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Mechanisms of Adaptive Choice History Biases in the Human Brain

Subject Area Human Cognitive and Systems Neuroscience
Term from 2014 to 2023
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 259469422
 
Numerous behavioral studies have revealed that human decision-making is profoundly shaped by strong biases. One important source of those biases is the history of previous choices. For example, when judging ambiguous evidence, people often repeat the same choice more frequently than expected by chance. Recent work in cognitive, systems, and theoretical neuroscience provides a glimpse into the emergence of choice history biases from the dynamics of internal brain states during sequences of decisions. Specifically, my team’s work during the first funding period of this DFG research grant has led to two hypotheses, which we aim to test in the second funding period of this grant: (i) the effect of choice history biases on internal brain state is mediated by the slow, and context-dependent, accumulation of choice-related neural signals across subsequent decisions; and (ii) the resulting neural biases shape the interpretation of new decision-relevant evidence, by biasing selective attention. To this end, we will perform systematic manipulations of choice history biases as well as of selective attention, and then quantify the resulting changes in internal brain states at the behavioral, algorithmic, and neural levels, in the intact human brain. We will perform detailed analyses of history patterns in choice behavior, fits of alternative algorithmic models to these behavioral patterns, and pupillometric and magnetoencephalographic (MEG) recordings of large-scale brain dynamics. We will focus on choice history biases during elementary perceptual decisions under uncertainty, enabling us to exploit well-characterized neural population measures of the encoding of sensory input (“evidence”), the evolving decision, and the resulting plan to act. This, in turn, will facilitate the identification of biases in these measures between subsequent decisions, which mediate the choice history bias at the behavioral level. We also plan to develop an integrated theoretical framework for choice history bias, based on the emerging understanding of choice history bias. The framework will bridge between insights from distinct avenues of research: insights from the levels of computation as well as underlying dynamical neural mechanisms, at the levels of local microcircuits and brain-wide networks; and insights from studies of perceptual and value-based decisions. Taken together, this project will provide deep insights into the biological basis of human judgment and decision-making under uncertainty.
DFG Programme Research Grants
 
 

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