brain integrity in reference to a normative sample. Since the quantitative neuroimaging, including DTI measures only assess the anatomical aspects of the network, functional activation of a ROI or network could be assessed with functional MRI (fMRI).
Table 3.2 Networks creating the functioning social brain (the letters in the table refer to entries in the references list at the end of the chapter).
| Affective Networks | Emotional scene and face processing a, e, f, h, i, m, o, s, t, z, dd |
| Reward‐related decision making c, d, e, f, h, i, m, aa, dd | |
| Cognitive emotion regulation a, c, d, e, f, g, h, i, j, k, l, m, n, p, q, r, s, t, v, w, x, y, z, bb, cc, dd, ee, ff, gg | |
| Executive Networks | Vigilant attention a, b, c, e, h, i, k, m, o, t, u, z, dd, gg |
| Cognitive action control a, b, c, e, f, g, h, i, j, k, l, m, n, q, t, v, w, x, z, bb, cc, dd, ee, ff, gg | |
| Extended multi‐demand c, e, h, i, m, s, t, v, w, z, bb, dd, ee | |
| Working memory c, h, i, m, q, s, t, z, aa, bb, dd | |
| Social Networks | Empathy a, b, d, e, f, g, h, i, k, l, m, n, r, w, x, y, z, cc, dd, ee, ff |
| Mirror neuron system a, c, e, h, i, k, l, m, t, z, cc, dd | |
| Theory of mind a, b, c, e, g, h, i, j, k, l, m, o, p, r, t, u, w, y, bb, cc, dd, ee, ff | |
| Task‐deactivation and Interacting Networks | Default mode c, e, h, i, m, n, q, s, t, u, aa, dd, ee |
| Extended socio‐affective default b, d, e, f, g, h, i, k, l, m, n, o, p, r, s, t, v, w, x, y, z, aa, bb, cc, dd, ee, ff |
A gradient difference can be detected in the fMRI signal from oxygenated to the de‐oxygenated state when a particular ROI is participating in a function (Jones et al., 2020). This is the basis for what is referred to as blood oxygen level dependent (BOLD) contrast imaging. Detection of increased BOLD fMRI signal shows regional changes in oxygen uptake that can be used to infer task participation.
The BOLD fMRI method introduced another novel neuroimaging technique to study social brain development (Kishida & Montague, 2012; Tymofiyeva et al., 2020). Returning to the brain structures identified in Figures 3.5 and 3.7 and Table 3.1, social‐developmental experiments could be designed and brain activation patterns assessed to target those structures. For example, an empirically designed social scenario could be crafted to display a visual threat simulation, all presented in the MR scanner, studying fMRI brain activation patterns. This fMRI approach permitted a more direct way to study the role of ROI brain structures like the amygdala in perceiving threatening social situations, to include how these types of neural responses are governed by maturation (Hein & Monk, 2017; McClure et al., 2007; Muhlberger et al., 2011; Noack et al., 2019; Sudre et al., 2017). This approach has even been used in large research centers with multiple scanners, where research participants engage in social discourse all‐the‐while in separate MRI machines, allowing real‐time BOLD activation to study human social interaction between individuals (Xie et al., 2020).
As well as the fMRI brain activation paradigms described above, considerable information about neural networks can actually be extracted from imaging the brain at rest (Kim & Yoon, 2018; Sato & Uono, 2019; Tompson et al., 2018, 2020; Wong et al., 2019). Using fMRI techniques in conjunction with other neuroimaging and electrophysiological measures led to the discovery of what is referred to as the “default mode network” (DMN) (Raichle, 2015). Justifiably, cognitive neuroscience in the past had been focused on activation techniques in the quest to examine regional and coordinated brain activity, as described in the previous paragraph. But what occurred with the discovery of the DMN focused brain regions that became disengaged from an activity or the state of brain activity just prior to engagement. These studies showed a network of frontal, parietal, and temporal lobe regions, all of which displayed characteristic connectivity and organization when at rest. In other words, until the brain had to respond, DMN controlled the brain’s idle, keeping the brain in a “ready” position for when activation was necessary.
While a variety of functional neuroimaging methods have been used to study the DMN, the most common have used a fMRI paradigm (Al‐Ezzi et al., 2020), especially in the study of social cognition (Schilbach et al., 2008). In fact, early in the discovery of the DMN, Schilbach et al. noted the “remarkable overlap between the brain regions typically involved in social cognitive processes and the ‘default system’. We, henceforth, suggest that the physiological ‘baseline’ of the brain is intimately linked to a psychological ‘baseline’: human beings have a predisposition for social cognition as the default mode of cognizing which is implemented in the robust pattern of intrinsic brain activity known as the ‘default system’” (2008, p. 457). The resting state fMRI quickly resulted in a new method to examine brain connectivity, referred to as resting state (rs), functional connectivity (fc) MRI or rs‐fcMRI (Nielsen et al., 2014; Parkes et al., 2020), which has become a mainstay in network theory and development related to understanding the social brain.
With these novel methods for neuroimaging‐identified networks, the emphasis shifted to how these networks interfaced with the DMN and how many separate networks related to social processing and responding that could be identified.
Identifying Social Brain Networks and their Role in Social Functioning
The burgeoning field of cognitive neuroscience, neuroimaging and social‐developmental researchers began to further parse out the networks that governed social development (Redcay & Warnell, 2018; Schurz et al., 2020). Table 3.2 represents a partial list of those networks considered to be important in social‐emotional development that have been identified using DTI, rs‐fcMRI mapping and structural image analysis. Note that many are basic for a particular motor, sensory, language, or general cognitive function, but all relate back to essential requirements for social development. For example, the interplay between the visual processing network, ability to visually perceive and detect facial emotion in another individual, to retain that information and use it to modify and regulate behavior in response to that individual requires multiple network systems simultaneously interacting to make even the simplest of a social gesture between two individuals.
All of the networks shown in Table 3.2 take years to develop. Cortical regions do not necessarily have the same growth curves as does the whole brain as was shown in Figure 3.3, and maturation curves differ for each lobe and ROI as well (Bigler, 2021). This is shown in Figure 3.8 from Somerville. Note in terms of the GM pruning and cortical thickness, that the frontal lobe exhibits the slowest maturation. This also links with neurobehavioral assessments that demonstrate
