Emotion and motivation have crucial roles in determining human behavior. Yet, how they interact with cognitive control functions is less understood. Here, the basic elements of a conceptual framework ...for understanding how they interact are introduced. More broadly, the ‘dual competition’ framework proposes that emotion and motivation affect both perceptual and executive competition. In particular, the anterior cingulate cortex is hypothesized to be engaged in attentional/effortful control mechanisms and to interact with several other brain structures, including the amygdala and nucleus accumbens, in integrating affectively significant signals with control signals in prefrontal cortex. An implication of the proposal is that emotion and motivation can either enhance or impair behavioral performance depending on how they interact with control functions.
The current view of brain organization supports the notion that there is a considerable degree of functional specialization and that many regions can be conceptualized as either 'affective' or ...'cognitive'. Popular examples are the amygdala in the domain of emotion and the lateral prefrontal cortex in the case of cognition. This prevalent view is problematic for a number of reasons. Here, I will argue that complex cognitive-emotional behaviours have their basis in dynamic coalitions of networks of brain areas, none of which should be conceptualized as specifically affective or cognitive. Central to cognitive-emotional interactions are brain areas with a high degree of connectivity, called hubs, which are critical for regulating the flow and integration of information between regions.
A subcortical pathway through the superior colliculus and pulvinar to the amygdala is commonly assumed to mediate the non-conscious processing of affective visual stimuli. We review anatomical and ...physiological data that argue against the notion that such a pathway plays a prominent part in processing affective visual stimuli in humans. Instead, we propose that the primary role of the amygdala in visual processing, like that of the pulvinar, is to coordinate the function of cortical networks during evaluation of the biological significance of affective visual stimuli. Under this revised framework, the cortex has a more important role in emotion processing than is traditionally assumed.
How does motivation interact with cognitive control during challenging behavioral conditions? Here, we investigated the interactions between motivation and cognition during a response conflict task ...and tested a specific model of the effect of reward on cognitive processing. Behaviorally, participants exhibited reduced conflict during the reward versus no-reward condition. Brain imaging results revealed that a group of subcortical and fronto-parietal regions was robustly influenced by reward at cue processing and, importantly, that cue-related responses in fronto-parietal attentional regions were predictive of reduced conflict-related signals in the medial pFC (MPFC)/ACC during the upcoming target phase. Path analysis revealed that the relationship between cue responses in the right intraparietal sulcus (IPS) and interference-related responses in the MPFC during the subsequent target phase was mediated via signals in the left fusiform gyrus, which we linked to distractor-related processing. Finally, reward increased functional connectivity between the right IPS and both bilateral putamen and bilateral nucleus accumbens during the cue phase, a relationship that covaried with across-individual sensitivity to reward in the case of the right nucleus accumbens. Taken together, our findings are consistent with a model in which motivationally salient cues are employed to upregulate top–down control processes that bias the selection of visual information, thereby leading to more efficient stimulus processing during conflict conditions.
In the past few years, important contributions have been made to the study of emotional visual perception. Researchers have reported responses to emotional stimuli in the human amygdala under some ...unattended conditions (i.e. conditions in which the focus of attention was diverted away from the stimuli due to task instructions), during visual masking and during binocular suppression. Taken together, these results reveal the relative degree of autonomy of emotional processing. At the same time, however, important limitations to the notion of complete automaticity have been revealed. Effects of task context and attention have been shown, as well as large inter-subject differences in sensitivity to the detection of masked fearful faces (whereby briefly presented, target fearful faces are immediately followed by a neutral face that ‘masks’ the initial face). A better understanding of the neural basis of emotional perception and how it relates to visual attention and awareness is likely to require further refinement of the concepts of automaticity and awareness.
A study that goes beyond the debate over functional specialization to describe the ways that emotion and cognition interact and are integrated in the brain.
Understanding the correlation structure associated with multiple brain measurements informs about potential “functional groupings” and network organization. The correlation structure can be ...conveniently captured in a matrix format that summarizes the relationships among a set of brain measurements involving two regions, for example. Such functional connectivity matrix is an important component of many types of investigation focusing on network-level properties of the brain, including clustering brain states, characterizing dynamic functional states, performing participant identification (so-called “fingerprinting”) understanding how tasks reconfigure brain networks, and inter-subject correlation analysis. In these investigations, some notion of proximity or similarity of functional connectivity matrices is employed, such as their Euclidean distance or Pearson correlation (by correlating the matrix entries). Here, we propose the use of a geodesic distance metric that reflects the underlying non-Euclidean geometry of functional correlation matrices. The approach is evaluated in the context of participant identification (fingerprinting): given a participant’s functional connectivity matrix based on resting-state or task data, how effectively can the participant be identified? Using geodesic distance, identification accuracy was over 95% on resting-state data, and exceeded the Pearson correlation approach by 20%. For whole-cortex regions, accuracy improved on a range of tasks by between 2% and as much as 20%. We also investigated identification using pairs of subnetworks (say, dorsal attention plus default mode), and particular combinations improved accuracy over whole-cortex participant identification by over 10%. The geodesic distance also outperformed Pearson correlation when the former employed a fourth of the data as the latter. Finally, we suggest that low-dimensional distance visualizations based on the geodesic approach help uncover the geometry of task functional connectivity in relation to that during resting-state. We propose that the use of the geodesic distance is an effective way to compare the correlation structure of the brain across a broad range of studies.
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Emotion is often understood in terms of a circumscribed set of cortical and subcortical brain regions. I propose, instead, that emotion should be understood in terms of large-scale network ...interactions spanning the entire neuroaxis. I describe multiple anatomical and functional principles of brain organization that lead to the concept of ‘functionally integrated systems’, cortical–subcortical systems that anchor the organization of emotion in the brain. The proposal is illustrated by describing the cortex–amygdala integrated system and how it intersects with systems involving the ventral striatum/accumbens, septum, hippocampus, hypothalamus, and brainstem. The important role of the thalamus is also highlighted. Overall, the model clarifies why the impact of emotion is wide-ranging, and how emotion is interlocked with perception, cognition, motivation, and action.
Research on the emotional brain has often focused on a few structures thought to be central to this type of processing—hypothalamus, amygdala, insula, and so on. Conceptual thinking about emotion has ...viewed this mental faculty as linked to broader brain circuits, too, including early ideas by Papez and others. In this article, we discuss research that embraces a distributed view of emotion circuits and efforts to unravel the impact on emotional manipulations on the processing of several large-scale brain networks that are chiefly important for mental operations traditionally labeled with terms such as “perception,” “action,” and “cognition.” Furthermore, we describe networks as dynamic processes and how emotion-laden stimuli strongly affect network structure. As networks are not static entities, their organization unfolds temporally, such that specific brain regions affiliate with them in a time-varying fashion. Thus, at a specific moment, brain regions participate more strongly in some networks than others. In this dynamic view of brain function, emotion has broad, distributed effects on processing in a manner that transcends traditional boundaries and inflexible labels, such as “emotion” and “cognition.” What matters is the coordinated action that supports behaviors.
The aims of this study were to perform the cross-cultural adaptation of the Borg Rating of Perceived Exertion (RPE) 6-20 Scale to Brazilian Portuguese language and to start testing its validity and ...reliability. After performing the cross-cultural adaptation of the Scale, concurrent and discriminative validity, and reliability were determined on a treadmill in young (18-30 years) and older adult women (60-75 years). Considering young and older adult women, RPE presented high and moderate positive correlation with heart rate and high and low positive correlation with oxygen consumption, respectively. Older adult women presented RPE (11 ± 2) significantly higher than young ones (8 ± 1) exercising at the same absolute intensity. Intraclass coefficient correlation was excellent for RPE to young and older adult women. The Scale presented concurrent validity only to young adult women, whereas it presented discriminative validity between such groups of women. Moreover, the scale is reliable to young and older adult women.
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