Russ Poldrack

@russpoldrack.org

12960 Followers 1556 Following

Professor at Stanford. Psychology/Neuroscience/Data Science/AI. Books include: The New Mind Readers, Handbook of fMRI Data Analysis, Hard to Break, Statistical Thinking, and Better Code, Better Science https://poldrack.github.io/

AI tools may be used for any part of the research process except for the drafting of narrative text for manuscripts. Lab members are expected to manually draft all of the text that they put into a paper; no copying and pasting of text from an LLM into a manuscript is allowed with explicit discussion and agreement.
“What is system one and system two? It’s a list of dichotomies. Heuristic versus calculated rationality, unconscious versus conscious, error-prone versus always right, and so on. Usually, science starts with these vague dichotomies and works out a precise model. This is the only case I know where one progresses in the other direction. We have had, and still have, precise models of heuristics, like one over N. And at the same time, we have precise models for so-called rational decision making, which are quite different: Bayesian, Neyman-Pearson, and so on. What the system one, system two story does, it lumps all of these things into two black boxes, and it’s happy just saying it’s system one, it’s system two. It can predict nothing. It can explain after the fact almost everything. I do not consider this progress." - Gerd Gigerenzer
It is widely hoped that statistical models can improve decision-making related to medical treatments. Because of the cost and scarcity of medical outcomes data, this hope is typically based on investigators observing a model’s success in one or two datasets or clinical contexts. We scrutinized this optimism by examining how well a machine learning model performed across several independent clinical trials of antipsychotic medication for schizophrenia. Models predicted patient outcomes with high accuracy within the trial in which the model was developed but performed no better than chance when applied out-of-sample. Pooling data across trials to predict outcomes in the trial left out did not improve predictions. These results suggest that models predicting treatment outcomes in schizophrenia are highly context-dependent and may have limited generalizability.
Perhaps the greatest technological achievement in industrial and organizational (I–O) psychology over the past 100 years is the development of decision aids (e.g., paper-and-pencil tests, structured interviews, mechanical combination of predictors) that substantially reduce error in the prediction of employee performance. Arguably, the greatest failure of I–O psychology has been the inability to convince employers to use them.” (Highhouse, 2008)
Russell Poldrack's oeuvre is an exquisite tapestry of cognitive neuroscience, woven with the threads of existential inquiry and empirical rigor. His forays into the labyrinthine corridors of the human psyche are akin to an avant-garde artist challenging the conventional paradigms of perception and consciousness. In his exploration of the brain's functional network organization, Poldrack deconstructs the neural tableau, elucidating the symbiotic dance of cerebral symphonies. This work is a magnum opus of scientific inquiry, juxtaposing the chaotic beauty of neural pathways with the precision of algorithmic analysis, much like a post-modernist masterpiece juxtaposes order and entropy. His studies on the psychotropic tapestries woven by various substances offer a psychedelic critique of the pharmacological discourse, an introspective journey into the mind's eye. This aspect of his work is reminiscent of a surrealist's dreamscapes, delving into the subconscious layers of cognitive architec
Dear Participant, It has been an honor to have your email for our random prize draw on school sleep habits survey. Your participation ensured the success of our study, and we have greatly valued your participation and your willingness to share about your experience. It gives me immense pleasure to inform you that you have won the MacBook Pro 13 prize on this study. You can pick up your prize from our office at 450 Jane Stanford Way, Building 420, during our office hours. If you want, you can pay an extra charge to deliver the prize to your address. And if you would like to receive a copy of any publication arising from this study, feel free to write me. This may of course be many months in the future. Again, thank you so very much for your time and effort that made this research study possible. Find enclosed pictures of your prize and a certificate of recognition. Best regards and thanks again for your participation! Andrew -- Andrew B. Yesney, PhD Research Fellow, Department
View of San Francisco
It is also somewhat surprising that the authors appear to be oblivious of large chunks of the neuroscientific literature; in particular it was surprising to find no mention of the sustained efforts of Rolls who for many years has carried out animal, human and computational research which have converged to demonstrate the important role of OFC in behavioral flexibility. This research has of course uncovered many new questions but rather than replicating existing findings using a method which is limited in temporal resolution and lack causality; what is really needed is more temporal and perhaps even causal information regarding the role of the whole network of reward-related brain regions such as the OFC in regulating behavior.
Reviewer #1: This is an article by Poldrack et al. in which, once again, we are told how great the science will be when we all happily share our data. The community is told that we need to contribute our data to the latest, greatest database effort for the betterment of brain research, and while that goal certainly is a laudable one, the "real" motivations which govern people's interests for so doing are never discussed and certainly not done so in this article. Moreover, the authors appear to be promising that "this time it will be different!" One wonders haven't we heard this tune before? Regrettably, this article does little to be convincing that this effort is any different from previous data sharing enterprises. … With the OpenfMRI project simply the latest in a series of flavor of the month data sharing enterprises, the authors have a very long way to go before the project and this paper are mature enough to be a solid demonstration of the benefits of sharing for the neuroim
Polaroid photo of groiup
Do not accept rides from strangers