Dr Guy Hawkins
Senior Lecturer
School of Psychological Sciences
- Email:guy.hawkins@newcastle.edu.au
- Phone:(02) 4985 4493
Hindsight, Prediction and a Final Decision
University of Newcastle Researcher Dr Guy Hawkins chooses to spend his days developing and testing computational and mathematical models of cognitive processes, with a primary focus on the psychology of decision making.
We’ve all made a snap purchase at the end of a day of careful browsing, or watched quiz show contestants panic and suddenly change their answer at the last second. On a wider scale, history is littered with the catastrophic side effects of bad choices, snap decisions and mistakes made on the fly.
Some prefer to leave mistakes in the past and move on. On the contrary, Dr Guy Hawkins argues, the best way to learn to make better choices is by examining the mathematical and mechanical minutiae of the decision making process.
“My belief is that by understanding the psychological processes that influence how people make decisions, and the external factors that may impinge on those decisions, we can facilitate the environment in ways that help people make better decisions.”
In his research, Guy is investigating the decision mechanisms and strategies that people use to select consumer products and service options.
FACILITATING ENVIRONMENTS
So, how does this research inform society in practical terms?
“A simple example is that we know people find it easier to understand counts than probabilities,” Guy explains.
“People make fewer and less extreme reasoning errors when asked to make decisions about information when in the format of ‘8 out of 10 people will develop a symptom’ (counts), rather than ‘80% of people will develop a symptom’ (probabilities).”
“We can then use this knowledge to help people make more informed and less error prone decisions.”
For instance, physicians could describe potential prognoses with counts rather than probabilities, allowing patients to make better informed treatment choices.
A better understanding of decision making processes helps keep workplaces safe and productive too.
“In organisational contexts one can investigate whether an incorrect action or decision was the result of poor consideration of the evidence or insufficient time allocated to the decision,” Guy explains.
“The outcome implies a particular avenue for remediation and behaviour change: training proficiency in evaluating evidence or altering system processes to provide more time to make important decisions.”
And because consumerism is all about decisions, companies whose core business is conveying information about uncertain outcomes, like insurance agencies, can utilise Guy’s research. Not only to develop a better understanding of statistical reasoning and consumer preference, but to improve communications and marketing.
SEARCHING FOR COMMONALITIES
Surely choosing between brands of biscuits and opting for a risky medical treatment are hardly comparable?
Although there are clear surface-level differences between the gravity of these choices, a key challenge in Guy’s research is using computational and neural models to identify commonalities.
Ultimately, he explains, all decisions require the base processes of perception, evaluation and action. From simple detection requiring rapid action through to making choices with only limited or ambiguous input, we use a similar framework to make many small and not so small decisions every day.
“I am most excited about finding so-called ‘domain general’ mechanisms.”
“This means finding psychological processes that are common to how people make decisions in seemingly very different situations, like detecting the colour of a traffic light and evaluating features of a consumer product.”
Another area of focus has been on how people update the care with which they decide relative to the time frame and quality of options available.
“If we don’t come to a decision quite quickly, we tend to become increasingly willing to make decisions on the basis of less evidence – we become less and less cautious as the decision takes longer and longer.”
My research has aimed to discover factors that influence when we use this strategy to make decisions. For example, is it when we’re under time pressure? Or when the decision is likely too difficult?
IMPROVING OUTCOMES
Guy began his research journey completing his PhD in Newcastle. This work earned him a Postdoctoral Research position at UNSW looking at judgement biases exhibited when reasoning with statistical information.
Two years at the University of Amsterdam’s Brain and Cognition Center followed, utilising computational and neural methods to explore the effect of mind wandering on the ability to complete simple tasks.
Returning to Newcastle in 2017, Guy collaborates with fellow mathematical psychology researchers in the Newcastle Cognition Laboratory and cognitive neuroscientists in the Functional Neuroimaging Laboratory. He also works with researchers at universities in Australia, USA, Canada, UK, The Netherlands, and Norway.
For now, he chooses to stay at the University of Newcastle, working with numbers, neuroscience and the process of making big and small decisions. And apparently, we have much still to learn about making better choices.
“We know there are similarities in the underlying decision processes, yet we have limited understanding of their structure, function and activation in different situations,” Guy says.
“Finding those similarities and capitalising on them so as to improve decision outcomes for people is what keeps me excited about this research.”
Hindsight, Prediction and a Final Decision
University of Newcastle Researcher Dr Guy Hawkins chooses to spend his days developing and testing computational and mathematical models of cognitive processes, with a primary focus on the psychology of decision making.We’ve all made a snap purchase at the end…
Career Summary
Biography
In previous research positions, including his ARC DECRA Fellowship, Guy investigated the decision mechanisms and strategies that people use to select consumer products and service options. This research provided insight into how people reason with and utilise information to inform their decisions.
From 2014-2016 Guy was a Postdoctoral Research Associate at the Amsterdam Brain and Cognition Center, University of Amsterdam, The Netherlands. In this role he used computational and neural methods to investigate the effect of mind wandering on the ability to complete simple tasks. Before moving overseas, Guy was a Postdoctoral Research Associate in the School of Psychology at UNSW Sydney. In this role he investigated approaches to mitigate judgement biases that people exhibit when reasoning with statistical information.
Guy earned his PhD in 2013 and his Bachelor of Psychology (Honours 1) in 2008, both at the University of Newcastle. In his position at the University of Newcastle he collaborates with fellow mathematical psychology researchers in the Newcastle Cognition Laboratory (for details, see newcastlecl.org) and cognitive neuroscientists in the Functional Neuroimaging Laboratory. He also works with researchers at universities in Australia, USA, Canada, UK, The Netherlands, and Norway.
Qualifications
- Doctor of Philosophy, University of Newcastle
- Bachelor of Psychology (Honours), University of Newcastle
Keywords
- Cognition
- Cognitive Psychology
- Cognitive Science
- Cognitive neuroscience
- Decision making
- Mathematical psychology
- Quantitative modelling
- Statistics
Fields of Research
Code | Description | Percentage |
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520105 | Psychological methodology, design and analysis | 20 |
520402 | Decision making | 70 |
520406 | Sensory processes, perception and performance | 10 |
Professional Experience
UON Appointment
Title | Organisation / Department |
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Senior Lecturer | University of Newcastle School of Psychology Australia |
Academic appointment
Dates | Title | Organisation / Department |
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1/1/2017 - 31/12/2019 | ARC DECRA Fellow | The University of Newcastle Australia |
4/8/2014 - 6/12/2016 | Postdoctoral Research Associate | University of Amsterdam School of Psychology Netherlands |
24/1/2013 - 30/6/2014 | Postdoctoral Research Associate | UNSW School of Psychology Australia |
Awards
Award
Year | Award |
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2020 |
William K. Estes Early Career Award Society for Mathematical Psychology (United States) |
2018 |
Fellow of the Psychonomic Society Psychonomic Society |
2017 |
Faculty of Science Award for Early Career Research and Innovation Excellence Faculty of Science and IT, University of Newcastle |
2017 |
Australian Research Council Discovery Early Career Researcher Award ARC (Australian Research Council) |
2017 |
Vice-Chancellor's Award for Early Career Research and Innovation Excellence The University of Newcastle |
2013 |
Clifford T. Morgan Best Article Award (Behavior Research Methods) Psychonomic Society |
Research Award
Year | Award |
---|---|
2014 |
Early Career Researcher Visiting Fellowship University of Newcastle |
2012 |
Society for Mathematical Psychology Travel Award Society for Mathematical Psychology (United States) |
2011 |
Outstanding Postgraduate (Research) Achievement Award Faculty of Science and IT, University of Newcastle |
2010 |
Society for Mathematical Psychology Travel Award Society for Mathematical Psychology (United States) |
Publications
For publications that are currently unpublished or in-press, details are shown in italics.
Journal article (55 outputs)
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2024 |
Viet HD, Gunawan D, Minh-Ngoc T, Kohn R, Hawkins GE, Brown SD, 'Efficient Selection Between Hierarchical Cognitive Models: Cross-Validation With Variational Bayes', PSYCHOLOGICAL METHODS, 29 219-241 (2024) [C1]
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2023 |
Karayanidis F, Hawkins GE, Wong ASW, Aziz F, Hunter M, Steyvers M, 'Jointly modeling behavioral and EEG measures of proactive control in task switching.', Psychophysiology, 60 e14241 (2023) [C1]
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2023 |
Hawkins GE, Cooper G, Cavallaro J-P, 'The standard relationship between choice frequency and choice time is violated in multi-attribute preferential choice', Journal of Mathematical Psychology, 115 102775-102775 (2023) [C1]
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2023 |
Larson JS, Hawkins GE, 'Speed-Accuracy Tradeoffs in Decision Making: Perception Shifts and Goal Activation Bias Decision Thresholds', JOURNAL OF EXPERIMENTAL PSYCHOLOGY-LEARNING MEMORY AND COGNITION, 49 1-32 (2023) [C1]
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2023 |
Gronau QF, Bennett MS, Brown SD, Hawkins GE, Eidels A, 'Do choice tasks and rating scales elicit the same judgments?', Journal of Choice Modelling, 49 100437-100437 (2023) [C1]
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2022 |
Hawkins GE, Mittner M, Forstmann BU, Heathcote A, 'Self-reported mind wandering reflects executive control and selective attention', PSYCHONOMIC BULLETIN & REVIEW, 29 2167-2180 (2022) [C1]
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2022 |
Gunawan D, Hawkins GE, Kohn R, Tran M-N, Brown SD, 'Time-evolving psychological processes over repeated decisions.', Psychological review, 129 438-456 (2022) [C1]
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2021 |
Tran M-N, Scharth M, Gunawan D, Kohn R, Brown SD, Hawkins GE, 'Robustly estimating the marginal likelihood for cognitive models via importance sampling', BEHAVIOR RESEARCH METHODS, 53 1148-1165 (2021) [C1]
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2021 |
Greenaway KH, Kalokerinos EK, Hinton S, Hawkins GE, 'Emotion Experience and Expression Goals Shape Emotion Regulation Strategy Choice', EMOTION, 21 1452-1469 (2021) [C1]
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2021 |
Hawkins GE, Heathcote A, 'Racing against the clock: Evidence-based versus time-based decisions.', Psychological Review, 128 222-263 [C1]
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2021 |
Wall L, Gunawan D, Brown SD, Tran MN, Kohn R, Hawkins GE, 'Identifying relationships between cognitive processes across tasks, contexts, and time', Behavior Research Methods, 53 78-95 (2021) [C1] It is commonly assumed that a specific testing occasion (task, design, procedure, etc.) provides insights that generalize beyond that occasion. This assumption is infrequently car... [more] It is commonly assumed that a specific testing occasion (task, design, procedure, etc.) provides insights that generalize beyond that occasion. This assumption is infrequently carefully tested in data. We develop a statistically principled method to directly estimate the correlation between latent components of cognitive processing across tasks, contexts, and time. This method simultaneously estimates individual-participant parameters of a cognitive model at each testing occasion, group-level parameters representing across-participant parameter averages and variances, and across-task correlations. The approach provides a natural way to ¿borrow¿ strength across testing occasions, which can increase the precision of parameter estimates across all testing occasions. Two example applications demonstrate that the method is practical in standard designs. The examples, and a simulation study, also provide evidence about the reliability and validity of parameter estimates from the linear ballistic accumulator model. We conclude by highlighting the potential of the parameter-correlation method to provide an ¿assumption-light¿ tool for estimating the relatedness of cognitive processes across tasks, contexts, and time.
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2020 |
Katsimpokis D, Hawkins GE, van Maanen L, 'Not all Speed-Accuracy Trade-Off Manipulations Have the Same Psychological Effect', Computational Brain & Behavior, 3 252-268 (2020) [C1]
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2020 |
Evans NJ, Hawkins GE, Brown SD, 'The Role of Passing Time in Decision-Making', JOURNAL OF EXPERIMENTAL PSYCHOLOGY-LEARNING MEMORY AND COGNITION, 46 316-326 (2020) [C1]
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2020 |
Gunawan D, Hawkins GE, Tran M-N, Kohn R, Brown SD, 'New estimation approaches for the hierarchical Linear Ballistic Accumulator model', JOURNAL OF MATHEMATICAL PSYCHOLOGY, 96 (2020) [C1]
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2020 |
Boayue NM, Csifcsák G, Aslaksen P, Turi Z, Antal A, Groot J, et al., 'Increasing propensity to mind-wander by transcranial direct current stimulation? A registered report', European Journal of Neuroscience, 51 755-780 (2020) [C1] Transcranial direct current stimulation (tDCS) has been proposed to be able to modulate different cognitive functions. However, recent meta-analyses conclude that its efficacy is ... [more] Transcranial direct current stimulation (tDCS) has been proposed to be able to modulate different cognitive functions. However, recent meta-analyses conclude that its efficacy is still in question. Recently, an increase in subjects¿ propensity to mind-wander has been reported as a consequence of anodal stimulation of the left dorsolateral prefrontal cortex (Axelrod et¿al., Proceedings of the National Academy of Sciences of the United States of America, 112, 2015). In addition, an independent group found a decrease in mind wandering after cathodal stimulation of the same region. These findings seem to indicate that high-level cognitive processes such as mind wandering can reliably be influenced by non-invasive brain stimulation. However, these previous studies used low sample sizes and are as such subject to concerns regarding the replicability of their findings. In this registered report, we implement a high-powered replication of Axelrod et¿al. (2015) finding that mind-wandering propensity can be increased by anodal tDCS. We used Bayesian statistics and a preregistered sequential-sampling design resulting in a total sample size of N¿=¿192 participants collected across three different laboratories. Our findings show support against a stimulation effect on self-reported mind-wandering scores. The effect was small, in the opposite direction as predicted and not reliably different from zero. Using a Bayes Factor specifically designed to test for replication success, we found strong evidence against a successful replication of the original study. Finally, even when combining data from both the original and replication studies, we could not find evidence for an effect of anodal stimulation. Our results underline the importance of designing studies with sufficient power to detect evidence for or against behavioural effects of non-invasive brain stimulation techniques, preferentially using robust Bayesian statistics in preregistered reports.
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2019 |
Dutilh G, Annis J, Brown SD, Cassey P, Evans NJ, Grasman RPPP, et al., 'The Quality of Response Time Data Inference: A Blinded, Collaborative Assessment of the Validity of Cognitive Models', Psychonomic Bulletin and Review, 26 1051-1069 (2019) [C1] Most data analyses rely on models. To complement statistical models, psychologists have developed cognitive models, which translate observed variables into psychologically interes... [more] Most data analyses rely on models. To complement statistical models, psychologists have developed cognitive models, which translate observed variables into psychologically interesting constructs. Response time models, in particular, assume that response time and accuracy are the observed expression of latent variables including 1) ease of processing, 2) response caution, 3) response bias, and 4) non-decision time. Inferences about these psychological factors, hinge upon the validity of the models¿ parameters. Here, we use a blinded, collaborative approach to assess the validity of such model-based inferences. Seventeen teams of researchers analyzed the same 14 data sets. In each of these two-condition data sets, we manipulated properties of participants¿ behavior in a two-alternative forced choice task. The contributing teams were blind to the manipulations, and had to infer what aspect of behavior was changed using their method of choice. The contributors chose to employ a variety of models, estimation methods, and inference procedures. Our results show that, although conclusions were similar across different methods, these "modeler¿s degrees of freedom" did affect their inferences. Interestingly, many of the simpler approaches yielded as robust and accurate inferences as the more complex methods. We recommend that, in general, cognitive models become a typical analysis tool for response time data. In particular, we argue that the simpler models and procedures are sufficient for standard experimental designs. We finish by outlining situations in which more complicated models and methods may be necessary, and discuss potential pitfalls when interpreting the output from response time models.
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2019 |
Chandrasekaran C, Hawkins GE, 'ChaRTr: An R toolbox for modeling choices and response times in decision-making tasks', Journal of Neuroscience Methods, 328 (2019) [C1]
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2019 |
Steyvers M, Hawkins GE, Karayanidis F, Brown SD, 'A large-scale analysis of task switching practice effects across the lifespan', Proceedings of the National Academy of Sciences of the United States of America, 116 17735-17740 (2019) [C1] An important feature of human cognition is the ability to flexibly and efficiently adapt behavior in response to continuously changing contextual demands. We leverage a large-scal... [more] An important feature of human cognition is the ability to flexibly and efficiently adapt behavior in response to continuously changing contextual demands. We leverage a large-scale dataset from Lumosity, an online cognitive-training platform, to investigate how cognitive processes involved in cued switching between tasks are affected by level of task practice across the adult lifespan. We develop a computational account of task switching that specifies the temporal dynamics of activating task-relevant representations and inhibiting task-irrelevant representations and how they vary with extended task practice across a number of age groups. Practice modulates the level of activation of the task-relevant representation and improves the rate at which this information becomes available, but has little effect on the task-irrelevant representation. While longterm practice improves performance across all age groups, it has a greater effect on older adults. Indeed, extensive task practice can make older individuals functionally similar to lesspracticed younger individuals, especially for cognitive measures that focus on the rate at which task-relevant information becomes available.
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2019 |
Evans NJ, Hawkins GE, 'When humans behave like monkeys: Feedback delays and extensive practice increase the efficiency of speeded decisions', Cognition, 184 11-18 (2019) [C1] The study of non-human primates has been foundational in understanding the neural origins of human decision processes, yet the approach rests on the assumption that one can validl... [more] The study of non-human primates has been foundational in understanding the neural origins of human decision processes, yet the approach rests on the assumption that one can validly extrapolate from the animal to the human. In the context of decision making, this requires constancy across species in physiological and cognitive processes. The former cannot be experimentally validated and therefore remains assumed, and recent findings have called into question the latter: non-human primates become increasingly urgent as the time spent making a decision increases, but humans do not; from a normative perspective, monkeys are making closer-to-optimal decisions than humans. Rather than presuming species differences, here we test an alternative hypothesis: previously overlooked differences in methodological procedures from the two research traditions implicitly reinforced fundamentally different decision strategies across the two species. We show that when humans experience decision contexts matched to those experienced by non-human primates ¿ extensive task practice, or time-based penalties ¿ they display increasing levels of urgency as decision time grows longer, in precisely the same manner as non-human primates. Our findings indicate that previously observed differences in decision strategy between humans and non-human primates are eliminated when the decision environment is more closely matched across species, placing a constraint on the interpretation and mapping of neurophysiological results in non-human primates to humans when there are fundamental differences in the task design.
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2019 |
Cooper GJ, Hawkins GE, 'Investigating consumer decision strategies with systems factorial technology', JOURNAL OF MATHEMATICAL PSYCHOLOGY, 92 (2019) [C1]
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2019 |
Turi Z, Csifcsák G, Boayue NM, Aslaksen P, Antal A, Paulus W, et al., 'Blinding is compromised for transcranial direct current stimulation at 1 mA for 20 min in young healthy adults', European Journal of Neuroscience, 50 3261-3268 (2019) [C1] Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation method that is frequently used to study cortical excitability changes and their impact on cognit... [more] Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation method that is frequently used to study cortical excitability changes and their impact on cognitive functions in humans. While most stimulators are capable of operating in double-blind mode, the amount of discomfort experienced during tDCS may break blinding. Therefore, specifically designed sham stimulation protocols are being used. The ¿fade-in, short-stimulation, fade-out¿ (FSF) protocol has been used in hundreds of studies and is commonly believed to be indistinguishable from real stimulation applied at 1 mA for 20¿min. We analysed subjective reports of 192 volunteers, who either received real tDCS (n¿=¿96) or FSF tDCS (n¿=¿96). Participants reported more discomfort for real tDCS and correctly guessed the condition above chance-level. These findings indicate that FSF does not ensure complete blinding and that better active sham protocols are needed.
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2019 |
Hawkins GE, Mittner M, Forstmann BU, Heathcote A, 'Modeling distracted performance', Cognitive Psychology, 112 48-80 (2019) [C1] The sustained attention to response task (SART) has been the primary method of studying the phenomenon of mind wandering. We develop and experimentally test the first integrated c... [more] The sustained attention to response task (SART) has been the primary method of studying the phenomenon of mind wandering. We develop and experimentally test the first integrated cognitive process model that quantitatively explains all stationary features of behavioral performance in the SART. The model assumes that performance is generated by a competitive race between a stimulus-related decision process and a stimulus-unrelated rhythmic response process. We propose that the stimulus-unrelated process entrains to timing regularities in the task environment, and is unconditionally triggered as a habit or ¿insurance policy¿ to protect against the deleterious effects of mind wandering on ongoing task performance. For two SART experiments the model provided a quantitatively precise account of a range of previously reported trends in choice, response time and self-reported mind wandering data. It also accounted for three previously unidentified features of response time distributions that place critical constraints on cognitive models of performance in situations when people might engage in task-unrelated thoughts. Furthermore, the parameters of the rhythmic race model were meaningfully associated with participants¿ self-reported distraction, even though the model was never informed by these data. In a validation test, we disrupted the latent rhythmic component with a manipulation of inter-trial-interval variability, and showed that the architecture of the model provided insight into its counter-intuitive effect. We conclude that performance in the presence of mind wandering can be conceived as a competitive latent decision vs. rhythmic response process. We discuss how the rhythmic race model is not restricted to the study of distraction or mind wandering; it is applicable to any domain requiring repetitive responding where evidence accumulation is assumed to be an underlying principle of behavior.
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2019 |
Hawkins GE, Islam T, Marley AAJ, 'Like it or not, you are using one value representation', Decision, 6 237-260 (2019) [C1] Do we use the same information to decide what we like and what we do not like? Best-worst scaling-where respondents select their most and their least preferred option from a set o... [more] Do we use the same information to decide what we like and what we do not like? Best-worst scaling-where respondents select their most and their least preferred option from a set of options-is an efficient method for obtaining information of direct relevance to this question. Many best-worst scaling applications use multinomial logit (MNL) models to predict such best and worst choice data, explicitly or implicitly assuming that best and worst choices are driven by the same parameters for utility information. Some recent literature, however, has criticized this common practice as an overly simplistic representation of the choice process. We tested this assumption by applying three MNL-type models of increasing complexity in their parameterization to the stated best-worst choices from a total of 1,200 individuals drawn from five data sets. Our Bayesian latent mixture modeling found clear evidence that the same utility parameters drive individuals' best and worst choices, although usually with an additional scale parameter leading to more variable worst choices. These conclusions also held for stated best-worst choices of the same individuals for the same alternatives after a 6-, 12-, and 18-month delay. We argue that the conclusion of several recent papers that best and worst choices are driven by different utility information or reflect different decision processes is based on inadequate data and/or data analyses.
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2018 |
Quinn RK, James MH, Hawkins GE, Brown AL, Heathcote A, Smith DW, et al., 'Temporally specific miRNA expression patterns in the dorsal and ventral striatum of addiction-prone rats', Addiction Biology, 23 631-642 (2018) [C1] MicroRNAs (miRNAs) within the ventral and dorsal striatum have been shown to regulate addiction-relevant behaviours. However, it is unclear how cocaine experience alone can alter ... [more] MicroRNAs (miRNAs) within the ventral and dorsal striatum have been shown to regulate addiction-relevant behaviours. However, it is unclear how cocaine experience alone can alter the expression of addiction-relevant miRNAs within striatal subregions. Further, it is not known whether differential expression of miRNAs in the striatum contributes to individual differences in addiction vulnerability. We first examined the effect of cocaine self-administration on the expression of miR-101b, miR-137, miR-212 and miR-132 in nucleus accumbens core and nucleus accumbens shell (NAcSh), as well as dorsomedial striatum and dorsolateral striatum (DLS). We then examined the expression of these same miRNAs in striatal subregions of animals identified as being ¿addiction-prone¿, either immediately following self-administration training or following extinction and relapse testing. Cocaine self-administration was associated with changes in miRNA expression in a regionally discrete manner within the striatum, with the most marked changes occurring in the nucleus accumbens core. When we examined the miRNA profile of addiction-prone rats following self-administration, we observed increased levels of miR-212 in the dorsomedial striatum. After extinction and relapse testing, addiction-prone rats showed significant increases in the expression of miR-101b, miR-137, miR-212 and miR-132 in NAcSh, and miR-137 in the DLS. This study identifies temporally specific changes in miRNA expression consistent with the engagement of distinct striatal subregions across the course of the addiction cycle. Increased dysregulation of miRNA expression in NAcSh and DLS at late stages of the addiction cycle may underlie habitual drug seeking, and may therefore aid in the identification of targets designed to treat addiction.
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2018 |
Hayes BK, Ngo J, Hawkins GE, Newell BR, 'Causal explanation improves judgment under uncertainty, but rarely in a Bayesian way', MEMORY & COGNITION, 46 112-131 (2018) [C1]
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2018 |
Boehm U, Annis J, Frank MJ, Hawkins GE, Heathcote A, Kellen D, et al., 'Estimating across-trial variability parameters of the Diffusion Decision Model: Expert advice and recommendations', Journal of Mathematical Psychology, 87 46-75 (2018) [C1] For many years the Diffusion Decision Model (DDM) has successfully accounted for behavioral data from a wide range of domains. Important contributors to the DDM's success are... [more] For many years the Diffusion Decision Model (DDM) has successfully accounted for behavioral data from a wide range of domains. Important contributors to the DDM's success are the across-trial variability parameters, which allow the model to account for the various shapes of response time distributions encountered in practice. However, several researchers have pointed out that estimating the variability parameters can be a challenging task. Moreover, the numerous fitting methods for the DDM each come with their own associated problems and solutions. This often leaves users in a difficult position. In this collaborative project we invited researchers from the DDM community to apply their various fitting methods to simulated data and provide advice and expert guidance on estimating the DDM's across-trial variability parameters using these methods. Our study establishes a comprehensive reference resource and describes methods that can help to overcome the challenges associated with estimating the DDM's across-trial variability parameters.
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2017 | Kary A, Hawkins GE, Hayes BK, Newell BR, 'A Bayesian latent mixture model approach to assessing performance in stock-flow reasoning', JUDGMENT AND DECISION MAKING, 12 430-444 (2017) [C1] | Nova | |||||||||
2017 |
Evans NJ, Hawkins GE, Boehm U, Wagenmakers E-J, Brown SD, 'The computations that support simple decision-making: A comparison between the diffusion and urgency-gating models.', Sci Rep, 7 (2017) [C1]
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2016 |
Cassey P, Hawkins GE, Donkin C, Brown SD, 'Using alien coins to test whether simple inference is Bayesian', Journal of Experimental Psychology: Learning Memory and Cognition, 42 497-503 (2016) [C1] Reasoning and inference are well-studied aspects of basic cognition that have been explained as statistically optimal Bayesian inference. Using a simplified experimental design, w... [more] Reasoning and inference are well-studied aspects of basic cognition that have been explained as statistically optimal Bayesian inference. Using a simplified experimental design, we conducted quantitative comparisons between Bayesian inference and human inference at the level of individuals. In 3 experiments, with more than 13,000 participants, we asked people for prior and posterior inferences about the probability that 1 of 2 coins would generate certain outcomes. Most participants' inferences were inconsistent with Bayes' rule. Only in the simplest version of the task did the majority of participants adhere to Bayes' rule, but even in that case, there was a significant proportion that failed to do so. The current results highlight the importance of close quantitative comparisons between Bayesian inference and human data at the individual-subject level when evaluating models of cognition.
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2016 |
Winkel J, Hawkins GE, Ivry RB, Brown SD, Cools R, Forstmann BU, 'Focal striatum lesions impair cautiousness in humans', Cortex, 85 37-45 (2016) [C1] Functional neuroimaging data indicate the dorsal striatum is engaged when people are required to vary the cautiousness of their decisions, by emphasizing the speed or accuracy of ... [more] Functional neuroimaging data indicate the dorsal striatum is engaged when people are required to vary the cautiousness of their decisions, by emphasizing the speed or accuracy of responding in laboratory-based decision tasks. However, the functional contribution of the striatum to decision making is unknown. In the current study we tested patients with focal ischemic lesions of the dorsal striatum and matched non-lesion control participants on a speed-accuracy tradeoff (SAT) task. Analysis using a computational model of response selection in a competitive and time-pressured context indicated that the decisions of patients with striatal lesions were less cautious than those of matched controls. This deficit was most prominent when the accuracy of decisions was emphasized. The results are consistent with the hypothesis that the striatum plays an important role in strategically setting response caution, an essential function for flexible behavior.
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2016 |
Boehm U, Hawkins GE, Brown S, van Rijn H, Wagenmakers EJ, 'Of monkeys and men: Impatience in perceptual decision-making', Psychonomic Bulletin and Review, 23 738-749 (2016) [C1] For decades sequential sampling models have successfully accounted for human and monkey decision-making, relying on the standard assumption that decision makers maintain a pre-set... [more] For decades sequential sampling models have successfully accounted for human and monkey decision-making, relying on the standard assumption that decision makers maintain a pre-set decision standard throughout the decision process. Based on the theoretical argument of reward rate maximization, some authors have recently suggested that decision makers become increasingly impatient as time passes and therefore lower their decision standard. Indeed, a number of studies show that computational models with an impatience component provide a good fit to human and monkey decision behavior. However, many of these studies lack quantitative model comparisons and systematic manipulations of rewards. Moreover, the often-cited evidence from single-cell recordings is not unequivocal and complimentary data from human subjects is largely missing. We conclude that, despite some enthusiastic calls for the abandonment of the standard model, the idea of an impatience component has yet to be fully established; we suggest a number of recently developed tools that will help bring the debate to a conclusive settlement.
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2015 |
Hawkins GE, Forstmann BU, Wagenmakers EJ, Ratcliff R, Brown SD, 'Revisiting the evidence for collapsing boundaries and urgency signals in perceptual decision-making', Journal of Neuroscience, 35 2476-2484 (2015) [C1] For nearly 50 years, the dominant account of decision-making holds that noisy information is accumulated until a fixed threshold is crossed. This account has been tested extensive... [more] For nearly 50 years, the dominant account of decision-making holds that noisy information is accumulated until a fixed threshold is crossed. This account has been tested extensively against behavioral and neurophysiological data for decisions about consumer goods, perceptual stimuli, eyewitness testimony, memories, and dozens of other paradigms, with no systematic misfit between model and data. Recently, the standard model has been challenged by alternative accounts that assume that less evidence is required to trigger a decision as time passes. Such ¿collapsing boundaries¿ or ¿urgency signals¿ have gained popularity in some theoretical accounts of neurophysiology. Nevertheless, evidence in favor of these models is mixed, with support coming from only a narrow range of decision paradigms compared with a long history of support from dozens of paradigms for the standard theory. We conducted the first large-scale analysis of data from humans and nonhuman primates across three distinct paradigms using powerful model-selection methods to compare evidence for fixed versus collapsing bounds. Overall, we identified evidence in favor of the standard model with fixed decision boundaries. We further found that evidence for static or dynamic response boundaries may depend on specific paradigms or procedures, such as the extent of task practice. We conclude that the difficulty of selecting between collapsing and fixed bounds models has received insufficient attention in previous research, calling into question some previous results.
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Nova | |||||||||
2015 |
Jones LG, Hawkins GE, Brown SD, 'Using Best-Worst Scaling to Improve Psychological Service Delivery: An Innovative Tool for Psychologists in Organized Care Settings', PSYCHOLOGICAL SERVICES, 12 20-27 (2015) [C1]
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Nova | |||||||||
2015 |
Hawkins GE, Wagenmakers E-J, Ratcliff R, Brown SD, 'Discriminating evidence accumulation from urgency signals in speeded decision making.', J Neurophysiol, 114 40-47 (2015) [C1]
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Nova | |||||||||
2014 |
Hawkins GE, Marley AAJ, Heathcote A, Flynn TN, Louviere JJ, Brown SD, 'Integrating Cognitive Process and Descriptive Models of Attitudes and Preferences', COGNITIVE SCIENCE, 38 701-735 (2014) [C1]
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Nova | |||||||||
2014 |
Hawkins GE, Marley AAJ, Heathcote A, Flynn TN, Louviere JJ, Brown SD, 'The best of times and the worst of times are interchangeable.', Decision, 1 192-214 (2014) [C1]
|
Nova | |||||||||
2013 |
Hawkins GE, Rae B, Nesbitt KV, Brown SD, 'Gamelike features might not improve data', BEHAVIOR RESEARCH METHODS, 45 301-318 (2013) [C1]
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Nova | |||||||||
2012 |
Walker AK, Hawkins GE, Sominsky Bar L, Hodgson DM, 'Transgenerational transmission of anxiety induced by neonatal exposure to lipopolysaccharide: Implications for male and female germ lines', Psychoneuroendocrinology, 37 1320-1335 (2012) [C1]
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Nova | |||||||||
2012 |
Hawkins GE, Brown SD, Steyvers M, Wagenmakers E-J, 'Context effects in multi-alternative decision making: Empirical data and a Bayesian model', Cognitive Science, 36 498-516 (2012) [C1]
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Nova | |||||||||
2012 |
Hawkins GE, Brown SD, Steyvers M, Wagenmakers EJ, 'An optimal adjustment procedure to minimize experiment time in decisions with multiple alternatives', Psychonomic Bulletin & Review, 19 339-348 (2012) [C1]
|
Nova | |||||||||
2012 |
Prince MA, Hawkins GE, Love JP, Heathcote AJ, 'An R package for state-trace analysis', Behavior Research Methods, 44 644-655 (2012) [C1]
|
Nova | |||||||||
2012 |
Hawkins GE, Brown SD, Steyvers M, Wagenmakers E-J, 'Decision speed induces context effects in choice', Experimental Psychology, 59 206-215 (2012) [C1]
|
Nova | |||||||||
Show 52 more journal articles |
Conference (22 outputs)
Year | Citation | Altmetrics | Link | |||||
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2017 |
Hawkins GE, Mittner M, Heathcote A, Forstmann BU, 'Cognitive models of distracted performance and strange data', Abstracts of the 58th Annual Meeting of the Psychonomic Society, Vancouver, BC (2017)
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2015 | Hayes BK, Hawkins GE, Newell BR, 'Why do people fail to consider alternative hypotheses in judgments under uncertainty?', Proceedings of the 37th Annual Conference of the Cognitive Science Society, Pasadena, CA (2015) | |||||||
2015 |
Hawkins GE, Mittner M, Heathcote A, Forstmann BU, 'Matter over mind (wandering): Electrophysiological predictors of task-unrelated decrements in performance', Chicago, IL (2015)
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2015 | Van Gerven M, Ghebreab S, Hawkins G, Borst J, 'Neural correlates of cognitive models', Proceedings of ICCM 2015 - 13th International Conference on Cognitive Modeling (2015) | |||||||
2012 |
Hawkins GE, Rae BP, Nesbitt KV, Brown SD, 'To game or not to game, perhaps there is no question: Game-like features might not improve data', Combined Abstracts of 2012 Australian Psychology Conferences, Sydney, NSW (2012) [E3]
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2011 |
Hawkins GE, Brown SD, Steyvers M, Wagenmakers E-J, 'Leave the experiment as quickly as possible, without looking stupid: An optimal adjustment procedure to explain context effects in mulit-alternative choice', Abstracts of the Psychonomic Society 52nd Annual Meeting, Seattle, WA (2011) [E3]
|
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2011 |
Walker AK, Hawkins GE, Sominsky Bar L, Hodgson DM, 'Transgenerational effects of anxiety-like behaviour in rats exposed to a bacterial mimetic during neonatal life: Implications for male and female germ lines', Brain, Behavior, and Immunity, Chicago, Illinois (2011) [E3]
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2010 |
Hawkins GE, Prince MA, Brown SD, Heathcote AJ, 'Designing state-trace expeiments to assess the number of latent psychological variables underlying binary choices', Proceedings of the 32nd Annual Conference of the Cognitive Science Society, Portland, Oregon (2010) [E1]
|
Nova | ||||||
2010 |
Camilleri A, Newell B, Hawkins GE, Dodds PM-J, Brown SD, 'Judgment and choice in a sequential sampling paradigm', Australasian Mathematical Psychology Conference 2010 (AMPC 2010), Margaret River, WA (2010) [E3]
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2010 |
Hawkins GE, Dodds PM-J, Camilleri A, Brown SD, Newell B, 'A particle filter account for the estimation of probability', Australasian Mathematical Psychology Conference 2010 (AMPC 2010), Margaret River, WA (2010) [E3]
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2010 |
Hawkins GE, Prince MA, Brown SD, Heathcote AJ, 'State-trace analysis of recognition memory data: A Bayes Factor approach', Australasian Mathematical Psychology Conference 2010 (AMPC 2010), Margaret River, WA (2010) [E3]
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2010 |
Prince MA, Hawkins GE, Brown SD, Heathcote AJ, 'Bayesian ordinal analysis of state-trace data', Australasian Mathematical Psychology Conference 2010 (AMPC 2010), Margaret River, WA (2010) [E3]
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2010 |
Hawkins GE, Brown SD, Steyvers M, Wagenmakers EJ, 'Hick's Law: How high can it go?', Combined Abstracts of 2010 Australian Psychology Conferences, Melbourne, Vic (2010) [E3]
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2010 |
Walker AK, Hawkins GE, Hodgson DM, 'Epigenetic inheritance of anxiety', Brain, Behavior, and Immunity, Dublin, Ireland (2010) [E3]
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2008 |
Walker AK, Hawkins GE, Hunter M, Hodgson DM, 'Transgenerational implications for neonatal lipopolysaccharide exposure on adulthood anxiety and maternal care of second generation offspring', Proceedings of the Australian Health and Medical Research Congress 2008, Brisbane, QLD (2008) [E3]
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Show 19 more conferences |
Grants and Funding
Summary
Number of grants | 17 |
---|---|
Total funding | $2,880,548 |
Click on a grant title below to expand the full details for that specific grant.
20231 grants / $20,000
Cyber Maturity Phase 2$20,000
Funding body: Defence Innovation Network NSW
Funding body | Defence Innovation Network NSW |
---|---|
Project Team | Professor Ami Eidels, Professor Scott Brown, Doctor Guy Hawkins, Riley Innes |
Scheme | Scholarship |
Role | Investigator |
Funding Start | 2023 |
Funding Finish | 2024 |
GNo | G2301404 |
Type Of Funding | C2400 – Aust StateTerritoryLocal – Other |
Category | 2400 |
UON | Y |
20221 grants / $1,121,313
Evaluation and comparison of the Human Machine Interface (HMI) in vehicles in the Australian Market$1,121,313
Funding body: Australian Automobile Association (AAA)
Funding body | Australian Automobile Association (AAA) |
---|---|
Project Team | Professor Kristen Pammer, Professor Scott Brown, Professor Ami Eidels, Doctor Cassandra Gauld, Doctor Guy Hawkins, Mr Angus McKerral, Professor Kristen Pammer, Sarah Roberts, Doctor Rachael Wynne |
Scheme | Research Project |
Role | Investigator |
Funding Start | 2022 |
Funding Finish | 2025 |
GNo | G2200861 |
Type Of Funding | C3100 – Aust For Profit |
Category | 3100 |
UON | Y |
20211 grants / $356,109
Perceiving is believing: Perceptual inference anomalies in schizophrenia$356,109
Funding body: NHMRC (National Health & Medical Research Council)
Funding body | NHMRC (National Health & Medical Research Council) |
---|---|
Project Team | Professor Juanita Todd, Dr Ryszard Auksztulewicz, Professor Scott Brown, Dean Salisbury, Prof Dean Salisbury, Ryszard Auksztulewicz, Doctor Guy Hawkins, Mr Matthew Godfrey |
Scheme | Ideas Grants |
Role | Investigator |
Funding Start | 2021 |
Funding Finish | 2024 |
GNo | G2000628 |
Type Of Funding | C1100 - Aust Competitive - NHMRC |
Category | 1100 |
UON | Y |
20201 grants / $385,115
Quantitative psychological theories for a dynamic world$385,115
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Professor Scott Brown, Professor Scott Brown, Doctor Guy Hawkins, Professor Andrew Heathcote, Conjoint Professor Andrew Heathcote, Doctor Guy Hawkins, Professor Ami Eidels |
Scheme | Discovery Projects |
Role | Investigator |
Funding Start | 2020 |
Funding Finish | 2023 |
GNo | G1901515 |
Type Of Funding | C1200 - Aust Competitive - ARC |
Category | 1200 |
UON | Y |
20183 grants / $417,987
The value of time during decisions$343,171
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Doctor Guy Hawkins, Professor Scott Brown |
Scheme | Discovery Projects |
Role | Lead |
Funding Start | 2018 |
Funding Finish | 2020 |
GNo | G1700292 |
Type Of Funding | C1200 - Aust Competitive - ARC |
Category | 1200 |
UON | Y |
Smart Transportation Choices for Smart City Newcastle$67,316
Funding body: Newcastle City Council
Funding body | Newcastle City Council |
---|---|
Project Team | Ami Eidels, Guy Hawkins, Elise Kalokerinos, Scott Brown |
Scheme | Smart City Newcastle |
Role | Investigator |
Funding Start | 2018 |
Funding Finish | 2019 |
GNo | |
Type Of Funding | Other Public Sector - Local |
Category | 2OPL |
UON | N |
Gaze-based cognitive models of consumer preferences$7,500
Funding body: Faculty of Science and IT, University of Newcastle
Funding body | Faculty of Science and IT, University of Newcastle |
---|---|
Project Team | Guy E Hawkins |
Scheme | New Staff Grant |
Role | Lead |
Funding Start | 2018 |
Funding Finish | 2018 |
GNo | |
Type Of Funding | Internal |
Category | INTE |
UON | N |
20175 grants / $530,847
Cognitive models of mental architectures in consumer preference$383,055
Funding body: ARC (Australian Research Council)
Funding body | ARC (Australian Research Council) |
---|---|
Project Team | Doctor Guy Hawkins |
Scheme | Discovery Early Career Researcher Award (DECRA) |
Role | Lead |
Funding Start | 2017 |
Funding Finish | 2019 |
GNo | G1600338 |
Type Of Funding | C1200 - Aust Competitive - ARC |
Category | 1200 |
UON | Y |
Early Career Researcher HDR Candidate Scholarship$78,864
Funding body: The University of Newcastle
Funding body | The University of Newcastle |
---|---|
Project Team | Guy Hawkins |
Scheme | Early Career Researcher HDR Candidate Scholarship |
Role | Lead |
Funding Start | 2017 |
Funding Finish | 2020 |
GNo | |
Type Of Funding | International - Competitive |
Category | 3IFA |
UON | N |
DVC(RI) Research Support for DECRA (DE17)$47,928
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Doctor Guy Hawkins |
Scheme | DECRA Support |
Role | Lead |
Funding Start | 2017 |
Funding Finish | 2019 |
GNo | G1700225 |
Type Of Funding | Internal |
Category | INTE |
UON | Y |
Model-based cognitive neuroscience summer school$20,000
Funding body: William K. and Katherine W. Estes Fund
Funding body | William K. and Katherine W. Estes Fund |
---|---|
Project Team | Prof Birte Forstmann, Dr Dora Matzke, Prof Uta Noppeney, Prof Andrew Heathcote, Dr Brandon Turner, Mr Gilles de Hollander, Dr Guy Hawkins |
Scheme | Advancement of Mathematical Psychology |
Role | Investigator |
Funding Start | 2017 |
Funding Finish | 2017 |
GNo | |
Type Of Funding | International - Competitive |
Category | 3IFA |
UON | N |
School of Psychology Travel Support$1,000
Funding body: University of Newcastle
Funding body | University of Newcastle |
---|---|
Project Team | Dr Guy Hawkins |
Scheme | School of Psychology Travel Support |
Role | Lead |
Funding Start | 2017 |
Funding Finish | 2017 |
GNo | |
Type Of Funding | Internal |
Category | INTE |
UON | N |
20161 grants / $20,000
Bayesian estimation of evidence accumulation architectures in neuroscience and cognition$20,000
Funding body: William K. and Katherine W. Estes Fund
Funding body | William K. and Katherine W. Estes Fund |
---|---|
Project Team | Prof Andrew Heathcote, Prof Scott Brown, Dr Brandon Turner, Dr Dora Matzke, Dr Guy Hawkins, Dr Maxim Bushmakin |
Scheme | Advancement of Mathematical Psychology |
Role | Investigator |
Funding Start | 2016 |
Funding Finish | 2016 |
GNo | |
Type Of Funding | International - Competitive |
Category | 3IFA |
UON | N |
20152 grants / $22,000
Model-based cognitive neuroscience$20,500
Funding body: Volkswagenstiftung (Volkswagen Foundation)
Funding body | Volkswagenstiftung (Volkswagen Foundation) |
---|---|
Project Team | Prof Birte Forstmann, Dr Leendert van Maanen, Prof Jane Neumann, Dr Guy Hawkins, Prof Roger Ratcliff |
Scheme | Symposia and Summer Schools |
Role | Investigator |
Funding Start | 2015 |
Funding Finish | 2015 |
GNo | |
Type Of Funding | International - Competitive |
Category | 3IFA |
UON | N |
Symposium on model-based neuroscience of mind wandering$1,500
Funding body: Amsterdam Brain and Cognition Center
Funding body | Amsterdam Brain and Cognition Center |
---|---|
Project Team | Dr Guy Hawkins, Prof Birte Forstmann |
Scheme | Amsterdam Brain and Cognition Center Small Grants Scheme |
Role | Investigator |
Funding Start | 2015 |
Funding Finish | 2016 |
GNo | |
Type Of Funding | International - Non Competitive |
Category | 3IFB |
UON | N |
20141 grants / $3,827
Faculty of Science Early Career Researcher Visiting Fellowship$3,827
Funding body: The University of Newcastle
Funding body | The University of Newcastle |
---|---|
Project Team | Dr Guy Hawkins, Prof Andrew Heathcote |
Scheme | Faculty of Science Early Career Researcher Visiting Fellowship |
Role | Lead |
Funding Start | 2014 |
Funding Finish | 2014 |
GNo | |
Type Of Funding | Internal |
Category | INTE |
UON | N |
20091 grants / $3,350
Pushing the limits of Hick's Law: Evidence accumulation during multi-alternative decisions$3,350
Funding body: Keats Endowment Research Fund
Funding body | Keats Endowment Research Fund |
---|---|
Project Team | Professor Scott Brown, Doctor Guy Hawkins |
Scheme | Research Grant |
Role | Investigator |
Funding Start | 2009 |
Funding Finish | 2010 |
GNo | G0900112 |
Type Of Funding | Grant - Aust Non Government |
Category | 3AFG |
UON | Y |
Research Supervision
Number of supervisions
Current Supervision
Commenced | Level of Study | Research Title | Program | Supervisor Type |
---|---|---|---|---|
2024 | PhD | Performance and Behavioural Strategies of Human-Human and Human-Bot Teams | PhD (Psychology - Science), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2024 | PhD | An Exploration of Mood and Decision-Making: The Role of Affective States on Strategy Selection | PhD (Psychology - Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2024 | PhD | Advancing Neuropsychological Assessment: A Multifaceted Approach to Addressing Accessibility and Technological Innovations in Cognitive Evaluation | PhD (Psychology - Science), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2022 | PhD | Quantitative Psychological Theories for a Dynamic World | PhD (Psychology - Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2022 | PhD | Exploring the Role of Trust in Human-Bot Teaming in the Domain of Cybersecurity | PhD (Psychology - Science), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2022 | PhD | What Dads Want: Examining Fathers' Preferences for Parenting Programs and Efficacy of Preferred Program Design | PhD (Clinical Psychology), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2022 | PhD | Developing a Benchmark for Human-Bot Performance | PhD (Psychology - Science), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2021 | PhD | Understanding the Nature of Cognitive Decline - a Cognitive Modelling Approach | PhD (Psychology - Science), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2021 | PhD | First to the Finish Line: Exploring the Stability of Decision-Making Strategies Across Contexts Using the Time Racing Diffusion Model | PhD (Psychology - Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2020 | Masters | Does Changing from a Predictive to an Inferential Task Change the Way that we Learn? | M Philosophy (Psychology), College of Engineering, Science and Environment, The University of Newcastle | Co-Supervisor |
2019 | PhD | Examining the Assumptions of Cognitive Models of Decision Making | PhD (Psychology - Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2018 | PhD | Gaze-Based Cognitive Models of Mental Architectures in Consumer Preference | PhD (Psychology - Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
Past Supervision
Year | Level of Study | Research Title | Program | Supervisor Type |
---|---|---|---|---|
2023 | PhD | The Role of Time in Consumer-Like Choices | PhD (Psychology - Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
Research Collaborations
The map is a representation of a researchers co-authorship with collaborators across the globe. The map displays the number of publications against a country, where there is at least one co-author based in that country. Data is sourced from the University of Newcastle research publication management system (NURO) and may not fully represent the authors complete body of work.
Country | Count of Publications | |
---|---|---|
Australia | 55 | |
Netherlands | 31 | |
United States | 22 | |
Norway | 8 | |
Germany | 5 | |
More... |
Dr Guy Hawkins
Position
Senior Lecturer
Cognitive Psychology
School of Psychological Sciences
College of Engineering, Science and Environment
Contact Details
guy.hawkins@newcastle.edu.au | |
Phone | (02) 4985 4493 |
Link | Personal webpage |
Office
Room | W-342 |
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Building | Behavioural Sciences Building |
Location | Callaghan University Drive Callaghan, NSW 2308 Australia |