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The Journal of Neuroscience : the... Nov 2020Many mammals have evolved to be social creatures. In humans, the ability to learn from others' experiences is essential to survival; and from an early age, individuals... (Review)
Review
Many mammals have evolved to be social creatures. In humans, the ability to learn from others' experiences is essential to survival; and from an early age, individuals are surrounded by a social environment that helps them develop a variety of skills, such as walking, talking, and avoiding danger. Similarly, in rodents, behaviors, such as food preference, exploration of novel contexts, and social approach, can be learned through social interaction. Social encounters facilitate new learning and help modify preexisting memories throughout the lifespan of an organism. Moreover, social encounters can help buffer stress or the effects of negative memories, as well as extinguish maladaptive behaviors. Given the importance of such interactions, there has been increasing work studying social learning and applying its concepts in a wide range of fields, including psychotherapy and medical sociology. The process of social learning, including its neural and behavioral mechanisms, has also been a rapidly growing field of interest in neuroscience. However, the term "social learning" has been loosely applied to a variety of psychological phenomena, often without clear definition or delineations. Therefore, this review gives a definition for specific aspects of social learning, provides an overview of previous work at the circuit, systems, and behavioral levels, and finally, introduces new findings on the social modulation of learning. We contextualize such social processes in the brain both through the role of the hippocampus and its capacity to process "social engrams" as well as through the brainwide realization of social experiences. With the integration of new technologies, such as optogenetics, chemogenetics, and calcium imaging, manipulating social engrams will likely offer a novel therapeutic target to enhance the positive buffering effects of social experiences or to inhibit fear-inducing social stimuli in models of anxiety and post-traumatic stress disorder.
Topics: Animals; Humans; Learning; Memory; Optogenetics; Social Behavior; Social Cognition
PubMed: 33177112
DOI: 10.1523/JNEUROSCI.1280-20.2020 -
Neuropsychologia Aug 2020From the perspective of constructivist theories, emotion results from learning assemblies of relevant perceptual, cognitive, interoceptive, and motor processes in...
From the perspective of constructivist theories, emotion results from learning assemblies of relevant perceptual, cognitive, interoceptive, and motor processes in specific situations. Across emotional experiences over time, learned assemblies of processes accumulate in memory that later underlie emotional experiences in similar situations. A neuroimaging experiment guided participants to experience (and thus learn) situated forms of emotion, and then assessed whether participants tended to experience situated forms of the emotion later. During the initial learning phase, some participants immersed themselves in vividly imagined fear and anger experiences involving physical harm, whereas other participants immersed themselves in vividly imagined fear and anger experiences involving negative social evaluation. In the subsequent testing phase, both learning groups experienced fear and anger while their neural activity was assessed with functional magnetic resonance imaging (fMRI). A variety of results indicated that the physical and social learning groups incidentally learned different situated forms of a given emotion. Consistent with constructivist theories, these findings suggest that learning plays a central role in emotion, with emotion adapted to the situations in which it is experienced.
Topics: Adult; Anger; Cognition; Emotions; Fear; Female; Humans; Learning; Memory; Middle Aged; Young Adult
PubMed: 29330097
DOI: 10.1016/j.neuropsychologia.2018.01.008 -
Neurobiology of Learning and Memory Jan 2022Although we can learn new information while asleep, we usually cannot consciously remember the sleep-formed memories - presumably because learning occurred in an...
Although we can learn new information while asleep, we usually cannot consciously remember the sleep-formed memories - presumably because learning occurred in an unconscious state. Here, we ask whether sleep-learning expedites the subsequent awake-learning of the same information. To answer this question, we reanalyzed data (Züst et al., 2019, Curr Biol) from napping participants, who learned new semantic associations between pseudowords and translation-words (guga-ship) while in slow-wave sleep. They retrieved sleep-formed associations unconsciously on an implicit memory test following awakening. Then, participants took five runs of paired-associative learning to probe carry-over effects of sleep-learning on awake-learning. Surprisingly, sleep-learning diminished awake-learning when participants learned semantic associations that were congruent to sleep-learned associations (guga-boat). Yet, learning associations that conflicted with sleep-learned associations (guga-coin) was unimpaired relative to learning new associations (resun-table; baseline). We speculate that the impeded wake-learning originated in a deficient synaptic downscaling and resulting synaptic saturation in neurons that were activated during both sleep-learning and awake-learning.
Topics: Adult; Association Learning; Female; Humans; Learning; Male; Mental Recall; Sleep; Vocabulary; Wakefulness; Young Adult
PubMed: 34863922
DOI: 10.1016/j.nlm.2021.107569 -
Behavioural Processes Mar 2023Learning to stop responding is an important process that allows behavior to adapt to a changing and variable environment. This article reviews recent research in this... (Review)
Review
Learning to stop responding is an important process that allows behavior to adapt to a changing and variable environment. This article reviews recent research in this laboratory and others that has studied how animals learn to stop responding in operant extinction, punishment, and feature-negative learning. Extinction and punishment are shown to be similar in two fundamental ways. First, the response-suppressing effects of both are highly context-specific. Second, the response-suppressing effects of both can be remarkably response-specific: Inhibition of one response transfers little to other responses. Learning to inhibit the response so specifically may result from the correction of "response error," the difference between the level of responding and what the current reinforcer supports. In contrast, the inhibition of responding that develops in feature-negative learning, where the response is reinforced during one discriminative stimulus (A) but not in a compound of A and stimulus B, is less response-specific: The inhibition of responding by stimulus B transfers and inhibits a second response, especially if the second response has itself been inhibited before. The results thus indicate both response-specific and response-general forms of behavioral inhibition. One possibility is that response-specific inhibition is learned when the circumstances encourage the organism to pay attention to the response-to what it is actually doing-as behavioral suppression is learned.
Topics: Animals; Conditioning, Operant; Extinction, Psychological; Learning; Punishment; Inhibition, Psychological
PubMed: 36702436
DOI: 10.1016/j.beproc.2023.104830 -
Current Opinion in Neurobiology Oct 2019The nervous system learns new associations while maintaining memories over long periods, exhibiting a balance between flexibility and stability. Recent experiments... (Review)
Review
The nervous system learns new associations while maintaining memories over long periods, exhibiting a balance between flexibility and stability. Recent experiments reveal that neuronal representations of learned sensorimotor tasks continually change over days and weeks, even after animals have achieved expert behavioral performance. How is learned information stored to allow consistent behavior despite ongoing changes in neuronal activity? What functions could ongoing reconfiguration serve? We highlight recent experimental evidence for such representational drift in sensorimotor systems, and discuss how this fits into a framework of distributed population codes. We identify recent theoretical work that suggests computational roles for drift and argue that the recurrent and distributed nature of sensorimotor representations permits drift while limiting disruptive effects. We propose that representational drift may create error signals between interconnected brain regions that can be used to keep neural codes consistent in the presence of continual change. These concepts suggest experimental and theoretical approaches to studying both learning and maintenance of distributed and adaptive population codes.
Topics: Brain; Learning; Memory; Neurons
PubMed: 31569062
DOI: 10.1016/j.conb.2019.08.005 -
Topics in Cognitive Science Jul 2020Artificial grammar learning (AGL) paradigms have proven to be productive and useful to investigate how young infants break into the grammar of their native language(s).... (Review)
Review
Artificial grammar learning (AGL) paradigms have proven to be productive and useful to investigate how young infants break into the grammar of their native language(s). The question of when infants first show the ability to learn abstract grammatical rules has been central to theoretical debates about the innate vs. learned nature of grammar. The presence of this ability early in development, that is, before considerable experience with language, has been argued to provide evidence for a biologically endowed ability to acquire language. Artificial grammar learning tasks also allow infant populations to be readily compared with adults and non-human animals. Artificial grammar learning paradigms with infants have been used to investigate a number of linguistic phenomena and learning tasks, from word segmentation to phonotactics and morphosyntax. In this review, we focus on AGL studies testing infants' ability to learn grammatical/structural properties of language. Specifically, we discuss the results of AGL studies focusing on repetition-based regularities, the categorization of functors, adjacent and non-adjacent dependencies, and word order. We discuss the implications of the results for a general theory of language acquisition, and we outline some of the open questions and challenges.
Topics: Humans; Infant; Infant Behavior; Language Development; Learning; Linguistics
PubMed: 30554481
DOI: 10.1111/tops.12400 -
Neurobiology of Learning and Memory Sep 2023The Rescorla-Wagner model remains one of the most important and influential theoretical accounts of the conditions under which Pavlovian learning occurs. Moreover, the... (Review)
Review
The Rescorla-Wagner model remains one of the most important and influential theoretical accounts of the conditions under which Pavlovian learning occurs. Moreover, the experimental approaches that inspired the model continue to provide powerful behavioral tools to advance mechanistic understanding of how we and other animals learn to fear and learn to reduce fear. Here we consider key features of the Rescorla-Wagner model as applied to study of fear learning. We review evidence for key insights of the model. First, learning to fear and learning to reduce fear are governed by a common, signed prediction error. Second, this error drives variations in effectiveness of the shock US that are causal to whether and how much fear is learned or lost during a conditioning trial. We also consider behavioral and neural findings inconsistent with the model and which will be essential to understand and advance understanding of fear learning.
Topics: Animals; Conditioning, Classical; Learning; Fear
PubMed: 37442411
DOI: 10.1016/j.nlm.2023.107799 -
PLoS Computational Biology Jun 2022Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM)...
Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) algorithm realizes these forms of computation. It learns sequences in an unsupervised and continuous manner using local learning rules, permits a context specific prediction of future sequence elements, and generates mismatch signals in case the predictions are not met. While the HTM algorithm accounts for a number of biological features such as topographic receptive fields, nonlinear dendritic processing, and sparse connectivity, it is based on abstract discrete-time neuron and synapse dynamics, as well as on plasticity mechanisms that can only partly be related to known biological mechanisms. Here, we devise a continuous-time implementation of the temporal-memory (TM) component of the HTM algorithm, which is based on a recurrent network of spiking neurons with biophysically interpretable variables and parameters. The model learns high-order sequences by means of a structural Hebbian synaptic plasticity mechanism supplemented with a rate-based homeostatic control. In combination with nonlinear dendritic input integration and local inhibitory feedback, this type of plasticity leads to the dynamic self-organization of narrow sequence-specific subnetworks. These subnetworks provide the substrate for a faithful propagation of sparse, synchronous activity, and, thereby, for a robust, context specific prediction of future sequence elements as well as for the autonomous replay of previously learned sequences. By strengthening the link to biology, our implementation facilitates the evaluation of the TM hypothesis based on experimentally accessible quantities. The continuous-time implementation of the TM algorithm permits, in particular, an investigation of the role of sequence timing for sequence learning, prediction and replay. We demonstrate this aspect by studying the effect of the sequence speed on the sequence learning performance and on the speed of autonomous sequence replay.
Topics: Learning; Models, Neurological; Neural Networks, Computer; Neuronal Plasticity; Neurons; Synapses
PubMed: 35727857
DOI: 10.1371/journal.pcbi.1010233 -
Advances in Physiology Education Jun 2019One of the "important peculiarities" of human learning (Bjork RA and Bjork EL. , 1992, p. 35-67) is that certain conditions that produce forgetting-that is, impair... (Review)
Review
One of the "important peculiarities" of human learning (Bjork RA and Bjork EL. , 1992, p. 35-67) is that certain conditions that produce forgetting-that is, impair access to some to-be-learned information studied earlier-also enhance the learning of that information when it is restudied. Such conditions include changing the environmental context from when some to-be-learned material is studied to when that material is restudied; increasing the delay from when something is studied to when it is tested or restudied; and interleaving, rather than blocking, the study or practice of the components of to-be-learned knowledge or skills. In this paper, we provide some conjectures as to why conditions that produce forgetting can also enable learning, and why a misunderstanding of this peculiarity of how humans learn can result in nonoptimal teaching and self-regulated learning.
Topics: Humans; Learning; Memory; Mental Recall; Teaching
PubMed: 30998108
DOI: 10.1152/advan.00001.2019 -
Neuropsychologia Dec 2014Response inhibition is typically considered a hallmark of deliberate executive control. In this article, we review work showing that response inhibition can also become... (Review)
Review
Response inhibition is typically considered a hallmark of deliberate executive control. In this article, we review work showing that response inhibition can also become a 'prepared reflex', readily triggered by information in the environment, or after sufficient training, or a 'learned reflex' triggered by the retrieval of previously acquired associations between stimuli and stopping. We present new results indicating that people can learn various associations, which influence performance in different ways. To account for previous findings and our new results, we present a novel architecture that integrates theories of associative learning, Pavlovian conditioning, and executive response inhibition. Finally, we discuss why this work is also relevant for the study of 'intentional inhibition'.
Topics: Executive Function; Humans; Inhibition, Psychological; Learning; Reflex
PubMed: 25149820
DOI: 10.1016/j.neuropsychologia.2014.08.014