scholarly journals Accumulation of continuously time-varying sensory evidence constrains neural and behavioral responses in human collision threat detection

2021 ◽  
Vol 17 (7) ◽  
pp. e1009096
Author(s):  
Gustav Markkula ◽  
Zeynep Uludağ ◽  
Richard McGilchrist Wilkie ◽  
Jac Billington
Keyword(s):  
Decision Making ◽  
Behavioral Responses ◽  
Brain Regions ◽  
Threat Detection ◽  
Time Varying ◽  
Evidence Accumulation ◽  
Human Decision ◽  
Detection Response ◽  
Sensory Evidence ◽  
Successful Behavior

Evidence accumulation models provide a dominant account of human decision-making, and have been particularly successful at explaining behavioral and neural data in laboratory paradigms using abstract, stationary stimuli. It has been proposed, but with limited in-depth investigation so far, that similar decision-making mechanisms are involved in tasks of a more embodied nature, such as movement and locomotion, by directly accumulating externally measurable sensory quantities of which the precise, typically continuously time-varying, magnitudes are important for successful behavior. Here, we leverage collision threat detection as a task which is ecologically relevant in this sense, but which can also be rigorously observed and modelled in a laboratory setting. Conventionally, it is assumed that humans are limited in this task by a perceptual threshold on the optical expansion rate–the visual looming–of the obstacle. Using concurrent recordings of EEG and behavioral responses, we disprove this conventional assumption, and instead provide strong evidence that humans detect collision threats by accumulating the continuously time-varying visual looming signal. Generalizing existing accumulator model assumptions from stationary to time-varying sensory evidence, we show that our model accounts for previously unexplained empirical observations and full distributions of detection response. We replicate a pre-response centroparietal positivity (CPP) in scalp potentials, which has previously been found to correlate with accumulated decision evidence. In contrast with these existing findings, we show that our model is capable of predicting the onset of the CPP signature rather than its buildup, suggesting that neural evidence accumulation is implemented differently, possibly in distinct brain regions, in collision detection compared to previously studied paradigms.

scholarly journals Evidence accumulation, not a perceptual threshold, constrains neural and behavioural responses in human collision threat detection

2020 ◽  
Author(s):  
Gustav Markkula ◽  
Zeynep Uludağ ◽  
Richard Wilkie ◽  
Jac Billington
Keyword(s):  
Collision Detection ◽  
Applied Research ◽  
Brain Regions ◽  
Detection Task ◽  
Threat Detection ◽  
Time Varying ◽  
Evidence Accumulation ◽  
Behavioural Responses ◽  
Basic And Applied Research ◽  
Perceptual Threshold

Detection of impending collision is fundamental to many human activities, and is widely assumed to be limited by a ‘looming threshold’. Evidence accumulation models explain decision-making in abstract paradigms, but have not been shown to remain valid for continuously time-varying, ecologically relevant stimuli. Here, we record behavioural and EEG responses in a collision detection task, disprove the conventional looming threshold assumption, and instead provide stringent evidence for a looming accumulation model. Generalising existing model assumptions from stationary to time-varying evidence, we show that our model accounts for previously unexplained observations and full distributions of detection. We replicate a centroparietal pre-decision positivity in scalp potentials, and show that our model explains its onset rather than its buildup, suggesting that neural evidence accumulation is implemented differently, possibly in distinct brain regions, in collision detection compared to previous paradigms. Our findings illustrate the value of connecting basic and applied research on human behaviour.

scholarly journals The speed-accuracy tradeoff reveals flexible access to accumulating sensory evidence during human decision making

2018 ◽  
Author(s):  
Stephanie Nelli ◽  
Sirawaj Itthipuripat ◽  
Nuttida Rungratsameetaweemana ◽  
John T. Serences
Keyword(s):  
Decision Making ◽  
Task Demands ◽  
Event Related Potential ◽  
Response Threshold ◽  
Evidence Accumulation ◽  
Human Decision ◽  
Sensory Evidence ◽  
Adaptively Adjusting ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

AbstractDecisions made about identical perceptual stimuli can be radically different under changing task demands. For example, the need to make a fast decision undermines the accuracy of that decision, a well-documented effect termed the speed-accuracy tradeoff (SAT). Models of the SAT are generally based on theories of decision making in which responses are triggered only after sensory evidence accumulation terminates at a set threshold. Within this accumulate-to-bound framework, speed pressure operates by lowering the response threshold, allowing for faster responses at the expense of accumulated sensory evidence. To empirically examine the mechanisms necessary for adaptively adjusting the speed and accuracy of decisions, we used an event-related potential that indexes sensory evidence accumulation in the human brain. Instead of lowering response thresholds, we found that speed pressure adaptively shifts responses to occur close to where the rate of evidence accumulation peaks. Moreover, responses are not triggered automatically by the termination of the accumulation process, as sensory evidence continues to build after speeded decisions. Together these results suggest that response processes adaptively access accumulating sensory evidence depending on task demands and support parallel over serial models of decision making.

Human Medial Orbitofrontal Cortex Is Recruited During Experience of Imagined and Real Rewards

2010 ◽  
Vol 103 (5) ◽  
pp. 2506-2512 ◽  
Author(s):  
Signe Bray ◽  
Shinsuke Shimojo ◽  
John P. O'Doherty
Keyword(s):  
Decision Making ◽  
Orbitofrontal Cortex ◽  
Critical Role ◽  
Brain Regions ◽  
Mental Simulation ◽  
Human Decision ◽  
Tangible Rewards ◽  
Action Choice

Human decision-making frequently relies on mental simulation of future rewards to guide action choice. In this study, we sought to uncover brain regions engaged during reward imagery and to address whether these regions functionally overlap with regions activated by tangible rewards. We found that medial orbitofrontal cortex (mOFC) is engaged both for real and imagined rewards and is preferentially engaged for imagery with rewarding content compared with other nonrewarding imagery. These findings support a critical role for mOFC in the representation of rewarding goal states, even if hypothetical.

scholarly journals Pupil-linked arousal biases evidence accumulation towards desirable percepts during perceptual decision-making

2020 ◽  
Author(s):  
Yuan Chang Leong ◽  
Roma Dziembaj ◽  
Mark D’Esposito
Keyword(s):  
Decision Making ◽  
Computational Models ◽  
Visual Image ◽  
Perceptual Decision Making ◽  
Evidence Accumulation ◽  
Perceptual Judgments ◽  
Arousal System ◽  
Sensory Evidence ◽  
Arousal Response ◽  
Objective Representation

AbstractPeople are biased towards seeing outcomes they are motivated to see. The arousal system coordinates the body’s response to motivationally significant events, and is well positioned to regulate motivational effects on sensory perception. However, it remains unclear whether arousal would enhance or reduce motivational biases. Here we measured pupil dilation as a measure of arousal while participants performed a visual categorization task. We used monetary bonuses to motivate participants to see one category over another. Even though the reward-maximizing strategy was to perform the task accurately, participants were more likely to report seeing the motivationally desirable category. Furthermore, higher arousal levels were associated with making motivationally biased responses. Analyses using computational models indicated that arousal enhanced motivational effects by biasing evidence accumulation in favor of motivationally desirable percepts. These results suggest heightened arousal biases people towards what they want to see and away from an objective representation of the environment.Statement of RelevanceWhen confronted with an event of motivational significance (e.g., an opportunity to earn a huge reward), people often experience a strong arousal response that includes increased sweating, faster heart-rate and larger pupils. Does this arousal response help individuals make more accurate decisions, or does it instead bias and impair decision-making? This work examines the effects of arousal on how people decide what they see when they are motivated to see a particular outcome. We found that heightened arousal, as measured by larger pupils, was associated with a bias in how participants accumulated sensory evidence to make their decisions. As a result, participants became more likely to report seeing an ambiguous visual image as the interpretation they were motivated to see. Our results suggest that arousal biases perceptual judgments towards desirable percepts, and that modulating arousal levels could be a promising approach in reducing motivational biases in decision-making.

Decision Confidence and Uncertainty in Diffusion Models with Partially Correlated Neuronal Integrators

2010 ◽  
Vol 22 (7) ◽  
pp. 1786-1811 ◽  
Author(s):  
Rubén Moreno-Bote
Keyword(s):  
Decision Making ◽  
Exact Solution ◽  
Reaction Times ◽  
Decision Time ◽  
Diffusion Models ◽  
Time Varying ◽  
Decision Confidence ◽  
Human Decision ◽  
Decision Boundaries ◽  
Natural Description

Diffusion models have become essential for describing the performance and statistics of reaction times in human decision making. Despite their success, it is not known how to evaluate decision confidence from them. I introduce a broader class of models consisting of two partially correlated neuronal integrators with arbitrarily time-varying decision boundaries that allow a natural description of confidence. The dependence of decision confidence on the state of the losing integrator, decision time, time-varying boundaries, and correlations is analytically described. The marginal confidence is computed for the half-anticorrelated case using the exact solution of the diffusion process with constant boundaries and compared to that of the independent and completely anticorrelated cases.

scholarly journals Distinct effects of prefrontal and parietal cortex inactivations on an accumulation of evidence task in the rat

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Jeffrey C Erlich ◽  
Bingni W Brunton ◽  
Chunyu A Duan ◽  
Timothy D Hanks ◽  
Carlos D Brody
Keyword(s):  
Decision Making ◽  
Parietal Cortex ◽  
Posterior Parietal Cortex ◽  
Neural Correlates ◽  
Brain Regions ◽  
Integration Time ◽  
Detailed Model ◽  
Evidence Accumulation ◽  
Posterior Parietal ◽  
Cortical Regions

Numerous brain regions have been shown to have neural correlates of gradually accumulating evidence for decision-making, but the causal roles of these regions in decisions driven by accumulation of evidence have yet to be determined. Here, in rats performing an auditory evidence accumulation task, we inactivated the frontal orienting fields (FOF) and posterior parietal cortex (PPC), two rat cortical regions that have neural correlates of accumulating evidence and that have been proposed as central to decision-making. We used a detailed model of the decision process to analyze the effect of inactivations. Inactivation of the FOF induced substantial performance impairments that were quantitatively best described as an impairment in the output pathway of an evidence accumulator with a long integration time constant (>240 ms). In contrast, we found a minimal role for PPC in decisions guided by accumulating auditory evidence, even while finding a strong role for PPC in internally-guided decisions.

scholarly journals Distinct behavioral effects of prefrontal and parietal cortex inactivations on an accumulation of evidence task in the rat

2014 ◽  
Author(s):  
Jeffrey C Erlich ◽  
Bingni W Brunton ◽  
Chunyu A Duan ◽  
Timothy D Hanks ◽  
Carlos D Brody
Keyword(s):  
Decision Making ◽  
Parietal Cortex ◽  
Posterior Parietal Cortex ◽  
Neural Correlates ◽  
Brain Regions ◽  
Integration Time ◽  
Detailed Model ◽  
Evidence Accumulation ◽  
Posterior Parietal ◽  
Cortical Regions

Numerous brain regions have been shown to have neural correlates of gradually accumulating evidence for decision-making, but the causal roles of these regions in decisions driven by accumulation of evi- dence have yet to be determined. Here, in rats performing an auditory evidence accumulation task, we inactivated the frontal orienting fields (FOF) and posterior parietal cortex (PPC), two rat cortical regions that have neural correlates of accumulating evidence and that have been proposed as central to decision-making. We used a detailed model of the decision process to analyze the effect of inactivations. Inactivation of the FOF induced substantial performance impairments that were quantitatively best de- scribed as an impairment in the output pathway of an evidence accumulator with a long integration time constant (>240ms). In contrast, we found a minimal role for PPC in decisions guided by accumulating auditory evidence, even while finding a strong role for PPC in internally-guided decisions.

scholarly journals Evidence and urgency related EEG signals during dynamic decision-making in humans

2020 ◽  
Author(s):  
Y. Yau ◽  
T. Hinault ◽  
M. Taylor ◽  
P. Cisek ◽  
L.K. Fellows ◽  
...  
Keyword(s):  
Decision Making ◽  
Dynamic Decision Making ◽  
Decision Variable ◽  
Decision Threshold ◽  
Neural Signals ◽  
Addictive Disorders ◽  
Evidence Accumulation ◽  
Gating Model ◽  
Decision Variables ◽  
Sensory Evidence

AbstractA successful class of models link decision-making to brain signals by assuming that evidence accumulates to a decision threshold. These evidence accumulation models have identified neuronal activity that appears to reflect sensory evidence and decision variables that drive behavior. More recently, an additional evidence-independent and time-variant signal, named urgency, has been hypothesized to accelerate decisions in the face of insufficient evidence. However, most decision-making paradigms tested with fMRI or EEG in humans have not been designed to disentangle evidence accumulation from urgency. Here we use a face-morphing decision-making task in combination with EEG and a hierarchical Bayesian model to identify neural signals related to sensory and decision variables, and to test the urgency-gating model. We find that an evoked potential time-locked to the decision, the centroparietal positivity, reflects the decision variable from the computational model. We further show that the unfolding of this signal throughout the decision process best reflects the product of sensory evidence and an evidence-independent urgency signal. Urgency varied across subjects, suggesting that it may represent an individual trait. Our results show that it is possible to use EEG to distinguish neural signals related to sensory evidence accumulation, decision variables, and urgency. These mechanisms expose principles of cognitive function in general and may have applications to the study of pathological decision-making as in impulse control and addictive disorders.Significance StatementPerceptual decisions are often described by a class of models that assumes sensory evidence accumulates gradually over time until a decision threshold is reached. In the present study, we demonstrate that an additional urgency signal impacts how decisions are formed. This endogenous signal encourages one to respond as time elapses. We found that neural decision signals measured by EEG reflect the product of sensory evidence and an evidence-independent urgency signal. A nuanced understanding of human decisions, and the neural mechanisms that support it, can improve decision-making in many situations and potentially ameliorate dysfunction when it has gone awry.

scholarly journals Predictive activation of sensory representations as a source of evidence in perceptual decision-making

2020 ◽  
Author(s):  
Daniel Feuerriegel ◽  
Tessel Blom ◽  
Hinze Hogendoorn
Keyword(s):  
Decision Making ◽  
Decision Model ◽  
Perceptual Decision Making ◽  
Specific Stimulus ◽  
Perceptual Decision ◽  
Evidence Accumulation ◽  
Neural Representations ◽  
Sensory Environment ◽  
Sensory Evidence ◽  
Diffusion Decision Model

Our brains can represent expected future states of our sensory environment. Recent work has shown that, when we expect a specific stimulus to appear at a specific time, we can predictively generate neural representations of that stimulus even before it is physically presented. These observations raise two exciting questions: Are pre-activated sensory representations used for perceptual decision-making? And, are there instances in which we transiently perceive an expected stimulus that does not actually appear? To address these questions, we propose that pre-activated neural representations provide sensory evidence that is used for perceptual decision-making. This can be understood within the framework of the Diffusion Decision Model as an early accumulation of decision evidence in favour of the expected percept. Our proposal makes novel predictions relating to expectation effects on neural markers of decision evidence accumulation, and also provides an explanation for why we do not typically perceive stimuli that are expected, but do not appear.

scholarly journals Neural population dynamics underlying evidence accumulation in multiple rat brain regions

2021 ◽  
Author(s):  
Brian DePasquale ◽  
Jonathan W Pillow ◽  
Carlos Brody
Keyword(s):  
Decision Making ◽  
Neural Activity ◽  
Posterior Parietal Cortex ◽  
Dorsal Striatum ◽  
Brain Regions ◽  
Neural Representation ◽  
Neural Population ◽  
Evidence Accumulation ◽  
Posterior Parietal ◽  
The Moment

Accumulating evidence in service of sensory decision making is a core cognitive function. However, previous work has focused either on the dynamics of neural activity during decision-making or on models of evidence accumulation governing behavior. We unify these two perspectives by introducing an evidence-accumulation framework that simultaneously describes multi-neuron population spiking activity and dynamic stimulus-driven behavior during sensory decision-making. We apply our method to behavioral choices and neural activity recorded from three brain regions - the posterior parietal cortex (PPC), the frontal orienting fields (FOF), and the anterior-dorsal striatum (ADS) - while rats performed a pulse-based accumulation task. The model accurately captures the relationship between stimuli and neural activity, the coordinated activity of neural populations, and the distribution of animal choices in response to the stimulus. Model fits show strikingly distinct accumulation models expressed within each brain region, and that all differ strongly from the accumulation strategy expressed at the level of choices. In particular, the FOF exhibited a suboptimal 'primacy' strategy, where early sensory evidence was favored. Including neural data in the model led to improved prediction of the moment-by-moment value of accumulated evidence and the intended-and ultimately made-choice of the animal. Our approach offers a window into the neural representation of accumulated evidence and provides a principled framework for incorporating neural responses into accumulation models.

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