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Rest related negative affect (RRNA) has gained scientific interest in the past decade. However, it is mostly studied within the context of mind-wandering (MW), and the relevance of other psychological and neural aspects of the resting state to its’ occurrence has never been studied. Several indications associate RRNA with internally directed attention, yet the nature of this relation remains largely unknown. Moreover, the role of neural networks associated with rest related phenomenology – the default mode (DMN), executive (EXE), and salience (SAL) networks, has not been studied in this context. To this end, we explored two 5 (baseline) and 15-minute resting-state simultaneous fMRI-EEG scans of 29 participants. As vigilance has been shown to affect attention, and thus its availability for inward allocation, EEG-based vigilance levels were computed for each participant. Questionnaires for affective assessment were administered before and after scans, and retrospective reports of MW were additionally collected. Results revealed increased negative affect following rest, but only among participants who retained high vigilance levels. Among low-vigilance participants, changes in negative affect were negligible, despite reports of MW occurrence in both groups. In addition, in the high-vigilance group only, a significant increase in functional connectivity (FC) levels was found between the DMN-related ventral anterior cingulate cortex (ACC), associated with emotional processing, and the EXE-related dorsal ACC, associated with monitoring of self and other’s behavior. These heightened FC levels further correlated with reported negative affect among this group. Taken together, these results demonstrate that, rather than an unavoidable outcome of the resting state, RRNA depends on internal allocation of attention at rest. Results are discussed in terms of two rest-related possible scenarios which defer in mental and neural processing, and subsequently, in the occurrence of RRNA.
Recent years in cognitive neuroscience have seen a major paradigm shift from emphasizing task related neural activity to exploring rest related neural and mental states. Within a relatively short period, a substantial body of findings led to the recognition that the study of the resting state is necessary for a more complete understanding of human psychological functioning and its underlying neural mechanisms. Within rest related cognition, most efforts have focused on studying mind-wandering (MW), which may be defined as ongoing mentation that occurs spontaneously, and largely autonomously, whenever an awake individual is either at rest or not fully concentrated during performance of a task (
Though most studies of rest-related mental functioning have focused on MW, a related psychological phenomenon that has been recurrently documented is rest related negative affect (RRNA). For instance,
To date, RRNA has mostly been studied in the context of MW. The exact relation between RRNA and MW is, however, a matter of debate. For instance,
Though direct empirical evidence is scarce, several indications exist for a potential role of the direction of attention inward in the ultimate occurrence of RRNA. For instance,
Based on what is known about rest-related neural mechanisms, several functional neural networks may be suggested to be of relevance to RRNA. The default-mode network (DMN), as well as the executive network (EXE), have both been reliably associated with resting state phenomenology (
The current study was designed to examine the conditions under which, during rest, RRNA occurs. Our hypothesis was that availability of attentional resources is a-priori condition for RRNA, and that low attentional resources during rest will be found to result in less negative affect. On the neural level, an exploratory approach was adopted in relation to regions of interest (ROIs) extracted from the default-mode, executive, and saliency networks. To pursue this goal, two simultaneous EEG-fMRI rest scans, a baseline 5-minute scan and a 15-minute rest scan, were collected from a group of healthy volunteers (
Twenty-nine participants (age: 33 ± 11; 12 females) took part in the study. All participants were healthy, with no neurologic or psychiatric history. Participants provided written informed consent approved by The Tel-Aviv Sourasky Medical Center ethical review board. fMRI data of one participant was discarded from analysis due to extensive head movements; the final fMRI analysis thus included 28 participants.
Prior to scanning, participants first filled out several behavioral questionnaires (specified below). Following, the EEG cap was fitted on their heads and they entered the MRI scanner. The fMRI scan included a 5-minute baseline rest session, a 4-minute masking auditory task and a 15-minute rest session in which high or low vigilance states were examined. The 15-minute rest scan, emphasized to participants as “the main part of the experiment,” was intended to allow a state of reduced vigilance, while the auditory task was used to create an even cognitive load among participants before entering this scan. All scans were performed with eyes closed and both rest scans (5 and 15-minute long scans) included instructions to “lie down and not do anything in particular.”
To allow close proximity of the second behavioral report to participants’ experience during the long rest scan, the later was always recorded last, right before participants exited the scanner. After exiting the scanner, participants were asked on their perceived level of vigilance and filled out questionnaires with the instruction to relate to the main part of the experiment. The study procedure is illustrated in
In order to evaluate the level of mental activity during the long rest scan without interrupting participants’ stream of consciousness we used an indirect measure of MW (
To capture change in negative affect following rest, the positive and negative affect scale (PANAS;
Imaging was performed on a 3T general electric (GE) Horizon echo speed scanner with a resonant gradient echo planar imaging system (GE, Milwaukee, WI, USA). All images were acquired using a standard head coil. The scanning session included functional T2*-weighted images (FOV = 200 mm, matrix size-64 × 64, voxel size-3 × 3 × 4, TR/TE = 2000/35, Slice thickness = 4 mm, 35 slices without gap, oriented according to the fourth ventricle, flip angle 90°) and a three-dimensional (3D) anatomical scan using T1 SPGR sequence (1 mm × 1 mm × 1 mm).
SPM5 software (
EEG data was recorded simultaneously with fMRI acquisition using the MRI compatible BrainAmp-MR EEG amplifier (Brain Products, Munich, Germany) and the electrode cap of BrainCap with sintered Ag/AgCl ring electrodes providing 32 channels: 30 EEG channels, 1 ECG, and 1 EOG channel (Falk Minow Services, Herrsching-Breitbrunn, Germany). The reference electrode was between Fz and Cz. Raw EEG was sampled at 5 kHz. Recording was done using the Brain Vision Recorder software (Brain Products, Munich, Germany).
EEG data underwent the same analysis steps as depicted in our previous work (
An increase in relative alpha (8–12 Hz) power in frontal electrodes is a known marker of decreased vigilance (
The pre-processed EEG data was segmented into consecutive 3 s parts and visually inspected for muscular artifacts, fMRI artifact residuals, and sleep spindles which would lead to participant exclusion. Noise contaminated segments were not taken into account in the analysis of the vigilance score and led to the exclusion of one participant due to excessive artifacts (in this case the vigilance classification was set to the “rest” group based on self report). Datasets were further re-referenced to an average electrode calculated as the mean of all 30 channels.
FFT was applied to four main channels (F3, F4, O1, and O2) which are critical in the vigilance assessment algorithm, producing the power in the alpha (8–12 Hz), theta (4–7 Hz), and upper delta (2–4 Hz) rhythms in each second. These power estimations were averaged across 3 s and classified according to the vigilance classification algorithm (
Mean vigilance scores were computed for each participant in each rest scan. Participants were considered in the “drowsiness” group if their mean vigilance score was higher than the median score (1.14) of all participants during 15-minute rest and their datasets contained at least 5% of reduced vigilance stages (1.2 or higher).
In accordance with the study hypotheses, major nodes of each of the three functional networks were defined as functional ROIs. For the default mode network these nodes were extracted from a meta analysis by
ROIs from the default-mode, executive and salience networks included in the analysis.
Regions | Laterality | MNI coordinates( |
||
---|---|---|---|---|
Precuneus (BA 7,31) | Midline | -4 | -62 | 45 |
Ventral anterior cingulate | Midline | 2 | 33 | -8 |
Posterior cingulate (BA 31) | Midline | -4 | -55 | 21 |
Middle temporal gyrus/angular gyrus (BA 39) | R | 46 | -69 | 14 |
Inferior parietal lobule (BA 40) | R | 52 | -30 | 25 |
Middle frontal gyrus (BA 8) | L | -26 | 14 | 49 |
Lateral premotor | R | 28 | 1 | 54 |
Dorsal cingulate/medial premotor (SMA) | Midline | -2 | 10 | 46 |
Medial posterior parietal (BA 7) | Midline | 10 | -70 | 48 |
Inferior parietal lobule (BA 40) | L | -36 | -53 | 40 |
Inferior parietal lobule (BA 40) | R | 40 | -51 | 38 |
Dorsolateral prefrontal (BA 46,9) | R | 40 | 31 | 34 |
Orbitofrontal insula (BA 47,12) | L | -40 | 18 | -12 |
Orbitofrontal insula (BA 47,12) | R | 42 | 10 | -12 |
Paracingulate (BA 32) | Midline | 0 | 44 | 28 |
Dorsal ACC (BA 24) | L | -6 | 18 | 30 |
Hypothalamus | L | -10 | -14 | -8 |
Ventrolateral PFC (BA 47) | R | 42 | 46 | 0 |
In order to examine correlation coefficients in the BOLD signal across the predefined ROIs, we extracted the mean time course for each ROI for both rest scans (baseline and 15-minute scan) for each participant. As common in connectivity analyses (
Among participants in the “rest” group, the difference in mean vigilance score between the baseline and the 15-minute rest scans was found to be mildly significant (
Five participants (two of the “rest” group, three of the “drowsiness” group) expressed difficulty in quantifying their experienced degree of MW, and were thus instructed to leave this measure empty. Among the remaining participants, reports of participants on the visual analog scale indicated that MW did occur in both “rest” and “drowsiness” groups [
Cronbach’s alpha coefficients for evaluation of internal consistency within the 10-item negative subscale of the PANAS in the first measurement were found to be at the threshold of marginal reliability (0.63 in the “drowsiness” group and 0.56 in the “rest” group), whereas values following the study manipulation were found to be satisfactory in both groups (“rest” group: 0.87; “drowsiness” group: 0.89). When computed on the change between the first and second measurement, Cronbach’s alpha values were 0.796 and 0.792 for the “rest” and “drowsiness” groups, respectively.
A significant rise from baseline in negative affect as measured by the PANAS questionnaire negative subscale was found among the “rest” group in a paired-samples
Though this study’s main interest was in RRNA, the PANAS positive subscale was analyzed as well in order to check the specificity of the effect of the study manipulation to negative affect. PANAS positive subscale scores were found to change in both groups in a manner which showed no sensitivity to vigilance level. Although a significant decline in positive scores was found in both groups [
To investigate the neural modulation associated with RRNA we first explored the ROI correlations within the “rest” group. Out of all ROI pairs examined (
Across groups, the same pair of regions, the dorsal cingulate cortex and the ventral ACC, was the only pair in which the difference in correlation in the long rest scan relative to the baseline scan was found to differ significantly between the “rest” and “drowsiness” groups [
Whereas no correlations were found between baseline FC in the dorsal-ventral ACC pair and baseline negative affect measurements, a significant positive correlation (
Correspondingly, the increase from baseline FC in dorsal-ventral ACC was found to be positively correlated with the increase in reports of negative affect among participants in the “rest” group in a mildly significant manner (
In the current study we hypothesized that RRNA would be found to occur to the extent that attentional resources are available for inward allocation. Our findings support this hypothesis, revealing that negative affect did not appear to rise when levels of vigilance decreased while replicating the finding of RRNA among participants who remained vigilant during rest. The two groups were further found to differ in degree of modification of FC between specific nodes of the executive and the default-mode networks. Moreover, the degree of this functional connection was found to be correlated with the degree of negative affect only among the vigilant “rest” group. To our knowledge, this is the first demonstration of a dramatic difference in occurrence of rest-related negative affect by simply monitoring the degree of vigilance.
Segregating participants into two groups according to their vigilance levels during a 15-minute rest scan revealed that indeed, and in accordance with the study hypothesis, the rise in negative affect following rest was dependent on a maintained level of vigilance: when vigilance was diminished, negative affect level did not increase. First and foremost, this finding serves as evidence that rest-related negative affect is not a necessary outcome of the awake resting state. Once this important dissociation is empirically established, it is intriguing to examine which factors, in both neural and psychological terms, stem from the current findings as mediating the occurrence of RRNA.
First, vigilance is demonstrated in the current study as a mediating factor of the occurrence of negative affect. Assuming that reduced vigilance in fact resulted in lower availability of attentional resources (
Additional insights into the mechanisms underlying RRNA stem from the current findings of neural differences between high and low vigilance resting states. To begin with, a notable finding is that both rest conditions (high and low levels of vigilance) were found to share many neural commonalities: out of the three networks inspected, including a total of 153 ROI pairs, only one specific functional connection was found to be significantly different across low and high vigilance conditions. This pair of regions includes the subgenual, ventral ACC, extracted from the DMN (
Functionally, the ventral, subgenual ACC has been described as a critical node in self and emotional related mental processing (
The finding that RRNA is mediated by attentional processes and, when increased, is associated with increased connectivity in dorsal and ventral ACC heightens the potential relevance of the degree of engagement of the self in rest related mental activity to the outcome experience. Indeed, both dorsal and ventral ACC have been implied as major neural hubs of self-referential mental activity, and even more so in the processing of self-referential information which also carry additional emotional aspects (
The psychological and neural differences between high and low vigilance groups in the current study thus point toward two potentially parallel scenarios of rest related neural and mental states. While MW may occur in both scenarios, the alert resting state might be characterized by stronger activity in attentional-emotion self-monitoring neural circuits, resulting in heightened negative affect. In contrast, a more drowsy resting state might not involve this aspect of activation, resulting in a less negative emotional experience. This proposition is in fact in line with the finding that when participants are found to be off-task during task performance, in or outside the laboratory, negative affect is reported (
Several issues need to be addressed as limitations of the current study. First, we used a subjective measure of MW administered retroactively at the end of the fMRI-EEG scan. The current study was designed to collect relatively long uninterrupted fMRI and EEG scans, based on the assumption that longer rest sessions are required to create identifiably different patterns of rest, which can later be compared to each other in terms of vigilance, neural connectivity, and psychological phenomenology. In order to enable the occurrence of undisturbed rest, all reports in this study, including that of mind wandering, had to be obtained retroactively. Nevertheless, such reports may have compromised the accuracy of MW levels in comparison with real-time thought sampling or other task related measurements. Secondly, we used an objective, yet indirect measure of attention allocation by examining known EEG parameters of vigilance, given that drowsiness leads to a lower availability of attentional resources. Future studies could use a combined approach of rest and parametric attention manipulations (for instance using a task with several degrees of cognitive load) to directly examine the role of attention allocation in shaping RRNA. Finally, the current study focused on the affective experience induced by a long session of rest while taking vigilance state into account. For a more comprehensive explanatory model, empirical examinations of other possible factors (e.g., physiological arousal, relevant personality traits, the content of MW, etc.) could further illuminate the nature of the interplay between attention allocation and RRNA.
To conclude, our findings support, both on the behavioral and on the neural level, the proposition that rest-related negative affect is associated with allocation of attention inward. This finding echoes known models of emotion regulation and reappraisal emphasizing the crucial role that attention and meta-awareness play in affective processing. Similar with the meditation practice of letting thoughts go, it seems that the less we monitor our internal world, the happier we are.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.