Can Depression be Diagnosed by Response to Mother's Face? A Personalized Attachment-Based Paradigm for Diagnostic fMRI

OBJECTIVE: Objective measurement of depression remains elusive. Depression has been associated with insecure attachment, and both have been associated with changes in brain reactivity in response to viewing standard emotional and neutral faces. In this study, we developed a method to calculate predicted scores for the Beck Depression Inventory II (BDI-II) using personalized stimuli: fMRI imaging of subjects viewing pictures of their own mothers. METHODS: 28 female subjects ages 18-30 (14 healthy controls and 14 unipolar depressed diagnosed by MINI psychiatric interview) were scored on the Beck Depression Inventory II (BDI-II) and the Adult Attachment Interview (AAI) coherence of mind scale of global attachment security. Subjects viewed pictures of Mother (M), Friend (F) and Stranger (S), during functional magnetic resonance imaging (fMRI). Using a principal component regression method (PCR), a predicted Beck Depression Inventory II (BDI-II) score was obtained from activity patterns in the paracingulate gyrus (Brodmann area 32) and compared to clinical diagnosis and the measured BDI-II score. The same procedure was performed for AAI coherence of mind scores. RESULTS: Activity patterns in BA-32 identified depressed subjects. The categorical agreement between the derived BDI-II score (using the standard clinical cut-score of 14 on the BDI-II) and depression diagnosis by MINI psychiatric interview was 89%, with sensitivity 85.7% and specificity 92.8%. Predicted and measured BDI-II scores had a correlation of 0.55. Prediction of attachment security was not statistically significant. CONCLUSIONS: Brain activity in response to viewing one's mother may be diagnostic of depression. Functional magnetic resonance imaging using personalized paradigms has the potential to provide objective assessments, even when behavioral measures are not informative. Further, fMRI based diagnostic algorithms may enhance our understanding of the neural mechanisms of depression by identifying distinctive neural features of the illness

Socially connected brains: Mechanisms that shape our social networks and positions within them

The overarching goal of the present research is to gain a better understanding of mechanisms that shape our interpersonal ties and social networks by investigating their associated brain bases in naturally occurring groups. All three studies rely on a novel round-robin neuroimaging paradigm that incorporates group members as both participants in the fMRI scanner (perceivers) and stimuli (targets) presented during a naturalistic face-viewing task. Study 1 elucidates how group members’ popularity is tracked by neural systems underlying valuation (i.e., processing reward value and evaluating others’ motivational significance), which in turn engage social cognition systems that facilitate understanding others’ mental states. Individual differences in the sensitivity of this neural mechanism are examined and found to correlate with perceivers’ own popularity. Studies 2 and 3 extend the paradigm developed in Study 1 to incorporate social network data collected in a longitudinal context, and further test whether neural measures collected during the initial stages of group formation can prospectively predict group members’ future liking ties (Study 2) and social network centrality (Study 3). In Study 2, neural activity in the aforementioned valuation systems predicts newly acquainted group members’ future—but not current—idiosyncratic liking of one another. Further analyses suggest this effect reflects only one facet of a far more nuanced interpersonal phenomenon implicated in the eventual emergence of dyadic liking reciprocity: individuals’ initial liking preferences are not personally tracked by their own brains’ idiosyncratic valuation responses to particular group members, but rather interpersonally tracked by the neural valuation responses they uniquely evoke in those particular group members; moreover, each dyad member’s idiosyncratic valuation activity influences both their own and each other’s future liking. Having established in Studies 1 and 2 a paradigm for measuring how social network members implicitly evaluate one another, Study 3 extends it to include oneself (i.e., the perceiver) as an evaluate target of social perception. Revisiting the Study 1 social network members’ data, enhanced valuation activity in response to oneself (relative to others) correlates positively with questionnaire measures of dispositional narcissism (but not self-esteem) and negatively with sociometric popularity. Using the data from Study 2, the trait narcissism effect is replicated and extended to a context in which the “others” are newly acquainted group members. This longitudinal data also reveals that the neural measure of narcissistic self-valuation prospectively predicts future (un)popularity, even controlling for initial levels of popularity. Considered together, this research aims to integrate conceptual and methodological frameworks across social psychology (e.g., round-robin experimental designs), cognitive neuroscience (e.g., fMRI), and sociology (e.g., social network analysis)

Interplay Between Default-Mode and Task-Positive Networks: Functional Characterization of the Brain's Large-Scale Neural Systems.

Recent work has demonstrated that the human brain is functionally organized into distinct large-scale networks, with particular attention focused on the default-mode network (DMN) and the anti-correlated “task-positive” networks. Despite the growing evidence that these neural systems are intrinsically connected at rest and during the performance of cognitive functions, little is known about network relationships during tasks that actively recruit DMN, such as social cognition. Characterizing how the functions and the interactions of the DMN may modulate brain activity in other large-scale neural systems may be a critical step in advancing our understanding of network dynamics. Using behavioral and functional magnetic resonance imaging (fMRI) experiments, this dissertation aims: 1) To characterize network dynamics when functions carried out by the DMN are required, and 2) to determine the modulatory effects of task demand on network dynamics in processing these functions. Four experiments were developed to address these aims. Using a task that probes a fundamental aspect of social cognition - appraising another individual, experiment 1 showed parallel recruitment of the DMN (medial prefrontal and posterior cingulate cortices) and the task-positive network (pre-SMA, dACC, bilateral fronto-parietal cortices). Connectivity analyses (psychophysiological interaction) further showed functional interaction within the DMN, and with the task-positive network, both vary as a function of social preference. In another set of experiments, a novel dual-task paradigm was developed that parametrically manipulated factors known to affect cortical activity in the default-mode and task-positive networks: social cognition and spatial working memory demand, respectively. Two behavioral experiments showed selective interference, manifested as a drop in working memory accuracy, between spatial working memory and the evaluative appraisal of self, suggesting functional overlap. Finally, a neuroimaging experiment adopted this dual-task paradigm to examine the interactions between DMN, social cognition and task demand. Significant social cognition-by-task demand interactions were present in multiple regions of the DMN (medial prefrontal regions) and the task-positive networks (primarily posterior parietal foci). Overall, these results suggest that network dynamics, at least between the two neural systems considered herein, are dependent on social cognition as well as task demand.Ph.D.NeuroscienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/75923/1/cnchen_1.pd

Meaning in words - How social context amplifies processing of emotional language

Schindler S. Meaning in words - How social context amplifies processing of emotional language. Bielefeld: Universität Bielefeld; 2016.Language is a unique and core human ability. Language is abstract and arbitrary and yet it enables us to communicate with each other. Language allows communication and communication is inherently social. Communicating with and about others is of highest interest for humans, as humans are social beings. This is why receiving human feedback is often extremely emotional. Although we have an extensive knowledge about the neuronal bases of emotional language processing, there are only a few studies yet conducted to investigate socio-communicative influences on language processing. In my dissertation I examine the influence of a social communicative partner on emotional language processing. Three studies systematically manipulated the expertise and identity of putative interaction partners. These interaction partners gave feedback on positive, negative and neutral adjectives while a high-density Electroencephalogram (EEG) was recorded. Actually, in all conditions random feedback was presented, thus a differential processing could only be attributed to sender characteristics. By means of event-related potentials (ERPs), the influence of sender characteristics, emotional content and their interaction was observed. In studies I and II - as a proof of principle - a 'human sender' was compared to a random computer (unequal expertise, unequal humanness). In this study, both feedback anticipation (study I) as well as feedback presentation was investigated (study II). In study III the 'human sender' was compared to a socially intelligent computer (similar expertise, unequal humanness). Eventually, in a fourth study a 'human expert' was compared to a 'layperson' and a random computer sender (unequal expertise, but the 'expert' and 'layperson' were both 'humans'). During anticipation of 'human' feedback, an extremely early enhanced general processing was found. On later stages a more intense processing of emotional adjectives was found in the 'human sender' condition. In general, effects during feedback presentation were substantially larger than during feedback anticipation. Here, large effects were found on early and late ERP components, for both human-generated and emotional feedback. Further, emotional feedback given by a 'human' was additionally amplified. Eventually, in study IV 'expert-feedback' was processed most intensely, followed by 'layperson-feedback' and finally 'computer-feedback'. Localization methods found enhanced sensory processing for 'human-generated' and emotional feedback. Studies III and IV showed additionally increased activations in somatosensory and frontal effects for 'human senders'. Overall, these experiments showed that not only emotional content but particularly also communicative context influences language processing. We automatically seem to take context factors into account when processing language. Here, 'expertise' results in an enhanced processing aldready on early and highly automatic stages, while supposed humanness seems to be of highest relevance: 'Human-generated' feedback led to enhanced processing in sensory, but also somatosensory and frontal areas. This shows that in human interactions language is amplified processed, which is especially true for emotional language. This dissertation shows for the first time that in realistic communicative settings (emotional) language processing is altered. Here, it seems that first sender information is processed, while emotional content affects later processing stages. The use of state of the art source localization methods enabled to get next to the extremely high temporal resolution (when something happens), a good and reliable spatial resolution (where something happens) of the cortical generator structures of the ERP effects

An investigation of self-biases in perception and visual perspective taking

This thesis addressed three questions regarding our tendency to prioritise recently learned self-associations. Following an overview of cognitive self-biases in Chapter 1, Chapter 2 explored how novel self-associations impact higher-level social cognition, namely, visual perspective taking (VPT). In Experiments 1–3, we examined how participants respond to third-person perspectives (3PPs) associated with self and other. Participants showed superior performance when explicitly targeting a self-associated (vs. other-associated) 3PP. Chapter 3 extended this line of research by examining whether these self-bias effects are related to social-cognitive ability and executive function. In Experiments 4–5, we found that both individual differences in empathy and putative age-relevant motivations reliably modulated self-bias in third-person VPT. These findings suggest that VPT paradigms draw on domain-specific and domain-general capacities. Chapter 4 examined the extent to which interpersonal dimensions (e.g., day-to-day personal relevance and valence) may explain self-tagging effects. Using behavioural and fMRI methodology, Experiments 6–8 showed that self-processing was largely independent of responses to relevance and valence in others. Finally, Chapter 5 provides a broader discussion of findings from the preceding chapters, offering some possible future research directions