Theoretical strategies for an embodied cognitive neuroscience: Mechanistic explanations of brain-body-environment systems

Cognitive neuroscience seeks to explain mind, brain, and behavior. But how do we generate explanations? In this integrative theoretical paper, we review the commitments of the 'New Mechanist' movement within the philosophy of science, focusing specifically on the role of mechanistic models in scientific explanation. We highlight how this approach differs from other explanatory approaches within the field, showing its unique contributions to the efforts of scientific explanation. We then argue that the commitments of the Embodied Cognition framework converge with the commitments of the New Mechanist movement in a way that provides a necessary explanatory strategy available to cognitive neuroscience. We then discuss a number of consequences of this convergence, including issues related to the inadequacy of statistical prediction, neuroscientific reduction, the autonomy of psychology from neuroscience, and psychological and neuroscientific ontology. We hope that our integrative thesis provides researchers with a theoretical strategy for an embodied cognitive neuroscience.

Affordances for throwing: An uncontrolled manifold analysis

Movement systems are massively redundant, and there are always multiple movement solutions to any task demand; motor abundance. Movement consequently exhibits 'repetition without repetition', where movement outcomes are preserved but the kinematic details of the movement vary across repetitions. The uncontrolled manifold (UCM) concept is one of several methods that analyses movement variability with respect to task goals, to quantify repetition without repetition and test hypotheses about the control architecture producing a given abundant response to a task demand. However, like all these methods, UCM is under-constrained in how it decomposes a task and performance. In this paper, we propose and test a theoretical framework for constraining UCM analysis, specifically the perception of task-dynamical affordances. Participants threw tennis balls to hit a target set at 5m, 10m or 15m, and we performed UCM analysis on the shoulder-elbow-wrist joint angles with respect to variables derived from an affordance analysis of this task as well as more typical biomechanical variables. The affordance-based UCM analysis performed well, although data also showed thrower dynamics (effectivities) need to be accounted for as well. We discuss how the theoretical framework of affordances and affordance-based control can be connected to motor abundance methods in the future.

Reduced learning rates but successful learning of a coordinated rhythmic movement by older adults

Previous work has investigated the information-based mechanism for learning and transfer of learning in coordinated rhythmic movements. In those papers, we trained young adults to produce either 90° or 60° and showed in both cases that learning entailed learning to use relative position as information for the relative phase. This variable then supported transfer of learning to untrained coordinations +/30° on either side. In this article, we replicate the 90° study with younger adults and extend it by training older adults (aged between 55 and 65 years). Other work has revealed a steep decline in learning rate around this age, and no follow-up study has been able to successfully train older adults to perform a novel coordination. We used a more intensive training paradigm and showed that while older adult learning rates remain about half that of younger adults, given time they are able to acquire the new coordination. They also learn to use relative position, and consequently show the same pattern of transfer. We discuss implications for attempts to model the process of learning in this task.

Interactionally Embedded Gestalt Principles of Multimodal Human Communication

Natural human interaction requires us to produce and process many different signals, including speech, hand and head gestures, and facial expressions. These communicative signals, which occur in a variety of temporal relations with each other (e.g., parallel or temporally misaligned), must be rapidly processed as a coherent message by the receiver. In this contribution, we introduce the notion of interactionally embedded, affordance-driven gestalt perception as a framework that can explain how this rapid processing of multimodal signals is achieved as efficiently as it is. We discuss empirical evidence showing how basic principles of gestalt perception can explain some aspects of unimodal phenomena such as verbal language processing and visual scene perception but require additional features to explain multimodal human communication. We propose a framework in which high-level gestalt predictions are continuously updated by incoming sensory input, such as unfolding speech and visual signals. We outline the constituent processes that shape high-level gestalt perception and their role in perceiving relevance and prägnanz. Finally, we provide testable predictions that arise from this multimodal interactionally embedded gestalt-perception framework. This review and framework therefore provide a theoretically motivated account of how we may understand the highly complex, multimodal behaviors inherent in natural social interaction.

Integrating Philosophy of Understanding With the Cognitive Sciences

We provide two programmatic frameworks for integrating philosophical research on understanding with complementary work in computer science, psychology, and neuroscience. First, philosophical theories of understanding have consequences about how agents should reason if they are to understand that can then be evaluated empirically by their concordance with findings in scientific studies of reasoning. Second, these studies use a multitude of explanations, and a philosophical theory of understanding is well suited to integrating these explanations in illuminating ways.

Applications of cybernetics to psychological theory: Historical and conceptual explorations

This article outlines links between cybernetics and psychology through the black box metaphor using a tripartite narrative. The first part explores first-order cybernetic approaches to opening the black box. These developments run parallel to the decline of radical behaviorism and advancements in information processing theory and neuropsychology. We then describe how cybernetics migrates towards a second-order approach (expanding and questioning features of first-order inquiry), understanding applications of rule-based tools to sociocultural phenomena and dynamic mental models, inspiring radical constructivism, and also accepting social constructivism. Psychology, however, enters the cognitive revolution, adhering to the computer metaphor of first-order cyberneticians to streamline human consciousness. The article concludes by outlining how second-order cybernetic approaches emerging in the 1990s may provide cues to psychologists to adopt mixed methods, and bioecological models in the information age, uniting understandings of observable human activity, inner perceptions, and physiological processes across contexts to understand consciousness.

The Ecological Task Dynamics of Learning and Transfer in Coordinated Rhythmic Movement

Research spanning 100 years has revealed that learning a novel perception-action task is remarkably task-specific. With only a few exceptions, transfer is typically very small, even with seemingly small changes to the task. This fact has remained surprising given previous attempts to formalise the notion of what a task is, which have been dominated by common-sense divisions of tasks into parts. This article lays out an ecologically grounded alternative, ecological task dynamics, which provides us with tools to formally define tasks as experience from the first-person perspective of the learner. We explain this approach using data from a learning and transfer experiment using bimanual coordinated rhythmic movement as the task, and acquiring a novel coordination as the goal of learning. 10 participants were extensively trained to perform 60° mean relative phase; this learning transferred to 30° and 90°, against predictions derived from our previous work. We use recent developments in the formal model of the task to guide interpretation of the learning and transfer results.

Studying Behaviour Change Mechanisms under Complexity

Understanding the mechanisms underlying the effects of behaviour change interventions is vital for accumulating valid scientific evidence, and useful to informing practice and policy-making across multiple domains. Traditional approaches to such evaluations have applied study designs and statistical models, which implicitly assume that change is linear, constant and caused by independent influences on behaviour (such as behaviour change techniques). This article illustrates limitations of these standard tools, and considers the benefits of adopting a complex adaptive systems approach to behaviour change research. It (1) outlines the complexity of behaviours and behaviour change interventions; (2) introduces readers to some key features of complex systems and how these relate to human behaviour change; and (3) provides suggestions for how researchers can better account for implications of complexity in analysing change mechanisms. We focus on three common features of complex systems (i.e., interconnectedness, non-ergodicity and non-linearity), and introduce Recurrence Analysis, a method for non-linear time series analysis which is able to quantify complex dynamics. The supplemental website provides exemplifying code and data for practical analysis applications. The complex adaptive systems approach can complement traditional investigations by opening up novel avenues for understanding and theorising about the dynamics of behaviour change.

Zoom Out Camera! The Reflexive Character of an Enactive Account

The reflexive character of enactive theory is spelled out, in an effort to make explicit that which is usually implicit in debate: that we are responsible for the distinctions we draw, and that ultimately, the world that we collectively characterize is a joint production. Enaction, as treated here, is not a positivist scientific field, but an epistemologically self-conscious way to ground our understanding of the value-saturated lives of embodied beings. This stance is seen as entirely congruent with the scientific field of ecological psychology, which is itself then cast as a specific example of the kind of science that can be done in an enactive mode.

Perceptual information supports transfer of learning in coordinated rhythmic movement

In this paper, we trained people to produce 90° mean relative phase using task-appropriate feedback and investigated whether and how that learning transfers to other coordinations. Past work has failed to find transfer of learning to other relative phases, only to symmetry partners (identical coordinations with reversed lead–lag relationships) and to other effector combinations. However, that research has all trained people using transformed visual feedback (visual metronomes, Lissajous feedback) which removes the relative motion information typically used to produce various coordinations (relative direction, relative position; Wilson and Bingham, in Percept Psychophys 70(3):465–476, 2008). Coordination feedback (Wilson et al., in J Exp Psychol Hum Percept Perform 36(6):1508, 2010) preserves that information and we have recently shown that relative position supports transfer of learning between unimanual and bimanual performance of 90° (Snapp-Childs et al., in Exp Brain Res 233(7), 2225–2238, 2015). Here, we ask whether that information can support the production of other relative phases. We found large, asymmetric transfer of learning bimanual 90° to bimanual 60° and 120°, supported by perceptual learning of relative position information at 90°. For learning to transfer, the two tasks must overlap in some critical way; this is additional evidence that this overlap must be informational. We discuss the results in the context of an ecological, task dynamical approach to understanding the nature of perception–action tasks.

Mechanisms in psychology: The road towards unity?

The focus of this special issue of Theory & Psychology is on explanatory mechanisms in psychology, especially on problems of particular prominence for psychological science such as theoretical integration and unification. Proponents of the framework of mechanistic explanation claim, in short, that satisfactory explanations in psychology and related fields are causal. They stress the importance of explaining phenomena by describing mechanisms that are responsible for them, in particular by elucidating how the organization of component parts and operations in mechanisms gives rise to phenomena in certain conditions. We hope for cross-pollination between philosophical approaches to explanation and experimental psychology, which could offer methodological guidance, in particular where mechanism discovery and theoretical integration are at issue. Contributions in this issue pertain to theoretical integration and unification of psychology as well as the growing importance of causal mechanistic explanations in psychological science.