1. Neural substrates of rumination tendency in non-depressed individuals
Xiao Chen 陈骁
The R-fMRI Lab, Institute of Psychology, Chinese Academy of Science

2. Outline
Introduction
Methods
Results
Discussion

3. Introduction Rumination
“ruminations are repetitive and passive thinking about symptoms of depression and the possible causes and consequences of these symptoms”
Susan Nolen-Hoeksema (1959 – 2013)

4. Introduction

5. Introduction What am I doing to deserve this? Why can’t I get going?
Why do I always react this way?

6. Introduction Rumination Depression
Rumination is an important vulnerability factor in the development of depression
Constitute a maladaptive mental habit in depression

7. Introduction Cognitive mechanisms behind rumination
Executive Functions
Cognitive inflexibility and difficulties in disengaging attention from irrelevant information

8. Introduction Rumination? Neural substrates of rumination
Emotional Reactivity
Rumination?
Cognitive control

9. Introduction Subjects: 19 healthy participants
Tasks: recall of autobiographical negative memories and subsequent focus on elicited emotions
Results: rumination is associated with activity in subgenual ACC (sgACC) and medial PFC
Subjects: MDD
Task: rumination induction VS. abstract distraction
Results: increased activation in
amygdala, rostral anterior cingulate cortex/medial prefrontal cortex
(PFC), dorsolateral PFC, and parahippocampal cortex, during
rumination relative to an abstract distraction task
Subjects: depressed patients
Methods: factor structure &
A paradigm alternating cognitive and emotional tasks
Results: trait rumination correlated not only with amygdala but also hippocampus activity. Other regions in PCC, MPFC, dorsolateral PFC, and anterior insula
Subjects: MDD patients
Results: Rumination is associated with greater difficulties in deactivating the posterior cingulate cortex (PCC)
As well as lower activation in anterior cingulate cortex (ACC)
Subjects: 41 healthy participants
Tasks: analytical VS. experiential self-focus
Results: lower brooding scores measured by the RRS correlated with increased activation of the posterior midline structures
Task: Cognitive reappraisal of emotional pictures
Subjects: healthy female
Results: higher amygdala response when increasing negative affect
Lower medial prefrontal activity when decreasing negative affect.

10. Introduction

11. Introduction

12. Introduction Experiment design
Active cognitive condition(task switching paradigm)
Resting state condition

13. Introduction Hypothesis Lower attentional shifting abilities
Ruminative processes
Higher activation of self-related regions during lower cognitive load
Higher ruminative tendencies
Reduced engagement of the brain areas reflecting attentional control

14. Methods Participants: 20 healthy subjects ( 10 women & 10 men)
Questionnaires:
22 – items of the Ruminative Response Scale (RRS)
Beck Depression Inventory – II (BDI)
Beck Anxiety Inventory (BAI)

15. Methods
Behavioral task (task switching paradigm)

16. Methods
Reaction?
EMOTION

17. Methods Switch condition (high cognitive load)
Emotion
Gender
Color
Switch condition (high cognitive load)
Emotion
Emotion
Emotion
Repetition condition (low cognitive load)

18. Methods Data analysis Pre-processing steps: SPM5 + Matlab R2007b
Realign: iterative rigid body transformations
Normalize: MNI EPI template
Smooth: a Gaussian kernel with FWHM of 8 mm
Co-registration: A high-resolution structural image was co-registered with the mean image of the EPI seriesand normalized

19. Methods Cognitive task data: A two – step analysis:
GLM for event-related design in SPM5
1. The onsets of conditions of interest were convolved with the canonical hemodynamic response function (HRF) and used as a regressor in the individual design matrix (first level)
2. The individual statistical images from each condition were used in a second-level ANOVA analysis to create the contrasts of interest, i.e. Repetition (easy) versus Switching (difficult)conditions.

20. Methods Resting state data Same pre-processing steps
1. independent component analysis (ICA) using the GIFT toolbox
2. The group maps were then inspected to select networks of interest for subsequent analyses

21. Methods
Contrasts from the second level analysis of the cognitive task
Maps from the ICA analysis of resting state
Using a multiple linear regression model with the scores of each individual from the RRS, BDI, and BAI.

22. Results

23. Results
Reaction times and switch cost did not correlate with RRS, but accuracy across all trials showed a negative correlation with RRS(r (20) = −.54, p = .011).

24. Results Resting-state fMRI data an attentional network map
a visual network map
ICA analysis
DMN(medial prefrontal activations)
DMN(medial parietal activations)

25. Results
significant positive correlation for the visual network map between resting activity in the entorhinal cortex and the score of rumination

26. Results
A negative correlation for the attention network map between rumination scores and activity in the left middle occipital gyrus

27. Results
The first frontal-dominant DMN map showed a negative correlation of RRS with ACC and PCC, whereas the second map also showed a selective negative correlation in PCC and no effect in ACC.

28. Results Cognitive tasks Contrast Switch > Repetition
significant increases in regions associated with attentional shifting and monitoring, including bilateral superior parietal lobules (SPL) and PCC.
Contrast Repetition > Switch
significant activations in the left caudate nucleus, the right inferior frontal gyrus, the left superior frontal gyrus, and the right dorsomedial PFC

29. Results
3. the contrast “easy > difficult” and rumination
medial temporal lobe region strikingly similar to that observed in the previous analysis of resting state: i.e. the left entorhinal cortex

30. Results

31. Results
Higher RRS scores were associated with lower activity in the right anterior insula during the easy vs. difficult condition

32. Results
Brooding is not associated with the insula during the easy condition
This weaker effect found for brooding during rest might reflect that ruminations at rest are also linked to more adaptive components of rumination, such as reflection and problem solving in association with mind wandering, whereas intrusive thoughts during low attention demands are more specifically linked to the maladaptive component associated with brooding

33. Discussion

34. Discussion Support a hypothesis
People with a propensity to ruminate, even when non-depressed, tend to recruit brain systems mediating the retrieval of personal memories and self-related information more strongly or persistently than non-ruminators

35. Discussion Negative correlations
By contrast, the reverse correlation observed in visual areas during rest suggests that individual with higher self-focus and ruminations allocate less resources to the processing of sensory visual inputs from the external world and/or engage less in visual imagery during rest.

36. Discussion Findings about insula
The insula is implicated in self monitoring, saliency detection, and interoceptive awareness, we postulate that rumination tendencies may represent a maladaptive style of response with a relative lack of attention to bodily and affective signals in favor of internal cognitions

37. Discussion up
Cognitive load
down
Rumination

38. Discussion Executive Functions Rumination
These studies could not conclude if ruminations diminish cognitive resources, or if insufficient cognitive resources predispose to ruminations.

39. Thank you for your attention!