" In Imagination and the Meaningful Brain, psychoanalyst Arnold Modell claims that subjective human experience must be included in any scientific...

ArgumentThis essay considers the metaphors of projection in Hugo Münsterberg's theory of cinema spectatorship. Münsterberg (1863–1916), a German born and educated professor of psychology at Harvard University, turned his attention to cinema only a few years before his untimely death at the age of fifty-three. But he brought to the new medium certain lasting preoccupations. This account begins with the contention that Münsterberg's intervention in the cinema discussion pursued his well-established strategy of pitting a laboratory model against a clinical (...) one, in this case the “master-trope” of early cinema a spectatorship drawn from hysteria, hypnosis, and related phenomena like double-consciousness. Münsterberg's laboratory-oriented account also flowed from his account of cinema technology as an outgrowth of the apparatus of his own discipline of experimental psycho-physiology, which entailed a model of cinema spectatorship continuous with the epistemological setting of laboratory relations. I argue that inThe Photoplayand related writings projection functioned in three registers: material, psychological, and philosophical. Münsterberg's primary concern was with psychological projection, where he drew upon his own work in experimental aesthetics to articulate an account of how the basic automatisms of cinema produce a state of oscillation between immersion and distraction. I show how Münsterberg's experimental aesthetics drew upon German doctrines of aesthetic empathy, orEinfühlung, which Münsterberg sought to modify in accordance with the dynamic and temporal characteristics of psycho-physiological experiment. Finally, I argue that Münsterberg's cinema theory was enfolded in his action or double-standpoint theory, in which the transcendental self posits the material, objective conditions of laboratory experience as a means to know itself. This philosophical projection explained cinema's uncanny ability to suspend ordinary perceptions of space, time, and causality. It also made cinema uniquely suited for the philosophical emancipation of a popular mass audience. (shrink)

The complexity of the human brain creates a spectrum of sophisticated behavioral repertoires, such as language, tool use, self-awareness, symbolic thought, cultural learning, and consciousness. Understanding how the human brain achieves that has been a longstanding challenge for neuroscientists and may bring insights into the evolution of human cognition and disease states. Human pluripotent stem cells could differentiate into specialized cell types and tissues in vitro. From this pluripotent state, it is possible to generate models of the human (...) brain, such as brain organoids. The recent observation that brain organoids can spontaneously develop complex neural network activity in a dish can help one understand how neural network oscillations evolve and vary between normal and disease states. Moreover, this finding can be leveraged to other applications outside medicine, including engineering and artificial intelligence. However, as the brain model technology becomes more complex, it raises a series of ethical and moral dilemmas. This article discusses the status of this technology, some of its current limitations, and a vision of the future. (shrink)

Is your mind the same thing as your brain, or are there aspects of mind beyond the brain's biology? This is the mind-body problem, and it has captivated curious minds since the dawn of human contemplation. Today many insist that the mind is completely reducible to the brain. But is that claim justified? In this stimulating anthology, twenty-five philosophers and scientists offer fresh insights into the mind-brain debate, drawing on psychology, neurology, philosophy, computer science, and neurosurgery. (...) Their provocative conclusion? The mind is indeed more than the brain. (shrink)

Innovative understanding or explanation stems almost exclusively from analogical reasoning. Induction systematizes the familiar; deduction casts it into formal relationship. Reasoning by analogy brings to bear on the familiar a new perspective derived from another realm of inquiry. Models are fruits from the tree of analogical knowledge.

This is an exciting time for brain science. Recent progress has been such that it now seems realistic to look toward an explanation of mind in terms of the brain's anatomy and physiology. Models based on artificially symmetrical arrays of idealized neurons are now being superseded by ones which properly take into account the brain's actual circuitry. This book presents a comprehensive overview of the current state of brain modeling, containing contributions from many leading researchers in (...) this field. It will be of interest not only to researchers in the fields of brain science and neurobiology, but also to psychologists and those involved in the study of artificial intelligence. (shrink)

Hilary Putnam’s BIV argument first occurred to him when ‘thinking about a theorem in modern logic, the “Skolem–Löwenheim Theorem”’ (Putnam 1981: 7). One of my aims in this paper is to explore the connection between the argument and the Theorem. But I also want to draw some further connections. In particular, I think that Putnam’s BIV argument provides us with an impressively versatile template for dealing with sceptical challenges. Indeed, this template allows us to unify some of Putnam’s most enduring (...) contributions to the realism/antirealism debate: his discussions of brains-in-vats, of Skolem’s Paradox, and of permutations. In all three cases, we have an argument which does not merely defeat the sceptic; it also shows us that we must reject some prima facie plausible philosophical picture. (shrink)

Computational neuroscientists not only employ computer models and simulations in studying brain functions. They also view the modeled nervous system itself as computing. What does it mean to say that the brain computes? And what is the utility of the ‘brain-as-computer’ assumption in studying brain functions? In previous work, I have argued that a structural conception of computation is not adequate to address these questions. Here I outline an alternative conception of computation, which I call the (...) analog-model. The term ‘analog-model’ does not mean continuous, non-discrete or non-digital. It means that the functional performance of the system simulates mathematical relations in some other system, between what is being represented. The brain-as-computer view is invoked to demonstrate that the internal cellular activity is appropriate for the pertinent information-processing task.Keywords: Computation; Computational neuroscience; Analog computers; Representation; Simulation. (shrink)

An underlying assumption in computational approaches in cognitive and brain sciences is that the nervous system is an input–output model of the world: Its input–output functions mirror certain relations in the target domains. I argue that the input–output modelling assumption plays distinct methodological and explanatory roles. Methodologically, input–output modelling serves to discover the computed function from environmental cues. Explanatorily, input–output modelling serves to account for the appropriateness of the computed function to the explanandum information-processing task. I compare very (...) briefly the modelling explanation to mechanistic and optimality explanations, noting that in both cases the explanations can be seen as complementary rather than contrastive or competing. (shrink)

In the context of this publication on blindsight, I want to address further the brain processes critically responsible for organizing our conscious experience. As in a previous related publication , I am restricting myself to brain and conscious experience, not the fuller topic of ‘consciousness’ as this might be determined by genetic and environmental factors, nor as it is defined in Eastern traditions and in esoteric Western religion and philosophy. For my thoughts on this broader topic the reader (...) is referred to a recent publication prepared for the centennial celebration of Norbert Wiener's birth. That paper is entitled: ‘What is Mind that the Brain May Order It? (shrink)

Visual narratives like comics involve a range of complex cognitive operations in order to be understood. The Parallel Interfacing Narrative‐Semantics (PINS) Model integrates an emerging literature showing that comprehension of wordless image sequences balances two representational levels of semantic and narrative structure. The neurocognitive mechanisms that guide these processes are argued to overlap with other domains, such as language and music.

The aim of cognitive neuropsychology is to articulate the functional architecture underlying normal cognition, on the basis of congnitive performance data involving brain-damaged subjects. Throughout the history of the subject, questions have been raised as to whether the methods of neuropsychology are adequate to its goals. The question has been reopened by Glymour [1994], who formulates a discovery problem for cognitive neuropsychology, in the sense of formal learning theory, concerning the existence of a reliable methodology. It appears that the (...) discovery problem may be insoluble in principle! I propose a modified formulation of Glymour's discovery problem and argue that a sceptical conclusion about the possiblity of cognitive neuropsychology as an empirical science is not warranted. (shrink)

People suffering from Obsessive-Compulsive Disorder (OCD) do things they do not want to do, and/or they think things they do not want to think. In about 10 percent of OCD patients, none of the available treatment options is effective. A small group of these patients is currently being treated with deep brain stimulation (DBS). Deep brain stimulation involves the implantation of electrodes in the brain. These electrodes give a continuous electrical pulse to the brain area in (...) which they are implanted. It turns out that patients may experience profound changes as a result of DBS treatment. It is not just the symptoms that change; patients rather seem to experience a different way of being in the world. These global effects are insufficiently captured by traditional psychiatric scales, which mainly consist of behavioural measures of the severity of the symptoms. In this article we aim to capture the changes in the patients’ phenomenology and make sense of the broad range of changes they report. For that we introduce an enactive, affordance-based model that fleshes out the dynamic interactions between person and world in four aspects. The first aspect is the patients’ experience of the world. We propose to specify the patients’ world in terms of a field of affordances, with the three dimensions of broadness of scope (‘width’ of the field), temporal horizon (‘depth’), and relevance of the perceived affordances (‘height’). The second aspect is the person-side of the interaction, that is, the patients’ self-experience, notably their moods and feelings. Thirdly, we point to the different characteristics of the way in which patients relate to the world. And lastly, the existential stance refers to the stance that patients take towards the changes they experience: the second-order evaluative relation to their interactions and themselves. With our model we intend to specify the notion of being in the world in order to do justice to the phenomenological effects of DBS treatment. (shrink)

Category theory has foundational importance because it provides conceptual lenses to characterize what is important and universal in mathematics—with adjunctions being the primary lens. If adjunctions are so important in mathematics, then perhaps they will isolate concepts of some importance in the empirical sciences. But the applications of adjunctions have been hampered by an overly restrictive formulation that avoids heteromorphisms or hets. By reformulating an adjunction using hets, it is split into two parts, a left and a right semiadjunction. Semiadjunctions (...) (essentially a formulation of universal mapping properties using hets) can then be combined in a new way to define the notion of a brain functor that provides an abstract model of the intentionality of perception and action (as opposed to the passive reception of sense-data or the reflex generation of behavior). (shrink)

The central idea is that the cerebral cortex is a model building machine, where regularities in the world serve as templates for the models it builds. First it is shown how this idea can be naturalized, and how the representational contents of our internal models depend upon the evolutionarily endowed design principles of our model building machine. Current neuroscience suggests a powerful form that these design principles may take, allowing our brains to uncover deep structures of the world (...) hidden behind surface sensory stimulation, the individuals, kinds, and properties that form the objects of human perception and thought. It is then shown how this account solves various problems that arose for previous attempts at naturalizing intentionality, and also how it supports rather than undermines folk psychology. As in the parable of the blind men and the elephant, the seemingly unrelated pieces of earlier theories (information, causation, isomorphism, success, and teleology) emerge as different aspects of the evolved model-building mechanism that explains the intentional features of our kind of mind. (shrink)

A simple exactly solvable model is given of the dynamical coupling between a person’s classically described perceptions and that person’s quantum mechanically described brain. The model is based jointly upon von Neumann’s theory of measurements and the empirical findings of close connections between conscious intentions and synchronous oscillations in well separated parts of the brain. A quantum-Zeno-effect-based mechanism is described that allows conscious intentions to influence brain activity in a functionally appropriate way. The robustness of (...) this mechanism in the face of environmental decoherence effects is emphasized. (shrink)

In this paper, I examined whether evidence from the neuroscience of morality supports the standard models of phronesis, i.e., Jubilee and Aretai Centre Models. The standard models explain phronesis as a multifaceted construct based on interaction and coordination among functional components. I reviewed recent neuroscience studies focusing on brain networks associated with morality and their connectivity to examine the validity of the models. Simultaneously, I discussed whether the evidence helps the models address challenges, particularly those from the phronesis eliminativism. (...) Neuroscientific evidence supported the importance of brain networks, i.e., the default mode, salience, and central executive functioning networks, in moral functioning in general. The findings favorably supported the multifaceted and integrative nature of phronesis proposed by the standard models. Finally, I considered how the two models could explain the mechanisms of phronesis more integratively based on neuroscientific findings. At the end of this paper, with the evidence, I proposed several practical ideas to promote the cultivation of phronesis, e.g., the consideration of coordination among components for moral functioning and the use of moral exemplars. (shrink)

Some dichotomies related to modeling electrocortical activities are analyzed. Attractor neural networks versus biologically motivated models, near-equilibrium versus nonequilibrium processes, linear and nonlinear dynamics, stochastic and chaotic patterns, local and global scale simulation of cortical activities are discussed.

Prediction Error Minimization theory (PEM) is one of the most promising attempts to model perception in current science of mind, and it has recently been advocated by some prominent philosophers as Andy Clark and Jakob Hohwy. Briefly, PEM maintains that “the brain is an organ that on aver-age and over time continually minimizes the error between the sensory input it predicts on the basis of its model of the world and the actual sensory input” (Hohwy 2014, p. (...) 2). An interesting debate has arisen with regard to which is the more adequate epistemological interpretation of PEM. Indeed, Hohwy maintains that given that PEM supports an inferential view of perception and cognition, PEM has to be considered as conveying an internalist epistemological perspective. Contrary to this view, Clark maintains that it would be incorrect to interpret in such a way the indirectness of the link between the world and our inner model of it, and that PEM may well be combined with an externalist epistemological perspective. The aim of this paper is to assess those two opposite interpretations of PEM. Moreover, it will be suggested that Hohwy’s position may be considerably strengthened by adopting Carlo Cellucci’s view on knowledge (2013). (shrink)

Recent models of psychopathology and psychotherapy highlight the importance of interpersonal factors. The current review offers a biological perspective on these interpersonal processes by examining inter-brain synchrony—the coupling of brain activity between people interacting with one another. High inter-brain synchrony is associated with better relationships in therapy and in daily life, while deficits in the ability to achieve inter-brain synchrony are associated with a variety of psychological and developmental disorders. The review suggests that therapy improves patients’ (...) ability to achieve such synchrony through inter-brain plasticity—a process by which recurring exposure to high inter-brain synchrony leads to lasting change in a person’s overall ability to synchronize. Therapeutic sessions provide repeated situations with high inter-brain synchrony. This can lead to a long-term increase in the ability to synchronize, first with the therapist, then generalized to other interpersonal relationships, ultimately leading to symptom reduction. The proposed inter-brain plasticity model offers a novel biological framework for understanding relational change in psychotherapy and its links to various forms of psychopathology and provides testable hypotheses for future research. Understanding this mechanism may help improve existing psychotherapy methods and develop new ones. (shrink)

Computational modeling of the brain holds great promise as a bridge from brain to behavior. To fulfill this promise, however, it is not enough for models to be 'biologically plausible': models must be structurally accurate. Here, we analyze what this entails for so-called psychobiological models, models that address behavior as well as brain function in some detail. Structural accuracy may be supported by (1) a model's a priori plausibility, which comes from a reliance on evidence-based assumptions, (...) (2) fitting existing data, and (3) the derivation of new predictions. All three sources of support require modelers to be explicit about the ontology of the model, and require the existence of data constraining the modeling. For situations in which such data are only sparsely available, we suggest a new approach. If several models are constructed that together form a hierarchy of models, higher-level models can be constrained by lower-level models, and low-level models can be constrained by behavioral features of the higher-level models. Modeling the same substrate at different levels of representation, as proposed here, thus has benefits that exceed the merits of each model in the hierarchy on its own. (shrink)

We build a topological model, based on intuitionistic logic, for multi-agent biological systems (such as _Physarum polycephalum_, bacterial colonies or any other swarm), reacting to external nourishment stimuli. Our construction follows the topological description of brain activity, where particles (neurons) are activated by an external environment, represented by a topological space _X_ with an open cover \(\{U_i:i\in I\}\). The brain builds the model of this external space via the nerve (trace) of a topological space _X_. Here (...) the body of _Physarum polycephalum_ or a swarm made of networks of tubular structures represents a nerve (trace) of _X_ also which means that _Physarum polycephalum_ or a swarm gains orientation in the space of external stimuli even in the absence of any neural system. The logic of living organisms is based on open subsets of _X_ and thus can be represented by Heyting algebra (i.e. intuitionistically). We also consider the generalisation of the nerve construction to a categorical context, where the category is determined by the network structures of multi-agent biological system. This model can be generalised up to simulating the behaviour of any swarm by means of intuitionistic logic. (shrink)

Brain Computer Interfaces (BCIs) enable one to control peripheral ICT and robotic devices by processing brain activity on-line. The potential usefulness of BCI systems, initially demonstrated in rehabilitation medicine, is now being explored in education, entertainment, intensive workflow monitoring, security, and training. Ethical issues arising in connection with these investigations are triaged taking into account technological imminence and pervasiveness of BCI technologies. By focussing on imminent technological developments, ethical reflection is informatively grounded into realistic protocols of brain-to-computer (...) communication. In particular, it is argued that human-machine adaptation and shared control distinctively shape autonomy and responsibility issues in current BCI interaction environments. Novel personhood issues are identified and analyzed too. These notably concern (i) the “sub-personal” use of human beings in BCI-enabled cooperative problem solving, and (ii) the pro-active protection of personal identity which BCI rehabilitation therapies may afford, in the light of so-called motor theories of thinking, for the benefit of patients affected by severe motor disabilities. (shrink)

Many of Grush's arguments should apply equally to animals with small brains, for which the capacity to internally model the body and environment must be limited. The dilemma may be solved by making only very approximate predictions, or only attempting to derive a “high-level” prediction from “high-level” output. At the extreme, in either case, the “emulation” step becomes trivial.

In order to make an attempt at grouping the various aspects of brain functional imaging (fMRI, MRS, EEG-MEG, ...) within a coherent frame, we implemented a model consisting of a system of differential equations, that includes: (1) sodium membrane transport, (2) Na/K ATPase, (3) neuronal energy metabolism (i.e. glycolysis, buffering effect of phosphocreatine, and mitochondrial respiration), (4) blood-brain barrier exchanges and (5) brain hemodynamics, all the processes which are involved in the activation of brain areas. (...) We assumed that the correlation between brain activation and metabolism could be due to either changes in the concentrations of ATP and ADP following activation of Na/K ATPase that result from the changes in ion concentrations, or the involvement, in different phases of metabolism, of a second messenger such as calcium. In this article, we show how this type of model enables interpretation of MRS and fMRI published data that were obtained during prolonged stimulations. (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)

The phenomenon of consciousness has always been a central question for philosophers and scientists. Emerging in the past decade are new approaches to the understanding of consciousness in a scientific light. This book presents a series of essays by leading thinkers giving an account of the current ideas prevalent in the scientific study of consciousness. The value of the book lies in the discussion of this interesting though complex subject from different points of view ranging from physics, computer science to (...) the cognitive sciences. Reviews of controversial ideas related to the philosophy of mind from western and eastern sources including classical Indian first person methodologies provide a breadth of coverage that has seldom been attempted in a book before. Additionally, chapters relating to the new approaches in computational modelling of higher order cognitive function and consciousness are included. The book is of great value for established as well as young researchers from a wide cross-section of interdisciplinary scientific backgrounds, aiming to pursue research in this field, as well as an informed public. * Presents the latest developments in the scientific study of consciousness * Critically reviews different theoretical and philosophical explanations related to the subject * An important book for both students and researchers in designing research projects on consciousness. (shrink)

Although neurological disease and mental illness can cause terrible human suffering, strategies for researching their causes and cures are not obvious. Invasive brain research on actual human being...

People become addicted in different ways, and they respond differently to different interventions. There may nevertheless be a core neural pathology responsible for all distinctively addictive suboptimal behavioral habits. In particular, timing models of reward learning suggest a hypothesis according to which all addiction involves neuroadaptation that attenuates serotonergic inhibition of a mesolimbic dopamine system that has learned that cues for consumption of the addictive target are signals of a high-reward-rate environment.

In this paper, I will introduce you to a new theory of mental representation, emphasizing two important features. First, the theory coheres very well with folk psychology; better, I believe, than its competitors (e.g. Cummins, 1996; Dretske, 1988; Fodor, 1987 and Millikan, 1989, with which it has the most in common), though I will do little by way of direct comparison in this paper. Second, it receives support from current neuroscience. While other theories may be consistent with current neuroscience, none (...) that I know of actually receives some degree of confirmation from it. There are many different kinds of representations. Some examples are maps, words, meter and gauge readings, diagrams, pictures, scale models, computer simulations, blueprints, charts, musical notation, smoke signals, semaphore, and computer data structures. Qua representations, they all possess intentionality, or aboutness: maps are about places, most words are about the entities they refer to, meters and gauges are about the quantities they measure, etc. However, it seems they have little in common beyond this aboutness (Millikan, 1984, p. 85). Therefore we should be open to the possibility that the aboutness of different representations is ultimately to be explained in different ways. It is becoming increasingly popular to understand the aboutness of a large class of these representations in terms of function.1 For example, a tire gauge represents one of the properties that it indicates or carries information about, namely air pressure. However, it also carries information about other quantities. If the pressure and volume of the tire are kept constant, the tire gauge will indicate the temperature of the air inside the tire, and if the temperature and pressure are kept constant, the gauge will indicate the tire volume. However, although the tire gauge indicates these things, it does not represent them. It only.. (shrink)

According to a growing trend in theoretical neuroscience, the human perceptual system is akin to a Bayesian machine. The aim of this article is to clearly articulate the claims that perception can be considered Bayesian inference and that the brain can be considered a Bayesian machine, some of the epistemological challenges to these claims; and some of the implications of these claims. We address two questions: (i) How are Bayesian models used in theoretical neuroscience? (ii) From the use of (...) Bayesian models in theoretical neuroscience, have we learned or can we hope to learn that perception is Bayesian inference or that the brain is a Bayesian machine? From actual practice in theoretical neuroscience, we argue for three claims. First, currently Bayesian models do not provide mechanistic explanations; instead they are useful devices for predicting and systematizing observational statements about people's performances in a variety of perceptual tasks. That is, currently we should have an instrumentalist attitude towards Bayesian models in neuroscience. Second, the inference typically drawn from Bayesian behavioural performance in a variety of perceptual tasks to underlying Bayesian mechanisms should be understood within the three-level framework laid out by David Marr ( [1982] ). Third, we can hope to learn that perception is Bayesian inference or that the brain is a Bayesian machine to the extent that Bayesian models will prove successful in yielding secure and informative predictions of both subjects' perceptual performance and features of the underlying neural mechanisms. (shrink)

Standard semantic information processing models—information in; information processed; information out —lend themselves to standard models of the functioning of the brain in terms, e.g., of threshold-switch neurons connected via classical synapses. That is, in terms of sophisticated descendants of McCulloch and Pitts models. I argue that both the cognition and the brain sides of this framework are incorrect: cognition and thought are not constituted as forms of semantic information processing, and the brain does not function in terms (...) of passive input processing units organized as neural nets. An alternative framework is developed that models cognition and thought not in terms of semantic information processing, and, correspondingly, models brain functional processes also not in terms of semantic information processing. As alternative to such models: I outline a pragmatist oriented, interaction based, model of representation; derive from this model a fundamental framework of constraints on how the brain must function; show that such a framework is in fact found in the brain, and develop the outlines of a broader model of how mental processes can be realized within this alternative framework. Part I of this discussion focuses on some criticisms of standard modeling frameworks for representation and cognition, and outlines an alternative interactivist, pragmatist oriented, model. In part II, the focus is on the fact that the brain does not, in fact, function in accordance with standard passive input processing models—e.g., information processing models. Instead, there are multiple endogenously active processes at multiple spatial and temporal scales across multiple kinds of cells. A micro-functional model that accounts for, and even predicts, these multi-scale phenomena in generating emergent representation and cognition is outlined. That is, I argue that the interactivist model of representation outlined offers constraints on how the brain should function that are in fact empirically found, and, in reverse, that the multifarious details of brain functioning entail the pragmatist representational model—a very strong interrelationship. In the sequel paper, starting with part III, this model is extended to address macro-functioning in the CNS. In part IV, I offer a discussion of an approach to brain functioning that has some similarities with, as well as differences from, the model presented here: sometimes called the predictive brain approach. (shrink)