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3 June 2026

Functional Activity and Connectivity Patterns During Recent and Remote Autobiographical Memory Retrieval Depend on Subjective Qualia

,
,
and
1
Department of Psychological and Brain Sciences, University of Louisville, Louisville, KY 40208, USA
2
Department of Psychological and Brain Sciences, University of Indiana, Bloomington, IN 47405, USA
3
Deportment of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
4
Department of Anatomical Sciences & Neurobiology, University of Louisville, Louisville, KY 40208, USA
Neuroimaging2026, 1(2), 9;https://doi.org/10.3390/neuroimaging1020009
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Abstract

Background/Objectives: Autobiographical memories (AMs) are an essential type of memory for our sense of self. A broad network of brain regions supports the retrieval of AMs, encompassing the medial temporal lobe (MTL), medial prefrontal cortex (mPFC), and parietal and visual cortices. However, little is known about how the subjective qualia of these memories relate to the underlying functional networks supporting their retrieval. Methods: AM cues were generated from early and recent life encompassing both object- and location-specific memories. While undergoing functional imaging, participants were cued on to retrieve differing time (remote, recent) and type (object, location) AMs followed by subjective ratings of each memory cued. Results: Functional activation patterns were consistent across the time and type of memory and reflect the existing literature. Functional connectivity analyses were similar across memory age, with only recent memories having greater connectivity compared to remote memories. Subjective qualia moderated the connectivity between regions for both remote and recent memories. Connections from the mPFC were modulated by multiple ratings across memory age, with important recent memories showing a significant negative connection with the hippocampus (pFDR < 0.05). Conclusions: Subjective qualia mostly modulated the connectivity profile of the mPFC with other visual and MTL regions underlying the mPFC’s importance during retrieval of autobiographical memories. These connections, in relation to differing subjective qualia across memory age, highlight the possible differences in the reinstantiation of AMs.
Keywords:
autobiographical memory; retrieval; subjective qualia; fMRI; cognitive neuroscience; functional connectivity
Key Contribution:
Subjective qualia moderate the functional connectivity profile for the retrieval of autobiographical memory, highlighting the mPFC being an important region for this interaction.

1. Introduction

Declarative memory comprises episodic memory and semantic memory (factual knowledge), which allow us to “look back” at previous events and recall facts related to those events [1]. Declarative memory pertaining to the episodic and semantic knowledge of one’s own past is known as autobiographical memory (AM) [2]. For example, an AM of a trip to a museum may include an episodic recollection of all the exhibits you visited, the social interactions you had, and the semantic details of the exhibits you engaged with. The nature of AMs is important for understanding oneself within a temporal frame and provides consistency to our daily lives. When individuals were asked to forget positive and negative social feedback, it was found that memories of positive social feedback were harder to forget compared to memories of negative social feedback [3]. This further highlights how AMs are an important cognitive attribute of our self-referential conception.
A recent meta-analysis of fMRI papers found that the medial prefrontal cortex (mPFC), hippocampal complex (including the surrounding parahippocampal gyrus), precuneus, posterior cingulate cortex, and angular gyrus are consistently activated by AM retrieval [4]. These results are consistent with, and additive to, past meta-analyses of AM retrieval that found similar activations across these areas [5,6,7,8]. Taken together, these regions construct a network subserving self-referential, visual, and spatial elements, which are incorporated into and bind memory ensembles, which support the retrieval and subjective experience of one’s past.
Few studies have assessed how subjective reports concerning one’s memories influence or are related to the functional characteristics of neural activation and connectivity when AMs are retrieved. Parametric modulation to assess the effects of vividness on activation maps during AM retrieval found that these subjective reports are related to specific clusters of hippocampal activation [9]. The ability to internally visualize memories can also shed insight into the subjective and neurobiological mechanisms of AM retrieval. People with aphantasia experience a marked reduction or complete lack of voluntary sensory imagery [10]. When retrieving AMs, aphantasics showed decreased activation in the hippocampus and reduced functional connectivity between the hippocampus and visual cortices [11]. In the same study, healthy controls showed a correlation between visualization ability and functional connectivity between the hippocampus and visual cortices, indicating that the more one is able to visualize their memories, the more these regions co-activate. This provides a coarse explanation as to how subjective vividness may modulate hippocampal activity and provides evidence that subjective reports on memory qualia could be used to understand neural dynamics during retrieval.
Research indicates that affective content is also relevant in the retrieval of AMs. It has long been observed that individuals attend to negative information more than positive information [12], and that people retrieve more negative memories compared to positive memories [13]. Functional activation of both positive and negative memories showed similar qualitative activation patterns, albeit with differences in greater quantitative activity, specifically when comparing the two, such that positive activation was greater than negative [14]. This pattern also extended to functional connectivity analyses, with differences seen only when positive was compared directly to negative memories. It has also been shown that AMs rated as having higher levels of emotional intensity increased the effective connectivity (causational) between the vmPFC and the hippocampus, indicating that the subjective content of a memory affects neural network dynamics [15]. Together, with studies looking at vividness, it seems apparent that subjective aspects of AMs potentially affect their retrieval and the underlying neural processes. However, how other subjective qualities of AMs modulate neural and behavioral characteristics of retrieval remains largely unanswered.
The current investigation aims to further our understanding of the functional activation and connectivity profile of subjectively rated and generated AMs. Subsequently, we aim to test whether this profile differs between contextual attributes (object vs. location), as well as the age (recent vs. remote) of an individual’s memories. We first reveal functional activity patterns, which provide a template of neural regions to subsequently examine how these regions are functionally connected during AM retrieval. In addition, we aim to test how several types of subjective ratings concerning the qualia of AMs further modulate functional connectivity dynamics. To accomplish this, we had participants generate AMs, provide cues and, subsequently, recall memories 24 h later while undergoing fMRI.
Hypotheses: (1) We hypothesize that retrieval of autobiographical memories relies on frontal, visual, and parietal regions to support the hippocampal (and associated supporting MTL cortices) reinstatement of AMs. (2) We further hypothesize that remote AMs will elicit greater functional activation across the retrieval network, due to these memories being retrieved and reinstated more than recent AMs. (3) In addition, we hypothesize that remote memories will induce higher subjective ratings, indicating a richer encoding of remote AMs. (4) We also hypothesize that functional connectivity results will show similar qualitative connectivity patterns between remote and recent memories; however, quantitative differences will emerge for greater connectivity (overall) for remote vs. recent AMs. Finally, we hypothesize that the functional connectivity results will be modulated by subjective ratings, with arousal and valence ratings modulating the frontal-hippocampal connections, and vividness ratings modulating parieto-temporo-visual cortical connectivity.

2. Materials and Methods

2.1. Participants

Twenty healthy young adults were recruited (16 females; Age M = 20.2, SD = 1.88) for the present study. All participants were right-handed, with normal or corrected-to-normal vision and hearing, and had no disclosed history of neurological or psychiatric disorders. Participants were recruited through on-campus flyers and an online research participation system (SONA Systems) and were compensated with $50 for their time. This study was carried out in accordance with the recommendations of the University of Louisville’s Institutional Review Board. All subjects gave written informed consent in accordance with the Declaration of Helsinki, and the experimental protocol was approved by the University of Louisville’s Institutional Review Board (IRB #: 14.0811). No participants were excluded from any analyses.

2.2. Procedure

Participants enrolled into the study followed a two-day protocol. On the first day, participants visited the laboratory to sign consent forms and read through task instructions. Participants were also instructed to complete a memory details task where participants generated memory cues, followed by post-task ratings of the generated memories. On the second day, participants completed the functional magnetic resonance imaging (fMRI) portion of the study at the University of Louisville School of Medicine, where they recalled the memories they generated on day one, followed by post-scan ratings of the generated memories.

2.2.1. Stimuli

Participants were asked to generate several cues that reminded them of certain events from early and present-day life. In the memory details task, participants were asked to remember 20 independent memories: 5 object-related memories and 5 location-related memories from 2 different times in their lives for a total of 20 memories. The windows of time from which participants’ memories were recalled were early memories until the age of 7 (remote) and recent memories from the last year (recent). Individuals also completed various subjective rating scales on aspects of the memories (i.e., arousal, frequency, difficulty, valence, vividness, importance). After completing this task, the cues generated from it were used as cues for the memory recall task completed in day two in the scanner (see Figure 1). Participants were then shown these cues while recalling the memories in an fMRI scanner. During scanning, visual stimuli were displayed through E-Prime2 (Psychology Software Tools, Pittsburg, PA, USA) onto an Invivo Esys LCD TV monitor at the back of the scanner bore, which was viewed by participants through a mirror on the head coil. Auditory stimuli were present binaurally through headphones at a predetermined constant level.
Figure 1. Layout of the experimental procedure across both sessions. (A) Experimental procedure on day 1 in which participants generate memory cues and rate memories. (B) Experimental procedure on day 2 in which participants retrieved memories and rated them in the scanner.

2.2.2. Scanning Paradigm

In the memory retrieval task, participants were presented with a lexical memory cue for 10 s followed by a pseudo-random jitter (ITI) before another memory cue was presented. Each memory from each type (object or location for recent, or remote memories) was repeated 3 times for a total of 90 trials. Total task length was 15 min, with 4 min of jitter.

2.3. Neuroimaging Methods

All structural MRI images were acquired using a Siemens 3-T Skyra MR scanner (Erlangen, Germany) located at the University of Louisville, School of Medicine. A 20-channel head coil was used for radiofrequency reception. Participants were given earplugs to reduce scanner noise and headphones to receive instructions. Foam padding was added to limit motion if additional room remained within the head coil, and a piece of folded tape was placed over the participant’s forehead as a reminder to remain still throughout the scan. Structural images were obtained via a T1-weighted magnetization-prepared rapid gradient-echo sequence (MPRAGE) in 208 sagittal slices. Imaging parameters were as follows: echo time (TE) = 2.26 ms, repetition time (TR) = 1700 ms, flip angle = 9.0°, field of view (FoV) = 204 mm, and voxel size = 0.8 mm3. Scan parameters were consistent for all imaging sessions.
Functional blood oxygenation level-dependent (BOLD) images were collected using gradient-echo T2*-weighted echoplanar imaging (TR = 3000 ms; TE = 30 ms; multi-band accelerated factor 2; FoV = 192 mm; 78 transverse slices, 1.5 mm3 voxels, flip angle = 90°). Slices were oriented obliquely along the AC–PC line. An additional high-contrast full-head BOLD image was obtained to facilitate three-stage registration (TR = 7390 ms; TE = 30 ms; FoV = 192 mm; 100 transverse slices, 1.5 mm3 voxels, flip angle = 90°).

2.4. Behavioral Analysis Methods

All statistical analyses performed on the subjective ratings data were done using R Studio version 4.4.0 [16]. A 2 (Time) × 2 (Type) ANOVA test was completed using the afex package version 1.4-1 [17]. The subjective ratings used in the behavioral analysis were averaged over the two behavioral sessions. All pairwise t-tests and paired t-tests were completed using the Rstatix package version 0.7.2 [18].

2.5. Neuroimaging Analysis Methods

2.5.1. Functional Analyses

Image preprocessing and data analysis were implemented using the FSL package version 5.0.9, Analysis group, FMRIB, Oxford, UK https://fsl.fmrib.ox.ac.uk/fsl/docs/#/ (accessed on 14 May 2026). FSL preprocessing pipeline constituted optiBET—brain extraction [19], time-series prewhitening, and high-pass filtering (0.01 Hz). Functional images were smoothed with a Gaussian kernel of 6 mm full-width at half-maximum (FWHM) for whole-brain analyses. Three-stage registration was performed. Each individual’s functional task images were first registered to a high-contrast full-head functional volume to facilitate registration of the multislice acquisition (multiband) images. Functional images were then registered to high-resolution MPRAGE scans via 6-parameter linear registration, and the MPRAGE images were in turn registered to the Montreal Neurological Institute (MNI) 152 T1-1 mm template via 12-parameter nonlinear registration [20]. These registrations were combined to align the functional images to the 1 mm standard template. Following preprocessing, lower-level statistics were implemented in FEAT. Using multiple regression analysis, statistical maps representing the association between the observed time series (e.g., BOLD signal) and one or a linear combination of regressors for each subject were constructed. Following preprocessing, lower-level statistics were implemented in FEAT. Using multiple regression analysis, statistical maps representing the association between the observed time series (e.g., BOLD signal) and one or a linear combination of regressors for each subject were constructed. Regressors for the main effects were constructed by modeling each of the conditions—Recent, Remote, Object, and Location—versus low-level fMRI baseline (ITI fixation), in order to create contrasts of interest: Recent > Remote (Rec > Rem) and Object > Location (Obj > Loc). For each regressor, a double-gamma hemodynamic response function (HRF) was convolved with an event vector starting at the stimulus onset through rating response to capture both the stimulus processing. Higher-level analysis was conducted using FLAME 1 to combine and spatially normalize all subjects. The higher-level models employed nonparametric permutation methods through FSL’s randomize function [21]. For each contrast of interest, cluster thresholding and correction for multiple comparisons were implemented through the Threshold-Free Cluster Enhancement (TFCE) method, which detects clusters of contiguous voxels without first setting an arbitrary statistical cutoff (e.g., Z > 2.3) and controls the family-wise error (FWE) rate at p < 0.05 [21].

2.5.2. Functional Connectivity

All functional analyses were performed using CONN release 21.a [22] and SPM12 (release version 12.7771) [23]. Functional and anatomical data were preprocessed using a flexible preprocessing pipeline [24] including realignment with correction of susceptibility distortion interactions, slice timing correction, outlier detection, direct segmentation and MNI-space normalization, and smoothing. Functional data were realigned using SPM’s realign and unwarp procedure [25], where all scans were co-registered to a reference image (first scan of the first session) using a least squares approach and a 6-parameter (rigid body) transformation [26] resampled using b-spline interpolation to correct for motion and magnetic susceptibility interactions. Temporal misalignment between different slices of the functional data (acquired in interleaved Siemens order) was corrected following SPM’s slice-timing correction (STC) procedure [27,28], using sinc temporal interpolation to resample each slice BOLD time series to a common mid-acquisition time. Potential outlier scans were identified using ART [29] as acquisitions with framewise displacement above 0.9 mm or global BOLD signal changes above 5 standard deviations [24,30], and a reference BOLD image was computed for each subject by averaging all scans excluding outliers. Functional and anatomical data were normalized into standard MNI space, segmented into grey matter, white matter, and CSF tissue classes, and resampled to 2 mm isotropic voxels following a direct normalization procedure [24,31] using SPM’s unified segmentation and normalization algorithm [32,33] with the default IXI-549 tissue probability map template. Finally, functional data were smoothed using spatial convolution with a Gaussian kernel of 8 mm FWHM. In addition, functional data were denoised using a standard denoising pipeline [24] including the regression of potential confounding effects characterized by white matter time series (5 CompCor noise components), CSF time series (5 CompCor noise components), motion parameters and their first order derivatives (12 factors) [34], outlier scans (below 94 factors) [30], and linear trends (2 factors) within each functional run, followed by high-pass frequency filtering of the BOLD time series [35] above 0.008 Hz. CompCor [36] noise components within white matter and CSF were estimated by computing the average BOLD signal as well as the largest principal components orthogonal to the BOLD average, motion parameters, and outlier scans within each subject’s eroded segmentation masks.
For ROI–ROI functional connectivity analyses, five masks were generated from the significant clusters from the recent memory location contrast in our functional activation analysis, as they yielded the greatest activation extent. The ROIs from the significant clusters (thresholded using TFCE with a FWE set at p < 0.05) included the visual cortex (visual), hippocampal/amygdala (H/A), lingual gyrus (lingual), medial prefrontal cortex (mPFC), and subgenual anterior cingulate cortex (sgACC), as seen in Figure 3C. In addition, we validated our ROIs using probabilistic reverse inference in Neurosynth https://www.neurosynth.org (accessed on 14 March 2026) to assure that they were associated with memory retrieval within the first 10 results. All subjective ratings were included as covariates in the second-level model and were averaged across session and memory type. Network level functional connectivity was assessed at a threshold of p < 0.05, and multiple comparisons were subjected to False-Discovery Rate (FDR) correction at p < 0.05 to establish significance.
In addition to the network functional connectivity analysis, we extracted the connectivity values from each ROI–ROI connection shared by both recent and remote memories for each subject and correlated these with their subjective ratings. This analysis enabled us to look beyond network level functional connectivity, by examining individual ROI–ROI connections and their correlations with the subjective ratings using William’s tests to compare the difference in correlation coefficients between recent and remote memories and their qualia [14].

3. Results

3.1. Results of Memory Ratings

Descriptive statistics of all the ratings averaged from both sessions are displayed in Table 1. Mean ratings averaged across sessions are visualized in Figure 2. A 2 (Time) × 2 (Type) analysis of variance (ANOVA) was used on the rating from the first session to test the effects of the type and time on the subjective ratings. For all ratings excluding valence, only the main effect of time was significant (see Table 2). The only significant interaction effect of time and type was on the importance ratings (F (1, 19) = 8.140, ηp2 = 0.30, p = 0.01). This was followed by a pairwise t-test on the importance ratings, which showed that the participants rated recent memories as more important than remote memories for objects (T (199) = −4.43, p < 0.001) but not locations (T (199) = 0.395, p = 0.693) (results are Bonferroni corrected).
Table 1. Descriptive statistics for the subjective ratings.
Table 2. 2 × 2 ANOVA results for each subjective rating.
Figure 2. Mean ratings by variable (averaged across sessions).

3.2. Functional Activation

Whole-brain univariate analyses were first conducted to investigate changes in activation for each contrast of interest (Recent, Remote, Object, and Location). Omnibus results for each main condition were thresholded using TFCE with an FWE set at p < 0.05. Significant clusters for each condition are presented in Table 3. Figure 3A,B displays voxel-wise thresholded images (p < 0.01) to visualize the extent of the omnibus functional activation. Since the main effect functional activation maps indicated a high degree of activation overlap for both (i) object and location as well as (ii) recent and remote, we subsequently focused on the recent location condition’s statistical map to establish ROIs for further functional connectivity analyses, thresholded using TFCE with an FWE set at p < 0.05. Figure 3C illustrates the resultant ROIs (visual, lingual, hippocampus/amygdala (H/A), sgACC, mPFC) for connectivity analyses.
Table 3. Cluster statistics of Object, Location, Recent, and Remote contrasts.
Figure 3. Functional activation maps for (A) recent (red) and remote (yellow) and (B) location (blue) and object (yellow). All activation shown is significant at p < 0.01 voxel-wise to visually illustrate the activation extent. (C) Axial view of the ROIs derived from the recent location functional activation results overlaid on the MNI template (red = mPFC, dark blue = sgACC, yellow = hippocampus/amygdala, light blue = lingual gyrus, green = visual cortex). Results are cluster corrected using TFCE (see methods).

3.3. Functional Connectivity

Network level functional connectivity analyses conducted on the individual recent and remote conditions yielded an almost identical network connectivity pattern, with recent memories having an additional significant ROI–ROI pair connection between the visual and the sgACC pair (T(19) = 3.54, p = 0.0022, pFDR = 0.0044), as well as differences in connectivity strength between ROI pairings. To test these differences, we next contrasted recent with remote memories, which indicated an un-corrected significant difference between the mPFC–sgACC pair (T(19) = 2.59, p = 0.018, pFDR = 0.098) and the H/A–sgACC pair (T(19) = 2.55, p = 0.019, pFDR = 0.098), illustrating a largely overlapping but slightly different network organization for recent and remote memories (Figure 4).
Figure 4. Functional connectivity results for (A) remote, (B) recent, and (C) the contrast between recent and remote memories. Visual = visual cortex ROI, Lingual = lingual gyrus ROI, H/A = hippocampus/amygdala ROI, mPFC = medial PFC ROI, sgACC = subgenual anterior cingulate cortex ROI. ** denotes p < 0.05 FDR-corrected additional connection in the recent condition. * denotes p < 0.05 uncorrected, for the recent > remote condition contrast.

3.4. Functional Connectivity Regressed with Subjective Qualia

To understand whether subjective qualia were related to network connectivity, we next submitted the subjective ratings to network level functional connectivity analyses for both recent and remote memories, individually. Results from recent memories indicated decreases in arousal were associated with increased functional connectivity between the mPFC and lingual pair (T(18) = −2.67, p = 0.015, pFDR = 0.155). Less important memories were associated with increased functional connectivity between the mPFC and lingual pair (T(18) = −2.38, p = 0.028, pFDR = 0.142) and the mPFC and the H/A pair (T(18) = −3.32, p = 0.004, pFDR = 0.038). Higher valenced memories were associated with increased functional connectivity between the visual area and the sgACC pair (T(18) = 2.73, p = 0.014, pFDR = 0.138) and the mPFC and the lingual pair (T(18) = 2.16, p = 0.044, pFDR = 0.221). Results from remote memories indicated that more vivid memories were associated with increased functional connectivity between the visual and the mPFC pair (T(18) = 2.72, p = 0.014, pFDR = 0.140). While these relationships between subjective ratings and ROI–ROI pairs appear variable, one consistent finding is that all correlations involve the mPFC ROI, suggesting differences in subjective qualia affect frontal modulation of memory reinstatement and its corresponding functional connectivity.
Finally, because the network level analyses examining ROI pairings correlated with subjective qualia produced interesting but likely insufficiently powered results (i.e., yielding in one significant and three significant but uncorrected findings), we assessed the differences between remote and recent memories at individual ROI–ROI pairings. This exploratory analysis compared the ROI–ROI correlations with each of the subjective ratings using William’s tests. Analyses indicated that for importance ratings, remote memories showed a greater correlation with the ratings than recent memories (T(17) = −2.24, p = 0.038) for the visual and the H/A pair. For vividness ratings, remote memories showed a greater correlation with the ratings for the mPFC and the lingula pair (T(17) = −2.42, p = 0.027), as well as the mPFC and H/A pair (T(17) = −2.26, p = 0.025). The relationships between the importance and vividness subjective ratings and ROI–ROI pairs indicate two consistent findings: (i) that these relationships rely on mPFC (similar to network level relationships above) modulating visual and MTL regions, and that (ii) increases in functional connectivity are related to increased importance and vividness within the remote memory condition.

4. Discussion

Autobiographical memory is an essential type of memory for understanding ourselves and others. We sought to investigate the neural basis and network structure underlying AM retrieval. To do this, we employed a memory task in which participants generated memory cues on day 1 followed by a retrieval session the following day while in the MRI. Our results show that across the age of memory, a common neural system is engaged in retrieval. These activation patterns are consistent with the literature [4,6,7] and confirm our hypothesis that retrieval is supported by the visual, medio-frontal, and MTL cortices.

4.1. Functional Activation

Contrary to our hypothesis, more significant clusters of functional activation were seen in recent memories compared to remote memories. Two theoretical explanations are possible: (i) more regions of activation during recent memories may reflect increased recruitment of the functional network to support successful retrieval for memories that are less likely to be well instantiated, or alternatively, (ii) because recent memories have been encoded/consolidated more recently, their reinstantiation is easier. In our functional activity analysis, more clusters were active in the frontal gyri (middle and inferior) in addition to medial frontal regions like the vmPFC and sgACC, for recent than remote memories. The medial structures have been found to reflect the affective value [37,38,39] as well as the self-referential nature of AMs [40]. The increased recruitment of these areas exemplifies the more affective and autobiographical nature of memories made in the last year. This difference runs contrary to research indicating that older memories are represented more diversely across the AM network, most notably in the vmPFC [41,42]. When comparing location to object memory retrieval, significant differences were observed in the precuneus and the parahippocampal cortex. Increased activation in the precuneus likely represents the increased visuospatial demands required by memory retrieval of locations, which are more information dense and may require more integration of allocentric and egocentric representations [43]. Our results support evidence that the parahippocampal cortex supports visuospatial memory rather than object memory [44,45,46].

4.2. Functional Connectivity

Our functional connectivity analysis found that both recent and remote memories shared almost identical network level functional connections, with the only qualitative difference between the two conditions being a connection between the sgACC and visual pair, as well as quantitative differences in connection strength (see Figure 5). For both memory ages, the medial PFC regions and visual regions were inter- and intra-connected, while the hippocampus was connected with both medial PFC and visual regions. This connectivity profile supports the importance of self-referential memory and visual cortices for the retrieval of AMs. The functional connection between the sgACC and visual cortex could be indicative of the need for greater control over visual sensory representations in recent memories, or alternatively, that more recent memories elicit increased activation/connectivity due to their more recent nature. To our knowledge, no studies have looked at the association between subjective qualia of AMs in relation to the functional connectivity of the brain during retrieval. The lack of differences could be alternatively explained by a potential rehearsal effect from prior retrieval during cue generation the day before scanning. For further discussion about this potential limitation, see the Section 4.4 below.
Figure 5. Functional connectivity correlations with subjective qualia. Network level ROI–ROI pair correlations (A–D). Individual ROI–ROI pair correlations (E,F). Visual = visual cortex ROI, Lingual = lingual gyrus ROI, H/A = hippocampus/amygdala ROI, mPFC = medial PFC ROI, sgACC = subgenual anterior cingulate cortex ROI. ** denotes p < 0.05 FDR-corrected additional connection in the recent condition. * denotes p < 0.05 uncorrected, for the recent > remote condition contrast.
Taken together, our functional results on the main effect of time (recent/remote) indicate that while recent differs in connectivity strength as well as an extra connection between the sgACC and visual ROI, the network supporting these memories is largely the same. Simply put, minor differences in the connectivity profiles of recent and remote memories could either represent an increased or decreased ease of reinstantiation of the memory, depending on the interpretation of ‘what’ increased activation or connectivity represents. We next discuss the behavioral qualia to gain insight into which of these theoretical alternatives are more supported from the current findings.

4.3. Functional Connectivity Regressed with Subjective Qualia

Subjective qualia ratings of memories did indeed modulate both recent and remote connectivity profiles, but the connections modulated by specific ratings differ from our initial hypothesis. Extending on our functional connectivity results, connectivity between the mPFC and visual cortex has been found to reflect early reconstruction of AMs [47]. Interestingly, arousal and importance ratings were associated with decreased functional connectivity between the mPFC and lingual gyrus/hippocampus/amygdala in recent memories. Decreased connectivity between these regions could be indicative of the decreased need for control over self-referential and affective processing, as the higher arousal and/or importance of the associated memories supports successful reinstantiation. Conversely, the mPFC/sgACC showed increases in functional connectivity to the lingual gyrus and visual cortex in relation to increases in valence ratings during recent memory retrieval. This result again supports the importance of the mPFC regions for affective self-referential processing, which in turn supports the successful reconstruction of AMs. Only vividness was significantly associated with differences in functional connectivity for remote memories. Increased activation in the mPFC has been found to be associated with vividness ratings of AMs [48]. The increased connectivity between the mPFC and the visual pair again supports the mPFC’s role in memory reconstruction, as this connection facilitates visual reconstruction, which in turn supports the vividness of a memory. Taken together, our connectivity results represent neural processes of reconstruction/reinstatement and early elaboration of AMs [47,49]. Due to the characteristics and size of our sample, our ROI–ROI results should be interpreted with some caution, as many of these relationships do not survive multiple comparison correction.
Extending our network level correlations between functional connectivity and subjective qualia, we aimed to increase power by investigating individual ROI–ROI pairings in a contrast of recent and remote memories. Our exploratory analysis using William’s tests indicate that within remote, greater than recent memories, increased subjective ratings of importance and vividness were both related to increases in functional connectivity of the mPFC with the visual cortex, and the mPFC with MTL structures, respectively. These findings support the mPFC’s role in memory reconstruction, as these connections with both visual and MTL areas facilitate reconstruction and relate to the qualia of the memory.
Taken together, our results highlight the importance of medial PFC regions (mPFC/sgACC) for supporting the subjective experience of AMs. The functional connectivity of these regions with the MTL and visual cortex supports the self-referential and affective value of AMs for their successful and rich reconstruction. While activation and connectivity profiles were largely similar across the age of retrieved memories, interesting differences emerged when connectivity profiles were regressed with subjective qualia of memories. First, across condition and qualia, the mPFC was indicated in every finding, again supporting the unequivocal nature of the mPFC’s involvement in the retrieval of AMs. While increases in subjective qualia appeared to decrease the functional connectivity within recent memories, they appeared to conversely increase functional connectivity in remote memories. Perhaps, this juxtaposition is related to a quantitative difference in the ease of reinstantiation of AMs, in general, with more recent memories simply being easier to recall. Our subjective qualia rating differences support this conclusion, as recent memories were rated higher in every domain except difficulty and valence. Subjective increases in difficulty of remote memories reflects support for our interpretation. However, increases in valence remained as the only qualia to elicit greater connectivity in recent memories. Perhaps, increases in valence elicit more “noise” intrinsic to memory representation, as research has long suggested highly emotional memories are processed to a higher degree [49,50], thus increasing the need for neural communication. In conclusion, as much of the interpretation of “what” increases in functional activation or connectivity actually correspond to in terms of behavior or qualia, the inference is largely subjective, and more research is warranted to confirm our analyses and further our understanding of the neural correlates of the subjective qualia of AMs.

4.4. Limitations

We offer insight into the current study and paradigm to present limitations that can be instituted in further studies to improve investigation into the subjective qualia of AMs. Since the two sessions of the experiment induced a one-day delay between formation of cues and retrieval of the memory, it is possible that the reinstatement of older memories the day before scanning could have influenced the results of the remote memories to be stronger than they would have been the day prior. While prior reinstatement before scanning likely does not change the manner in which older memories are encoded in the cortex, this prior reinstatement may affect the mechanism supporting the more typical network supporting retrieval. Due to the low sample size (N = 20), the functional connectivity analysis had insufficient power to detect the effects of the different subjective ratings on the connectivity profile. In addition, the majority of our sample comprised young women (80%), which could bias our results due to the potential failure to capture the effects of age, sex, and gender on the relationship between neural substrates and subjective qualia. Future investigations would benefit from increased sample sizes to better capture the effects of subjective qualia on the functional activation and connectivity profiles of AMs. Consideration should be taken to ensure as much variance in the sample can be captured to increase validity. Future designs should also look to designing their procedures to avoid reinstantiation of older memories before scanning, while also maximizing the reliability of cueing older memories. The combination of a small sample size as well as the sex imbalance of our sample warrant careful interpretation of our findings.

5. Conclusions

Subjective qualia mostly modulated the connectivity profile of the mPFC with other visual and MTL regions, underlying the mPFC’s importance during retrieval of autobiographical memories. These connections, in relation to differing subjective qualia across memory age, highlight the possible differences in the reinstantiation and retrieval of AMs.

Author Contributions

Conceptualization, B.E.D.; Methodology, B.E.D. and F.N.; Formal Analysis, J.F., F.N. and B.E.D.; Investigation, J.F., A.P., F.N. and B.E.D.; Resources, B.E.D.; Writing—Original Draft Preparation, J.F.; Writing—Review and Editing, J.F., B.E.D. and A.P.; Supervision, B.E.D. All authors have read and agreed to the published version of the manuscript.

Funding

No funding was obtained for the collection of the data used in this manuscript.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of the University of Louisville (IRB #: 14.0811, approved on 25 March 2015).

Data Availability Statement

Data is available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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