Mechanisms for widespread hippocampal involvement in cognition.

Shohamy, Daphna; Turk‐Browne, Nicholas B.

doi:10.1037/a0034461

Cited by 171 publications

(154 citation statements)

References 145 publications

(200 reference statements)

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“…Our findings also add to a growing body of literature suggesting that HPC supports cognitive tasks beyond the domain of episodic memory (43). The finding that anterior HPC forms concept-specific representations speaks to the debate on HPC's role in representing complex visual objects (44) and classification learning (4).…”

Section: Discussionmentioning

confidence: 70%

Dynamic updating of hippocampal object representations reflects new conceptual knowledge

Mack

Love

Preston

2016

Proc. Natl. Acad. Sci. U.S.A.

207

248

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Concepts organize the relationship among individual stimuli or events by highlighting shared features. Often, new goals require updating conceptual knowledge to reflect relationships based on different goal-relevant features. Here, our aim is to determine how hippocampal (HPC) object representations are organized and updated to reflect changing conceptual knowledge. Participants learned two classification tasks in which successful learning required attention to different stimulus features, thus providing a means to index how representations of individual stimuli are reorganized according to changing task goals. We used a computational learning model to capture how people attended to goal-relevant features and organized object representations based on those features during learning. Using representational similarity analyses of functional magnetic resonance imaging data, we demonstrate that neural representations in left anterior HPC correspond with model predictions of concept organization. Moreover, we show that during early learning, when concept updating is most consequential, HPC is functionally coupled with prefrontal regions. Based on these findings, we propose that when task goals change, object representations in HPC can be organized in new ways, resulting in updated concepts that highlight the features most critical to the new goal.category learning | attention | computational modeling | hippocampus | fMRI C oncepts are organizing principles that define how items or events are similar to one another. Goals are critical to shaping concepts, by emphasizing some shared features over others. When goals change, previously experienced events may be organized in new ways, resulting in an updated concept that highlights the features most critical to the new goal. For instance, consider purchasing a home. One must learn which features make for the most desirable home. A young couple seeking a cosmopolitan lifestyle may organize potential houses based on trendy features like exposed brick walls, a wet bar, and room for vintage record collections. However, with the news of a baby on the way, the couple's goals are likely to shift. After pouring through parenting books and web forums to learn what makes for a child-friendly home, they may look at those previously seen potential homes in a different light. Instead, family-oriented features such as whether or not a home has a bathtub, is within walking distance to a park, and is in a well-respected school district may matter more resulting in a reorganization of which homes are a good buy. At the core of this example are the fundamental challenges we face in flexible goaldirected learning. When learning new concepts (e.g., child-friendly instead of a trendy house), attention changes focus to different information and items that were conceptually dissimilar (e.g., two houses with and without a wet bar) may become more similar (e.g., they both are close to a park) and vice versa (1). Understanding how conceptual knowledge is created and updated during learning is a cen...

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Section: Discussionmentioning

confidence: 70%

Dynamic updating of hippocampal object representations reflects new conceptual knowledge

Mack

Love

Preston

2016

Proc. Natl. Acad. Sci. U.S.A.

207

248

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“…Discussion continues about the nature of declarative memory and about when exactly the hippocampus (and related structures) is involved in learning and memory. One proposal is that, whereas conscious recollection depends on the hippocampus as described above, the hippocampus is also important for unconscious memory under some circumstances (Henke 2010;Hannula and Greene 2012;Shohamy and Turk-Browne 2013). One way to explore this issue has been to record eye movements while volunteers are making behavioral memory judgments.…”

Section: Lr Squire and Ajo Dedementioning

confidence: 99%

Conscious and Unconscious Memory Systems

Squire

Dede

2015

Cold Spring Harb Perspect Biol

271

234

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The idea that memory is not a single mental faculty has a long and interesting history but became a topic of experimental and biologic inquiry only in the mid-20th century. It is now clear that there are different kinds of memory, which are supported by different brain systems. One major distinction can be drawn between working memory and long-term memory. Long-term memory can be separated into declarative (explicit) memory and a collection of nondeclarative (implicit) forms of memory that include habits, skills, priming, and simple forms of conditioning. These memory systems depend variously on the hippocampus and related structures in the parahippocampal gyrus, as well as on the amygdala, the striatum, cerebellum, and the neocortex. This work recounts the discovery of declarative and nondeclarative memory and then describes the nature of declarative memory, working memory, nondeclarative memory, and the relationship between memory systems.T he idea that memory is not a single faculty has a long history. In his Principles of Psychology, William James (1890) wrote separate chapters on memory and habit. Bergson (1910) similarly distinguished between a kind of memory that represents our past and memory that is not representational but nevertheless allows the effect of the past to persist into the present. One finds other antecedents as well. McDougall (1923) wrote about explicit and implicit recognition memory, and Tolman (1948) proposed that there is more than one kind of learning. These early proposals were often expressed as a dichotomy involving two forms of memory. The terminologies differed, but the ideas were similar. Thus, Ryle (1949) distinguished between knowing how and knowing that, and Bruner (1969) identified memory without record and memory with record. Later, the artificial intelligence literature introduced a distinction between declarative and procedural knowledge (Winograd 1975). Yet constructs founded in philosophy and psychology are often abstract and have an uncertain connection to biology, that is, to how the brain actually stores information. History shows that as biological information becomes available about structure and function, understanding becomes more concrete and less dependent on terminology. THE DISCOVERY OF DECLARATIVE AND NONDECLARATIVE MEMORY SYSTEMSBiological and experimental inquiry into these matters began with studies of the noted patient H.M. (Scoville and Milner 1957;Squire 2009).

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“…Theoretical frameworks for working memory call on the interplay of distinct components (12) and their integration in broader cognitive circuits (1). The empirical neuroimaging literature has bolstered these conceptualizations by identifying several distinct sets of brain areas underlying working-memory performance (13)(14)(15)(16)(17).…”

mentioning

confidence: 99%

“…However, emerging evidence indicates that many so-called "domain-general" areas engage in multiple functions, differing from "domain-specific" areas such as primary visual cortex that perform a very specific function (1,2). Such broad engagement is enabled by two fundamental features of brain function: time and interconnectivity.…”

mentioning

confidence: 99%

Dynamic reconfiguration of frontal brain networks during executive cognition in humans

Braun

Schäfer

Walter

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

705

723

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The brain is an inherently dynamic system, and executive cognition requires dynamically reconfiguring, highly evolving networks of brain regions that interact in complex and transient communication patterns. However, a precise characterization of these reconfiguration processes during cognitive function in humans remains elusive. Here, we use a series of techniques developed in the field of "dynamic network neuroscience" to investigate the dynamics of functional brain networks in 344 healthy subjects during a working-memory challenge (the "n-back" task). In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks. This reconfiguration, which characterizes "network flexibility," employs transient and heterogeneous connectivity between frontal systems, which we refer to as "integration." Frontal integration predicted neuropsychological measures requiring working memory and executive cognition, suggesting that dynamic network reconfiguration between frontal systems supports those functions. Our results characterize dynamic reconfiguration of large-scale distributed neural circuits during executive cognition in humans and have implications for understanding impaired cognitive function in disorders affecting connectivity, such as schizophrenia or dementia.

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Mechanisms for widespread hippocampal involvement in cognition.

Cited by 171 publications

References 145 publications

Dynamic updating of hippocampal object representations reflects new conceptual knowledge

Dynamic updating of hippocampal object representations reflects new conceptual knowledge

Conscious and Unconscious Memory Systems

Dynamic reconfiguration of frontal brain networks during executive cognition in humans

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