scholarly journals Neural Correlates of Value Are Intrinsically History Dependent

2020 ◽  
Author(s):  
Sangil Lee ◽  
Caryn Lerman ◽  
Joseph W. Kable
Keyword(s):  
Population Level ◽  
Neural Correlates ◽  
Practical Application ◽  
Efficient Coding ◽  
Decision Neuroscience ◽  
History Effects ◽  
Repetition Suppression ◽  
Subjective Value ◽  
Out Of Sample ◽  
Prediction Approach

AbstractA central finding in decision neuroscience is that BOLD activity in several regions, including ventral striatum and ventromedial prefrontal cortex, is correlated with the subjective value of the option being considered, and that BOLD activity in these regions can predict choices out of sample, even at the population-level. Here we show, across two different decision making tasks in a large sample of subjects, that these BOLD value-correlates are intrinsically history dependent. If the subjective value of the previous offer was high, the signal on the current trial will be lower, and vice versa. This kind of history dependency is distinct from previously described adaptation or repetition suppression effects, but instead is of the form predicted by theories of efficient coding such as time-dependent cortical normalization. In terms of practical application, since value-based choice behavior does not exhibit the same history dependence, neural prediction studies may exhibit systematic errors without accounting for history effects. The data-driven, interpretable, whole-brain prediction approach we use to identify history effects also illustrates one way to adjust predictions for neural history dependency.

scholarly journals The Neuroscience of Information Sharing

2019 ◽  
pp. 284-307
Author(s):  
Christin Scholz ◽  
Emily B. Falk
Keyword(s):  
Information Sharing ◽  
Structural Model ◽  
Population Level ◽  
Neural Correlates ◽  
Computational Social Science ◽  
Psychological Processes ◽  
Thought Processes ◽  
Psychological Mechanisms ◽  
Subjective Value ◽  
Share Information

Information sharing is a core human activity that catalyzes innovation and development. Recent advances in neuroscience reveal information about the psychological mechanisms that drive sharing, with a particular focus on self-relevance, social cognition, and subjective value. Based on these insights, this chapter proposes a structural model of the neurocognitive and psychological processes that drive sharing decisions, called value-based virality. Further, it maps existing knowledge about neural correlates and moderators of thought processes linked to individual and population-level sharing events and outcomes and suggests avenues for future investigation. Finally, the chapter discusses the potential of the neuroscience of information sharing to interact productively with other methodological traditions such as computational social science. Initial neuroimaging studies of information sharing provide insights into psychological mechanisms that were previously inaccessible. With the development of more realistic experimental setups and multimethod designs, future efforts promise advances toward a unifying theory of why and how people share information.

scholarly journals The neural correlates of subjective value during intertemporal choice

2007 ◽  
Vol 10 (12) ◽  
pp. 1625-1633 ◽  
Author(s):  
Joseph W Kable ◽  
Paul W Glimcher
Keyword(s):  
Intertemporal Choice ◽  
Neural Correlates ◽  
Subjective Value

scholarly journals Comparison of Shape Encoding in Primate Dorsal and Ventral Visual Pathways

2007 ◽  
Vol 97 (1) ◽  
pp. 307-319 ◽  
Author(s):  
Sidney R. Lehky ◽  
Anne B. Sereno
Keyword(s):  
Population Level ◽  
Shape Selectivity ◽  
Visual Pathways ◽  
Neural Population ◽  
Inferotemporal Cortex ◽  
Lateral Intraparietal Cortex ◽  
Dorsal Pathway ◽  
Repetition Suppression ◽  
Shape Encoding ◽  
High Level

Ventral and dorsal visual pathways perform fundamentally different functions. The former is involved in object recognition, whereas the latter carries out spatial localization of stimuli and visual guidance of motor actions. Despite the association of the dorsal pathway with spatial vision, recent studies have reported shape selectivity in the dorsal stream. We compared shape encoding in anterior inferotemporal cortex (AIT), a high-level ventral area, with that in lateral intraparietal cortex (LIP), a high-level dorsal area, during a fixation task. We found shape selectivities of individual neurons to be greater in anterior inferotemporal cortex than in lateral intraparietal cortex. At the neural population level, responses to different shapes were more dissimilar in AIT than LIP. Both observations suggest a greater capacity in AIT for making finer shape distinctions. Multivariate analyses of AIT data grouped together similar shapes based on neural population responses, whereas such grouping was indistinct in LIP. Thus in a first comparison of shape response properties in late stages of the two visual pathways, we report that AIT exhibits greater capability than LIP for both object discrimination and generalization. These differences in the two visual pathways provide the first neurophysiological evidence that shape encoding in the dorsal pathway is distinct from and not a mere duplication of that formed in the ventral pathway. In addition to shape selectivity, we observed stimulus-driven cognitive effects in both areas. Stimulus repetition suppression in LIP was similar to the well-known repetition suppression in AIT and may be associated with the “inhibition of return” memory effect observed during reflexive attention.

scholarly journals Population adaptation in efficient balanced networks

2017 ◽  
Author(s):  
Gabrielle J. Gutierrez ◽  
Sophie Denève
Keyword(s):  
Metabolic Cost ◽  
Population Level ◽  
Efficient Coding ◽  
Global Cost ◽  
Stable Representation ◽  
Reliable Representation ◽  
Sensory Responses ◽  
The Cost ◽  
External Stimuli ◽  
Accuracy Tradeoff

AbstractAdaptation is a key component of efficient coding in sensory neurons. However, it remains unclear how neurons can provide a stable representation of external stimuli given their history-dependent responses. Here we show that a stable representation is maintained if efficiency is optimized by a population of neurons rather than by neurons individually. We show that spike-frequency adaptation and E/I balanced recurrent connectivity emerge as solutions to a global cost-accuracy tradeoff. The network will re-distribute sensory responses from highly excitable neurons to less excitable neurons as the cost of neural activity increases. This does not change the representation at the population level, despite causing dynamic changes in individual neurons. By applying this framework to an orientation coding network, we reconcile neural and behavioral findings. Our approach underscores the common mechanisms behind the diversity of neural adaptation and its role in producing a reliable representation of the stimulus while minimizing metabolic cost.

scholarly journals Neural correlates of episodic memory modulated by temporally delayed rewards

2019 ◽  
Author(s):  
Jungsun Yoo ◽  
Seokyoung Min ◽  
Seung-Koo Lee ◽  
Sanghoon Han
Keyword(s):  
Memory Performance ◽  
Long Term Potentiation ◽  
Neural Correlates ◽  
Temporal Distance ◽  
Long Term Memory ◽  
Memory Encoding ◽  
Term Potentiation ◽  
Subjective Value ◽  
Behavioral Memory

AbstractWhen a stimulus is associated with an external reward, its chance of being consolidated into long-term memory is boosted via dopaminergic facilitation of long-term potentiation in the hippocampus. Given that higher temporal distance (TD) has been found to discount the subjective value of a reward, we hypothesized that memory performance associated with a more immediate reward will result in better memory performance. We tested this hypothesis by measuring both behavioral memory performance and brain activation using functional magnetic resonance imaging (fMRI) during memory encoding and retrieval tasks. Contrary to our hypothesis, both behavioral and fMRI results suggest that the TD of rewards might enhance the chance of the associated stimulus being remembered. The fMRI data demonstrate that the lateral prefrontal cortex, which shows encoding-related activation proportional to the TD, is reactivated when searching for regions that show activation proportional to the TD during retrieval. This is not surprising given that this region is not only activated to discriminate between future vs. immediate rewards, it is also a part of the retrieval-success network. These results provide support for the conclusion that the encoding-retrieval overlap provoked as the rewards are more delayed lead to better memory performance of the items associated with the rewards.

scholarly journals Efficient coding of subjective value

2018 ◽  
Author(s):  
Rafael Polanía ◽  
Michael Woodford ◽  
Christian C. Ruff
Keyword(s):  
Empirical Data ◽  
Information Structure ◽  
Limited Capacity ◽  
Inference Process ◽  
Efficient Coding ◽  
Mechanistic Explanations ◽  
Level Of Confidence ◽  
Subjective Value ◽  
Subjective Valuation ◽  
Optimal Decoding

AbstractPreference-based decisions are essential for survival, for instance when deciding what we should (not) eat. Despite their importance, choices based on preferences are surprisingly variable and can appear irrational in ways that have defied mechanistic explanations. Here we propose that subjective valuation results from an inference process that accounts for the information structure of values in the environment and that maximizes information in value representations in line with demands imposed by limited coding resources. A model of this inference process explains the variability in both subjective value reports and preference-based choices, and predicts a new preference illusion that we validate with empirical data. Interestingly, the same model also explains the level of confidence associated with these reports. Our results imply that preference-based decisions reflect information-maximizing transmission and statistically optimal decoding of subjective values by a limited-capacity system. These findings provide a unified account of how humans perceive and valuate the environment to optimally guide behavior.

scholarly journals The neural correlates of intertemporal decision-making: Contributions of subjective value, stimulus type, and trait impulsivity

2010 ◽  
Vol 32 (10) ◽  
pp. 1637-1648 ◽  
Author(s):  
Chandra Sekhar Sripada ◽  
Richard Gonzalez ◽  
K. Luan Phan ◽  
Israel Liberzon
Keyword(s):  
Decision Making ◽  
Stimulus Type ◽  
Neural Correlates ◽  
Subjective Value ◽  
Trait Impulsivity
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