108. Robert Wilson: 10 simple rules for computational modelling, phishing, and reproducibility

BJKS Podcast

Robert (Bob) Wilson is an Associate Professor of Psychology at Georgia Tech. We talk about his tutorial paper (w/ Anne Collins) on computational modelling, and some of his recent work on detecting phishing.
BJKS Podcast is a podcast about neuroscience, psychology, and anything vaguely related, hosted by Benjamin James Kuper-Smith.
Support the show: https://geni.us/bjks-patreon
Timestamps
0:00:00: Bob's strange path through computational cognitive neuroscience
0:07:37: Phishing: a computational model with real-life applications
0:25:46: Start discussing Bob's paper 10 simple rules for computational modeling of behavioral data
0:32:15: Rule 0: Why even do computational modelling?
0:46:24: Rules 1 & 2: Design a good experiment & Design a good model
1:02:51: Rule 3: Simulate!
1:05:48: Rules 4 & 5: Parameter estimation and recovery
1:18:28: Rule 6: Model recovery
1:25:55: Rules 7 & 8: Collect data and validate the model
1:33:15: Rule 9: Latent variable analysis
1:36:24: Rule 10: Report your results
1:37:46: Computational modelling and the open science movement
1:40:17: A book or paper more people should read
1:43:35: Something Bob wishes he'd learnt sooner
1:47:18: Advice for PhD students/postdocs
Podcast links

• Website: https://geni.us/bjks-pod
• Twitter: https://geni.us/bjks-pod-twt

Robert's links

• Website: https://geni.us/wilson-web
• Google Scholar: https://geni.us/wilson-scholar
• Twitter: https://geni.us/wilson-twt

Ben's links

• Website: https://geni.us/bjks-web
• Google Scholar: https://geni.us/bjks-scholar
• Twitter: https://geni.us/bjks-twt

References
Episodes w/ Paul Smaldino:
https://geni.us/bjks-smaldino
https://geni.us/bjks-smaldino_2
Bechara, Damasio, Damasio, & Anderson (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition.
Feng, Wang, Zarnescu & Wilson (2021). The dynamics of explore–exploit decisions reveal a signal-to-noise mechanism for random exploration. Scientific Reports.
Grilli, ... & Wilson (2021). Is this phishing? Older age is associated with greater difficulty discriminating between safe and malicious emails. The Journals of Gerontology: Series B.
Hakim, Ebner, ... & Wilson (2021). The Phishing Email Suspicion Test (PEST) a lab-based task for evaluating the cognitive mechanisms of phishing detection. Behavior research methods.
Harootonian, Ekstrom & Wilson (2022). Combination and competition between path integration and landmark navigation in the estimation of heading direction. PLoS Computational Biology.
Hopfield (1982). Neural networks and physical systems with emergent collective computational abilities. PNAS.
MacKay (2003). Information theory, inference and learning algorithms.
Miller, Eugene & Pribram (1960). Plans and the Structure of Behaviour.
Sweis, Abram, Schmidt, Seeland, MacDonald III, Thomas, & Redish (2018). Sensitivity to “sunk costs” in mice, rats, and humans. Science.
Walasek & Stewart (2021). You cannot accurately estimate an individual’s loss aversion using an accept–reject task. Decision.
Wilson & Collins (2019). Ten simple rules for the computational modeling of behavioral data. Elife.

Chapters

1. Bob's strange path through computational cognitive neuroscience (00:00:00)

2. Phishing: a computational model with real-life applications (00:07:37)

3. Start discussing Bob's paper 10 simple rules for computational modeling of behavioral data (00:25:46)

4. Rule 0: Why even do computational modelling? (00:32:15)

5. Rules 1 & 2: Design a good experiment & Design a good model (00:46:24)

6. Rule 3: Simulate! (01:02:51)

7. Rules 4 & 5: Parameter estimation and recovery (01:05:48)

8. Rule 6: Model recovery (01:18:28)

9. Rules 7 & 8: Collect data and validate the model (01:25:55)

10. Rule 9: Latent variable analysis (01:33:15)

11. Rule 10: Report your results (01:36:24)

12. Computational modelling and the open science movement (01:37:46)

13. A book or paper more people should read (01:40:17)

14. Something Bob wishes he'd learnt sooner (01:43:35)

15. Advice for PhD students/postdocs (01:47:18)