cortex during a leftward/rightward covert visuospatial attention task. We found that the global FC topology between either ROIs or networks was independent on the attended side. The side of attention significantly modulated FC strength between brain networks, with leftward attention primarily involving the connections of the right visual network with dorsal and ventral attention networks in both the left and right hemisphere. High hemispheric functional segregation significantly correlated with faster target detection response times (i.e., better performance). Our findings suggest that the dominance of the right hemisphere in visuospatial attention is associated with an hemispheric functional segregation that is beneficial for behavioral performance.

Background: Recent developments in virtual reality (VR) provide considerable opportunities for identification of behavioral markers indexing deficits in attention and goal-directed behavior. Eye movements and other rich data obtained in VR resembling situations where symptoms are manifested could help in the objective detection of various symptoms in clinical conditions, such as attention deficit hyperactivity disorder (ADHD). Methods: We conducted a VR experiment using Pico Neo 2 Eye head-mounted display with inbuilt Tobii 90Hz eye tracker. Data was collected in 37 children with ADHD and 36 typically developing controls (9–13 y.o) while they were performing tasks related to everyday household chores in a virtual home. We used a saccade velocity threshold algorithm to extract fixations and saccades and mapped those to task-related objects with the Unity game engine. Moreover, saliency, attractiveness, and relevance of the perceived objects were modelled. A support vector machine (SVM) classifier was trained with either eye movement features or task performance data to predict participant’s group status. Findings: Eye movement patterns had prominent differences between ADHD and control groups. However, the group differences were dispersed across the full performance time, rather than associated with specific events or stimulus features. The SVM classifier trained on eye movement data during active task execution showed excellent discrimination ability with 0.91 area under curve, which was significantly higher than for task performance measures or for eye movements obtained in a VR visual search task.Interpretation: We have demonstrated that a naturalistic VR task combined with eye tracking allows accurate prediction of real-world attention deficits and detailed mapping of human-environment interaction during everyday goal-directed behavior. This novel approach paves the way for improved diagnostic precision.

At any moment, the visual system is confronted with a huge number of stimuli, which exceeds our cognitive processing capacities. Different attentional control (AC) mechanisms guide attention and are responsible for selecting one of the many available stimuli; however, it is unclear whether they synergistically or independently operate in assigning attentional priority to a specific item/spatial location. Here we report four experiments, based on the same visual search task, in order to characterize the unique and combined influence of two AC mechanisms, namely goal-directed and experience-dependent signals. Specifically, Experiment 1 and 2 assessed the unique influence of goal-directed and experience-dependent control, respectively by presenting a (neutral/valid) central visual cue before the stimuli array onset, or by manipulating target probability (high/intermediate/low) across locations. Results showed better performance in valid- (vs. neutral-) cue trials and for targets in the high- (vs. low-) frequency location. By combining the described endogenous cueing and statistical learning (SL) protocols, Experiments 3 and 4 directly tested the combined effect of these two mechanisms on behavior and ERP markers. Behaviorally, we found a clear-cut interaction, namely goal-directed attention exerted a gating effect over experience-dependent priority assignment, with the latter emerging only in the absence of goal-directed guidance (neutral-cue trials). EEG data also revealed this interaction, however, regardless of the presence of goal-directed control, the N2pc elicited by targets in high-frequency location was larger than the N2pc elicited in the low-frequency location, suggesting a general attentional bias toward the location where the target is more likely to occur. Together, these findings confirmed both goal-directed and experience-dependent influences on attentional deployment and, when active together, a partially prevalence of goal-directed control over statistical learning.

Visuo-spatial attention prioritizes the processing of relevant inputs via different types of signals, including current goals and stimulus salience. Complex mixtures of these signals engage in everyday life situations, but little is known about how these signals jointly modulate distributed patterns of activity across the occipital regions that represent visual space. Here, we measured spatio-topic, quadrant-specific occipital activity during the processing of visual displays containing both task-relevant targets and salient color-singletons. We computed spatial bias vectors indexing the effect of attention in 2D space, as coded by distributed activity in the occipital cortex. We found that goal-directed spatial attention biased activity towards the target and that salience further modulated this endogenous effect: salient distractors decreased the spatial bias, while salient targets increased it. Analyses of effective connectivity revealed that the processing of salient distractors relied on the modulation of the bidirectional connectivity between the occipital and the posterior parietal cortex, as well as the modulation of the lateral interactions within the occipital cortex. These findings demonstrate that goal-directed attention and salience jointly contribute to shaping processing priorities in the occipital cortex and highlight that multiple functional paths determine how spatial information about these signals is distributed across occipital regions.

This work reports an investigation of the effect of combined top-down and bottom-up attentional control sources, using known attention-related EEG components that are thought to reflect target selection (N2pc) and distractor suppression (PD), in easy and difficult visual search tasks.

Episodic memory entails the storage of events together with their spatio-temporal context and retrieval comprises the subjective experience of a link between the person who remembers and the episode itself. We used an encoding procedure with mobile-phones to generate experimentally-controlled episodes in the real world: object-images were sent to the participants' phone, with encoding durations up to 3 weeks. In other groups of participants, the same objects were encoded during the exploration of a virtual town (45 min) or using a standard laboratory paradigm, with pairs of object/place-images presented in a sequence of unrelated trials (15 min). At retrieval, we tested subjective memory for the objects (remember/familiar) and memory for the context (place and time). We found that accurate and confident context-memory increased the likelihood of “remember” responses, in all encoding contexts. We also tested the participants' ability to judge the temporal-order of the encoded episodes. Using a model of temporal similarity, we demonstrate scale-invariant properties of order-retrieval, but also highlight the contribution of non-chronological factors. We conclude that the mechanisms governing episodic memory retrieval can operate across a wide range of spatio-temporal contexts and that the multi-dimensional nature of the episodic traces contributes to the subjective experience of retrieval.

In-scanner head motion represents a major confounding factor in functional connectivity studies and it raises particular concerns when motion correlates with the effect of interest. One such instance regards research focused on functional connectivity modulations induced by sustained cognitively demanding tasks. Indeed, cognitive engagement is generally associated with substantially lower in-scanner movement compared with unconstrained, or minimally constrained, conditions. Consequently, the reliability of condition-dependent changes in functional connectivity relies on effective denoising strategies. In this study, we evaluated the ability of common denoising pipelines to minimize and balance residual motion-related artifacts between resting-state and task conditions. Denoising pipelines-including realignment/tissue-based regression, PCA/ICA-based methods (aCompCor and ICA-AROMA, respectively), global signal regression, and censoring of motion-contaminated volumes-were evaluated according to a set of benchmarks designed to assess either residual artifacts or network identifiability. We found a marked heterogeneity in pipeline performance, with many approaches showing a differential efficacy between rest and task conditions. The most effective approaches included aCompCor, optimized to increase the noise prediction power of the extracted confounding signals, and global signal regression, although both strategies performed poorly in mitigating the spurious distance-dependent association between motion and connectivity. Censoring was the only approach that substantially reduced distance-dependent artifacts, yet this came at the great cost of reduced network identifiability. The implications of these findings for best practice in denoising task-based functional connectivity data, and more generally for resting-state data, are discussed.