PINTS

PINTS is an annual event aimed to bring together cognitive, computational, and systems neuroscience researchers from the Paris region.

This year's symposium will feature keynote and invited lectures by renowned speakers, with a primary focus on contributed talks from the community. We encourage everyone to submit an abstract for a talk and/or poster at PINTS. Submissions are welcome from all career stages, and you are welcome to recycle abstracts from previous conferences (e.g. SFN or COSYNE).

Trial matching: capturing variability with data-constrained spiking neural networks

Simultaneous behavioral and electrophysiological recordings call for new methods to reveal the interactions between neural activity and behavior. One main challenge is to create an interpretable model of the co-variability of spiking activity and behavior across trials. In this talk, we will present our model of a mouse cortical sensory-motor pathway in a tactile detection task reported by licking.

Neural representations of learning and behavior

A fundamental question in neuroscience is to understand how coordinated neural activity and structured circuitry in the brain are responsible for generating behavior. Decades of experimental and theoretical work have demonstrated that correlated neural activity has a strong impact on population coding by reshaping neural representations of external stimuli. More recently, large-scale recordings have provided insight as to the dynamic mechanisms by which neural populations perform computations, but the link to their circuitry remains unclear.

A psycholinguistic look at subjective predicates: When faultless disagreement is not so faultless

The information we encounter on a daily basis involves both objective facts about the world and people’s subjective opinions. This distinction is also reflected in language: Words that express opinions (e.g. fun, amazing) differ from words conveying more objective facts (e.g. wooden, Bostonian): Subjective adjectives are perspective-sensitive and reflect someone’s opinion/attitude.

How robust are meta-analyses to publication bias? Sensitivity analysis methods and empirical findings

Publication bias can distort meta-analytic results, sometimes justifying considerable skepticism toward meta-analyses. This talk will discuss recently developed statistical sensitivity analyses for publication bias, which enable statements such as: “For publication bias to shift the observed point estimate to the null, ‘significant’ results would need to be at least 10-fold more likely to be published than negative or ‘non-significant’ results” or “no amount of publication bias could explain away the average effect.” The methods are based on inverse-probability weighted estimators and

The rational use of cognitive resources

Psychologists and computer scientists have very different views of the mind. Psychologists tell us that humans are error-prone, using simple heuristics that result in systematic biases. Computer scientists view human intelligence as aspirational, trying to capture it in artificial intelligence systems. How can we reconcile these two perspectives? In this talk, I will argue that we can do so by reconsidering how we think about rational action.

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