A Neural Representation of Categorization Uncertainty in the Human Brain

Grinband, Jack; Hirsch, Joy; Ferrera, Vincent P.

doi:10.1016/j.neuron.2006.01.032

Cited by 321 publications

(302 citation statements)

References 36 publications

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“…For instance, someone may forego possible large rewards in favour of smaller, but less uncertain, rewards (risk aversion). Imaging studies report increased AI signals when making risky decisions (gambles) compared to safe decisions 13 and in response to increasing task 'instability' 30 , complexity 31 and ambiguity 11 , which engender uncertainty through lack of knowledge. Mathematical tools derived from economics permit a mechanistic description of how AI represents risk and uncertainty: In a decision-making task, if the probability and magnitude of each potential outcome are known, the precise risk of each decision can be calculated.…”

Section: The Role Of Anterior Insula In Uncertainty and Uncertainty Pmentioning

confidence: 99%

A common role of insula in feelings, empathy and uncertainty

Singer

Critchley

Preuschoff

2009

Trends in Cognitive Sciences

1,142

735

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Section: The Role Of Anterior Insula In Uncertainty and Uncertainty Pmentioning

confidence: 99%

A common role of insula in feelings, empathy and uncertainty

Singer

Critchley

Preuschoff

2009

Trends in Cognitive Sciences

1,142

735

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“…such as perceptual salience or response uncertainty (Grinband et al, 2006;Kayser et al, 2010a). With respect to these processes, perceptual salience, for example, might give rise to a parametric BOLD effect during the Stimulus phase; but it would not easily explain nonparametric peak activity during the response phase, when the stimulus is absent.…”

Section: Stimulusmentioning

confidence: 99%

The neural representation of sensorimotor transformations in a human perceptual decision making network

Erickson

Kayser

2013

NeuroImage

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Humans can quickly engage a neural network to transform complex visual stimuli into a motor response. Activity from a key region within this network, the intraparietal sulcus (IPS), has been associated with evidence accumulation and motor planning, thus implicating it in sensorimotor transformations. If such transformations occur within a brain region, a key and untested prediction is that neural activity reflecting both the parametric amount of evidence available and the timing of motor planning can be independently manipulated. To investigate these ideas, we constructed a dot motion discrimination task in which information about response modality (what to use) and response mapping (how to use it) was provided independently either before or after presentation of a dot motion coherence stimulus whose strength varied across trials. Consistent with our hypothesis, activity within IPS covaried with dot motion coherence during the stimulus phase, and as information necessary for the response was delayed, the peak of IPS activity shifted to the response phase. In contrast, areas such as the motion-sensitive region MT+ and the supplementary motor area demonstrated activity limited to the stimulus and response phases of the task, respectively. These results show that activity in IPS correlates with temporally dissociable representations consistent with both evidence accumulation and motor planning, and suggest that IPS is a core component for sensorimotor transformations within the perceptual decision-making network.© 2013 Elsevier Inc. All rights reserved. IntroductionThe ability to link sensation with action is integral to even the most fundamental of decisions. In humans, a number of studies have identified a frontoparietal network involved in processes during perceptual decisions, including sensory processing, attentional control, evidence accumulation, and motor planning (Heekeren et al., 2008; Kayser et al., 2010a,b;Liu and Pleskac, 2011;Ploran et al., 2007Ploran et al., , 2011Rowe et al., 2010;Ho et al., 2009;Tosoni et al., 2008). Previously we demonstrated that for subjects performing a dot motion discrimination task, this network displays a blood oxygen level-dependent (BOLD) response that varies inversely with motion coherence (Kayser et al., 2010a). Consistent with previous and subsequent findings (e.g., Hebart et al., 2012;Ho et al., 2009;Kayser et al., 2010b), this negative parametric effect matched predictions of a proportional-rate diffusion model for evidence accumulation to a threshold (Palmer et al., 2005;Ratcliff and McKoon, 2008), and linked human brain activity with a computational model of the transformation from stimulus to response.Although this parametric effect is necessary, it is not sufficient to define regions that support such sensorimotor transformations. Human studies, for example, show that areas such as the motion-sensitive region MT+, supplementary motor area (SMA), and intraparietal sulcus (IPS) all display this parametric effect. Importantly, results from macaque studies show that ...

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“…Closely linked to the OFC in its evaluative function is the striatum that was similarly active in the interaction contrast (Grinband, Hirsch, & Ferrera, 2006;Oenguer, Ferry, & Price, 2003;Schoenbaum, Roesch, Stalnaker, & Takahashi, 2009). …”

Section: Bias Vs Balance -Prefrontally Mediated Integration Of Incommentioning

confidence: 99%

Neural changes when actions change: Adaptation of strong and weak expectations

Schiffer

Ahlheim

Ulrichs

et al. 2012

Human Brain Mapping

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Repeated experiences with an event create the expectation that subsequent events will expose an analog structure. These spontaneous expectations rely on an internal model of the event that results from learning. But what happens when events change? Do experience-based internal models get adapted instantaneously, or is model adaptation a function of the solidity of, i.e. familiarity with, the corresponding internal model? The present fMRI study investigated the effects of model solidity on model adaptation in an action observation paradigm. Subjects were made acquainted with a set of action movies that displayed an altered script when encountered again in the scanning session. We found model adaptation to result in an attenuation of the premotor-parietal network for action observation. Model solidity was found to modulate activation in the parahippocampal gyrus and the anterior cerebellar lobules, where increased solidity correlated with activity increase. Finally, the comparison between early and late stages of learning indicated an effect of model solidity on adaptation rate. This contrast revealed the involvement of a fronto-mesial network of Brodmann area 10 and the ACC in those states of learning that were signified by high model solidity, no matter if the memorized original or to the altered action model was the more solid component. Findings suggest that the revision of an internal model is dependent on its familiarity. Unwarranted adaptations, but also perseverations may thus be prevented.

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A Neural Representation of Categorization Uncertainty in the Human Brain

Cited by 321 publications

References 36 publications

A common role of insula in feelings, empathy and uncertainty

A common role of insula in feelings, empathy and uncertainty

The neural representation of sensorimotor transformations in a human perceptual decision making network

Neural changes when actions change: Adaptation of strong and weak expectations

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