Naturalistic Learning
Naturalistic Learning - Related Videos
02:30
Naturalistic Observations
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2020
If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
10:36
fMRI Validation of fNIRS Measurements During a Naturalistic Task
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Cited by 107 •
2015
We present a method to compare functional brain activity recorded during a naturalistic task using fNIRS with activity recorded during fMRI.
14:38
Creating Objects and Object Categories for Studying Perception and Perceptual Learning
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Cited by 12 •
2012
We describe a novel methodology for creating naturalistic 3-D objects and object categories with precisely defined feature variations. We use simulations of the biological processes of morphogenesis and phylogenesis to create novel, naturalistic virtual 3-D objects and object categories that can then be rendered as visual images or haptic objects.
10:06
An Introduction to Learning and Memory
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2023
Learning is the process of acquiring new information and memory is the retention or storage of that information. Different types of learning, such as non-associative and associative learning, and different types of memory, such as long-term and short-term memory, have been associated with human behaviors. Studying these components in detail helps behavioral scientists understand the neural mechanisms behind these two complex phenomena. JoVE's overview on learning and memory introduces common...
06:02
Visual Statistical Learning
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2023
Source: Laboratory of Jonathan Flombaum—Johns Hopkins University The visual environment contains massive amounts of information involving the relations between objects in space and time; certain objects are more likely to appear in the vicinity of other objects. Learning these regularities can support a wide array of visual processing, including object recognition. Unsurprisingly, then, humans appear to learn these regularities automatically, quickly, and without conscious awareness. The name...
FAQs
Rather than isolating one input, researchers consider how continuous sensory streams recruit attention, memory, sensory integration, and prediction together. This combination matters because learners must select relevant information while relating incoming signals to existing internal representations. Studying these interacting processes can reveal how neural systems coordinate when behavior unfolds across changing, information-rich experiences.
Prediction errors provide a mechanism for learning from mismatches between expected and incoming information. When feedback reveals that an internal representation does not adequately account for experience, the representation can be updated over time. In naturalistic learning, this process is examined within ongoing activity rather than as an isolated response, linking adaptation to realistic goals and contexts.
Naturalistic Learning differs from highly controlled laboratory tasks by preserving more of the continuous and social structure that shapes everyday behavior. Researchers can therefore examine how goals, social cues, sensory integration, and feedback operate together instead of treating them as separate factors. The comparison helps identify which laboratory findings generalize to complex behavior outside the laboratory.
An investigation can be organized around experiences that include continuous sensory input, goals, social cues, and feedback. Researchers then examine how attention, memory, sensory integration, and prediction are engaged as those elements unfold. This design keeps the analysis focused on coordinated learning processes while retaining features that make the experience more similar to everyday environments.
This approach can show how neural systems coordinate during complex behavior and how internal representations change as prediction errors drive updates over time. These observations complement findings from tightly controlled tasks, helping researchers judge how well models of learning account for the richer conditions in which human behavior normally occurs.
Naturalistic Learning can connect neuroscience with education, rehabilitation, artificial intelligence, and ecological research. In each setting, its value lies in testing learning ideas against conditions that include ongoing input, goals, social information, or feedback. This broader connection may improve the relevance of models by reflecting how learning operates when multiple information sources are present together.