How the Human Brain Represents Perceived Dangerousness or “Predacity” of Animals

Abstract

Common or folk knowledge about animals is dominated by three dimensions: (1) level of cognitive complexity or "animacy;" (2) dangerousness or "predacity;" and (3) size. We investigated the neural basis of the perceived dangerousness or aggressiveness of animals, which we refer to more generally as "perception of threat." Using functional magnetic resonance imaging (fMRI), we analyzed neural activity evoked by viewing images of animal categories that spanned the dissociable semantic dimensions of threat and taxonomic class. The results reveal a distributed network for perception of threat extending along the right superior temporal sulcus. We compared neural representational spaces with target representational spaces based on behavioral judgments and a computational model of early vision and found a processing pathway in which perceived threat emerges as a dominant dimension: whereas visual features predominate in early visual cortex and taxonomy in lateral occipital and ventral temporal cortices, these dimensions fall away progressively from posterior to anterior temporal cortices, leaving threat as the dominant explanatory variable. Our results suggest that the perception of threat in the human brain is associated with neural structures that underlie perception and cognition of social actions and intentions, suggesting a broader role for these regions than has been thought previously, one that includes the perception of potential threat from agents independent of their biological class.

Using the Force: STEM Knowledge and Experience Construct Shared Neural Representations of Engineering Concepts

“…Additionally, within the ventral stream, more anterior informational networks more strongly reflect the learned categorical structure for both groups of participants. This anterior-to-posterior hierarchy is consistent with previous findings that highlight the increased conceptual and categorical knowledge represented in more anterior regions of the ventral visual stream (Connolly et al, 2016;Connolly & Haxby, 2012;Rugg & Thompson-Schill, 2013). Lastly, the observed dorsalto-ventral shift also echoes the concrete-to-abstract conceptual change described in the developmental learning literature (Bruner, 1973;Bruner, 1966;Fyfe, McNeil, Son, & Goldstone, 2014).…”

“…1B). Fitting the expert model of mechanical similarity into a DSM allows for a robust comparison of expert and novice representational spaces, across behavioral and neural responses and between mechanical and naïve models of similarity (Connolly et al, 2016;Kriegeskorte, 2008).…”

“…Here we test how conceptual change resulting from a STEM learning task about Newtonian force is represented in changes in neural activity patterns. This investigation is enabled by the use of a multivariate analysis approach that identifies similar neural representations across patterns of activity in disparate regions of the brain (i.e., informational networks; Connolly et al, 2016). Using these techniques, we investigated how cognitive and neural changes vary as a function of students' prior knowledge and experience.…”

“…In addition to assessing learning as reflected by behavioral ratings, representational similarity spaces are also used to model and assess neural representations using multivariate pattern analysis of brain activity (Connolly et al, 2016;Kriegeskorte, 2008;Kriegeskorte & Kievit, 2013). Thus, an additional advantage of using the card-sorting methodology is that it also allows for observation of the neural representations closely corresponding to the similarity spaces established during learning.…”

Theory of Mind: Towards an Evolutionary Theory

“…Several investigations have pointed to a possible relationship between ToM and threat perception. Connolly et al (2016), for example, showed that when evaluating the dangerousness or predaticity of various animals the human brain relies on an area called the superior temporal sulcus. As pointed out in the introduction, this area is centrally implicated in the control of both face recognition and mindreading.…”