Skip to main content
NCBI home page
Social Cognitive and Affective Neuroscience logoLink to Social Cognitive and Affective Neuroscience
. 2016 Mar 24;11(6):991–1001. doi: 10.1093/scan/nsw031

Resting-state functional connectivity between amygdala and the ventromedial prefrontal cortex following fear reminder predicts fear extinction

Pan Feng 1, Yong Zheng 1,2, Tingyong Feng 1,2,✉
PMCID: PMC4884324  PMID: 27013104

Abstract

Investigations of fear conditioning have elucidated the neural mechanisms of fear acquisition, consolidation and extinction, but it is not clear how the neural activation following fear reminder influence the following extinction. To address this question, we measured human brain activity following fear reminder using resting-state functional magnetic resonance imaging, and investigated whether the extinction effect can be predicted by resting-state functional connectivity (RSFC). Behaviorally, we found no significant differences of fear ratings between the reminder group and the no reminder group at the fear acquisition and extinction stages, but spontaneous recovery during re-extinction stage appeared only in the no reminder group. Imaging data showed that functional connectivity between ventromedial prefrontal cortex (vmPFC) and amygdala in the reminder group was greater than that in the no reminder group after fear memory reactivation. More importantly, the functional connectivity between amygdala and vmPFC of the reminder group after fear memory reactivation was positively correlated with extinction effect. These results suggest RSFC between amygdala and the vmPFC following fear reminder can predict fear extinction, which provide important insight into the neural mechanisms of fear memory after fear memory reactivation.

Keywords: resting-state fMRI, fear reactivation, functional connectivity, amygdala, vmPFC

Introduction

Fear is biologically adaptive responses to environmental threat, and fear learning serves a key role in adaptive function. However, fear learning can be maladaptive at some times, resulting in excessive fear, anxiety and post-traumatic stress disorder (PTSD) (Schiller et al., 2009). Recent research on changing fears [weaken aversive conditioned stimulus (CS)–unconditioned stimulus (US) associations, or dampen traumatic memories] has examined targeting reconsolidation (Monfils et al., 2009; Schiller et al., 2009). In the process of reconsolidation, stored information is rendered labile after being retrieved and requires new protein synthesis to persist further. During this labile state, old fear memories can be updated with non-fearful information provided during the reconsolidation window (Alberini, 2005; Hupbach et al., 2007).

With regard to the behavioral research of fear reconsolidation, a lot of recent researches involving animals and humans demonstrated that the retrieval extinction conducted during the reconsolidation window could be the best way to blockade the spontaneous recovery or the reinstatement of fear responses, and to prevent drug craving and relapse (Monfils et al., 2009; Quirk and Milad, 2010; Schiller et al., 2009; Xue et al., 2012). These results suggest that the fear memory reminder and the reconsolidation window can be two indispensable factors to fear extinction. Especially, studies of Pavlovian fear conditioning in rodents suggest that the amygdala and the ventromedial prefrontal cortex (vmPFC) also contribute to the reconsolidation of emotional memory traces following their retrieval (Nader et al., 2000; Akirav and Maroun, 2006). Furthermore, Agren et al. (2012) found that extinction training initiated during reconsolidation abolished fear expression by erasing a memory trace in the amygdala. Moreover, the amygdala memory trace activity is functionally coupled to the fear network including insula, hippocampus, and the midline anterior cingulate cortex after normal memory reconsolidation (standard extinction learning) but not after disrupted reconsolidation. Importantly, standard extinction learning (repeated presentations of a CS without the aversive outcome) do not significantly alter the fear memory itself, but rather regulate its expression via the PFC’s inhibition of the amygdala (Phelps et al., 2004; Sotres-Bayon et al., 2006; Milad et al., 2007; Quirk and Mueller, 2007). However, Schiller et al. (2013) found that extinction training during fear memory reconsolidation window prevents the return of the fear and diminishes the involvement of the vmPFC. Moreover, the vmPFC showed enhanced functional connectivity with the amygdala only during standard extinction learning, but not the extinction learning during reconsolidation window. However, neural state of human after fear memory reactivation has not yet been well understood. Especially, it is not clear how the neural state after fear memory reactivation influence the following extinction learning.

Resting-state functional connectivity (RSFC) is a highly effective and efficient method for mapping complex neural circuits that is thought to reflect the underlying neuroanatomy (Andrews-Hanna et al., 2007; Vincent et al., 2007; Hagmann et al., 2008; Greicius et al., 2009). This study used the similar methods to investigate functional connectivity (the reminder group vs the no reminder group) after fear memory reactivation. We also attempted to examine whether the extinction effect could be predicted by RSFC following the fear memory reminder.

Based on the above mentioned researches, we expected to see differences in interregional RSFC between the reminder group and the no reminder group after fear memory reactivation (on the second day), and a close association between the RSFC after memory reactivation and the extinction effect. Specifically, we aimed to find out whether individual differences in amygdala-vmPFC functional connectivity in reminder group after fear memory reactivation (on the second day) could predict individuals’ extinction effect.

Materials and methods

Participants

A total of 60 right-handed college students were recruited for the study, and they were paid for their participation. The participants were randomly assigned in to three groups: the reminder group, the no reminder group and the control group (see below). The reminder group consisted of 20 college students (Mage = 21.60, SD = 1.57 years, 10 females), whereas an additional group of 20 college students (Mage = 22.05, SD = 1.80, 12 females) in the no reminder group and the control group of 20 college students (Mage = 22.30, SD = 2.05, 10 females) was recruited from the same university. There was no significant difference of trait anxiety among the reminder group (M = 41.4, SD = 1.85), no reminder group (M = 40.45, SD =1.86) and the control group (M = 42.1, SD =1.82), F(2, 57) = 0.20, P = 0.82. There was also no significant difference of state anxiety among the reminder group (M = 36.55, SD = 1.59), no reminder group (M = 34.70, SD =1.40) and the control group (M = 34.75, SD = 1.40), F(2, 57) = 0.52, P = 0.60). Individuals with a history of psychiatric care, neurological disease or head injury were excluded. Written informed consent was obtained from each participant. The study was approved by the Institutional Review Board of the Southwest University.

The paradigm consisted of three consecutive stages conducted 24h apart: day 1-Acquisition, day 2-Reminder, Reconsolidation and Extinction and day 3-Re-extinction. On the first day, all participants were divided into two groups: fear acquisition group and the control group. In respect to fear acquisition group (n = 40), a fear conditioning session was completed on day 1, while the control group underwent the same task without fear reinforcement. On the second day, the fear acquisition participants were randomly assigned into one of the two groups: the reminder group and the no reminder group. On the second day, four participants (two participants for each group) were removed from the fMRI (task-based) analysis and two participants in the no reminder group were removed from the resting-state analysis due to excessive head movement. On the third day, two participants (two participants for the reminder group) were removed from the fMRI (task-based) analysis due to excessive head movement. All sessions were performed in the scanner in the three consecutive days.

Stimuli

To choose the materials of US and the neutral stimulus (the fear and neutral pictures), other 50 participants rated 533 pictures chosen from the Internet and International Affective Picture System which was used in the fear conditioning task (Lang et al., 1999; Feng et al., 2013, 2014). In accordance with the previous literature, we used a dimensional model for measuring pictures along three dimensions, ‘valence’, ‘arousal’ and ‘the degree of fear’. They rated the respective dimensions on a 7-point Likert scale. We then chose 60 fear pictures and 160 neutral pictures, in which the disparity of the degree of fear and the valence was as large as possible [the fear picture (fear): M = 5.72, SD = 0.51, the neutral picture (fear): M = 1.85, SD = 0.55, t(49) = 33.38, P < 0.001; the fear picture (valence): M = 6.08, SD = 1.09, the neutral picture(valence): M = 2.86, SD = 0.50, t(49) = 18.35, P < 0.001] and the arousal of fear pictures and neural pictures was as follows: the fear picture (arousal): M = 5.12, SD = 0.35, the neutral picture (arousal): M = 4.74, SD = 0.27, t(49) = 1.36, 0.1. The CS (CS+, CS-) were yellow and blue squares and the US were the fear pictures.

Design and procedure

The experiment consisted of three stages conducted in three consecutive days: day 1-Acquisition, day 2-Reminder, Reconsolidation and Extinction and day 3-Re-extinction (see Figure 1). The detailed procedures are described below:

Fig. 1.

Fig. 1.

Open in a new tab

Schematic illustration of the paradigm for the experiment.

Day 1: fear acquisition

During acquisition, all fear acquisition participants (n = 40) underwent a Pavlovian discrimination fear-conditioning paradigm with partial reinforcement (Monfils et al., 2009; Schiller et al., 2009; Agren et al., 2012), while the control group (n = 20) underwent the same task without fear reinforcement. The CS (CS+, CS−) were yellow and blue squares (2 s) and the US was the fear picture (2 s) following the CS+. The inter-trial-interval was 2–6 s. The CS+ was paired with a fear picture on a 62.5% partial reinforcement schedule and the CS− was always paired with a neutral picture. The whole session lasted for 40 min, where 120 CS+ and 60 CS− were presented. Participants were instructed to pay attention to the screen and try to figure out the relationship between the squares appearing on the screen and the following picture. Moreover, when the CS+ appeared on screen, the participants need to press key ‘1’, otherwise they should press ‘3’. Two orders were used to counterbalance for key (within-subjects design) and designations of colored squares (blue or yellow) as CS+ or CS− (between-subjects design). In control group, participants performed an associative learning task where the yellow or blue color square was paired with two types of emotionally neutral pictures, i.e. scenes or objects. In other words, the participants were instructed to predict the kind of picture following each of the color square. Subjective fear ratings (CS+ and CS−) were obtained immediately following acquisition stages using an 1–7 fearfulness scale, where the CS+ and CS− presented four times, respectively(1, mildly; 4, moderately; and 7, extremely).

Day 2: fear memory reminder, reconsolidation and extinction

After 24 h the fear acquisition participants returned to lab and were randomly assigned to one of the two groups: the reminder group (n = 20) and the no reminder group (n = 20). The two groups underwent extinction training where the CS+ and CS− were repeatedly presented without the US (the neural picture followed by the CS+ and the CS−). In the reminder group, the fear memory was reactivated prior to extinction. During reactivation, the CS+ with the US was presented in Duvarci and Nader (2004) followed by a 10 min resting state (REST2 for the reminder group, REST1 for the no reminder group) in which the fear memory was activated (Monfils et al., 2009; Schiller et al., 2009). However, in the no-reminder group, all procedures were the same as the reminder group except for no reinforcement (the CS +  with the neural pictures presented). During the resting state, participants were instructed to keep their eyes closed, relax their mind, and remain motionless as much as possible. The resting-state scan lasted for 600 s. All participants informed that they had not fallen asleep during the scan.

The extinction lasted for 30 min, where 60 CS +  and 60 CS− were presented without reinforcement. Subjective fear ratings (CS+ and CS−) were obtained immediately following fear extinction stages using an 1–7 scale of fearfulness (on a 7-point Likert scale: 1, mildly; 4, moderately;7, extremely), where the CS +  and CS− presented four times, respectively.

Day 3 fear re-extinction

In re-extinction stage, the stimulus with non-reinforcement was presented (the CS +  with the neural pictures presented).The re-extinction was similar for both groups and consisted of stimuli with non reinforcement (60 CS+, 60 CS−). The re-extinction sessions lasted for 30 min. Finally, subjective fear ratings (CS+ and CS−) were obtained immediately following re-extinction stages using an 1–7 scale of fearfulness (on a 7-point Likert scale: 1, mildly; 4, moderately; 7, extremely), where the CS +  and CS− presented four times, respectively.

We used the fear picture as the US at the stage of fear acquisition, so the process of fear acquisition and the extinction became slower, and that was why the number of CS (CS +  and CS−) was more than that in the typical design during the stage of fear acquisition, fear extinction and fear re-extinction in the present design (Feng et al., 2013, 2014). Additionally, to confirm that both the subjective fear ratings and the skin conductance response (SCR) are the index of fear response. Other 25 right-handed participants were recruited for the study (two participants were eliminated from statistical analysis because they did not acquire fear conditioning). We used the subjective fear ratings (on a 7-point Likert scale: 1, mildly; 4, moderately; 7, extremely) and SCR in the same experimental paradigms to measure the fear response of CS (CS +  and CS−).

Image acquisition and analysis

fMRI acquisition

Data were acquired using a Siemens 3T scanner (Siemens Magnetom Trio TIM, Erlangen, Germany). Head movement was restricted using foam cushions (>2 mm, 2°). T1-weighted images were recorded with a total of 176 slices at a thickness of 1 mm and in-plane resolution of 0.98 × 0.98 mm (TR = 1900 ms; TE = 2.52 ms; flip angle = 9°; FOV = 250 × 250 mm2). During visual presentations blood oxygen level dependent (BOLD) imaging was performed using a single shot echo-planar imaging (EPI) sequence with parameters TR = 2000 ms; TE = 30 ms; flip angle= 90°; FoV =192 ×192 mm2; matrix size = 64 × 64; voxel size = 3 × 3 × 3 mm3; interslice skip = 0.99 mm; Slices = 32. We employed the identical data acquisition parameter and preprocessing step in resting-state fMRI.

fMRI data analysis

Task-based fMRI

We used SPM8 to analysis the functional data (Friston et al., 1994). For T2*-weighted images, slice timing was used to correct for different slice scan timings, the data were realigned to estimate and modify the six parameters of head movement, and first five images were discarded to achieve magnet-steady images. The T1-weighted images were co-registered to the EPI mean images and segmented into white matter, grey matter and cerebrospinal fluid (CSF).These images were then normalized to Montreal Neurological Imaging (MNI) space in 3 × 3 × 3 mm3 voxel sizes. The normalized data were spatially smoothed with a Gaussian kernel, and the full width at half maximum was specified as 8 × 8 × 8 mm3.

In the first-level specify the four functional scanning runs were modeled in one general linear model in fear extinction (four runs) and re-extinction task (four runs) on the second day and the third day respectively. Four regressors (‘+’, CS+, CS− and neutral picture) were created for each run after convolution with the Canonical Hemodynamic Response Function. These regressors further included six realignment parameters, and the resulted design matrix was filtered with a high-band pass of 128 s. After these we used the contrast of CS+ and CS− to explore the fear extinction and fear re-extinction related brain regions in the second-level specify, and the threshold of P-value was 0.05, False discovery rate (FDR) corrected.

Psychophysiological interaction (PPI) analysis employs one regressor (CS+ minus CS−) representing the psychological variable, one regressor representing the time course in a given volume of interest (VOI) (the physiological variable), and a third regressor representing the cross-product of the previous two (the PPI term). Based on the BOLD activation results (ROI defined by the no reminder group vs reminder group during re-extinction on day 3; P < 0.05, FDR corrected), we defined the bilateral amygdala as seed regions with the contrast of (1 −1) (CS +  minus CS−). VOIs’ time courses (first eigenvariate) were extracted from the seed regions and then the PPI term was created with the time course and the psychological variable. PPI analysis were then carried out for VOI in each subject and a followed group-level two-sample t-test was conducted to examine which brain regions showed higher functional connectivity with the amygdala in the no reminder group vs reminded group. ‘To examine the functional connectivity between the reminder group and the no reminder group at extinction stages, we also performed PPI analysis at the early extinction stage and late extinction stage (day 2). Based on the BOLD activation results (ROI defined by CS +  minus CS− contrast of the no reminder group vs reminder group during the extinction on day 2, we defined the bilateral amygdala as seed regions with the contrast of (1 −1) (CS+  minus CS−)’ .

Resting-state fMRI

The identical data acquisition parameter and pre-processing step were employed here as they were in task-based fMRI. However, the spatially smoothing kernel was 6 × 6 × 6 mm3. The REST and DPARSF software were further used in rest-state analysis (Yan and Zang, 2010; Song et al., 2011). We removed the linear drift and filtered the spectrum with the band pass of 0.01–0.08 Hz before the calculation of voxel wise and ROI voxel wise for each subject (Zang et al., 2007).

Regions of interest analysis (Voxel wise and ROI wise)

To further elucidate the network by which the amygdala exert its different effects between the reminder group and the no reminder group after fear memory reactivation, especially in regard to the vmPFC, we performed voxel wise and ROI wise analysis. For voxel wise analysis, here we calculated the voxel-wise functional connectivity with the region of interests (ROI) in amygdala. ROI were selected on the basis of prior researches(Agren et al., 2012) and the ROI was defined using MarsBaR (Brett et al., 2002), that is, the amygdala was defined as a 10 mm (semi-diameter) spherical ROI centered on the MNI coordinate (right amygdala, 27, 5, −17; left amygdala, −15, −1, −14).The functional connectivity was estimated based on the detrended, filtered, and covariables removed images. The covariables included the six head motion parameters, global mean signal, white matter signal and CSF signal (Fox et al., 2005). The global signal is thought to reflect a combination of physiological processes (i.e. cardiac and respiratory fluctuations), and therefore, was treated as covariables to control for such factors (Margulies et al., 2007; Di Martino et al., 2008; Roy et al., 2009). Each participant’s time courses were obtained separately from activation maps, and were then used as regressors in a voxel-based whole-brain correlation analysis. Importantly, the time course from the same voxel was used as a regressor for each participant.

For ROI wise analysis, we selected the amygdala and vmPFC as ROIs. The vmPFC was defined as a 10 mm spherical ROI centered on the MNI coordinates xyz = 4, 32, −5 on the basis of prior researches (Phelps et al., 2004; Milad et al., 2007), and the definition of the amygdala is the same as the voxel wise analysis. Difference in the functional amygdala-vmPFC coupling between the reminder group (REST2) and the no reminder group (REST1) was obtained by subtracting the individual time course correlation coefficient between amygdala and vmPFC during resting state and converting it to normal distribution with Fisher’s z transformation. The threshold was P < 0.01, corrected for multiple comparisons using the FDR correction.

Correlation analysis between RSFC and behavioral data

To investigate whether the functional connectivity between amygdala and vmPFC following fear reminder (on the second day) in the reminder group can predict extinction effect, we conducted the correlation analysis between functional connectivity of amygdala-vmPFC and the change (Δ) of subjective fear ratings (the first day vs the third day).

Results

Behavioral results

To verify that apart from SCR, the subjective fear ratings can also be used an indicator of fear response, the correlation analysis showed that the subjective fear ratings (differential fear ratings to the CS +  and CS−) was positively correlated with the SCR (r = 0.74, P = 0.001).The result suggested that the subjective fear ratings could reflect the fear response in the same way as the SCR did in our study.

Subjective fear ratings (CS+ and CS−) were obtained using a 1–7 scale of fearfulness (on a 7-point Likert scale: 1, mildly; 4, moderately; 7, extremely) immediately following the stage of fear acquisition (on the first day), fear memory extinction (on the second day) and fear memory re-extinction (on the third day). On the first day, two-way mixed ANOVA analysis on the group (fear acquisition group vs control group) and the type of the CS (CS +  vs CS−) revealed that there was a significant interaction between two factors, F(1, 54) = 79.45, P < 0.001. To examine the effect of experiment treatment, we performed a simple effect analysis. The following results were obtained: in the fear acquisition group, the subjective fear ratings of CS +  and CS− were as follows: the CS+: M  = 5.42, SD = 1.52, the CS−: M = 1.28, SD = 0.77, t (35) = 13.07, P < 0.001. In the control group, the subjective fear ratings of CS+ and CS− were as follows: the CS+: M = 1.75, SD = 0.55, the CS−: M = 1.6, SD = 0.60, t (19) = 1.14, P = 0.27. For another simple effect analysis, the following results were obtained: there was no significant difference between the subjective fear ratings of CS− in fear acquisition group (M = 1.28, SD = 0.77) and the subjective fear ratings in the control group (M = 1.6, SD = 0.60), t(54) = 1.59, P = 0.12; However, participants in the fear acquisition group have greater fear ratings of CS +  (M  = 5.42, SD = 1.52) than that in the control group (M  = 1.75, SD = 0.55), t(54) = 10.34, P < 0.001. In the following analysis, we used the differential fear ratings (CS +  vs CS−) as the fear indicator which was in line with the prior researches (Monfils et al., 2009; Schiller et al., 2009; Agren et al., 2012). Additionally, there was no significant difference of the subjective fear ratings (CS+ vs CS−) between the reminder group (M = 4.45, SD = 1.19) and the no reminder group (M  = 4.13, SD = 1.09) during the stage of fear acquisition (on the first day), t (34) = 0.85, P = 0.40. The behavioral results showed that the fear acquisition group (the reminder group and the no reminder group) acquired the conditioned fear.

Extinction effect was assessed using a two-way mixed ANOVA on the group (reminder group vs the no reminder group) and the time (the second day vs the third day). This showed a significant interaction between the group and time, F(1,34) = 14.18, 0.001. After performing simple effect analysis, the results showed that there was no significant difference of fear ratings (the differential fear ratings between CS +  and CS−) between the reminder group (M = 1.90, SD = 0.72) and the no-reminder group (M = 1.63, SD = 0.62) during the stage of fear extinction (on the second day) [t(34) = 1.21, P = 0.23]. However, participants in the no-reminder group had greater fear ratings (M = 3.31, SD = 1.70) than that in the reminder group (M = 1.75, SD = 0.55) (on the third day) [t(34) = 3.87, P = 0.001]. For another simple effect analysis, the following results were obtained: in the reminder group, there was no significant difference between the subjective fear ratings on the second day (M = 1.90, SD = 0.72) and the subjective fear ratings on the third day (M = 1.75, SD = 0.55), [t(19) = 0.83, P = 0.42] However, participants in the no reminder group had greater fear ratings (M = 3.31, SD = 1.70) on the third day than that on the second day (M = 1.63, SD = 0.62), t(15) = 3.40, P < 0.01 (see Figure 2). The behavioral results showed that spontaneous recovery appeared only in the no reminder group on the re-extinction stages, whereas participants in the reminder group showed no spontaneous recovery. These results suggested that the spontaneous recovery of fear after extinction can be prevented if extinction training is conducted following the fear memory reminder during the fear reconsolidation window.

Fig. 2.

Fig. 2.

Open in a new tab

Mean differential fear ratings (CS+ minus CS−) during acquisition, extinction and re-extinction for the reminder group and the no reminder group.

The fMRI results during the acquisition, extinction and re-extinction stage

In order to investigate whether the fear matrix is only active in the fear acquisition group and ensure the effect of fear acquisition, we performed the paired t-test between the CS+ and the CS− in the fear acquisition group and control group, respectively. The results revealed that the fear matrix, including amygdala, mPFC, insula, thalamus and temporal lobe, was only active in the fear acquisition group (the reminder group and no reminder group), but not in control group (P < 0.05, FDR corrected) (Feng et al., 2014).To investigate the neural representation of the fear extinction effect, we performed a two sample t-test (CS+ vs CS− image for each group). During the stage of fear extinction (on the second day), there was no significant difference of brain activity between the reminder group and the no reminder group. However, during the stage of fear re-extinction (on the third day), significantly greater activity was evident in the bilateral amygdala in the no-reminder group (standard extinction training) as compared with the reminder group (extinction training during fear memory reconsolidation window) (see Figure 3 and Table 1). At the early stage of fear extinction (day 2), PPI analysis revealed that there was much stronger functional connectivity between amygdala and vmPFC (extending to dmPFC) in the reminder group than that in the no reminder group at the early extinction stage. However, there was no significant difference of amygdala-vmPFC connectivity between the reminder group and the no reminder group at late extinction stage (see Figure 4A). Moreover, we performed a two-way ANOVA on the group (reminder group vs the no reminder group) and the time (early extinction vs late extinction) in the amygdala-vmPFC functional connectivity. The results showed a significant interaction between the group and time, F(1, 34) = 9.68, P < 0.005. After performing simple effect analysis, the results showed that functional connectivity between vmPFC and amygdala in the reminder group was greater than that in the no reminder group at the early extinction stage. In another simple effect analysis, as extinction progressed, the functional connectivity of vmPFC-amygdala increased from early extinction to later extinction for the no reminder group (P < 0.05), but it decreased from early extinction to later extinction for the reminder group (P < 0.05) (see Figure 4B).These results further suggest that extinction during reconsolidation prevents fear recovery and diminishes PFC involvement. On the stage of fear re-extinction (day 3), PPI analysis revealed that there was much stronger functional connectivity between amygdala and vmPFC in no reminder group than that in the reminder group (P < 0.05, corrected) (see Figure 5). The fMRI results of extinction and re-extinction were consistent with our behavioral results, which demonstrated the reminder and reconsolidation window may be important determinants to prevent spontaneous recovery. Why could the extinction training during fear memory reconsolidation window prevent fear recovery? The neural state of activation following fear reminder may serves a key role in the following extinction learning.

Fig. 3.

Fig. 3.

Open in a new tab

Significantly greater activity was evident bilaterally in the amygdala (right amygdala, 27,−4, −14; left amygdala, −26, −2, −14) in the no-reminder group as compared with the reminder group on the stage of fear re-extinction (on the third day) (P < 0.05, FDR corrected).

Table 1.

Different areas of brain activation for CS+ vs CS− between the no reminder group and the reminder group in the re-extinction training

Region BA No. Voxels Peak t-value x y z
R. Parahippocampa/Lingual/Fusiform/Superior Temporal/Inferior Frontal Gyrus 19/36/30 479 4.98 27 −4 −11
L. Parahippocampa/Superior Temporal/Inferior Frontal Gyrus 40/13/41 422 4.18 −27 2 −14
R. Medial/Superior Frontal Gyrus 10 71 3.04 −12 56 1
R. Insula/Superior Temporal Gyrus 40/41/13 303 3.81 48 −28 7
L. Superior/Middle Occipital/Middle Temporal Gyrus 19/7 71 3.35 −36 −88 22
Open in a new tab

Detailed information for clusters showing group differences (MNI coordinates).

Fig. 4.

Fig. 4.

Open in a new tab

(A) There was much stronger functional connectivity between amygdala and vmPFC in reminder group than that in no reminder group at early extinction stage (P < 0.05, corrected). (B) As extinction progressed, the functional connectivity of vmPFC-amygdala increased from early extinction to late extinction for the no reminder group CS+ (P < 0.05), but it decreased from early extinction to late extinction for the reminder group (P < 0.05).

Fig. 5.

Fig. 5.

Open in a new tab

There was stronger amygdala-vmPFC functional coupling in the no reminder group as compared with the reminder group on the stage of re-extinction (P < 0.05, corrected).

Resting-state fMRI results

The RSFC result (voxel wise and ROI wise) after fear memory reactivation

To further elucidate the RSFC after fear memory reactivation, we performed a whole-brain voxel-based correlation using time courses obtained from the amygdala as seed (Voxel wise). The results indicated the amygdala was functionally positively coupled with vmPFC in the reminder group [t(19) = 3.4, P =  0.01, ‘FDR corrected’]. In the no-reminder group, the amygdala exerted a similar pattern which positively correlated with vmPFC [t(17) = 3.5, P = 0.01, ‘FDR corrected’] (see Figure 6). As the Figure 6 showed, there was much stronger functional connectivity between the amygdala and vmPFC in the reminder group than that in the no reminder group.

Fig. 6.

Fig. 6.

Open in a new tab

Based on prior research, we extract the ROI for resting analysis (right amygdala, 27, 5, −17; left amygdala, −15, −1, −14; vmPFC, 4, 32, −5). Sagittal views of interregional functional coupling maps, focused on the amygdala coupling with vmPFC separately obtained from the no-reminder group (REST1) and the reminder group after fear memory reactivation (REST2) (P = 0.01, FDR corrected).

To compare functional connectivity between the reminder group and the no reminder group, we subtracted the individual time course correlation coefficient between amygdala and vmPFC (ROI-wise). ROIs were selected on the basis of prior researches (right amygdala, 27, 5, −17; left amygdala, −15, −1, −14; vmPFC,4, 32, −5) (Phelps et al., 2004; Milad et al., 2007; Agren et al., 2012). The result showed that functional connectivity analysis revealed that stronger functional connectivity between the amygdala and vmPFC in the reminder group than that in the no-reminder group [t(35) = 2.32, P = 0.026] (see Figure 7).

Fig. 7.

Fig. 7.

Open in a new tab

The difference in amygdala-vmPFC functional connectivity between the reminder group and the no reminder group after fear memory reactivation (P < 0.05).

In summary, the results of voxel and ROI wise revealed that RSFC between the amygdala and vmPFC played a key role in the state of fear memory reactivation. However, could the RSFC after fear memory reactivation influence the following extinction or re-extinction stage?

The RSFC after fear memory reactivation predicts extinction effect

To investigate whether the RSFC between amygdala and vmPFC following fear reminder can predict extinction effect (Δfear ratings: the fear ratings on the first day subtract the fear ratings on the third day), we conducted the correlation analysis between functional connectivity of amygdala-vmPFC and the change (Δ) of subjective fear ratings (the first day vs the third day) in the reminder group. The correlation analysis showed that functional connectivity of the amygdala-vmPFC was positively correlated with the change (Δ) of subjective fear ratings (r = 0.51, P = 0.02) (see Figure 8). However, there was no significant correlation between RSFC of the amygdala-vmPFC and Δfear ratings in the no reminder group (r = 0.23, P = 0.39).The findings suggested individual differences in amgydala-vmPFC functional connectivity following fear reminder can predict individuals’ extinction effect.

Fig. 8.

Fig. 8.

Open in a new tab

Individual differences in amgydala-vmPFC functional connectivity after fear memory reactivation predicted individuals’ extinction effect (the change (Δ) in subjective fear ratings: the fear ratings on the first day subtract the fear ratings on the third day), r = 0.51, P = 0.02.

Discussion

Using rs-fMRI, we measured functional connectivity after fear memory reactivation, and investigated whether the extinction effect can be predicted by RSFC after fear memory reactivation. Behaviorally, there was no significant difference of fear ratings between the reminder group and the no reminder group on the fear acquisition and extinction stages, but spontaneous recovery appeared only in the no reminder group on the re-extinction stage. More importantly, neuroimaging results revealed three primary findings: first, in the no reminder group (standard extinction training), significantly activity was evident in the bilateral amygdala during the stage of fear memory re-extinction (on the third day); second, the reminder group had stronger functional connectivity between vmPFC and amygdala than that in the no reminder group after fear memory reactivation; finally, the RSFC between amygdala and vmPFC in the reminder group after fear memory reactivation can predict extinction effect. In summary, these results provided a new perspective for exploring the neural state of fear activation after fear memory reactivation.

In line with prior researches, our behavioral results demonstrated that extinction conducted during the reconsolidation window prevented the spontaneous recovery. It has been suggested that the reminder and the fear reconsolidation window may be important determinants to prevent spontaneous recovery (Alberini, 2005; Hupbach et al., 2007; Monfils et al., 2009). In accordance with prior researches, we found significantly greater activity in the bilateral amygdala in the no-reminder group (standard extinction training) as compared with the reminder group (extinction training during the fear reconsolidation window) during the stage of fear re-extinction (on the third day). A wealth of behavioral researches suggested that humans and rodents are alike, reactivated fear memories can be attenuated by disrupting reconsolidation with extinction training (Monfils et al., 2009; Schiller et al., 2009; Xue et al., 2012). Using fMRI, Agren et al. (2012) showed that, after a conditioned fear memory was formed, reactivation and reconsolidation left a memory trace in the basolateral amygdala that predicted subsequent fear expression and was tightly coupled to activity in the fear circuit of the brain. In contrast, reactivation followed by disrupting reconsolidation suppressed fear, abolished the memory trace, and attenuated fear-circuit connectivity. Furthermore, we found stronger amygdala-vmPFC functional connectivity in the reminder group as compared with no reminder group at the stage of early extinction. As extinction progressed, the amygdala-vmPFC functional connectivity increased in the no reminder group, but it decreased in the reminder group. These findings suggest that extinction during fear reconsolidation window following fear reminder may increase the necessity for vmPFC inhibition (for reminder group), but as extinction progressed, standard extinction training (for no reminder group) may increasingly need the inhibition of vmPFC from early extinction, later extinction and re-extinction. Consistent with prior research, our results suggest that targeting reconsolidation may reduce the necessity for vmPFC inhibition, which linked to more persistent reduction of fear reactions (Schiller et al., 2013). At the same time, there was stronger amygdala-vmPFC functional coupling (CS +  vs CS−) in the no reminder group as compared with the reminder group on the stage of re-extinction. The present finding consisted with the prior finding (Koenigs et al., 2007; Koenigs and Grafman, 2009; Schiller et al., 2013). In the reminder group, there was a relative disconnect between the amygdala and vmPFC. This attenuated connectivity may play an important role in enabling extinction training to more permanently modify the original threat memory trace, thus preventing the return of fear reactions. As previously demonstrated in rodents and humans, our findings suggested that the fear memory was not erased, but only was transitorily suppressed via the vmPFC its connections with the amygdala if not disrupted reconsolidation following reactivation. We could conclude that extinction training initiated during reconsolidation abolishes fear expression by erasing a memory trace in the amygdala and diminishes the involvement of the vmPFC.

More important findings were that the reminder group was greater functional connectivity between vmPFC and amygdala comparing with the no reminder group after fear memory reactivation. There may be two reasons why extinction training coinciding with fear memory reconsolidation can prevent the spontaneous recovery responses. On the one hand, recent research in rodents indicated that the amygdala and vmPFC contributed to the reconsolidation of emotional memory traces following their retrieval. These studies demonstrated the extinction in the fear memory reconsolidation window may not reflect memory erasure or unlearning, but rather a new learning process of a CS-no-event contingency, which competes with the original CS–US association in determining behavior (Bouton, 2002; Monfils et al., 2009; Schiller et al., 2009; Barak and Hamida, 2012). Specifically, Nader et al. (2000) found that fear memories require de novo protein synthesis in the amygdala for reconsolidation after retrieval. In addition, Monfils et al. (2009) found that reduced phosphorylation of GluR1 glutamate receptors (a molecular marker of reconsolidation) in the amygdala following immediate but not delayed extinction after reactivation. With respect to vmPFC, Akirav and his fellow’s research indicated that both protein synthesis and NMDA receptors are required for reconsolidation of recognition memory in the vmPFC (Akirav and Maroun, 2006). On the other hand, the amygdala and vmPFC may serve vital role for emotional regulation by interaction with other brain regions (Ochsner et al., 2002; Schaefer et al., 2002; Phelps et al., 2004). With respect to rodent connectivity, prelimbic PFC and infralimbic PFC can modulate fear expression through descending projections to the amygdala. (Royer and Pare, 2002; Quirk et al., 2003; Likhtik et al., 2005; Amir et al., 2011; Liang et al., 2012). With regard to human connectivity, the success of emotion regulation appears to be associated with reduced amygdala activation together with increased activation of various prefrontal regions, including the vmPFC (Hartley and Phelps, 2009; Kim et al., 2011). Moreover, greater connectivity of the default network such as vmPFC with the amygdala during fear reconsolidation may be particularly interesting in light of the suggestion that a function of the default network is to maintain the organism in a state of readiness for expected future events such as improving extinction effect (Raichle and Gusnard, 2005). Interestingly, Agren et al. (2012) found that amygdala memory trace activity is functionally coupled to the fear network after normal memory reconsolidation but not after disrupted reconsolidation. This result suggested that the amygdala could be the primary site of memory plasticity, but also influenced reconsolidation by affecting other regions of the fear network. Another research indicated that vmPFC serves as a key role in the effect of extinction training after fear reminder. Specially, extinction training after fear reminder diminished vmPFC involvement and reduced vmPFC-amygdala coupling, which might enable extinction learning training to more persistently change the original fear-memory trace within the amygdala (Schiller et al., 2013). On the whole, the RSFC results suggested that amygdala and vmPFC played key role in the fear reconsolidation. When the fear memories are diminished through standard extinction, the amygdala’s representation remains largely intact and the PFC inhibits its expression, thus allowing the learned fear responses to recover. However, extinction during fear reconsolidation window eliminates the necessity of prefrontal inhibition. This altered connectivity may serve an important role in enabling extinction learning training to more persistently modify the original threat-memory trace within the amygdala, thus preventing the return of fear (Sotres-Bayon and Quirk, 2010; Agren et al., 2012; Pare and Duvarci, 2012; Schiller et al., 2013). Our findings also directly indicated that the timing of extinction relative to the reactivation of the memory can capitalize on reconsolidation mechanisms. Specifically, extinction training during fear memory reconsolidation window disrupted fear memory reconsolidation but not enhanced extinction.

Interestingly, the functional connectivity between amygdala and vmPFC in the reminder group after fear memory reactivation was positively correlated with extinction effect. In many researches, resting metabolism can predict the effect of the extinction and symptoms of psychopathologies (e.g. anxiety, PTSD). Specifically, Linnman et al. (2012) showed that resting metabolism in the dACC and in the vmPFC might predict the magnitude of fear learning and fear extinction in healthy individuals. In particular, the metabolism in amygdala positively predicted activation in the vmPFC and negatively predicted activation in the dACC during extinction training. However, the predictive relationships were reversed during re-extinction. More importantly, limited PFC involvement (early in development and following vmPFC damage) has also been linked to a more persistent reduction of fear reactions. Kim and Richardson (2010) found that in post-weanling-aged rats (24-days old) extinction was ‘adult-like’ in the sense that the extinguished threat memory recovered following renewal, reinstatement, and spontaneous recovery. Preweanling-aged rats (17-days old); however, did not display these phenomena. The vmPFC and amygdala may play an important role in the extinction training of adult rats, whereas in young rats (17-days old) extinction learning engaged the amygdala but not the vmPFC (Kim and Richardson, 2008; Kim et al., 2009). These results suggested that the extinguished memory was never erased, but only inhibited in adult rats (24-days old) extinction learning via the vmPFC inhibition to the amygdala(Bouton, 2004). Moreover, Koenigs et al. (2007) found that veterans with damage either to the vmPFC or the amygdala had substantially less occurrence of PTSD. It suggested the consequences of vmPFC damage was not in releasing amygdala from inhibition (Koenigs and Grafman, 2009), but rather in inducing a fundamental change in the memory processes occurring at the level of the amygdala itself. In this study, the extinction training during the fear memory reconsolidation window disrupted the vmPFC inhibition to the amygdala after fear memory reactivation. The present study suggested that functional connectivity between amygdala and vmPFC after fear memory reactivation can predict the effect of fear extinction. Extinction training during the fear reconsolidation window may not only disturb the fear memory reconsolidation, but also diminish the vmPFC involvement and reduce vmPFC-amygdala coupling in the fear extinction. In particular, the vmPFC played an important role in the effect of extinction training after fear memory reactivation.

Using rs-fMRI, this study explored functional connectivity after fear memory reactivation, and investigated whether RSFC after fear memory reactivation can predict the extinction effect. Accordingly, the present study provided insight into the neural systems and state after fear memory reactivation. From a therapeutic point of view, reducing the necessity of the functional connectivity between the vmPFC and amygdala to control fear reactions may help overcome a primary obstacle in the long-term efficacy for correlated fear disorders. In methodology, the present study may provide an innovative and effective method (RSFC) for mapping the network and elucidate how the neural state affects the following extinction after fear memory reactivation.

Several caveats resulting from this study’s design should be taken into account when interpreting the findings reported here. First, the current study did not include objective behavioral data such as SCR which are commonly measured in the human conditioning task. Thus it may not be stronger evidence that the participants acquired the conditioned fear and erased or persistently inhibited fear memory. Second, we lacked of follow-up test to examine whether the observed blockade of fear memory persists and whether the spontaneous activation of brain and intrinsic connectivity change. Third, as the differential effects on fear processing in men and women are prevalent (Schwabe et al., 2013; Williams et al., 2005), future studies should consider gender difference. However, future research should also attempt to identify specific genetic and environmental factors which may contribute to individual differences in the fear reconsolidation researches.

In summary, these findings suggest that the functional connectivity between amygdala and vmPFC after fear memory reactivation may serve a major role in the following extinction training. Importantly, the functional connectivity between amygdala and vmPFC after fear memory reactivation can predict extinction effect. It was important to note here that RSFC after fear memory reactivation may be particularly valuable for great clinical promise in phobia treatment in order to dissociate fear from cognitive memory.

Funding

This study was supported by the National Natural Science Foundation of China (31571128; 31271117) and the Fundamental Research Funds for the Central Universities (SWU1509392) and the General project of Chongqing frontier and applied basic research (cstc2015jcyjA10127).

Conflict of interest. None declared.

References

  1. Agren T., Engman J., Frick A., et al. (2012). Disruption of reconsolidation erases a fear memory trace in the human amygdala. Science, 337, 1550–2. [DOI] [PubMed] [Google Scholar]
  2. Akirav I., Maroun M. (2006). Ventromedial prefrontal cortex is obligatory for consolidation and reconsolidation of object recognition memory. Cerebral Cortex, 16, 1759–65. [DOI] [PubMed] [Google Scholar]
  3. Alberini C.M. (2005). Mechanisms of memory stabilization: are consolidation and reconsolidation similar or distinct processes? Trends in Neurosciences, 28, 51–6. [DOI] [PubMed] [Google Scholar]
  4. Amir A., Amano T., Pare D. (2011). Physiological identification and infralimbic responsiveness of rat intercalated amygdala neurons. Journal of Neurophysiology, 105, 3054–66. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Andrews-Hanna J.R., Snyder A.Z., Vincent J.L., et al. (2007). Disruption of large-scale brain systems in advanced aging. Neuron, 56, 924–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Barak S., Hamida S.B. (2012). Memory erasure, enhanced extinction and disrupted reconsolidation. The Journal of Neuroscience, 32, 2250–1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Bouton M.E. (2002). Context, ambiguity, and unlearning: sources of relapse after behavioral extinction. Biological Psychiatry, 52, 976–86. [DOI] [PubMed] [Google Scholar]
  8. Bouton M.E. (2004). Context and behavioral processes in extinction. Learning and Memory, 11, 485–94. [DOI] [PubMed] [Google Scholar]
  9. Brett M., Anton J.L., Valabregue R., Poline J.B. (2002). Region of interest analysis using the MarsBar toolbox for SPM 99. Neuroimage, 16, S497. [Google Scholar]
  10. Di Martino A., Scheres A., Margulies D., et al. (2008). Functional connectivity of human striatum: a resting state FMRI study. Cerebral Cortex, 18, 2735–47. [DOI] [PubMed] [Google Scholar]
  11. Duvarci S., Nader K. (2004). Characterization of fear memory reconsolidation. The Journal of Neuroscience, 24, 9269–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Feng P., Feng T., Chen Z., Lei X. (2014). Memory consolidation of fear conditioning: Bi-stable amygdala connectivity with dorsal anterior cingulate and medial prefrontal cortex. Social Cognitive and Affective Neuroscience, 9, 1730–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Feng T., Feng P., Chen Z. (2013). Altered resting-state brain activity at functional MRI during automatic memory consolidation of fear conditioning. Brain Research, 1523, 59–67. [DOI] [PubMed] [Google Scholar]
  14. Fox M.D., Snyder A.Z., Vincent J.L., Corbetta M., Van Essen D.C., Raichle M.E. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences of the United States of America, 102, 9673.. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Friston K.J., Holmes A.P., Worsley K.J., Poline J.P., Frith C.D., Frackowiak R.S.J. (1994). Statistical parametric maps in functional imaging: a general linear approach. Human Brain Mapping, 2, 189–210. [Google Scholar]
  16. Greicius M.D., Supekar K., Menon V., Dougherty R.F. (2009). Resting-state functional connectivity reflects structural connectivity in the default mode network. Cerebral Cortex, 19, 72–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Hagmann P., Cammoun L., Gigandet X., et al. (2008). Mapping the structural core of human cerebral cortex. PLoS Biology, 6, e159.. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Hartley C.A., Phelps E.A. (2009). Changing fear: the neurocircuitry of emotion regulation. Neuropsychopharmacology, 35, 136–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Hupbach A., Gomez R., Hardt O., Nadel L. (2007). Reconsolidation of episodic memories: a subtle reminder triggers integration of new information. Learning and Memory 14, 47–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Kim J.H., Hamlin A.S., Richardson R. (2009). Fear extinction across development: the involvement of the medial prefrontal cortex as assessed by temporary inactivation and immunohistochemistry. The Journal of Neuroscience, 29, 10802–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Kim J.H., Richardson R. (2008). The effect of temporary amygdala inactivation on extinction and reextinction of fear in the developing rat: unlearning as a potential mechanism for extinction early in development. The Journal of Neuroscience, 28, 1282–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Kim J.H., Richardson R. (2010). New findings on extinction of conditioned fear early in development: theoretical and clinical implications. Biological Psychiatry, 67, 297–303. [DOI] [PubMed] [Google Scholar]
  23. Kim M.J., Loucks R.A., Palmer A.L., et al. (2011). The structural and functional connectivity of the amygdala: from normal emotion to pathological anxiety. Behavioural Brain Research, 223, 403–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Koenigs M., Grafman J. (2009). Posttraumatic stress disorder: the role of medial prefrontal cortex and amygdala. The Neuroscientist. 15, 540–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Koenigs M., Huey E.D., Raymont V., et al. (2007). Focal brain damage protects against post-traumatic stress disorder in combat veterans. Nature Neuroscience, 11, 232–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Lang P.J., Bradley M.M., Cuthbert B.N. (1999). International Affective Picture System (IAPS): Technical Manual and Affective Ratings. Gainesville, FL: The Center for Research in Psychophysiology, University of Florida. [Google Scholar]
  27. Liang Z., King J., Zhang N. (2012). Anticorrelated resting-state functional connectivity in awake rat brain. Neuroimage, 59, 1190–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Likhtik E., Pelletier J.G., Paz R., Paré D. (2005). Prefrontal control of the amygdala. The Journal of Neuroscience, 25, 7429–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Linnman C., Zeidan M.A., Furtak S.C., Pitman R.K., Quirk G.J., Milad M.R. (2012). Resting Amygdala and Medial Prefrontal Metabolism Predicts Functional Activation of the Fear Extinction Circuit. American Journal of Psychiatry, 169, 415–23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Margulies D.S., Kelly A., Uddin L.Q., Biswal B.B., Castellanos F.X., Milham M.P. (2007). Mapping the functional connectivity of anterior cingulate cortex. Neuroimage, 37, 579–88. [DOI] [PubMed] [Google Scholar]
  31. Milad M.R., Wright C.I., Orr S.P., Pitman R.K., Quirk G.J., Rauch S.L. (2007). Recall of fear extinction in humans activates the ventromedial prefrontal cortex and hippocampus in concert. Biological Psychiatry, 62, 446–54. [DOI] [PubMed] [Google Scholar]
  32. Monfils M.H., Cowansage K.K., Klann E., LeDoux J.E. (2009). Extinction-reconsolidation boundaries: key to persistent attenuation of fear memories. Science, 324, 951–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Nader K., Schafe G.E., Le Doux J.E. (2000). Fear memories require protein synthesis in the amygdala for reconsolidation after retrieval. Nature, 406, 722–6. [DOI] [PubMed] [Google Scholar]
  34. Ochsner K.N., Bunge S.A., Gross J.J., Gabrieli J.D. (2002). Rethinking feelings: An fMRI study of the cognitive regulation of emotion. Journal of Cognitive Neuroscience, 14, 1215–29. [DOI] [PubMed] [Google Scholar]
  35. Pare D., Duvarci S. (2012). Amygdala microcircuits mediating fear expression and extinction. Current Opinion in Neurobiology, 22, 717–23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Phelps E.A., Delgado M.R., Nearing K.I., LeDoux J.E. (2004). Extinction learning in humans: role of the amygdala and vmPFC. Neuron, 43, 897–905. [DOI] [PubMed] [Google Scholar]
  37. Quirk G.J., Likhtik E., Pelletier J.G., Paré D., 2003. Stimulation of medial prefrontal cortex decreases the responsiveness of central amygdala output neurons. The Journal of Neuroscience, 23, 8800–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Quirk G.J., Milad M.R. (2010). Neuroscience: editing out fear. Nature, 463, 36–7. [DOI] [PubMed] [Google Scholar]
  39. Quirk G.J., Mueller D. (2007). Neural mechanisms of extinction learning and retrieval. Neuropsychopharmacology, 33, 56–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Raichle M.E., Gusnard D.A. (2005). Intrinsic brain activity sets the stage for expression of motivated behavior. The Journal of Comparative Neurology, 493, 167–76. [DOI] [PubMed] [Google Scholar]
  41. Roy A.K., Shehzad Z., Margulies D.S., et al. (2009). Functional connectivity of the human amygdala using resting state fMRI. Neuroimage, 45, 614–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Royer S., Pare D. (2002). Bidirectional synaptic plasticity in intercalated amygdala neurons and the extinction of conditioned fear responses. Neuroscience, 115, 455–62. [DOI] [PubMed] [Google Scholar]
  43. Schaefer S.M., Jackson D.C., Davidson R.J., Aguirre G.K., Kimberg D.Y., Thompson-Schill S.L. (2002). Modulation of amygdalar activity by the conscious regulation of negative emotion. Journal of Cognitive Neuroscience, 14, 913–21. [DOI] [PubMed] [Google Scholar]
  44. Schiller D., Kanen J.W., LeDoux J.E., Monfils M.H., Phelps E.A. (2013). Extinction during reconsolidation of threat memory diminishes prefrontal cortex involvement. Proceedings of the National Academy of Sciences of the United States of America, 110, 20040–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Schiller D., Monfils M.H., Raio C.M., Johnson D.C., LeDoux J.E., Phelps E.A. (2009). Preventing the return of fear in humans using reconsolidation update mechanisms. Nature, 463, 49–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Schwabe L., Höffken O., Tegenthoff M., Wolf O.T. (2013). Opposite effects of noradrenergic arousal on amygdala processing of fearful faces in men and women. Neuroimage, 73, 1–7. [DOI] [PubMed] [Google Scholar]
  47. Song X.W., Dong Z.Y., Long X.Y., et al. (2011). REST: a toolkit for resting-state functional magnetic resonance imaging data processing. PloS One, 6, e25031.. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Sotres-Bayon F., Cain C.K., LeDoux J.E. (2006). Brain mechanisms of fear extinction: historical perspectives on the contribution of prefrontal cortex. Biological Psychiatry, 60, 329–36. [DOI] [PubMed] [Google Scholar]
  49. Sotres-Bayon F., Quirk G.J. (2010). Prefrontal control of fear: more than just extinction. Current Opinion in Neurobiology, 20, 231–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Vincent J., Patel G., Fox M., et al. (2007). Intrinsic functional architecture in the anaesthetized monkey brain. Nature, 447, 83–6. [DOI] [PubMed] [Google Scholar]
  51. Williams L.M., Barton M.J., Kemp A.H., et al. (2005). Distinct amygdala–autonomic arousal profiles in response to fear signals in healthy males and females. Neuroimage, 28, 618–26. [DOI] [PubMed] [Google Scholar]
  52. Xue Y.X., Luo Y.X., Wu P., et al. (2012). A memory retrieval-extinction procedure to prevent drug craving and relapse. Science, 336, 241–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Yan C.G., Zang Y.F., (2010). DPARSF: a MATLAB toolbox for “pipeline” data analysis of resting-state fMRI. Frontiers in Systems Neuroscience, 4, 13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Zang Y.F., Yong H., Chao-Zhe Z., et al. (2007). Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. Brain and Development, 29, 83–91. [DOI] [PubMed] [Google Scholar]

Articles from Social Cognitive and Affective Neuroscience are provided here courtesy of Oxford University Press

RESOURCES