Biology subjects

Cisek, P.

Publications and source records attributed to Cisek, P..

13 recordsLinked to original sources

bioRxiv2024

Planning-while-acting: addressing the continuous dynamics of planning and action in a sequential embodied task

Everyday tasks, such as selecting routes when driving or preparing meals, require making sequences of embodied decisions, in which planning and action processes are intertwined. In this study, we address how people make sequential embodied decisions, requiring balancing be-tween immediate affordances and long-term utilities of alternative action plans. We designed a novel virtually embodied task in which participants controlled an avatar tasked with "crossing rivers" by jumping across rocks. The task permitted us to assess how participants balanced between immediate jumping affordances ("safe" versus "risky" jumps) and the utility (length) of the ensuing paths to the goal. Behavioral and computational analyses revealed that partici-pants planned ahead their path to the goal rather than simply focusing on the most immediate jumping affordances. Furthermore, spatial and embodied components of the task influenced participants decision strategies, as participants current direction of movement and momen-tum influenced their choice between safe and risky jumps. Additionally, participants showed (pre)planning before making the first jump, but they continued deliberating during it, with movement speed decreasing at decision points and when approaching them. Computational modeling indicates that farsighted participants who assigned greater weight to the utility of future jumps showed a better performance, highlighting the usefulness of planning in embodied settings. Finally, analysing participants performance across trials indicates that during the experiment, they become faster in moving and deciding but they do not change their overall strategy. Our findings underscore the importance of studying decision-making and planning in ecologically valid, embodied settings, providing new insights into the interplay between action and cognition in real-world planning-while-acting scenarios. Significance statementEveryday activities, such as navigating a crowded street or assembling objects, often involve contin-uous interactions between planning and action. Yet, it is unclear how people balance opportunities for action (affordances) with long-term planning in embodied settings. In a novel virtually embod-ied task, in which people have to "cross rivers" by making a series of jumps across rocks, we found that they plan ahead their path to the goal rather than simply focusing on the immediate jumping affordances - and they continue deliberating during movement. Crucially, spatial and embodied constraints, such as movement direction and momentum, influenced decision-making, challenging traditional models that treat decision and action as distinct stages and highlighting the importance of studying decisions in ecologically valid, embodied settings.

animal behavior and cognition↗

bioRxiv2024

Biomechanical Costs Influence Decisions Made During Ongoing Actions

Accurate interaction with the environment relies on the integration of external information about the spatial layout of potential actions and knowledge of their costs and benefits. Previous studies have shown that when given a choice between voluntary reaching movements, humans tend to prefer actions with lower biomechanical costs. However, these studies primarily focused on decisions made before the onset of movement ("decide-then-act" scenarios), and it is not known to what extent their conclusions generalize to many real-life situations, in which decisions occur during ongoing actions ("decide-while-acting"). For example, one recent study found that biomechanical costs did not influence decisions to switch from a continuous manual tracking movement to a point-to-point movement, suggesting that biomechanical costs may be disregarded in decide-while-acting scenarios. To better understand this surprising result, we designed an experiment in which participants were faced with the decision between continuing to track a target moving along a straight path or changing paths to track a new target that gradually moved along a direction that deviated from the initial one. We manipulated tracking direction, angular deviation rate, and side of deviation, allowing us to compare scenarios where biomechanical costs favored either continuing or changing the path. Crucially, here the choice was always between two continuous tracking actions. Our results show that in this situation, decisions clearly took biomechanical costs into account. Thus, we conclude that biomechanics are not disregarded during decide-while-acting scenarios, but rather, that cost comparisons can only be made between similar types of actions. NEW & NOTEWORTHYIn this study, we aim to shed light on how biomechanical factors influence decisions made during ongoing actions. Previous work suggested that decisions made during actions disregard biomechanical costs, in contrast to decisions made prior to movement. Our results challenge that proposal and suggest instead that the effect of biomechanical factors is dependent on the types of actions being compared (e.g., continuous tracking vs. point-to-point reaching). These findings contribute to our understanding of the dynamic interplay between biomechanical considerations and action choices during ongoing interactions with the environment.

neuroscience↗

bioRxiv2023

Preference shifts during multi-attribute decision-making

When choosing between options with multiple attributes, do we decide by integrating all of the attributes into a unified measure for comparison, or does the comparison occur at the level of each attribute, involving independent competitive processes that can dynamically influence each other? What happens when independent sensory features all carry information about the same decision factor, such as reward value? To investigate these questions, we asked human participants to perform a two-alternative forced choice task in which the reward value of a target was indicated by two independent visual attributes - its brightness ("bottom-up" feature) and its orientation ("top-down" feature). If decisions always occur after integration of both features, there should be no difference in the reaction time (RT) distribution regardless of the attribute combinations that drove the choice. Counter to that prediction, almost two-thirds of the participants exhibited RT differences that depended on the attribute combinations of given targets. The RT was shortest when both attributes were congruent or when the choice was based on the bottom-up feature, and longer when the attributes were in conflict (favoring opposite options), especially when choosing the option favored by the top-down feature. We also observed mid-reach changes-of-mind in a subset of conflict trials, mostly changing from the bottom-up to the top-down-favored target. These data suggest that multi-attribute value-based decisions are better explained by a distributed competition among different features than by a competition based on a single, integrated estimate of choice value. New & NoteworthyThis study showed that during value-based decisions, humans do not always take all information about reward value into account to make their choice, but instead can "jump the gun" using partial information. In particular, when different sources of information were in conflict, early decisions were mostly based on fast bottom-up information, and sometimes followed by corrective changes-of-mind based on slower top-down information. Our results suggest that parallel decision processes occur among different information sources, as opposed to between a single integrated "common currency".

neuroscience↗

bioRxiv2022

Distinct trajectories in low-dimensional neural oscillation state space track dynamic decision-making in humans

The brain evolved to govern behavior in a dynamic world, in which pertinent information about choices is often in flux. Thus, the commitment to an action choice must reflect a balance between monitoring that information and the necessity to act before opportunities are lost. Here, we investigate the mechanisms of dynamic decision-making in humans using low dimensional space representation of brain wide magnetoencephalography recordings. We show that the principal components (PCs) of alpha (9-13 Hz) and beta power (16-24 Hz) are involved in tracking sensory information evolving over time in the sensorimotor and visual cortex. We also found that alpha PCs reflect the commitment to a particular choice, while beta PCs reflect motor execution. Finally, higher frequency components in subcortical areas reflect the adjustment of speed- accuracy tradeoff policies. These results provide a new detailed characterization of the distributed oscillatory brain processes underlying dynamic decision-making in humans.

neuroscience↗

bioRxiv2021

Overlapping influences shape motor activity during hasty sensorimotor decisions

Humans and other animals are able to adjust their speed-accuracy tradeoff (SAT) at will depending on the urge to act, favoring either cautious or hasty decision policies in different contexts. An emerging view is that SAT regulation relies on influences exerting broad changes on the motor system, tuning its activity up globally when hastiness is at premium. The present study aimed to test this hypothesis. Fifty subjects performed a task involving choices between left and right index fingers, in which incorrect choices led either to a high or to a low penalty in two contexts, inciting them to emphasize either cautious or hasty policies. We applied transcranial magnetic stimulation on multiple motor representations, eliciting motor evoked potentials (MEP) in nine finger and leg muscles. MEP amplitudes allowed us to probe activity changes in the corresponding finger and leg representations, while subjects were deliberating about which index to choose. Our data indicate that hastiness entails a broad amplification of motor activity, though this amplification was limited to the chosen side. On top of this effect, we identified a local suppression of motor activity, surrounding the chosen index representation. Hence, a decision policy favoring speed over accuracy appears to rely on overlapping processes producing a broad (but not global) amplification and a surround suppression of motor activity. The latter effect may help to increase the signal-to-noise ratio of the chosen representation, as supported by single-trial correlation analyses indicating a stronger differentiation of activity changes in finger representations in the hasty context.

neuroscience↗

bioRxiv2021

Deliberation gated by opportunity cost adapts to context with urgency

Finding the right amount of deliberation, between insufficient and excessive, is a hard decision making problem that depends on the value we place on our time. Average-reward, putatively encoded by tonic dopamine, serves in existing reinforcement learning theory as the stationary opportunity cost of time, and of deliberation in particular. However, this cost often varies with environmental context that can change over time. Here, we introduce an opportunity cost of deliberation estimated adaptively on multiple timescales to account for non-stationary contextual factors. We use it in a simple decision-making heuristic based on average-reward reinforcement learning (AR-RL) that we call Performance-Gated Deliberation (PGD). We propose PGD as a strategy used by animals wherein deliberation cost is implemented directly as urgency, a previously characterized neural signal effectively controlling the speed of the decision-making process. We show PGD outperforms AR-RL solutions in explaining behaviour and urgency of non-human primates in a context-varying random walk prediction task and is consistent with relative performance and urgency in a context-varying random dot motion task. We make readily testable predictions for both neural activity and behaviour and call for an integrated research program in cognitive and systems neuroscience around the value of time.

neuroscience↗

bioRxiv2021

Changes of mind after movement onset: a motor-state dependent decision-making process

Decision-making is traditionally described as a cognitive process of deliberation followed by commitment to an action choice, preceding the planning and execution of the chosen action. However, this is challenged by recent data suggesting that multiple options are specified simultaneously and compete in pre-motor cortical areas for selection and execution. Previous studies focused on the competition during planning, and leave unaddressed the dynamics of decisions during movement. Does deliberation extend into the execution phase? Are non-selected options still considered? Here we studied a decision-making task in which human participants were instructed to select a reaching path trajectory from an origin to a rectangular target, where reward was distributed non-uniformly at the target. Critically, we applied mechanical perturbations to the arm during movement to study under which conditions such perturbations produce changes of mind. Our results show that participants initially selected the direction of movement towards the highest reward region, and changed their mind most frequently when the two choices offered the same reward, showing that deliberation continues and follows cost-benefit considerations during movement. Furthermore, changes of mind were dependent upon the intensity of the perturbation and the current state of the motor system, including velocity and distance to targets. Although reward remains most relevant, our results indicate that the state of the motor system when the perturbation occurs is a crucial determinant of changes of mind. This indicates that the neural circuits that assess reward and those that control movements operate synergistically rather than sequentially during decision-making. Significance StatementOur study provides supporting evidence for the notion that deliberation during decision-making continues after movement onset because unselected potential actions are not completely suppressed or discarded. From a neurophysiological perspective, our findings suggest that the competition between actions is not over before action initiation, possibly because the initially unselected neuronal population retains some sub-threshold activation, which enables them to take control afterwards. Furthermore, our findings also suggest that decision-makers have a variable degree of commitment to their initial choice, which depends on the relative reward of the offers and on the state of the motor system. The commitment is stronger if the initially selected plan leads to higher rewards, and changes of mind occur more frequently if the velocity and relative position of the end-point are within specific ranges.

neuroscience↗

bioRxiv2020

Shared population-level dynamics in monkey premotor cortex during solo action, joint action and action observation

Studies of neural population dynamics of cell activity from monkey motor areas during reaching show that it mostly represents the generation and timing of motor behavior. We compared neural dynamics in dorsal premotor cortex (PMd) during the performance of a visuomotor task executed individually or cooperatively and during an observation task. In the visuomotor conditions, monkeys applied isometric forces on a joystick to guide a visual cursor in different directions, either alone or jointly with a conspecific. In the observation condition, they observed the cursors motion guided by the partner. We found that in PMd neural dynamics were widely shared across action execution and observation, with cursor motion directions more accurately discriminated than task types. This suggests that PMd encodes spatial aspects irrespective of specific behavioral demands. Furthermore, our results suggest that largest components of premotor population dynamics, which have previously been suggested to reflect a transformation from planning to movement execution, may rather reflect higher cognitive-motor processes, such as the covert representation of actions and goals shared across tasks that require movement and those that do not. HIGHLIGHTSO_LIIn PMd neural dynamics is shared across action execution and mere observation C_LIO_LITask directional features are more accurately discriminated than action types C_LIO_LISpatial aspects are encoded in PMd independently from specific behavioral demands C_LIO_LIPMd dynamics largely reflect higher cognitive-motor processes rather than strictly motor-related functions C_LI

neuroscience↗

bioRxiv2020

Unified neural dynamics of decisions and actions in the cerebral cortex and basal ganglia

Several theoretical models suggest that deciding about actions and executing them are not completely distinct neural mechanisms but instead two modes of an integrated dynamical system. Here, we investigate this proposal by examining how neural activity unfolds during a dynamic decision-making task within the high-dimensional space defined by the activity of cells in monkey dorsal premotor (PMd), primary motor (M1), and dorsolateral prefrontal cortex (dlPFC) as well as the external and internal segments of the globus pallidus (GPe, GPi). Dimensionality reduction shows that the four strongest components of neural activity are functionally interpretable, reflecting a state transition between deliberation and commitment, the transformation of sensory evidence into a choice, and the baseline and slope of the rising urgency to decide. Analysis of the contribution of each population to these components shows differences between regions but no distinct clusters within each region. During deliberation, cortical activity unfolds on a two-dimensional "decision manifold" defined by sensory evidence and urgency, and falls off this manifold at the moment of commitment into a choice-dependent trajectory leading to movement initiation. The structure of the manifold varies between regions: In PMd it is curved, in M1 it is nearly perfectly flat, and in dlPFC it is almost entirely confined to the sensory evidence dimension. In contrast, pallidal activity during deliberation is primarily defined by urgency. We suggest that these findings reveal the distinct dynamics of different regions, supporting a unified recurrent attractor model of action selection and execution.

neuroscience↗

bioRxiv2020

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

A 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.

neuroscience↗

bioRxiv2020

Dynamic changes in urgency over the course of a decision

Humans and other animals often need to balance the desire to gather sensory information (to make the best choice) with the urgency to act, facing a speed-accuracy tradeoff (SAT). Given the ubiquity of SAT across species, extensive research has been devoted to understanding the computational mechanisms allowing its regulation at different timescales, including from one context to another, and from one decision to another. However, animals must frequently change their SAT on even shorter timescales - i.e., over the course of an ongoing decision - and little is known about the mechanisms that allow such rapid adaptations. The present study aimed at addressing this issue. Human subjects performed a decision task with changing evidence. In this task, subjects received rewards for correct answers but incurred penalties for mistakes. An increase or a decrease in penalty occurring halfway through the trial promoted rapid SAT shifts, favoring speeded decisions either in the early or in the late stage of the trial. Importantly, these shifts were associated with stage-specific adjustments in the accuracy criterion exploited for committing to a choice. Those subjects who decreased the most their accuracy criterion at a given decision stage exhibited the highest gain in speed, but also the highest cost in terms of performance accuracy at that time. Altogether, the current findings offer a unique extension of previous work, by suggesting that dynamic changes in accuracy criterion allow the regulation of the SAT within the timescale of a single decision. New and noteworthyExtensive research has been devoted to understanding the mechanisms allowing the regulation of the speed-accuracy tradeoff (SAT) from one context to another and from one decision to another. Here, we show that humans can voluntarily change their SAT on even shorter timescales - i.e., over the course of a decision. These rapid SAT shifts are associated with dynamic adjustments in the accuracy criterion exploited for committing to a choice.

animal behavior and cognition↗

bioRxiv2019

Neural correlates of evidence and urgency during human perceptual decision-making in dynamically changing conditions

Current models of decision-making assume that the brain gradually accumulates evidence and drifts towards a threshold which, 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 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.

neuroscience↗

bioRxiv2018

M1 disruption delays motor processes but not deliberation about action choices

Decisions about actions typically involve a period of deliberation that ends with the commitment to a choice and the motor processes overtly expressing that choice. Previous studies have shown that neural activity in sensorimotor areas, including the primary motor cortex (M1), correlates with deliberation features during action selection. Yet, the causal contribution of these areas to the decision process remains unclear. Here, we investigated whether M1 determines choice commitment, or whether it simply reflects decision signals coming from upstream structures and instead mainly contributes to the motor processes that follow commitment. To do so, we tested the impact of a disruption of M1 activity, induced by continuous theta burst stimulation (cTBS), on the behavior of human subjects in (1) a simple reaction time (SRT) task allowing us to estimate the duration of the motor processes and (2) a modified version of the tokens task (Cisek et al., 2009), which allowed us to estimate subjects time of commitment as well as accuracy criterion. The efficiency of cTBS was attested by a reduction in motor evoked potential amplitudes following M1 disruption, as compared to those following a sham stimulation. Furthermore, M1 cTBS lengthened SRTs, indicating that motor processes were perturbed by the intervention. Importantly, all of the behavioral results in the tokens task were similar following M1 disruption and sham stimulation, suggesting that the contribution of M1 to the deliberation process is potentially negligible. Taken together, these findings favor the view that M1 contribution is downstream of the decision process.\n\nNew and noteworthyDecisions between actions are ubiquitous in the animal realm. Deliberation during action choices entails changes in the activity of the sensorimotor areas controlling those actions, but the causal role of these areas is still often debated. Using continuous theta burst stimulation, we show that disrupting the primary motor cortex (M1) delays the motor processes that follow instructed commitment but does not alter volitional deliberation, suggesting that M1 contribution may be downstream of the decision process.

neuroscience↗