Abstract

Brain functions during the resting state have attracted considerable attention in the past several years. However, little has been known about spontaneous activity in the sensory cortices in the task-free state. This study used functional magnetic resonance imaging (fMRI) to investigate the existence of spontaneous activity in the primary visual areas (PVA) of normal-sighted subjects and to explore the physiological implications of such activity. Our results revealed that we were able to detect spontaneous activity, which was nonrandom in that it was distinctly clustered both temporally and spatially in the PVA of each subject. In addition, the neural network associated with the PVA-related spontaneous activity included the visual association areas, the precuneus, the precentral/postcentral gyrus, the middle frontal gyrus, the fusiform gyrus, the inferior/middle temporal gyrus, and the parahippocampal gyrus. After considering the functions of these regions, we speculated that the PVA-related spontaneous activity may be associated with memory-related mental imagery and/or visual memory consolidation processes. These findings confirm the presence of spontaneous activity in the PVA and related brain areas. This confirmation supports the perspective that brain is a system intrinsically operating on its own, and sensory information interacts with rather than determines the operation of the system.

Introduction

Interest in investigating what happens in the human brain when subjects do not perform any cognitively demanding tasks has been increased in the past several years. This issue is important because a baseline or control state is fundamental in understanding human brain functions (Raichle and Mintun 2006). In adult humans, the brain accounts for about 2% of the body weight but consumes approximately 20% of the energy (Clark and Sokoloff 1999). Local changes that can be explained as response to task-related activity rarely amount to more than 5% of the high rate of ongoing basal metabolism (Sokoloff et al. 1955; Fox et al. 1985, 1987; Roland et al. 1987; Friston et al. 1990; Madsen et al. 1995). That is to say, even in the task-free state, the brain continuously expends a considerable amount of energy, and external tasks only modestly modulate the effect of such ongoing activity. The above findings are consistent with the perspective that the brain is a system intrinsically operating on its own, primarily driven by internal dynamics, with external events modulating rather than determining the activity of the systems (Llinas 1988; Arieli et al. 1996; Gusnard and Raichle 2001; Kenet et al. 2003; Fiser et al. 2004; Maclean et al. 2005; Olshausen and Field 2005; Raichle and Gusnard 2005; Raichle and Mintun 2006). Therefore, as suggested by Raichle and colleagues, in terms of overall brain functions, the ongoing intrinsic activity within various brain systems may be at least as important as the activity evoked by external stimuli (Raichle and Gusnard 2005; Raichle and Mintun 2006).

A previous animal study found that there were spontaneous fluctuations in the primary visual cortex of anesthetized cat in the absence of any sensory stimulus and that the spontaneous patterns of activity were not random but resembled the patterns of activity produced in response to certain visual stimuli (Kenet et al. 2003). This study suggested the need to address the properties of ongoing activity in the task-free state. It should be emphasized that their study was performed on anesthetized animals. Therefore, to further address the functional significance of these spontaneous cortical states, it will be necessary to study whether the spontaneous activity also occurs in animals that are awake (Kenet et al. 2003; Ringach 2003). For this reason, the present study investigated the existence and the characteristics of spontaneous activity in the human brain during the resting state using the blood oxygen level–dependent (BOLD) imaging technique.

The BOLD imaging technique has been widely used to explore changes in neuronal activity associated with discrete events. During the resting state, many previous studies have found that the spontaneous fluctuations of BOLD signals are coherent within specific neuroanatomical systems in the human brain (Biswal et al. 1995; Lowe et al. 1998; Stein et al. 2000; Cordes et al. 2001; Hampson et al. 2002; Greicius et al. 2003; Jiang et al. 2004; Fox et al. 2005). This suggests that these spontaneous fluctuations could partially reflect the underlying spontaneous neuronal activity within specific systems (Biswal et al. 1995; Nir et al. 2006). It should be noted that the previously used standard functional connectivity analysis primarily focused on the correlation patterns between different brain areas rather than on the activity pattern within a specific brain region. In order to more directly evaluate the characteristics of spontaneous activity, in the present study, we used a spontaneous activity detection method similar to that of Hunter et al. (2005) to investigate the spontaneous activity in the primary visual areas (PVAs) of human beings during the resting state. By examining episodic signal increases that are statistically similar in magnitude to externally evoked activations such as those that have been found in other functional magnetic resonance imaging (fMRI) experiments, this method could detect the pattern of spontaneous activity in the PVA. We chose the PVA as the region of interest (ROI) based on the following considerations: 1) Previous studies, as well as our daily experiences, have indicated that memory-related visual imagery is one of the important mental processes during the resting state (Christoff et al. 2004). According to earlier findings, visual imagery can activate brain areas that are similar to those activated during visual perception (Roland and Gulyas 1994; Ishai and Sagi 1995, 1997a, 1997b; Mellet et al. 1996, 1998; D'Esposito et al. 1997; Ishai et al. 2000). Although some previous studies have found the activations of the PVA during visual recall and visual imagery (Kosslyn et al. 1993, 1995, 1999; Le Bihan et al. 1993), there is still debate for the involvement of PVA in mental imagery processes (Kosslyn et al. 2001). This issue is very important because if the PVA participates in the spontaneous mental processes (such as visual imagery), the implication may be that such mental processes could incorporate sensory representations from earlier processing stages in the visual pathway. Moreover, it offers the possibility that such inner mental processes may even modulate our perception of what we are really seeing (Bertolo 2005). 2) Previous studies that used optical imaging of voltage-sensitive dyes have found that the PVA of anesthetized animals have spontaneous activity when there is no visual stimulus (Arieli et al. 1995, 1996; Tsodyks et al. 1999; Kenet et al. 2003). These findings offer direct evidence for the existence of spontaneous activity in the PVA. However, whether such spontaneous activity also exists in the waking human brain and whether such spontaneous activity is associated with specific mental processes still need to be elucidated. After obtaining the pattern of spontaneous activity, we analyzed the neural network that was associated with spontaneous activity in the PVA to verify the possible functional significance of the activity.

The overall purpose of this study was to investigate the existence of spontaneous activity in the PVAs of normal-sighted subjects during the resting state with eyes closed and to explore the possible physiological implications of such activity. Our results showed that during the resting state, some episodic activity increases (that can be defined as spontaneous activity) in the BOLD signals of the PVA occurred. Through examining the neural network that was associated with the emergence of spontaneous activity in the PVA, we found that such spontaneous activity may partially reflect memory-related mental imagery and/or the visual memory consolidation processes. The present study confirms the existence of spontaneous activity during the resting state and offers new evidence for the perspective that the brain is a system that can intrinsically operate on its own when there is no external stimulus.

Materials and Methods

Subjects

This study was approved by the medical research ethics committee of Xuanwu Hospital of Capital University of Medical Sciences, and all participants gave written, informed consent prior to taking part in the study. Twenty-five right-handed, normal-sighted subjects (11 males and 14 females; mean age, 23.5 years; range, 19–30 years) participated in our study. All participants had normal brain anatomy and no known neurological abnormalities.

Data Acquisition

The images were scanned on a 3.0 Tesla Siemens MR system. During data acquisition, the subjects were instructed to keep their eyes closed, relax their minds, and move as little as possible. More importantly, all participants were asked to keep awake during their examinations. A foam pad and headphones were used to reduce head motion and scanner noise. BOLD images of the entire brain were acquired in 32 axial slices using an echo-planar imaging (EPI) sequence (time repetition/time echo [TR/TE] = 2000/30 ms, flip angle = 90°, field of view = 22 cm, matrix = 64 × 64, thickness = 3 mm, gap = 1 mm). The fMRI scanning lasted for 9 min. Other images not used in the present study are not described here.

Data Preprocessing

All preprocessing steps were carried out using statistical parametric mapping (SPM2, http://www.fil.ion.ucl.ac.uk/spm/). Because of the instability of the initial signals and to allow for the subjects' adaptation to the situation, the first 10 images were discarded. The remaining images were first corrected for within-scan acquisition time differences between slices and then realigned to the first volume to correct for interscan head motions. Next, we spatially normalized the realigned images to the standard EPI template and resampled them to a voxel size of 3 × 3 × 3 mm3. Subsequently, the functional images were spatially smoothed with a Gaussian kernel of 4 × 4 × 4 mm3 FWHW to decrease spatial noise.

Definition of ROI

We chose the Brodmann's area (BA) 17 as the ROI. This procedure was performed using the WFU_PickAtlas free software (http://www.ansir.wfubmc.edu) (Maldjian et al. 2003). After the ROI of BA 17 (both left and right hemisphere) was selected from the BA atlas, the ROI image was normalized to the standard EPI template and resampled to a voxel size of 3 × 3 × 3 mm3 to obtain a new ROI image with the same spatial resolution as the preprocessed fMRI images.

Identification of the Pattern of Spontaneous Activity in the ROI

Hunter et al. (2005) proposed a method for estimating the level of activity in speech-sensitive auditory regions in the control state of a task paradigm. In this study, we used a similar procedure to identify the pattern of spontaneous activity in the PVA during the resting state. To guarantee the independence of each time point, we used 52 time points out of the total 260 time points, with an interval of 5 × 2 s = 10 s. For these 52 time points, the following procedure was performed for the ROI of each subject, based on both the height and spatial extent of signal changes:

  1. For each voxel, the Z value was calculated at each time point: 

    graphic
    where x (t) is the signal value at the time point t, t = 1, 2, 3, …, 52 and SD is the standard deviation.

  2. At every time point, the number of voxels with Z > 2 was calculated. Then the time points were sorted in descending order according to the number of voxels with Z > 2.

  3. If the number of voxels with Z > 2 at the first ranked time point exceeded 2.5% of the total voxel number in the ROI (i.e., exceeded the Gaussian assumptions), this time point was defined as spontaneously activated time point (“Spon-TP”).

  4. If the number of voxels with Z > 2 at the second ranked time point exceeded 2.5% of the total voxel number in the ROI, this time point was also defined as Spon-TP.

  5. Other time points had to satisfy 2 criteria in order to be considered as Spon-TPs:

    • (i) The number of voxels with Z > 2 at this time point exceeded 2.5% of the total voxel number in the ROI.

    • (ii) A large proportion (more than 30%) of the voxels with Z > 2 at this time point must have appeared in the set of voxels with Z > 2 at higher ranked time points that have been defined as Spon-TPs. We added this criterion to avoid misinterpreting noise as spontaneous activations.

After detecting each of the spontaneously activated time point, we obtained a pattern of spontaneous activity in the PVA of each subject. This pattern defined the time points of spontaneous activity (Spon-TPs) and the time points associated with a lack of such activity (“Remain-TPs”). A schematic representation of the pattern in a single subject can be seen in Figure 1.

Figure 1.

Schematic representation of the pattern of spontaneous activity in the PVA. Data presented is from a randomly selected subject. (A) At every time point (abscissa) during the resting state, the ordinate shows the percentage of Z > 2 voxels. The dashed line represents the spatial extent threshold (2.5%, corresponding to P = 0.025). The time points labeled by dots are those in which spontaneous activity occurred. It should be noted that, according to the identification procedure we used in the present study, not all of the time points with percentage of Z > 2 voxels exceeding the 2.5% threshold (exceed the Gaussian assumption) will be taken as spontaneous activated time points. (B and C) The translation and rotation parameters of the subject's head motion. The subject had very few head motions during the scanning procedure (less than 0.5 mm translations and less than 0.5° rotations), and the subject's motion amplitudes had no significant correlations (P > 0.1) with the number of voxels satisfying Z > 2 at each time point (correlation coefficient = 0.18, −0.03, −0.21 for the x, y, z translations, respectively, and correlation coefficient = 0.08, 0.01, 0.09 for the rotations in the 3 axes, respectively).

Figure 1.

Schematic representation of the pattern of spontaneous activity in the PVA. Data presented is from a randomly selected subject. (A) At every time point (abscissa) during the resting state, the ordinate shows the percentage of Z > 2 voxels. The dashed line represents the spatial extent threshold (2.5%, corresponding to P = 0.025). The time points labeled by dots are those in which spontaneous activity occurred. It should be noted that, according to the identification procedure we used in the present study, not all of the time points with percentage of Z > 2 voxels exceeding the 2.5% threshold (exceed the Gaussian assumption) will be taken as spontaneous activated time points. (B and C) The translation and rotation parameters of the subject's head motion. The subject had very few head motions during the scanning procedure (less than 0.5 mm translations and less than 0.5° rotations), and the subject's motion amplitudes had no significant correlations (P > 0.1) with the number of voxels satisfying Z > 2 at each time point (correlation coefficient = 0.18, −0.03, −0.21 for the x, y, z translations, respectively, and correlation coefficient = 0.08, 0.01, 0.09 for the rotations in the 3 axes, respectively).

Identification of the Neural Network Associated with the Spontaneous Activity in the PVA

The next procedures were also carried out using SPM2 (http://www.fil.ion.ucl.ac.uk/spm/). For each subject, the images of Spon-TPs and images of Remain-TPs were entered into a first-level 2-sample t-test. This procedure obtained an effect of interest (Spon-TPs vs. Remain-TPs) on a voxel-by-voxel basis throughout the entire brain of each subject. Next, the contrast images (Con*.img) of each subject derived from the preceding first-level analysis were entered into a random effect 1-sample 2-tailed t-test to detect the brain regions that were associated with PVA-related spontaneous activity at the group level.

Results

To exclude the possibility that the spontaneous activity that we had detected might be influenced by system noise, we also detected the time points that satisfied Z > 2 in the whole-brain mean signals of each subject. We discarded the data of 3 subjects who had more than one spontaneous activated time points (Spon-TPs) satisfying Z > 2 in the mean signals of the whole brain. In the remaining subjects, there was no significant difference between the Spon-TPs and the Remain-TPs (P > 0.25) in the mean signals of the whole brain. In addition, to exclude another possibility that the detected spontaneous activity was influenced by the spurious activations due to the subject's movement during the scanning session, we also examined the correlations between the patterns of the spontaneous activity and the head motion parameters acquired during the process of motion correction. In fact, none of the 22 subjects had greater than 1 mm maximum displacement in any of the x, y, z directions or greater than 1° of angular rotation in the 3 axes. This strict criterion insured that subjects' movement could not have a great effect on the results. As shown in Figure 1, for the given subject, the percentage of voxels satisfying Z > 2 at each time point (Fig. 1A) had no significant correlations with the subject's head motion parameters (Fig. 1B, C). To obtain further assurance on this issue, we also evaluated the following 2 correlations: 1) the correlation between the head motion amplitudes (HMA) (based on the method initiated by Jiang et al. 1995) of the 22 subjects and the number of their Spon-TPs; 2) the correlation between the HMA and the number of their spontaneously activated voxels (“Spon-Voxels”) at these Spon-TPs. As shown in the Figure 2, no significant correlations between the HMA and the patterns of spontaneous activity (r = 0.083, P = 0.71 for HMA vs. Spon-TPs; and r = −0.006, P = 0.97 for HMA vs. Spon-Voxels) were found. All the above results suggest that the spontaneous activity that we have detected was not greatly influenced by the subjects' head motions or system noise.

Figure 2.

(A) Correlation between the amplitudes of subjects' head motions and the subjects' number of spontaneously activated time points (Spon-TPs). (B) Correlation between the amplitudes of subjects' head motion and the subjects' mean number of spontaneously activated voxels (Spon-voxels) at those Spon-TPs.

Figure 2.

(A) Correlation between the amplitudes of subjects' head motions and the subjects' number of spontaneously activated time points (Spon-TPs). (B) Correlation between the amplitudes of subjects' head motion and the subjects' mean number of spontaneously activated voxels (Spon-voxels) at those Spon-TPs.

Temporal Domain Properties of PVA Spontaneous Activity

In the PVA of each subject that remained after 3 subjects were excluded, Spon-TPs could be detected during the resting state with eyes closed. A schematic representation of the pattern of spontaneous activity in a randomly selected subject can be seen in Figure 1. At certain time points, a large proportion (even >40%) of voxels in the PVA demonstrated significantly increased (Z > 2) activity. As shown in Table 1, at the group level, we detected about 6 Spon-TPs, which are more than 10% of the overall resting-state time points.

Table 1

Characteristics of the spontaneous activity in the PVA of NS subjects during the resting state

Characteristics NS (n = 22) 
Temporal domain  
    Total time points 52 
    Mean ± SD, Spon-TPs 5.5 ± 2.0 
    Mean ± SD (percentage of total time points) 10.6 ± 3.9 % 
Spatial domain  
    Total voxels in the PVA 213 
    Mean ± SD, expected voxels with Z > 2 5.3 ± 3.3 
    Mean ± SD, observed voxels with Z > 2 32.6 ± 12.3 
    Mean ± SD (percentage of total voxels) 15.3 ± 5.8 % 
Characteristics NS (n = 22) 
Temporal domain  
    Total time points 52 
    Mean ± SD, Spon-TPs 5.5 ± 2.0 
    Mean ± SD (percentage of total time points) 10.6 ± 3.9 % 
Spatial domain  
    Total voxels in the PVA 213 
    Mean ± SD, expected voxels with Z > 2 5.3 ± 3.3 
    Mean ± SD, observed voxels with Z > 2 32.6 ± 12.3 
    Mean ± SD (percentage of total voxels) 15.3 ± 5.8 % 

Note: The expected number of voxels satisfying Z > 2 has been corrected for the effect arising from the spatial smoothing based on the results of Worsley et al. (1995). NS, normal sighted.

Spatial Domain Properties of PVA Spontaneous Activity

The ROI of the PVA consisted of 213 voxels. According to Gaussian assumptions, the expected number (mean ± SD) of voxels with Z > 2 could be estimated to be about 5.3 ± 3.3 (corrected for spatial smoothing based on the results of Worsley et al. 1995). As shown in the Table 1, the mean number of voxels with Z > 2 in the PVA at spontaneously activated time points was 32.6 ± 12.3 (about 15.3 ± 5.8 [%] of the overall voxels in the ROI). This number obviously exceeded the expectation level (2.5%) and therefore suggested that these spontaneous activations were not random but associated with an underlying mechanism.

Neural Network Associated with PVA Spontaneous Activity

At the group level, we found that some brain regions had a similar activity pattern (Spon-TPs > Remain-TPs) with that of spontaneous activity in the PVA, and no region showed an opposite pattern (Spon-TPs < Remain-TPs). The neural network associated with PVA spontaneous activity consisted of 3 parts: 1) the bilateral visual areas including the middle occipital gyrus, cuneus, and lingual gyrus (BA 17/18/19), which also extended to the precuneus (BA 31/7); 2) the left precentral gyrus/middle frontal gyrus (BA 4/6) and right precentral gyrus/postcentral gyrus (BA 4/3); and 3) the bilateral temporal lobe including bilateral middle temporal gyrus (MTG; BA 20/21), bilateral fusiform gyrus (BA 20), left parahippocampal gyrus and right inferior temporal gyrus (ITG; BA 20/21). More details of the regions in the neural network can be seen in Table 2 and the representations in Figures 3 and 4.

Figure 3.

External view of the neural network associated with spontaneous activity in the PVA at the group level (P < 0.000005, cluster size > 50 voxels).

Figure 3.

External view of the neural network associated with spontaneous activity in the PVA at the group level (P < 0.000005, cluster size > 50 voxels).

Figure 4.

Brain regions located in the neural network associated with spontaneous activity in the PVA at the group level (P < 0.000005, cluster size > 50 voxels). See Table 2 for details of Talairach coordinates.

Figure 4.

Brain regions located in the neural network associated with spontaneous activity in the PVA at the group level (P < 0.000005, cluster size > 50 voxels). See Table 2 for details of Talairach coordinates.

Table 2

The foci of brain areas located in the neural network associated with the PVA-related spontaneous activity during the resting state

Region Hem CS (voxels) BA (x, y, zt-score 
Middle occipital gyrus/Cuneus/Lingual gyrus/Precuneus 1204 17/18/19/31/7 (−21, −84, 4) 13.93 
    (−24, −72, 12) 13.42 
Middle occipital gyrus/cuneus/lingual gyrus/precuneus 1471 17/18/19/31 (3, −87, 2) 12.2 
      
Precentral gyrus/middle frontal gyrus 257 4/6 (−30, −26, 54) 11.09 
    (−12, −6, 50) 10.69 
Precentral gyrus/postcentral gyrus 126 4/3 (27, −29, 54) 10.32 
    (36, −21, 45) 9.73 
MTG/fusiform gyrus/parahippocampal gyrus 176 20/21/38 (−56, −18, −9) 10.36 
    (−36, −4, −27) 10.34 
ITG/MTG/fusiform gyrus 100 20/21 (50, −6, −12) 11.02 
    (41, −13, −22) 9.61 
    (50, −16, −27) 9.43 
Region Hem CS (voxels) BA (x, y, zt-score 
Middle occipital gyrus/Cuneus/Lingual gyrus/Precuneus 1204 17/18/19/31/7 (−21, −84, 4) 13.93 
    (−24, −72, 12) 13.42 
Middle occipital gyrus/cuneus/lingual gyrus/precuneus 1471 17/18/19/31 (3, −87, 2) 12.2 
      
Precentral gyrus/middle frontal gyrus 257 4/6 (−30, −26, 54) 11.09 
    (−12, −6, 50) 10.69 
Precentral gyrus/postcentral gyrus 126 4/3 (27, −29, 54) 10.32 
    (36, −21, 45) 9.73 
MTG/fusiform gyrus/parahippocampal gyrus 176 20/21/38 (−56, −18, −9) 10.36 
    (−36, −4, −27) 10.34 
ITG/MTG/fusiform gyrus 100 20/21 (50, −6, −12) 11.02 
    (41, −13, −22) 9.61 
    (50, −16, −27) 9.43 

Note: CS, cluster size; Hem, hemisphere; (x, y, z), coordinates of primary peak locations in the space of Talairach (Talairach and Tournoux 1988). P < 0.000005, CS > 50 voxels.

Discussion

This study showed that there were intermittent episodes of strikingly increased activity in the PVAs when subjects were in the resting state with their eyes closed. The strikingly increased activity, which exceeds the statistical definition of activation used in the analysis of fMRI data, can be defined as spontaneous activity (Hunter et al. 2005). In each subject, there was spontaneous activity in the PVA, and the spontaneous activity was nonrandom in that they were distinctly clustered both temporally and spatially. At the group level, about 6 time points (more than 10% of the total number) showed spontaneous activity and these spontaneously activated time points involved an average of 33 voxels (about 15% of the total number of voxels) in the PVA, which greatly exceeded the statistically expected frequencies. This phenomenon suggests that during the resting state, the PVA of human beings is not “silent” but still has spontaneous activity that may be associated with certain mental processes.

Our results showed that activity of bilateral middle occipital gyrus, bilateral cuneus, bilateral lingual gyrus, and bilateral precuneus were associated with spontaneous activity in the PVA. We suggest that the activity may be related to visual imagery processes for the following reasons: one is that the PVA and the occipitoparietal and occipitotemporal visual association areas have been found to be activated by visual imagery tasks (Kosslyn et al. 1993, 1995, 1999; Le Bihan et al. 1993; Roland and Gulyas 1994; Mellet et al. 1996, 1998; D'Esposito et al. 1997; Ishai et al. 2000; Lambert et al. 2004) and the other is that previous studies have suggested that the precuneus is a critical node of the neural substrate of visual imagery occurring in memory recall (Buckner et al. 1995; Fletcher et al. 1995; Halsband et al. 1998; Henson et al. 1999; Ishai et al. 2000; Lambert et al. 2004). Therefore, the presence of spontaneous activity in the occipital visual areas and the precuneus could indicate that visual imagery is an important mental process during the resting state.

Our result also showed that some frontal/parietal regions including the precentral/postcentral gyrus and middle frontal gyrus were associated with spontaneous activity in the PVA. Similar results have been reported by Nir et al. (2006), who found that fluctuations in resting BOLD signals of the occipital visual areas were highly correlated with those of the precentral gyrus and the postcentral gyrus. The occipital visual areas and frontal/parietal sensorimotor areas have been found to be jointly activated during mental imagery tasks (Mellet et al. 1996, 1998; Mazard et al. 2002, 2005). In addition, previous studies have suggested that these regions in the sensorimotor systems mediate the early designation or refinement of the search criteria for a target object in the memory, and this is an important procedure of the mental imagery processes (Kraut et al. 2002, 2003; Assaf et al. 2006). Therefore, the involvement of sensorimotor systems also suggests that such PVA-related spontaneous activity is associated with mental imagery processes during the resting state.

Two other clusters, which included the bilateral MTG, bilateral fusiform gyrus, right ITG and left parahippocampal gyrus, were located in the temporal lobe. These findings have been supported by many previous studies, which reported activity in the temporal lobe during the resting state (Binder et al. 1999; Stark and Squire 2001; Christoff et al. 2004). As proposed by Christoff et al. (2004), the recruitment of the temporal lobe regions during the resting state suggests that memory processes form the core of spontaneous thought. Previous studies have also suggested the temporal lobe as the memory storehouse for visual representations of complex stimuli (Miyashita 1988; Miyashita and Chang 1988), and the MTG/ITG play a role in integrating different types of information about complex objects, both within and across modalities (visual, auditory, or sensorimotor) (Beauchamp et al. 2004). During mental imagery, the participants retrieve objects from memory through integrating features from multiple cognitive systems. This concept could explain the involvement of the MTG/ITG in the present study. The fusiform gyrus has been widely found to be activated by the perception of faces and other categories of objects (Haxby et al. 1994, 2001; Kanwisher et al. 1997; Chao et al. 1999; Ishai et al. 1999; Sperling et al. 2001). In fact, the neural activations in the fusiform gyrus could also be modulated by visual imagery (Ishai et al. 2000, 2002; O'Craven and Kanwisher 2000), which could partially explain why spontaneous activity in the fusiform gyrus is associated with those in the occipital visual areas.

In addition, our results showed that the parahippocampal gyrus was also involved in the neural network associated with spontaneous activity in the visual system. The involvement of the parahippocampal gyrus may still reflect a memory-related visual imagery process as the parahippocampal gyrus is part of the medial temporal lobe that plays an important role in the memory mechanisms of human beings (Squire et al. 2004). In addition, previous studies have also suggested that the ITG (BA 20, also called the area TE) is a site for long-term visual memory storage and the medial temporal lobe works in conjunction with the ITG to establish long-term visual memory (Mishkin 1982; Miyashita 1993). Therefore, the coactivity in the ITG and the parahippocampal gyrus may also be associated with visual memory-storage mechanisms. In fact, previous studies have indicated that long-term memory is stored as an outcome of processing and in the same regions of the neocortex that are specialized for remembering information (Mishkin 1982; Squire 1987). During the processing period, the medial temporal lobe initially works together with the neocortex to allow the memory to be encoded (Hasselmo and McClelland 1999; Squire et al. 2004). In this view, the synchronous spontaneous activity in the visual system and the medial temporal lobe may also imply a visual memory consolidation process during the resting state.

Based on all of above pieces of evidence, our results suggest that the PVA-related spontaneous activity may involve the memory-related mental imagery processes and/or the mechanism of replaying previous information for visual memory consolidation, during which complex information was represented and retrieved from memory as mental images. This is consistent with previous suggestions of the presence of long-term memory, mental imagery, and introspective evaluative processes in the absence of tasks (Kosslyn et al. 1995; Stark and Squire 2001; Christoff et al. 2004) and is also consistent with our daily experience that when we close our eyes, some memory-related scenes are still displayed in our “mind's eye.”

A recent study by Nir et al. (2006) has also found that fluctuations of BOLD signals in the visual areas synchronously changed during the resting state, which is consistent with our present results. However, after comparing the correlation patterns of some high-level visual areas during the resting state and during a navigation imagery task, they suggested that mental imagery may not be the underlying source of these spontaneous fluctuations. It should be noted that the physiological processes during the resting state are mainly subconscious ones, which may even be a mixture of many specific physiological processes. It is reasonable that the activity pattern of such processes is different from that of a specific experimental task. Therefore, the results by Nir et al. (2006) may not totally exclude the possibility that mental imagery is one of the candidate processes underlying the spontaneous fluctuations in the visual system. In fact, the presence of visual imagery in the absence of tasks has been widely reported by previous studies (Antrobus and Singer 1964; Antrobus et al. 1970; Singer and Antrobus 1972; Giambra 1995). Kosslyn et al. (1995) also found that the activation of visual imagery tasks was obscured when a resting baseline was used, due to the presence of rest-related mental imagery. Of course, the memory-related mental imagery is not the only possible process underlying the spontaneous activity in the visual system. As indicated in the above discussion, replaying previously acquired information for visual memory consolidation may also be a candidate process underlying the spontaneous activity. This conclusion is consistent with the suggestions of Nir et al. (2006).

As a whole, the present study confirms the existence of spontaneous activity in the human brain during the resting state. This could be considered to be an extension of the previous pioneering study by Kenet et al. (2003). Using voltage-sensitive dye imaging, Kenet et al. (2003) found that the primary visual cortex of anesthetized cat encompasses a set of dynamically switching cortical states. By using resting-state fMRI, the present study indicated that the PVA of the human brain during the resting state shows episodic spontaneous activity, which is clustered both temporally and spatially. By comparing these spontaneously appearing cortical states with those that corresponded to certain visual stimuli, Kenet et al. (2003) found that these spontaneous cortical states resembled the so-called orientation maps that were produced in the cat cortex by looking at oriented stimulus. By investigating the neural network that is associated with spontaneous activity in PVA, the present study also suggests that the spontaneous activity in the conscious resting human brain is not random but rather may be involved in certain mental processes (in which memory-related mental imagery processes and visual memory consolidation processes may be involved). The present finding that spontaneous activity associated with certain mental processes also exists in the PVA of waking human beings may give us an opportunity to analyze the context within which the visual perception occurs and to further investigate how the spontaneous activity interacts with external stimuli to produce behavioral responses (Kenet et al. 2003; Ringach 2003).

Conclusions

In summary, this study provided quantitative evidence for the existence of spontaneous activity in the PVAs of human beings during the resting state. We also found that there was a neural network that was associated with the emergence of spontaneous activity in the PVA. Although the precise mental processes supported by such a neural network remain to be elucidated, our results suggest that memory-related mental imagery and visual memory consolidation processes may be candidates. By investigating spontaneous activity without any external stimulus, our study may offer a new perspective for exploring the visual perception and other brain processing. In addition, the phenomenon that PVA has spontaneous activity without any stimulus offers new evidence for the perspective that the brain is a system intrinsically operating on its own and sensory information interacts with rather than determines the operation of the system.

Funding

This work was partially supported by the Natural Science Foundation of China, grant nos. 30425004, 60121302 and 30670601; the National Key Basic Research and Development Program (973), grant no. 2004CB318107; and Beijing Scientific and Technological New Star Program, grant no. 2005B21.

The authors express appreciation to Dr Keith J. Worsley for his helpful comments on this work. The authors also wish to thank Drs. Rhoda E. Perozzi and Edmund F. Perozzi for English language and editing assistance. Conflict of Interest: None declared.

References

Antrobus
JS
Singer
JL
Eye movements accompanying daydreaming, visual imagery, and thought suppression
J Abnorm Psychol
 , 
1964
, vol. 
69
 (pg. 
244
-
252
)
Antrobus
JS
Singer
JL
Goldstein
S
Fortgang
M
Mindwandering and cognitive structure
Trans NY Acad Sci
 , 
1970
, vol. 
32
 (pg. 
242
-
252
)
Arieli
A
Shoham
D
Hildesheim
R
Grinvald
A
Coherent spatiotemporal patterns of ongoing activity revealed by real-time optical imaging with single-unit recording in the cat visual cortex
J Neurophysiol
 , 
1995
, vol. 
73
 (pg. 
2072
-
2093
)
Arieli
A
Sterkin
A
Grinvald
A
Aerstent
A
Dynamics of ongoing activity: explanation of the large variability in evoked cortical response
Science
 , 
1996
, vol. 
273
 (pg. 
1868
-
1871
)
Assaf
M
Calhoun
VD
Kuzu
CH
Kraut
MA
Rivkin
PR
Hart
JJ
Pearlson
GD
Neural correlates of the object-recall process in semantic memory
Psychiatry Res
 , 
2006
, vol. 
147
 (pg. 
115
-
126
)
Beauchamp
MS
Lee
KE
Argall
BD
Martin
A
Integration of auditory and visual information about objects in superior temporal sulcus
Neuron
 , 
2004
, vol. 
41
 (pg. 
809
-
823
)
Bertolo
H
Visual imagery without visual perception?
Psicologica
 , 
2005
, vol. 
26
 (pg. 
173
-
188
)
Binder
JR
Frost
JA
Hammeke
TA
Bellgowan
PS
Rao
SM
Cox
RW
Conceptual processing during the conscious resting state. A functional MRI study
J Cogn Neurosci
 , 
1999
, vol. 
11
 (pg. 
80
-
95
)
Biswal
B
Yetkin
FZ
Haughton
VM
Hyde
JS
Functional connectivity in the motor cortex of resting human brain using echo-planar MRI
Magn Reson Med
 , 
1995
, vol. 
34
 (pg. 
537
-
541
)
Buckner
RL
Petersen
SE
Ojemann
JG
Miezin
FM
Squire
LR
Raichle
ME
Functional anatomic studies of explicit and implicit memory retrieval tasks
J Neurosci
 , 
1995
, vol. 
15
 (pg. 
12
-
29
)
Chao
LL
Haxby
JV
Martin
A
Attribute-based neural substrates in temporal cortex for perceiving and knowing about objects
Nat Neurosci
 , 
1999
, vol. 
2
 (pg. 
913
-
919
)
Christoff
K
Ream
JM
Gabrieli
JDE
Neural basis of spontaneous thought processes
Cortex
 , 
2004
, vol. 
40
 (pg. 
623
-
630
)
Clark
DD
Sokoloff
L
Siegel
GJ
Agranoff
BW
Albers
RW
Fisher
SK
Uhler
MD
Circulation and energy metabolism of the brain
Basic neuro-chemistry: molecular, cellular and medical aspects, 6th ed
 , 
1999
Philadelphia
Lippincott-Raven
(pg. 
637
-
670
)
Cordes
D
Haughton
V
Arfanakis
K
Carew
JD
Turski
PA
Moritz
CH
Quigley
MA
Meyerand
ME
Frequencies contributing to functional connectivity in the cerebral cortex in “resting-state” data
Am J Neuroradiol
 , 
2001
, vol. 
22
 (pg. 
1326
-
1333
)
D'Esposito
M
Deter
JA
Aguirre
GK
Stallcup
M
Alsop
DC
Tippet
LJ
Farah
MJ
A functional MRI study of mental image generation
Neuropsychologia
 , 
1997
, vol. 
35
 (pg. 
725
-
730
)
Fiser
J
Chiu
C
Weliky
M
Small modulation of ongoing cortical dynamics by sensory input during natural vision
Nature
 , 
2004
, vol. 
431
 (pg. 
573
-
578
)
Fletcher
PC
Frith
CD
Baker
SC
Shallice
T
Frackowiak
RS
Dolan
RJ
The mind's eye—precuneus activation in memory–related imagery
NeuroImage
 , 
1995
, vol. 
2
 (pg. 
195
-
200
)
Fox
MD
Snyder
AZ
Vincent
JL
Corbetta
M
Van Essen
DC
Raichle
ME
The human brain is intrinsically organized into dynamic, anticorrelated functional networks
Proc Natl Acad Sci USA
 , 
2005
, vol. 
102
 (pg. 
9673
-
9678
)
Fox
PT
Burton
H
Raichle
ME
Mapping human somatosensory cortex with positron emission tomography
J Neurosurg
 , 
1987
, vol. 
67
 (pg. 
34
-
43
)
Fox
PT
Fox
JM
Raichle
ME
Burde
RM
The role of cerebral cortex in the generation of voluntary saccades: a positron emission tomographic study
J Neurophysiol
 , 
1985
, vol. 
54
 (pg. 
348
-
369
)
Friston
KJ
Frith
CD
Liddle
PF
Dolan
RJ
Lammertsma
AA
Frackowiak
RS
The relationship between global and local changes in PET scans
J Cereb Blood Flow Metab
 , 
1990
, vol. 
10
 (pg. 
458
-
466
)
Giambra
LM
A laboratory method for investigating influences on switching attention to task-unrelated imagery and thought
Conscious Cogn
 , 
1995
, vol. 
4
 (pg. 
1
-
21
)
Greicius
MD
Krasnow
B
Reiss
AL
Menon
V
Functional connectivity in the resting brain: a network analysis of the default mode hypothesis
Proc Natl Acad Sci USA
 , 
2003
, vol. 
100
 (pg. 
253
-
258
)
Gusnard
DA
Raichle
ME
Searching for a baseline: functional imaging and the resting human brain
Nat Rev Neurosci
 , 
2001
, vol. 
2
 (pg. 
685
-
694
)
Halsband
U
Krause
BJ
Schmidt
D
Herzog
H
Tellman
L
Muller-Gartner
HW
Encoding and retrieval in declarative learning: a positron emission tomography study
Behav Brain Res
 , 
1998
, vol. 
97
 (pg. 
69
-
78
)
Hampson
M
Peterson
BS
Skudlarski
P
Gatenby
JC
Gore
JC
Detection of functional connectivity using temporal correlations in MR images
Hum Brain Mapp
 , 
2002
, vol. 
15
 (pg. 
247
-
262
)
Hasselmo
ME
McClelland
JL
Neural models of memory
Curr Opin Neurobiol
 , 
1999
, vol. 
9
 (pg. 
184
-
188
)
Haxby
JV
Gobbini
MI
Furey
ML
Ishai
A
Schouten
JL
Pietrini
P
Distributed and overlapping representations of faces and objects in ventral temporal cortex
Science
 , 
2001
, vol. 
293
 (pg. 
2425
-
2430
)
Haxby
JV
Horwitz
B
Ungerleider
LG
Maisog
JM
Pietrini
P
Grady
CL
The functional organization of human extrastriate cortex: a PET-rCBF study of selective attention to faces and locations
J Neurosci
 , 
1994
, vol. 
14
 (pg. 
6336
-
6353
)
Henson
RN
Rugg
MD
Shallice
T
Josephs
O
Dolan
RJ
Recollection and familiarity in recognition memory: an event-related functional magnetic resonance imaging study
J Neurosci
 , 
1999
, vol. 
19
 (pg. 
3962
-
3972
)
Hunter
MD
Eickhoff
SB
Miller
TWR
Farrow
TFD
Wilkinson
ID
Woodruff
PWR
Neural activity in speech-sensitive auditory cortex during silence
Proc Natl Acad Sci USA
 , 
2005
, vol. 
103
 (pg. 
189
-
194
)
Ishai
A
Haxby
JV
Ungerleider
LG
Visual imagery of famous faces: effects of memory and attention revealed by fMRI
NeuroImage
 , 
2002
, vol. 
17
 (pg. 
1729
-
1741
)
Ishai
A
Sagi
D
Common mechanisms of visual imagery and perception
Science
 , 
1995
, vol. 
268
 (pg. 
1772
-
1774
)
Ishai
A
Sagi
D
Visual imagery facilitates visual perception: psychophysical evidence
J Cogn Neurosci
 , 
1997
, vol. 
9
 (pg. 
476
-
489
)
Ishai
A
Sagi
D
Visual imagery: effects of short- and long-term memory
J Cogn Neurosci
 , 
1997
, vol. 
9
 (pg. 
734
-
742
)
Ishai
A
Ungerleider
LG
Haxby
JV
Distributed neural systems for the generation of visual images
Neuron
 , 
2000
, vol. 
28
 (pg. 
979
-
990
)
Ishai
A
Ungerleider
LG
Martin
A
Schouten
JL
Haxby
JV
Distributed representation of objects in the human ventral visual pathway
Proc Natl Acad Sci USA
 , 
1999
, vol. 
96
 (pg. 
9379
-
9384
)
Jiang
A
Kennedy
DN
Baker
JR
Weisskoff
RM
Tootell
RB
Woods
RP
Benson
RR
Kwong
KK
Brady
TJ
Rosen
BR
, et al.  . 
Motion detection and correction in functional MR imaging
Hum Brain Mapp
 , 
1995
, vol. 
3
 (pg. 
224
-
235
)
Jiang
TZ
He
Y
Zang
YF
Weng
XC
Modulation of functional connectivity during the resting state and the motor task
Hum Brain Mapp
 , 
2004
, vol. 
22
 (pg. 
63
-
71
)
Kanwisher
N
McDermott
J
Chun
MM
The fusiform face area: a module in human extrastriate cortex specialized for face perception
J Neurosci
 , 
1997
, vol. 
17
 (pg. 
4302
-
4311
)
Kenet
T
Bibitchkov
D
Tsodyks
M
Grinvald
A
Arieli
A
Spontaneous emerging cortical representations of visual attributes
Nature
 , 
2003
, vol. 
425
 (pg. 
954
-
956
)
Kosslyn
SM
Alpert
NM
Thompson
WL
Maljkovic
V
Weise
SB
Chabris
CF
Hamilton
SE
Rauch
SL
Buonanno
FS
Visual mental imagery activates topographically organized visual cortex: PET investigations
J Cogn Neurosci
 , 
1993
, vol. 
5
 (pg. 
263
-
287
)
Kosslyn
SM
Ganis
G
Thompson
WL
Neural foundations of imagery
Nat Rev Neurosci
 , 
2001
, vol. 
2
 (pg. 
635
-
642
)
Kosslyn
SM
Pascual-Leone
A
Felician
O
Camposano
S
Kee-nan
JP
Thompson
WL
Ganis
G
Sukel
KE
Alpert
NM
The role of area 17 in visual imagery: convergent evidence from PET and rTMS
Science
 , 
1999
, vol. 
284
 (pg. 
167
-
170
)
Kosslyn
SM
Thompson
WL
Kim
IJ
Alpert
NM
Topographical representations of mental images in primary visual cortex
Nature
 , 
1995
, vol. 
378
 (pg. 
496
-
498
)
Kraut
MA
Calhoun
V
Pitcock
JA
Cusick
C
Jr
Hart J
Neural hybrid model of semantic object memory: implications from event-related timing using fMRI
J Int Neuropsych Soc
 , 
2003
, vol. 
9
 (pg. 
1031
-
1040
)
Kraut
MA
Kremen
S
Moo
LR
Segal
JB
Calhoun
V
Jr
Hart J
Object activation in semantic memory from visual multimodal feature input
J Cogn Neurosci
 , 
2002
, vol. 
14
 (pg. 
37
-
47
)
Lambert
S
Sampaio
E
Mauss
Y
Scheiber
C
Blindness and brain plasticity: contribution of mental imagery? An fMRI study
Cogn Brain Res
 , 
2004
, vol. 
20
 (pg. 
1
-
11
)
Le Bihan
D
Turner
R
Zeffiro
T
Cuendo
C
Jezzard
P
Bonnerot
V
Activation of human primary visual cortex during visual recall: a magnetic resonance imaging study
Proc Natl Acad Sci USA
 , 
1993
, vol. 
90
 (pg. 
11802
-
11805
)
Llinas
R
The intrinsic electrophysiological properties of mammalian neurons: insights into central nervous system function
Science
 , 
1988
, vol. 
242
 (pg. 
1654
-
1664
)
Lowe
MJ
Mock
BJ
Sorenson
JA
Functional connectivity in single and multislice echoplanar imaging using resting state fluctuations
NeuroImage
 , 
1998
, vol. 
7
 (pg. 
119
-
132
)
MacLean
JN
Watson
BO
Aaron
GB
Yuste
R
Internal dynamics determine the cortical response to thalamic stimulation
Neuron
 , 
2005
, vol. 
48
 (pg. 
811
-
823
)
Madsen
PL
Hasselbalch
SG
Hagemann
LP
Olsen
KS
Bulow
J
Holm
S
Wildschiodtz
G
Paulson
OB
Lassen
NA
Persistent resetting of the cerebral oxygen/glucose uptake ratio by brain activation: evidence obtained with the Kety-Schmidt technique
J Cereb Blood Flow Metab
 , 
1995
, vol. 
15
 (pg. 
485
-
491
)
Maldjian
JA
Laurienti
PJ
Kraft
RA
Burdette
JH
An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets
NeuroImage
 , 
2003
, vol. 
19
 (pg. 
1233
-
1239
)
Mazard
A
Laou
L
Joliot
M
Mellet
E
Neural impact of the semantic content of visual mental images and visual percepts
Cogn Brain Res
 , 
2005
, vol. 
24
 (pg. 
423
-
435
)
Mazard
A
Mazoyer
B
Etard
O
Tzourio-Mazoyer
N
Kosslyn
SM
Mellet
E
Impact of fMRI acoustic noise on the functional anatomy of visual mental imagery
J Cogn Neurosci
 , 
2002
, vol. 
14
 (pg. 
172
-
186
)
Mellet
E
Petit
L
Mazoyer
B
Denis
M
Tzourio
N
Reopening the mental imagery debate: lessons from functional anatomy
NeuroImage
 , 
1998
, vol. 
8
 (pg. 
129
-
139
)
Mellet
E
Tzourio
N
Crivello
F
Joliot
M
Denis
M
Mazoyer
B
Functional anatomy of spatial mental imagery generated from verbal instructions
J Neurosci
 , 
1996
, vol. 
16
 (pg. 
6504
-
6512
)
Mishkin
M
A memory system in the monkey
Philos Trans R Soc Lond B Biol Sci
 , 
1982
, vol. 
298
 (pg. 
85
-
92
)
Miyashita
Y
Neural correlate of visual associative long-term memory in the primate temporal cortex
Nature
 , 
1988
, vol. 
335
 (pg. 
817
-
820
)
Miyashita
Y
Inferior temporal cortex: where visual perception meets memory
Ann Rev Neurosci
 , 
1993
, vol. 
16
 (pg. 
245
-
263
)
Miyashita
Y
Chang
HS
Neural correlate of pictorial short-term memory in the primate temporal cortex
Nature
 , 
1988
, vol. 
331
 (pg. 
68
-
70
)
Nir
Y
Hasson
U
Levy
I
Yeshurun
Y
Malach
R
Widespread functional connectivity and fMRI fluctuations in human cortex in the absence of visual stimulation
NeuroImage
 , 
2006
, vol. 
30
 (pg. 
1313
-
1324
)
O'Craven
KM
Kanwisher
N
Mental imagery of faces and places activates corresponding stimulus-specific brain regions
J Cogn Neurosci
 , 
2000
, vol. 
12
 (pg. 
1013
-
1023
)
Olshausen
BA
Field
DJ
How close are we to understanding V1?
Neural Comput
 , 
2005
, vol. 
17
 (pg. 
1665
-
1699
)
Raichle
ME
Gusnard
DA
Intrinsic brain activity sets the stage for expression of motivated behavior
J Comp Neurol
 , 
2005
, vol. 
493
 (pg. 
167
-
176
)
Raichle
ME
Mintun
MA
Brain work and brain imaging
Annu Rev Neurosci
 , 
2006
, vol. 
29
 (pg. 
449
-
476
)
Ringach
DL
States of mind
Nature
 , 
2003
, vol. 
425
 (pg. 
912
-
913
)
Roland
PE
Eriksson
L
Stone-Elander
S
Widen
L
Does mental activity change the oxidative metabolism of the brain
J Neurosci
 , 
1987
, vol. 
7
 (pg. 
2373
-
2389
)
Roland
PE
Gulyas
B
Visual imagery and visual representation
Trends Neurosci
 , 
1994
, vol. 
17
 (pg. 
281
-
287
)
Singer
JL
Antrobus
JS
Sheehan
PW
Daydreaming, imaginal processes and personality: a normative study
The function and nature of imagery
 , 
1972
New York
Academic Press
(pg. 
175
-
202
)
Sokoloff
L
Mangold
R
Wechsler
R
Kennedy
C
Kety
SS
The effect of mental arithmetic on cerebral circulation and metabolism
J Clin Invest
 , 
1955
, vol. 
34
 (pg. 
1101
-
1108
)
Sperling
RA
Bates
JF
Cocchiarella
AJ
Schacter
DL
Rosen
BR
Albert
MS
Encoding novel face–name associations: a functional MRI study
Hum Brain Mapp
 , 
2001
, vol. 
14
 (pg. 
129
-
139
)
Squire
LR
Memory and brain
1987
New York
Oxford University Press
Squire
LR
Stark
CE
Clark
RE
The medial temporal lobe
Annu Rev Neurosci
 , 
2004
, vol. 
27
 (pg. 
279
-
306
)
Stark
CE
Squire
LR
When zero is not zero: the problem of ambiguous baseline conditions in fMRI
Proc Natl Acad Sci USA
 , 
2001
, vol. 
98
 (pg. 
12760
-
12766
)
Stein
T
Moritz
C
Quigley
M
Cordes
D
Haughton
V
Meyerand
E
Functional connectivity in the thalamus and hippocampus studied with functional MR imaging
Am J Neuroradiol
 , 
2000
, vol. 
21
 (pg. 
1397
-
1401
)
Talairach
J
Tournoux
PA
Coplanar stereotactic atlas of the human brain
1988
Stuttgart
Thieme Verlag
Tsodyks
M
Kenet
T
Grinvald
A
Arieli
A
Linking spontaneous activity of single cortical neurons and underlying functional architecture
Science
 , 
1999
, vol. 
286
 (pg. 
1943
-
1946
)
Worsley
KJ
Poline
JB
Vandal
AC
Friston
KJ
Tests for distributed, non-focal brain activations
NeuroImage
 , 
1995
, vol. 
2
 (pg. 
183
-
194
)