From Knowing to Remembering: The Semantic–Episodic Distinction

Renoult, Louis; Irish, Muireann; Moscovitch, Morris; Rugg, Michael D.

doi:10.1016/j.tics.2019.09.008

Cited by 258 publications

(200 citation statements)

References 181 publications

(193 reference statements)

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“…sensory or motor) areas to transmodal, highlevel areas 33,34 . These transmodal areas are thought to facilitate cognitive processes, such as autobiographical memory, in a content-agnostic fashion 16,32,33,[35][36][37] . Intriguingly, however, our data show that place-memory selective subregions exist within each of these default mode network hubs, broadly mirroring the category-selective subdivisions of the visual system 22,38,39 .…”

Section: Fig 1 Distinct Topology Of Place-memory and Scene-perceptimentioning

confidence: 99%

A network linking scene perception and spatial memory systems in posterior cerebral cortex

Steel

Billings

Silson

et al. 2020

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word count: 75 Main text word count: 1,913ABSTRACT Here, we report a new link between the spatial-memory and scene-perception systems of the human brain. Using fine-grained individual-subject fMRI, we describe three cortical areas, each lying immediately anterior to a region of the scene perception network, that are selectively activated when recalling familiar places. Network analyses show that these regions constitute a distinct functional network and interface with memory systems during naturalistic scene understanding. These regions may bridge perception and memory, supporting visually-guided navigation. MAIN TEXTSuccessful navigation requires integrating the current field-of-view with memory of the larger spatial context. While the neural systems supporting visual scene processing in posterior cerebral cortex 1-7 and spatial memory in the hippocampus and medial temporal lobe 8-15 are welldescribed in humans, little is known about how visual and spatio-mnemonic systems interface in the brain. Two disparate lines of inquiry yield different hypotheses. On the one hand, explicit recall of visual scenes (i.e. mental imagery) is thought to reinstate the same activity as perception in visual regions of the brain, including areas of the scene-perception network (parahippocampal place area (PPA), occipital place area (OPA), and medial place area (MPA)) [16][17][18][19] . On the other hand, theories of scene processing have posited that memory-based representations are not colocalized with perceptual representations, but instead, that visual information transitions from perceptual to memory-based representations moving anteriorly from areas of the sceneperception network 1,20-23 . Distinguishing between these possibilities is critical to understanding the neural mechanisms underlying navigation. Do scene perception and place memory share common neural substrates in the human brain?To address these issues, we used individual-subject fMRI to map the topology of sceneperception and place-memory related activity in the human brain in fine-grained detail and assess whether these responses are co-localized at the individual subject level. First, we independently localized the three regions of the scene-perception network by comparing activation when participants viewed images of scenes, people, and objects (Methods). Next, in the same subjects, we localized areas that showed preferential BOLD-activation when participants (N=14) recalled personally familiar places (e.g. their house) and people (e.g. their mother).This analysis revealed a striking topological pattern. In all participants, we found three clusters of place-memory activity proximate to, but distinct from, the three areas of the scene-perception network, which we refer to as 'place-memory areas' for brevity ( Figure 1). Across the lateral, ventral and medial cortical surfaces, the pairs of place-memory and scene-perception areas

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Section: Fig 1 Distinct Topology Of Place-memory and Scene-perceptimentioning

confidence: 99%

A network linking scene perception and spatial memory systems in posterior cerebral cortex

Steel

Billings

Silson

et al. 2020

Preprint

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“…Semantic memory is most often defined as general, culturally shared knowledge, such as knowledge of facts, public events, concepts and people (Binder & Desai, 2011;Hart, et al, 2007;Martin, 2001;Renoult, 2016;Renoult, et al, 2019). It refers to public, accessible information with enough general awareness that it can be shared by members of a culture.…”

Section: Categories Of External Details: Separating Personal From Genmentioning

confidence: 99%

“…Given effects on inferolateral temporal lobe structures mediating semantic knowledge, we predicted that production of general semantics would be reduced in association with damage to these regions (Lambon Ralph, Jefferies, Patterson, & Rogers, 2017;Renoult, Irish, Moscovitch, & Rugg, 2019) as assessed by high resolution structural MRI. Decomposing these external details into different subcategories, Strikwerda-Brown et al (2018) reported that, in their group of dementia patients (SD and Alzheimer's), general semantic details were elevated and, in the case of SD patients, there was no difference in personal semantic details with control participants, an unexpected finding considering the prevalent impairment of semantic memory in SD (Lambon Ralph, Jefferies, Patterson, & Rogers, 2017).…”

Section: Introductionmentioning

confidence: 99%

Classification of general and personal semantic details in the Autobiographical Interview

Renoult¹,

Armson²,

Diamond³

et al. 2020

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The Autobiographical Interview (AI) separates internal (episodic) and external (non-episodic) details from transcribed protocols using an exhaustive and reliable scoring system. While the details comprising the internal composite are centered on elements of episodic memory, external details are more heterogeneous as they are meant to capture a variety of non-episodic utterances: general semantics, different types of personal semantics details, metacognitive statements, repetitions, and details about off topic events. Elevated external details are consistently observed in aging and in neurodegenerative diseases. In the present study, we augmented the AI scoring system to differentiate subtypes of external details to test whether the elevation of these details in aging and frontotemporal lobar degeneration (including mixed frontotemporal/semantic dementia [FTD/SD] and progressive non-fluent aphasia [PNFA]) would be specific to general and personal semantics or would concern all subtypes. Specifically, we separated general semantic details from personal semantic details (including autobiographical facts, self-knowledge, and repeated events). With aging, external detail elevation was observed for general and personal semantic details but not for other types of external details. In frontotemporal lobar degeneration, patients with FTD/SD (but not PNFA) generated an excess of personal semantic details ¬but not general semantic details. The increase in personal but not general semantic details in FTD/SD is consistent with prevalent impairment of general semantic memory in SD, and with the personalization of concepts in this condition. Under standard AI instructions, external details were intended to capture off-topic utterances and were not intended as a direct measure of semantic abilities. Future investigations concerned with semantic processing in aging and in dementia could modify standard instructions of the AI to directly probe semantic content.

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“…A key distinction from the kind of rapid statistical learning tasks employed here is that such semantic memory-based predictions may emanate through spreading activation within neocortex, anatomically shielding them from interference by episodic encoding in the hippocampus. However, whether semantic and episodic memories can be fully dissociated remains unclear (Renoult et al, 2019), suggesting a potential interaction of prediction from semantic memory with episodic memory.…”

Section: Relation To Models Of Learning and Memorymentioning

confidence: 99%

Statistical prediction of the future impairs episodic encoding of the present

Sherman¹,

Turk‐Browne²

2019

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Memory enables reminiscence about past experiences and guides processing of future experiences. However, these two functions are inherently at odds: remembering specific past experiences requires storing idiosyncratic properties, but by definition such properties may not be shared with similar situations in the future and thus are not as useful for prediction. We discovered that, when faced with this conflict, the brain prioritizes prediction over encoding. Behavioral tasks showed that pictures allowing for prediction of what will appear next based on learned regularities are poorly encoded into memory. Brain imaging revealed that predictive representations in the hippocampus may be responsible for this worse episodic encoding and suggested that such interference may result from competition between hippocampal pathways. This tradeoff between statistical learning and episodic memory may be adaptive, focusing encoding on experiences for which we do not yet have a predictive model. whereas statistical learning refers to extracting what is common across mul-5 tiple experiences (e.g., what tends to happen at birthday parties). Episodic memory allows for vivid recollection and nostalgia about past events, whereas statistical learning leads to more generalized knowledge and predictions about new situations. Episodic memory occurs rapidly and stores even related expe-10 riences distinctly in order to minimize interference, whereas statistical learning occurs more slowly and overlays memories in order to represent their common elements or regularities. Given these behavioral and computational differences, theories of memory have argued that these two kinds of information must be processed serially and stored separately in the brain (McClelland et al., 1995; 15 Squire, 2004): episodic memories are formed first in the hippocampus and these memories in turn provide the input for later statistical learning in the neocortex as a result of consolidation (Frankland and Bontempi, 2005; Richards et al., 2014;Tompary and Davachi, 2017).Here we reveal a relationship between episodic memory and statistical learn-20 ing in the reverse direction, whereby learned regularities determine which memories are formed in the first place. Specifically, we examine whether the ability to predict what will appear next -a signature of statistical learning -reduces encoding of the current experience into episodic memory. This hypothesis depends on two theoretical commitments: first, that the adaptive function of memory is 25 to guide future behavior by generating expectations based on prior experience ; second, that memory resources are limited, because of attentional bottlenecks that constrain encoding (Aly and Turk-Browne, 2017) and/or because new encoding interferes with the storage or retrieval of existing memories (Shiffrin and Atkinson, 1969). Accordingly, in allocating memory re-30 sources, we propose that it is less important to encode an ongoing experience when it already generates strong expectations about future states of the world...

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From Knowing to Remembering: The Semantic–Episodic Distinction

Cited by 258 publications

References 181 publications

A network linking scene perception and spatial memory systems in posterior cerebral cortex

A network linking scene perception and spatial memory systems in posterior cerebral cortex

Classification of general and personal semantic details in the Autobiographical Interview

Statistical prediction of the future impairs episodic encoding of the present

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