Neurokognition der Entscheidungsfindung
Zusammenfassung der Projektergebnisse
Perceptual decision making is the act of choosing one option or course of action from a set of alternatives based on the available sensory evidence. Thus, when we make decisions, sensory information must be interpreted and translated into behavior. Behavioral decision-making research has resulted in mathematical models of the assumed underlying cognitive processes. The diffusion model, which assumes that decisions are formed by continuously accumulating sensory information until a response criterion is reached, is particularly successful in explaining behavior in perceptual decision making tasks. Recent advances in both neurophysiological studies in monkeys and functional brain imaging methods have inspired studies of perceptual decision making in humans. Several important questions have remained unanswered, however. The general objective of this project thus has been to directly link behavioral measures (that is, revealed decisions) to signals in the human brain in the context of human perceptual decision making. The project has yielded the following findings: Both in the visual and the somatosensory domain findings from human neuroimaging work parallel those from monkey physiology experiments. In both species sensory evidence is represented in sensory processing areas, but the accumulation of sensory evidence occurs in decision-making areas that are downstream of the sensory processing areas (e.g., in the dorsolateral prefrontal cortex, DLPFC). Decision makers determine (rewarded) perceptual decisions by collecting evidence until reaching a point of choice, the decision criterion or threshold. They can either make decisions quickly, thereby risking more errors, or make decisions carefully, thereby risking to have fewer opportunities for being maximally rewarded. Our MEG results show that the supplementary motor area dynamically facilitates fast responses during stimulus processing, whereas DLPFC reflects accumulated evidence before response execution. In a subsequent fMRI study, we found that adapting decision criteria to maximize reward is instantiated by a change in interaction between brain systems that mediate decision making, such as DLPFC and striatum. Furthermore, we discovered that during binary value-based decision-making ventromedial prefrontal cortex (VMPFC) integrates information from sensory regions into a value signal using a difference-based comparator operation. Crucially, the same mechanism also seems to hold for cost-benefit decisions. VMPFC and DLPFC compare costs and benefits by computing the difference between anticipated benefit and cost signals in ventral striatum and amygdala, respectively. The brain thus weighs costs against benefits by combining neural benefit and cost signals into a single, difference-based neural representation of net value, which is accumulated over time until the individual decides to accept or reject an option. It has been claimed that sensorimotor areas involved in planning a response, such an eye movement or a button press, also participate in decision making. Results of an fMRI study challenge this view and suggest that when stimulus-response associations are not pre-assigned, motor regions do not participate in the integration of sensory evidence underlying the perceptual decision. The framework of this project might also prove useful for advancing our understanding of clinical disorders, such as obsessive–compulsive disorder, which is characterized by indecisiveness and inflexibility in regulating behaviors. Ultimately, understanding how the human brain makes perceptual decisions will further our understanding of the neural mechanisms that are involved in the complex decisions that we repeatedly encounter in everyday life.
Projektbezogene Publikationen (Auswahl)
- (2006). Involvement of human left dorsolateral prefrontal cortex in perceptual decision making is independent of response modality. Proceedings of the National Academy of Sciences, 103(26), 10023-10028
Heekeren, H. R., Marrett, S., Ruff, D. A., Bandettini, P. A., & Ungerleider, L. G.
- (2008). The neural systems that mediate human perceptual decision making. Nature reviews neuroscience,9(6), 467-479
Heekeren, H. R., Marrett, S., & Ungerleider, L. G.
- (2010). A mechanistic account of value computation in the human brain. Proceedings of the National Academy of Sciences, 107(20), 9430-9435
Philiastides, M. G., Biele, G., & Heekeren, H. R.
- (2010). How the brain integrates costs and benefits during decision making. Proceedings of the National Academy of Sciences, 107(50), 21767-21772
Basten, U., Biele, G., Heekeren, H. R., & Fiebach, C. J.
- (2010). Prior information biases stimulus representations during vibrotactile decision making. Journal of Cognitive Neuroscience, 22(5), 875-87
Preuschhof C, Schubert T, Villringer A, & Heekeren H. R.
- (2011). Causal role of dorsolateral prefrontal cortex in human perceptual decision making. Current Biology, 21(11), 980-983
Philiastides, M. G., Auksztulewicz, R., Heekeren, H. R., & Blankenburg, F.
- (2011). Neural characterization of the speed–accuracy tradeoff in a perceptual decision-making task. The Journal of Neuroscience, 31(4), 1254-1266
Wenzlaff, H., Bauer, M., Maess, B., & Heekeren, H. R.
- (2012). Changes in neural connectivity underlie decision threshold modulation for reward maximization. The Journal of Neuroscience, 32(43), 14942-14950
Green, N., Biele, G. P., & Heekeren, H. R.
(Siehe online unter https://doi.org/10.1523/JNEUROSCI.0573-12.2012) - (2013). How embodied is perceptual decision making? Evidence for separate processing of perceptual and motor decisions. The Journal of Neuroscience, 33(5), 2121-2136
Filimon, F., Philiastides, M. G., Nelson, J. D., Kloosterman, N. A., & Heekeren, H. R.
(Siehe online unter https://doi.org/10.1523/JNEUROSCI.2334-12.2013) - (2013). Reduction of influence of task difficulty on perceptual decision making by STN deep brain stimulation. Current Biology, 23(17), 1681-1684
Green, N., Bogacz, R., Huebl, J., Beyer, A. K., Kühn, A. A., & Heekeren, H. R.
(Siehe online unter https://doi.org/10.1016/j.cub.2013.07.001)
