Emergence of complex dynamics of choice due to repeated exposures to extinction learning.
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ABSTRACT:
SUBMITTER: Donoso JR
PROVIDER: S-EPMC8492564 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Extinction learning refers to the phenomenon that a previously learned response to an environmental stimulus, for example the expression of an aversive behavior upon exposure to a specific context, is reduced when the stimulus is repeatedly presented in the absence of a previously paired aversive event. Extinction of fear memories has been implicated with the treatment of anxiety disease but the molecular processes that underlie fear extinctionare only beginning to emerge. Here we show that fear extinction initiates up-regulation of hippocampal insulin-growth factor 2 (Igf2) and down-regulation of insulin-growth factor binding protein 7 (Igfbp7). In line with this observation we demonstrate that IGF2 facilitates fear extinction, while IGFBP7 impairs fear extinction in an IGF2-dependent manner. Furthermore, we identify one cellular substrate of altered IGF2-signaling during fear extinction. To this end we show that fear extinction-induced IGF2/IGFBP7-signaling promotes the survival of 17-19 day-old newborn hippocampal neurons. In conclusion, our data suggests that therapeutic strategies that enhance IGF2-signaling and adult neurogenesis might be suitable to treat disease linked to excessive fear memory. We employed mice to investigate fear extinction in the hippocampus-dependent contextual fear conditioning paradigm. To this end, male C57BL/6J mice were exposed to the fear conditioning box (context) followed by an electric foot-shock which elicits the acquisition of conditioned contextual fear. For extinction training animals were repeatedly reexposed to the conditioned context on consecutive days (24h interval) without receiving the footshockagain (extinction trial, E). This procedure eventually results in the decline of the aversive freezing behavior. Mice that were exposed to the conditioning context without receiving fear conditioning training served as control groups. To gain a better understanding of the molecular processes underlying fear extinction we performed a genome-wide analysis of the hippocampal transcriptome during fear extinction. In the employed paradigm fear extinction is a gradual process. To capture the longitudinal course of fear extinction we decided to perform hippocampal microarray analysis at two time points: (1) After the first extinction trial (E1) when animals display high levels of aversive freezing behavior and (2) at the extinction trial on which the freezing behavior was significantly reduced when compared to E1. This extinction trial, in the case of this experiment E5, we termed “extinction trial low freezing” (ELF). Mice that were exposed to the conditioning context without receiving fear conditioning training served as control groups (3). For all three groups we hybridized 5 samples (biological replicates).
2011-08-07 | E-GEOD-31063 | biostudies-arrayexpress
Project description:Extinction learning refers to the phenomenon that a previously learned response to an environmental stimulus, for example the expression of an aversive behavior upon exposure to a specific context, is reduced when the stimulus is repeatedly presented in the absence of a previously paired aversive event. Extinction of fear memories has been implicated with the treatment of anxiety disease but the molecular processes that underlie fear extinctionare only beginning to emerge. Here we show that fear extinction initiates up-regulation of hippocampal insulin-growth factor 2 (Igf2) and down-regulation of insulin-growth factor binding protein 7 (Igfbp7). In line with this observation we demonstrate that IGF2 facilitates fear extinction, while IGFBP7 impairs fear extinction in an IGF2-dependent manner. Furthermore, we identify one cellular substrate of altered IGF2-signaling during fear extinction. To this end we show that fear extinction-induced IGF2/IGFBP7-signaling promotes the survival of 17-19 day-old newborn hippocampal neurons. In conclusion, our data suggests that therapeutic strategies that enhance IGF2-signaling and adult neurogenesis might be suitable to treat disease linked to excessive fear memory.
2011-08-08 | GSE31063 | GEO
Project description:IntroductionWe determine whether diminished Learning Over Repeated Exposures (LORE) identifies subtle memory decrements in cognitively unimpaired (CU) older adults with Alzheimer's disease (AD) biomarker burden.MethodsNinety-four CU participants (mean age = 77.6 ± 5.02) completed a challenging associative memory test, at home, monthly, for up to 1 year (mean = 9.97 months) on a study-issued iPad. Learning curves for face-name memory were computed for two versions completed monthly: same face-name pairs (A-A-A) and alternate face-name pairs (B-C-D). Positron emission tomography (PET) imaging characterized global amyloid (Pittsburgh Compound-B (PiB); amyloid beta (Aβ)+/-) and regional tau burden (flortaucipir).ResultsDiminished LORE for same (but not alternate) face-name pairs was associated with greater amyloid and tau burden. Aβ+/- group differences for same face-name pairs emerged by the fourth exposure and was of medium-to-large magnitude (Cohen's d = 0.66; 95% confidence interval [CI] = 0.25-1.08).DiscussionSubtle decrements in learning related to AD pathological burden in CU are detectable over short time-intervals (ie, months). Implications for prevention trial design are discussed.
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Project description:Game theory is the standard tool used to model strategic interactions in evolutionary biology and social science. Traditionally, game theory studies the equilibria of simple games. However, is this useful if the game is complicated, and if not, what is? We define a complicated game as one with many possible moves, and therefore many possible payoffs conditional on those moves. We investigate two-person games in which the players learn based on a type of reinforcement learning called experience-weighted attraction (EWA). By generating games at random, we characterize the learning dynamics under EWA and show that there are three clearly separated regimes: (i) convergence to a unique fixed point, (ii) a huge multiplicity of stable fixed points, and (iii) chaotic behavior. In case (iii), the dimension of the chaotic attractors can be very high, implying that the learning dynamics are effectively random. In the chaotic regime, the total payoffs fluctuate intermittently, showing bursts of rapid change punctuated by periods of quiescence, with heavy tails similar to what is observed in fluid turbulence and financial markets. Our results suggest that, at least for some learning algorithms, there is a large parameter regime for which complicated strategic interactions generate inherently unpredictable behavior that is best described in the language of dynamical systems theory.
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Project description:Measurements of response time (RT) have long been used to infer neural processes underlying various cognitive functions such as working memory, attention, and decision making. However, it is currently unknown if RT is also informative about various stages of value-based choice, particularly how reward values are constructed. To investigate these questions, we analyzed the pattern of RT during a set of multi-dimensional learning and decision-making tasks that can prompt subjects to adopt different learning strategies. In our experiments, subjects could use reward feedback to directly learn reward values associated with possible choice options (object-based learning). Alternatively, they could learn reward values of options' features (e.g. color, shape) and combine these values to estimate reward values for individual options (feature-based learning). We found that RT was slower when the difference between subjects' estimates of reward probabilities for the two alternative objects on a given trial was smaller. Moreover, RT was overall faster when the preceding trial was rewarded or when the previously selected object was present. These effects, however, were mediated by an interaction between these factors such that subjects were faster when the previously selected object was present rather than absent but only after unrewarded trials. Finally, RT reflected the learning strategy (i.e. object-based or feature-based approach) adopted by the subject on a trial-by-trial basis, indicating an overall faster construction of reward value and/or value comparison during object-based learning. Altogether, these results demonstrate that the pattern of RT can be informative about how reward values are learned and constructed during complex value-based learning and decision making.
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Project description:Various physical, social, and biological systems generate complex fluctuations with correlations across multiple time scales. In physiologic systems, these long-range correlations are altered with disease and aging. Such correlated fluctuations in living systems have been attributed to the interaction of multiple control systems; however, the mechanisms underlying this behavior remain unknown. Here, we show that a number of distinct classes of dynamical behaviors, including correlated fluctuations characterized by 1/f scaling of their power spectra, can emerge in networks of simple signaling units. We found that, under general conditions, complex dynamics can be generated by systems fulfilling the following two requirements, (i) a "small-world" topology and (ii) the presence of noise. Our findings support two notable conclusions. First, complex physiologic-like signals can be modeled with a minimal set of components; and second, systems fulfilling conditions i and ii are robust to some degree of degradation (i.e., they will still be able to generate 1/f dynamics).
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Project description:Extinction of contextual fear in rats is enhanced by exposure to a novel environment at 1-2 h before or 1 h after extinction training. This effect is antagonized by administration of protein synthesis inhibitors anisomycin and rapamycin into the hippocampus, but not into the amygdala, immediately after either novelty or extinction training, as well as by the gene expression blocker 5,6-dichloro-1-beta-D-ribofuranosylbenzimidazole administered after novelty training, but not after extinction training. Thus, this effect can be attributed to a mechanism similar to synaptic tagging, through which long-term potentiation can be enhanced by other long-term potentiations or by exposure to a novel environment in a protein synthesis-dependent fashion. Extinction learning produces a tag at the appropriate synapses, whereas novelty learning causes the synthesis of plasticity-related proteins that are captured by the tag, strengthening the synapses that generated this tag.
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