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Cerebral Cortex Advance Access published online on June 29, 2007
Cerebral Cortex, doi:10.1093/cercor/bhm105
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© The Author 2007. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org

Spontaneous Activity Associated with Primary Visual Cortex: A Resting-State fMRI Study

Kun Wang1, Tianzi Jiang1, Chunshui Yu2, Lixia Tian1, Jun Li1, Yong Liu1, Yuan Zhou1, Lijuan Xu1, Ming Song1 and Kuncheng Li2

1 National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, People's Republic of China, 2 Department of Radiology, Xuanwu Hospital of Capital University of Medical Science, Beijing 100053, People's Republic of China

Address correspondence to email: jiangtz{at}nlpr.ia.ac.cn.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Funding
 References
 
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.

Key Words: fMRI • primary visual areas • resting state • spontaneous activity


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 Conclusions
 Funding
 References
 
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 2006Go). In adult humans, the brain accounts for about 2% of the body weight but consumes approximately 20% of the energy (Clark and Sokoloff 1999Go). 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. 1955Go; Fox et al. 1985Go, 1987Go; Roland et al. 1987Go; Friston et al. 1990Go; Madsen et al. 1995Go). 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 1988Go; Arieli et al. 1996Go; Gusnard and Raichle 2001Go; Kenet et al. 2003Go; Fiser et al. 2004Go; Maclean et al. 2005Go; Olshausen and Field 2005Go; Raichle and Gusnard 2005Go; Raichle and Mintun 2006Go). 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 2005Go; Raichle and Mintun 2006Go).

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. 2003Go). 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. 2003Go; Ringach 2003Go). 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. 1995Go; Lowe et al. 1998Go; Stein et al. 2000Go; Cordes et al. 2001Go; Hampson et al. 2002Go; Greicius et al. 2003Go; Jiang et al. 2004Go; Fox et al. 2005Go). This suggests that these spontaneous fluctuations could partially reflect the underlying spontaneous neuronal activity within specific systems (Biswal et al. 1995Go; Nir et al. 2006Go). 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)Go 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. 2004Go). According to earlier findings, visual imagery can activate brain areas that are similar to those activated during visual perception (Roland and Gulyas 1994Go; Ishai and Sagi 1995Go, 1997aGo, 1997bGo; Mellet et al. 1996Go, 1998Go; D'Esposito et al. 1997Go; Ishai et al. 2000Go). Although some previous studies have found the activations of the PVA during visual recall and visual imagery (Kosslyn et al. 1993Go, 1995Go, 1999Go; Le Bihan et al. 1993Go), there is still debate for the involvement of PVA in mental imagery processes (Kosslyn et al. 2001Go). 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 2005Go). 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. 1995Go, 1996Go; Tsodyks et al. 1999Go; Kenet et al. 2003Go). 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
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 Conclusions
 Funding
 References
 
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 x 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 x 3 x 3 mm3. Subsequently, the functional images were spatially smoothed with a Gaussian kernel of 4 x 4 x 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. 2003Go). 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 x 3 x 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)Go 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 x 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:

    Formula
    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
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  		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
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 Conclusions
 Funding
 References
 
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. 1995Go) 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
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  		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.


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  		Table 1 Characteristics of the spontaneous activity in the PVA of NS subjects during the resting state

 
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. 1995Go). 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
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  		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
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  		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.

 


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  		Table 2 The foci of brain areas located in the neural network associated with the PVA-related spontaneous activity during the resting state

 

   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
Conclusions
 Funding
 References
 
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. 2005Go). 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. 1993Go, 1995Go, 1999Go; Le Bihan et al. 1993Go; Roland and Gulyas 1994Go; Mellet et al. 1996Go, 1998Go; D'Esposito et al. 1997Go; Ishai et al. 2000Go; Lambert et al. 2004Go) 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. 1995Go; Fletcher et al. 1995Go; Halsband et al. 1998Go; Henson et al. 1999Go; Ishai et al. 2000Go; Lambert et al. 2004Go). 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)Go, 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. 1996Go, 1998Go; Mazard et al. 2002Go, 2005Go). 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. 2002Go, 2003Go; Assaf et al. 2006Go). 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. 1999Go; Stark and Squire 2001Go; Christoff et al. 2004Go). As proposed by Christoff et al. (2004)Go, 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 1988Go; Miyashita and Chang 1988Go), 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. 2004Go). 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. 1994Go, 2001Go; Kanwisher et al. 1997Go; Chao et al. 1999Go; Ishai et al. 1999Go; Sperling et al. 2001Go). In fact, the neural activations in the fusiform gyrus could also be modulated by visual imagery (Ishai et al. 2000Go, 2002Go; O'Craven and Kanwisher 2000Go), 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. 2004Go). 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 1982Go; Miyashita 1993Go). 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 1982Go; Squire 1987Go). During the processing period, the medial temporal lobe initially works together with the neocortex to allow the memory to be encoded (Hasselmo and McClelland 1999Go; Squire et al. 2004Go). 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. 1995Go; Stark and Squire 2001Go; Christoff et al. 2004Go) 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)Go 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)Go 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 1964Go; Antrobus et al. 1970Go; Singer and Antrobus 1972Go; Giambra 1995Go). Kosslyn et al. (1995)Go 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)Go.

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)Go. Using voltage-sensitive dye imaging, Kenet et al. (2003)Go 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)Go 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. 2003Go; Ringach 2003Go).


   Conclusions
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
Funding
 References
 
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
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Funding
References
 
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.


   Acknowledgments
 
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
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Funding
 References
 
Antrobus JS, Singer JL. Eye movements accompanying daydreaming, visual imagery, and thought suppression. J Abnorm Psychol (1964) 69:244–252.[CrossRef][Web of Science][Medline]

Antrobus JS, Singer JL, Goldstein S, Fortgang M. Mindwandering and cognitive structure. Trans NY Acad Sci (1970) 32:242–252.[Web of Science][Medline]

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) 73:2072–2093.[Abstract/Free Full Text]

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