Academic literature on the topic 'Frontoparietal attentional network'

Relations between spatial attention and motor intention were investigated by means of an EEG potential elicited by shifting attention to a location in space as well as by the selection of a hand for responding. High-density recordings traced this potential to a common frontoparietal network activated by attentional orienting and by response selection. Within this network, parietal and frontal cortex were activated sequentially, followed by an anterior-to-posterior migration of activity culminating in the lateral occipital cortex. Based on temporal and polarity information provided by EEG, we hypothesize that the frontoparietal activation, evoked by directional information, updates a task-defined preparatory state by deselecting or inhibiting the behavioral option competing with the cued response side or the cued direction of attention. These results from human EEG demonstrate a direct EEG manifestation of the frontoparietal attention network previously identified in functional imaging. EEG reveals the time-course of activation within this network and elucidates the generation and function of associated directing-attention EEG potentials. The results emphasize transient activation and a decision-related function of the frontoparietal attention network, contrasting with the sustained preparatory activation that is commonly inferred from neuroimaging.

AbstractThe frontoparietal control network, anatomically and functionally interposed between the dorsal attention network and default mode network, underpins executive control functions. Individuals with attention-deficit/hyperactivity disorder (ADHD) commonly exhibit deficits in executive functions, which are mainly mediated by the frontoparietal control network. Involvement of the frontoparietal control network based on the anterior prefrontal cortex in neurobiological mechanisms of ADHD has yet to be tested. We used resting-state functional MRI and seed-based correlation analyses to investigate functional connectivity of the frontoparietal control network in a sample of 25 children with ADHD (7–14 years; mean 9.94±1.77 years; 20 males), and 25 age-, sex-, and performance IQ-matched typically developing (TD) children. All participants had limited in-scanner head motion. Spearman’s rank correlations were used to test the associations between altered patterns of functional connectivity with clinical symptoms and executive functions, measured by the Conners’ Continuous Performance Test and Spatial Span in the Cambridge Neuropsychological Test Automated Battery. Compared with TD children, children with ADHD demonstrated weaker connectivity between the right anterior prefrontal cortex (PFC) and the right ventrolateral PFC, and between the left anterior PFC and the right inferior parietal lobule. Furthermore, this aberrant connectivity of the frontoparietal control network in ADHD was associated with symptoms of impulsivity and opposition-defiance, as well as impaired response inhibition and attentional control. The findings support potential integration of the disconnection model and the executive dysfunction model for ADHD. Atypical frontoparietal control network may play a pivotal role in the pathophysiology of ADHD. (JINS, 2015, 21, 271–284)

Abstract Despite the abundance of behavioral evidence showing the interaction between attention and prediction in infants, the neural underpinnings of this interaction are not yet well understood. The endogenous attentional function in adults have been largely localized to the frontoparietal network. However, resting-state and neuroanatomical investigations have found that this frontoparietal network exhibits a protracted developmental trajectory and involves weak and unmyelinated long-range connections early in infancy. Can this developmentally nascent network still be modulated by predictions? Here, we conducted the first investigation of infant frontoparietal network engagement as a function of the predictability of visual events. Using functional near-infrared spectroscopy, the hemodynamic response in the frontal, parietal, and occipital lobes was analyzed as infants watched videos of temporally predictable or unpredictable sequences. We replicated previous findings of cortical signal attenuation in the frontal and sensory cortices in response to predictable sequences and extended these findings to the parietal lobe. We also estimated background functional connectivity (i.e., by regressing out task-evoked responses) to reveal that frontoparietal functional connectivity was significantly greater during predictable sequences compared to unpredictable sequences, suggesting that this frontoparietal network may underlie how the infant brain communicates predictions. Taken together, our results illustrate that temporal predictability modulates the activation and connectivity of the frontoparietal network early in infancy, supporting the notion that this network may be functionally available early in life despite its protracted developmental trajectory.

We investigated the brain activity patterns associated with stabilizing performance during challenges to attention. Our findings revealed distinct patterns of frontoparietal activity and functional connectivity associated with increased attentional effort versus preserved performance during challenged attention. Participants performed a visual signal detection task with and without presentation of a perceptual-attention challenge (changing background). The challenge condition increased activation in frontoparietal regions including right mid-dorsal/dorsolateral PFC (RPFC), approximating Brodmann's area 9, and superior parietal cortex. We found that greater behavioral impact of the challenge condition was correlated with greater RPFC activation, suggesting that increased engagement of cognitive control regions is not always sufficient to maintain high levels of performance. Functional connectivity between RPFC and ACC increased during the challenge condition and was also associated with performance declines, suggesting that the level of synchronized engagement of these regions reflects individual differences in attentional effort. Pretask, resting-state RPFC–ACC connectivity did not predict subsequent performance, suggesting that RPFC–ACC connectivity increased dynamically during task performance in response to performance decrement and error feedback. In contrast, functional connectivity between RPFC and superior parietal cortex not only during the task but also during pretask rest was associated with preserved performance in the challenge condition. Together, these data suggest that resting frontoparietal connectivity predicts performance on attention tasks that rely on those same cognitive control networks and that, under challenging conditions, other control regions dynamically couple with this network to initiate the engagement of cognitive control.

Background: Resting state functional MRI (rs-fMRI) provides many advantages to task-based fMRI in neurosurgical populations, foremost of which is the lack of the need to perform a task. Many networks can be identified by rs-fMRI in a single period of scanning. Despite the advantages, there is a paucity of literature on rs-fMRI in neurosurgical populations. Methods: Eight patients with tumours near areas traditionally considered as eloquent cortex participated in a five minute rs-fMRI scan. Resting-state fMRI data underwent Independent Component Analysis (ICA) using the Multivariate Exploratory Linear Optimized Decomposition into Independent Components (MELODIC) toolbox in FSL. Resting state networks (RSNs) were identified on a visual basis. Results: Several RSNs, including language (N=7), sensorimotor (N=7), visual (N=7), default mode network (N=8) and frontoparietal attentional control (n=7) networks were readily identifiable using ICA of rs-fMRI data. Conclusion: These pilot data suggest that ICA applied to rs-fMRI data can be used to identify motor and language networks in patients with brain tumours. We have also shown that RSNs associated with cognitive functioning, including the default mode network and the frontoparietal attentional control network can be identified in individual subjects with brain tumours. While preliminary, this suggests that rs-fMRI may be used pre-operatively to localize areas of cortex important for higher order cognitive functioning.

Human behavior involves monitoring and adjusting performance to meet established goals. Performance-monitoring systems that act by detecting conflict in stimulus and response processing have been hypothesized to influence cortical control systems to adjust and improve performance. Here we used fMRI to investigate the neural mechanisms of conflict monitoring and resolution during voluntary spatial attention. We tested the hypothesis that the ACC would be sensitive to conflict during attentional orienting and influence activity in the frontoparietal attentional control network that selectively modulates visual information processing. We found that activity in ACC increased monotonically with increasing attentional conflict. This increased conflict detection activity was correlated with both increased activity in the attentional control network and improved speed and accuracy from one trial to the next. These results establish a long hypothesized interaction between conflict detection systems and neural systems supporting voluntary control of visual attention.

The AB refers to the performance impairment that occurs when visual selective attention is overloaded through the very rapid succession of two targets (T1 and T2) among distractors by using the rapid serial visual presentation task (RSVP). Under these conditions, performance is typically impaired when T2 is presented within 200–500 ms from T1 (AB). Based on neuroimaging studies suggesting a role of top-down attention and working memory brain hubs in the AB, here we potentiated via anodal or sham tDCS the activity of the right DLPFC (F4) and of the right PPC (P4) during an AB task. The findings showed that anodal tDCS over the F4 and over P4 had similar effects on the AB. Importantly, potentiating the activity of the right frontoparietal network via anodal tDCS only benefitted poor performers, reducing the AB, whereas in good performers it accentuated the AB. The contribution of the present findings is twofold: it shows both top-down and bottom-up contributions of the right frontoparietal network in the AB, and it indicates that there is an optimal level of excitability of this network, resulting from the individual level of activation and the intensity of current stimulation.

Eye gaze is a powerful cue for orienting attention in space. Studies examining whether gaze and symbolic cues recruit the same neural mechanisms have found mixed results. We tested whether there is a specialized attentional mechanism for social cues. We separately measured BOLD activity during orienting and reorienting attention following predictive gaze and symbolic cues. Results showed that gaze and symbolic cues exerted their influence through the same neural networks but also produced some differential modulations. Dorsal frontoparietal regions in left intraparietal sulcus (IPS) and bilateral MT+/lateral occipital cortex only showed orienting effects for symbolic cues, whereas right posterior IPS showed larger validity effects following gaze cues. Both exceptions may reflect the greater automaticity of gaze cues: Symbolic orienting may require more effort, while disengaging attention during reorienting may be more difficult following gaze cues. Face-selective regions, identified with a face localizer, showed selective activations for gaze cues reflecting sensory processing but no attentional modulations. Therefore, no evidence was found linking face-selective regions to a hypothetical, specialized mechanism for orienting attention to gaze cues. However, a functional connectivity analysis showed greater connectivity between face-selective regions and right posterior IPS, posterior STS, and inferior frontal gyrus during gaze cueing, consistent with proposals that face-selective regions may send gaze signals to parts of the dorsal and ventral frontoparietal attention networks. Finally, although the default-mode network is thought to be involved in social cognition, this role does not extend to gaze orienting as these regions were more deactivated following gaze cues and showed less functional connectivity with face-selective regions during gaze cues.

Autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD) have been difficult to differentiate in clinical settings, as these two disorders are phenotypically similar and both exhibit atypical attention and executive functioning. Mischaracterizations between these two disorders can lead to inappropriate medication regimes, significant delays in special services, and personal distress to families and caregivers. There is evidence that ASD and ADHD are biologically different for attentional and executive functioning mechanisms, as only half of individuals with co-occurring ASD and ADHD respond to stimulant medication. Further, neurobehavioral work has supported these biological differences for ASD and ADHD, with both shared and distinct functional connectivity. In specific, two brain networks have been implicated in these disorders: the salience network (SN) and frontoparietal network (FPN). The SN is a network anchored by bilateral anterior insula and the dorsal anterior cingulate cortex and has been implicated in “bottom-up” attentional processes for both internal and external events. The FPN is anchored by lateral prefrontal cortex areas and the parietal lobe and plays a roll in “top-down” executive processes. Functional connectivity subgroups differentiated ASD from ADHD with between SN-FPN connectivity patterns, but not by within-SN or within-FPN connectivity patterns. Further, subgroup differences in ASD+ADHD comorbidity vs. ASD only were found for within-FPN connectivity.
Master of Science
Autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD) have been difficult to differentiate in clinical settings, as these two disorders are similar and both exhibit attention and executive functioning difficulties. ASD and ADHD have shared and distinct functional brain network connectivity related to attention and executive functioning. Two brain networks have been implicated in these disorders: the salience network (SN) and frontoparietal network (FPN). The SN is a network that has been implicated in “bottom-up” attentional processes for both internal and external events. The FPN plays a roll in “top-down” executive processes. This study found that functional connectivity patterns between the SN and FPN differentiated ASD from ADHD. Further, connectivity patterns in children with co-occurring ASD and ADHD were characterized by within-FPN connectivity.

Any natural visual environment contains a huge collection of objects, which impact on our perception and compete for drawing our interest and therefore for being preferentially noticed. By effectively selecting a relevant fraction of the incoming information for further in-depth processing, visual selective attention (VSA) optimizes vision in order to overcome the intrinsically limited computational capacity of the visual system. Single-unit recording studies have demonstrated that multiple stimuli simultaneously impinging onto the receptive field (RF) of a given neuron compete for controlling its firing by interacting with each other through mutual inhibition (Reynold & Chelazzi, 2004; Chelazzi et al., 2011; see also Biased competition model by Moran & Desimone, 1985). Thus, neural responses to stimulus pairs in the RF approximate a weighted average of the responses elicited by individual stimuli (for further details, see Reynold & Chelazzi, 2004; Chelazzi et al., 2011; see also Normalization model by Reynolds et al., 1999). The crucial question to ask is how the competition is resolved. Neurophysiological studies have shown that when two stimuli are simultaneously presented within the same receptive field (RF), neuronal responses in the absence of attentional control are largely determined by the strongest or most salient stimulus, e.g. the one presented at higher luminance contrast, which stands conspicuously against the background (Reynolds & Desimone, 2003). This reflects a bottom-up biasing of the competition on the basis of stimulus saliency. Crucially, top-down attentional control can resolve the competition between stimuli in favor of the most behaviorally relevant stimulus (target) by specifying its properties. In other words, attention can switch control of the neuronal response to the stimulus of interest, independently of its saliency, so that the target will determine the response of that neuron; in other words, the response of a given neuron to a pair of stimuli impinging on its RF will equate the neuronal response to the target stimulus, when presented alone. As a consequence, the neuronal representation of the target is enhanced within visual areas at the expense of the visual representation of the distractor (Corbetta et al., 1990; Treue & Trujillo, 1999; Luck et al., 2000, for reviews, see Chelazzi et al., 2011; Carrasco, 2011; Roe et al., 2012). Importantly, there is a wide range of observations which describe the impact of attention on sensory representations along the visual pathway. Crucially, attentional biasing of the neuronal activity within visual cortices is not uniform, but rather results in different forms of neuronal modulation (see e.g. Treue & Martinez Trujillo, 1999; Fries et al., 2001, 2008; Martinez-Trujillo & Treue, 2002; Carrasco et al., 2000; Carrasco, 2006). The traditional view of VSA maintains that attentional control is organized in a master-slave hierarchical manner: Modulatory top-down signals from a distributed frontoparietal attentional network (e.g. Moore, Armstrong, 2003; Wardak et al., 2004; Silvanto et al., 2006) - the master - impact on sensory (visual) cortical areas - the slave. In other words, lower-order sensory areas execute visual representations commanded via feedback projections from higher-order centers. Recent research has greatly challenged this conventional view, leading to the new and striking hypothesis that master centers do not have an exclusive role in attentional control, but rather the slave ventral (and dorsal) visual pathway areas might capitalize on their internal microcircuitry to directly instantiate attentional mechanisms even in the absence of control from master centers (e.g. Reynolds & Heeger, 2009; Baluch & Itti, 2011). Interestingly, a behavioral assessment following circumscribed lesions of macaque areas V4 and TEO showed a strong impairment in the animal ability to select a stimulus based on its behavioral relevance while discarding other, perceptually more conspicuous stimuli; in other word, after lesions to those areas, the behavior of the animal was at the mercy of stimulus salience (De Weerd et al., 1999; see also Gallant et al., 2000 for analogous findings in humans). These areas along the ventral pathway have therefore been claimed as essential for the instantiation of attentional mechanisms, and in particular mechanisms for the efficient filtering of non-relevant distractors (De Weerd et al., 1999; Chelazzi et al., 2011). The aim of the present study is to extend the current understanding of the brain mechanisms underlying VSA, by directly testing their possible residence within the human object-recognition pathway itself. An excellent human slave candidate to test this possibility is represented by the lateral occipital cortex (LO), a mid-tier area of the ventral stream, which is a key node for shape-object perception (Malach et al., 1995). Specifically, by applying TMS stimulation over human LO (or a control site), we examined the role of LO during a VSA task, in order to directly test its role in the attentional filtering of distracting information. Crucially, we manipulated the timing of TMS application in two related experiments, in order to disentangle the contribution of LO to perceptual and attentional operations. As a result, we observed TMS modulation of activity within LO area during the attentional processing of our VSA task. By using early TMS (before stimulus display onset) and late TMS (during stimulus display onset) application over LO cortex, we obtained more general perceptual enhancement and more specific improvement of attentional filtering, respectively. We can therefore conclude that human slave LO area contains internal attentional microcircuits necessary for attentional target selection and distractor filtering.
Any natural visual environment contains a huge collection of objects, which impact on our perception and compete for drawing our interest and therefore for being preferentially noticed. By effectively selecting a relevant fraction of the incoming information for further in-depth processing, visual selective attention (VSA) optimizes vision in order to overcome the intrinsically limited computational capacity of the visual system. Single-unit recording studies have demonstrated that multiple stimuli simultaneously impinging onto the receptive field (RF) of a given neuron compete for controlling its firing by interacting with each other through mutual inhibition (Reynold & Chelazzi, 2004; Chelazzi et al., 2011; see also Biased competition model by Moran & Desimone, 1985). Thus, neural responses to stimulus pairs in the RF approximate a weighted average of the responses elicited by individual stimuli (for further details, see Reynold & Chelazzi, 2004; Chelazzi et al., 2011; see also Normalization model by Reynolds et al., 1999). The crucial question to ask is how the competition is resolved. Neurophysiological studies have shown that when two stimuli are simultaneously presented within the same receptive field (RF), neuronal responses in the absence of attentional control are largely determined by the strongest or most salient stimulus, e.g. the one presented at higher luminance contrast, which stands conspicuously against the background (Reynolds & Desimone, 2003). This reflects a bottom-up biasing of the competition on the basis of stimulus saliency. Crucially, top-down attentional control can resolve the competition between stimuli in favor of the most behaviorally relevant stimulus (target) by specifying its properties. In other words, attention can switch control of the neuronal response to the stimulus of interest, independently of its saliency, so that the target will determine the response of that neuron; in other words, the response of a given neuron to a pair of stimuli impinging on its RF will equate the neuronal response to the target stimulus, when presented alone. As a consequence, the neuronal representation of the target is enhanced within visual areas at the expense of the visual representation of the distractor (Corbetta et al., 1990; Treue & Trujillo, 1999; Luck et al., 2000, for reviews, see Chelazzi et al., 2011; Carrasco, 2011; Roe et al., 2012). Importantly, there is a wide range of observations which describe the impact of attention on sensory representations along the visual pathway. Crucially, attentional biasing of the neuronal activity within visual cortices is not uniform, but rather results in different forms of neuronal modulation (see e.g. Treue & Martinez Trujillo, 1999; Fries et al., 2001, 2008; Martinez-Trujillo & Treue, 2002; Carrasco et al., 2000; Carrasco, 2006). The traditional view of VSA maintains that attentional control is organized in a master-slave hierarchical manner: Modulatory top-down signals from a distributed frontoparietal attentional network (e.g. Moore, Armstrong, 2003; Wardak et al., 2004; Silvanto et al., 2006) - the master - impact on sensory (visual) cortical areas - the slave. In other words, lower-order sensory areas execute visual representations commanded via feedback projections from higher-order centers. Recent research has greatly challenged this conventional view, leading to the new and striking hypothesis that master centers do not have an exclusive role in attentional control, but rather the slave ventral (and dorsal) visual pathway areas might capitalize on their internal microcircuitry to directly instantiate attentional mechanisms even in the absence of control from master centers (e.g. Reynolds & Heeger, 2009; Baluch & Itti, 2011). Interestingly, a behavioral assessment following circumscribed lesions of macaque areas V4 and TEO showed a strong impairment in the animal ability to select a stimulus based on its behavioral relevance while discarding other, perceptually more conspicuous stimuli; in other word, after lesions to those areas, the behavior of the animal was at the mercy of stimulus salience (De Weerd et al., 1999; see also Gallant et al., 2000 for analogous findings in humans). These areas along the ventral pathway have therefore been claimed as essential for the instantiation of attentional mechanisms, and in particular mechanisms for the efficient filtering of non-relevant distractors (De Weerd et al., 1999; Chelazzi et al., 2011). The aim of the present study is to extend the current understanding of the brain mechanisms underlying VSA, by directly testing their possible residence within the human object-recognition pathway itself. An excellent human slave candidate to test this possibility is represented by the lateral occipital cortex (LO), a mid-tier area of the ventral stream, which is a key node for shape-object perception (Malach et al., 1995). Specifically, by applying TMS stimulation over human LO (or a control site), we examined the role of LO during a VSA task, in order to directly test its role in the attentional filtering of distracting information. Crucially, we manipulated the timing of TMS application in two related experiments, in order to disentangle the contribution of LO to perceptual and attentional operations. As a result, we observed TMS modulation of activity within LO area during the attentional processing of our VSA task. By using early TMS (before stimulus display onset) and late TMS (during stimulus display onset) application over LO cortex, we obtained more general perceptual enhancement and more specific improvement of attentional filtering, respectively. We can therefore conclude that human slave LO area contains internal attentional microcircuits necessary for attentional target selection and distractor filtering.

This article reviews the contribution of transcranial magnetic stimulation (TMS) research to the understanding of attention, eye movements, visual search, and neglect. It considers how TMS studies have confirmed, refined, or challenged prevailing ideas about the neural basis of higher visual cognition. It shows that TMS has enhanced the understanding of the location, timing, and functional roles of visual cognitive processes in the human brain. The main focus is on studies of posterior parietal cortex (PPC), with reference to recent work on the frontal eye fields (FEFs). TMS offers many advantages to complement neuropsychological patient studies to enhance the understanding of how the fronto-parietal cortical nerves function. The visuo-spatial neglect- and extinction-like deficits incurred by parietal damage have been modelled successfully using TMS. Future work might be directed at teasing apart the distinct functional roles of nodes within this frontoparietal network in different sensorimotor contexts.

Attention, working memory, decision-making, and executive control are fundamental cognitive functions that involve large-scale networks largely defined on the basis of functional magnetic resonance imaging (fMRI) studies. These networks include areas of the lateral and medial prefrontal, orbitofrontal, anterior, and midcingulate cortices, anterior insula, and lateral and medial posterior parietal cortices as well as areas of the temporal lobe and temporoparietal junction. These networks include the dorsal and ventral attention networks, frontoparietal, cingulo-opercular and salience control networks, and the default mode network. These networks are located along a hierarchical gradient of cortical organization. Dysfunction of large-scale cortical networks is a cardinal feature of neurodegenerative dementias and psychiatric disorders.

This chapter addresses functional magnetic resonance imaging (fMRI) of brain in children with neurodevelopmental and behavioral disorders. Common challenges of pediatric fMRI studies are related to acquisition and processing. In children with disruptive behavior disorders, deficits in affective response, empathy, and decision-making have been reported. Resting-state fMRI studies in attention-deficit hyperactivity disorder (ADHD) have shown altered activity in default mode and cognitive control networks. Task-based fMRI studies in ADHD have implicated frontoparietal cognitive and attentional networks. The role of stimulants in restoring the altered brain function has been examined using fMRI studies. In children with autism spectrum disorder, fMRI studies using face-processing tasks, theory-of-mind tasks, imitation, and language processing (e.g., sentence comprehension), as well as studies of gaze aversion, interest in social faces, and faces with emotions have implicated cerebellum, amygdala, hippocampus, insula, fusiform gyrus, superior temporal sulcus, planum temporale, inferior frontal gyrus, basal ganglia, thalamus, cingulate cortex, corpus callosum, and brainstem. In addition, fMRI has been a valuable research tool for understanding neurobiological substrates in children with psychiatric disorders (e.g., psychosis, posttraumatic stress disorder, and anxiety disorders).