1 / 33

Branislava Ćurčić-Blake, Marte Swart and André Aleman

Frontal lobe activation mediates the activation of the amygdala during cognitive-emotional learning : an effective connectivity study. Branislava Ćurčić-Blake, Marte Swart and André Aleman

ferrol
Télécharger la présentation

Branislava Ćurčić-Blake, Marte Swart and André Aleman

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Frontal lobe activation mediates the activation of the amygdala during cognitive-emotional learning : an effective connectivity study Branislava Ćurčić-Blake,Marte Swart and André Aleman Cognitive Neuropsychiatry group, Neuroimaging center (NIC), University medical center Groningen (UMCG), The Netherlands

  2. Overview • Quick introduction and key points regarding DCM • Our emotional learning study • Questions and suggestions welcome at any point

  3. A B A B Phenomenon of brain connectivity? • Anatomical : The connections between brain areas by means of white matter tracts (groups of axons) • Functional :Analyses of inter-regional effects: what are the interactions between the elements of a given neuronal system? How functionally specialised regions interact with each other • a) Functional connectivity: • the temporal correlation between spatially remote neurophysiological events • b) Effective connectivity • the influence that the elements of a neuronal system exert on each other

  4. DCM • Neat method to establish effective connectivity (as defined by Friston!) • A well-defined model or set of models is required • The fMRI data dynamics are modeled • Make inferences about processes that underlie measured time series • Idea is to estimate parameters of a reasonably realistic neuronal system model such that predicted BOLD corresponds as close as possible to measured BOLD From Burkhard Pleger, Functional Imaging Lab, University College London

  5. What DCM can do and what cannot • DCM can make inferences about how much the activity in area A can induce change of activation in area B! • DCM cannot make inferences about speed of the processes, nor timing.

  6. z λ y DCMConceptual overview Neural state equation The bilinear model effective connectivity modulation of connectivity integration hemodynamic model Friston et al. 2003, NeuroImage

  7. Input u(t) direct inputs c1 b23 neuronal states a12 activity z2(t) activity z3(t) activity z1(t) y y y BOLD Important coefficients • A –Effective connectivity • B – modulatory effects • C - Inputs

  8. observation model posterior  likelihood ∙ prior ηθ|y How it works in practice: parameter estimation • Combining the neural and hemodynamic states gives the complete forward model. • An observation model includes measurement errore and confounds X (e.g. drift). • Bayesian parameter estimation • Result:Gaussian a posteriori parameter distributions, characterised by mean ηθ|y and covariance Cθ|y and posterior covariance of noise Ce.

  9. Choosing the model Bayes Theorem Bayes factor Akaike information criterion (AIC): Bayesian information criterion (BIC): Penny et al. 2004, NeuroImage Here p is the number of parameters and Nsis the number of data points

  10. Cognitive-Emotional learning study • What is known about emotional learning • Our idea • Our experiments • Results and Conclusions

  11. Emotional learning • “Emotional memories constitute the core of our personal history” (La Bar 2006) • Learning is enhanced or inhibited by emotions (Phelps 2004, Richter-Levin 2004) • Emotions can • Enhance memory (Learning emotional words or faces; Kensinger 2004) • Modulate memory (LeDeux) • Inhibit memory (spatial learning followed by stress – rats in water maze: reviewed in Richter-Levin 2004) • LaBar,K.S. & Cabeza,R. Cognitive neuroscience of emotional memory. Nat Rev Neurosci 7, 54-64 (2006). • Phelps,E.A. Human emotion and memory: interactions of the amygdala and hippocampal complex. Curr. Opin. Neurobiol. 14, 198-202 (2004). • Richter-Levin,G. The amygdala, the hippocampus, and emotional modulation of memory. Neuroscientist. 10, 31-39 (2004). • Kensinger,E.A. & Corkin,S. Two routes to emotional memory: distinct neural processes for valence and arousal. Proc. Natl. Acad. Sci. U. S. A 101, 3310-3315 (2004). • LeDoux,J. The emotional brain: misterious underpinnings of emotional life. Simon & Schuster, New York (1996).

  12. Emotional learning • Amygdala and Hippocampus complex are anatomically connected (Ameral 1992; Stefanacci 1996); • Emotional enhancement of learning: • Amygdala modulates encoding and storage of Hippocampal memories. • Hippocampal complex (episodic representations, interpretations of events) can influence the amygdala response to emotional stimuli. • Hippocampus – Amygdala effective connectivity is modulated by positive and negative emotions during emotional retrieval (Smith et al. 2006). • Amygdala modulates parahippocampal and frontal regions during emotional memory storage (Kilpatric 2003) and encoding item for + and – stimuli (Kensinger 2006) etc. 1. D. G. Amaral, J. L. Price, A. Pitkänen, S. T. Carmichael, in The Amygdala: Neurobiological aspects of emotion, memory and mental dysfunction, J. P. Aggleton, Ed. (Wiley Liss, New York, 1992). 2. L. Stefanacci, W. A. Suzuki, D. G. Amaral, J.Comp Neurol. 375, 552-582 (1996). 3. E. A. Phelps, Curr.Opin.Neurobiol. 14, 198-202 (2004). 4. E. A. Kensinger and D. L. Schacter, J.Neurosci. 26, 2564-2570 (2006). 5. L. Kilpatrick and L. Cahill, Neuroimage. 20, 2091-2099 (2003).

  13. The emotional situations influence memory on its every stage: • Encoding (LeDeux 1996; Kensinger 2006) • Consolidation (Richter-Levin 2004) • Storage (Kilpatric 2003; Phelps 2004) • Retrieval (Smith 2006) • LeDoux,J. The emotional brain: misterious underpinnings of emotional life. Simon & Schuster, New York (1996). • E. A. Kensinger and D. L. Schacter, J.Neurosci. 26, 2564-2570 (2006). • Richter-Levin,G. The amygdala, the hippocampus, and emotional modulation of memory. Neuroscientist. 10, 31-39 (2004). • E. A. Phelps, Curr.Opin.Neurobiol. 14, 198-202 (2004). • L. Kilpatrick and L. Cahill, Neuroimage. 20, 2091-2099 (2003). • Smith,A.P., Stephan,K.E., Rugg,M.D. & Dolan,R.J. Task and content modulate amygdala-hippocampal connectivity in emotional retrieval. Neuron 49, 631-638 (2006).

  14. Brain areas involved Data pooled across nine experiments consistently show haemodynamic changes evoked by conditioned fear stimuli in the amygdala and subjacent periamygdaloid cortex (coronal sections, left), and the thalamus and anterior cingulate/dorsomedial prefrontal cortex (ACC/DMPFC, mid-sagittal section, right). Functional MRI (fMRI) activation is monitored while healthy adults encode high-arousing negative words, low-arousing negative words (valence only) and neutral words. LaBar,K.S. & Cabeza,R. Cognitive neuroscience of emotional memory. Nat Rev Neurosci 7, 54-64 (2006).

  15. MFcortex and IFcortex • Emotional memory studies show also involvement of MFC and IFC • MFC is sensitive to tasks involving emotions, mental state attribution (1), monitoring for and detecting errors (2), and mentalizing (3). • IFC is engaged in emotion regulation, processing semantic aspects of face recognition, and language tasks. The left IFG selects the task-relevant information (emotional connotation as target information from specific competing semantic alternatives; 4). • Olsson,A. & Ochsner,K.N. The role of social cognition in emotion. Trends Cogn Sci. 12, 65-71 (2008). • Summerfield,C. et al. Predictive Codes for Forthcoming Perception in the Frontal Cortex. Science 314, 1311-1314 (2006). • Amodio,D.M. & Frith,C.D. Meeting of minds: the medial frontal cortex and social cognition. Nat Rev Neurosci 7, 268-277 (2006). • Ethofer,T. et al. Cerebral pathways in processing of affective prosody: A dynamic causal modeling study. NeuroImage 30, 580-587 (2006)

  16. Model of Amygdala involvement in Emotional Learning • Potential mechanisms by which the amygdala mediates the influence of emotional arousal on memory. LaBar,K.S. & Cabeza,R. Cognitive neuroscience of emotional memory. Nat Rev Neurosci 7, 54-64 (2006).

  17. Our aim • how the emotions and cognition interact during cognitive emotional learning ? • whether the emotions revealed by activation of the amygdala modulate the way in which the cognition works during an associative emotional learning task that engages HIGHER COGNITIVE PROCESSES during the learning of emotional stimuli. • We incorporate both positive and negative emotional stimuli in order to see whether these circles differ and if so, how.

  18. Starting point • Data obtained from experiments by Marte Swart • Students: 20 LOW score on BVAQ (Bermond-Vorst Alexithymia Questionnaire). • An emotional picture-word associate learning task (ALT) • Thus cognitive emotional processing

  19. Task ALT Dopicture and word fit? Memorize Roomijs (= ice-cream in English)) 3sec 2-8sec The task • An emotional picture (International Affective Picture System) and a word were displayed for 3 seconds. • 2-8 seconds to decide if the word and picture fitted together AND to remember them

  20. MFGR AmyR AmyR FGR IFGR Results RFX analysis ALT emotional > neutral for low-alexithymia subjects (p<0.005, T>2.92, unc.). Crosshair [12,-16,-14], MNA. • bilateral amygdala (AMY), • inferior frontal gyrus (IFG), • medial frontal gyrus (MFG), and • fusiform gyrus (FG) during the ALT.

  21. MFGL IFGL AmyL AmyL IFGL AmyL The DCM ROI selection Fig. 3 Contrast as it is used to define VOI’s: ALT emotional >fixation point (random effects t-test) for 20 subjects. The IFG, MFG and Amy are circled for illustration (p<0.001, T>3.3, unc.). Crosshair [-22,-4,-16], MNI.

  22. The maximum activation per ROI

  23. The creation of VOI’s • The VOI’s for each subject ! • created by choosing the closest supra-threshold (p < 0.05) voxel • within the Maximum Probability Maps (of the Anatomical Toolbox in SPM5) • Belongs to the region (visual inspection) • Sphere of 4 mm drawn around • 10-33 voxels • Time series extracted • 1st Principal Component (PA)

  24. AMY AMY AMY AMY AMY AMY MF MF MF MF MF MF IF IF IF IF IF IF Model M Model I Model A Model MI Model AI Model MA Fig 4. Full DCM models with different areas of input for the selection of input area(s). Input is illustrated by black arrows, and effective connectivity by grey arrows. Checking for input

  25. IF IF IF IF IF IF MF MF MF MF MF MF AMY AMY AMY AMY AMY AMY Model #1 Model #2 Model #3 Model #4 Model #5 Model #6 Choosing the best connectivity mod Fig 5.Illustration of models of effective connectivity during an ALT. Input consisting of positive, negative and neutral conditions goes parallel to the IFG and MFG. In Model #1 the IF and MF communicate directly and with the Amy as opposed to #2 and #3 where the IF and MF communicate through the Amy. Models #4,5 and 6 are variations of model #1. The winning model #1 was also compared to the full MI model. The results are presented in Table 3.

  26. The resulting connectivities and modulatory effects Table 4b. Right Table 4 a. Left

  27. The resulting connectivities and modulatory effects Fig 6. Modulatory effects of the best DCM model. Increasing effect (red bold arrows) and decreasing effect (blue dashed arrow) are presented with the % of influence on the effective connectivity and the significance level (in brackets).

  28. Lateralization yes or no? • t – test between modulatory effects for left and right hemisphere showed NO significant difference between mean values of modulatory effects for each pair. • Thus, we can not claim that there is lateralization.

  29. Conclusions • The area involved in basic emotional learning (the amygdala) does not affect the change in activity of the cognitive areas (the IFG and MFG). • The subjects appear to pay more attention to the context and evaluation of the given stimuli, and these processes were not affected by emotions. • In our case it seems that the subjects concentrated on the task and suppressed their emotions to some extent

  30. Main conclusion • In conclusion, it is evident that complex emotional learning is led by a “top-down” process from the frontal areas- the MFG and IFG- to the amygdala.

  31. Pitfall • There are gender differences (Cahil et al 2001;2002): • Correlations between Left Amygdala – emotional memory enhancements for Females • Correlations between Right Amygdala – emotional memory enhancements for Males • We found no significant gender differences due to low statistical power for such a comparison

  32. Still • We have demonstrated that complex emotional learning is led by top-down processes from the frontal lobe toward the amygdala. • This type of learning is more complicated than conditioned fear therefore the learning circuit is more complex. • The top-down processes demonstrate that the cognition here is “emotion free”. • The amygdala might still play a role in the modulation of learning material delivered to the memory areas. (it does! data not shown here ;-D)

More Related