scholarly journals Representations of evidence for a perceptual decision in the human brain

2018 ◽  
Author(s):  
Sebastian Bitzer ◽  
Hame Park ◽  
Burkhard Maess ◽  
Katharina von Kriegstein ◽  
Stefan Kiebel

In perceptual decision making the brain extracts and accumulates decision evidence from a stimulus over time and eventually makes a decision based on the accumulated evidence. Several characteristics of this process have been observed in human electrophysiological experiments, especially an average build-up of motor-related signals supposedly reflecting accumulated evidence, when averaged across trials. Another recently established approach to investigate the representation of decision evidence in brain signals is to correlate the within-trial fluctuations of decision evidence with the measured signals. We here report results for a two-alternative forced choice reaction time experiment in which we applied this approach to human magnetoencephalographic (MEG) recordings. These results consolidate a range of previous findings. In addition, they show: 1) that decision evidence is most strongly represented in the MEG signals in three consecutive phases, 2) that motor areas contribute longer to these representations than parietal areas and 3) that posterior cingulate cortex is involved most consistently, among all brain areas, in all three of the identified phases. As most previous work on perceptual decision making in the brain has focused on parietal and motor areas, our findings therefore suggest that the role of the posterior cingulate cortex in perceptual decision making may be currently underestimated.

2018 ◽  
Vol 115 (7) ◽  
pp. E1588-E1597 ◽  
Author(s):  
Brian Odegaard ◽  
Piercesare Grimaldi ◽  
Seong Hah Cho ◽  
Megan A. K. Peters ◽  
Hakwan Lau ◽  
...  

Recent studies suggest that neurons in sensorimotor circuits involved in perceptual decision-making also play a role in decision confidence. In these studies, confidence is often considered to be an optimal readout of the probability that a decision is correct. However, the information leading to decision accuracy and the report of confidence often covaried, leaving open the possibility that there are actually two dissociable signal types in the brain: signals that correlate with decision accuracy (optimal confidence) and signals that correlate with subjects’ behavioral reports of confidence (subjective confidence). We recorded neuronal activity from a sensorimotor decision area, the superior colliculus (SC) of monkeys, while they performed two different tasks. In our first task, decision accuracy and confidence covaried, as in previous studies. In our second task, we implemented a motion discrimination task with stimuli that were matched for decision accuracy but produced different levels of confidence, as reflected by behavioral reports. We used a multivariate decoder to predict monkeys’ choices from neuronal population activity. As in previous studies on perceptual decision-making mechanisms, we found that neuronal decoding performance increased as decision accuracy increased. However, when decision accuracy was matched, performance of the decoder was similar between high and low subjective confidence conditions. These results show that the SC likely signals optimal decision confidence similar to previously reported cortical mechanisms, but is unlikely to play a critical role in subjective confidence. The results also motivate future investigations to determine where in the brain signals related to subjective confidence reside.


2017 ◽  
Author(s):  
Brian Odegaard ◽  
Piercesare Grimaldi ◽  
Seong Hah Cho ◽  
Megan A.K. Peters ◽  
Hakwan Lau ◽  
...  

AbstractRecent studies suggest that neurons in sensorimotor circuits involved in perceptual decision-making also play a role in decision confidence. In these studies, confidence is often considered to be an optimal readout of the probability that a decision is correct. However, the information leading to decision accuracy and the report of confidence often co-varied, leaving open the possibility that there are actually two dissociable signal types in the brain: signals that correlate with decision accuracy (optimal confidence) and signals that correlate with subjects’ behavioral reports of confidence (subjective confidence). We recorded neuronal activity from a sensorimotor decision area, the superior colliculus (SC) of monkeys, while they performed two different tasks. In our first task, decision accuracy and confidence co-varied, as in previous studies. In our second task, we implemented a novel motion discrimination task with stimuli that were matched for decision accuracy but produced different levels of confidence as reflected by behavioral reports. We used a multivariate decoder to predict monkeys’ choices from neuronal population activity. As in previous studies on perceptual decision-making mechanisms, we found that neuronal decoding performance increased as decision accuracy increased. However, when decision accuracy was matched, performance of the decoder was similar between high and low subjective confidence conditions. These results show that the SC likely signals optimal decision confidence similar to previously reported cortical mechanisms, but is unlikely to play a critical role in subjective confidence. The results also motivate future investigations to determine where in the brain signals related to subjective confidence reside.Significance StatementConfidence is thought to reflect the rational or optimal belief concerning one’s choice accuracy. Here, we introduce a novel version of the dot-motion discrimination task with stimulus conditions that produce similar accuracy but different subjective behavioral reports of confidence. We decoded decision performance of this task from neuronal signals in the superior colliculus (SC), a subcortical region involved in decision-making. We found that SC activity signaled a perceptual decision for visual stimuli, with the strength of this activity reflecting decision accuracy, but not the subjective level of confidence as reflected by behavioral reports. These results demonstrate an important role for the SC in perceptual decision-making and challenge current ideas about how to measure subjective confidence in monkeys and humans.


Author(s):  
Genís Prat-Ortega ◽  
Klaus Wimmer ◽  
Alex Roxin ◽  
Jaime de la Rocha

AbstractPerceptual decisions require the brain to make categorical choices based on accumulated sensory evidence. The underlying computations have been studied using either phenomenological drift diffusion models or neurobiological network models exhibiting winner-take-all attractor dynamics. Although both classes of models can account for a large body of experimental data, it remains unclear to what extent their dynamics are qualitatively equivalent. Here we show that, unlike the drift diffusion model, the attractor model can operate in different integration regimes: an increase in the stimulus fluctuations or the stimulus duration promotes transitions between decision-states leading to a crossover between weighting mostly early evidence (primacy regime) to weighting late evidence (recency regime). Between these two limiting cases, we found a novel regime, which we name flexible categorization, in which fluctuations are strong enough to reverse initial categorizations, but only if they are incorrect. This asymmetry in the reversing probability results in a non-monotonic psychometric curve, a novel and distinctive feature of the attractor model. Finally, we show psychophysical evidence for the crossover between integration regimes predicted by the attractor model and for the relevance of this new regime. Our findings point to correcting transitions as an important yet overlooked feature of perceptual decision making.


2012 ◽  
Vol 32 (1) ◽  
pp. 215-222 ◽  
Author(s):  
R. Leech ◽  
R. Braga ◽  
D. J. Sharp

2021 ◽  
Author(s):  
Kyra Schapiro ◽  
Kresimir Josic ◽  
Zachary Kilpatrick ◽  
Joshua I Gold

Deliberative decisions based on an accumulation of evidence over time depend on working memory, and working memory has limitations, but how these limitations affect deliberative decision-making is not understood. We used human psychophysics to assess the impact of working-memory limitations on the fidelity of a continuous decision variable. Participants decided the average location of multiple visual targets. This computed, continuous decision variable degraded with time and capacity in a manner that depended critically on the strategy used to form the decision variable. This dependence reflected whether the decision variable was computed either: 1) immediately upon observing the evidence, and thus stored as a single value in memory; or 2) at the time of the report, and thus stored as multiple values in memory. These results provide important constraints on how the brain computes and maintains temporally dynamic decision variables.


2018 ◽  
Author(s):  
Ben Deverett ◽  
Sue Ann Koay ◽  
Marlies Oostland ◽  
Samuel S.-H. Wang

To make successful evidence-based decisions, the brain must rapidly and accurately transform sensory inputs into specific goal-directed behaviors. Most experimental work on this subject has focused on forebrain mechanisms. Here we show that during perceptual decision-making over a period of seconds, decision-, sensory-, and error-related information converge on the lateral posterior cerebellum in crus I, a structure that communicates bidirectionally with numerous forebrain regions. We trained mice on a novel evidence-accumulation task and demonstrated that cerebellar inactivation reduces behavioral accuracy without impairing motor parameters of action. Using two-photon calcium imaging, we found that Purkinje cell somatic activity encoded choice- and evidence-related variables. Decision errors were represented by dendritic calcium spikes, which are known to drive plasticity. We propose that cerebellar circuitry may contribute to the set of distributed computations in the brain that support accurate perceptual decision-making.


2020 ◽  
Vol 19 (4) ◽  
pp. 290-305
Author(s):  
Silvia S. Hidalgo Tobón ◽  
Pilar Dies Suárez ◽  
Eduardo Barragán Pérez ◽  
Javier M. Hernández López ◽  
Julio García ◽  
...  

Introduction: Lisdexamfetamine (LDX) is a drug used to treat ADHD/impulsive patients. Impulsivity is known to affect inhibitory, emotional and cognitive function. On the other hand, smell and odor processing are known to be affected by neurological disorders, as they are modulators of addictive and impulsive behaviors specifically. We hypothesize that, after LDX ingestion, inhibitory pathways of the brain would change, and complementary behavioral regulation mechanisms would appear to regulate decision-making and impulsivity. Methods: 20 children were studied in an aleatory crossover study. Imaging of BOLD-fMRI activity, elicited by olfactory stimulation in impulsive children, was performed after either LDX or placebo ingestion. Results: Findings showed that all subjects who underwent odor stimulation presented activations of similar intensities in the olfactory centers of the brain. This contrasted with inhibitory regions of the brain such as the cingulate cortex and frontal lobe regions, which demonstrated changed activity patterns and intensities. While some differences between the placebo and medicated states were found in motor areas, precuneus, cuneus, calcarine, supramarginal, cerebellum and posterior cingulate cortex, the main changes were found in frontal, temporal and parietal cortices. When comparing olfactory cues separately, pleasant food smells like chocolate seemed not to present large differences between the medicated and placebo scenarios, when compared to non-food-related smells. Conclusions: It was demonstrated that LDX, first, altered the inhibitory pathways of the brain, secondly it increased activity in several brain regions which were not activated by smell in drug-naïve patients, and thirdly, it facilitated a complementary behavioral regulation mechanism, run by the cerebellum, which regulated decision-making and impulsivity in motor and frontal structures.


2020 ◽  
Vol 30 (10) ◽  
pp. 5471-5483
Author(s):  
Y Yau ◽  
M Dadar ◽  
M Taylor ◽  
Y Zeighami ◽  
L K Fellows ◽  
...  

Abstract Current models of decision-making assume that the brain gradually accumulates evidence and drifts toward a threshold that, once crossed, results in a choice selection. These models have been especially successful in primate research; however, transposing them to human fMRI paradigms has proved it to be challenging. Here, we exploit the face-selective visual system and test whether decoded emotional facial features from multivariate fMRI signals during a dynamic perceptual decision-making task are related to the parameters of computational models of decision-making. We show that trial-by-trial variations in the pattern of neural activity in the fusiform gyrus reflect facial emotional information and modulate drift rates during deliberation. We also observed an inverse-urgency signal based in the caudate nucleus that was independent of sensory information but appeared to slow decisions, particularly when information in the task was ambiguous. Taken together, our results characterize how decision parameters from a computational model (i.e., drift rate and urgency signal) are involved in perceptual decision-making and reflected in the activity of the human brain.


2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Rinaldo Livio Perri ◽  
Marika Berchicci ◽  
Giuliana Lucci ◽  
Donatella Spinelli ◽  
Francesco Di Russo

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