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Cortex; a Journal Devoted To the Study... 2010In this review results of human lesion studies are compared examining associative learning in the motor, emotional and cognitive domain. Motor and emotional learning... (Review)
Review
In this review results of human lesion studies are compared examining associative learning in the motor, emotional and cognitive domain. Motor and emotional learning were assessed using classical eyeblink and fear conditioning. Cerebellar patients were significantly impaired in acquisition of conditioned eyeblink and fear-related autonomic and skeletal responses. An additional finding was disordered timing of conditioned eyeblink responses. Cognitive learning was examined using stimulus-stimulus-response paradigms, with an experimental set-up closely related to classical conditioning paradigms. Cerebellar patients were impaired in the association of two visual stimuli, which could not be related to motor performance deficits. Human lesion and functional brain imaging studies in healthy subjects are in accordance with a functional compartmentalization of the cerebellum for different forms of associative learning. The medial zone appears to contribute to fear conditioning and the intermediate zone to eyeblink conditioning. The posterolateral hemispheres (that is lateral cerebellum) appear to be of additional importance in fear conditioning in humans. Future studies need to examine the reasonable assumption that the posterolateral cerebellum contributes also to higher cognitive forms of associative learning. Human cerebellar lesion studies provide evidence that the cerebellum is involved in motor, emotional and cognitive associative learning. Because of its simple and homogeneous micro-circuitry a common computation may underly cerebellar involvement in these different forms of associative learning. The overall task of the cerebellum may be the ability to provide correct predictions about the relationship between sensory stimuli.
Topics: Association Learning; Cerebellum; Cognition; Emotions; Humans; Motor Skills
PubMed: 19665115
DOI: 10.1016/j.cortex.2009.06.009 -
Annual Review of Psychology 1997The scientific study of associative learning began nearly 100 years ago with the pioneering studies of Thorndike and Pavlov, and it continues today as an active area of... (Review)
Review
The scientific study of associative learning began nearly 100 years ago with the pioneering studies of Thorndike and Pavlov, and it continues today as an active area of research and theory. Associative learning should be the foundation for our understanding of other forms of behavior and cognition in human and nonhuman animals. The laws of associative learning are complex, and many modern theorists posit the involvement of attention, memory, and information processing in such basic conditioning phenomena as overshadowing and blocking, and the effects of stimulus preexposure on later conditioning. An unresolved problem for learning theory is distinguishing the formation of associations from their behavioral expression. This and other problems will occupy future generations of behavioral scientists interested in the experimental investigation of associative learning. Neuroscientists and cognitive scientists will both contribute to and benefit from that effort in the next 100 years of inquiry.
Topics: Animals; Association Learning; Attention; Brain; Conditioning, Classical; Humans; Mental Recall; Neurosciences
PubMed: 9046569
DOI: 10.1146/annurev.psych.48.1.573 -
Cognitive Science Mar 2016Cross-situational statistical learning of words involves tracking co-occurrences of auditory words and objects across time to infer word-referent mappings. Previous...
Cross-situational statistical learning of words involves tracking co-occurrences of auditory words and objects across time to infer word-referent mappings. Previous research has demonstrated that learners can infer referents across sets of very phonologically distinct words (e.g., WUG, DAX), but it remains unknown whether learners can encode fine phonological differences during cross-situational statistical learning. This study examined learners' cross-situational statistical learning of minimal pairs that differed on one consonant segment (e.g., BON-TON), minimal pairs that differed on one vowel segment (e.g., DEET-DIT), and non-minimal pairs that differed on two or three segments (e.g., BON-DEET). Learners performed above chance for all pairs, but performed worse on vowel minimal pairs than on consonant minimal pairs or non-minimal pairs. These findings demonstrate that learners can encode fine phonetic detail while tracking word-referent co-occurrence probabilities, but they suggest that phonological encoding may be weaker for vowels than for consonants.
Topics: Adolescent; Adult; Association Learning; Attention; Female; Humans; Male; Neuropsychological Tests; Probability Learning; Vocabulary; Young Adult
PubMed: 25866868
DOI: 10.1111/cogs.12243 -
Neural Networks : the Official Journal... Mar 2002Recognition-by-components is one of the possible strategies proposed for object recognition by the brain, but little is known about the low-level mechanism by which the...
Recognition-by-components is one of the possible strategies proposed for object recognition by the brain, but little is known about the low-level mechanism by which the parts of objects can be learned without a priori knowledge. Recent work by Lee and Seung (Nature 401 (1999) 788) shows the importance of non-negativity constraints in the building of such models. Here we propose a simple feedforward neural network that is able to learn the parts of objects by the auto-association of sensory stimuli. The network is trained to reproduce each input with only excitatory interactions. When applied to a database of facial images, the network extracts localized features that resemble intuitive notion of the parts of faces. This kind of localized, parts-based internal representation is very different from the holistic representation created by the unconstrained network, which emulates principal component analysis. Furthermore, the simple model has some ability to minimize the number of active hidden units for certain tasks and is robust when a mixture of different stimuli is presented.
Topics: Algorithms; Association Learning; Face; Neural Networks, Computer; Pattern Recognition, Automated; Recognition, Psychology
PubMed: 12022515
DOI: 10.1016/s0893-6080(01)00145-9 -
Behavioural Processes Jan 2014We understand time through our models of it. These are typically models of our physical chronometers, which we then project into our subjects. A few of these models of... (Review)
Review
We understand time through our models of it. These are typically models of our physical chronometers, which we then project into our subjects. A few of these models of the nature of time and its effects on the behavior of organisms are reviewed. New models, such as thermodynamics and spectral decomposition, are recommended for the potential insights that they afford. In all cases, associations are essential features of timing. To make them, time must be discretized by stimuli such as hours, minutes, conditioned stimuli, trials, and contexts in general. Any one association is seldom completely dominant, but rather shares control through proximity in a multidimensional space, important dimensions of which may include physical space and time as rendered by Fourier transforms.
Topics: Association Learning; Computer Simulation; Humans; Models, Theoretical; Time; Time Perception
PubMed: 23973706
DOI: 10.1016/j.beproc.2013.08.003 -
Cognitive Psychology Sep 2017Word learning is a notoriously difficult induction problem because meaning is underdetermined by positive examples. How do children solve this problem? Some have argued...
Word learning is a notoriously difficult induction problem because meaning is underdetermined by positive examples. How do children solve this problem? Some have argued that word learning is achieved by means of inference: young word learners rely on a number of assumptions that reduce the overall hypothesis space by favoring some meanings over others. However, these approaches have difficulty explaining how words are learned from conversations or text, without pointing or explicit instruction. In this research, we propose an associative mechanism that can account for such learning. In a series of experiments, 4-year-olds and adults were presented with sets of words that included a single nonsense word (e.g. dax). Some lists were taxonomic (i.,e., all items were members of a given category), some were associative (i.e., all items were associates of a given category, but not members), and some were mixed. Participants were asked to indicate whether the nonsense word was an animal or an artifact. Adults exhibited evidence of learning when lists consisted of either associatively or taxonomically related items. In contrast, children exhibited evidence of word learning only when lists consisted of associatively related items. These results present challenges to several extant models of word learning, and a new model based on the distinction between syntagmatic and paradigmatic associations is proposed.
Topics: Adult; Association Learning; Child, Preschool; Female; Humans; Language Development; Male; Models, Psychological; Verbal Learning; Vocabulary
PubMed: 28641208
DOI: 10.1016/j.cogpsych.2017.06.001 -
Behavioural Processes May 2014Propositional models of associative learning postulate that the behavioral impact of regularities in the presence of two events is mediated by the formation of... (Review)
Review
Propositional models of associative learning postulate that the behavioral impact of regularities in the presence of two events is mediated by the formation of propositions about the relation between these events. Because the mere statistical contingency between events often does not provide enough information to infer the nature of the relation between those events (e.g., whether one event is a cause or an effect of the other event), it is likely that people will take into account relational information that is provided by the context when forming propositions about the relation between events. Hence, propositional models predict that contextual cues which provide relational information can moderate associative learning. The present paper provides a brief review of several studies that support this prediction. These findings contribute not only to the cognitive literature on the mental mechanisms that mediate associative learning but also to the functional literature on associative learning by providing novel evidence for arbitrarily applicable relational responding. Vice versa, functional research on relational responding can provide a new source of information for the development of cognitive theories of associative learning. This article is part of a Special Issue entitled: SQAB 2013.
Topics: Association Learning; Cognition; Humans; Models, Psychological
PubMed: 24518680
DOI: 10.1016/j.beproc.2014.02.002 -
Learning & Behavior Mar 2012We present and test an instance model of associative learning. The model, Minerva-AL, treats associative learning as cued recall. Memory preserves the events of...
We present and test an instance model of associative learning. The model, Minerva-AL, treats associative learning as cued recall. Memory preserves the events of individual trials in separate traces. A probe presented to memory contacts all traces in parallel and retrieves a weighted sum of the traces, a structure called the echo. Learning of a cue-outcome relationship is measured by the cue's ability to retrieve a target outcome. The theory predicts a number of associative learning phenomena, including acquisition, extinction, reacquisition, conditioned inhibition, external inhibition, latent inhibition, discrimination, generalization, blocking, overshadowing, overexpectation, superconditioning, recovery from blocking, recovery from overshadowing, recovery from overexpectation, backward blocking, backward conditioned inhibition, and second-order retrospective revaluation. We argue that associative learning is consistent with an instance-based approach to learning and memory.
Topics: Association Learning; Conditioning, Classical; Cues; Extinction, Psychological; Inhibition, Psychological; Memory; Models, Psychological
PubMed: 21913057
DOI: 10.3758/s13420-011-0046-2 -
PLoS Computational Biology Nov 2015Two important ideas about associative learning have emerged in recent decades: (1) Animals are Bayesian learners, tracking their uncertainty about associations; and (2)...
Two important ideas about associative learning have emerged in recent decades: (1) Animals are Bayesian learners, tracking their uncertainty about associations; and (2) animals acquire long-term reward predictions through reinforcement learning. Both of these ideas are normative, in the sense that they are derived from rational design principles. They are also descriptive, capturing a wide range of empirical phenomena that troubled earlier theories. This article describes a unifying framework encompassing Bayesian and reinforcement learning theories of associative learning. Each perspective captures a different aspect of associative learning, and their synthesis offers insight into phenomena that neither perspective can explain on its own.
Topics: Algorithms; Animals; Association Learning; Bayes Theorem; Computational Biology; Humans; Models, Neurological
PubMed: 26535896
DOI: 10.1371/journal.pcbi.1004567 -
Journal of Experimental Psychology.... Oct 2019Many theories of conditioning describe learning as a process by which stored information about the relationship between a conditioned stimulus (CS) and unconditioned... (Review)
Review
Many theories of conditioning describe learning as a process by which stored information about the relationship between a conditioned stimulus (CS) and unconditioned stimulus (US) is progressively updated upon each occasion (trial) that the CS occurs with, or without, the US. These simple trial-based descriptions can provide a powerful and efficient means of extracting information about the correlation between 2 events, but they fail to explain how animals learn about the timing of events. This failure has motivated models of conditioning in which animals learn continuously, either by explicitly representing temporal intervals between events or by sequentially updating an array of associations between temporally distributed elements of the CS and US. Here, I review evidence that some aspects of conditioning are not the consequence of a continuous learning process but reflect a trial-based process. In particular, the way that animals learn about the absence of a predicted US during extinction suggests that they encode and remember trials as single complete episodes rather than as a continuous experience of unfulfilled expectation of the US. These memories allow the animal to recognize repeated instances of nonreinforcement and encode these as a sequence that, in the case of a partial reinforcement schedule, can become associated with the US. The animal is thus able to remember details about the pattern of a CS's reinforcement history, information that affects how long the animal continues to respond to the CS when all reinforcement ceases. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Topics: Animals; Association Learning; Behavior, Animal; Conditioning, Classical; Reinforcement, Psychology
PubMed: 31414879
DOI: 10.1037/xan0000223