Rational regulation of learning dynamics by pupil–linked arousal systems
By Matthew R. Nassar, Katherine M. Rumsey, Robert C. Wilson, Kinjan Parikh, B. Heasly, Joshua I. Gold. Nature Neuroscience, 2012
664 citations recorded by the source corpus.
The ability to make inferences about the current state of a dynamic process requires ongoing assessments of the stability and reliability of data generated by that process. We found that these assessments, as defined by a normative model, were reflected in nonluminance-mediated changes in pupil diameter of human subjects performing a predictive-inference task. Brief changes in pupil diameter reflected assessed instabilities in a process that generated noisy data. Baseline pupil diameter reflected the reliability with which recent data indicate the current state of the data-generating process and individual differences in expectations about the rate of instabilities. Together these pupil metrics predicted the influence of new data on subsequent inferences. Moreover, a task- and luminance-independent manipulation of pupil diameter predictably altered the influence of new data. Thus, pupil-linked arousal systems can help to regulate the influence of incoming data on existing beliefs in a dynamic environment.
Subfields: Cognitive Neuroscience, Sensory Systems
View Paper: https://www.semanticscholar.org/paper/e2727c91c5a541af92749787f39189f570e33014
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Citations in the corpus
- Hierarchical decision processes that operate over distinct timescales underlie choice and changes in strategy (2016, neutral): “dve =dT μe,T − λve + ffiffiffiffiffiffi dT p ξe, veð0Þ= 0, [14]”
- Relationships between pupil diameter and neuronal activity in the locus coeruleus, colliculi, and cingulate cortex (2015, methodology): “…to distinguish from the LC using our recording techniques) (Kalwani et al., 2014) because of its previously proposed links to pupil diameter (Nassar et al., 2012; Nieuwenhuis et al., 2011; Varazzani et al., 2015; Phillips et al., 2000; Hou et al., 2005; Beatty, 1982a, 1982b; Richer and…”
- Attention, learning and the value of information (2012, background): “…and Platt, 2005; O’Neill and Schultz, 2010; Preuschoff et al., 2006, 2008; Schultz et al., 2008; So and Stuphorn, 2012; Tobler et al., 2009) and have been linked with variables such as arousal, anxiety, risk preference, or global learning rates (Nassar et al., 2012; Preuschoff and Bossaerts, 2007).”
- Ten simple rules for the computational modeling of behavioral data (2019, background): “, 2017), but also for EEG, ECOG, electrophysiology and pupillometry among many others (OReilly et al., 2013; A. G. Collins & Frank, 2018; Samejima, Ueda, Doya, & Kimura, 2005; Cavanagh, Wiecki, Kochar, & Frank, 2014; Nassar et al., 2012).”
- Waking State: Rapid Variations Modulate Neural and Behavioral Responses (2015, neutral): “Human and animal studies have shown that changes in pupil diameter (after controlling for changes associated with luminance and depth accommodation) are correlated with arousal, attention, emotion, cognitive perception, and ‘‘brain gain,’’ as well as heart rate and galvanic skin reflex, indicating a”
- Reorienting Spatial Attention within Visual Working Memory (2019, methodology): “Interestingly, the pupil dilation, which was tightly connected to the arousal systems (Alnæs et al., 2014; Granholm & Steinhauer, 2004; Nassar et al., 2012), appeared stronger for the exogenous cues than the endogenous cues at a similar latency of around 400ms (experiment 1).”