scholarly journals Humans sacrifice decision-making for action execution when a demanding control of movement is required

2020 ◽  
Author(s):  
Amélie J. Reynaud ◽  
Clara Saleri Lunazzi ◽  
David Thura
Keyword(s):  
Decision Making ◽  
Human Subjects ◽  
Decision Task ◽  
Shared Decision ◽  
Perceptual Decision Making ◽  
Action Execution ◽  
Starting Position ◽  
Decision Speed ◽  
Urgency Level ◽  
Speed And Accuracy

ABSTRACTA growing body of evidence suggests that decision-making and action execution are governed by partly overlapping operating principles. Especially, previous work proposed that a shared decision urgency/movement vigor signal, possibly computed in the basal ganglia, coordinates both deliberation and movement durations in a way that maximizes the reward rate. Recent data support one aspect of this hypothesis, indicating that the urgency level at which a decision is made influences the vigor of the movement produced to express this choice. Here we investigated whether conversely, the motor context in which a movement is executed determines decision speed and accuracy. Twenty human subjects performed a probabilistic decision task in which perceptual choices were expressed by reaching movements toward targets whose size and distance from a starting position varied in distinct blocks of trials. We found strong evidence for an influence of the motor context on most of the subjects’ decision policy but contrary to the predictions of the “shared regulation” hypothesis, we observed that slow movements executed in the most demanding motor blocks in terms of accuracy were often preceded by faster and less accurate decisions compared to blocks of trials in which big targets allowed expression of choices with fast and inaccurate movements. These results suggest that decision-making and motor control are not regulated by one unique “invigoration” signal determining both decision urgency and action vigor, but more likely by independent, yet interacting, decision urgency and movement vigor signals.NEW & NOTEWORTHYRecent hypotheses propose that choices and movements share optimization principles derived from economy, possibly implemented by one unique context-dependent regulation signal determining both processes speed. In the present behavioral study conducted on human subjects, we demonstrate that action properties indeed influence perceptual decision-making, but that decision duration and action vigor are actually independently set depending on the difficulty of the movement executed to report a choice.

scholarly journals Humans sacrifice decision-making for action execution when a demanding control of movement is required

2020 ◽  
Vol 124 (2) ◽  
pp. 497-509
Author(s):  
Amélie J. Reynaud ◽  
Clara Saleri Lunazzi ◽  
David Thura
Keyword(s):  
Decision Making ◽  
Human Subjects ◽  
Behavioral Study ◽  
Perceptual Decision Making ◽  
Action Execution ◽  
Perceptual Decision ◽  
Context Dependent ◽  
Unique Context

Recent hypotheses propose that choices and movements share optimization principles derived from economy, possibly implemented by one unique context-dependent regulation signal determining both processes’ speed. In the present behavioral study conducted on human subjects, we demonstrate that action properties indeed influence perceptual decision-making, but that decision duration and action vigor are actually independently set depending on the difficulty of the movement executed to report a choice.

scholarly journals The Role of Passing Time in Decision-Making

2018 ◽  
Author(s):  
Nathan J. Evans ◽  
Guy Hawkins ◽  
Scott Brown
Keyword(s):  
Decision Making ◽  
Task Design ◽  
Perceptual Decision Making ◽  
Improve Performance ◽  
Decision Speed ◽  
Decision Environments ◽  
Threshold Amount ◽  
And Task ◽  
Response Deadlines

Theories of perceptual decision-making have been dominated by the idea that evidence accumulates in favor of different alternatives until some fixed threshold amount is reached, which triggers a decision. Recent theories have suggested that these thresholds may not be fixed during each decision, but change as time passes. These collapsing thresholds can improve performance in particular decision environments, but reviews of data from typical decision-making paradigms have failed to support collapsing thresholds. We designed three experiments to test collapsing threshold assumptions in decision environments specifically tailored to make them optimal. An emphasis on decision speed encouraged the adoption of collapsing thresholds – most strongly through the use of response deadlines, but also through instruction to a lesser extent – but setting an explicit goal of reward rate optimality through both instructions and task design did not. Our results provide a new explanation for previous findings regarding decision-making differences between humans and non-human primates.

scholarly journals Performance-optimized hierarchical models only partially predict neural responses during perceptual decision making

2017 ◽  
Author(s):  
Laura Gwilliams ◽  
Jean-Rémi King
Keyword(s):  
Decision Making ◽  
Human Subjects ◽  
Brain Activity ◽  
Hand Movement ◽  
Temporal Organization ◽  
Natural Image ◽  
Neural Responses ◽  
Perceptual Decision Making ◽  
Healthy Human ◽  
Perceptual Decision

AbstractModels of perceptual decision making have historically been designed to maximally explain behaviour and brain activity independently of their ability to actually perform tasks. More recently, performance-optimized models have been shown to correlate with brain responses to images and thus present a complementary approach to understand perceptual processes. In the present study, we compare how these approaches comparatively account for the spatio-temporal organization of neural responses elicited by ambiguous visual stimuli. Forty-six healthy human subjects performed perceptual decisions on briefly flashed stimuli constructed from ambiguous characters. The stimuli were designed to have 7 orthogonal properties, ranging from low-sensory levels (e.g. spatial location of the stimulus) to conceptual (whether stimulus is a letter or a digit) and task levels (i.e. required hand movement). Magneto-encephalography source and decoding analyses revealed that these 7 levels of representations are sequentially encoded by the cortical hierarchy, and actively maintained until the subject responds. This hierarchy appeared poorly correlated to normative, drift-diffusion, and 5-layer convolutional neural networks (CNN) optimized to accurately categorize alpha-numeric characters, but partially matched the sequence of activations of 3/6 state-of-the-art CNNs trained for natural image labeling (VGG-16, VGG-19, MobileNet). Additionally, we identify several systematic discrepancies between these CNNs and brain activity, revealing the importance of single-trial learning and recurrent processing. Overall, our results strengthen the notion that performance-optimized algorithms can converge towards the computational solution implemented by the human visual system, and open possible avenues to improve artificial perceptual decision making.

scholarly journals Dissociating the Impact of Movement Time and Energy Costs on Decision-Making and Action Initiation in Humans

2021 ◽  
Vol 15 ◽  
Author(s):  
Clara Saleri Lunazzi ◽  
Amélie J. Reynaud ◽  
David Thura
Keyword(s):  
Decision Making ◽  
Energy Expenditure ◽  
Decision Task ◽  
Perceptual Decision Making ◽  
Movement Initiation ◽  
Time Condition ◽  
Perceptual Decision ◽  
Trade Offs ◽  
The Impact ◽  
Action Initiation

Recent theories and data suggest that adapted behavior involves economic computations during which multiple trade-offs between reward value, accuracy requirement, energy expenditure, and elapsing time are solved so as to obtain rewards as soon as possible while spending the least possible amount of energy. However, the relative impact of movement energy and duration costs on perceptual decision-making and movement initiation is poorly understood. Here, we tested 31 healthy subjects on a perceptual decision-making task in which they executed reaching movements to report probabilistic choices. In distinct blocks of trials, the reaching duration (“Time” condition) and energy (“Effort” condition) costs were independently varied compared to a “Reference” block, while decision difficulty was maintained similar at the block level. Participants also performed a simple delayed-reaching (DR) task aimed at estimating movement initiation duration in each motor condition. Results in that DR task show that long duration movements extended reaction times (RTs) in most subjects, whereas energy-consuming movements led to mixed effects on RTs. In the decision task, about half of the subjects decreased their decision durations (DDs) in the Time condition, while the impact of energy on DDs were again mixed across subjects. Decision accuracy was overall similar across motor conditions. These results indicate that movement duration and, to a lesser extent, energy expenditure, idiosyncratically affect perceptual decision-making and action initiation. We propose that subjects who shortened their choices in the time-consuming condition of the decision task did so to limit a drop of reward rate.

scholarly journals Large-scale network dynamics of beta-band oscillations underlie auditory perceptual decision-making

2017 ◽  
Vol 1 (2) ◽  
pp. 166-191 ◽  
Author(s):  
Mohsen Alavash ◽  
Christoph Daube ◽  
Malte Wöstmann ◽  
Alex Brandmeyer ◽  
Jonas Obleser
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Network Dynamics ◽  
Neural Oscillations ◽  
Perceptual Decision Making ◽  
Beta Band ◽  
Perceptual Decision ◽  
Large Scale Network ◽  
Scale Network ◽  
Decision Speed

Perceptual decisions vary in the speed at which we make them. Evidence suggests that translating sensory information into perceptual decisions relies on distributed interacting neural populations, with decision speed hinging on power modulations of the neural oscillations. Yet the dependence of perceptual decisions on the large-scale network organization of coupled neural oscillations has remained elusive. We measured magnetoencephalographic signals in human listeners who judged acoustic stimuli composed of carefully titrated clouds of tone sweeps. These stimuli were used in two task contexts, in which the participants judged the overall pitch or direction of the tone sweeps. We traced the large-scale network dynamics of the source-projected neural oscillations on a trial-by-trial basis using power-envelope correlations and graph-theoretical network discovery. In both tasks, faster decisions were predicted by higher segregation and lower integration of coupled beta-band (∼16–28 Hz) oscillations. We also uncovered the brain network states that promoted faster decisions in either lower-order auditory or higher-order control brain areas. Specifically, decision speed in judging the tone sweep direction critically relied on the nodal network configurations of anterior temporal, cingulate, and middle frontal cortices. Our findings suggest that global network communication during perceptual decision-making is implemented in the human brain by large-scale couplings between beta-band neural oscillations.

scholarly journals A perceptual decision making EEG/fMRI data set

2018 ◽  
Author(s):  
Yasmin K. Georgie ◽  
Camillo Porcaro ◽  
Stephen D. Mayhew ◽  
Andrew P. Bagshaw ◽  
Dirk Ostwald
Keyword(s):  
Decision Making ◽  
Human Subjects ◽  
Open Science ◽  
Fmri Data ◽  
Imaging Data ◽  
Perceptual Decision Making ◽  
Data Set ◽  
Perceptual Decision ◽  
Neuroimaging Data ◽  
Science Framework

AbstractWe present a neuroimaging data set comprising behavioural, electroencephalographic (EEG), and functional magnetic resonance imaging (fMRI) data that were acquired from human subjects performing a perceptual decision making task. EEG data were acquired both independently and simultaneously with fMRI data. Potential data usages include the validation of biocomputational accounts of human perceptual decision making or the empirical validation of simultaneous EEG/fMRI data processing algorithms. The dataset is available from the Open Science Framework and organized according to the Brain Imaging Data Structure standard.

scholarly journals Influence of expected reward on perceptual decision making

2018 ◽  
Author(s):  
Mohsen Rakhshan ◽  
Vivian Lee ◽  
Emily Chu ◽  
Lauren Harris ◽  
Lillian Laiks ◽  
...  
Keyword(s):  
Decision Making ◽  
Sensory Processing ◽  
Human Subjects ◽  
Target Selection ◽  
Judgment Task ◽  
Neural Mechanisms ◽  
Perceptual Bias ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Reward Effects

AbstractPerceptual decision making is influenced by reward expected from alternative options or actions, but the underlying neural mechanisms are currently unknown. More specifically, it is debated whether reward effects are mediated through changes in sensory processing and/or later stages of decision making. To address this question, we conducted two experiments in which human subjects made saccades to what they perceived to be the first or second of two visually identical but asynchronously presented targets, while we manipulated expected reward from correct and incorrect responses on each trial. We found that unequal reward caused similar shifts in target selection (reward bias) between the two experiments. Moreover, observed reward biases were independent of the individual’s sensitivity to sensory signals. These findings suggest that the observed reward effects were determined heuristically via modulation of decision-making processes instead of sensory processing and thus, are more compatible with response bias rather than perceptual bias. To further explain our findings and uncover plausible neural mechanisms, we simulated our experiments with a cortical network model and tested alternative mechanisms for how reward could exert its influence. We found that our observations are more compatible with reward-dependent input to the output layer of the decision circuit. Together, our results suggest that during a temporal judgment task, the influence of reward information on perceptual choice is more compatible with changing later stages of decision making rather than early sensory processing.

scholarly journals Age-related deficits in rapid visuomotor decision-making

2021 ◽  
Author(s):  
Ana Gómez-Granados ◽  
Deborah A Barany ◽  
Margaret Schrayer ◽  
Isaac L. Kurtzer ◽  
Cédrick T Bonnet ◽  
...  
Keyword(s):  
Older Adults ◽  
Decision Making ◽  
Sensory Information ◽  
Dorsal Stream ◽  
Task Demands ◽  
Decision Task ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Age Related ◽  
Induced Changes

Many goal-directed actions that require rapid visuomotor planning and perceptual decision-making are affected in older adults, causing difficulties in execution of many functional activities of daily living. Visuomotor planning and perceptual decision-making are mediated by the dorsal and ventral visual streams, respectively, but it is unclear how age-induced changes in sensory processing in these streams contribute to declines in goal-directed actions. Previously, we have shown that in healthy adults, task demands influence movement strategies during visuomotor decision-making, reflecting differential integration of sensory information between the two streams. Here, we asked the question if older adults would exhibit larger declines in interactions between the two streams during demanding motor tasks. Older adults (n=15) and young controls (n=26) performed reaching or interception movements towards virtual objects. In some blocks of trials, participants also had to select an appropriate movement goal based on the shape of the object. Our results showed that older adults corrected fewer initial decision errors during both reaching and interception movements. During the interception decision task, older adults made more decision- and execution-related errors than young adults, which were related to early initiation of their movements. Together, these results suggest that older adults have a reduced ability to integrate new perceptual information to guide online action, which may reflect impaired ventral-dorsal stream interactions.

Sign in / Sign up

Export Citation Format

Share Document