Search tips
Search criteria 


Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Neuropharmacology. Author manuscript; available in PMC 2013 January 1.
Published in final edited form as:
PMCID: PMC3196277

Impact of Chronic Hypercortisolemia on Affective Processing


Cushing syndrome (CS) is the classic condition of cortisol dysregulation, and cortisol dysregulation is the prototypic finding in Major Depressive Disorder (MDD). We hypothesized that subjects with active CS would show dysfunction in frontal and limbic structures relevant to affective networks, and also manifest poorer facial affect identification accuracy, a finding reported in MDD.Twenty-one patients with confirmed CS (20 ACTH-dependent and 1 ACTH-independent) were compared to 21 healthy controlsubjects. Identification of affective facial expressions (Facial Emotion Perception Test) was conducted in a 3 Tesla GE fMRI scanner using BOLD fMRI signal. The impact of disease (illness duration, current hormone elevation and degree of disruption of circadian rhythm), performance, and comorbid conditions secondary to hypercortisolemia were evaluated.CS patients made more errors in categorizing facial expressions and had less activation in left anterior superior temporal gyrus, a region important in emotion processing. CS patients showed higher activation in frontal, medial, and subcortical regions relative to controls. Two regions of elevated activation in CS, left middle frontal and lateral posterior/pulvinar areas, were positively correlated with accuracy in emotion identification in the CS group, reflecting compensatory recruitment. In addition, within the CSgroup, greater activation in left dorsal anterior cingulatewas related to greater severity of hormone dysregulation. In conclusion, cortisol dysregulation in CS patients is associated with problems in accuracy of affective discrimination and altered activation of brain structures relevant to emotion perception, processing and regulation, similar to the performance decrements and brain regions shown to be dysfunctional in MDD.

Keywords: HPA, cortisol, ACTH, emotion, affect, fMRI, Cushings


Excessive, chronic, exposure to high levels of glucocorticoids (GC) has multiple adverse effects on brain biology in animals and humans (Abercrombie et al, 2011; Akil et al, 1993; Axelson et al, 1993; Erickson et al, 2003; Lupien et al, 1998; Starkman et al, 1992; Tessner et al, 2007), most clearly in animal studies (Magarinos and McEwen, 1995; Roozendaal et al, 2009). Specifically, GC administration and/or threat challenges that increase GC concentrations in animals result in increased depressive and anxiety-like symptoms as well as enhancement of aversive/avoidance memories linked to limbic function(McEwen, 1997; Mitra and Sapolsky, 2008; Mitra et al, 2006; Vyas et al, 2003).These animal studies strengthen the hypothesis that GC exposure results in morphologic/functional changes in brain structures supporting memory and affective processing.

There is increasing interest in possible effects of chronic GC exposure on cognitive and affective processing in humans (Brown et al, 2007; Sapolsky, 2000; Seeman et al, 1997). While the animal studies are highly informative, there are difficulties in creating parallels between animal behaviors and human medical and psychiatric illnesses. Behaviors elicited in animals are not the same as those observed in humans, nor can they be clarified absent self-report of symptoms (Starkman et al, 1981).Investigation of in vivo brain changes in humans secondary to chronic GC exposure are needed in order to clarify translation of animal studies to humans and to better understand cognitive and affective outcomes in humans.

A useful human illustration of the pathophysiologic effects of chronic, excessive GC exposure is Cushings Syndrome (CS). In CS, chronic, stress-level concentrations of cortisol lead to depressed mood in over 60% of patients (Starkman et al, 1981), vegetative symptoms, abnormal sleep profiles (Shipley et al, 1992) and cognitive dysfunction, especially in memory (Forget et al, 2000; Starkman et al, 2001; Starkman et al, 1986a). In addition, there is evidence of reduced regional brain volumes in the hippocampus, as well as decreased glucose utilization during active hypercortisolism (Khiat et al, 1999; Starkman et al, 1992).

With normalization in cortisol levels following treatment, we have shown reductions in mood and anxiety symptoms (Starkman et al, 1986b), increase in memory and hippocampal volume (Starkman et al, 1999; Starkman et al, 2003), and improvements in fluency and processing speed (Hook et al, 2007). We have also observed a post-treatment decrease in depressed/anxious mood related to an increase in caudate head, but not hippocampal volume in this study (Starkman et al, 2007). In summary, the human work with CS, as well as the animal work with GC administration or manipulation suggest that chronic GC exposure has direct effects upon cognitive and affective functioning and supportive brain regions in medial temporal, limbic, and frontal areas.

Affective functioning and its neural correlates is an important, yet understudied area in humans that is also related to medial temporal function and disruption secondary to GC exposure. In human studies, a few functional neuroimaging studies of emotion processing and regulation in volunteers using observational, normal levels of GC have been conducted. Using naturalistic measurement of normal-range cortisol levels in healthy adults during fMRI, these studies demonstrate positive relationships of medial temporal and frontal activation with GC concentrations (Pruessner et al, 2008; Tessner et al, 2007; Urry et al, 2006; van Stegeren et al, 2007). In a PET study with a mixed bipolar and major depression (MDD) group, there was a positive association between left amygdala glucose metabolism and plasma cortisol concentrations (Drevets et al, 2002). In contrast, the study of acute GC administration in humans is now being explored more extensively with current imaging technologies, including in psychiatric groups (Abercrombie et al, 2011; Scheel et al, 2009).

In the present study, we extend our investigations of the impact of chronic GC exposure to sensitive brain regions with high GR/MR receptor concentrations. We expand our prior work with mood and cognition in CS to now use an affective identification task during fMRI. The goal of the present study was to examine the relationship between excessive GC exposure and disruption of affective networks and processing, by studying individuals with CS prior to treatment. We tested the following hypotheses: 1) CS patients would demonstrate decreased ability to identify facial expressions of emotion; 2) CS patients would exhibit dysfunction in frontal and limbic regions, regionsthat also mediate successful and efficient identification of facial emotional expressions; and 3) Decrements in emotional identification ability and markers of severity of HPA axis dysfunction and duration of hypercortisolemia would be related to abnormal activation in regions within the affective processing circuits

Materials and Methods


Twenty-one patients with CS and 21 healthy control subjects participated in the study after giving informed consent. The study was approved by the University of Michigan Institutional Review Board for Medical Experimentation, with protocols consistent with the Declaration of Helsinki. Demographic and select clinical data are reported in Table 1.

Table 1
Demographic and Clinical Data for CS and Control Participants

Patients with CS were recruited after the diagnosis was confirmed using diagnostic criteria which involved confirmation of elevated serum and urine free cortisol, absence of circadian rhythm and abnormal suppression with 1 mg dexamethasone (Schteingart, 1989). Twenty patients with CS were ACTH-dependent and had pituitary microadenomas confirmed by positive MRI, inferior petrosal sinus sampling, and/or transphenoidal surgery. One additional patient had pituitary-ACTH-independent CS due to adrenal cortical adenoma. This person was included in all analyses (except posthoc analyses with ACTH), as the imaging results were similar to patients who had pituitary-dependent disease.Three CS patients completed practice testing only. These patients had truncal obesity that exceeded the bore diameter for the 3 Tesla GE fMRI scanner and were unable to comfortably lie in the scanner to complete the protocol. One patient with CS had a history of longstanding seizure disorder. The results were in identical foci, but with larger extent of activation and Z values without inclusion. For sake of completeness given the small sample size, this subject was retained. The fMRI analyses compared the remaining 18 CS patients with the 21 control subjects.

The control subjects were recruited through advertisements in the Medical Center and surrounding community. The control group was screened using a semi-structured screening interview based upon neurological conditions, fMRI safety, and the Structured Clinical Interview for DSM-IV(SCID-I) non-patient edition (First et al, 1995; Landfield, 1987; Langenecker and Nielson, 2003). All control subjects were found to be free of any past or current psychiatric or neurologic disorder (self or first degree family members), including alcohol and substance abuse or dependence. They did not have any clinical manifestations of hypercortisolemia, though urinary or serum cortisol measurements were not collected.Exclusion criteria for all participants included use of antipsychotic (last six months), hypnotic (48 hours) or benzodiazepine (48 hours) drugs. The patient with longstanding seizure disorder was prescribed Dilantin. Results were similar with and without inclusion of this subject in the data analyses.

In the patients with CS, samples for plasma cortisol were collected every two hours for 24 hours for assessment of circadian rhythm (in Figure 1, for CS participants only due to funding limitations). Urine for free cortisol was also collected over a 24-hour period during an inpatient stay at the University of Michigan Clinical Research Unit, typically either the day prior to or after the fMRI study. Cortisol levels were measured using a Diagnostic Products Corporation (DPC) Coat-A-Count radioimmunoassay kit and plasma ACTH by the Nichols Allegro radioimmunometric assay. In some of the more recent patients, cortisol and ACTH were measured by automated methods that had a high degree of correlation with the other methods. Serum cortisol and plasma ACTH results are calculated as the mean of 12 values. Decrease in cortisol and ACTH from am peak (8, 10 and 12 measurements) to afternoon nadir (4, 6, and 8 pm measurements) was also calculated(Debono et al, 2009), weighing in the effect of the loss of circadian rhythm in patients with CS -(Peak-Nadir)/Peak (% decline in cortisol). A negative percentage would indicate a relatively normative circadian decline over this time period. Cortisol and ACTH percent change in peak-nadir measurements were highly correlated (r = .79, P< .05, see Table 2). Length of hypercortisolism was estimated in months by DES based upon prior procedures (Schteingart, 1989). These clinical endocrine values are also reported in Table 1 and correlations of endocrine, clinical, and performance variables are reported in Table 2.

Figure 1
Illustrates average cortisol levels across the measurement period (8 am to the following day at 6 am) in the patients with CS. Healthy control subjects did not have cortisol measurements for the study due to funding limitations. The cortisol levels were ...
Table 2
Correlations of Clinical Variables of Interest and with Facial Emotion Identification Performance.

CS is a disorder with a direct cause from GC, which has significant effects in CNS but also impact upon peripheral organs and functioning. As such, a number of covariates of interest are considered in the areas of interest to increase confidence in the direct effects of chronic GC exposure. In particular, diagnosis, treatment, and/or peripheral markers for depression/anxiety, hypertension, and hyperglycemia are evaluated in regions with between group differences to rule out these factors as secondarily causative of between group differences. In addition, medication effects are also evaluated in this light. Because of the relatively small sample size of CS patients who completed imaging (n=18), special care was taken to assess whether these secondary conditions/markers were the source of between group differences, and interpretations were adjusted accordingly.

Facial Emotion Perception Task (FEPT)

The FEPT was used to assess accuracy and speed of identification of facial expressions, with categorization of animals used as a control for visual processing ability and fine motor speed (Ekman and Friesen, 1976; Langenecker et al, 2005; Langenecker et al, 2007b; Rapport et al, 2002; Tottenham et al., 2002).Briefly, for this task participants were asked to categorize faces into one of four possible categories (happy, sad, fearful, and angry) and animals from each of four categories (dogs, cats, primates, and birds), described elsewhere (Langenecker et al, 2005; Langenecker et al, 2007b). The FEPT version used outside the scanner included the Ekman faces, and the in-scanner version used the MACBrain Foundation faces (Ekman et al, 1976; Langenecker et al, 2005; Langenecker et al, 2007b; Rapport et al, 2002; Tottenham et al., 2002).

Each event began with a briefly presented orienting cross (500 ms), followed by a brief presentation of the stimulus (300 ms), a visual mask (100 ms), and a response window (2600 ms). The outside-scanner version entailed one 7-minute run and included 12 animal trials and 54 face trials, with six neutral trials, used in prior studies of MDD and related disorders (Ekman et al, 1976; Langenecker et al, 2005; Langenecker et al, 2007b; Rapport et al, 2002; Tottenham et al., 2002). The in-scanner version entailed 3.5-minute runs and included 56 animals and 148 faces, with emotion type counterbalanced in presentation to the second order (e.g., Angry-Fearful, Angry-Happy sequences, etc. were equal in number and randomized in position within a run). Dependent variables were accuracy in categorization of emotional expressions, as well as average response time. Foci of activation in this study included fusiform gyrus, amygdala, hippocampus, dorsal and subgenual anterior cingulate gyrus, and bilateral ventro-lateral and dorso-lateral prefrontal cortex, consistent with those areas high in GC receptor concentrations (Diorio et al, 1993; Lopez et al, 1998; Patel et al, 2000; Swanson et al, 1983), and those regions reported in healthy control and psychiatric illnessstudies using protocols of this type.

Scanning Procedures

Participants completed the computer versionof the FEPT task before entering the fMRI scanner and completed the task while in the scanner. The fMRI scanning protocol with alternative tasks and populationsreported previously(Hsu et al, 2010; Langenecker et al, 2007a).

MRI Acquisition

Whole brain imaging was performed using a GE Sigma 3 T scanner (release VH3).fMRI series consisted of 30 contiguous oblique-axial sections acquired using a forward-reverse spiral sequence, which provides excellent fMRI sensitivity (Glover et al., 2004). The image matrix was 64 × 64 over a 24cm field of view for a 3.75 × 3.75 × 4mm voxel. The 30-slice volume was acquired serially at 1750ms temporal resolution (TR) for a total of 590 time points for FEPT. One hundred six high-resolution Fast SPGR IR axial anatomic images [TE = 3.4 ms; TR (repetition time) = 10.5 ms, 27degree flip angle, NEX (number of excitations) = 1, slice thickness = 1.5 mm, FOV (field of view) = 24 cm, matrix size = 256 × 256] were obtained for each participant for co-registration and normalization purposes.

MRI Processing

Processing of images was conducted using SPM2, including realignment, slice timing correction, co-registration, normalization to the MNI world space, and smoothing with a 5 FWHM filter. Contrast images were derived based upon the face processing minus animal processing blocks subtractions (FP – AP). These were computed by using the Blood Oxygenation Level Dependent (BOLD) signal for all face processing blocks and subtracting similar BOLD signal changes for animal processing blocks for each individual in a first level analysis. The SPM2 hemodynamic response function (hrf) model was used to model the BOLD response. Two group, random effects analyses were conducted using whole brain analyses from the individual group contrasts between the CS and control groups in SPM5.

Statistical Analyses

For behavioral data, repeated measures analyses of covariance for accuracy and response time were performed, with practice and in-scanner performance entered as within-subject variables, group entered as the between-subjects variable, and age and sex entered as covariates. For fMRI data, second level analyses were conducted with ANCOVAs within SPM5. The ANCOVA compared CS and control subjects using activation in the faces – animals contrast, with performance accuracy in classifying faces and sex as covariates. Statistical significance for between group comparisons was set at P< .003, with cluster minimum of 344 mm3. Based upon 1000 Monte Carlo simulations with AlphaSim inside the whole brain search region, a whole brain corrected alpha of .05 is achieved with this combined height by extent threshold strategy. Based upon apriori hypotheses, amygdala and hippocampus were used as regions of interest, with uncorrected P< .05 and extent threshold of 24 mm3. Posthoc analyses used extracted data from regions identified in whole-brain corrected,between group differences to evaluate the impact of disease and performance parameters.


Decreased Accuracy in Classification of Emotions in Faces for CSCompared to Controls

The healthy control group outperformed the CS group in accuracy of classification of emotion in human faces in a repeated measures ANCOVA (with age and sex as covariates) including both practice and in-scanner performance (F(1,35) = 7.67, P< .05). There was no difference between performance inside the scanner and practice (F(1,35) = 0.79, P> .05) and the interaction between setting (practice versus in-scanner) and group was not significant (F(1,35) = 1.77, P> .05).

In a similar repeated measures ANCOVA for response time, there was no main effect of group (F(1,35) = 2.51, P> .05). There was a main effect of setting for response time, with slower response times inside the scanner (F(1,35) = 11.91, P< .05). The interaction between setting and group was significant (F(1,35) = 5.59, P< .05). The control group responded faster than the CS group when initially classifying faces in practice, but not when performing the task inside the scanner. For classification of animals (the control condition), there was no difference between groups in accuracy or response time (P values > .05).

Bilateral Ventral Frontal Activation for Emotion Identification for Each Group Separately, with More Extensive Activation for CS

Activation for healthy control and CS groups separately is illustrated in Figure 2. Both groups exhibited bilateral ventrolateral prefrontal cortex and anterior insula activation. In addition, the CS group foci of activation included more extensive regions than those in healthy control foci, to include contiguous dorsolateral prefrontal cortex, plus medial prefrontal cortex including rostral and dorsal anterior cingulate, globus pallidus, hippocampus, thalamus and amygdala (left only). The control group exhibited activation in superior temporal gyrus, which was not present in the CS group.

Figure 2
Significant activation, after whole-brain correction using combined height and extent threshold with AlphaSim, for healthy control (yellow) and CS (red) groups separately. X (left to right) coordinates (Talairach) are listed for sagittal planes.

Hyperactivation in the CS Group compared to Control Group in BOLD Activation for Emotion Classification for CS

There were seven foci with significantly greater activity in the CS group compared to the healthy control group as initially hypothesized, in primarily medial and left frontal regions. (Table 3, Figure 3). In addition to theright rostral anterior cingulate, the left lateralized foci were middle frontal gyrus, dorsal anterior cingulate, caudate body, lateral posterior thalamus, substantia nigra, and superior parietal lobule. The control group exhibited greater activation relative to the CS group in left anterior superior/middle temporal gyrus (also Table 3, Figure 3). Activation for the Fear-Neutral contrast, which might be expected to be most closely related to the effects of CS, is reported in Table 4 for comparative purposes. The results are largely similar to the faces-animals between group contrast, the focus of the paper.

Figure 3
Differences in emotion processing (FP – AP) between the CS and the healthy control group. Blue represents greater activation in CS relative to healthy controls. Healthy control activation that is greater than the CS group is illustrated in green. ...
Table 3
Foci of Greater FP-AP Activation in CS Participants Compared to Control Participants in Identification of Facial Emotional Expressions
Table 4
Greater Activation in CS compared to Healthy Control Subjects in the Fear-Neutral Contrast.

In addition to the whole brain analyses described above, we also investigated predefined regions of interest in the amygdala and hippocampus. The CS group exhibited greater activation than the HC group in left anterior hippocampus (−27, −19, −19, Z = 1.83, P< .05, mm3 = 48). The healthy control group exhibited greater activation than the CS group in right middle hippocampus (26, −25, −10, Z = 1.78, P< .05, mm3 = 80).

Posthoc Analyses Investigating the Whole Brain Differences between Healthy Control and CS Groups

Exploratory, posthoc correlations were performed with activation in the eight regions with between group differences in whole brain comparisons (from Table 3). In the CS group, we explored the role of estimated illness duration, degree of HPA dysfunction as measured by current mean elevation in hormone concentrations of ACTH and cortisol, and percent change in these measures from peak to nadir. We then evaluated the relationship of activation upon measures of performance accuracy in the CS group. Due to the relatively small sample size and total number of correlations, these are considered exploratory for hypothesis generation.

Left Dorsal Cingulate Hyperactivation in CS Correlates with Disrupted Circadian Rhythm

The results of the hormone analyses revealed that activation in left dorsal anterior cingulate (DAC) was correlated with percent decline in ACTH from peak to nadir (rho = .51, P< .05) and marginally so for percent decline in cortisol from peak to nadir (rho = .49, P = .055), with both relationships illustrated in Figure 4a. Aflat or increasing pattern of ACTH/cortisol throughout the day, which is the greatest deviation from healthy hormone levels, was associated with the greatest activation in left DAC. Similarly, two clusters, left superior temporal gyrus (rho = .45, P = .08) and left superior parietal lobule (rho = .48, P = .06), showed marginally significant positive correlations between ACTH percent decline and activation. Percent decline in ACTH and cortisol Peak-Nadir was not associated with accuracy in emotion classification (rho = .17, P> .05, rho = .14, P> .05).

Figure 4a and 4bFigure 4a and 4b
4a illustrates activation within the left dorsal anterior cingulate as it relates to change in cortisol (white) and ACTH (red) from peak to nadir. The value is inverted, so that a negative percent change reflects a decrease that would be closer to a normal ...

Left Middle Frontal and Thalamic Hyperactivation in CS Correlates with Accuracy in Facial Emotion Identification

In contrast, accuracy in classification of emotions was associated with performance in other regions from amongst the eight regions of whole brain differences between groups. For CS, activation in two of the eight clusters, left lateral posterior/pulvinar nuclei of the thalamus (rho = .56, P< .05) and left middle frontal gyrus (rho = .50, P< .05), was positively associated with accuracy in emotion identification, with the latter relationship illustrated in Figure 4b. A marginally significant correlation was also observed in left superior parietal lobule (rho = .43, P = .08). Those individuals with CS who exhibited greater activation compared to the healthy control subjects in these three regions were able to attain good performance on the task.

Hyperactive Regions in CS are not Explained by Comorbid Conditions Secondary to Hypercortisolemia orby Medication Effects

We performed additional posthoc correlations on these eight regions from whole brain differences between groups to rule out the impact of comorbid conditions that occur secondarily to hypercortisolemia (hypertension, type II diabetes, depression). None of the seven CS > control or the one control > CS foci differed in the CS groups based upon the presence or absence of depression (p values > .19), type II diabetes (P values > .05), or presence of medications that might effect BOLD fMRI or affect processing (P values > .05), primarily focusing on antihypertensives and antidepressants). There were no differences between CS groups with and without hypertension in the seven clusters that were greater in CS relative to the control group. The CS group with hypertension did have lower activation in the left superior/middle temporal cluster that was observed in the control minus CS comparison (t(17) =2.69 P< .05). In essence, comorbid conditions and medications did not play a significant role in the areas of hyperactivity in CS relative to healthy control subjects.


The present results extend our previous observations linking a dysregulated HPA axis with alterations in central nervous system structure and cognitive performance, especially memory (Hook et al, 2007; Starkman et al, 1992; Starkman et al, 2003, 2007; Starkman et al, 1981, 1986b). The present study is the first report of alterations in emotion perception and processing as measured by fMRI in adult patients with untreated CS. Chronic hypercortisolemia affects the functioning of medial temporal and frontal circuitry, regions where MR and GR receptors are most heavily represented (Wellman, 2001). Disruption of these regions, which is critical for efficient and accurate emotional processing, is reflected in the poorer performance within the CS group. As such, the key findings of the present study are likely to reflect disruption of critical foci within circuitry for emotion processing, and in those brains where successful adaptation has occurred, compensatory recruitment. The results also shed light on the importance of understanding the behavioral and biological correlates of differences in activation between CS and healthy controls, considerations that are also relevant for study of other conditions like MDD. Hyperactivation for CS in some regions (i.e., left dorsal anterior cingulate) was reflective of the severity of the disease process, vis-à-vis the complete disruption in a daily circadian pattern of ACTH and cortisol. Yet hyperactivation in other regions (i.e., left lateral posterior/pulvinar nuclei of the thalamus and left middle frontal gyrus) for CS was indicative of compensation by recruitment; additional brain regions were recruited to attain a level of performance equivalent to healthy controls.

The main findings from the present study were of hyperactivation in the CS compared to the healthy control group in medial frontal and left lateralized regions, and also included subcortical regions of interest. The specific areas that demonstrated effects of chronic hypercortisolism, irrespective of secondary comorbidities or other symptoms, were consistent with areas affected in acute stress paradigms in humans, including dorsal anterior cingulate and medial prefrontal cortex(Pruessner et al, 2008).When exposed to emotionally evocative stimuli, groups with psychiatric illness have also demonstrated increased activation relative to controls in these same regions (Chen et al, 2007; Fairhall and Ishai, 2007; Grimm et al, 2008; Hamilton et al, 2008). Activation in the right rostral anterior cingulate cluster was not related to performance accuracy or to current or chronic measures of disease impact or burden. It has been reported that levels of resting cortisol and early childhood trauma are related to cingulate volume in a mixed group of controls and depressed subjects, supporting the sensitivity of this region to elevated hormones secondary to HPA axis dysfunction (Treadway et al, 2009).

The hyperactive regions most pertinent to the task are located where MR/GR receptors are most heavily represented, within rostral and dorsal anterior cingulate and superior temporal gyrus (Lopez et al, 1998; Patel et al, 2000; Wellman, 2001). It is also important to recognize, though, that with chronic GC administration, effects may be observed outside of regions with heavy receptor representation, including cascading effects of dendritic shrinkage and adjustment of these and related neuronal circuits. For example, animal and human studies of GC administration or stress/stimulation demonstrate a greater impact for chronic exposure in sensitive regions, including hippocampus, amygdala, caudate, and prefrontal cortex (Kole et al, 2004; Leverenz et al, 1999; Ohl et al, 2000; Scheel et al, 2009; Starkman et al, 1992; Starkman et al, 2007; van der Beek et al, 2004; Wellman, 2001). There may also be restructuring or plasticity in the functional organization of these and related circuits to adjust to the changed endocrine milieu present in chronic hypercortisolemia or dysregulated cortisol, though this has not yet been considered. There is substantial work on chronic GC administration in animals showing changes in dendritic structuring of hippocampus and amygdala, yet little is known about how these local changes in very complex foci would impact structures within the same and related circuits (Magarinos et al, 1995; Roozendaal et al, 2009). Preplanned region of interest analyses showed that even within these small comparison groups there was hypoactivation in right posterior hippocampus and hyperactivation in right anterior hippocampus in the CS group. Of course, in vivo measurements in humans rarely allow us to answer questions of mechanism or purpose of these activation changes, but correlation can be used to begin to dissect the processes that might be supporting or underlying the changes in question.

The relationship between a decrease or increase in ACTH from peak to nadir was reflective of normal, flattened, and inverted circadian rhythmicity in CS. There is not yet a clear understanding of how these dorsal and rostral cingulate regions of hyperactivation in CS might assist in regulation of (Treadway mood or emotion in chronic stress, although some studies have begun to investigate these links et al, 2009; Wellman, 2001). For example, is it a phasic response that is modulated acutely? It may be that these regions are mediating the reactivity to the emotional stimuli in light of a cognitive/emotional identification objective. Or does chronic hypercortisolemia increase the amplitude of response to emotional stimuli in these regions? In addition, whereas chronic GC administration occurs in some medical populations, the long term cognitive and affective consequences are still poorly understood.

The decreased activation in left anterior superior temporal gyrus in the CS group relative to the control group is an exciting new lead. This region is important in emotion processing (Fusar-Poli et al., 2009) and also has high levels of MR and GR receptors (Diorio et al, 1993; Lopez et al, 1998; Patel et al, 2000). It may be a particularly vulnerable region to chronic stress and/or hypercortisolemia, and it deserves further study.

There were two areas of hyperactivation in CS that were associated with preserved capacity for emotion classification accuracy. The left thalamus and middle frontal gyrus have well described relationships with emotion processing and regulation (Fusar-Poli et al, 2006; Phan et al, 2002). Increased activation that is associated with preserved performance on a given task is often interpreted in one of two ways. First, it can be considered additional, or compensatory activation. This interpretation is based upon the idea that for a weaker circuit, increased resources are needed to attain similar levels of performance (Deckersbach et al, 2006; Langenecker et al, 2003; Reuter-Lorenz et al, 1999; Woodard et al, 1998). A second interpretation is that of reorganization, assuming a lack of activation in important regions for task performance and increased activation in areas that are of distinct, but similar or perhaps supportive function (Bontempi et al, 1999; Madden et al, 1997; Stern et al, 2005). Unfortunately, as in this case, imaging studies are often underpowered for the task of addressing more nuanced interpretations such as reorganization, and results of this type are often viewed as compensatory.

There are a number of caveats to consider in interpreting the results. First, with regard to subjects, the CS sample is modest in number, although this is a reasonable sample for such a rare condition and for an fMRI investigation. In addition, in this recent sample of consecutively recruited CS subjects, cortisol levels were not as highly elevated as in our previous samples, and the subjects were relatively younger. Cortisol dysregulation has more deleterious effects with increasing age (Hook et al, 2007), rendering our study more conservatively biased. In addition, many of the CS subjects were taking medications, particularly including those for hypertension and depression. Post-hoc analyses indicated that the presence or absence of comorbid conditions did not influence the results, with the exception of hypertension for the left superior temporal gyrus. Those with hypertension were more likely to exhibit decreased activation in this region compared to those without hypertension and compared to healthy controls. Also, in previous work from our group examining cognitive decrements in 48 untreated CS subjects, when the potential confounding effect of medications was examined, there were no significant differences either between patients taking no medication versus those taking any medications, or among patients taking no drugs, antihypertensives only, antihypertensives plus other medications, and other medications only (Starkman et al, 2001). Finally, the uncorrected threshold within the amygdala/hippocampal ROI was also provided in the interests of comparison with previous ROI studies of emotion processing in mood disorders in these regions. It is less likely that these amygdala/hippocampal effects would be replicable.

To our knowledge, the present study is the first in adult humans to provide evidence for the strong relationship between emotion processing difficulties and hyperactivity in frontal, and subcortical regions during hypercortisolemia, irrespective of comorbid conditions and symptoms. The present results add support to our overarching hypothesis that there is a direct impact of dysregulated HPA axis products upon the CNS. In this case, continuous exposure to elevated cortisol and related HPA axis products can result in altered processing and regulation of emotion. The present results showing relationships among chronically elevated cortisol, disrupted brain activation patterns in key areas, and decrements in facial emotion processing can be tested further in subjects with mood disorders and those at risk for developing mood disorders.


We demonstrate the impact of chronic hypercortisolemia upon affective processing using functional MRI.

The study includes a Cushings Disorder group, where the disease results in excessive release of high levels of cortisol.

The Cushings Disorder group shows excessive activation in frontal and subcortical regions, primarily on the left.


This project was supported by a General Clinical Research Center pilot grant to MNS and SAL (for some control and all Cushing’s fMRI scans, from # MO1 RR00042), KL2 Career Development Award (RR024987, SAL), K23 Award (MH074459, SAL), NIMH grant (# MH 43372, MNS), a Rachel Upjohn Clinical Scholars Award for screening of control subjects (SAL), and some pilot (control) fMRI scans from the University of Michigan functional MRI lab (SAL,SLW). Allison M. Kade, Kathleen E. Hazlett, Michael L. Brinkman, Benjamin D. Long, Lawrence S. Own, Thomas M. Hooven, and Karandeep D. Singh, are thanked for their assistance in data collection and analysis for this work. We gratefully acknowledge James L. Abelson, M.D., Ph.D. for his constructive comments in the integration and presentation of data. The staff and faculty at the University of Michigan fMRI lab are gratefully acknowledged for their assistance and support in completing this work.


Disclosure Statement: The authors have nothing to disclose pertinent to the investigation conducted here.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.


  • Abercrombie HC, Jahn AL, Davidson RJ, Kern S, Kirschbaum C, Halverson J. Cortisol’s effects on hippocampal activation in depressed patients are related to alterations in memory formation. J Psychiatry Res. 2011;45(1):15–23. [PMC free article] [PubMed]
  • Akil H, Haskett RF, Young EA, Grunhaus L, Kotun J, Weinberg V, Greden J, Watson SJ. Multiple HPA profiles in endogenous depression: Effect of age and sex on cortisol and beta-endorphin. Biol Psychiatry. 1993;33:73–85. [PubMed]
  • Axelson DA, Doraiswamy PM, McDonald WM, Boyko OB, Tupler LA, Patterson LJ. Hypercortisolemia and hippocampal changes in depression. Psychiatry Res. 1993;47:163–173. [PubMed]
  • Bontempi B, Laurent-Demir C, Destratde C, Jaffard R. Time-dependent reorganization of brain circuitry underlying long-term memory storage. Nature. 1999;400:671–675. [PubMed]
  • Brown ES, Vera E, Frol AB, Woolston DJ, Johnson B. Effects of chronic prednisone therapy on mood and memory. JAffectDisord. 2007;99(1-3):279–283. [PMC free article] [PubMed]
  • Chen CH, Ridler K, Suckling J, Williams S, Fu CH, Merlo-Pich E, Bullmore E. Brain imaging correlates of depressive symptom severity and predictors of symptom improvement after antidepressant treatment. Biol Psychiatry. 2007 Sep 1;62(5):407–14. 2007. [PubMed]
  • Debono M, Ghobadi C, Rostami-Hodjegan A, Huatan H, Campbell MJ, Newell-Price J, Darzy K, Merke DP, Arlt W, Ross RJ. Modified-Release Hydrocortisone to Provide Circadian Cortisol Profiles. Clin Endocrin & Metab. 2009;94(5):1548–1554. [PubMed]
  • Deckersbach T, Dougherty DD, Savage C, McMurrich S, Fischman AJ, Nierenberg A, Sachs G, Rauch SL. Impaired recruitment of the dorsolateral prefrontal cortex and hippocampus during encoding in bipolar disorder. BiolPsychiatry. 2006;59(2):138–146. [PubMed]
  • Diorio D, Viau V, Meaney MJ. The role of the medial prefrontal cortex (cingulate gyrus) in the regulation of hypothalamic-pituitary-adrenal responses to stress. JNeurosci. 1993;13(9):3839–3847. [PubMed]
  • Drevets WC, Price J, Bardgett ME, Reich T, Todd R, Raichle M. Glucose metabolism in the amygdala in depression: relationship to diagnostic subtype and plasma cortisol levels. Pharm, Biochem Behav. 2002;71:431–447. [PubMed]
  • Ekman P, Friesen W. Pictures of Facial Affect. Consulting Psychologists Press; Palo Alto, CA: 1976.
  • Erickson K, Drevets WC, Schulkin J. Glucocorticoid regulation of diverse cognitive functions in normal and pathological emotional states. Neurosci Biobehav Rev. 2003;27(3):233–246. [PubMed]
  • Fairhall SL, Ishai A. Effective connectivity within the distributed cortical network for face perception. CerebCortex. 2007;17(10):2400–2406. [PubMed]
  • First MB, Spitzer RL, Gibbon M. Structured Clinical Interview for DSM-IV Axis 1 Disorder. Biometrics Research Department, New York State Psychiatric Institute; New York: 1995.
  • Forget H, Lacroix A, Somma M, Cohen H. Cognitive decline in patient’s with Cushing’s syndrome. J Int Neuropsychol Soc. 2000;6:20–29. [PubMed]
  • Fusar-Poli P, Placentino A, Carletti F, Landi P, Allen P, Surguladze S, Benedetti F, Abbamonte M, Gasparotti R, Barale F, Perez J, McGuire P, Politi P. Functional atlas of emotional faces processing: a voxel-based meta-analysis of 105 functional magnetic resonance imaging studies. J Psychiatry Neurosci. 2009;34:418–432. [PMC free article] [PubMed]
  • Glover GH, Thomason ME. Improved combination of spiral-in/out images for BOLD fMRI. Magnetic Resonance in Medicine. 2004;51(4):863–868. [PubMed]
  • Grimm S, Beck J, Schuepbach D, Hell D, Boesiger P, Bermpohl F, Niehaus L, Boeker H, Northoff G. Imbalance between left and right dorsolateral prefrontal cortex in major depression is linked to negative emotional judgment: an fMRI study in severe major depressive disorder. BiolPsychiatry. 2008;63(4):369–376. [PubMed]
  • Hamilton JP, Siemer M, Gotlib IH. Amygdala volume in major depressive disorder: a meta-analysis of magnetic resonance imaging studies. MolPsychiatry. 2008;13(11):993–1000. [PMC free article] [PubMed]
  • Hook JN, Giordani B, Schteingart DE, Guire K, Giles J, Ryan K, Gebarski SS, Langenecker SA, Starkman MN. Patterns of cognitive change over time and relationship to age following successful treatment of Cushing’s disease. J Int Neuropsychol Soc. 2007;13(1):21–29. [PubMed]
  • Hsu DT, Langenecker SA, Kennedy SE, Zubieta J-K, Heitzeg MM. fMRI BOLD responses to negative stimuli in the prefrontal cortex are dependent on levels of recent negative life stress in major depressive disorder. Psychiatry Res: Neuroimag. 2010;183:7. [PMC free article] [PubMed]
  • Khiat A, Bard C, Lacroix A, Rousseau J, Boulanger Y. Brain metabolic alterations in Cushing’s syndrome as monitored by proton magnetic resonance spectroscopy. NMR Biomed. 1999;12:357–363. [PubMed]
  • Kole MH, Czeh B, Fuchs E. Homeostatic maintenance in excitability of tree shrew hippocampal CA3 pyramidal neurons after chronic stress. Hippocampus. 2004;14(6):742–751. [PubMed]
  • Landfield P. Modulation of brain aging correlates by long-term alterations of adrenal steroids and neurally-active peptides. Prog Brain Res. 1987;72:279–300. [PubMed]
  • Langenecker SA, Bieliauskas LA, Rapport LJ, Zubieta J-K, Wilde EA, Berent S. Face emotion perception and executive functioning deficits in depression. JClin Exp Neuropsycho. 2005;l27(3):320–333. [PubMed]
  • Langenecker SA, Kennedy SE, Guidotti LM, Briceno EM, Own L, Hooven T, Young EA, Akil H, Noll DC, Zubieta JK. Frontal and limbic activation during inhibitory control predicts treatment response in major depressive disorder. Biol Psychiatry. 2007a;62:1272–1280. [PMC free article] [PubMed]
  • Langenecker SA, Caveney AF, Giordani B, Young EA, Nielson KA, Rapport LJ, Biellauskas LA, Mordhorst MJ, Marcus S, Yodkovik N, Kerber K, Berent S, Zubieta JK. The sensitivity and psychometric properties of a brief computer-based cognitive screening battery in a depression clinic. Psychiatry Res. 2007b;152(2-3):143–154. [PubMed]
  • Langenecker SA, Nielson KA. Frontal recruitment during response inhibition in older adults replicated with fMRI. NeuroImage. 2003;20(2):1384–1392. [PubMed]
  • Leverenz JB, Wilkinson CW, Wamble M, Corbin S, Grabber JE, Raskind MA, Peskind ER. Effect of chronic high-dose exogenous cortisol on hippocampal neuronal number in aged nonhuman primates. JNeurosci. 1999;19(6):2356–2361. [PubMed]
  • Lopez JF, Chalmers DT, Little KY, Watson SJ. Regulation of serotonin 1A, glucocorticoid, and mineralocorticoid receptor in rat and human hippocampus: implications for the neurobiology of depression. Biol Psychiatry. 1998;43:547–573. [PubMed]
  • Lupien SJ, DeLeon M, DeSanti S, Convit A, Tarshish C, Nair NPV, McEwen BS, Hauger RL, Meaney MJ. Longitudinal increase in cortisol during human aging predicts hippocampal atrophy and memory deficits. Nat Neurosci. 1998;1:69–73. [PubMed]
  • Madden DJ, Turkington TG, Provenzale JM, Hawk TC, Hoffman JM, Coleman RE. Selective and divided visual attention: age-related changes in regional cerebral blood flow measured by M2150 PET. Hum Brain Mapp. 1997;5:389–409. [PubMed]
  • Magarinos AM, McEwen BS. Stress-induced atrophy of apical dendrites of hippocampal CA3c neurons: comparisons of stressors. Neurosci. 1995;69(1):83–88. [PubMed]
  • McEwen BS. Possible mechanisms for atrophy of the human hippocampus. Mol Psychiatry. 1997;2:255–262. [PubMed]
  • Mitra R, Sapolsky RM. Acute corticosterone treatment is sufficient to induce anxiety and amygdaloid dendritic hypertrophy. ProcNatlAcadSciUSA. 2008;105(14):5573–5578. [PubMed]
  • Mitra R, Sundlass K, Parker KJ, Schatzberg AF, Lyons DM. Social stress-related behavior affects hippocampal cell proliferation in mice. Physiol Behav. 2006;89(2):123–127. [PubMed]
  • Ohl F, Michaelis T, Vollmann-Honsdorf GK, Kirschbaum C, Fuchs E. Effect of chronic psychosocial stress and long-term cortisol treatment on hippocampus-mediated memory and hippocampal volume: a pilot-study in tree shrews. Psychoneuroend. 2000;25(4):357–363. [PubMed]
  • Patel PD, Lopez JF, Lyons DM, Burke S, Wallace M, Schatzberg AF. Glucocorticoid and mineralocorticoid receptor mRNA expression in squirrel monkey brain. J PsychiatrRes. 2000;34:383–392. [PubMed]
  • Phan KL, Wager T, Taylor SF, Liberzon I. Functional neuroanatomy of emotion: a meta-analysis of emotion activation studies in PET and fMRI. NeuroImage. 2002;16(2):331–348. [PubMed]
  • Pruessner JC, Declovic K, Khalili-Mahani N, Engert V, Pruessner M, Buss C, Renwick R, Dagher A, Meaney MJ, Lupien S. Deactivation of the limbic system during acute psychosocial stress: Evidence from positron emission tomography and functional magnetic resonance Imaging studies. Biol Psychiatry. 2008;63:234–240. [PubMed]
  • Rapport LJ, Friedman S, Tzelepis A, VanVoorhis A. Experienced emotion and effect recognition in adult attention-deficit hyperactivity disorder. Neuropsycho. 2002;l16:102–110. [PubMed]
  • Reuter-Lorenz PA, Stanczak L, Miller AC. Neural recruitment and cognitive aging: Two hemispheres are better than one, especially as you age. Psychol Sci. 1999;10(6):494–500.
  • Roozendaal B, McEwen BS, Chattarji S. Stress, memory and the amygdala. Nat Rev Neurosci. 2009;10(6):423. (411) [PubMed]
  • Sapolsky RM. Glucocorticoids and hippocampal atrophy in neuropsychiatric disorders. Arch Gen Psychiatry. 2000;57(10):925–935. [PubMed]
  • Scheel M, Ströhle A, Bruhn H. Effects of short-term stress-like cortisol on cerebral metabolism: A proton magnetic resonance spectroscopy study at 3.0†T. J Psychiatric Res. 2009;44(8):521–526. [PubMed]
  • Schteingart DE. Cushing’s syndrome. Endocrin Metab Clinics of North Amer. 1989;18:311–338. [PubMed]
  • Seeman TE, McEwen BS, Singer BH, Albert MS, Rowe JW. Increase in urinary cortisol excretion and memory declines: MacArthur studies of successful aging. J Clin Endocrin Metab. 1997;82(8):2458–2465. [PubMed]
  • Shipley JE, Schteingart DE, Tandon R, Starkman MN. Sleep architecture and sleep apnea in patients with Cushing’s disease. Sleep. 1992;15(6):514–518. [PubMed]
  • Starkman MN, Gebarski SS, Berent S, Schteingart DE. Hippocampal formation volume, memory dysfunction, and cortisol levels in patients with Cushing’s syndrome. BiolPsychiatry. 1992;32(9):756–765. [PubMed]
  • Starkman MN, Giordani B, Berent S, Schork MA, Schteingart DE. Elevated cortisol levels in Cushing’s disease are associated with cognitive decrements. PsychosomMed. 2001;63(6):985–993. [PubMed]
  • Starkman MN, Giordani B, Gebarski SS, Berent S, Schork MA, Schteingart DE. Decrease in cortisol reverses human hippocampal atrophy following treatment of Cushing’s disease. BiolPsychiatry. 1999;46(12):1595–1602. [PubMed]
  • Starkman MN, Giordani B, Gebarski SS, Schteingart DE. Improvement in learning associated with increase in hippocampal formation volume. BiolPsychiatry. 2003;53(3):233–238. [PubMed]
  • Starkman MN, Giordani B, Gebarski SS, Schteingart DE. Improvement in mood and ideation associated with increase in right caudate volume. JAffectDisord. 2007;101(1-3):139–147. [PubMed]
  • Starkman MN, Schteingart DE, Schork MA. Depressed mood and other psychiatric manifestations of Cushing’s syndrome: relationship to hormone levels. PsychosomMed. 1981;43(1):3–18. [PubMed]
  • Starkman MN, Schteingart DE, Schork MA. Correlation of bedside cognitive and neuropsychological tests in patients with Cushing’s syndrome. Psychosom. 1986a;27(7):508–511. [PubMed]
  • Starkman MN, Schteingart DE, Schork MA. Cushing’s syndrome after treatment: changes in cortisol and ACTH levels, and amelioration of the depressive syndrome. Psychiatry Res. 1986b;19(3):177–188. [PubMed]
  • Stern Y, Habeck C, Moeller J, Scarmeas N, Anderson KE, Hilton HJ, Flynn J, Sackeim H, van, Heertum R. Brain networks associated with cognitive reserve in healthy young and old adults. CerebCortex. 2005;15(4):394–402. [PMC free article] [PubMed]
  • Swanson LW, Sawchenko PE, Rivier J, Vale WW. Organization of ovine corticotropin-releasing factor immunoreactive cells and fibers in the rat brain: an immunohistochemical study. Neuroendocrinology. 1983;36(3):165–186. [PubMed]
  • Tessner KD, Walker EF, Dhruv SH, Hochman K, Harnann S. The relation of cortisol levels with hippocampus volumes under baseline and challenge conditions. Brain Res. 2007;1179:70–78. [PubMed]
  • Tottenham N, Borscheid A, Ellertsen K, Marcus DJ, Nelson CA, editors. Categorization of facial expressions in children and adults: Establishing a larger stimulus set. Poster presented at the annual meeting; San Francisco, CA. 2002.
  • Treadway MT, Grant MM, Ding Z, Hollon SD, Gore JC, Shelton RC. Early Adverse Events, HPA Activity and Rostral AnteriorCingulate Volume in MDD. PLoS ONE. 2009;4(3):e4887. [PMC free article] [PubMed]
  • Urry HL, van Reekum CM, Johnstone T, Kalin NH, Thurow ME, Schaefer HS, Jackson CA, Frye CJ, Greischar LL, Alexander AL, Davidson RJ. Amygdala and ventromedial prefrontal cortex are inversely coupled during regulation of negative affect and predict the diurnal pattern of cortisol secretion among older adults. J Neurosci. 2006;26(16):4415–4425. [PubMed]
  • van der Beek EM, Wiegant VM, Schouten WG, van Eerdenburg FJ, Loijens LW, van der Plas C, Benning MA, de, Vries H, de Kloet ER, Lucassen PJ. Neuronal number, volume, and apoptosis of the left dentate gyrus of chronically stressed pigs correlate negatively with basal saliva cortisol levels. Hippocampus. 2004;14(6):688–700. [PubMed]
  • van Stegeren AH, Wolf OT, Everaerd W, Scheltens P, Barkhof F, Rombouts SARB. Endogenous cortisol level interacts with noradrenergic activation in the human amygdala. Neurobiol Learn Mem. 2007;87(1):57–66. [PubMed]
  • Vyas A, Bernal S, Chattarji S. Effects of chronic stress on dendritic arborization in the central and extended amygdala. Brain Res. 2003;965:290–294. [PubMed]
  • Wellman CL. Dendritic reorganization in pyramidal neurons in medial prefrontal cortex after chronic corticosterone administration. JNeurobiol. 2001;49(3):245–253. [PubMed]
  • Woodard JL, Grafton ST, Votaw JR, Green RC, Dobraski ME, Hoffman JM. Compensatory recruitment of neural resources during overt rehearsal of word lists in Alzheimer’s disease. Neuropsychol. 1998;12(4):491–504. [PubMed]
  • Young EA, Altemus M, Lopez JF, Kocsis JH, Schatzberg AF, DeBattista C, Zubieta J-K. HPA axis activation in major depression and response to fluoxetine: a pilot study. Psychoneuroendocrin. 2004;29(9):1198–1204. [PubMed]