Our everyday lives are full of events, such as waking up in the morning, making a sandwich, and writing an email. People have knowledge of these common events, called event knowledge, or the knowledge of patterns of activities in the world.

In particular, we have been investigating the temporal structure of event knowledge, that is, how people represent the order of activities within events in their mind. We are using network science techniques to analyze the complexity and richness of event structure (McRae, Brown, Elman, 2021), as well as to determine activities that are considered central (i.e., important for the event to occur). We are currently investigating whether network science measures of centrality overlap with people’s ratings of how central or standard activities are within common events.

Additionally, the lab has been studying how the temporal structure of event knowledge relates to autism spectrum disorder and autistic traits. Specifically, social communication is altered in autism, and we believe this may be related to atypical event knowledge. We are also looking at how higher-order language skills, such as making inferences, are related to event knowledge and autistic traits.

We believe that knowledge of common events is critical to all aspects of conceptual representations and language comprehension and production. We have recently published a neural network model of event knowledge and its interaction with language processing (Elman & McRae, 2019).

We have previously looked at how event knowledge has a role in people’s memory for the meaning of words, in their ability to understand sentences and discourse, and in false memories.

How do people understand concrete and abstract concepts?

People think about their future every day, and for that, they use information that comes from several sources and as well going through different processes. Understanding how people think about potential future events is an important component of human memory research.

We study how people simulate their futures based on their event knowledge, mental simulations, autobiographical memory, repetitive thoughts, executive functions, among others. These have been shown to influence the way that people simulate their future events. We are also interested in looking into the differences that emerge between spontaneously and deliberately thinking about the future. Moreover, we are curious to design novel approaches to study prospective cognition.

How do we understand time in laguange?

We understand the world as events unfolding over time. As such, we typically use language to describe events in the temporal order that they occur in the world. For example, if someone asked you what you did today, you may state that you went to school, then had dinner with your friends, then went home and watched TV before bed. However, we often use language in ways that manipulate the temporal order of events, leading to comprehension difficulties.

One way that we manipulate time in language is through words like before and after. Sentences beginning with before are intuitively difficult to understand since you need to mentally rearrange the order of events to match how they occurred in the real world (e.g., Before I had dinner with my friends, I went to school). The lab is currently studying whether providing individuals with contextual information prior to before-sentences makes them easier to read. This work will provide insight into how temporal mismatches are understood in natural language comprehension.

Another way that we manipulate time in language is through verb tense (i.e., past, present and future). Currently, the lab is studying whether we represent future events differently depending on if they are presented in future-imperfective tense (e.g., Chris will be picking up his friends at the airport) or future-perfective tense (e.g., Chris will have picked up his friends at the airport).