behaviorally inhibited monkeys demonstrate less coo calls...
TRANSCRIPT
Glucose
Glu
cose
Glucose
Glucose
Glu
cose
Glucose
Glu
cose
18-FDG
Glucose
Glu
cose
Glucose
Gluco
se
Glucose
Glu
cose
Glucose
Glu
cose
18-F
DG
18-FDG
Glucose
Glu
cose
Glucose
Gluco
se
Glucose
Glu
cose
Glucose
Glu
cose
18-F
DG
18-FDG
Glucose
Glu
cose
Glucose
Gluco
se
Glucose
Glu
cose
Glucose
Glu
cose
18-FDG
18-FDGGlucose
6P-FDG 6P-G
Phosphorylation
Glycolysis
Energy
18-FDGGlucose
6P-FDG 6P-G
Phosphorylation
Glycolysis
Energy
OH
HOOH
O
FHO
+
18-F 18-O
+
18-F
**+
**+
**+
Senso
r
Senso
r
Senso
r
PET Scanner
Behaviorally inhibited monkeys demonstrate less coo calls and more amygdala activation during separation
72.20/EE20
Departments of Psychology1, and Psychiatry2, and the Waisman Laboratory for Brain Imaging and Behavior3, at the Universtiy of Wisconsin-Madison
A.S.Fox1,3*, S.E.Shelton2, T.R.Oakes3, A.K.Converse3, R.J.Davidson1,2,3, N.H.Kalin2,3
Behavioral Inhibition
Vocalizations
Amygdala Cortisol
Time
Inte
nsi
ty
Individual 1Individual 2
Time
Inte
nsi
ty
Individual 1Individual 2
L R-3
-2
-1
0
1
2
3
-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5
Common Amygdala Region
Are
a 10
-3
-2
-1
0
1
2
3
Rig
ht
Are
a 46
-3
-2
-1
0
1
2
3
Lef
t A
rea
46
Extreme behavioral inhibition in childhood is a risk factor for the development of anxiety and affec-tive disorders (Fox NA et al., 2005). Individual differences in behavioral inhibition during childhood have been linked to increased cortisol levels (Buss et al., 2004), and increased amygdala respon-siveness to novelty in early adulthood (Schwartz et al., 2003). Moreover, work in rhesus monkeys demonstrated the amygdala to be involved in behavioral inhibition by using selective lesioning techniques (Emery et al., 2001; Kalin et al, 2004). Using Positron Emission Tomography (PET) im-aging in rhesus monkeys, our group observed individual differences in behavioral inhibition to be positively correlated with amygdala activity whereas individual differences in separation-induced cooing, or calling for help, were negatively correlated with amygdala activity (Fox AS et al., 2005). In the present study, we used high-resolution PET scanning in freely behaving rhesus monkeys to further examine amygdala activity in relation to extreme behavioral inhibition, cooing and plasma cortisol levels during separation.
Area 46/9
Area 10
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Low Med High
Co
mm
on
Am
ygd
ala
Reg
ion
-3
-2
-1
0
1
2
3
-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5
Co
rtis
ol
Common Amygdala Region
-3
-2
-1
0
1
2
3
-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5
Common Amygdala Region
Co
oin
g
AnteriorPosteriorL R L R
Positive Correlation with Cortisol in the Right Amygdala
High > Med Right Amygdala
Negative Correlation with Cooing in the Right Amygdala
The amygdala was significantly (p<.005, one-tailed uncor-rected) more activated in the high group (n=11) when com-pared to the medium group (n=12) during separation (p=.002).
The amygdala was significantly (p<.005, one-tailed uncorrected; n=35) positively correlated with plasma cortisol levels obtained following the behavioral para-digm (R2=.168).
The amygdala was significantly (p<.005, one-tailed un-corrected; n=35) negatively correlated with affiliative, coo vocalizations emitted during separation (R2=-.271).
While it has been suggested that behavioral inhibition may in part be due to alterations in self-regulation, no research has explored the neural basis for alterations in the regula-tion of emotion hypothesized to underlie behavioral inhibi-tion. Recent evidence suggests that the projections from the ventral-medial prefrontal cortex (VMPFC) to the amyg-dala may in part underlie the ability to regulate fear and anxiety related responses (Quirk et al., 2000; Quirk et al., 2003; Kim et al., 2004; Urry et al., 2006). The initiation of the VMPFC regulatory effects has been further suggested to involve the recruitment of dorsal-lateral prefrontal cortex (DLPFC; areas 46/9) and the anterior frontal pole (Area 10) (Davidson, Fox, & Kalin, in press; Johnstone et al., submitted; Kim et al., 2004; Urry et al., 2005).
A logical AND conjunction analysis within the amyg-dala revealed a significant (p<.005, one-tailed uncor-rected) region of the amygdala which differed be-tween the high and middle behavioral inhibition groups and was negatively correlated with the fre-quency of coo vocalizations, and positively corre-lated with cortisol.
Three groups of monkeys (High n=11; Med n=12; Low n=12) were selected from 117 ani-mals based on their propensity to be stably be-haviorally inhibited, as measured by their amount of freezing when presented with the profile of a human intruder (Kalin & Shelton, 1989).
Behavioral analyses for the behaviors occur-ring during the period of FDG uptake demon-strated significant differences across the be-havioral inhibition groups in freezing (F=5.585, p=.009) and cooing (F=8.924, p=.001) during separation. There were no significant differ-ences between groups in plasma cortisol levels when sampled immediately after the separation paradigm (F=1.199, p=.316).
Preprocessing of Imaging Data
MRI images were transformed into standard space and segmented according to standardized analysis protocols.
First, non-brain tissues were manually masked (i.e. set to zero) in all the MRI images. Masked MRI images were regis-
tered to a rhesus monkey template described in Fox et al. and Kalin et al., using a 60-parameter nonlinear registration as
implemented in the AIR software package (A. S. Fox et al., 2005; Kalin et al., 2005; Woods et al., 1998). Finally, MRI
images were segmented using a probabilistic segmentation algorithm, FSL (Zhang, Brady & Smith, 2001). The segmenta-
tion process created an image for each subject where the value of each voxel represented the probability of gray matter for
that voxel.
To facilitate across subject comparisons PET scans were transformed according to the MRI images using standard
methods (Worsley et al., 2002; Kalin et al., 2005). Specifically, FDG-PET scans were co-registered using a 6-parameter
rigid body registration to the anatomical MRI image taken from the same subject using the mutual information algorithm
implemented by FSL (Jenkinson and Smith, 2001). The transformations computed based on the MRI images were then
applied to the FDG-PET images resulting in individual FDG-PET scans in a standard space. To facilitate inter subject
comparisons, each FDG image was intensity normalized prior to statistical analyses. Intensity normalization was
performed based on a global scale factor determined by adjusting the mean based on whole-brain intensity values using
standard analysis techniques (Carmargo et al., 1992).
Statistical Analyses
Group comparisons were performed between the highly behaviorally inhibited group and the middle group exam-
ining differences in cooing and vocalizations as well as brain metabolism during separation. Group comparisons based on
ReferencesBuss K. A., et al. (2004). Developmental Psychology, 40(4), 583-594. Davidson R.J., et al. (in press). In J. Gross (Ed.), Handbook of Emotion
Regulation . New York: Guildford Press. Emery N. J., et al. (2001). Behavioral Neuroscience, 115(3), 515-544. Fox A. S., et al. (2005). Proc Nat Acad Sci USA, 102(11), 4176-4179. Fox N. A., et al. (2005). Ann Rev Psych, 56, 235-262. Jenkinson M., & Smith S. (2001). Med Image Anal. 5(2):143-56.Johnstone T., et al. (Submitted)Kalin N. H., & Shelton, S. E. (1989). Science, 243(4899), 1718-1721. Kalin N. H., et al. (2004). Journal of Neuroscience, 24(24), 5506-5515. Kalin N. H., et al. (2005) Biological Psychiatry, 58(10), 796-804.
This work was suppported by the HealthEmotions Research Institute, Meriter Hospita, and NIH Grants MH46729 and MH69315. We would like to thank T Johnstone, A Shackman, H Van Valkenberg, T Johnson, and the staff at the Harlow Center for Biological Psychology and the National Primate Research Center at the University of Wisconsin for their technical support.
brain metabolism were performed on a whole-brain voxelwise basis. Correlations were performed between brain metabo-
lism and the frequency of cooing occurring during the separation period and with cortisol levels assessed from samples
collected immediately after the separation period. All statistical comparisons involving brain metabolism were performed
on a voxelwise basis statistically controlling for age and gray-matter probability, to control for differences in anatomy
(Oakes et al., in press; Worsley et al., 1998). To investigate the common neural mechanisms that underlie different facets of
behavioral inhibition (i.e. group, cooing, and cortisol), a conjunction analysis was performed using a logical AND conjunc-
tion (Nichols, et al., 2005). The conjunction analysis was performed at the p<.005, one-tailed uncorrected threshold on a
voxelwise basis within the amygdala.
The relationship between amygdala activity with the rest of the brain in the highly inhibited group was compared
with that in the other groups. This was done by computing a voxelwise regression between the amygdala and the rest of the
brain in the middle group after statistically controlling for age and gray-matter probability (Oakes et al., in press; Worsley
et al., 1998). After identifying the regions that were significantly negatively correlated with the amygdala we examined the
highly inhibited group to determine the correlations between the amygdala and the same areas to see if the highly behavior-
ally inhibited monkeys showed a different relationship. This was done by extracting the regression coefficients attributable
to the amygdala and their standard deviations at each voxel in both the highly behaviorally inhibited and the middle groups.
Resulting regression coefficients were compared to each other using standard multiple regression techniques (Cohen et al.,
2003). The resulting statistical parametric map of t-values tested the null hypothesis at each voxel that the two groups had
equivalent correlations between that voxel and the amygdala.
Results in the Right Amygdala
Results demonstrated Areas 46/9 and 10 to be significantly (p<.005, one-tailed uncorrected) nega-tively associated with amygdala in the middle group (n=12; Right-R2=-.660, Left R2=-.663). Further analyses revealed these areas to show a significantly (p<.005, one-tailed uncorrected) greater negative correlation than the high group (n=11; Right-R2=.218, Left-R2=.199).
Regulation Results
Emotion Regulation
Kim H, et al. (2004). Journal of Cognitive Neuroscience, 16(10), 1730-1745.Nichols T. et al., (2005). Neuroimage, 25(3):653-60.Oakes T. R., et al. (In Press) Neuroimage.Quirk G. J., et al. (2003). Journal of Neuroscience, 23, 8800-8807. Quirk G. J., et al. (2000). Journal of Neuroscience, 20, 6225-31. Schwartz C. E. et al., (2003) Science, 300(5627), 1952-1953. Urry H. L. et al., (2006) Journal of Neuroscience, 26(16), 4415-4425. Woods RP, et al. (1998) J Comput Assist Tomogr 22:153-165.Worsley KJ, et al. (2002). NeuroImage, 15:1:15.Worsley KJ, et al. (1998). NeuroImage , 6:305-319.
2.65
2.7
2.75
2.8
2.85
2.9
2.95
3
ALNALN NECNEC
HHighigh
MMeded
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Low Med High
Co
oin
g +
SE
(Men
) LOW
MED
HIGH
LOW
MED
HIGH
0
50
100
150
200
250
300
350
400
450
Low Med HighBehavioral Inhibition GroupF
reezi
ng
+ S
E(M
ean
)
Screening 1 Screening 2
Definition of Groups
FDG PET Paradigm
Behavioral Paradigm
0 min.
Injection of Radiotracer
20 min. 40 min.
AnesthisiaInjection
Transportation
BeginPET Scan
10 min. 30 min. ~50 min.
FDG in theBrain
After identification of the 3 groups of animals, each monkey underwent a [18F]-fluoro-2-deoxy-D-glucose (FDG) PET scan to investi-gate the integrated neural activity associated with separation from their partner into a test cage. FDG was administered immediately prior to the 30 min separation period after which the monkeys were anesthetized and scanned.
Behavioral Analysis
FDG PET Methods
These results suggest that during social separation heightened amygdala activity is associated with excessive behavioral inhibition and decreased attempts to call for help. Furthermore, the relation-ship between amygdala activity and prefrontal cortex activity may underlie individual differences in the ability to appropriately regulate behavioral inhibition. Increased amygdala activity in behaviorally inhibited individuals may impair their ability to recruit social support during periods of stress which could be related to their increased risk to develop anxiety and depression.
Discussion
Introduction