Theory of Mind: A Neural Prediction Problem

Predictive coding posits that neural systems make forward-looking predictions about incoming information. Neural signals contain information not about the currently perceived stimulus, but about the difference between the observed and the predicted stimulus. We propose to extend the predictive coding framework from high-level sensory processing to the more abstract domain of theory of mind; that is, to inferences about others’ goals, thoughts, and personalities. We review evidence that, across brain regions, neural responses to depictions of human behavior, from biological motion to trait descriptions, exhibit a key signature of predictive coding: reduced activity to predictable stimuli. We discuss how future experiments could distinguish predictive coding from alternative explanations of this response profile. This framework may provide an important new window on the neural computations underlying theory of mind

Theory of Mind: A Neural Prediction Problem

Predictive coding posits that neural systems make forward-looking predictions about incoming information. Neural signals contain information not about the currently perceived stimulus, but about the difference between the observed and the predicted stimulus. We propose to extend the predictive coding framework from high-level sensory processing to the more abstract domain of theory of mind; that is, to inferences about others' goals, thoughts, and personalities. We review evidence that, across brain regions, neural responses to depictions of human behavior, from biological motion to trait descriptions, exhibit a key signature of predictive coding: reduced activity to predictable stimuli. We discuss how future experiments could distinguish predictive coding from alternative explanations of this response profile. This framework may provide an important new window on the neural computations underlying theory of mind.National Science Foundation (U.S.) (Award 0645960)National Science Foundation (U.S.) (Award 095518)National Institutes of Health (U.S.) (Grant 1R01 MH096914-01A1

Quantification and ACD: Evidence from Real-Time Sentence Processing

Data files and documentation available at http://hdl.handle.net/1721.1/76676Quantifiers, unlike proper names or definite descriptions, cannot be given the semantics of referring expressions. This fact has triggered a long standing debate in formal semantics and syntax as to the combinatorial means by which quantifiers are integrated into a sentence. The present paper contributes to this debate through an investigation of quantifier comprehension during real-time sentence processing. We present evidence showing that two potentially independent processes—the integration of a quantifier in object position and the resolution of antecedent-contained deletion (ACD)—are linked. Our data show, more specifically, that the resolution of a downstream ACD site is facilitated during real-time sentence processing if the upstream DP hosting the ACD site is quantificational but not if it is definite. We discuss these findings in the context of a QUANTIFIER RAISING based approach and a type-shifting-based approach to quantifier integration. We argue that facilitation of ACD resolution by an upstream quantifier is only expected by theories, such as the QUANTIFIER RAISING approach, which employ the same mechanism for both processes. We then compare the QUANTIFIER RAISING-based account with a non-grammatical experience-based approach to our data, which attempts to explain the findings in terms of corpus frequencies. Although we cannot rule out such an alternative at this stage, we offer reasons to believe that an account that exploits QUANTIFIER RAISING has an explanatory advantage

Thinking about seeing: Perceptual sources of knowledge are encoded in the theory of mind brain regions of sighted and blind adults

Blind people's inferences about how other people see provide a window into fundamental questions about the human capacity to think about one another's thoughts. By working with blind individuals, we can ask both what kinds of representations people form about others' minds, and how much these representations depend on the observer having had similar mental states themselves. Thinking about others' mental states depends on a specific group of brain regions, including the right temporo-parietal junction (RTPJ). We investigated the representations of others' mental states in these brain regions, using multivoxel pattern analyses (MVPA). We found that, first, in the RTPJ of sighted adults, the pattern of neural response distinguished the source of the mental state (did the protagonist see or hear something?) but not the valence (did the protagonist feel good or bad?). Second, these neural representations were preserved in congenitally blind adults. These results suggest that the temporo-parietal junction contains explicit, abstract representations of features of others' mental states, including the perceptual source. The persistence of these representations in congenitally blind adults, who have no first-person experience with sight, provides evidence that these representations emerge even in the absence of relevant first-person perceptual experiences.National Science Foundation (U.S.) (Award 0645960)National Science Foundation (U.S.) (Award 095518)National Institutes of Health (U.S.) (Grant 1R01 MH096914-01A1

Localizing Pain Matrix and Theory of Mind networks with both verbal and non-verbal stimuli

Functional localizer tasks allow researchers to identify brain regions in each individual's brain, using a combination of anatomical and functional constraints. In this study, we compare three social cognitive localizer tasks, designed to efficiently identify regions in the "Pain Matrix," recruited in response to a person's physical pain, and the "Theory of Mind network," recruited in response to a person's mental states (i.e. beliefs and emotions). Participants performed three tasks: first, the verbal false-belief stories task; second, a verbal task including stories describing physical pain versus emotional suffering; and third, passively viewing a non-verbal animated movie, which included segments depicting physical pain and beliefs and emotions. All three localizers were efficient in identifying replicable, stable networks in individual subjects. The consistency across tasks makes all three tasks viable localizers. Nevertheless, there were small reliable differences in the location of the regions and the pattern of activity within regions, hinting at more specific representations. The new localizers go beyond those currently available: first, they simultaneously identify two functional networks with no additional scan time, and second, the non-verbal task extends the populations in whom functional localizers can be applied. These localizers will be made publicly available.National Institutes of Health (U.S.) (Grant 1R01 MH096914-01A1

Mentalizing regions represent distributed, continuous, and abstract dimensions of others' beliefs

The human capacity to reason about others' minds includes making causal inferences about intentions, beliefs, values, and goals. Previous fMRI research has suggested that a network of brain regions, including bilateral temporo-parietal junction (TPJ), superior temporal sulcus (STS), and medial prefrontal-cortex (MPFC), are reliably recruited for mental state reasoning. Here, in two fMRI experiments, we investigate the representational content of these regions. Building on existing computational and neural evidence, we hypothesized that social brain regions contain at least two functionally and spatially distinct components: one that represents information related to others' motivations and values, and another that represents information about others' beliefs and knowledge. Using multi-voxel pattern analysis, we find evidence that motivational versus epistemic features are independently represented by theory of mind (ToM) regions: RTPJ contains information about the justification of the belief, bilateral TPJ represents the modality of the source of knowledge, and VMPFC represents the valence of the resulting emotion. These representations are found only in regions implicated in social cognition and predict behavioral responses at the level of single items. We argue that cortical regions implicated in mental state inference contain complementary, but distinct, representations of epistemic and motivational features of others' beliefs, and that, mirroring the processes observed in sensory systems, social stimuli are represented in distinct and distributed formats across the human brain. Keywords: Theory of mind; fMRI; Multi-voxel pattern analysis (MVPA)NSF Graduate Research Fellowships (Grant 0645960)NSF Graduate Research Fellowships (Grant 1122374)NSF CAREER award (Grant 095518)National Institutes of Health (Grant 1R01 MH096914-01A1)Packard Foundation (Grant 2008-333024

Thinking in patterns : representations in the neural basis of theory of mind

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2014.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 151-179).Social life depends on understanding other people's behavior: why they do the things they do, and what they are likely to do next. These actions are just observable consequences of an unobservable, internal causal structure: the person's intentions, beliefs, and goals. A cornerstone of the human capacity for social cognition is the ability to reason about these invisible causes; having a "theory of mind". A remarkable body of evidence has demonstrated that social cognition reliably and selectively recruits a specific group of brain regions. Yet, we have little insight into how these neural substrates function at a computational level. This thesis lays the groundwork to address that question, both empirically and theoretically, first by demonstrating that functional neuroimaging can find behaviorally relevant features of mental state representation within the cortical regions that support social cognition, and second by proposing a theoretical framework to interpret activity in these brain regions. In Chapter 1, I review the literature of the last 15 years, and argue that a key next step in understanding the neural basis of social cognition is characterizing the neural representations and computations supported by "social" brain regions. In Chapter 2, I demonstrate in four experiments that functional neuroimaging can be used to find neural representations of distinct features of mental states. Specifically, I show that multivoxel pattern analysis (MVPA) can detect features of mental state representations (e.g., intent), and that these neural patterns are behaviorally relevant, including in autism spectrum disorders. In Chapter 3, I demonstrate that these brain regions contain explicit, abstract representations of another feature of others' mental states: perceptual source. I find that these representations persist in the face of drastic changes in developmental history (congenital blindness), providing evidence that these representations emerge even in the absence of relevant first-person experience. In Chapter 4, I demonstrate that these cortical regions contain representations of epistemic and emotional features of others' beliefs, and that these features are represented along continuous, abstract dimensions. Finally, in Chapter 5, I extend a model from vision and neuroeconomics - predictive coding - and explore its application to the neural basis of social cognition. Together, this work provides a key next step to understanding the neural basis of theory of mind, by demonstrating that it is possible to find abstract, behaviorally relevant features of mental state inferences inside cortical regions that support social cognition, and taking a first step in characterizing their content and format.by Jorie Koster-Hale.Ph. D

Theory of Mind brain regions are sensitive to the content, not the structural complexity, of belief attributions

A distinct group of brain regions, the ‘Theory of Mind (ToM) network’, is implicated in representing other people’s mental states, yet we currently know little about which aspects of mental state attribution are represented or processed in these regions. Using fMRI, we investigated whether ToM regions, compared to language-processing regions, are sensitive to two dimensions along which mental state attributions vary: (1) structural complexity and (2) social content of the attributed thought. In short vignettes describing a character's belief, the belief structure was either first-order or higher-order, and the content was mundane or socially-relevant. All ToM regions showed sensitivity to distinctions in content; no ToM region showed sensitivity to structural manipulation. By contrast, language regions were sensitive to both manipulations. We conclude that while increased structural complexity of belief attributions modulates language processing, this type of complexity is not part of the representational space of the ToM-network

Decoding moral judgments from neural representations of intentions

Intentional harms are typically judged to be morally worse than accidental harms. Distinguishing between intentional harms and accidents depends on the capacity for mental state reasoning (i.e., reasoning about beliefs and intentions), which is supported by a group of brain regions including the right temporo-parietal junction (RTPJ). Prior research has found that interfering with activity in RTPJ can impair mental state reasoning for moral judgment and that high-functioning individuals with autism spectrum disorders make moral judgments based less on intent information than neurotypical participants. Three experiments, using multivoxel pattern analysis, find that (i) in neurotypical adults, the RTPJ shows reliable and distinct spatial patterns of responses across voxels for intentional vs. accidental harms, and (ii) individual differences in this neural pattern predict differences in participants’ moral judgments. These effects are specific to RTPJ. By contrast, (iii) this distinction was absent in adults with autism spectrum disorders. We conclude that multivoxel pattern analysis can detect features of mental state representations (e.g., intent), and that the corresponding neural patterns are behaviorally and clinically relevant.National Institutes of Health (U.S.) (Grant 1R01 MH096914-01A1)Simons FoundationNational Science Foundation (U.S.) (Grant 095518)John Merck Scholars Program (Grant)Charles A. Dana FoundationNational Science Foundation (U.S.). Graduate Research Fellowship Program (Grant 0645960