Building better theories

Reasoning Goals and Representational Decisions in Computational Cognitive Neuroscience: Lessons From the Drift Diffusion Model

Computational cognitive models are powerful tools for enhancing the quantitative and theoretical rigor of cognitive neuroscience. It is thus imperative that model users-researchers who develop models, use existing models, or integrate model-based findings into their own research-understand how these tools work and what factors need to be considered when engaging with them. To this end, we developed a philosophical toolkit that addresses core questions about computational cognitive models in the brain and behavioral sciences. Drawing on recent advances in the philosophy of modeling, we highlight the central role of model users' reasoning goals in the application and interpretation of formal models. We demonstrate the utility of this perspective by first offering a philosophical introduction to the highly popular drift diffusion model (DDM) and then providing a novel conceptual analysis of a long-standing debate about decision thresholds in the DDM. Contrary to most existing work, we suggest that the two model structures implicated in the debate offer complementary-rather than competing-explanations of speeded choice behavior. Further, we show how the type of explanation provided by each form of the model (parsimonious and normative) reflects the reasoning goals of the communities of users who developed them (cognitive psychometricians and theoretical decision scientists, respectively). We conclude our analysis by offering readers a principled heuristic for deciding which of the models to use, thus concretely demonstrating the conceptual and practical utility of philosophy for resolving meta-scientific challenges in the brain and behavioral sciences.

Formalising the role of behaviour in neuroscience

We develop a mathematical approach to formally proving that certain neural computations and representations exist based on patterns observed in an organism's behaviour. To illustrate, we provide a simple set of conditions under which an ant's ability to determine how far it is from its nest would logically imply neural structures isomorphic to the natural numbers ℕ . We generalise these results to arbitrary behaviours and representations and show what mathematical characterisation of neural computation and representation is simplest while being maximally predictive of behaviour. We develop this framework in detail using a path integration example, where an organism's ability to search for its nest in the correct location implies representational structures isomorphic to two-dimensional coordinates under addition. We also study a system for processinga n b n strings common in comparative work. Our approach provides an objective way to determine what theory of a physical system is best, addressing a fundamental challenge in neuroscientific inference. These results motivate considering which neurobiological structures have the requisite formal structure and are otherwise physically plausible given relevant physical considerations such as generalisability, information density, thermodynamic stability and energetic cost.

Theories, models and frameworks to understand barriers to the provision of mobility-assistive technologies: a scoping review

OBJECTIVES

There is strong evidence that mobility-assistive technologies improve occupational performance, social participation, educational and employment access and overall quality of life in people with disabilities. However, people with disabilities still face barriers in accessing mobility products and related services. This review aims to summarise and synthesise: (1) theories, models and frameworks that have been used to understand mobility-assistive technology access, (2) determinants of access and (3) gaps in knowledge.

DESIGN

A scoping review using the five-step framework by Arksey and O'Malley.

DATA SOURCES

We searched the MEDLINE, EMBASE, Cumulative Index to Nursing and Allied Health Literature and SCOPUS databases for publications published between 2000 and 2024. We searched for articles published up to 20 March 2024.

ELIGIBILITY CRITERIA

We included English-published literature in peer-reviewed journals that reported (a) barriers to the provision of mobility-assistive technologies, (b) including at least one theory, model or framework and (c) between 2000 and 2024.

DATA EXTRACTION AND SYNTHESIS

We extracted the study characteristics, theories, models, framework usage, research recommendations, key findings on mobility-assistive technology barriers and theoretical propositions. We conduct a theoretical synthesis guided by Turner's approach.

RESULTS

We included 18 articles that used 8 theories, models and frameworks, synthesised into 9 propositions. The synthesised theory emphasises that mobility is essential for human flourishing, and that certain health conditions may impose restrictions on mobility. This impact can be alleviated by two direct determinants: (1) the provision of suitable services and (2) their comprehensive provision. Policies and costs influence these services indirectly. Environmental and personal factors also affect the use of these services. Ineffectively addressing these determinants can limit access to mobility-assistive technologies and subsequent disabilities.

CONCLUSION

Our synthetic model describes the logic of providing evidence-based mobility-assistive technologies, and we identify the determinants of access that can act as targets for future work to improve the provision of mobility-assistive technologies.

Rethinking Norm Psychology

Norms permeate human life. Most of people's activities can be characterized by rules about what is appropriate, allowed, required, or forbidden-rules that are crucial in making people hyper-cooperative animals. In this article, I examine the current cognitive-evolutionary account of "norm psychology" and propose an alternative that is better supported by evidence and better placed to promote interdisciplinary dialogue. The incumbent theory focuses on rules and claims that humans genetically inherit cognitive and motivational mechanisms specialized for processing these rules. The cultural-evolutionary alternative defines normativity in relation to behavior-compliance, enforcement, and commentary-and suggests that it depends on implicit and explicit processes. The implicit processes are genetically inherited and domain-general; rather than being specialized for normativity, they do many jobs in many species. The explicit processes are culturally inherited and domain-specific; they are constructed from mentalizing and reasoning by social interaction in childhood. The cultural-evolutionary, or "cognitive gadget," perspective suggests that people alive today-parents, educators, elders, politicians, lawyers-have more responsibility for sustaining normativity than the nativist view implies. People's actions not only shape and transmit the rules, but they also create in each new generation mental processes that can grasp the rules and put them into action.

Speech disturbances in schizophrenia: Assessing cross-linguistic generalizability of NLP automated measures of coherence

INTRODUCTION

Language disorders - disorganized and incoherent speech in particular - are distinctive features of schizophrenia. Natural language processing (NLP) offers automated measures of incoherent speech as promising markers for schizophrenia. However, the scientific and clinical impact of NLP markers depends on their generalizability across contexts, samples, and languages, which we systematically assessed in the present study relying on a large, novel, cross-linguistic corpus.

METHODS

We collected a Danish (DK), German (GE), and Chinese (CH) cross-linguistic dataset involving transcripts from 187 participants with schizophrenia (111DK, 25GE, 51CH) and 200 matched controls (129DK, 29GE, 42CH) performing the Animated Triangles Task. Fourteen previously published NLP coherence measures were calculated, and between-groups differences and association with symptoms were tested for cross-linguistic generalizability.

RESULTS

One coherence measure, i.e. second-order coherence, robustly generalized across samples and languages. We found several language-specific effects, some of which partially replicated previous findings (lower coherence in German and Chinese patients), while others did not (higher coherence in Danish patients). We found several associations between symptoms and measures of coherence, but the effects were generally inconsistent across languages and rating scales.

CONCLUSIONS

Using a cumulative approach, we have shown that NLP findings of reduced semantic coherence in schizophrenia have limited generalizability across different languages, samples, and measures. We argue that several factors such as sociodemographic and clinical heterogeneity, cross-linguistic variation, and the different NLP measures reflecting different clinical aspects may be responsible for this variability. Future studies should take this variability into account in order to develop effective clinical applications targeting different patient populations.

Exploring the internal forward model: action-effect prediction and attention in sensorimotor processing

Action-effect predictions are believed to facilitate movement based on its association with sensory objectives and suppress the neurophysiological response to self- versus externally generated stimuli (i.e. sensory attenuation). However, research is needed to explore theorized differences in the use of action-effect prediction based on whether movement is uncued (i.e. volitional) or in response to external cues (i.e. stimulus-driven). While much of the sensory attenuation literature has examined effects involving the auditory N1, evidence is also conflicted regarding this component's sensitivity to action-effect prediction. In this study (n = 64), we explored the influence of action-effect contingency on event-related potentials associated with visually cued and uncued movement, as well as resultant stimuli. Our findings replicate recent evidence demonstrating reduced N1 amplitude for tones produced by stimulus-driven movement. Despite influencing motor preparation, action-effect contingency was not found to affect N1 amplitudes. Instead, we explore electrophysiological markers suggesting that attentional mechanisms may suppress the neurophysiological response to sound produced by stimulus-driven movement. Our findings demonstrate lateralized parieto-occipital activity that coincides with the auditory N1, corresponds to a reduction in its amplitude, and is topographically consistent with documented effects of attentional suppression. These results provide new insights into sensorimotor coordination and potential mechanisms underlying sensory attenuation.

Cancelling cancellation? Sensorimotor control, agency, and prediction

For decades, classic theories of action control and action awareness have been built around the idea that the brain predictively 'cancels' expected action outcomes from perception. However, recent research casts doubt over this basic premise. What do these new findings mean for classic accounts of action? Should we now 'cancel' old data, theories and approaches generated under this idea? In this paper, we argue 'No'. While doubts about predictive cancellation may urge us to fundamentally rethink how predictions shape perception, the wider pyramid using these ideas to explain action control and agentic experiences can remain largely intact. Some adaptive functions assigned to predictive cancellation can be achieved through quasi-predictive processes, that influence perception without actively tracking the probabilistic structure of the environment. Other functions may rely upon truly predictive processes, but not require that these predictions cancel perception. Appreciating the role of these processes may help us to move forward in explaining how agents optimise their interactions with the external world, even if predictive cancellation is cancelled from theory.

New Approaches to 3D Vision

New approaches to 3D vision are enabling new advances in artificial intelligence and autonomous vehicles, a better understanding of how animals navigate the 3D world, and new insights into human perception in virtual and augmented reality. Whilst traditional approaches to 3D vision in computer vision (SLAM: simultaneous localization and mapping), animal navigation (cognitive maps), and human vision (optimal cue integration) start from the assumption that the aim of 3D vision is to provide an accurate 3D model of the world, the new approaches to 3D vision explored in this issue challenge this assumption. Instead, they investigate the possibility that computer vision, animal navigation, and human vision can rely on partial or distorted models or no model at all. This issue also highlights the implications for artificial intelligence, autonomous vehicles, human perception in virtual and augmented reality, and the treatment of visual disorders, all of which are explored by individual articles. This article is part of a discussion meeting issue 'New approaches to 3D vision'.