Academic literature on the topic 'Ventral attention network'

The ventral attentional network (VAN) is thought to drive “stimulus driven attention” [e.g., Asplund, C. L., Todd, J. J., Snyder, A. P., & Marois, R. A central role for the lateral prefrontal cortex in goal-directed and stimulus-driven attention. Nature Neuroscience, 13, 507–512, 2010; Shulman, G. L., McAvoy, M. P., Cowan, M. C., Astafiev, S. V., Tansy, A. P., D' Avossa, G., et al. Quantitative analysis of attention and detection signals during visual search. Journal of Neurophysiology, 90, 3384–3397, 2003]; in other words, it instantiates within the current stimulus environment the top–down attentional biases maintained by the dorsal attention network [e.g., Kincade, J. M., Abrams, R. A., Astafiev, S. V., Shulman, G. L., & Corbetta, M. An event-related functional magnetic resonance imaging study of voluntary and stimulus-driven orienting of attention. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 25, 4593–4604, 2005]. Previous work has shown that the dorsal attentional network is sensitive to trial history, such that it is challenged by changes in task goals and facilitated by repetition thereof [e.g., Kristjánsson, A., Vuilleumier, P., Schwartz, S., Macaluso, E., & Driver, J. Neural basis for priming of pop-out during visual search revealed with fMRI. Cerebral Cortex, 17, 1612–1624, 2007]. Here, we investigate whether the VAN also preserves information across trials such that it is challenged when previously rejected stimuli become task relevant. We used fMRI to investigate the sensitivity of the ventral attentional system to prior history effects as measured by the distractor preview effect. This behavioral phenomenon reflects a bias against stimuli that have historically not supported task performance. We found regions traditionally considered to be part of the VAN (right middle frontal gyrus, inferior frontal gyrus and right supramarginal gyrus) [Shulman, G. L., McAvoy, M. P., Cowan, M. C., Astafiev, S. V., Tansy, A. P., D' Avossa, G., et al. Quantitative analysis of attention and detection signals during visual search. Journal of Neurophysiology, 90, 3384–3397, 2003] to be more active when task-relevant stimuli had not supported task performance in a previous trial than when they had. Investigations of the ventral visual system suggest that this effect is more reliably driven by trial history preserved within the VAN than that preserved within the visual system per se. We conclude that VAN maintains its interactions with top–down stimulus biases and bottom–up stimulation across time, allowing previous experience with the stimulus environment to influence attentional biases under current circumstances.

The ability to inhibit motor response is crucial for daily activities. However, whether brain networks connecting spatially distinct brain regions can explain individual differences in motor inhibition is not known. Therefore, we took a graph-theoretic perspective to examine the relationship between the properties of topological organization in functional brain networks and motor inhibition. We analyzed data from 141 healthy adults aged 20 to 78, who underwent resting-state functional magnetic resonance imaging and performed a stop-signal task along with neuropsychological assessments outside the scanner. The graph-theoretic properties of 17 functional brain networks were estimated, including within-network connectivity and between-network connectivity. We employed multiple linear regression to examine how these graph-theoretical properties were associated with motor inhibition. The results showed that between-network connectivity of the salient ventral attention network and dorsal attention network explained the highest and second highest variance of individual differences in motor inhibition. In addition, we also found those two networks span over brain regions in the frontal-cingulate-parietal network, suggesting that these network interactions are also important to motor inhibition.

Fluctuations in resting-state functional connectivity occur but their behavioral significance remains unclear, largely because correlating behavioral state with dynamic functional connectivity states (DCS) engages probes that disrupt the very behavioral state we seek to observe. Observing spontaneous eyelid closures following sleep deprivation permits nonintrusive arousal monitoring. During periods of low arousal dominated by eyelid closures, sliding-window correlation analysis uncovered a DCS associated with reduced within-network functional connectivity of default mode and dorsal/ventral attention networks, as well as reduced anticorrelation between these networks. Conversely, during periods when participants’ eyelids were wide open, a second DCS was associated with less decoupling between the visual network and higher-order cognitive networks that included dorsal/ventral attention and default mode networks. In subcortical structures, eyelid closures were associated with increased connectivity between the striatum and thalamus with the ventral attention network, and greater anticorrelation with the dorsal attention network. When applied to task-based fMRI data, these two DCS predicted interindividual differences in frequency of behavioral lapsing and intraindividual temporal fluctuations in response speed. These findings with participants who underwent a night of total sleep deprivation were replicated in an independent dataset involving partially sleep-deprived participants. Fluctuations in functional connectivity thus appear to be clearly associated with changes in arousal.

Neuroimaging studies have demonstrated that the right temporoparietal junction (TPJ) is activated during detection of salient stimuli, including pain, in the sensory environment. Right TPJ damage more often produces spatial neglect than left TPJ damage. We recently reported a right lateralized system of white matter connectivity of the TPJ. However, lateralization in intrinsic TPJ functional connectivity during a task/stimuli-independent state has not been fully characterized. Here we used resting-state functional MRI in healthy humans to compare the functional connectivity of right and left TPJ with salience- and attention-related brain networks. Independent components analysis revealed that both right and left TPJ were functionally connected with a network that included the anterior insula, dorsolateral prefrontal cortex (PFC), and mid-cingulate cortex, considered to be the salience/ventral attention network. Dual regression revealed this network was more strongly connected with right TPJ than left TPJ. Seed-based functional connectivity analysis showed 1) negative connectivity the TPJ bilaterally with the “default mode network”; 2) positive connectivity of TPJ bilaterally with the salience/ventral attention network; 3) stronger connectivity between right TPJ compared with left TPJ with regions within the salience/ventral attention network and mid-insula, S2, and temporal/parietal opercula (implicated in pain); and 4) stronger connectivity of left TPJ compared with right TPJ with the “executive control network,” including the dorsomedial/medial PFC, inferior frontal gyrus, and cerebellum (crus I/II). Our findings build on classic lesion and neuroimaging studies, demonstrating a complex spatial network organization of lateralization in TPJ functional connectivity in the absence of an overt stimulus.

Scholastic performance is the key metric by which schools measure student’s academic success, and it is important to understand the neural-correlates associated with greater scholastic performance. This study examines resting-state functional connectivity (RsFc) associated with scholastic performance (reading and mathematics) in preadolescent children (7–9 years) using an unbiased whole-brain connectome-wide multi-voxel pattern analysis (MVPA). MVPA revealed four clusters associated with reading composite score, these clusters were then used for whole-brain seed-based RsFc analysis. However, no such clusters were found for mathematics composite score. Post hoc analysis found robust associations between reading and RsFc dynamics with areas involved with the somatomotor, dorsal attention, ventral attention, limbic, frontoparietal, and default mode networks. These findings indicate that reading ability may be associated with a wide range of RsFc networks. Of particular interest, anticorrelations were observed between the default mode network and the somatomotor, dorsal attention, ventral attention, and frontoparietal networks. Previous research has demonstrated the importance of anticorrelations between the default mode network and frontoparietal network associated with cognition. These results extend the current literature exploring the role of network connectivity in scholastic performance of children.

Meditation experience has previously been shown to improve performance on behavioral assessments of attention, but the neural bases of this improvement are unknown. Two prominent, strongly competing networks exist in the human cortex: a dorsal attention network, that is activated during focused attention, and a default mode network, that is suppressed during attentionally demanding tasks. Prior studies suggest that strong anti-correlations between these networks indicate good brain health. In addition, a third network, a ventral attention network, serves as a “circuit-breaker” that transiently disrupts and redirects focused attention to permit salient stimuli to capture attention. Here, we used functional magnetic resonance imaging to contrast cortical network activation between experienced focused attention Vipassana meditators and matched controls. Participants performed two attention tasks during scanning: a sustained attention task and an attention-capture task. Meditators demonstrated increased magnitude of differential activation in the dorsal attention vs. default mode network in a sustained attention task, relative to controls. In contrast, there were no evident attention network differences between meditators and controls in an attentional reorienting paradigm. A resting state functional connectivity analysis revealed a greater magnitude of anticorrelation between dorsal attention and default mode networks in the meditators as compared to both our local control group and a n = 168 Human Connectome Project dataset. These results demonstrate, with both task- and rest-based fMRI data, increased stability in sustained attention processes without an associated attentional capture cost in meditators. Task and resting-state results, which revealed stronger anticorrelations between dorsal attention and default mode networks in experienced mediators than in controls, are consistent with a brain health benefit of long-term meditation practice.

We investigated the neuronal processes which occur during a decision- making task based on a perceptual classi cation judgment. For this purpose we have analysed three di erent experimental paradigms (somatosensory, visual, and auditory) in two di erent species (monkey and rat), with the common goal of shedding light into the information carried by neurons. In particular, we focused on how the information content is preserved in the underlying neuronal activity over time. Furthermore we considered how the decision, the stimuli, and the con dence are encoded in memory and, when the experimental paradigm allowed it, how the attention modulates these features. Finally, we went one step further, and we investigated the interactions between brain areas that arise during the process of decision- making.
Durant aquesta tesi hem investigat els processos neuronals que es pro- dueixen durant tasques de presa de decisions, tasques basades en un ju- dici l ogic de classi caci o perceptual. Per a aquest prop osit hem analitzat tres paradigmes experimentals diferents (somatosensorial, visual i auditiu) en dues espcies diferents (micos i rates), amb l'objectiu d'il.lustrar com les neurones codi quen informaci on referents a les t asques. En particular, ens hem centrat en com certes informacions estan cod- i cades en l'activitat neuronal al llarg del temps. Concretament, com la informaci o sobre: la decisi o comportamental, els factors externs, i la con- ana en la resposta, b e codi cada en la mem oria. A m es a m es, quan el paradigma experimental ens ho va permetre, com l'atenci o modula aquests aspectes. Finalment, hem anat un pas m es enll a, i hem analitzat la comu- nicaci o entre les diferents arees corticals, mentre els subjectes resolien una tasca de presa de decisions.

Les capacités attentionnelles sont nécessaires à la plupart des tâches de la vie quotidienne. Au cours du vieillissement normal, ces habiletés se modifient. De même, les études suggèrent que l’activité neurofonctionnelle du réseau fronto-pariétal qui sous-tend les capacités attentionnelles diffère entre les individus âgés et de jeunes adultes. Par contre, les changements en contexte du vieillissement du réseau fronto-pariétal ventral, aussi appelé le réseau attentionnel ventral, ont été peu investigués. Une telle question doit être soulevée dans le contexte où les plus récents modèles décrivant les changements fonctionnels associés au vieillissement rapportent que des possibles transformations neurofonctionnelles peuvent survenir au niveau intrahémisphérique et interhémisphérique. Le but de cet ouvrage est de déterminer comment le vieillissement normal affecte le réseau attentionnel ventral et de décrire la nature des changements qui peuvent survenir sur les axes intra et interhémisphériques. Pour y parvenir, la méthode de connectivité fonctionnelle fut privilégiée puisqu’elle permet de quantifier l’interaction neurofonctionnelle entre diverses régions composant un réseau fonctionnel. La première étude de cette thèse a permis de décrire les modifications de connectivité fonctionelle intrahémisphériques du réseau attentionnel ventral en comparant des adultes jeunes et âgés lorsqu’ils réalisent une tâche d’attention sélective en imagerie par résonance magnétique. Sur le plan comportemental, les individus âgés répondaient significativement plus lentement et commettaient davantage d’erreurs que le groupe composé de jeunes adultes. Les résultats de connectivité fonctionnelle montrent que le degré d’intégration de la connectivité fonctionnelle intrahémisphérique est globalement plus élevé chez les individus âgés dans l’ensemble des régions fronto-pariétales composant ce réseau. De plus, il semble que les aires antérieures du réseau, soit les aires préfrontales et insulaires, sont moins intégrées chez les individus âgés, alors que les zones pariétales, temporales et cérébelleuses le sont davantage. Le degré d’intégration de la connectivité est également plus élevé chez les adultes âgés entre les régions postérieures et antérieures. Ainsi, les résultats de cette étude suggèrent que la dynamique des régions antérieures et postérieures du réseau attentionnel ventral est modifiée au cours du vieillissement normal et que les régions postérieures occupent au sein de ce réseau un rôle plus important avec l’âge. Cette hyperconnectivité des aires pariétales pourrait représenter une stratégie de compensation intrahémisphérique (i.e. recrutement de régions additionnelles en postérieur) qui aurait cependant atteint un certain plateau puisque bien que les âgés réussissent à réaliser la tâche, ils performent significativement plus faiblement que de jeunes adultes. La seconde étude s’est intéressée aux modifications de connectivité interhémisphériques du même réseau fonctionnel en comparant le degré de connectivité fonctionnelle entre des individus jeunes et âgés. De manière similaire à l’étude 1, sur le plan comportemental les individus âgés répondaient significativement plus lentement et commettaient plus d’erreurs que les jeunes adultes. En ce qui concerne la dimension inter-hémisphérique du réseau, les résultats des analyses de connectivité montrent que le degré d’intégration des régions hémisphériques gauches fronto-pariétales et temporales est plus faible pour les participants âgés que pour les participants jeunes. Au contraire, les régions frontales, pariétales, temporales et sous-corticales de l’hémisphère droit sont plus intégrées. Par ailleurs, les résultats montrent également que le degré d’intégration interhémisphérique est plus élevé chez les individus âgés. Ainsi, cette étude suggère que le degré de connectivité fonctionnelle entre les régions hémisphériques droites du réseau attentionnel ventral augmente au cours du vieillissement, suggérant ainsi une amplification de la latéralisation de ce réseau vers l’hémisphère droit avec l’âge. Cette étude montre également que malgré une augmentation de la latéralisation du VAN à droite, celle-ci s’accompagne d’une augmentation du degré de connectivité fonctionnelle interhémisphérique qui pourrait être envisagée comme une tentative de compensation interhémisphérique (i.e. recrutement des régions homologues) qui aurait atteint toutefois un certain plateau car même si les âgés réussissent à réaliser la tâche, leur niveau de performance reste significativement plus faible que les jeunes. En somme, ce travail a permis de contribuer à notre compréhension de l’impact du vieillissement sur le réseau attentionnel ventral sur l’axe intrahémisphérique et interhémisphérique. Cet ouvrage lance de nouvelles pistes d’investigation dans ce domaine et pourrait éventuellement mener à l’élaboration d’interventions susceptibles de promouvoir une santé cognitive optimale lors du vieillissement.
Attention is necessary for most of daily life’s tasks. During aging, these cognitive abilities are changed. Studies suggest that the neurofunctional activity of the frontoparietal network, which upholds the attentional capacities, differ between young and older adults. However, age-related changes of the ventral frontoparietal network, also called the ventral attention network, have been less investigated. Such question has to be raised in context of recent models of neurofunctional changes in aging, who report possible functional transformation that could occur both at the intrahemispheric and interhemispheric levels. The goal of the present thesis is to determine how aging affects the ventral attention network and describe the nature of such changes that can occur on the intrahemispheric and interhemispheric axis. To do so, functional connectivity methods were favoured because of their capacity to measure the neurofunctional interaction between the regions of a network. The first study of the present thesis has allowed describing the age-related intrahemispheric modifications of functional connectivity in this network by comparing young and older adults while they respond on a selective attention task during a functional magnetic resonance imagery scan. On the task, aged adults performed significantly slower and made more errors than the young adults. At the functional connectivity level, the results show higher level of the functional connectivity between all frontoparietal regions of this network for the older group. Further, the integration level of functional connectivity in anterior regions of the network seems to be less integrated for the older participants, while posterior regions have more neurofunctional signal dependency. Also, the level of integration of functional connectivity is higher in older adults between anterior and posterior regions. Thus, results from this study suggest that the anterior and posterior regions of the ventral attention network interact differently during aging and that the posterior regions play a more important role with age in this network. This hyperconnectivity in the parietal regions could represent an unsuccessful intrahemispheric compensation attempt (i.e. recruitment of additional regions in posterior part of the brain) since older adults perform significantly less well than younger adults. The second study has investigated interhemispheric alterations of functional connectivity in the same functional network by comparing young and older adults. Like in the first study, younger adults were faster to respond on task and were more accurate. Regarding the neurofunctional lateralization of the network, the degree of functional connectivity is lower in older adults for the left hemisphere’s frontoparietal and temporal regions. However, older adults have a higher degree of functional connectivity in the right frontal, parietal, temporal and subcortical regions of the same network. Also, the results also show that the interhemispheric integration level is superior for the older adults. Thus, this study suggests that the level of functional connectivity with the right hemisphere’s regions of the ventral attention network increases with age, which could suggest an age-related lateralization of this network towards the right hemisphere. In this context, increased interhemispheric functional connectivity could be interpreted as a failed interhemispheric compensation attempt (i.e. recruitment of homologous regions) since the performance of older adults on task was significantly lower than younger adults. In short, this work has allowed contributing to our understanding of the impact of aging on the ventral attention network both on the intrahemispheric and interhemispheric axis. These various results bring up new hypothesis that needs to be investigated in further studies and eventually that could lead to the establishment of intervention that promote an optimal healthy cognitive aging.

ADHD patients appear to have complex multisystem impairments in several cognitive-domain dissociated inferior, dorsolateral, and medial fronto-striato-parietal and frontocerebellar neural networks during inhibition, attention, working memory, and timing functions. There is emerging evidence for abnormalities in motivation and affect control regions, most prominently in ventral striatum, but also orbital/ventromedial frontolimbic areas. Furthermore, there is an immature interrelationship between hypoengaged task-positive cognitive control networks and a poorly ‘switched off’ default mode network, both of which impact performance. Stimulant medication enhances the activation of inferior frontostriatal systems, while atomoxetine appears to have more pronounced effects on the dorsal attention network. More studies are needed to understand the neurofunctional correlates of the effects of age, gender, ADHD subtypes, and comorbidities with other psychiatric conditions. The use of pattern recognition analyses applied to imaging to make individual diagnostic or prognostic predictions are promising and will be the challenge over the next decade.

In recent years, there have been many studies on attention. These studies have found that there are two distinct kinds of neural networks employed for visual attention and tactile attention, respectively. This review summarizes the processing mechanism of these attention-related brain networks. One type is the top-down attention related brain structure, which includes the IPs/SPL (intraparietal sulcus/superior parietal lobule)-FEF (frontal eye field). The other is the bottom-up attention related brain structure, which includes the TPJ (temporoparietal junction)-VFC (ventral frontal cortex). Regarding research into tactile attention, in conclusion, the authors found that tactile attention had a similar neural network to that of visual attention in that there was top-down attention to the relevant IPs-FEF and bottom-up attention to the relevant TPJ-VFC.

Attention is generally taken to be the process by which people are able to concentrate on certain information or processes, while ignoring other events. It appears to be a fundamental attribute of human brain processing, although difficult to pin down in terms of mechanism. Psychologists have attempted to fractionate attention in many different ways, using ingenious behavioural paradigms. In this section we, too, will consider different aspects of attention: selective, phasic and sustained, divided and executive control of attention. However, it would be fair to say that all these aspects of attention do not normally operate in isolation. Instead they interact, and deficiencies in one aspect of attention, for example, in a patient population, often to do not occur in isolation. Functional imaging and lesion studies of attention have proliferated in recent years, attempting to place a neurobiological framework to these varied processes. In general, these studies also tend to confirm the view that attention is likely an emergent property of widespread brain networks, with a special emphasis on frontal and parietal regions of the human brain (Fig. 2.5.2.1). In this discussion we illustrate several aspects of attention with examples particularly from literature on visual attention, which is the most widely studied area, but it should be appreciated that many of the concepts discussed here extend to other domains. In fact, there is a good deal of evidence to suggest that several aspects of attention operate at a supra- or cross-modal level allowing integration of information from different sources. Recent studies suggest there are two fronto-parietal networks: (Fig. 2.5.2.1) a dorsal parieto-frontal network involving the superior parietal lobe (SPL) and dorsal frontal regions such as the frontal eye field (FEF); and a ventral network involving the inferior parietal lobe (IPL), temporoparietal junction (TPJ) and inferior frontal gyrus (IFG). In addition, dorsomedial frontal areas, including the anterior cingulate cortex (ACC) and pre-supplementary area (pre-SMA) may play a key role in flexible control of attention for strategic behaviour.

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.