scholarly journals Learning Structures: Predictive Representations, Replay, and Generalization

2020 ◽  
Author(s):  
Ida Momennejad
Keyword(s):  
Cognitive Maps ◽  
Latent Learning ◽  
Approach To Learning ◽  
Relational Structures ◽  
Multi Scale ◽  
Neural Representations ◽  
Compact Representations ◽  
New Directions ◽  
Flexible Behavior ◽  
The Brain

Memory and planning rely on learning the structure of relationships among experiences. Compact representations of these structures guide flexible behavior in humans and animals. A century after ‘latent learning’ experiments summarized by Tolman, the larger puzzle of cognitive maps remains elusive: how does the brain learn and generalize relational structures? This review focuses on a reinforcement learning (RL) approach to learning compact representations of the structure of states. We review evidence showing that capturing structures as predictive representations updated via replay offers a neurally plausible account of human behavior and the neural representations of predictive cognitive maps. We highlight multi-scale successor representations, prioritized replay, and policy-dependence. These advances call for new directions in studying the entanglement of learning and memory with prediction and planning.

scholarly journals Curiosity, latent learning, and cognitive maps

2020 ◽  
Author(s):  
Maya Zhe Wang ◽  
Benjamin Y. Hayden
Keyword(s):  
Value Of Information ◽  
Cognitive Maps ◽  
Cognitive Map ◽  
Decision Makers ◽  
Anterior Cingulate ◽  
Latent Learning ◽  
Dorsal Anterior Cingulate Cortex ◽  
Information Availability ◽  
New Information ◽  
Flexible Behavior

ABSTRACTCuriosity refers to a desire for information that is not driven by immediate strategic or instrumental concerns. Latent earning refers to a form of learning that is not directly driven by standard reinforcement learning processes. We propose that curiosity serves the purpose of motivating latent learning. Thus, while latent learning is often treated as an incidental or passive process, in practice it most often reflects a strong evolved pressure to consume large amounts of information. That large volume of information in turn allows curious decision makers to generate sophisticated representations of the structure of their environment, known as cognitive maps. Cognitive maps facilitate adaptive and flexible behavior while maintaining its adaptivity and flexibility via map updates based on new information. Here we describe data supporting the idea that orbitofrontal cortex (OFC) and dorsal anterior cingulate cortex (dACC) play complementary roles in curiosity-driven learning. Specifically, we propose that (1) OFC tracks the innate value of information and incorporates new information into a detailed cognitive map; and (2) dACC tracks the environmental demands and information availability to then use the cognitive map for guiding behavior.

scholarly journals How usefulness shapes neural representations during goal-directed behavior

2021 ◽  
Vol 7 (15) ◽  
pp. eabd5363
Author(s):  
G. Castegnetti ◽  
M. Zurita ◽  
B. De Martino
Keyword(s):  
Prefrontal Cortex ◽  
Neural Representation ◽  
Coding Scheme ◽  
Neural Representations ◽  
Specific Goal ◽  
Sensory Cortices ◽  
Flexible Behavior ◽  
Goal Directed Behavior ◽  
The Brain

Value is often associated with reward, emphasizing its hedonic aspects. However, when circumstances change, value must also change (a compass outvalues gold, if you are lost). How are value representations in the brain reshaped under different behavioral goals? To answer this question, we devised a new task that decouples usefulness from its hedonic attributes, allowing us to study flexible goal-dependent mapping. Here, we show that, unlike sensory cortices, regions in the prefrontal cortex (PFC)—usually associated with value computation—remap their representation of perceptually identical items according to how useful the item has been to achieve a specific goal. Furthermore, we identify a coding scheme in the PFC that represents value regardless of the goal, thus supporting generalization across contexts. Our work questions the dominant view that equates value with reward, showing how a change in goals triggers a reorganization of the neural representation of value, enabling flexible behavior.

scholarly journals Aggregation-and-Attention Network for brain tumor segmentation

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chih-Wei Lin ◽  
Yu Hong ◽  
Jinfu Liu
Keyword(s):  
Brain Tumor ◽  
Semantic Information ◽  
Spatial Relationship ◽  
Tumor Segmentation ◽  
Computer Assisted ◽  
Brain Tumor Segmentation ◽  
Attention Network ◽  
Multi Scale ◽  
Assisted Diagnosis ◽  
The Brain

Abstract Background Glioma is a malignant brain tumor; its location is complex and is difficult to remove surgically. To diagnosis the brain tumor, doctors can precisely diagnose and localize the disease using medical images. However, the computer-assisted diagnosis for the brain tumor diagnosis is still the problem because the rough segmentation of the brain tumor makes the internal grade of the tumor incorrect. Methods In this paper, we proposed an Aggregation-and-Attention Network for brain tumor segmentation. The proposed network takes the U-Net as the backbone, aggregates multi-scale semantic information, and focuses on crucial information to perform brain tumor segmentation. To this end, we proposed an enhanced down-sampling module and Up-Sampling Layer to compensate for the information loss. The multi-scale connection module is to construct the multi-receptive semantic fusion between encoder and decoder. Furthermore, we designed a dual-attention fusion module that can extract and enhance the spatial relationship of magnetic resonance imaging and applied the strategy of deep supervision in different parts of the proposed network. Results Experimental results show that the performance of the proposed framework is the best on the BraTS2020 dataset, compared with the-state-of-art networks. The performance of the proposed framework surpasses all the comparison networks, and its average accuracies of the four indexes are 0.860, 0.885, 0.932, and 1.2325, respectively. Conclusions The framework and modules of the proposed framework are scientific and practical, which can extract and aggregate useful semantic information and enhance the ability of glioma segmentation.

scholarly journals Latent learning drives sleep-dependent plasticity in distinct CA1 subpopulations

2020 ◽  
Author(s):  
Wei Guo ◽  
Jie J. Zhang ◽  
Jonathan P. Newman ◽  
Matthew A. Wilson
Keyword(s):  
Hippocampal Neurons ◽  
Dimensional Manifold ◽  
Latent Learning ◽  
Neural Ensembles ◽  
Correlated Activity ◽  
Place Fields ◽  
Internal States ◽  
Low Dimensional ◽  
Low Dimensional Manifold ◽  
The Brain

AbstractLatent learning allows the brain the transform experiences into cognitive maps, a form of implicit memory, without reinforced training. Its mechanism is unclear. We tracked the internal states of the hippocampal neural ensembles and discovered that during latent learning of a spatial map, the state space evolved into a low-dimensional manifold that topologically resembled the physical environment. This process requires repeated experiences and sleep in-between. Further investigations revealed that a subset of hippocampal neurons, instead of rapidly forming place fields in a novel environment, remained weakly tuned but gradually developed correlated activity with other neurons. These ‘weakly spatial’ neurons bond activity of neurons with stronger spatial tuning, linking discrete place fields into a map that supports flexible navigation.

scholarly journals Task dependence of neural representations of global scene properties but not scene categories in the prefrontal cortex

2020 ◽  
Author(s):  
Yaelan Jung ◽  
Dirk B. Walther
Keyword(s):  
Prefrontal Cortex ◽  
Visual Cortex ◽  
Scene Perception ◽  
Sound Level ◽  
Task Context ◽  
Complex Scene ◽  
Neural Representations ◽  
Task Conditions ◽  
Scene Content ◽  
The Brain

AbstractNatural scenes deliver rich sensory information about the world. Decades of research has shown that the scene-selective network in the visual cortex represents various aspects of scenes. It is, however, unknown how such complex scene information is processed beyond the visual cortex, such as in the prefrontal cortex. It is also unknown how task context impacts the process of scene perception, modulating which scene content is represented in the brain. In this study, we investigate these questions using scene images from four natural scene categories, which also depict two types of global scene properties, temperature (warm or cold), and sound-level (noisy or quiet). A group of healthy human subjects from both sexes participated in the present study using fMRI. In the study, participants viewed scene images under two different task conditions; temperature judgment and sound-level judgment. We analyzed how different scene attributes (scene categories, temperature, and sound-level information) are represented across the brain under these task conditions. Our findings show that global scene properties are only represented in the brain, especially in the prefrontal cortex, when they are task-relevant. However, scene categories are represented in the brain, in both the parahippocampal place area and the prefrontal cortex, regardless of task context. These findings suggest that the prefrontal cortex selectively represents scene content according to task demands, but this task selectivity depends on the types of scene content; task modulates neural representations of global scene properties but not of scene categories.

The Effect of Familiarity on Neural Representations of Music and Language

2021 ◽  
pp. 1-17
Author(s):  
Avital Sternin ◽  
Lucy M. McGarry ◽  
Adrian M. Owen ◽  
Jessica A. Grahn
Keyword(s):  
Language Processing ◽  
Instrumental Music ◽  
Training Period ◽  
Neural Representations ◽  
Music And Language ◽  
Brain Responses ◽  
Language And Music ◽  
Before And After ◽  
Musical Memory ◽  
The Brain

Abstract We investigated how familiarity alters music and language processing in the brain. We used fMRI to measure brain responses before and after participants were familiarized with novel music and language stimuli. To manipulate the presence of language and music in the stimuli, there were four conditions: (1) whole music (music and words together), (2) instrumental music (no words), (3) a capella music (sung words, no instruments), and (4) spoken words. To manipulate participants' familiarity with the stimuli, we used novel stimuli and a familiarization paradigm designed to mimic “natural” exposure, while controlling for autobiographical memory confounds. Participants completed two fMRI scans that were separated by a stimulus training period. Behaviorally, participants learned the stimuli over the training period. However, there were no significant neural differences between the familiar and unfamiliar stimuli in either univariate or multivariate analyses. There were differences in neural activity in frontal and temporal regions based on the presence of language in the stimuli, and these differences replicated across the two scanning sessions. These results indicate that the way we engage with music is important for creating a memory of that music, and these aspects, over and above familiarity on its own, may be responsible for the robust nature of musical memory in the presence of neurodegenerative disorders such as Alzheimer's disease.

An action-oriented perspective on space and affordances

2021 ◽  
pp. 73-140
Author(s):  
Michael A. Arbib
Keyword(s):  
Motor Control ◽  
Body Schema ◽  
Cognitive Maps ◽  
The Body ◽  
Perceptual Cues ◽  
Motor Patterns ◽  
General Rules ◽  
Hand Eye Coordination ◽  
Ongoing Behavior ◽  
The Brain

Architects design spaces that offer perceptual cues, affordances, for our various effectivities. Lina Bo Bardi’s São Paulo Museum demonstrates how praxic and contemplative actions are interleaved—space is effective and affective. Navigation often extends beyond wayfinding to support ongoing behavior. Scripts set out the general rules for a particular kind of behavior, and may suggest places that a building must provide. Cognitive maps support wayfinding. Other maps in the brain represent sensory or motor patterns of activity. Juhani Pallasmaa’s reflections on The Thinking Hand lead into a view of how the brain mediates that thinking, modeling hand–eye coordination at two levels. The first coordinates perceptual and motor schemas. The body schema is an adaptable collage of perceptual and motor skills. The second coordinates the ventral “what” pathway that can support planning of actions, and the dorsal “how” pathway that links affordance-related details to motor control. A complementary challenge is understanding how schemas in the head relate to social schemas. Finally, the chapter compares the cognitive challenges in designing a building and in developing a computational brain model of cognitive processes.

Disorders of consciousness, memory, and will

2018 ◽  
pp. 51-86
Author(s):  
Walter Glannon
Keyword(s):  
Psychiatric Disorder ◽  
Mental Content ◽  
Mental States ◽  
External World ◽  
The Body ◽  
Disorders Of Consciousness ◽  
Action Plans ◽  
Flexible Behavior ◽  
The Brain ◽  
Insight Into

This chapter examines major psychiatric disorders as disorders of consciousness, memory, and will. All of these disorders involve disturbances in how the brain processes and integrates information about the body and external world. Distorted mental content in these psychopathologies impairs the capacity to consider different action plans, and to form and execute particular plans in particular actions. Dysfunctional mental states correlating with dysfunctional neural states impair the capacity for flexible behavior and adaptability to the environment. This dysfunction also impairs the capacity for insight into a psychiatric disorder and understanding the need for and motivation to seek treatment.

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