Search and recovery of autobiographical and laboratory memories: Shared and distinct neural components

Abstract

Functional neuroimaging evidence suggests that there are differences in the neural correlates of episodic memory for laboratory stimuli (laboratory memory) and for events from one's own life (autobiographical memory). However, this evidence is scarce and often confounded with differences in memory testing procedures. Here, we directly compared the neural mechanisms underlying the search and recovery of autobiographical and laboratory memories while minimizing testing differences. Before scanning, participants completed a laboratory memory encoding task in which they studied four-word "chains" spread across three word pairs. During scanning, participants completed a laboratory memory retrieval task, in which they recalled the word chains, and an autobiographical memory retrieval task, in which they recalled specific personal events associated with word cues. Importantly, response times were similar in the two tasks, allowing for a direct comparison of the activation time courses. We found that during memory search (searching for the memory target), similar brain regions were activated during both the autobiographical and laboratory tasks, whereas during memory recovery (accessing the memory traces; i.e., ecphory), clear differences emerged: regions of the default mode network (DMN) were activated greater during autobiographical than laboratory memory, whereas the bilateral superior parietal lobules were activated greater during laboratory than autobiographical memory. Also, multivariate functional connectivity analyses revealed that regardless of memory stage, the DMN and ventral attention network exhibited a more integrated topology in the functional network underlying autobiographical (vs. laboratory) memory retrieval, whereas the fronto-parietal task control network exhibited a more integrated topology in the functional network underlying laboratory (vs. autobiographical) memory retrieval. These findings further characterize the shared and distinct neural components underlying autobiographical and laboratory memories, and suggest that differences in autobiographical vs. laboratory memory brain activation previously reported in the literature reflect memory recovery rather than search differences.

A Neurocognitive Perspective on the Forms and Functions of Autobiographical Memory Retrieval

“…There is a growing body of work suggesting that the anterior hippocampus plays a directive role in memory retrieval compared to the posterior hippocampus, particularly when forming complex mental event representation. For example, there is evidence that the anterior hippocampus is necessary for tasks that involve the online flexible construction of mental representations, including autobiographical experiences (McCormick et al, 2015; Ito and Lee, 2016; Mack et al, 2018; Monge et al, 2018), but not more rigid semantic memories that do not require this flexibility (e.g., Manns et al, 2003a,b; Winocur et al, 2010). With respect to our framework, it could be that a higher-order conceptual construct is a necessary framework for recalling autobiographical representations since recalling these events as episodic memories always require manipulating existing event-based knowledge (Nadel and Moscovitch, 1997; Moscovitch et al, 2006, 2016; Sekeres et al, 2018).…”

Evidence for Reduced Autobiographical Memory Episodic Specificity in Cognitively Normal Middle-Aged and Older Individuals at Increased Risk for Alzheimer’s Disease Dementia

“…Long before diagnosable cognitive impairment is present, Aβ and tau-related neurodegenerative mechanisms can collectively affect much of the neural network that supports episodic memory (Chen, Gilmore, Nelson, & McDermott, 2017; Gilboa, 2004; Monge, Wing, Stokes, & Cabeza, 2018; Rugg & Vilberg, 2013). For instance, the earliest stages of AD have been associated with increased accumulation of Aβ in parietal lobe regions that are anatomically and functionally connected to the medial temporal lobes (MTL) (Buckner et al, 2005; Chételat et al, 2010), with frontal and lateral temporal lobe regions also sites of Aβ accumulation (Masters et al, 2015; Price & Morris, 1999; Schmitt et al, 2000; Sperling et al, 2011).…”

“…Lesion studies have corroborated these neuroimaging findings and shown that EAM retrieval not only depends on the MTL (Cermak & O’Connor, 1983; Grilli & Verfaellie, 2014; Tulving, 1985) but also cortical regions of the episodic memory neural network (Berryhill, Phuong, Picasso, Cabeza, & Olson, 2007; Bertossi, Tesini, Cappelli, & Ciaramelli, 2016). Critically, recent task-based functional magnetic resonance imaging (fMRI) findings (Chen et al, 2017; Monge et al, 2018) have shown that when directly compared to lab-based episodic memory tasks (i.e., comparing the retrieval of episodic autobiographical memories cued by visual images or words to the recollection of prior exposure to visual images and word “chains”), EAM retrieval results in greater activation in the MTL (hippocampus and parahippocampal cortex), as well as connected posterior and anterior cortical regions (i.e., posterior cingulate cortex, retrosplenial cortex, angular gyrus, medial prefrontal cortex, and anterior lateral temporal lobe). Thus, compared to other components of episodic memory, EAM may be more sensitive to subtle changes in an MTL-cortical network that if compromised, increases risk for conversion to AD-related MCI and dementia.…”

Functional networks underlying item and source memory: shared and distinct network components and age-related differences

“…Modules do not function in isolation, and both the links between modules and the links within modules contribute to cognition (Cohen and D’Esposito, 2016; Davis et al, 2017; Grady et al, 2016; Stanley and Brigard, 2016). Several recent studies have demonstrated that modular properties of brain networks shift in response to cognitive demands of the environment (e.g., Cohen and D’Esposito, 2016; Geib et al, 2017a; Monge et al, 2018) and change across the lifespan (e.g., Betzel et al, 2014; Chan et al, 2017; Chan et al, 2014; Gallen et al, 2016; Geerligs et al, 2015; Grady et al, 2016; Monge et al, 2017), making the investigation of these properties worth studying in cognitive aging. To our knowledge, no study has investigated the functional-modular topology underlying IM and SM.…”