The ventral striatum dissociates information expectation, reward anticipation, and reward receipt

Filimon, Flavia; Nelson, Jonathan D.; Sejnowski, Terrence J.; Sereno, Martin I.; Cottrell, Garrison W.

doi:10.1073/pnas.1911778117

Cited by 38 publications

(30 citation statements)

References 64 publications

(104 reference statements)

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“…Similarly, in a recent study (Filimon, Nelson, Sejnowski, Sereno, & Cottrell, 2020), the nucleus accumbens was found to respond not only to the valence of feedback (positive versus negative), but also to the expectation of a more informative stimulus (high versus low information to help stimulus categorization).…”

Section: Shared Neural Correlates For Information and Reward Processing: A Domain-general Preference For Information?mentioning

confidence: 57%

Information-seeking in the brain

Charpentier¹,

Dezza²

2021

Preprint

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Recent advancements in psychology, behavioral economics and neuroscience have shown the human pursuit of knowledge to be an essential aspect of human cognition. It drives intellectual development, is integral to social interactions, and is crucial for learning, decision-making and goal-directed behavior. Information appears to be valuable in and of itself, even when it has no apparent use, whereas at other times, instrumental information is actively and paradoxically avoided. With this complex role, a wide range of neural mechanisms can be deployed to assign value to information and drive decisions to seek (or avoid) information. Evidence points towards key roles for the mesolimbic system and the prefrontal cortex in these processes. Specifically, two different networks appear to be involved in the implementation of information-seeking behaviors. One network, overlapping with areas involved in processing primary and monetary rewards, appear to drive a general preference for information, as well as valence-dependent information-seeking. The other network, independent of reward processing, is recruited when information is acquired to reduce uncertainty. In this chapter, we review some of the most recent discoveries in the field to provide an overview of the neural basis of information-seeking.

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Section: Shared Neural Correlates For Information and Reward Processing: A Domain-general Preference For Information?mentioning

confidence: 57%

Information-seeking in the brain

Charpentier¹,

Dezza²

2021

Preprint

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“…Images were normalized to standard Montreal Neurological Institute (MNI) space and smoothed with an 8 mm full width at half maximum (FWHM) Gaussian kernel. The voxel size and smoothing kernel used in our analysis are in accordance with other studies where similar parameters were included in order to study reward processing regions either using whole-brain analysis 44 or ROI-based analysis, including predefined reward regions, i.e., ventral striatum and insular segments 45 , 46 . A high-pass filter of 128 s cut off was applied, to eliminate physiological components such as respiration or heartbeat.…”

Section: Methodsmentioning

confidence: 99%

Interaction of schizophrenia and chronic cannabis use on reward anticipation sensitivity

et al. 2021

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Chronic cannabis use and schizophrenia are both thought to affect reward processing. While behavioural and neural effects on reward processing have been investigated in both conditions, their interaction has not been studied, although chronic cannabis use is common among these patients. In the present study eighty-nine participants divided into four groups (control chronic cannabis users and non-users; schizophrenia patient cannabis users and non-users) performed a two-choice decision task, preceded by monetary cues (high/low reward/punishment or neutral), while being scanned using functional magnetic resonance imaging. Reward and punishment anticipation resulted in activation of regions of interest including the thalamus, striatum, amygdala and insula. Chronic cannabis use and schizophrenia had opposing effects on reward anticipation sensitivity. More specifically control users and patient non-users showed faster behavioural responses and increased activity in anterior/posterior insula for high magnitude cues compared to control non-users and patient users. The same interaction pattern was observed in the activation of the right thalamus for reward versus punishment cues. This study provided evidence for interaction of chronic cannabis use and schizophrenia on reward processing and highlights the need for future research addressing the significance of this interaction for the pathophysiology of these conditions and its clinical consequences.

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“…Key applications include perceptual tasks (Najemnik & Geisler, 2005;Nelson & Cottrell, 2007), categorization (Markant & Gureckis, 2014;Nelson et al, 2010) associative learning (Kruschke, 2008), causal induction (Bramley et al, 2015;Steyvers et al, 2003), and hypothesis testing (Austerweil & Griffiths, 2011;Crupi et al, 2009;Oaksford & Chater, 1994, 1996. OED principles are also frequently used in developmental research (Kachergis et al, 2016;Nelson et al, 2014;Ruggeri & Lombrozo, 2015;Ruggeri et al, 2015) and neuroscience (Filimon et al, 2020;Nakamura, 2006). Applied issues include eye witness identification (Wells & Lindsay, 1980), medical diagnosis (Benish, 1999), reading (Legge et al, 1997), and the design of psychological experiments (Myung & Pitt, 2009).…”

Section: What Makes a Good Query?mentioning

confidence: 99%

What makes a good query? Prospects for a comprehensive theory of human information acquisition

Meder¹,

Crupi²,

Nelson³

2021

Preprint

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Searching for information in a goal-directed manner is central for learning, diagnosis, and prediction. Children continuously ask questions to learn new concepts, doctors do medical tests to diagnose their patients, and scientists perform experiments to test their theories. But what makes a good question? What principles govern human information acquisition and how do people decide which query to conduct to achieve their goals? What challenges need to be met to advance theory and psychology of human inquiry? Addressing these issues, we introduce the conceptual and mathematical ideas underlying different models of the value of information, what purpose these models serve in psychological research, and how they can be integrated in a unified formal framework. We also discuss the conflict between short- and long-term efficiency of prominent methods for query selection, and the resulting normative and methodological implications for studying human sequential search. A final point of discussion concerns the relations between probabilistic (Bayesian) models of the value of information and heuristic search strategies, and the insights than can be gained from bridging different levels of analysis and types of models. We conclude by discussing open questions and challenges that research needs to address to build a comprehensive theory of human information acquisition.

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The ventral striatum dissociates information expectation, reward anticipation, and reward receipt

Cited by 38 publications

References 64 publications

Information-seeking in the brain

Information-seeking in the brain

Interaction of schizophrenia and chronic cannabis use on reward anticipation sensitivity

What makes a good query? Prospects for a comprehensive theory of human information acquisition

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