What's in a name?
In our lab, “imagination” is roughly synonymous with the notion of mental simulation, or our ability to represent information other than what is immediately present in sensory representations. The term “modal cognition” derives from the philosophical notion of “modality”, which refers to the area of study concerned with understanding modal statements, that is, claims about necessity, possibility, contingency, and actuality, among others. As such, “modal cognition” refers to the psychological processes engaged when we imagine and reason about possibilities, necessities, contingencies, actualities, and other ways in which things can be.
How do science and philosophy inform each other?
We believe that philosophy and science are continuous, and that they provide important checks on each other. Empirical evidence often challenges philosophical theories developed on the basis of intuition, and philosophical analysis can reframe the scope of a particular scientific finding. Asa group of scientists and philosophers, we use our complementary backgrounds to design experiments that investigate the nature of human memory, imagination, and causal reasoning. We do this using functional magnetic resonance imaging (fMRI), electroencephalography (EEG), online and in-lab behavioral experiments, and computational models.
How do memory and imagination interact?
Remembering and imagining both involve mentally representing information other than what is present in your immediate environment. This capacity for 'offline simulation' is one of the defining features of the human mind, allowing us to re-experience the past and plan for the future.
We have suggested that remembering is a subprocess of imagination, and that these processes are part of a larger neurocognitive system responsible for generating episodic hypothetical thoughts. We are particularly interested in interactions between autobiographical memory (i.e., memory for your personal past) and episodic counterfactual thinking (i.e., thinking about how the past could have unfolded differently). We are currently investigating how episodic counterfactual thinking can be leveraged as an emotion regulation mechanism, how the episodic hypothetical thought system represents the plausibility of a particular hypothetical, and how these processes contribute to judgments of responsibility and causation.
How does morality factor into how we remember our personal past?
Most people believe they are morally good, and this belief plays an integral role in constructions of personal identity. Yet people commit moral transgressions with surprising frequency in everyday life. We have characterized a mechanism involving autobiographical memory that is utilized to foster a belief in a morally good self-concept in the present — despite frequent and repeated immoral behavior in the past. That is, when past moral transgressions are not forgotten, people strategically compare their more recent unethical behaviors with their more distant unethical behaviors to foster a perception of personal moral improvement over time. This, in turn, helps to portray the current self favorably.
People perceive themselves as more different and changed as a function of recalling morally wrong actions, and perceive themselves as more the same as a function of recalling morally right actions. This effect does not carry over to their recollection of others' actions.
Stanley, M.L. and De Brigard, F. (2019). Moral Memories and the Belief in the Good Self.
How do people make causal judgments?
Assessing who or what caused a particular outcome is a complex cognitive process involving a number of different factors. Following counterfactual theories of causation, we have argued that imagination of salient possibilities supports our capacity to select causes in physical, social, and moral domains. We have shown that the sorts of possibilities that people mentally simulate explain why omissions can be perceived as causal, why action is perceived as more causal than inaction, and why some omissions are judged to be more causal than others. Currently, we are using eye-tracking to investigate how norms direct attention toward norm-violating entities to make more normal possibilities salient for simulation. We are also investigating the distributional properties of causal ratings in relation to meta-cognitive assessments of uncertainty to determine the extent to which mental simulations contributing to causal judgments are probabilistic in nature.
What caused the goal to turn green?
How do people structure their memories and experiences?
It is well established that prior knowledge structures or “schemas” influence recognition memory. Unfortunately, given how long it usually takes to acquire new schemas, it has been difficult to experimentally track their influence on memory from learning to test. Inspired by recent work showing similarities between category- and schema-based memory effects, we developed a novel category learning paradigm that allow researchers to easily manipulate category learning to investigate the effects of knowledge acquisition on subsequent recognition memory. Using this paradigm, we have shown how category learning increases both hits and false-alarms for category-consistent items. We think that exploring the connections between categorical and schematic learning may contribute to our understanding of how our memory system employs prior knowledge to reconstruct past experiences.
Learning a category (a) both increases the likelihood that you remember items from that category and falsely remember items belonging to that category that you've never seen. Failing to learn a category (b) has no effect on memory performance.
How can philosophy inform neuroscience?
We believe that philosophy can—and should—have a role to play in the theoretical foundations and practice of cognitive psychology and neuroscience. Research in the philosophy of neuroscience promises to help to identify, diagnose and—why not—solve scientific challenges. Some of the research in the philosophy of neuroscience conducted in our lab involves issues such as the explanatory advantages of using certain tools from topology—particularly modularity algorithms in network neuroscience—when it comes to modeling neuronal redeployment, as well as the advantages of topological properties in predictive models in neuroscience, and the challenges that brain development pose to the prospect of characterizing a cognitive ontology.
A challenge posed by the aging brain: if Phase 1 and Phase 2 images reveal the set of mechanisms constituting a cognitive system responsible for a particular task at different times, which set accurately captures the cognitive system?