Threat Expectation Does Not Improve Perceptual Discrimination despite Causing Heightened Priority Processing in the Frontoparietal Network.

Threat cues have been widely shown to elicit increased sensory and attentional neural processing. However, whether this enhanced recruitment leads to measurable behavioral improvements in perception is still in question. Here, we adjudicate between two opposing theories: that threat cues do or do not enhance perceptual sensitivity. We created threat stimuli by pairing one direction of motion in a random dot kinematogram with an aversive sound. While in the MRI scanner, 46 subjects (both men and women) completed a cued (threat/safe/neutral) perceptual decision-making task where they indicated the perceived motion direction of each moving dot stimulus. We found strong evidence that threat cues did not increase perceptual sensitivity compared with safe and neutral cues. This lack of improvement in perceptual decision-making ability occurred despite the threat cue resulting in widespread increases in frontoparietal BOLD activity, as well as increased connectivity between the right insula and the frontoparietal network. These results call into question the intuitive claim that expectation automatically enhances our perception of threat and highlight the role of the frontoparietal network in prioritizing the processing of threat-related environmental cues.

Reversible deactivation of motor cortex reveals that areas in parietal cortex are differentially dependent on motor cortex for the generation of movement.

Primates are characterized by specializations for manual manipulation, including expansion of posterior parietal cortex (PPC) and, in Catarrhines, evolution of a dexterous hand and opposable thumb. Previous studies examined functional interactions between motor cortex and PPC in New World monkeys and galagos, by inactivating M1 and evoking movements from PPC. These studies found that portions of PPC depend on M1 to generate movements. We now add a species that more closely resembles humans in hand morphology and PPC: macaques. Inactivating portions of M1 resulted in all evoked movements being reduced (28%) or completely abolished (72%) at the PPC sites tested (in areas 5L, PF, and PFG). Anterior parietal area 2 was similarly affected (26% reduced and 74% abolished) and area 1 was the least affected (12% no effect, 54% reduced, and 34% abolished). Unlike previous studies in New World monkeys and galagos, interactions between both nonanalogous (heterotopic) and analogous (homotopic) M1 and parietal movement domains were commonly found in most areas. These experiments demonstrate that there may be two parallel networks involved in motor control: a posterior parietal network dependent on M1 and a network that includes area 1 that is relatively independent of M1. Furthermore, it appears that the relative size and number of cortical fields in parietal cortex in different species correlates with homotopic and heterotopic effect prevalence. These functional differences in macaques could contribute to more numerous and varied muscle synergies across major muscle groups, supporting the expansion of the primate manual behavioral repertoire observed in Old World monkeys.NEW & NOTEWORTHY Motor cortex and anterior and posterior parietal cortex form a sensorimotor integration network. We tested the extent to which parietal areas could initiate movements independent of M1. Our findings support the contention that, although areas 2, 5L, PF, and PFG are highly dependent on M1 to produce movement, area 1 may constitute a parallel corticospinal pathway that can function somewhat independently of M1. A similar functional architecture may underlie dexterous tool use in humans.

Frontoparietal and salience network synchronizations during nonsymbolic magnitude processing predict brain age and mathematical performance in youth.

The development and refinement of functional brain circuits crucial to human cognition is a continuous process that spans from childhood to adulthood. Research increasingly focuses on mapping these evolving configurations, with the aim to identify markers for functional impairments and atypical development. Among human cognitive systems, nonsymbolic magnitude representations serve as a foundational building block for future success in mathematical learning and achievement for individuals. Using task-based frontoparietal (FPN) and salience network (SN) features during nonsymbolic magnitude processing alongside machine learning algorithms, we developed a framework to construct brain age prediction models for participants aged 7-30. Our study revealed differential developmental profiles in the synchronization within and between FPN and SN networks. Specifically, we observed a linear increase in FPN connectivity, concomitant with a decline in SN connectivity across the age span. A nonlinear U-shaped trajectory in the connectivity between the FPN and SN was discerned, revealing reduced FPN-SN synchronization among adolescents compared to both pediatric and adult cohorts. Leveraging the Gradient Boosting machine learning algorithm and nested fivefold stratified cross-validation with independent training datasets, we demonstrated that functional connectivity measures of the FPN and SN nodes predict chronological age, with a correlation coefficient of .727 and a mean absolute error of 2.944 between actual and predicted ages. Notably, connectivity within the FPN emerged as the most contributing feature for age prediction. Critically, a more matured brain age estimate is associated with better arithmetic performance. Our findings shed light on the intricate developmental changes occurring in the neural networks supporting magnitude representations. We emphasize brain age estimation as a potent tool for understanding cognitive development and its relationship to mathematical abilities across the critical developmental period of youth. PRACTITIONER POINTS: This study investigated the prolonged changes in the brain's architecture across childhood, adolescence, and adulthood, with a focus on task-state frontoparietal and salience networks. Distinct developmental pathways were identified: frontoparietal synchronization strengthens consistently throughout development, while salience network connectivity diminishes with age. Furthermore, adolescents show a unique dip in connectivity between these networks. Leveraging advanced machine learning methods, we accurately predicted individuals' ages based on these brain circuits, with a more mature estimated brain age correlating with better math skills.

Similarity and difference in large-scale functional network alternations between behavioral addictions and substance use disorder: a comparative meta-analysis.

Behavioral addiction (BA) and substance use disorder (SUD) share similarities and differences in clinical symptoms, cognitive functions, and behavioral attributes. However, little is known about whether and how functional networks in the human brain manifest commonalities and differences between BA and SUD. Voxel-wise meta-analyses of resting-state functional connectivity (rs-FC) were conducted in BA and SUD separately, followed by quantitative conjunction analyses to identify the common and distinct alterations across both the BA and SUD groups. A total of 92 datasets with 2444 addicted patients and 2712 healthy controls (HCs) were eligible for the meta-analysis. Our findings demonstrated that BA and SUD exhibited common alterations in rs-FC between frontoparietal network (FPN) and other high-level neurocognitive networks (i.e. default mode network (DMN), affective network (AN), and salience network (SN)) as well as hyperconnectivity between SN seeds and the Rolandic operculum in SSN. In addition, compared with BA, SUD exhibited several distinct within- and between-network rs-FC alterations mainly involved in the DMN and FPN. Further, altered within- and between-network rs-FC showed significant association with clinical characteristics such as the severity of addiction in BA and duration of substance usage in SUD. The common rs-FC alterations in BA and SUD exhibited the relationship with consistent aberrant behaviors in both addiction groups, such as impaired inhibition control and salience attribution. By contrast, the distinct rs-FC alterations might suggest specific substance effects on the brain neural transmitter systems in SUD.

Aberrant brain dynamics in major depressive disorder during working memory task.

Working memory (WM) is a distributed and dynamic process, and WM deficits are recognized as one of the top-ranked endophenotype candidates for major depressive disorders (MDD). However, there is a lack of knowledge of brain temporal-spatial profile of WM deficits in MDD. We used the dynamical degree centrality (dDC) to investigate the whole-brain temporal-spatial profile in 40 MDD and 40 controls during an n-back task with 2 conditions (i.e., '0back' and '2back'). We explored the dDC temporal variability and clustered meta-stable states in 2 groups during different WM conditions. Pearson's correlation analysis was used to evaluate the relationship between the altered dynamics with clinical symptoms and WM performance. Compared with controls, under '2back vs. 0back' contrast, patients showed an elevated dDC variability in wide range of brain regions, including the middle frontal gyrus, orbital part of inferior frontal gyrus (IFGorb), hippocampus, and middle temporal gyrus. Furthermore, the increased dDC variability in the hippocampus and IFGorb correlated with worse WM performance. However, there were no significant group-related differences in the meta-stable states were observed. This study demonstrated the increased WM-related instability (i.e., the elevated dDC variability) was represented in MDD, and enhancing stability may help patients achieve better WM performance.

Default mode network scaffolds immature frontoparietal network in cognitive development.

The default mode network (DMN) is a workspace for convergence of internal and external information. The frontal parietal network (FPN) is indispensable to executive functioning. Yet, how they interplay to support cognitive development remains elusive. Using longitudinal developmental fMRI with an n-back paradigm, we show a heterogeneity of maturational changes in multivoxel activity and network connectivity among DMN and FPN nodes in 528 children and 103 young adults. Compared with adults, children exhibited prominent longitudinal improvement but still inferior behavioral performance, which paired with less pronounced DMN deactivation and weaker FPN activation in children, but stronger DMN coupling with FPN regions. Children's DMN reached an adult-like level earlier than FPN at both multivoxel activity pattern and intranetwork connectivity levels. Intrinsic DMN-FPN internetwork coupling in children mediated the relationship between age and working memory-related functional coupling of these networks, with posterior cingulate cortex (PCC)-dorsolateral prefrontal cortex (DLPFC) coupling emerging as most prominent pathway. Coupling of PCC-DLPFC may further work together with task-invoked activity in PCC to account for longitudinal improvement in behavioral performance in children. Our findings suggest that the DMN provides a scaffolding effect in support of an immature FPN that is critical for the development of executive functions in children.

Regional activity and effective connectivity within the frontoparietal network during precision walking with visual cueing: an fNIRS study.

Precision walking (PW) incorporates precise step adjustments into regular walking patterns to navigate challenging surroundings. However, the brain processes involved in PW control, which encompass cortical regions and interregional interactions, are not fully understood. This study aimed to investigate the changes in regional activity and effective connectivity within the frontoparietal network associated with PW. Functional near-infrared spectroscopy data were recorded from adult subjects during treadmill walking tasks, including normal walking (NOR) and PW with visual cues, wherein the intercue distance was either fixed (FIX) or randomly varied (VAR) across steps. The superior parietal lobule (SPL), dorsal premotor area (PMd), supplementary motor area (SMA), and dorsolateral prefrontal cortex (dlPFC) were specifically targeted. The results revealed higher activities in SMA and left PMd, as well as left-to-right SPL connectivity, in VAR than in FIX. Activities in SMA and right dlPFC, along with dlPFC-to-SPL connectivity, were higher in VAR than in NOR. Overall, these findings provide insights into the roles of different brain regions and connectivity patterns within the frontoparietal network in facilitating gait control during PW, providing a useful baseline for further investigations into brain networks involved in locomotion.

Distinct but cooperating brain networks supporting semantic cognition.

Semantic cognition is a complex multifaceted brain function involving multiple processes including sensory, semantic, and domain-general cognitive systems. However, it remains unclear how these systems cooperate with each other to achieve effective semantic cognition. Here, we used independent component analysis (ICA) to investigate the functional brain networks that support semantic cognition. We used a semantic judgment task and a pattern-matching control task, each with 2 levels of difficulty, to disentangle task-specific networks from domain-general networks. ICA revealed 2 task-specific networks (the left-lateralized semantic network [SN] and a bilateral, extended semantic network [ESN]) and domain-general networks including the frontoparietal network (FPN) and default mode network (DMN). SN was coupled with the ESN and FPN but decoupled from the DMN, whereas the ESN was synchronized with the FPN alone and did not show a decoupling with the DMN. The degree of decoupling between the SN and DMN was associated with semantic task performance, with the strongest decoupling for the poorest performing participants. Our findings suggest that human higher cognition is achieved by the multiple brain networks, serving distinct and shared cognitive functions depending on task demands, and that the neural dynamics between these networks may be crucial for efficient semantic cognition.

Attention recruits frontal cortex in human infants.

Young infants learn about the world by overtly shifting their attention to perceptually salient events. In adults, attention recruits several brain regions spanning the frontal and parietal lobes. However, it is unclear whether these regions are sufficiently mature in infancy to support attention and, more generally, how infant attention is supported by the brain. We used event-related functional magnetic resonance imaging (fMRI) in 24 sessions from 20 awake behaving infants 3 mo to 12 mo old while they performed a child-friendly attentional cuing task. A target was presented to either the left or right of the infant's fixation, and offline gaze coding was used to measure the latency with which they saccaded to the target. To manipulate attention, a brief cue was presented before the target in three conditions: on the same side as the upcoming target (valid), on the other side (invalid), or on both sides (neutral). All infants were faster to look at the target on valid versus invalid trials, with valid faster than neutral and invalid slower than neutral, indicating that the cues effectively captured attention. We then compared the fMRI activity evoked by these trial types. Regions of adult attention networks activated more strongly for invalid than valid trials, particularly frontal regions. Neither behavioral nor neural effects varied by infant age within the first year, suggesting that these regions may function early in development to support the orienting of attention. Together, this furthers our mechanistic understanding of how the infant brain controls the allocation of attention.

Differences in Functional Activity and Connectivity in the Right Frontoparietal Network between Nurses Working Long-Term Shifts and Fixed Day Shifts.

OBJECTIVES: To investigate the differences in functional brain activity and connectivity between nurses working long-term shifts and fixed day shift and explore their correlations with work-related psychological conditions. METHODS: Thirty-five nurses working long-term shifts and 35 nurses working fixed day shifts were recruited. After assessing work-related psychological conditions, such as burnout and perceived stress of these two groups of nurses, amplitude of low-frequency fluctuations (ALFF) and functional connectivity (FC) analyses were performed to investigate the between-group differences in brain functional activity and connectivity. Furthermore, correlation analysis between the ALFF/FC metrics and psychological conditions was conducted. RESULTS: Compared with nurses working fixed day shifts, nurses working long-term shifts showed higher levels of burnout, perceived stress, and depression scores; lower z-transformed ALFF (zALFF) values in the right dorsolateral prefrontal cortex (dlPFC), right superior parietal lobule (SPL), and right anterior cingulate cortex (ACC); and higher zALFF values in the right middle temporal gyrus (voxel-level p < 0.001, cluster-level p < 0.05, gaussian random field (GRF) correction), as well as lower FC values in the right dlPFC-right SPL and right dlPFC-right ACC (p < 0.05, false discovery rate (FDR) corrected). Moreover, the FC values in the right dlPFC-right SPL were negatively correlated with the perceived stress score in nurses working long-term shifts (p < 0.05, FDR corrected). CONCLUSIONS: This study demonstrated that nurses working long-term shifts had lower functional activity and weaker functional connectivity in the right frontoparietal network, which mainly includes the right dlPFC and right SPL, than those working on regular day shift. The current findings provide new insights into the impacts of long-term shift work on nurses' mental health from a functional neuroimaging perspective.

Task-based functional connectivity identifies two segregated networks underlying intentional action.

While much of motor behavior is automatic, intentional action is necessary for the selection and initiation of controlled motor acts and is thus an essential part of goal-directed behavior. Neuroimaging studies have shown that self-generated action implicates several dorsal and ventral frontoparietal areas. However, knowledge of the functional coupling between these brain regions during intentional action remains limited. We here studied brain activations and functional connectivity (FC) of thirty right-handed healthy participants performing a finger pressing task instructed to use a specific finger (externally-triggered action) or to select one of four fingers randomly (internally-generated action). Participants performed the task in alternating order either with their dominant right hand or the left hand. Consistent with previous studies, we observed stronger involvement of posterior parietal cortex and premotor regions when contrasting internally-generated with externally-triggered action. Interestingly, this contrast also revealed significant engagement of medial occipitotemporal regions including the left lingual and right fusiform gyrus. Task-based FC analysis identified increased functional coupling among frontoparietal regions as well as increased and decreased coupling between occipitotemporal regions, thus differentiating between two segregated networks. When comparing results of the dominant and nondominant hand we found less activation, but stronger connectivity for the former, suggesting increased neural efficiency when participants use their dominant hand. Taken together, our results reveal that two segregated networks that encompass the frontoparietal and occipitotemporal cortex contribute independently to intentional action.

Prioritizing flexible working memory representations through retrospective attentional strengthening.

Previous work has proposed two potential benefits of retrospective attention on working memory (WM): target strengthening and non-target inhibition. It remains unknown which hypothesis contributes to the improved WM performance, yet the neural mechanisms responsible for this attentional benefit are unclear. Here, we recorded electroencephalography (EEG) signals while 33 participants performed a retrospective-cue WM task. Multivariate pattern classification analysis revealed that only representations of target features were enhanced by valid retrospective attention during retention, supporting the target strengthening hypothesis. Further univariate analysis found that mid-frontal theta inter-trial phase coherence (ITPC) and ERP components were modulated by valid retrospective attention and correlated with individual differences and moment-to-moment fluctuations on behavioral outcomes, suggesting that both trait- and state-level variability in attentional preparatory processes influence goal-directed behavior. Furthermore, task-irrelevant target spatial location could be decoded from EEG signals, indicating that enhanced spatial binding of target representation is vital to high WM precision. Importantly, frontoparietal theta-alpha phase-amplitude coupling was increased by valid retrospective attention and predicted the reduced random guessing rates. This long-range connection supported top-down information flow in the engagement of frontoparietal networks, which might organize attentional states to integrate target features. Altogether, these results provide neurophysiological bases that retrospective attention improves WM precision by enhancing flexible target representation and emphasize the critical role of the frontoparietal attentional network in the control of WM representations.

Modulation effects of repeated transcranial direct current stimulation on the dorsal attention and frontal parietal networks and its association with placebo and nocebo effects.

Literature suggests that attention is a critical cognitive process for pain perception and modulation and may play an important role in placebo and nocebo effects. Here, we investigated how repeated transcranial direct current stimulation (tDCS) applied at the dorsolateral prefrontal cortex (DLPFC) for three consecutive days can modulate the brain functional connectivity (FC) of two networks involved in cognitive control: the frontoparietal network (FPN) and dorsal attention network (DAN), and its association with placebo and nocebo effects. 81 healthy subjects were randomized to three groups: anodal, cathodal, and sham tDCS. Resting state fMRI scans were acquired pre- and post- tDCS on the first and third day of tDCS. An Independent Component Analysis (ICA) was performed to identify the FPN and DAN. ANCOVA was applied for group analysis. Compared to sham tDCS, 1) both cathodal and anodal tDCS increased the FC between the DAN and right parietal operculum; cathodal tDCS also increased the FC between the DAN and right postcentral gyrus; 2) anodal tDCS led to an increased FC between the FPN and right parietal operculum, while cathodal tDCS was associated with increased FC between the FPN and left superior parietal lobule/precuneus; 3) the FC increase between the DAN and right parietal operculum was significantly correlated to the placebo analgesia effect in the cathodal group. Our findings suggest that both repeated cathodal and anodal tDCS could modulate the FC of two important cognitive brain networks (DAN and FPN), which may modulate placebo / nocebo effects.

A frontoparietal network for volitional control of gaze following.

Gaze following is a major element of non-verbal communication and important for successful social interactions. Human gaze following is a fast and almost reflex-like behaviour, yet it can be volitionally controlled and suppressed to some extent if inappropriate or unnecessary, given the social context. In order to identify the neural basis of the cognitive control of gaze following, we carried out an event-related fMRI experiment, in which human subjects' eye movements were tracked while they were exposed to gaze cues in two distinct contexts: A baseline gaze following condition in which subjects were instructed to use gaze cues to shift their attention to a gazed-at spatial target and a control condition in which the subjects were required to ignore the gaze cue and instead to shift their attention to a distinct spatial target to be selected based on a colour mapping rule, requiring the suppression of gaze following. We could identify a suppression-related blood-oxygen-level-dependent (BOLD) response in a frontoparietal network comprising dorsolateral prefrontal cortex (dlPFC), orbitofrontal cortex (OFC), the anterior insula, precuneus, and posterior parietal cortex (PPC). These findings suggest that overexcitation of frontoparietal circuits in turn suppressing the gaze following patch might be a potential cause of gaze following deficits in clinical populations.

In search of a human self-regulation system.

The capacity for self-regulation allows people to control their thoughts, behaviors, emotions, and desires. In spite of this impressive ability, failures of self-regulation are common and contribute to numerous societal problems, from obesity to drug addiction. Such failures frequently occur following exposure to highly tempting cues, during negative moods, or after self-regulatory resources have been depleted. Here we review the available neuroscientific evidence regarding self-regulation and its failures. At its core, self-regulation involves a critical balance between the strength of an impulse and an individual's ability to inhibit the desired behavior. Although neuroimaging and patient studies provide consistent evidence regarding the reward aspects of impulses and desires, the neural mechanisms that underlie the capacity for control have eluded consensus, with various executive control regions implicated in different studies. We outline the necessary properties for a self-regulation control system and suggest that the use of resting-state functional connectivity analyses may be useful for understanding how people regulate their behavior and why they sometimes fail in their attempts.

Associations between insomnia symptoms and functional connectivity in the UK Biobank cohort (n = 29,423).

An increasing number of studies harness resting-state fMRI functional connectivity analysis to investigate the neurobiological mechanisms of insomnia. The results to date are inconsistent and the detection of minor and widely distributed alterations in functional connectivity requires large sample sizes. The present study investigated associations between insomnia symptoms and resting-state functional connectivity at the whole-brain level in the largest sample to date. This cross-sectional analysis used resting-state imaging data from the UK Biobank, a large scale, population-based biomedical database. The analysis included 29,423 participants (age: 63.1 ± 7.5 years, 54.3% female), comprising 9210 with frequent insomnia symptoms and 20,213 controls without. Linear models were adjusted for relevant clinical, imaging, and socio-demographic variables. The Akaike information criterion was used for model selection. Multiple comparisons were corrected using the false discovery rate with a significance level of q < 0.05. Frequent insomnia symptoms were associated with increased connectivity within the default mode network and frontoparietal network, increased negative connectivity between the default mode network and the frontoparietal network, and decreased connectivity between the salience network and a node of the default mode network. Furthermore, frequent insomnia symptoms were associated with altered functional connectivity between nodes comprising sensory areas and the cerebellum. These functional alterations of brain networks may underlie dysfunctional affective and cognitive processing in insomnia and contribute to subjectively and objectively impaired sleep. However, it must be noted that the item that was used to assess frequent insomnia symptoms in this study did not assess all the characteristics of clinically diagnosed insomnia.

Post-Concussion Symptoms, Cognition and Brain Connectivity in an Australian Undergraduate Population: A Quantitative Electroencephalography Study.

BACKGROUND: An estimated 99 in 100,000 people experience a traumatic brain injury (TBI), with 85% being mild (mTBI) in nature. The Post-Concussion Symptom Scale (PCSS), is a reliable and valid measure of post-mTBI symptoms; however, diagnostic specificity is challenging due to high symptom rates in the general population. Understanding the neurobiological characteristics that distinguish high and low PCSS raters may provide further clarification on this phenomenon. AIM: To explore the neurobiological characteristics of post-concussion symptoms through the association between PCSS scores, brain network connectivity (using quantitative electroencephalography; qEEG) and cognition in undergraduates. HYPOTHESES: high PCSS scorers will have (1) more network dysregulation and (2) more cognitive dysfunction compared to the low PCSS scorers. METHODS: A sample of 40 undergraduates were divided into high and low PCSS scorers. Brain connectivity was measured using qEEG, and cognition was measured via neuropsychological measures of sustained attention, inhibition, immediate attention, working memory, processing speed and inhibition/switching. RESULTS: Contrary to expectations, greater frontoparietal network dysregulation was seen in the low PCSS score group (p = 0.003). No significant difference in cognitive dysfunction was detected between high and low PCSS scorers. Post-hoc analysis in participants who had experienced mTBI revealed greater network dysregulation in those reporting a more recent mTBI. CONCLUSIONS: Measuring post-concussion symptoms alone is not necessarily informative about changes in underlying neural mechanisms. In an exploratory subset analysis, brain network dysregulation appears to be greater in the early post-injury phase compared to later. Further analysis of underlying PCSS constructs and how to measure these in a non-athlete population and clinical samples is warranted.

A Gradient of Sharpening Effects by Perceptual Prior across the Human Cortical Hierarchy.

Prior knowledge profoundly influences perceptual processing. Previous studies have revealed consistent suppression of predicted stimulus information in sensory areas, but how prior knowledge modulates processing higher up in the cortical hierarchy remains poorly understood. In addition, the mechanism leading to suppression of predicted sensory information remains unclear, and studies thus far have revealed a mixed pattern of results in support of either the "sharpening" or "dampening" model. Here, using 7T fMRI in humans (both sexes), we observed that prior knowledge acquired from fast, one-shot perceptual learning sharpens neural representation throughout the ventral visual stream, generating suppressed sensory responses. In contrast, the frontoparietal and default mode networks exhibit similar sharpening of content-specific neural representation, but in the context of unchanged and enhanced activity magnitudes, respectively: a pattern we refer to as "selective enhancement." Together, these results reveal a heretofore unknown macroscopic gradient of prior knowledge's sharpening effect on neural representations across the cortical hierarchy.SIGNIFICANCE STATEMENT A fundamental question in neuroscience is how prior knowledge shapes perceptual processing. Perception is constantly informed by internal priors in the brain acquired from past experiences, but the neural mechanisms underlying this process are poorly understood. To date, research on this question has focused on early visual regions, reporting a consistent downregulation when predicted stimuli are encountered. Here, using a dramatic one-shot perceptual learning paradigm, we observed that prior knowledge results in sharper neural representations across the cortical hierarchy of the human brain through a gradient of mechanisms. In visual regions, neural responses tuned away from internal predictions are suppressed. In frontoparietal regions, neural activity consistent with priors is selectively enhanced. These results deepen our understanding of how prior knowledge informs perception.

Representational coding of overt and covert orienting of visuospatial attention in the frontoparietal network.

Orienting of visuospatial attention refers to reallocation of attentional focus from one target or location to another and can occur either with (overt) or without (covert) eye movement. Although it has been demonstrated that both types of orienting commonly involve frontal and parietal brain regions as the frontoparietal network (FPN), the underlying representational coding of these two types of orienting remains unclear. In this functional magnetic resonance imaging study, participants performed a task that elicited overt and covert orienting to endogenously or exogenously cued targets with eye-tracking to monitor eye movement. Although the FPN was commonly activated for both overt and covert orienting, multivariate patterns of the activation of voxels in the FPN accurately predicted whether eye movements were involved or not during orienting. These overt- and covert-preferred voxels were topologically distributed as distinct and interlaced clusters in a millimeter scale. Inclusion of the two types of clusters predicted orienting type more accurately than one type of clusters alone. These findings suggest that overt and covert orienting are represented by interdependent functional clusters of neuronal populations in regions of the FPN, which might reflect a generalizable principle in the nervous system for functional organization of closely associated processes.

Asymmetric directed functional connectivity within the frontoparietal motor network during motor imagery and execution.

Both imagery and execution of motor control consist of interactions within a neuronal network, including frontal motor-related and posterior parietal regions. To reveal neural representation in the frontoparietal motor network, two approaches have been proposed thus far: one is decoding of actions/modes related to motor control from the spatial pattern of brain activity; and the other is estimating directed functional connectivity (a directed association between two brain regions within motor areas). However, directed connectivity among multiple regions of the frontoparietal motor network during motor imagery (MI) or motor execution (ME) has not been investigated. Here, we attempted to characterize the directed functional connectivity representing the MI and ME conditions. We developed a delayed sequential movement and imagery task to evoke brain activity associated with ME and MI, which can be recorded by functional magnetic resonance imaging. We applied a causal discovery approach, a linear non-Gaussian acyclic causal model, to identify directed functional connectivity among the frontoparietal motor-related brain regions for each condition. We demonstrated higher directed functional connectivity from the contralateral dorsal premotor cortex (dPMC) to the primary motor cortex (M1) in ME than in MI. We further identified significant direct effects of the dPMC and ventral premotor cortex (vPMC) to the parietal regions. In particular, connectivity from the dPMC to the superior parietal lobule (SPL) in the same hemisphere showed significant positive effects across all conditions, while interlateral connectivities from the vPMC to the SPL showed significantly negative effects across all conditions. Finally, we found positive effects from A1 to M1, that is, the audio-motor pathway, in the same hemisphere. These results indicate that the sources of motor command originating in the d/vPMC influenced the M1 and parietal regions for achieving ME and MI. Additionally, sequential sounds may functionally facilitate temporal motor processes.