Find research datasets worth reusing

Data from: Aggressive jumping spiders make quicker decisions for preferred prey but not at the cost of accuracy

There has been an increasing interest in consistent interindividual differences in behavior (i.e., personality) in recent years. However, consistent interindividual differences in cognitive styles remain largely unexplored. Individual differences in cognitive styles are hypothesized to be functionally related to differences in personality types. It is assumed that proactive individuals make faster decisions at the expense of accuracy (i.e., the speed–accuracy trade-offs hypothesis). Here, we investigated the relationship between personality and speed–accuracy trade-off using Portia labiata, a specialized spider-eating jumping spider that exhibits excellent cognitive ability. We first established consistent individual differences in aggressiveness and decision-making in P. labiata. We then tested whether individual differences in aggressiveness could predict how fast and accurately P. labiata makes a prey-choice decision (a large vs. a small orb-web spider). We demonstrated that P. labiata exhibited individual differences not only in aggressiveness, but also in the speed of prey-choice decisions but not in the choices. Importantly, we found that aggressiveness was not related to the choice of the prey, but it predicted the speed of prey-choice decision: aggressive individuals were faster to make choices than docile ones but both chose large spiders as preferred prey. This suggests a lack of an association between a speed–accuracy trade-off and variation in personality types of P. labiata.

opencc-zeroNov 2019View details →

Data from: One-shot learning and behavioral eligibility traces in sequential decision making

In many daily tasks we make multiple decisions before reaching a goal. In order to learn such sequences of decisions, a mechanism to link earlier actions to later reward is necessary. Reinforcement learning theory suggests two classes of algorithms solving this credit assignment problem: In classic temporal-difference learning, earlier actions receive reward information only after multiple repetitions of the task, whereas models with eligibility traces reinforce entire sequences of actions from a single experience (one-shot). Here we show one-shot learning of sequences. We developed a novel paradigm to directly observe which actions and states along a multi-step sequence are reinforced after a single reward. By focusing our analysis on those states for which RL with and without eligibility trace make qualitatively distinct predictions, we find direct behavioral (choice probability) and physiological (pupil dilation) signatures of reinforcement learning with eligibility trace across multiple sensory modalities.

Data from: Multi-alternative decision making with non-stationary inputs

One of the most widely implemented models for multi-alternative decision-making is the multihypothesis sequential probability ratio test (MSPRT). It is asymptotically optimal, straightforward to implement, and has found application in modelling biological decision-making. However, the MSPRT is limited in application to discrete ('trial-based'), non-time-varying scenarios. By contrast, real world situations will be continuous and entail stimulus non-stationarity. In these circumstances, decision-making mechanisms (like the MSPRT) which work by accumulating evidence, must be able to discard outdated evidence which becomes progressively irrelevant. To address this issue, we introduce a new decision mechanism by augmenting the MSPRT with a rectangular integration window and a transparent decision boundary. This allows selection and de-selection of options as their evidence changes dynamically. Performance was enhanced by adapting the window size to problem difficulty. Further, we present an alternative windowing method which exponentially decays evidence and does not significantly degrade performance, while greatly reducing the memory resources necessary. The methods presented have proven successful at allowing for the MSPRT algorithm to function in a non-stationary environment.

Data from: Using sounds for making decisions: greater tube-nosed bats prefer antagonistic calls over non-communicative sounds when feeding

Bats vocalize extensively within different social contexts. The type and extent of information conveyed via their vocalizations and their perceptual significance, however, remains controversial and difficult to assess. Greater tube-nosed bats, Murina leucogaster, emit calls consisting of long rectangular broadband noise burst (rBNBl) syllables during aggression between males. To experimentally test the behavioral impact of these sounds for feeding, we deployed an approach and place-preference paradigm. Two food trays were placed on opposite sides and within different acoustic microenvironments, created by sound playback, within a specially constructed tent. Specifically, we tested whether the presence of rBNBl sounds at a food source effectively deters the approach of male bats in comparison to echolocation sounds and white noise. In each case, contrary to our expectation, males preferred to feed at a location where rBNBl sounds were present. We propose that the species-specific rBNBl provides contextual information, not present within non-communicative sounds, to facilitate approach towards a food source.

opencc-zeroApr 2020View details →

Data from: State-dependent decision-making by predators and its consequences for mimicry

The mimicry of one species by another provides one of the most celebrated examples of evolution by natural selection. Edible Batesian mimics deceive predators into believing they may be defended, whereas defended Müllerian mimics have evolved a shared warning signal, more rapidly educating predators to avoid them. However, it may benefit hungry predators to attack defended prey, while the benefits of learning about unfamiliar prey depends on the future value of this information. Previous energetic state-dependent models of predator foraging behaviour have assumed complete knowledge, while informational state-dependent models have assumed fixed levels of hunger. Here, we identify the optimal decision rules of predators accounting for both energetic and informational states. We show that the nature of mimicry is qualitatively and quantitatively affected by both sources of state dependence. Associative learning weakens the extent of parasitic mimicry by edible prey because naive predators often attack defended models. More importantly, mimicry among equally highly defended prey may be parasitic or mutualistic depending on the ecological context. Finally, mimicry by prey with intermediate defences corresponds to Batesian or Müllerian mimicry depending on whether the mimic is profitable to attack by hungry predators, but it is not a special case of mimicry.

opencc-zeroDec 2013View details →

Data from: Shared decision-making as a cost-containment strategy: US physician reactions from a cross-sectional survey

Objective: To assess US physicians' attitudes towards using shared decision-making (SDM) to achieve cost containment. Design: Cross-sectional mailed survey. Setting: US medical practice. Participants: 3897 physicians were randomly selected from the AMA Physician Masterfile. Of these, 2556 completed the survey. Main outcome measures: Level of enthusiasm for "Promoting better conversations with patients as a means of lowering healthcare costs"; degree of agreement with "Decision support tools that show costs would be helpful in my practice" and agreement with "should promoting SDM be legislated to control overall healthcare costs". Results: Of 2556 respondents (response rate (RR) 65%), two-thirds (67%) were 'very enthusiastic' about promoting SDM as a means of reducing healthcare costs. Most (70%) agreed decision support tools that show costs would be helpful in their practice, but only 24% agreed with legislating SDM to control costs. Compared with physicians with billing-only compensation, respondents with salary compensation were more likely to strongly agree that decision support tools showing costs would be helpful (OR 1.4; 95% CI 1.1 to 1.7). Primary care physicians (vs surgeons, OR 1.4; 95% CI 1.0 to 1.6) expressed more enthusiasm for SDM being legislated as a means to address healthcare costs. Conclusions: Most US physicians express enthusiasm about using SDM to help contain costs. They believe decision support tools that show costs would be useful. Few agree that SDM should be legislated as a means to control healthcare costs.

Data from: Soaring across continents: decision-making of a soaring migrant under changing atmospheric conditions along an entire flyway

(1) Thermal soaring birds reduce flight-energy costs by alternatingly gaining altitude in thermals and gliding across the earth's surface. To find out how soaring migrants adjust their flight behaviour to dynamic atmospheric conditions across entire migration routes, we combined optimal soaring migration theory with high-resolution GPS tracking data of migrating Honey Buzzards Pernis apivorus and wind data from a global numerical atmospheric model. (2) We compared measurements of gliding air speeds to predictions based on two distinct behavioural benchmarks for thermal soaring flight. The first being a time-optimal strategy whereby birds alter their gliding air speeds as a function of climb rates to maximize cross-country air speed over a full climb-glide cycle (Vopt). The second a risk-averse energy-efficient strategy at which birds alter their gliding air speed in response to tailwinds/headwinds to maximize the distance travelled in the intended direction during each glide phase (Vbgw). (3) Honey Buzzards were gliding on average 2.05 ms-1 slower than Vopt and 3.42 ms-1 faster than Vbgw while they increased air speeds with climb rates and reduced air speeds in tailwinds. They adopted flexible flight strategies gliding mostly near Vbgw under poor soaring conditions and closer to Vopt in good soaring conditions. (4) Honey Buzzards most adopted a time-optimal strategy when crossing the Sahara, and at the onset of spring migration, where and when they met with the best soaring conditions. The buzzards nevertheless glided slower than Vopt during most of their journeys, probably taking time to navigate, orientate and locate suitable thermals, especially in areas with poor thermal convection. (5) Linking novel tracking techniques with optimal migration models clarifies the way birds balance different trade-offs during migration.

opencc-by-4.0Mar 2020View details →

Foraging through multiple nest holes: an impediment to collective decision-making in ants

Raw Data: study investigating the impact of nest structure (number of nest entrances)  on the ability of ant colonies to  collectively exploit food resources and to select the most rewarding food source.

opencc-by-4.0Apr 2017View details →

Healthy Aging Is Associated With Decreased Risk-Taking in Motor Decision-Making

The Zip file contains all data relative to the publication. Data files are identified as follows: Part[Y/O for Younger/Older]Sess[Session Number] A description of the variables is contained in the file VARIABLE CODES.txt

opencc-by-4.0Dec 2023View details →

Double dissociation of dopamine and subthalamic nucleus stimulation on effortful cost/benefit decision making

Open the record for dataset details and reuse information.

opencc-by-4.0Feb 2024View details →

Dataset for "Activation of the mPFC-NAc pathway reduces motor impulsivity but does not affect risk-related decision-making in innately high-impulsive male rats"

Attention-deficit/hyperactivity disorder (ADHD) and substance use disorders (SUD) are characterized by exacerbated motor and risk-related impulsivities, which are associated with decreased cortical activity. In rodents, the medial prefrontal cortex (mPFC) and nucleus accumbens (NAc) have been separately implicated in impulsive behaviors, but studies on the specific role of the mPFC-NAc pathway in these behaviors are limited. Here, we investigated whether heightened impulsive behaviors are associated with reduced mPFC activity in rodents, and determined the involvement of the mPFC-NAc pathway in motor and risk-related impulsivities. We used the Roman High- (RHA) and Low-Avoidance (RLA) rat lines, which display divergent phenotypes in impulsivity. To investigate alterations in cortical activity in relation to impulsivity, regional brain glucose metabolism was measured using positron emission tomography and [18F]-fluorodeoxyglucose ([18F]FDG). Using chemogenetics, the activity of the mPFC-NAc pathway was either selectively activated in high-impulsive RHA rats or inhibited in low-impulsive RLA rats, and the effects of these manipulations on motor and risk-related impulsivity were concurrently assessed using the rat gambling task. We showed that basal [18F]FDG uptake was lower in the mPFC and NAc of RHA compared to RLA rats. Activation of the mPFC-NAc pathway in RHA rats reduced motor impulsivity, without affecting risk-related decision-making. Conversely, inhibition of the mPFC-NAc pathway had no effect in RLA rats. Our results suggest that the mPFC-NAc pathway controls motor impulsivity, but has limited involvement in risk-related decision-making. Our findings suggest that reducing fronto-striatal activity may help attenuate motor impulsivity in patients with impulse control dysregulation like ADHD or SUD.

opencc-by-4.0Apr 2024View details →

Replication package: Temperature and decision-making

Michelle Escobar Carias, David Johnston, Rachel Knott, Rohan Sweeney (2024). Replication package: Temperature and decision-making

opencc-by-4.0Dec 2024View details →

Uncertainty in Pedestrian Decision-Making in Urgent Scenarios Modulates Multi-Level Neural Hierarchies from Perception to Execution

In urgent traffic scenarios, pedestrians exhibit decision-making uncertainty, significantly influencing safe interaction dynamics with automated vehicles. However, the inherent mechanisms of such decision behavior remain inadequately understood. To address this gap, we designed dynamic interactive stimulus experiments to replicate pedestrian-vehicle interactions in urgent scenarios, incorporating spatiotemporal pressure and introducing substantial penalties for decision failures. We employed multimodal data analysis, including behavioral data, electroencephalography (EEG) and eye-tracking data, to investigate the influence of urgency on uncertainty in decision-making and the underlying multi-level neural processes. Our findings demonstrate that as the urgency of the stimulus increases, humans adjust their decision objectives, resulting in an initial decrease followed by an increase in decision uncertainty when dealing with more urgent stimuli. Specifically, urgency augments top-down perceptual processes during the early perception stage. Such a mechanism implies an enhanced dependence on prior experiences for perceptual decision-making in high-urgency situations. While urgency accelerated motion preparation time during the decision-execution stage, it is noteworthy that the culmination of evidence accumulation (represented by the CPP peak) manifested later than the actual response. These results suggest that insufficient perceptual information and evidence accumulation may increase decision-making uncertainty. Our experimental study unveils a correlation between human decision-making uncertainty and scenario urgency, particularly within a defined urgency range.

opencc-by-4.0Nov 2024View details →

Additional Material for: Debiasing Architectural Decision-Making: An Experiment With Students and Practitioners

Additional Material for: Debiasing Architectural Decision-Making: An Experiment With Students and Practitioners submitted to ICSA 2025. The files contain: 1. README.md - A short file describing the contents of the replication package. 2. Coding guide.docx - a guide used for coding, with examples from the experiment's participants. 3. Coding_results.xlsx - data with all measurements for all participants. 4. Questionnaire.xlsx - questionnaire used to gather demographic participant's data. 5. Experiment-plan.docx - the detailed plan of all the experiment steps. 6. Debiasing-workshop-slides.pptx - slides used during the debiasing workshop. 7. Debiasing-workshop-plan.docx - a detailed plan of the debiasing workshop, explaining how exactly the debiasing presentation should be used. 8. Consent_form.docx - a consent form that was signed by the participants from one of the author's countries, where guidelines suggested the use of gathering additional written consent.

opencc-zeroMar 2024View details →

Data and models for "An image-computable model of speeded decision-making"

Lost in Migration gameplay data and trained models for: <div>Jaffe, P. I., Gustavo, X. S. R., Schafer, R. J., Bissett, P. G., Poldrack, R. A. An image-computable model of speeded decision-making. eLife 13, RP98351 (2024).</div> <div> </div> This dataset can be used to reproduce all of the results of the manuscript, following the instructions in the code repository for the paper: <a href="https://github.com/pauljaffe/vam">https://github.com/pauljaffe/vam</a>. The dataset includes the following components: gameplay_data.zip: Trial-level gameplay metadata for Lost in Migration. Lost in Migration is a variant of the flanker task offered as a part of the Lumosity cognitive training platform (Lumos Labs, Inc.). The .zip file includes a separate .csv file for each of the 75 Lumosity users (participants) that we trained models on. Each .csv file has one row per trial with the following fields/columns: "anon_id", numerical identifier for the Lumosity user; "nth_play", the nth gameplay of Lost in Migration for this user; "trial", the nth trial for the current gameplay; "xpos", the signed horizontal distance from the center of the target bird to the left edge of the game window (pixels, non-negative); "ypos", the signed vertical distance from the center of the target bird to the bottom edge of the game window (pixels, non-negative); "flanker_direction", (L/R/U/D); "response_direction", (L/R/U/D); "target_direction", (L/R/U/D); "response_time", (ms); "stimulus_layout", numerical code for the layout of the bird flock for the current trial (0: horizontal line, 1: vertical line, 2: cross, 3: <, 4: >, 5: v, 6: ^). vam_models.zip: Parameters for the 75 visual accumulator models (VAMs) analyzed in the manuscript. task_opt_models.zip: Parameters for the 75 task-optimized models analyzed in the manuscript. metadata.csv: Metadata for each Lumosity user that a VAM/task-optimized model was trained on. The .csv file has one row per user with the following fields/columns: "user_id", numerical identifier for the Lumosity user (same as "anon_id" in gameplay_data.zip); "gender", self-reported gender ('m', 'f', or null, indicating no response was given); "binned_age", age bucketed into decade-long bins (20-29, 30-39... 80-89). derivatives.zip: The RTs/choices generated by the trained models, organized into separate folders by model type (vam/task_opt/binned_rt) and user ID.  Also includes a "summary_stats" folder with analysis products of the model activations and outputs. graphics.zip: Image files used to create the visual stimuli from the gameplay metadata. example_model_inputs.zip: The processed visual stimuli and gameplay data used as inputs to train one model (user ID 182). Note we provide instructions to recreate the stimuli and other model inputs for all models in the code repository.

opencc-zeroJan 2022View details →

Beaked whales and state-dependent decision-making: how does body condition affect the trade-off between foraging and predator avoidance?

Body condition is central to how animals balance foraging with predator-avoidance – a trade-off that fundamentally affects animal fitness. Animals in poor condition may accept greater predation risk to satisfy current foraging "needs", whilst those in good condition may be more risk averse to protect future "assets". These state-dependent behavioural predictions can help interpret responses to human activities, but are little explored in marine animals. This study investigates the influence of body condition on how beaked whales trade off foraging and predator-avoidance. Body density (indicating lipid-energy stores) was estimated for 15 foraging northern bottlenose whales tagged near Jan Mayen, Norway. Composite indices of foraging (diving and echolocation clicks) and anti-predation (long ascents, non-foraging dives and silent periods reducing predator eavesdropping) were negatively related. Experimental sonar exposures led to decreased foraging and increased risk aversion, confirming a foraging/perceived safety trade-off. However, lower lipid stores were not related to a decrease in predator-avoidance versus foraging, i.e. worse condition animals did not prioritise foraging. Individual differences ('personalities') or reproductive context could offer alternative explanations for the observed state-behaviour relationships. This study provides evidence of foraging/predator-avoidance trade-offs in a marine top predator and demonstrates that animals in worse condition might not always take more risks.

opencc-zeroJun 2022View details →

Information integration for nutritional decision-making in desert locusts

Swarms of the migratory desert locust can extend over several hundred square kilometres, and starvation compels this ancient pest to devour everything in its path. Theory suggests that gregarious behaviour benefits foraging efficiency over a wide range of spatial food distributions. However, despite the importance of identifying the processes by which swarms locate and select feeding sites to predict their progression, the role of social cohesion during foraging remains elusive. We investigated the evidence accumulation and information integration processes that underlie locusts' nutritional decision-making by employing a Bayesian formalism on high-resolution tracking data from foraging locusts. We tested individual gregarious animals and groups of different sizes in a 2-choice behavioural assay in which food patch qualities were either different or similar. We then predicted the decisions of individual locusts based on personally acquired and socially derived evidence by disentangling the relative contributions of each information class. Our study suggests that locusts balance incongruent evidence but reinforce congruent ones, resulting in more confident assessments when evidence aligns. We provide new insights into the interplay between personal experience and social context in locust foraging decisions which constitute a powerful empirical system to study local individual decisions and their consequent collective dynamics.

opencc-by-4.0Jul 2022View details →

Dataset (MATLAB format) from Yang et al (2022) Thalamus-driven functional populations in frontal cortex support decision-making. Nat. Neurosci.

Summary These experiments measure neuronal responses from the left hemisphere of premotor cortex (anterior lateral motor cortex, ALM) of adult mice performing pole location discrimination with a short-term memory. In a subset of the recordings, we inactivate activity of one of the brain regions providing inputs to ALM (ipsilateral S1/S2, contralateral ALM, and ipsilateral ThalALM) in some trials. This dataset contains data from 9626 single units, 73 mice, 347 sessions. The dataset is described as “the primary dataset” in the paper below. The experiments (including experiment methods) are described in the paper. Yang W, Tipparaju SL, Chen G, Li N, (2022). Thalamus-driven functional populations in frontal cortex activity supports decision-making. Nat Neurosci, in press.   The second dataset used in the paper can be downloaded also from Zenodo at <pre><a href="https://doi.org/10.5281/zenodo.6713616">https://doi.org/10.5281/zenodo.6713616</a></pre>   How to cite the data If you publish any work using the data, please cite the Chen et. al., (2021) publication above and also cite the dataset in the following recommended format: Li N (2022); Data and simulations related to: Thalamus-driven functional populations in frontal cortex activity supports decision-making. Yang et al (2022) Nat Neurosci. <a href="http://dx.doi.org/10.5281/zenodo.6846161">http://dx.doi.org/10.5281/zenodo.6846161</a>   How to get started Once downloaded 1) unzip “func” 2) unzip "scripts" 3) Run any scripts "demo_*.m" within "scripts"   A collection of analyses scripts that reproduce figures in " Yang et al (2022)" is included in the folder "\scripts\" demo_compute_activity_modes_independentTrials.m – plot t-SNE embedding and all the response profile clusters; plots PSTHs from an example cluster; plots neurons connected to S1/S2, cALM, ThalALM on the t-SNE. demo_compute_tSNE_embedding.m – t-SNE embedding of neuronal response profiles (based on PSTH shape) demo_compute_activity_modes.m – compute activity modes from neuronal population responses. demo_compute_selectivity_vector_stability.m – analysis of selectivity vectors

opencc-by-4.0Oct 2022View details →

Multimedia mixed reality interactive shared decision-making game in children with moderate to severe atopic dermatitis, a pilot study

Multimedia mixed reality interactive shared decision-making game in children with moderate to severe atopic dermatitis, a pilot study