-
Learning & Memory (Cold Spring Harbor,... 2004Human conditioning research shows that learning is closely related to consciously available contingency knowledge, requires attentional resources, and is influenced by... (Review)
Review
Human conditioning research shows that learning is closely related to consciously available contingency knowledge, requires attentional resources, and is influenced by language. This research suggests a cognitive model in which extinction consists of changes in contingency beliefs in long-term memory. Laboratory and clinical evidence on extinction is briefly reviewed, and it is concluded that the evidence supports the cognitive position. There is little evidence for a separate, noncognitive conditioning system. The primary implication for neural analysis is that learning and extinction are unlikely to be reducible to direct connections in which one stimulus simply activates or inhibits the memory representation of another. Rather, an adequate neural model will involve the integration of both low-level and high-level systems, including attention, representation of stimulus relations in long-term memory, and a dynamic performance mechanism based on anticipation, not just activation.
Topics: Animals; Association Learning; Attention; Cognition; Conditioning, Classical; Consciousness; Extinction, Psychological; Humans; Models, Neurological
PubMed: 15466299
DOI: 10.1101/lm.79604 -
Hippocampus 1995Sutherland and Rudy ([1989] Psychobiology 17:129-144) proposed that the hippocampal system is critical to normal learning and memory because of its function as the... (Review)
Review
Sutherland and Rudy ([1989] Psychobiology 17:129-144) proposed that the hippocampal system is critical to normal learning and memory because of its function as the central part of a configural association system. This system constructs a unique representation of the joint occurrence of the independent elements of a compound. There is evidence consistent with the theory's predictions, however, there also are data that unambiguously demonstrate that, under some conditions, animals lacking an intact hippocampal system acquire configural associations. Thus, Sutherland and Rudy's fundamental assumption cannot be correct. To integrate the supporting and contradictory data, we propose two simple modifications of our position: 1) The critical neural system for configural associations is in cortical circuitry outside the hippocampus, and 2) the output from the hippocampal formation contributes to configural processing by selectively enhancing, thereby making more salient, cortical units representing stimulus conjunctions. This enhancement has two important effects: 1) It decreases the similarity between the configural units representing the co-occurrence of cues and the units representing the cues, and 2) It increases the rate at which the configural units can acquire associative strength. The modified theory explains why damage to the hippocampal formation only impairs learning on a subset of nonlinear discrimination problems. It also integrates recent data on the effects of hippocampal formation damage on conditioning involving context cues and makes novel predictions about performance on nonlinear discrimination problems and place learning.
Topics: Association Learning; Hippocampus; Humans; Memory
PubMed: 8773252
DOI: 10.1002/hipo.450050502 -
Journal of Cognitive Neuroscience Oct 2018Learning to make rewarding choices in response to stimuli depends on a slow but steady process, reinforcement learning, and a fast and flexible, but capacity-limited...
Learning to make rewarding choices in response to stimuli depends on a slow but steady process, reinforcement learning, and a fast and flexible, but capacity-limited process, working memory. Using both systems in parallel, with their contributions weighted based on performance, should allow us to leverage the best of each system: rapid early learning, supplemented by long-term robust acquisition. However, this assumes that using one process does not interfere with the other. We use computational modeling to investigate the interactions between the two processes in a behavioral experiment and show that working memory interferes with reinforcement learning. Previous research showed that neural representations of reward prediction errors, a key marker of reinforcement learning, were blunted when working memory was used for learning. We thus predicted that arbitrating in favor of working memory to learn faster in simple problems would weaken the reinforcement learning process. We tested this by measuring performance in a delayed testing phase where the use of working memory was impossible, and thus participant choices depended on reinforcement learning. Counterintuitively, but confirming our predictions, we observed that associations learned most easily were retained worse than associations learned slower: Using working memory to learn quickly came at the cost of long-term retention. Computational modeling confirmed that this could only be accounted for by working memory interference in reinforcement learning computations. These results further our understanding of how multiple systems contribute in parallel to human learning and may have important applications for education and computational psychiatry.
Topics: Adolescent; Adult; Association Learning; Computer Simulation; Female; Humans; Male; Memory, Short-Term; Reinforcement, Psychology; Young Adult
PubMed: 29346018
DOI: 10.1162/jocn_a_01238 -
Progress in Neurobiology Nov 2015We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are... (Review)
Review
We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a synthesis these classical processes and cast them as successive hierarchical contextualisations of sensorimotor constructs, using the generative models that underpin Active Inference. This dissolves any apparent mechanistic distinction between the optimization processes that mediate classical control or learning. Furthermore, we generalize the scope of Active Inference by emphasizing interoceptive inference and homeostatic regulation. The ensuing homeostatic (or allostatic) perspective provides an intuitive explanation for how priors act as drives or goals to enslave action, and emphasises the embodied nature of inference.
Topics: Animals; Association Learning; Behavior; Brain; Homeostasis; Humans; Models, Neurological; Models, Psychological
PubMed: 26365173
DOI: 10.1016/j.pneurobio.2015.09.001 -
Neurobiology of Learning and Memory Jan 2019The multiple memory systems theory (MMS) postulates that the brain stores information based on the independent and parallel activity of a number of modules, each with... (Review)
Review
The multiple memory systems theory (MMS) postulates that the brain stores information based on the independent and parallel activity of a number of modules, each with distinct properties, dynamics, and neural basis. Much of the evidence for this theory comes from dissociation studies indicating that damage to restricted brain areas cause selective types of memory deficits. MMS has been the prevalent paradigm in memory research for more than thirty years, even as it has been adjusted several times to accommodate new data. However, recent empirical results indicating that the memory systems are not always dissociable constitute a challenge to fundamental tenets of the current theory because they suggest that representations formed by individual memory systems can contribute to more than one type of memory-driven behavioral strategy. This problem can be addressed by applying a dynamic network perspective to memory architecture. According to this view, memory networks can reconfigure or transiently couple in response to environmental demands. Within this context, the neural network underlying a specific memory system can act as an independent unit or as an integrated component of a higher order meta-network. This dynamic network model proposes a way in which empirical evidence that challenges the idea of distinct memory systems can be incorporated within a modular memory architecture. The model also provides a framework to account for the complex interactions among memory systems demonstrated at the behavioral level. Advances in the study of dynamic networks can generate new ideas to experimentally manipulate and control memory in basic or clinical research.
Topics: Animals; Association Learning; Brain; Humans; Memory; Models, Neurological; Models, Psychological; Psychological Theory
PubMed: 30439565
DOI: 10.1016/j.nlm.2018.11.005 -
Neurobiology of Learning and Memory Jul 2017Although Attention-Deficit Hyperactivity Disorder (ADHD) is closely linked to executive function deficits, it has recently been attributed to procedural learning...
Although Attention-Deficit Hyperactivity Disorder (ADHD) is closely linked to executive function deficits, it has recently been attributed to procedural learning impairments that are quite distinct from the former. These observations challenge the ability of the executive function framework solely to account for the diverse range of symptoms observed in ADHD. A recent neurocomputational model emphasizes the role of striatal dopamine (DA) in explaining ADHD's broad range of deficits, but the link between this model and procedural learning impairments remains unclear. Significantly, feedback-based procedural learning is hypothesized to be disrupted in ADHD because of the involvement of striatal DA in this type of learning. In order to test this assumption, we employed two variants of a probabilistic category learning task known from the neuropsychological literature. Feedback-based (FB) and paired associate-based (PA) probabilistic category learning were employed in a non-medicated sample of ADHD participants and neurotypical participants. In the FB task, participants learned associations between cues and outcomes initially by guessing and subsequently through feedback indicating the correctness of the response. In the PA learning task, participants viewed the cue and its associated outcome simultaneously without receiving an overt response or corrective feedback. In both tasks, participants were trained across 150 trials. Learning was assessed in a subsequent test without a presentation of the outcome or corrective feedback. Results revealed an interesting disassociation in which ADHD participants performed as well as control participants in the PA task, but were impaired compared with the controls in the FB task. The learning curve during FB training differed between the two groups. Taken together, these results suggest that the ability to incrementally learn by feedback is selectively disrupted in ADHD participants. These results are discussed in relation to both the ADHD dopaminergic dysfunction model and recent findings implicating procedural learning impairments in those with ADHD.
Topics: Adult; Association Learning; Attention Deficit Disorder with Hyperactivity; Feedback; Humans; Male; Probability Learning; Young Adult
PubMed: 28478078
DOI: 10.1016/j.nlm.2017.04.012 -
Journal of Experimental Psychology.... Apr 2022Inhibitory learning after feature negative training (A+/AB-) is typically measured by combining the Feature B with a separately trained excitor (e.g., C) in a summation...
Inhibitory learning after feature negative training (A+/AB-) is typically measured by combining the Feature B with a separately trained excitor (e.g., C) in a summation test. Reduced responding to C is taken as evidence that B has properties directly opposite to those of C. However, in human causal learning, transfer of B's inhibitory properties to another excitor is modest and depends on individual differences in inferred causal structure. Here we ask whether instead of opposing processes, a summation test might instead be thought of in terms of generalization. Using an allergist task, we tested whether inhibitory transfer would be influenced by similarity. We found that transfer was greater when the test stimuli were from the same semantic category as the training stimuli (Experiments 1 and 2) and when the test excitor had previously been associated with the same outcome (Experiment 3). We also found that the similarity effect applied across all self-reported causal structures. We conclude it may be more helpful to consider transfer of inhibition as a form of conceptual generalization rather than the arithmetic summation of opposing processes. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Topics: Association Learning; Conditioning, Classical; Generalization, Psychological; Humans; Individuality; Learning
PubMed: 35533103
DOI: 10.1037/xan0000320 -
Acta Psychologica Jan 2014This article reviews situations in which stimuli produce an increase or a decrease in nociceptive responses through basic associative processes and provides an... (Review)
Review
This article reviews situations in which stimuli produce an increase or a decrease in nociceptive responses through basic associative processes and provides an associative account of such changes. Specifically, the literature suggests that cues associated with stress can produce conditioned analgesia or conditioned hyperalgesia, depending on the properties of the conditioned stimulus (e.g., contextual cues and audiovisual cues vs. gustatory and olfactory cues, respectively) and the proprieties of the unconditioned stimulus (e.g., appetitive, aversive, or analgesic, respectively). When such cues are associated with reducers of exogenous pain (e.g., opiates), they typically increase sensitivity to pain. Overall, the evidence concerning conditioned stress-induced analgesia, conditioned hyperalagesia, conditioned tolerance to morphine, and conditioned reduction of morphine analgesia suggests that selective associations between stimuli underlie changes in pain sensitivity.
Topics: Analgesia; Analgesics, Opioid; Association Learning; Conditioning, Classical; Cues; Drug Tolerance; Humans; Hyperalgesia; Morphine; Smell; Stress, Psychological
PubMed: 24269884
DOI: 10.1016/j.actpsy.2013.10.009 -
Journal of Experimental Psychology.... Aug 2016Adaptive behaviors are believed to be shaped by both positive (the strengthening of correct associations) and negative (the pruning of incorrect associations or the...
Adaptive behaviors are believed to be shaped by both positive (the strengthening of correct associations) and negative (the pruning of incorrect associations or the building of inhibitory associations) forms of associative learning. However, there has been little direct documentation of how these basic processes participate in the learning of rich associative networks that support cognitive behaviors like categorization. Although negative associative learning is an important component of theories of development, it is not clear whether it involves acquiring specific (experience-dependent) content or represents a more general aspect of (experience-expectant) development. The authors thus trained pigeons on a complex many-to-many learning paradigm previously established as an analog to human word learning. Pigeons learned to map 16 objects onto 16 distinct report tokens; the authors manipulated the amount of negative associative learning that could occur by restricting which tokens were available as incorrect options. In testing, accuracy was lower on trials with foils that had not been presented with a target than on trials with previously experienced foils. Moreover, when the correct token was withheld, pigeons preferred foils novel to the target object over previously experienced foils. A second experiment replicated these results and further found that these effects only emerged after some positive associations had been acquired. Findings indicate that the learning of rich associative networks does not depend solely on positive associative learning, but also on negative associative learning; this conclusion has important implications for basic learning theories in both animals and humans, as well as for theories of development. (PsycINFO Database Record
Topics: Adaptation, Psychological; Animals; Association Learning; Columbidae; Models, Psychological; Verbal Learning
PubMed: 27336324
DOI: 10.1037/xge0000187 -
Behavioural Processes Mar 2018Habitat selection is fundamentally important to animal ecology, and animals that can learn about habitats can increase the probability of avoiding detection by predators...
Habitat selection is fundamentally important to animal ecology, and animals that can learn about habitats can increase the probability of avoiding detection by predators or quickly finding food. Here, we tested whether juveniles of the red swamp crayfish, Procambarus clarkii, can learn preference for habitat types based on experience with food availability. Crayfish were housed in arenas with two habitat types, half leaf habitat and half rock habitat. Over several days, crayfish were fed consistently in one of the habitat types. Initial tests revealed that crayfish had an innate preference for the leaf habitat, but conditioning over 2-3 weeks was sufficient to shift this preference to the rock habitat based on habitat cues rather than other spatial cues in their environment. The ability to learn the relevance of habitat features may be an important trait for the colonization success, and subsequent impact, of introduced species.
Topics: Animals; Association Learning; Astacoidea; Cues; Ecology; Ecosystem; Risk Factors
PubMed: 29330086
DOI: 10.1016/j.beproc.2018.01.006