Functional Compartmentalization of the Contribution of Hippocampal Subfields to Context-Dependent Extinction Learning

Méndez-Couz, Marta; Becker, Jana M; Manahan‐Vaughan, Denise

doi:10.3389/fnbeh.2019.00256

Cited by 13 publications

(15 citation statements)

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“…If systems consolidation was altered during this period, extinction learning would still be retained, but the association learned during acquisition would be overwritten and hence there would be no renewal. In line with this interpretation, recent findings suggest that extinction learning and renewal engage similar hippocampal subregions and neuronal populations 13 , thus, suggesting that manipulating the hippocampus can have an impact on prior learned experience and thus, subsequent renewal.…”

Section: Discussionmentioning

confidence: 62%

“…In particular, André and Manahan-Vaughan found that intracerebral administration of a dopamine receptor agonist, which alters synaptic plasticity in the hippocampus 12 , reduced the context-dependent expression of renewal in an appetitive ABA renewal task in a T-maze 9 . This task depends on the the specific involvement of certain subfields of the hippocampus 13 .…”

Section: Introductionmentioning

confidence: 99%

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Context-dependent extinction learning emerging from raw sensory inputs: a reinforcement learning approach

Walther

Diekmann

Vijayabaskaran

et al. 2021

Sci Rep

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The context-dependence of extinction learning has been well studied and requires the hippocampus. However, the underlying neural mechanisms are still poorly understood. Using memory-driven reinforcement learning and deep neural networks, we developed a model that learns to navigate autonomously in biologically realistic virtual reality environments based on raw camera inputs alone. Neither is context represented explicitly in our model, nor is context change signaled. We find that memory-intact agents learn distinct context representations, and develop ABA renewal, whereas memory-impaired agents do not. These findings reproduce the behavior of control and hippocampal animals, respectively. We therefore propose that the role of the hippocampus in the context-dependence of extinction learning might stem from its function in episodic-like memory and not in context-representation per se. We conclude that context-dependence can emerge from raw visual inputs.

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Section: Discussionmentioning

confidence: 62%

Section: Introductionmentioning

confidence: 99%

Context-dependent extinction learning emerging from raw sensory inputs: a reinforcement learning approach

Walther

Diekmann

Vijayabaskaran

et al. 2021

Sci Rep

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“…Spatial appetitive EL recruits hippocampal gene encoding (Mendez-Couz et al, 2019). As yet, it is unclear to what extent this process involves hippocampal synaptic plasticity, but context-dependent forms of synaptic plasticity that are triggered by learning have been reported (Manahan-Vaughan and Braunewell, 1999;Kemp and Manahan-Vaughan, 2004).…”

Section: Discussionmentioning

confidence: 99%

“…EL in the absence of a context change also depends on activation of the metabotropic glutamate receptor, mGlu5, whereas context-dependent EL does not (Andre et al, 2015a). Context-dependent EL recruits information processing in the hippocampus that involves gene encoding (Mendez-Couz et al, 2019), a process that has been linked to hippocampal synaptic plasticity (Kemp et al, 2013) and to context-dependent spatial learning (Hoang et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Genetic depletion of BDNF impairs both context-dependent and context-independent extinction learning of a spatial appetitive task

Méndez-Couz

Manahan‐Vaughan

2021

Preprint

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Brain derived neurotropic factor (BDNF) supports neuronal survival, growth, and differentiation and is involved in forms of hippocampus-dependent learning, as well as hippocampus-dependent learning. Extinction learning (EL) comprises active inhibition of no-longer relevant learned information, in conjunction with a decreased response of a previously learned behavior. It is highly dependent on context, and evidence exists that it requires hippocampal activation. Concordantly, the participation of BDNF in hippocampus-dependent memory is experience-dependent. BDNF has been associated with synaptic plasticity needed for acquisition and extinction learning of fear conditioning. However, little is known about its influence on the extinction and renewal of spatial appetitive extinction learning (EL). In this study, in BDNF+/−-mice we evaluated to what extent BDNF contributes to spatial appetitive EL in the presence (ABA) or absence (AAA) of a context change. Daily training, to reach acquisition criterion in a T-maze, resulted in a similar outcome in BDNF+/−-mice or their wildtype (wt) littermates. EL was delayed in the AAA, and significantly impaired in the ABA-context compared to EL in wt littermates. When renewal was tested in the ABA paradigm we detected a significant response in wt controls, but not in BDNF+/−-mice. Taken together, these results support an important role for BDNF in EL in AAA and ABA context, as well as renewal of a spatial appetitive task, processes that relate to information updating and retrieval.

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“…During a subsequent extinction phase, this rat can choose between at least four equally non-reinforced behaviors: turn left, turn right, return to the starting point before reaching the decision point, and refuse to leave the starting point altogether. Nevertheless, a typical analysis focuses only on the cessation of the previously conditioned response, in this case, turning right (28,29) . In this way, the effect of extinction learning on choice behavior remains undisclosed.…”

Section: Introductionmentioning

confidence: 99%

Emergence of complex dynamics of choice due to repeated exposures to extinction learning

Donoso

Packheiser

Pusch

et al. 2020

Preprint

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Extinction learning, the process of ceasing an acquired behavior in response to altered reinforcement contingencies, is essential for survival in a changing environment. So far, research has mostly neglected the learning dynamics and variability of behavior during extinction learning and instead focused on a few response types that were studied by population averages. Here, we take a different approach by analyzing the trial-by-trial dynamics of operant extinction learning in both pigeons and a computational model. The task involved discriminant operant conditioning in context A, extinction in context B, and a return to context A to test the context-dependent return of the conditioned response (ABA renewal). By studying single learning curves across animals under repeated sessions of this paradigm, we uncovered a rich variability of behavior during extinction learning: (1) Pigeons prefer the unrewarded alternative choice in one-third of the sessions, predominantly during the very first extinction session an animal encountered. (2) In later sessions, abrupt transitions of behavior at the onset of context B emerge, and (3) the renewal effect decays as sessions progress. While these results could be interpreted in terms of rule learning mechanisms, we show that they can be parsimoniously accounted for by a computational model based only on associative learning between stimuli and actions. Our work thus demonstrates the critical importance of studying the trial-by-trial dynamics of learning in individual sessions, and the unexpected power of "simple" associative learning processes. Significance StatementOperant conditioning is essential for the discovery of purposeful actions, but once a stimulus-response association is acquired, the ability to extinguish it in response to altered reward contingencies is equally important. These processes also play a fundamental role in the development and treatment of pathological behaviors such as drug addiction, overeating and gambling. Here we show that extinction learning is not limited to the cessation of a previously reinforced response, but also drives the emergence of complex and variable choices that change from learning session to learning session. At first sight, these behavioral changes appear to reflect abstract rule learning, but we show in a computational model that they can emerge from "simple" associative learning.

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Functional Compartmentalization of the Contribution of Hippocampal Subfields to Context-Dependent Extinction Learning

Cited by 13 publications

References 59 publications

Context-dependent extinction learning emerging from raw sensory inputs: a reinforcement learning approach

Context-dependent extinction learning emerging from raw sensory inputs: a reinforcement learning approach

Genetic depletion of BDNF impairs both context-dependent and context-independent extinction learning of a spatial appetitive task

Emergence of complex dynamics of choice due to repeated exposures to extinction learning

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