Neuroscience constrains psychology, but stating these constraints with precision is not simple. Here I consider whether mechanistic analysis provides a useful way to integrate models of cognitive and neural structure. Recent evidence suggests that cognitive systems map onto overlapping, distributed networks of brain regions. These highly entangled networks often depart from stereotypical mechanistic behaviors. While this casts doubt on the prospects for classical mechanistic integration of psychology and neuroscience, I argue that it does not impugn a realistic interpretation of either (...) type of model. Cognitive and neural models may depict different, but equally real, causal structures within the mind/brain. (shrink)

Neurosciences and cognitive sciences provide us with myriad empirical findings that shed light on hypothesised primitive numerical processes in the brain and in the mind. Yet, the hypotheses on which the experiments are based, and hence the results, depend strongly on sophisticated abstract models used to describe and explain neural data or cognitive representations that supposedly are the empirical roots of primary arithmetical activity. I will question the foundational role of such models. I will even cast doubt upon the search (...) for a general and unified philosophical foundation of an empirical science. First, it seems to me hard to draw a global and coherent view from the innumerable and piecemeal neuropsychological experiments and their variable, and sometimes uneasily compatible or fully divergent interpretations. Secondly, I think that the aim of empirical research is to describe dynamical processes, establishing correlations between different sets of data, without meaning to fix an origin or to point to a cause, let alone to a ground. From the very scientific and philosophical point of view it is essential to distinguish between explanations, which provide correlations or, at best, causal mechanisms, and grounding, which involves a claim to some form of determinism. (shrink)

Evolutionary psychology tends to be associated with a massively modular cognitive architecture. On this framework of human cognition, an assembly of specialized information processors called modules developed under selection pressures encountered throughout the phylogenic history of hominids. The coordinated activity of domain-specific modules carries out all the processes of belief fixation, abstract reasoning, and other facets of central cognition. Against the massive modularity thesis, I defend an account of systemic functional adaptedness, according to which non-modular systems emerged because of adaptive (...) problems imposed by the intrinsic physiology of the evolving human brain. The proposed reformulation of evolutionary theorizing draws from neural network models and Cummins’ (1975) account of systemic functions to identify selection pressures that gave rise to non-modular, domain-general mechanisms in cognitive architecture. (shrink)

How linguistic structures evolve so as to become easier to process is addressed by Isbilen and Christiansen for the Now‐or‐Never bottleneck. The authors suggest that this fundamental challenge in language processing is coped with by rapid compression of the transient linguistic input into chunks then to be passed on. As linguistic structures that can be chunked more easily tend to stabilize and proliferate, language evolves to fit learners’ cognitive capabilities.

Recent work on enculturation suggests that our cognitive capacities are significantly transformed in the course of the scaffolded acquisition of cognitive practices such as reading and writing. Phylogenetically, enculturation is the result of the co-evolution of human organisms and their socio-culturally structured cognitive niche. It is rendered possible by evolved cerebral and extra-cerebral bodily learning mechanisms that make human organisms apt to acquire culturally inherited cognitive practices. In addition, cultural learning allows for the intergenerational transmission of relevant knowledge and skills. (...) Ontogenetically, enculturation is associated with neural plasticity and the development of new motor routines and action schemas. It relies on scaffolded learning that structures novice-teacher interactions. The acquisition of reading and writing are paradigm examples of enculturation. Based on an empirically informed analysis of the components of enculturation, I will apply the emerging account of enculturated cognition to narrative practices. To date, research on the impact of narratives on the constitution of the self and our understanding of folk psychology has not paid much attention to the question how narratives are influenced by cumulative cultural evolution and our capacity to acquire reading and writing during ontogeny. I will argue that textual narratives, above and beyond oral narratives, provide genuinely new ways of narration. Therefore, the enculturated interaction with textual narratives has the potential to contribute to a better understanding of ourselves and other cognitive agents. (shrink)

Many of our cognitive capacities are the result of enculturation. Enculturation is the temporally extended transformative acquisition of cognitive practices in the cognitive niche. Cognitive practices are embodied and normatively constrained ways to interact with epistemic resources in the cognitive niche in order to complete a cognitive task. The emerging predictive processing perspective offers new functional principles and conceptual tools to account for the cerebral and extra-cerebral bodily components that give rise to cognitive practices. According to this emerging perspective, many (...) cases of perception, action, and cognition are realized by the on-going minimization of prediction error. Predictive processing provides us with a mechanistic perspective that helps investigate the functional details of the acquisition of cognitive practices. The argument of this paper is that research on enculturation and recent work on predictive processing are complementary. The main reason is that predictive processing operates at a sub-personal level and on a physiological time scale of explanation only. A complete account of enculturated cognition needs to take additional levels and temporal scales of explanation into account. This complementarity assumption leads to a new framework—enculturated predictive processing—that operates on multiple levels and temporal scales for the explanation of the enculturated predictive acquisition of cognitive practices. Enculturated predictive processing is committed to explanatory pluralism. That is, it subscribes to the idea that we need multiple perspectives and explanatory strategies to account for the complexity of enculturation. The upshot is that predictive processing needs to be complemented by additional considerations and conceptual tools to realize its full explanatory potential. (shrink)

In this paper, I summarize an emerging debate in the cognitive sciences over the right taxonomy for understanding cognition – the right theory of and vocabulary for describing the structure of the mind – and the proper role of neuroscientific evidence in specifying this taxonomy. In part because the discussion clearly entails a deep reconsideration of the supposed autonomy of psychology from neuroscience, this is a debate in which philosophers should be interested, with which they should be familiar, and to (...) which they should contribute. Here, I outline some of the positions being advocated, and reflect on some of the possible implications of this work both for scientific and folk psychology. (shrink)

Evolutionary Psychology (EP) tends to be associated with a Massively Modular (MM) cognitive architecture. I argue that EP favors a non-MM cognitive architecture. The main point of dispute is whether central cognition, such as abstract reasoning, exhibits domain-general properties. Partisans of EP argue that domain-specific modules govern central cognition, for it is unclear how the cognitive mind could have evolved domain-generality. In response, I defend a distinction between exogenous and endogenous selection pressures, according to which exogenous pressures tend to select (...) for domain-specificity, whereas the latter, endogenous pressures, select in favor of domain-generality. I draw on models from brain network theory to motivate this distinction, and also to establish that a domain-general, non-MM cognitive architecture is the more parsimonious adaptive solution to endogenous pressures. (shrink)

Decision-making has traditionally been modelled as a serial process, consisting of a number of distinct stages. The traditional account assumes that an agent first acquires the necessary perceptual evidence, by constructing a detailed inner repre- sentation of the environment, in order to deliberate over a set of possible options. Next, the agent considers her goals and beliefs, and subsequently commits to the best possible course of action. This process then repeats once the agent has learned from the consequences of her (...) actions and subsequently updated her beliefs. Under this interpretation, the agent’s body is considered merely as a means to report the decision, or to acquire the relevant goods. However, embodied cognition argues that an agent’s body should be understood as a proper part of the decision-making pro- cess. Accepting this principle challenges a number of commonly held beliefs in the cognitive sciences, but may lead to a more unified account of decision-making. This thesis explores an embodied account of decision-making using a recent frame- work known as predictive processing. This framework has been proposed by some as a functional description of neural activity. However, if it is approached from an embodied perspective, it can also offer a novel account of decision-making that ex- tends the scope of our explanatory considerations out beyond the brain and the body. We explore work in the cognitive sciences that supports this view, and argue that decision theory can benefit from adopting an embodied and predictive perspective. (shrink)