The Psychological Construction of Emotion by Lisa Feldman Barrett

Author:Lisa Feldman Barrett
Language: eng
Format: azw3, epub
ISBN: 9781462517022
Publisher: Guilford Publications
Published: 2014-12-28T16:00:00+00:00

BRAIN NETWORKS FOR RESOURCE ALLOCATION

Overall, as reviewed earlier, the data gathered from animal and human studies support the existence of reward networks with important subcomponents of wanting, liking, and learning. While it is tempting to work out the circuitry of brain regions in these networks in isolation, it is pertinent to take a more global brain perspective on how to interpret the changes found in brain activity (Lindquist & Barrett, 2012; Oosterwijk, Touroutoglou, & Lindquist, Chapter 5, this volume).

In particular it is important to integrate these reward networks with activity in widely distributed brain networks, often called resting state networks. We have previously speculated that activity in one of these brain resting state networks, the so-called default mode network (Gusnard & Raichle, 2001; Raichle et al., 2001) is closely linked to reward processing and may have an important role in shaping our overall well-being (Kringelbach & Berridge, 2009).

The last few years have seen a shift in the focus of modern neuroimaging from the study of extrinsic to intrinsic brain activity (Biswal et al., 2010). This change has been brought about by the realization that while the vast majority of neuroimaging studies have been devoted to studying task-related changes in brain activity, the additional energy associated with this activity is remarkable low, often less than 5% (Raichle & Mintun, 2006). Instead, the majority of brain energy consumption study is devoted to intrinsic brain activity.

Such intrinsic brain activity was mapped during the resting period in cognitive studies in which researchers found a network of brain regions with remarkably high rates of change in metabolic markers such as cerebral blood flow, oxygen extraction, and blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) (Lou et al., 1999). In this network of brain regions termed the default mode network, the main regions showed the largest deactivations during extrinsic cognitive tasks (Gusnard & Raichle, 2001; Raichle et al., 2001).

Subsequent sophisticated independent component analyses of resting state patterns have identified at least seven networks that stay coherent over several minutes (Damoiseaux et al., 2006). Based on their brain components, these networks have been classified in (1) primary input–­output networks (including sensorimotor, visual, and auditory regions), (2) higher integrative networks (including attention, language, default mode, and executive regions; Beckmann, DeLuca, Devlin, & Smith, 2005), and (3) cortical–­subcortical networks (including structures such as the thalamus, basal ganglia, and cerebellum; Fox & Raichle, 2007). Interestingly, regions of the default mode network remain tightly coherent but tend to show negative correlations with task-positive regions in the other networks.

The intrinsic activity of the human brain must be closely related to the large-scale anatomical connectivity between brain regions (Barrett & Satpute, 2013). Techniques such diffusion spectrum imaging and graph theory have revealed that the human brain exhibits a special kind of topology known as small-world architecture (Watts & Strogatz, 1998), which is characterized by high levels of local clustering among neighboring nodes (Bullmore & Sporns, 2009; Hagmann et al., 2007). Some nodes have higher connectivity in comparison with other nodes and are called hubs (He et al.

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