Galatea, or the Future of Darwinism W Russell Brain Originally published in 1927 "A brilliant exposition…of the evolutionary hypothesis." The Guardian "Should prove invaluable…" Literary Guide This non-technical but closely-reasoned book is a challenge to the orthodox teaching on evolution known as Neo-Darwinism. The author claims that although Neo-Darwinian theories can possibly account for the evolution of forms, they are quite inadequate to explain the evolution of functions. 88pp ************** Daedalus or Science and the Future J B S Haldane (...) Originally published in 1924. "The essay is brilliant. Sparkling with wit and bristling with challenges." British Medical Journal "Predicts the most startling changes." Morning Post This volume examines the future of scientific research from religious, philosophical social and economic standpoints. 94pp Automaton, or the Future of Mechanical Man H Stafford Hatfield Originally published in 1928 "It is impossible to do justice to his volume in a brief review…"Daily Herald At the time of original publication mankind’s chief inventions had been extensions of his senses or limbs. This work prophesies the dawn of an era in which substitutes will gradually be found even for the human brain. 96pp Gallio or the Tyranny of Science J W N Sullivan Originally published in 1927 "So packed with ideas it is not possible to give any adequate résumé of its contents." Times Literary Supplement "Remarkable monograph…devastating summary of materialism…" Spectator An attack on the values which science is so successfully imposing upon civilization. 90pp. (shrink)

The development of predictive brain implant (PBI) technology that is able to forecast specific neuronal events and advise and/or automatically administer appropriate therapy for diseases of the brain raises a number of ethical issues. Provided that this technology satisfies basic safety and functionality conditions, one of the most pressing questions to address is its relation to the autonomy of patients. As Frederic Gilbert in his article asks, if autonomy implies a certain idea of freedom, or self-government, how (...) can an individual be considered to decide freely if the implanted device stands at the inception of the causal chain producing his decisions? He claims that PBIs threaten persons’ autonomy by diminishing their post-operative experience of self-control. In this commentary, I wish to discuss this claim. Contrary to Gilbert, I will suggest that PBIs do not pose a significant threat to patient’s autonomy, as self-control, but rather to his/her sense of authenticity. My claim is that the language of authenticity, already introduced in the recent bioethical literature, may offer a better way to voice some of the concerns with PBIs that Gilbert recognized. (shrink)

In this paper, I discuss the relationship between bodily experiences in dreams and the sleeping, physical body. I question the popular view that dreaming is a naturally and frequently occurring real-world example of cranial envatment. This view states that dreams are functionally disembodied states: in a majority of dreams, phenomenal experience, including the phenomenology of embodied selfhood, unfolds completely independently of external and peripheral stimuli and outward movement. I advance an alternative and more empirically plausible view of dreams as weakly (...) phenomenally-functionally embodied states. The view predicts that bodily experiences in dreams can be placed on a continuum with bodily illusions in wakefulness. It also acknowledges that there is a high degree of variation across dreams and different sleep stages in the degree of causal coupling between dream imagery, sensory input, and outward motor activity. Furthermore, I use the example of movement sensations in dreams and their relation to outward muscular activity to develop a predictive processing account. I propose that movement sensations in dreams are associated with a basic and developmentally early kind of bodily self-sampling. This account, which affords a central role to active inference, can then be broadened to explain other aspects of self- and world-simulation in dreams. Dreams are world-simulations centered on the self, and important aspects of both self- and world-simulation in dreams are closely linked to bodily self-sampling, including muscular activity, illusory own-body perception, and vestibular orienting in sleep. This is consistent with cognitive accounts of dream generation, in which long-term beliefs and expectations, as well as waking concerns and memories play an important role. What I add to this picture is an emphasis on the real-body basis of dream imagery. This offers a novel perspective on the formation of dream imagery and suggests new lines of research. (shrink)

Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing to (...) adaptive success. This target article critically examines this approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action. Sections 1 and 2 lay out the key elements and implications of the approach. Section 3 explores a variety of pitfalls and challenges, spanning the evidential, the methodological, and the more properly conceptual. The paper ends (sections 4 and 5) by asking how such approaches might impact our more general vision of mind, experience, and agency. (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)

A cognitivist account of decision-making views choice behaviour as a serial process of deliberation and commitment, which is separate from perception and action. By contrast, recent work in embodied decision-making has argued that this account is incompatible with emerging neurophysiological data. We argue that this account has significant overlap with an embodied account of predictive processing, and that both can offer mutual development for the other. However, more importantly, by demonstrating this close connection we uncover an alternative perspective on (...) the nature of decision-making, and the mechanisms that underlie our choice behaviour. This alternative perspective allows us to respond to a challenge for predictive processing, which claims that the satisfaction of distal goal-states is underspecified. Answering this challenge requires the adoption of an embodied perspective. (shrink)

During the lengthy and complex process of human evolution our ancestors had to adapt to extremely testing situations in which survival depended on making rapid choices that subjected muscles and the body as a whole to extreme tension. In order to seize a prey traveling at speeds that could reach 36 km per hour Homo sapiens had just thousandths of a second in which to anticipate the right moment and position himself before the prey arrived. He also had to prepare (...) the appropriate gesture, tensing his muscles and overcoming the resistance determined by body weight. While we are no longer faced with an environment that is anything so threatening, our brain continues to use these mechanisms day in day out to save time and energy, enabling us to avoid situations of danger, sense in advance the intentions of an interlocutor, and more besides. In this article we set out to show that our brain is not only a reactive mechanism, capable of reacting quickly to the stimuli that arrive from the external environment, but is above all a pro-active mechanism that allows us to make hypotheses, anticipate the consequences of actions, and formulate expectations: in short, to wrong foot an adversary. (shrink)

Biological brains are increasingly cast as ‘prediction machines’: evolved organs whose core operating principle is to learn about the world by trying to predict their own patterns of sensory stimulation. This, some argue, should lead us to embrace a brain-bound ‘neurocentric’ vision of the mind. The mind, such views suggest, consists entirely in the skull-bound activity of the predictive brain. In this paper I reject the inference from predictive brains to skull-bound minds. Predictive brains, I (...) hope to show, can be apt participants in larger cognitive circuits. The path is thus cleared for a new synthesis in which predictive brains act as entry-points for ‘extended minds’, and embodiment and action contribute constitutively to knowing contact with the world. (shrink)

Among the exciting prospects raised by advocates of predictive processing [PP] is the offer of a systematic description of our neural activity suitable for drawing explanatory bridges to the structure of conscious experience. Yet the gulf to cross seems wide. For, as critics of PP have argued, our visual experience certainly doesn’t seem probabilistic.While Clark proposes a means to make PP compatible with the experience of a determinate world, I argue that we should not rush to do so. Two (...) notions of determinacy are conflated in the claim that perception is determinate: ‘univocality’ and ‘full detail’. The former, as Clark argues, is only to be expected in any PP agent that models its world for the purpose of acting on it. But as Husserl argued, and as perceptual psychology has borne out, we significantly overestimate the degree of detail with which we perceive a univocal world.This second form of indeterminacy is due not to the probabilistic nature of PP’s model, but rather to its hierarchical structure, with increasingly coarse-grained representations as we move further from the sensory periphery. A PP system may, or may not, deliver a univocal hypothesis at each of these levels. An action-oriented PP system would only be expected to do so only at the level needed for successful action guidance. A naïve reporter’s overestimation of the degree of determinate detail in their visual experience can thereby be accounted for with a more gradual version of the ‘refrigerator light’ effect: we experience determinate details just to the degree that they’re needed – immediately as they’re needed. (shrink)

The proposal that probabilistic inference and unconscious hypothesis testing are central to information processing in the brain has been steadily gaining ground in cognitive neuroscience and associated fields. One popular version of this proposal is the new theoretical framework of predictive processing or prediction error minimization, which couples unconscious hypothesis testing with the idea of ‘active inference’ and claims to offer a unified account of perception and action. Here we will consider one outstanding issue that still looms large (...) at the core of the PEM framework: the lack of a clear criterion for distinguishing conscious states from unconscious ones. In order to fulfill the promise of becoming a unifying framework for describing and modeling cognition, PEM needs to be able to differentiate between conscious and unconscious mental states or processes. We will argue that one currently popular view, that the contents of conscious experience are determined by the ‘winning hypothesis’, falls short of fully accounting for conscious experience. It ignores the possibility that some states of a system can control that system’s behavior even though they are apparently not conscious. What follows from this is that the ‘winning hypothesis’ view does not provide a complete account of the difference between conscious and unconscious states in the probabilistic brain. We show how this problem for the received view can be resolved by augmenting PEM with Daniel Dennett’s multiple drafts model of consciousness. This move is warranted by the similar roles that attention and internal competition play in both the PEM framework and the multiple drafts model. (shrink)

What principles and mechanisms allow humans to encode complex 3D information, and how can it be so fast, so accurately and so flexibly transformed into coordinated action? How do these processes work when developed to the limit of human physiological and cognitive capacity—as they are in high-speed sports, such as alpine skiing or motor racing? High-speed sports present not only physical challenges, but present some of the biggest perceptual-cognitive demands for the brain. The skill of these elite athletes is (...) in many ways an attractive model for studying human performance “in the wild”, and its neurocognitive basis. This article presents a framework theory for how these abilities may be realized in high-speed sports. It draws on a careful analysis of the case of the motorsport athlete, as well as theoretical concepts from: (1) cognitive neuroscience of wayfinding, steering, and driving; (2) cognitive psychology of expertise; (3) cognitive modeling and machine learning; (4) human-in-the loop modellling in vehicle system dynamics and human performance engineering; (5) experimental research (in the laboratory and in the field) on human visual guidance. The distinctive contribution is the way these are integrated, and the concept ofchunkingis used in a novel way to analyze a high-speed sport. The mechanisms invoked are domain-general, and not specific to motorsport or the use of a particular type of vehicle (or any vehicle for that matter); theegocentric chunking hypothesisshould therefore apply to any dynamic task that requires similar core skills. It offers a framework for neuroscientists, psychologists, engineers, and computer scientists working in the field of expert sports performance, and may be useful in translating fundamental research into theory-based insight and recommendations for improving real-world elite performance. Specific experimental predictions and applicability of the hypotheses to other sports are discussed. (shrink)

In their scholarly target article, Gilead et al. explain how abstract mental representations and the predictive brain enable prospection and time-traveling. However, their exclusive focus on intrapsychic capacities misses an important point, namely, the degree to which mind and brain are tuned by the environment. This neglected aspect of adaptive cognition is discussed and illustrated from a cognitive-ecological perspective.

According to the free energy principle biological agents resist a tendency to disorder in their interactions with a dynamically changing environment by keeping themselves in sensory and physiological states that are expected given their embodiment and the niche they inhabit :127–138, 2010. doi: 10.1038/nrn2787). Why would a biological agent that aims at minimising uncertainty in its encounters with the world ever be motivated to seek out novelty? Novelty for such an agent would arrive in the form of sensory and physiological (...) states that are unexpected. Such an agent ought therefore to avoid novel and surprising interactions with the world one might think. Yet humans and many other animals find play and other forms of novelty-seeking and exploration hugely rewarding. How can this be understood in frameworks for studying the mind that emphasise prediction error minimisation? This problem has been taken up in recent research concerned with epistemic action—actions an agent engages in to reduce uncertainty. However that work leaves two questions unanswered, which it is the aim of our paper to address. First, no account has been given yet of why it should feel good to the agent to engage the world playfully and with curiosity. Second an appeal is made to precision-estimation to explain epistemic action, yet it remains unclear how precision-weighting works in action more generally, or active inference. We argue that an answer to both questions may lie in the bodily states of an agent that track the rate at which free energy is being reduced. The recent literature on the predictive brain has connected the valence of emotional experiences to the rate of change in the reduction of prediction error :e1003094, 2013. doi: 10.1371/journal.pcbi.1003094; Van de Cruys, in Metzinger and Wiese Philosophy and predictive processing, vol 24, MIND Group, Frankfurt am Main, 2017. doi: 10.15502/9783958573253). In this literature valenced emotional experiences are hypothesised to be identical with changes in the rate at which prediction error is reduced. Experiences are negatively valenced when overall prediction error increases and are positively valenced when the sum of prediction errors decrease. We offer an ecological-enactive interpretation of the concept of valence and its connection to rate of change of prediction error. We show how rate of change should be understood in terms of embodied states of affordance-related action readiness. We then go on to apply this ecological-enactive account of error dynamics to provide an answer to the first question we have raised: It may explain why it should feel good to an agent to be curious and playful. Our ecological-enactive account also allows us to show how error dynamics may provide an answer to the second question we have raised regarding how precision-weighting works in active inference. An agent that is sensitive to rates of error reduction can tune precision on the fly. We show how this ability to tune precision on the go can allow agents to develop skills for adapting better and better to the unexpected, and search out opportunities for resolving uncertainty and progressing in its learning. (shrink)

The rise of Bayesianism in cognitive science promises to shape the debate between nativists and empiricists into more productive forms—or so have claimed several philosophers and cognitive scientists. The present paper explicates this claim, distinguishing different ways of understanding it. After clarifying what is at stake in the controversy between nativists and empiricists, and what is involved in current Bayesian cognitive science, the paper argues that Bayesianism offers not a vindication of either nativism or empiricism, but one way to talk (...) precisely and transparently about the kinds of mechanisms and representations underlying the acquisition of psychological traits without a commitment to an innate language of thought. (shrink)

The rise of Bayesianism in cognitive science promises to shape the debate between nativists and empiricists into more productive forms—or so have claimed several philosophers and cognitive scientists. The present paper explicates this claim, distinguishing different ways of understanding it. After clarifying what is at stake in the controversy between nativists and empiricists, and what is involved in current Bayesian cognitive science, the paper argues that Bayesianism offers not a vindication of either nativism or empiricism, but one way to talk (...) precisely and transparently about the kinds of mechanisms and representations underlying the acquisition of psychological traits without a commitment to an innate language of thought. (shrink)

In recent years, scientists have increasingly taken to investigate the predictive nature of cognition. We argue that prediction relies on abstraction, and thus theories of predictive cognition need an explicit theory of abstract representation. We propose such a theory of the abstract representational capacities that allow humans to transcend the “here-and-now.” Consistent with the predictive cognition literature, we suggest that the representational substrates of the mind are built as ahierarchy, ranging from the concrete to the abstract; however, (...) we argue that there are qualitative differences between elements along this hierarchy, generating meaningful, often unacknowledged,diversity.Echoing views from philosophy, we suggest that the representational hierarchy can be parsed into:modality-specificrepresentations, instantiated on perceptual similarity;multimodalrepresentations, instantiated primarily on the discovery of spatiotemporal contiguity; andcategoricalrepresentations, instantiated primarily on social interaction. These elements serve as the building blocks ofcomplex structures discussed in cognitive psychology (e.g., episodes, scripts) and are the inputs for mental representations that behave like functions, typically discussed in linguistics (i.e.,predicators). We support our argument for representational diversity by explaining how the elements in our ontology are all required to account for humans’ predictive cognition (e.g., in subserving logic-based prediction; in optimizing the trade-off between accurate and detailed predictions) and by examining how the neuroscientific evidence coheres with our account. In doing so, we provide a testable model of the neural bases of conceptual cognition and highlight several important implications to research on self-projection, reinforcement learning, and predictive-processing models of psychopathology. (shrink)

Prediction draws on both simulation and theory. I ask how simulation is defined, and what the roles of simulation and theory are, respectively. Simulation is flexible in structure and resources. Often simulation and theory are combined in prediction. The function of simulation consists of representing a situation that is relevantly like the target situation with regards to the feature predicted.

Surprisal and Valuation in the Predictive Brain.

Joaquín M. Fuster is an eminent cognitive neuroscientist whose research over the last five decades has made fundamental contributions to our understanding of the neural structures underlying cognition and behaviour. This book provides his view on the eternal question of whether we have free will. Based on his seminal work on the functions of the prefrontal cortex in decision-making, planning, creativity, working memory, and language, Professor Fuster argues that the liberty or freedom to choose between alternatives is a function of (...) the cerebral cortex, under prefrontal control, in its reciprocal interaction with the environment. Freedom is therefore inseparable from that circular relationship. The Neuroscience of Freedom and Creativity is a fascinating inquiry into the cerebral foundation of our ability to choose between alternative actions and to freely lead creative plans to their goal. (shrink)

In their review, Ruba and Repacholi summarize the methods used to assess preverbal infants’ understanding of emotions, and analyze the existing evidence in light of classical and constructionist ac...

Recently, a number of neuroscientists and philosophers have taken the so-called predictive coding approach to support a form of radical neuro-representationalism, according to which the content of our conscious experiences is a neural construct, a brain-generated simulation. There is remarkable similarity between this account and ideas found in and developed by German neo-Kantians in the mid-nineteenth century. Some of the neo-Kantians eventually came to have doubts about the cogency and internal consistency of the representationalist framework they were operating (...) within. In this paper, I will first argue that some of these concerns ought to be taken seriously by contemporary proponents of predictive coding. After having done so, I will turn to phenomenology. As we shall see, Husserl’s endorsement of transcendental idealism was partially motivated by his rejection of representationalism and phenomenalism and by his attempt to safeguard the objectivity of the world of experience. This confronts us with an intriguing question. Which position is best able to accommodate our natural inclination for realism: Contemporary neuro-representationalism or Husserl’s transcendental idealism? (shrink)

Hyperscanning studies using functional Near-Infrared Spectroscopy have been performed to understand the neural mechanisms underlying human-human interactions. In this study, we propose a novel methodological approach that is developed for fNIRS multi-brain analysis. Our method uses support vector regression to predict one brain activity time series using another as the predictor. We applied the proposed methodology to explore the teacher-student interaction, which plays a critical role in the formal learning process. In an illustrative application, we collected fNIRS data (...) of the teacher and preschoolers’ dyads performing an interaction task. The teacher explained to the child how to add two numbers in the context of a game. The Prefrontal cortex and temporal-parietal junction of both teacher and student were recorded. A multivariate regression model was built for each channel in each dyad, with the student’s signal as the response variable and the teacher’s ones as the predictors. We compared the predictions of SVR with the conventional ordinary least square predictor. The results predicted by the SVR model were statistically significantly correlated with the actual test data at least one channel-pair for all dyads. Overall, 29/90 channel-pairs across the five dyads presented significant signal predictions withthe SVR approach. The conventional OLS resulted in only 4 out of 90 valid predictions. These results demonstrated that the SVR could be used to perform channel-wise predictions across individuals, and the teachers’ cortical activity can be used to predict the student brain hemodynamic response. (shrink)

The predictable rhythmic structure is important to most ecologically relevant sounds for humans, such as is found in the rhythm of speech or music. This study addressed the question of how rhythmic predictions are maintained in the auditory system when there are multiple perceptual interpretations occurring simultaneously and emanating from the same sound source. We recorded the electroencephalogram (EEG) while presenting participants with a tone sequence that had two different tone feature patterns, one based on the sequential rhythmic variation in (...) tone duration and the other on sequential rhythmic variation in tone intensity. Participants were presented with the same sound sequences and were instructed to listen for the intensity pattern (ignore fluctuations in duration) and press a response key to detected pattern deviants (attend intensity pattern task); to listen to the duration pattern (ignore fluctuations in intensity) and make a button press to duration pattern deviants (attend duration pattern task), and to watch a movie and ignore the sounds presented to their ears (attend visual task). Both intensity and duration patterns occurred predictably 85% of the time, thus the key question involved evaluating how the brain treated the irrelevant feature patterns (standards and deviants) while performing an auditory or visual task. We expected that task-based feature patterns would have a more robust brain response to attended standards and deviants than the unattended feature patterns. Instead, we found that the neural entrainment to the rhythm of the standard attended patterns had similar power to the standard of the unattended feature patterns. In addition, the infrequent pattern deviants elicited the event-related brain potential called the mismatch negativity component (MMN). The MMN elicited by task-based feature pattern deviants had a similar amplitude to MMNs elicited by unattended pattern deviants that were unattended because they were not the target pattern or because the participant ignored the sounds and watched a movie. Thus, these results demonstrate that the brain tracks multiple predictions about the complexities in sound streams and can automatically track and detect deviations with respect to these predictions. This capability would be useful for switching attention rapidly among multiple objects in a busy auditory scene. (shrink)

Performance on working memory (WM) tasks may partially be supported by long-term memory (LTM) processing. Hence, brain activation recently being implicated in WM may actually have been driven by (incidental) LTM formation. We examined which brain regions actually support successful WM processing, rather than being confounded by LTM processes, during the maintenance and probe phase of a WM task. We administered a four-pair (faces and houses) associative delayed-match-to-sample (WM) task using event-related fMRI and a subsequent associative recognition LTM (...) task, using the same stimuli. This enabled us to analyze subsequent memory effects for both the WM and the LTM test by contrasting correctly recognized pairs with incorrect pairs for either task. Critically, with respect to the subsequent WM effect, we computed this analysis exclusively for trials that were forgotten in the subsequent LTM recognition task. Hence, brain activity associated with successful WM processing was less likely to be confounded by incidental LTM formation. The subsequent LTM effect, in contrast, was analyzed exclusively for pairs that previously had been correctly recognized in the WM task, disclosing brain regions involved in successful LTM formation after successful WM processing. Results for the subsequent WM effect showed no significantly activated brain areas for WM maintenance, possibly due to an insensitivity of fMRI to mechanisms underlying active WM maintenance. In contrast, a correct decision at WM probe was linked to activation in the “retrieval success network” (anterior and posterior midline brain structures). The subsequent LTM analyses revealed greater activation in left dorsolateral prefrontal cortex and posterior parietal cortex in the early phase of the maintenance stage. No supra-threshold activation was found during the WM probe. Together, we obtained clearer insights in which brain regions support successful WM and LTM without the potential confound of the respective memory system. (shrink)

PurposeAlthough an increasing body of literature suggests a relationship between brain irradiation and deterioration of neurocognitive function, it remains as the standard therapeutic and prophylactic modality in patients with brain tumors. This review was aimed to abstract and evaluate the prediction models for radiation-induced neurocognitive decline in patients with primary or secondary brain tumors.MethodsMEDLINE was searched on October 31, 2021 for publications containing relevant truncation and MeSH terms related to “radiotherapy,” “brain,” “prediction model,” and “neurocognitive impairments.” (...) Risk of bias was assessed using the Prediction model Risk Of Bias ASsessment Tool.ResultsOf 3,580 studies reviewed, 23 prediction models were identified. Age, tumor location, education level, baseline neurocognitive score, and radiation dose to the hippocampus were the most common predictors in the models. The Hopkins verbal learning and the trail making tests were the most frequent outcome assessment tools. All studies used regression as machine learning method. All models were judged to have a high risk of bias mainly due to issues in the analysis.ConclusionExisting models have limited quality and are at high risk of bias. Following recommendations are outlined in this review to improve future models: developing cognitive assessment instruments taking into account the peculiar traits of the different brain tumors and radiation modalities; adherence to model development and validation guidelines; careful choice of candidate predictors according to the literature and domain expert consensus; and considering radiation dose to brain substructures as they can provide important information on specific neurocognitive impairments. (shrink)

Open peer commentary on the target article “How and Why the Brain Lays the Foundations for a Conscious Self” by Martin V. Butz. Excerpt: Surprisingly, the paper entirely neglects the issue of the dynamic properties of our environment. Focusing on (static, inanimate) objects only, it fails to acknowledge that anticipation becomes especially relevant when things around us change without being under our control: this is when we are forced to adapt quickly to new circumstances. To estimate as precisely as (...) necessary what will when be where is of vital meaning. Surprisingly though, this issue is not addressed at all. Although it is acknowledged that the environment contains dynamics that are to be predicted somehow (§3) and that have to be represented in the brain somehow (§28), concepts about and empirical data on the prediction of external events are not dealt with further. (shrink)

Brain age prediction is a relatively new tool in neuro-medicine and the neurosciences. In research and clinical practice, it finds multiple use as a marker for biological age, for general health status of the brain and as an indicator for several brain-based disorders. Its utility in all these tasks depends on detecting outliers and thus failing to correctly predict chronological age. The indicative value of brain age prediction is generated by the gap between a brain’s (...) chronological age and the predicted age, the brain age gap (BAG). This article shows how the clinical and research use of brain age prediction tacitly pathologizes the states that it is sensitive to. It will be argued that the tacit character of this transformation conceals the need for its explicit justification. (shrink)