EEG and fMRI evidence for autobiographical memory reactivation in empathy.
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ABSTRACT:
SUBMITTER: Meconi F
PROVIDER: S-EPMC8410563 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Whilst patients with semantic dementia (SD) are known to suffer from semantic memory and language impairments, there is less agreement about whether memory for personal everyday experiences, autobiographical memory, is compromised. In healthy individuals, functional MRI (fMRI) has helped to delineate a consistent and distributed brain network associated with autobiographical recollection. Here we examined how the progression of SD affected the brain's autobiographical memory network over time. We did this by testing autobiographical memory recall in a SD patient, AM, with fMRI on three occasions, each one year apart, during the course of his disease. At the outset, his autobiographical memory was intact. This was followed by a gradual loss in recollective quality that collapsed only late in the course of the disease. There was no evidence of a temporal gradient. Initially, AM's recollection was supported by the classic autobiographical memory network, including atrophied tissue in hippocampus and temporal neocortex. This was subsequently augmented by up-regulation of other parts of the memory system, namely ventromedial and ventrolateral prefrontal cortex, right lateral temporal cortex, and precuneus. A final step-change in the areas engaged and the quality of recollection then preceded the collapse of autobiographical memory. Our findings inform theoretical debates about the role of the hippocampus and neocortical areas in supporting remote autobiographical memories. Furthermore, our results suggest it may be possible to define specific stages in SD-related memory decline, and that fMRI could complement MRI and neuropsychological measures in providing more precise prognostic and rehabilitative information for clinicians and carers.
| S-EPMC2806951 | biostudies-literature
Project description:Autobiographical memory retrieval is associated with activity of a distributed network that is similar to the default-mode network (DMN) identified via activity correlations measured during rest. We tested whether activity correlations could be used to identify the autobiographical network during extended bouts of retrieval. Global-correlativity analysis identified regions with activity correlation differences between autobiographical-retrieval and resting states. Increased correlations were identified for retrieval versus resting states within a distributed network that included regions prototypical for autobiographical memory. This network segregated into two subnetworks comprised of regions related to memory versus cognitive control, suggesting greater functional segregation during autobiographical retrieval than rest. DMN regions were important drivers of these effects, with increased correlations between DMN and non-DMN regions and segregation of the DMN into distinct subnetworks during retrieval. Thus, the autobiographical network can be robustly identified via activity correlations and retrieval is associated with network functional organization distinct from rest.
| S-EPMC6314301 | biostudies-literature
Project description:FMRI studies of autobiographical memory (AM) retrieval typically ask subjects to retrieve memories silently to avoid speech-related motion artifacts. Recently, some fMRI studies have started to use overt (spoken) retrieval to probe moment-to-moment retrieved content. However, the extent to which the overt retrieval method alters fMRI activations during retrieval is unknown. Here we examined this question by eliciting unrehearsed AMs during fMRI scanning either overtly or silently, in the same subjects, in different runs. Differences between retrieval modality (silent vs. narrated) included greater activation for silent retrieval in the anterior hippocampus, left angular gyrus, PCC, and superior PFC, and greater activation for narrated retrieval in speech production regions, posterior hippocampus, and the DLPFC. To probe temporal dynamics, we divided each retrieval period into an initial search phase and a later elaboration phase. The activations during the search and elaboration phases were broadly similar regardless of modality, and these activations were in line with previous fMRI studies of AM temporal dynamics employing silent retrieval. For both retrieval modalities, search activated the hippocampus, mPFC, ACC, and PCC, and elaboration activated the left DLPFC and middle temporal gyri. To examine content-specific reactivation during retrieval, the timecourse of narrated memory content was transcribed and modeled. We observed dynamic activation associated with object content in the lateral occipital complex, and activation associated with scene content in the retrosplenial cortex. The current findings show that both silent and narrated AMs activate a broadly similar memory network, with some key differences, and add to current knowledge regarding the content-specific dynamics of AM retrieval. However, these observed differences between retrieval modality suggest that studies using overt retrieval should carefully consider this method's possible effects on cognitive and neural processing.
| S-EPMC11299904 | biostudies-literature
Project description:The story of our lifetime - our narrative self - is constructed from our autobiographical memories. A central claim of social psychology is that this narrative self is inherently social: When we construct our lives, we do so in a real or imagined interaction. This predicts that self-referential processes which are involved in recall of autobiographical memories overlap with processes involved in social interactions. Indeed, previous functional MRI studies indicate that regions in the medial prefrontal cortex (mPFC) are activated during autobiographical memory recall and virtual communication. However, no fMRI study has investigated recall of autobiographical memories in a real-life interaction. We developed a novel paradigm in which participants overtly reported self-related and other-related memories to an experimenter, whose non-verbal reactions were being filmed and online displayed to the participants in the scanner. We found that recall of autobiographical vs. non-autobiographical memories was associated with activation of the mPFC, as was recall in the social as compared to a non-social control condition; however, both contrasts involved different non-overlapping regions within the mPFC. These results indicate that self-referential processes involved in autobiographical memory recall are different from processes supporting social interactions, and argue against the hypothesis that autobiographical memories are inherently social.
| S-EPMC3448611 | biostudies-literature
Project description:Memory reactivation during sleep is critical for consolidation, but also extremely difficult to measure as it is subtle, distributed and temporally unpredictable. This article reports a novel method for detecting such reactivation in standard sleep recordings. During learning, participants produced a complex sequence of finger presses, with each finger cued by a distinct audio-visual stimulus. Auditory cues were then re-played during subsequent sleep to trigger neural reactivation through a method known as targeted memory reactivation (TMR). Next, we used electroencephalography data from the learning session to train a machine learning classifier, and then applied this classifier to sleep data to determine how successfully each tone had elicited memory reactivation. Neural reactivation was classified above chance in all participants when TMR was applied in SWS, and in 5 of the 14 participants to whom TMR was applied in N2. Classification success reduced across numerous repetitions of the tone cue, suggesting either a gradually reducing responsiveness to such cues or a plasticity-related change in the neural signature as a result of cueing. We believe this method will be valuable for future investigations of memory consolidation.
| S-EPMC5988689 | biostudies-literature
Project description:Advances in computer and communications technology have deeply affected the way we communicate. Social media have emerged as a major means of human communication. However, a major limitation in such media is the lack of non-verbal stimuli, which sometimes hinders the understanding of the message, and in particular the associated emotional content. In an effort to compensate for this, people started to use emoticons, which are combinations of keyboard characters that resemble facial expressions, and more recently their evolution: emojis, namely, small colorful images that resemble faces, actions and daily life objects. This paper presents evidence of the effect of emojis on memory retrieval through a functional Magnetic Resonance Imaging (fMRI) study. A total number of fifteen healthy volunteers were recruited for the experiment, during which successive stimuli were presented, containing words with intense emotional content combined with emojis, either with congruent or incongruent emotional content. Volunteers were asked to recall a memory related to the stimulus. The study of the reaction times showed that emotional incongruity among word+emoji combinations led to longer reaction times in memory retrieval compared to congruent combinations. General Linear Model (GLM) and Blind Source Separation (BSS) methods have been tested in assessing the influence of the emojis on the process of memory retrieval. The analysis of the fMRI data showed that emotional incongruity among word+emoji combinations activated the Broca's area (BA44 and BA45) in both hemispheres, the Supplementary Motor Area (SMA) and the inferior prefrontal cortex (BA47), compared to congruent combinations. Furthermore, compared to pseudowords, word+emoji combinations activated the left Broca's area (BA44 and BA45), the amygdala, the right temporal pole (BA48) and several frontal regions including the SMA and the inferior prefrontal cortex.
| S-EPMC7329082 | biostudies-literature
Project description:BackgroundThe brain functional correlates of autobiographical recall are well established, but have been little studied in schizophrenia. Additionally, autobiographical memory is one of a small number of cognitive tasks that activates rather than de-activates the default mode network, which has been found to be dysfunctional in this disorder.MethodsTwenty-seven schizophrenic patients and 30 healthy controls underwent functional magnetic resonance imaging while viewing cue words that evoked autobiographical memories. Control conditions included both non-memory-evoking cues and a low level baseline (cross fixation).ResultsCompared to both non-memory evoking cues and low level baseline, autobiographical recall was associated with activation in default mode network regions in the controls including the medial frontal cortex, the posterior cingulate cortex and the hippocampus, as well as other areas. Clusters of de-activation were seen outside the default mode network. There were no activation differences between the schizophrenic patients and the controls, but the patients showed clusters of failure of de-activation in non-default mode network regions.ConclusionsAccording to this study, patients with schizophrenia show intact activation of the default mode network and other regions associated with recall of autobiographical memories. The finding of failure of de-activation outside the network suggests that schizophrenia may be associated with a general difficulty in de-activation rather than dysfunction of the default mode network per se.
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Project description:Autobiographical odor memory (AM-odor) accompanied by a sense of realism of a specific memory elicits strong emotions. AM-odor differs from memory triggered by other sensory modalities, possibly because olfaction involves a unique sensory process. Here, we examined the orbitofrontal cortex (OFC), using functional magnetic resonance imaging (fMRI) to determine which OFC subregions are related to AM-odor. Both AM-odor and a control odor successively increased subjective ratings of comfortableness and pleasantness. Importantly, AM-odor also increased arousal levels and the vividness of memories, and was associated with a deep and slow breathing pattern. fMRI analysis indicated robust activation in the left posterior OFC (L-POFC). Connectivity between the POFC and whole brain regions was estimated using psychophysiological interaction analysis (PPI). We detected several trends in connectivity between L-POFC and bilateral precuneus, bilateral rostral dorsal anterior cingulate cortex (rdACC), and left parahippocampus, which will be useful for targeting our hypotheses for future investigations. The slow breathing observed in AM-odor was correlated with rdACC activation. Odor associated with emotionally significant autobiographical memories was accompanied by slow and deep breathing, possibly involving rdACC processing.
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Project description:Rising life expectancies coupled with an increasing awareness of age-related cognitive decline have led to the unwarranted use of psychopharmaceuticals, including acetylcholinesterase inhibitors (AChEIs), by significant numbers of healthy older individuals. This trend has developed despite very limited data regarding the effectiveness of such drugs on non-clinical groups and recent work indicates that AChEIs can have negative cognitive effects in healthy populations. For the first time, we use a combination of EEG and simultaneous EEG/fMRI to examine the effects of a commonly prescribed AChEI (donepezil) on cognition in healthy older participants. The short- and long-term impact of donepezil was assessed using two double-blind, placebo-controlled trials. In both cases, we utilised cognitive (paired associates learning (CPAL)) and electrophysiological measures (resting EEG power) that have demonstrated high-sensitivity to age-related cognitive decline. Experiment 1 tested the effects of 5 mg/per day dosage on cognitive and EEG markers at 6-hour, 2-week and 4-week follow-ups. In experiment 2, the same markers were further scrutinised using simultaneous EEG/fMRI after a single 5 mg dose. Experiment 1 found significant negative effects of donepezil on CPAL and resting Alpha and Beta band power. Experiment 2 replicated these results and found additional drug-related increases in the Delta band. EEG/fMRI analyses revealed that these oscillatory differences were associated with activity differences in the left hippocampus (Delta), right frontal-parietal network (Alpha), and default-mode network (Beta). We demonstrate the utility of simple cognitive and EEG measures in evaluating drug responses after acute and chronic donepezil administration. The presentation of previously established markers of age-related cognitive decline indicates that AChEIs can impair cognitive function in healthy older individuals. To our knowledge this is the first study to identify the precise neuroanatomical origins of EEG drug markers using simultaneous EEG/fMRI. The results of this study may be useful for evaluating novel drugs for cognitive enhancement.
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Project description:The default network is involved in self-generated thought, a class of cognition that includes autobiographical memory, prospection, and reasoning about the mental states of others. We collected a replication sample of Spreng and Grady (J Cogn. Neurosci. 22, 1112-1123, 2010), confirming that the default network differentially supports each of these forms of self-generated thought. Here we describe this dataset of multi-echo fMRI data in 31 young adults during autobiographical remembering, imagining, and mentalizing; we also provide an additional resting-state scan for each subject. In this new sample, the findings from the original report are successfully replicated using the same analysis. Physiological measures were additionally collected and allow for interrogation of the impact of multi-echo independent components preprocessing both in task and rest. Future work on this dataset may provide insight into evoked brain response for cued self-generated thought, International Affective Picture System viewing, resting state dynamics, preprocessing procedures, and more. The dataset is accompanied by experimental code for independent behavioral data collection.
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