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Fuat Balci - One of the best experts on this subject based on the ideXlab platform.
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inhibition of pre supplementary motor area by continuous theta burst stimulation leads to more cautious decision making and more efficient Sensory Evidence integration
Journal of Cognitive Neuroscience, 2017Co-Authors: Tugce Tosun, Dilara Berkay, Alexander T Sack, Yusuf Ozgur Cakmak, Fuat BalciAbstract:Decisions are made based on the integration of available Evidence. The noise in Evidence accumulation leads to a particular speed-accuracy tradeoff in decision-making, which can be modulated and optimized by adaptive decision threshold setting. Given the effect of pre-SMA activity on striatal excitability, we hypothesized that the inhibition of pre-SMA would lead to higher decision thresholds and an increased accuracy bias. We used offline continuous theta burst stimulation to assess the effect of transient inhibition of the right pre-SMA on the decision processes in a free-response two-alternative forced-choice task within the drift diffusion model framework. Participants became more cautious and set higher decision thresholds following right pre-SMA inhibition compared with inhibition of the control site (vertex). Increased decision thresholds were accompanied by an accuracy bias with no effects on post-error choice behavior. Participants also exhibited higher drift rates as a result of pre-SMA inhibition compared with the vertex inhibition. These results, in line with the striatal theory of speed-accuracy tradeoff, provide Evidence for the functional role of pre-SMA activity in decision threshold modulation. Our results also suggest that pre-SMA might be a part of the brain network associated with the Sensory Evidence integration.
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Inhibition of Pre–Supplementary Motor Area by Continuous Theta Burst Stimulation Leads to More Cautious Decision-making and More Efficient Sensory Evidence Integration
Journal of cognitive neuroscience, 2017Co-Authors: Tugce Tosun, Dilara Berkay, Alexander T Sack, Yusuf Ozgur Cakmak, Fuat BalciAbstract:Decisions are made based on the integration of available Evidence. The noise in Evidence accumulation leads to a particular speed-accuracy tradeoff in decision-making, which can be modulated and optimized by adaptive decision threshold setting. Given the effect of pre-SMA activity on striatal excitability, we hypothesized that the inhibition of pre-SMA would lead to higher decision thresholds and an increased accuracy bias. We used offline continuous theta burst stimulation to assess the effect of transient inhibition of the right pre-SMA on the decision processes in a free-response two-alternative forced-choice task within the drift diffusion model framework. Participants became more cautious and set higher decision thresholds following right pre-SMA inhibition compared with inhibition of the control site (vertex). Increased decision thresholds were accompanied by an accuracy bias with no effects on post-error choice behavior. Participants also exhibited higher drift rates as a result of pre-SMA inhibition compared with the vertex inhibition. These results, in line with the striatal theory of speed-accuracy tradeoff, provide Evidence for the functional role of pre-SMA activity in decision threshold modulation. Our results also suggest that pre-SMA might be a part of the brain network associated with the Sensory Evidence integration.
Johannes J. Fahrenfort - One of the best experts on this subject based on the ideXlab platform.
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Humans strategically shift decision bias by flexibly adjusting Sensory Evidence accumulation
eLife, 2019Co-Authors: Niels A. Kloosterman, Jan Willem De Gee, Markus Werkle-bergner, Ulman Lindenberger, Douglas D. Garrett, Johannes J. FahrenfortAbstract:Decision bias is traditionally conceptualized as an internal reference against which Sensory Evidence is compared. Instead, we show that individuals implement decision bias by shifting the rate of Sensory Evidence accumulation toward a decision bound. Participants performed a target detection task while we recorded EEG. We experimentally manipulated participants' decision criterion for reporting targets using different stimulus-response reward contingencies, inducing either a liberal or a conservative bias. Drift diffusion modeling revealed that a liberal strategy biased Sensory Evidence accumulation toward target-present choices. Moreover, a liberal bias resulted in stronger midfrontal pre-stimulus 2-6 Hz (theta) power and suppression of pre-stimulus 8-12 Hz (alpha) power in posterior cortex. Alpha suppression in turn was linked to the output activity in visual cortex, as expressed through 59-100 Hz (gamma) power. These findings show that observers can intentionally control cortical excitability to strategically bias Evidence accumulation toward the decision bound that maximizes reward.
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humans strategically shift decision bias by flexibly adjusting Sensory Evidence accumulation
bioRxiv, 2018Co-Authors: Niels A. Kloosterman, Jan Willem De Gee, Ulman Lindenberger, Douglas D. Garrett, Johannes J. Fahrenfort, Markus WerklebergnerAbstract:Abstract Decision bias is traditionally conceptualized as an internal reference against which Sensory Evidence is compared. Instead, we show that individuals implement decision bias by shifting the rate of Sensory Evidence accumulation towards a decision bound. Participants performed a target detection task while we recorded EEG. We experimentally manipulated participants’ decision criterion for reporting targets using different stimulus-response reward contingencies, inducing either a liberal or a conservative bias. Drift diffusion modeling revealed that a liberal strategy biased Sensory Evidence accumulation towards target-present choices. Moreover, a liberal bias resulted in stronger midfrontal pre-stimulus 2-6 Hz (theta) power and suppression of pre-stimulus 8—12 Hz (alpha) power in posterior cortex. The alpha suppression in turn mediated the output activity of visual cortex, as expressed in 59—100 Hz (gamma) power. These findings show that observers can intentionally control cortical excitability to strategically bias Evidence accumulation towards the decision bound that maximizes their reward.
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humans strategically shift decision bias by flexibly adjusting Sensory Evidence accumulation in visual cortex
bioRxiv, 2018Co-Authors: Niels A. Kloosterman, Jan Willem De Gee, Ulman Lindenberger, Douglas D. Garrett, Markus Werklebergner, Johannes J. FahrenfortAbstract:Decision bias is traditionally conceptualized as a flexible internal reference against which Sensory Evidence is compared. Here, in contrast, we show that experimental manipulation of decision bias adjusts the rate of Evidence accumulation in visual cortex towards one of the choice alternatives. Participants performed a visual detection task during EEG recordings. We experimentally manipulated participants response criterion using different stimulus-response reward contingencies, inducing liberal and conservative decision biases in different conditions. Drift diffusion modeling of choice behavior revealed that an experimentally induced liberal decision bias specifically biased the rate of Sensory Evidence accumulation towards yes choices. In visual cortex, the liberal bias manipulation suppressed prestimulus 8-12 Hz (alpha) power, which in turn boosted cortical stimulus-related activity in the 59-100 Hz (gamma) range. Together, these findings show that observers can intentionally control cortical excitability to strategically bias Evidence accumulation towards the decision bound that maximizes reward within a given ecological context.
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criterion setting modulates neural excitability of human visual cortex
bioRxiv, 2017Co-Authors: Niels A. Kloosterman, Jan Willem De Gee, Douglas D. Garrett, Markus Werklebergner, Johannes J. FahrenfortAbstract:Biases, systematic tendencies toward one choice option, are hallmarks of decision-making under uncertainty. In perceptual decision-making, bias can be conceptualized as an internal reference to which incoming Sensory Evidence is compared. This reference, often called criterion, can be flexibly adjusted to match external asymmetries in the payoffs for certain outcomes. Yet, very little is known about how the human brain implements such strategic criterion shifts. Recent studies suggest that spontaneous fluctuations in neural excitability (indexed by suppression of prestimulus alpha-band (8-12 Hz) power in posterior cortex) may impact the criterion. Crucially however, it is currently unknown whether neural excitability and criterion can flexibly and intentionally be adjusted to meet external demands. Here, we experimentally induced criterion shifts in humans through through verbal instruction and asymmetric reward contingencies and show for the first time that neural excitability is enhanced when humans adopt a liberal criterion compared to a more conservative criterion. Moreover, we show how increased excitability boosts subsequent stimulus-related visual cortical EEG activity in the gamma (59-100 Hz) range by enhancing Sensory response gain. Drift diffusion modeling of choice behaviour further confirms that a liberal criterion is achieved by biasing the Sensory Evidence accumulation process towards yes choices. Together, these findings show that humans are able to intentionally and flexibly adapt neural excitability to current task demands, and that such changes in excitability implement criterion shifts by biasing Sensory Evidence accumulation.
Zachary F. Mainen - One of the best experts on this subject based on the ideXlab platform.
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The impact of learning on perceptual decisions and its implication for speed-accuracy tradeoffs
Nature Communications, 2020Co-Authors: André G. Mendonça, Jan Drugowitsch, M. Inês Vicente, Eric E. J. Dewitt, Alexandre Pouget, Zachary F. MainenAbstract:Here, the authors show that rats’ performance on olfactory decision tasks is best explained by a Bayesian model that combines reinforcement-based learning with accumulation of uncertain Sensory Evidence. The results suggest that learning is a critical factor contributing to speed-accuracy tradeoffs. In standard models of perceptual decision-making, noisy Sensory Evidence is considered to be the primary source of choice errors and the accumulation of Evidence needed to overcome this noise gives rise to speed-accuracy tradeoffs. Here, we investigated how the history of recent choices and their outcomes interact with these processes using a combination of theory and experiment. We found that the speed and accuracy of performance of rats on olfactory decision tasks could be best explained by a Bayesian model that combines reinforcement-based learning with accumulation of uncertain Sensory Evidence. This model predicted the specific pattern of trial history effects that were found in the data. The results suggest that learning is a critical factor contributing to speed-accuracy tradeoffs in decision-making, and that task history effects are not simply biases but rather the signatures of an optimal learning strategy.
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the impact of learning on perceptual decisions and its implication for speed accuracy tradeoffs
Nature Communications, 2020Co-Authors: André G. Mendonça, Jan Drugowitsch, Eric E. J. Dewitt, Alexandre Pouget, Ines M Vicente, Zachary F. MainenAbstract:In standard models of perceptual decision-making, noisy Sensory Evidence is considered to be the primary source of choice errors and the accumulation of Evidence needed to overcome this noise gives rise to speed-accuracy tradeoffs. Here, we investigated how the history of recent choices and their outcomes interact with these processes using a combination of theory and experiment. We found that the speed and accuracy of performance of rats on olfactory decision tasks could be best explained by a Bayesian model that combines reinforcement-based learning with accumulation of uncertain Sensory Evidence. This model predicted the specific pattern of trial history effects that were found in the data. The results suggest that learning is a critical factor contributing to speed-accuracy tradeoffs in decision-making, and that task history effects are not simply biases but rather the signatures of an optimal learning strategy.
Tugce Tosun - One of the best experts on this subject based on the ideXlab platform.
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inhibition of pre supplementary motor area by continuous theta burst stimulation leads to more cautious decision making and more efficient Sensory Evidence integration
Journal of Cognitive Neuroscience, 2017Co-Authors: Tugce Tosun, Dilara Berkay, Alexander T Sack, Yusuf Ozgur Cakmak, Fuat BalciAbstract:Decisions are made based on the integration of available Evidence. The noise in Evidence accumulation leads to a particular speed-accuracy tradeoff in decision-making, which can be modulated and optimized by adaptive decision threshold setting. Given the effect of pre-SMA activity on striatal excitability, we hypothesized that the inhibition of pre-SMA would lead to higher decision thresholds and an increased accuracy bias. We used offline continuous theta burst stimulation to assess the effect of transient inhibition of the right pre-SMA on the decision processes in a free-response two-alternative forced-choice task within the drift diffusion model framework. Participants became more cautious and set higher decision thresholds following right pre-SMA inhibition compared with inhibition of the control site (vertex). Increased decision thresholds were accompanied by an accuracy bias with no effects on post-error choice behavior. Participants also exhibited higher drift rates as a result of pre-SMA inhibition compared with the vertex inhibition. These results, in line with the striatal theory of speed-accuracy tradeoff, provide Evidence for the functional role of pre-SMA activity in decision threshold modulation. Our results also suggest that pre-SMA might be a part of the brain network associated with the Sensory Evidence integration.
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Inhibition of Pre–Supplementary Motor Area by Continuous Theta Burst Stimulation Leads to More Cautious Decision-making and More Efficient Sensory Evidence Integration
Journal of cognitive neuroscience, 2017Co-Authors: Tugce Tosun, Dilara Berkay, Alexander T Sack, Yusuf Ozgur Cakmak, Fuat BalciAbstract:Decisions are made based on the integration of available Evidence. The noise in Evidence accumulation leads to a particular speed-accuracy tradeoff in decision-making, which can be modulated and optimized by adaptive decision threshold setting. Given the effect of pre-SMA activity on striatal excitability, we hypothesized that the inhibition of pre-SMA would lead to higher decision thresholds and an increased accuracy bias. We used offline continuous theta burst stimulation to assess the effect of transient inhibition of the right pre-SMA on the decision processes in a free-response two-alternative forced-choice task within the drift diffusion model framework. Participants became more cautious and set higher decision thresholds following right pre-SMA inhibition compared with inhibition of the control site (vertex). Increased decision thresholds were accompanied by an accuracy bias with no effects on post-error choice behavior. Participants also exhibited higher drift rates as a result of pre-SMA inhibition compared with the vertex inhibition. These results, in line with the striatal theory of speed-accuracy tradeoff, provide Evidence for the functional role of pre-SMA activity in decision threshold modulation. Our results also suggest that pre-SMA might be a part of the brain network associated with the Sensory Evidence integration.
André G. Mendonça - One of the best experts on this subject based on the ideXlab platform.
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The impact of learning on perceptual decisions and its implication for speed-accuracy tradeoffs
Nature Communications, 2020Co-Authors: André G. Mendonça, Jan Drugowitsch, M. Inês Vicente, Eric E. J. Dewitt, Alexandre Pouget, Zachary F. MainenAbstract:Here, the authors show that rats’ performance on olfactory decision tasks is best explained by a Bayesian model that combines reinforcement-based learning with accumulation of uncertain Sensory Evidence. The results suggest that learning is a critical factor contributing to speed-accuracy tradeoffs. In standard models of perceptual decision-making, noisy Sensory Evidence is considered to be the primary source of choice errors and the accumulation of Evidence needed to overcome this noise gives rise to speed-accuracy tradeoffs. Here, we investigated how the history of recent choices and their outcomes interact with these processes using a combination of theory and experiment. We found that the speed and accuracy of performance of rats on olfactory decision tasks could be best explained by a Bayesian model that combines reinforcement-based learning with accumulation of uncertain Sensory Evidence. This model predicted the specific pattern of trial history effects that were found in the data. The results suggest that learning is a critical factor contributing to speed-accuracy tradeoffs in decision-making, and that task history effects are not simply biases but rather the signatures of an optimal learning strategy.
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the impact of learning on perceptual decisions and its implication for speed accuracy tradeoffs
Nature Communications, 2020Co-Authors: André G. Mendonça, Jan Drugowitsch, Eric E. J. Dewitt, Alexandre Pouget, Ines M Vicente, Zachary F. MainenAbstract:In standard models of perceptual decision-making, noisy Sensory Evidence is considered to be the primary source of choice errors and the accumulation of Evidence needed to overcome this noise gives rise to speed-accuracy tradeoffs. Here, we investigated how the history of recent choices and their outcomes interact with these processes using a combination of theory and experiment. We found that the speed and accuracy of performance of rats on olfactory decision tasks could be best explained by a Bayesian model that combines reinforcement-based learning with accumulation of uncertain Sensory Evidence. This model predicted the specific pattern of trial history effects that were found in the data. The results suggest that learning is a critical factor contributing to speed-accuracy tradeoffs in decision-making, and that task history effects are not simply biases but rather the signatures of an optimal learning strategy.
