An approach to emotion is described in which emotions are defined as states elicited by instrumental reinforcers, that is, by stimuli that are the goals for action. This leads to a theory of the evolutionary adaptive value of emotions, which is that different genes specify different goals in their own self-interest, and any actions can then be learned and performed by instrumental learning to obtain the goals. The brain mechanisms for emotion in brain regions such as the orbitofrontal and anterior (...) cingulate cortex provide a foundation for understanding the neural basis of emotion. Classically conditioned effects may modulate the actions initiated by this system. In addition to this instrumental learning system, some stimuli may elicit responses, for example approach, withdrawal, or fixed action patterns, but intervening states are not required for this type of adaptive response. In addition, a rational thought system involved in multistep planning can allow gene-specified goals to be deferred or avoided in order to achieve longer-term types of goals that may be more advantageous to the individual than to the genes. (shrink)

The relation between mental states and brain states is important in computational neuroscience, and in psychiatry in which interventions with medication are made on brain states to alter mental states. The relation between the brain and the mind has puzzled philosophers for centuries. Here a neuroscience approach is proposed in which events at the sub-neuronal, neuronal, and neuronal network levels take place simultaneously to perform a computation that can be described at a high level as a mental state, with content (...) about the world. It is argued that as the processes at the different levels of explanation take place at the same time, they are linked by a non-causal supervenient relationship: causality can best be described in brains as operating within but not between levels. This allows the supervenient properties to be emergent, though once understood at the mechanistic levels they may seem less emergent, and expected. This mind-brain theory allows mental events to be different in kind from the mechanistic events that underlie them; but does not lead one to argue that mental events cause brain events, or vice versa: they are different levels of explanation of the operation of the computational system. This approach may provide a way of thinking about brains and minds that is different from dualism and from reductive physicalism, and which is rooted in the computational processes that are fundamental to understanding brain and mental events, and that mean that the mental and mechanistic levels are linked by the computational process being performed. Explanations at the different levels of operation may be useful in different ways. For example, if we wish to understand how arithmetic is performed in the brain, description at the mental level of the algorithm being computed will be useful. But if the brain operates to result in mental disorders, then understanding the mechanism at the neural processing level may be more useful, in for example, the treatment of psychiatric disorders. (shrink)

The relation between mental states and brain states is important in computational neuroscience, and in psychiatry in which interventions with medication are made on brain states to alter mental states. The relation between the brain and the mind has puzzled philosophers for centuries. Here a neuroscience approach is proposed in which events at the sub-neuronal, neuronal, and neuronal network levels take place simultaneously to perform a computation that can be described at a high level as a mental state, with content (...) about the world. It is argued that as the processes at the different levels of explanation take place at the same time, they are linked by a non-causal supervenient relationship: causality can best be described in brains as operating within but not between levels. This allows the supervenient (e.g., mental) properties to be emergent, though once understood at the mechanistic levels they may seem less emergent, and expected. This mind-brain theory allows mental events to be different in kind from the mechanistic events that underlie them; but does not lead one to argue that mental events cause brain events, or vice versa: they are different levels of explanation of the operation of the computational system. This approach may provide a way of thinking about brains and minds that is different from dualism and from reductive physicalism, and which is rooted in the computational processes that are fundamental to understanding brain and mental events, and that mean that the mental and mechanistic levels are linked by the computational process being performed. Explanations at the different levels of operation may be useful in different ways. For example, if we wish to understand how arithmetic is performed in the brain, description at the mental level of the algorithm being computed will be useful. But if the brain operates to result in mental disorders, then understanding the mechanism at the neural processing level may be more useful, in for example, the treatment of psychiatric disorders. (shrink)

Twenty-five years after his death, critics and academics, film-makers and journalists continue to argue over Sartre's legacy. But certain interpretations have congealed around his iconic text _Nausea_, tending to confine it within the framework provided by the later philosophical work, _Being and Nothingness_. This volume opens up the text to a range of new approaches within the fields of English and Comparative Literature, as well as Philosophy and French Studies, under the headings: ‘Text’, ‘Context’, and ‘Intertext’: the textual strategies at (...) work within the novel; the literary, cultural and philosophical context of its production; and the intertextual web within which it is situated. This volume will interest a wide public of teachers, students and all those who want to reconsider Sartre’s legacy in the twenty–first century. (shrink)

What produces emotions? Why do we have emotions? How do we have emotions? Why do emotional states feel like something? This book considers these questions, going beyond examining brain mechanisms of emotion, by proposing a theory of what emotions are, and an evolutionary, Darwinian, theory of the adaptive value of emotion.

The study of the autonomic nervous system (ANS) function has shown to provide useful indicators for risk stratification and early detection on a variety of cardiovascular pathologies. However, data gathered during different tests of the ANS are difficult to analyse, mainly due to the complex mechanisms involved in the autonomic regulation of the cardiovascular system (CVS). Although model-based analysis of ANS data has been already proposed as a way to cope with this complexity, only a few models coupling the main (...) elements involved have been presented in the literature. In this paper, a new model of the CVS, representing the ventricles, the circulatory system and the regulation of the CVS activity by the ANS, is presented. The models of the vascular system and the ventricular activity have been developed using the Bond Graph formalism, as it proposes a unified representation for all energetic domains, facilitating the integration of mechanic and hydraulic phenomena. In order to take into account the electro-mechanical behaviour of both ventricles, an electrophysiologic model of the cardiac action potential, represented by a set of ordinary differential equations, has been integrated. The short-term ANS regulation of heart rate, cardiac contractility and peripheral vasoconstriction is represented by means of continuous transfer functions. These models, represented in different continuous formalisms, are coupled by using a multi-formalism simulation library. Results are presented for two different autonomic tests, namely the Tilt Test and the Valsalva Manoeuvre, by comparing real and simulated signals. (shrink)

In this paper, a mathematical model of the respiratory mechanics is used to reproduce experimental signal waveforms acquired from three newborn lambs. As the main challenge is to determine specific lamb parameters, a sensitivity analysis has been realized to find the most influent parameters, which are identified using an evolutionary algorithm. Results show a close match between experimental and simulated pressure and flow waveforms obtained during spontaneous ventilation and pleural pressure variations acquired during the application of positive pressure, since root (...) mean square errors equal to 0.0119, 0.0052 and 0.0094. The identified parameters were discussed in light of previous knowledge of respiratory mechanics in the newborn. (shrink)

The topics treated in The brain and emotion include the definition, nature, and functions of emotion (Ch. 3); the neural bases of emotion (Ch. 4); reward, punishment, and emotion in brain design (Ch. 10); a theory of consciousness and its application to understanding emotion and pleasure (Ch. 9); and neural networks and emotion-related learning (Appendix). The approach is that emotions can be considered as states elicited by reinforcers (rewards and punishers). This approach helps with understanding the functions of emotion, with (...) classifying different emotions, and in understanding what information-processing systems in the brain are involved in emotion, and how they are involved. The hypothesis is developed that brains are designed around reward-and punishment-evaluation systems, because this is the way that genes can build a complex system that will produce appropriate but flexible behavior to increase fitness (Ch. 10). By specifying goals rather than particular behavioral patterns of responses, genes leave much more open the possible behavioral strategies that might be required to increase fitness. The importance of reward and punishment systems in brain design also provides a basis for understanding the brain mechanisms of motivation, as described in Chapters 2 for appetite and feeding, 5 for brain-stimulation reward, 6 for addiction, 7 for thirst, and 8 for sexual behavior. Key Words: amygdala; brain evolution; consciousness; dopamine; emotion; hunger; orbitofrontal cortex; punishment; reward; taste. (shrink)

Memory, attention, and decision-making are three major areas of psychology. They are frequently studied in isolation, and using a range of models to understand them. This book brings a unified approach to understanding these three processes. It shows how these fundamental functions for cognitive neuroscience can be understood in a common and unifying computational neuroscience framework. This framework links empirical research on brain function from neurophysiology, functional neuroimaging, and the effects of brain damage, to a description of how neural networks (...) in the brain implement these functions using a set of common principles. The book describes the principles of operation of these networks, and how they could implement such important functions as memory, attention, and decision-making.The topics covered includeThe hippocampus and memoryReward and punishment related learning: emotion and motivationVisual object recognition learningShort term memoryAttention, short term memory, and biased competitionProbabilistic decision-makingAction selectionDecision-makingAlso included are tutorial appendices onNeural networks in the brainNeural encoding in the brain'Memory, Attention and Decision-Making' will be valuable for those in the fields of neuroscience, psychology, and cognitive neuroscience from advanced undergraduate level upwards. It will also be of interest to those interested in neuroeconomics, animal behaviour, zoology, evolutionary biology, psychiatry, medicine, and philosophy. The book has been written with modular chapters and sections, making it possible to select particular Chapters for course work. (shrink)

The ventricular pressure profile is characteristic of the cardiac contraction progress and is useful to evaluate the cardiac performance. In this contribution, a tissue-level electromechanical model of the left ventricle is proposed, to assist the interpretation of left ventricular pressure waveforms. The left ventricle has been modeled as an ellipsoid composed of twelve mechano-hydraulic sub-systems. The asynchronous contraction of these twelve myocardial segments has been represented in order to reproduce a realistic pressure profiles. To take into account the different energy (...) domains involved, the tissue-level scale and to facilitate the building of a modular model, multiple formalisms have been used: Bond Graph formalism for the mechano-hydraulic aspects and cellular automata for the electrical activation. An experimental protocol has been defined to acquire ventricular pressure signals from three pigs, with different afterload conditions. Evolutionary Algorithms have been used to identify the model parameters in order to minimize the error between experimental and simulated ventricular pressure signals. Simulation results show that the model is able to reproduce experimental ventricular pressure. In addition, electro-mechanical activation times have been determined in the identification process. For example, the maximum electrical activation time is reached, respectively, 96.5, 139.3 and 131.5 ms for the first, second, and third pigs. These preliminary results are encouraging for the application of the model on non-invasive data like ECG, arterial pressure or myocardial strain. (shrink)

The objective of the current study was to propose a sensitivity analysis of a 3D left ventricle model in order to assess the influence of parameters on myocardial mechanical dispersion. A finite element model of LV electro-mechanical activity was proposed and a screening method was used to evaluate the sensitivity of model parameters on the standard deviation of time to peak strain. Results highlight the importance of propagation parameters associated with septal and lateral segments activation. Simulated curves were compared to (...) myocardial strains, obtained from echocardiography of one healthy subject and one patient diagnosed with intraventricular dyssynchrony and coronary artery disease. Results show a close match between simulation and clinical strains and illustrate the model ability to reproduce myocardial strains in the context of intraventricular dyssynchrony. (shrink)

The traditional distinction between basic and applied science has been much criticized in recent decades. The criticism is based on a combination of historical and systematic epistemic argument. The present paper is mostly concerned with the historical aspect. I argue that the critics impose an understanding at odds with the way the distinction was understood by its supporters in debates on science education and science policy in the nineteenth and twentieth centuries. And I show how a distinction that refers to (...) difference on several epistemic and social dimensions makes good sense of representative historical cases. If this argument is tenable it suggests more continuity in the epistemology and politics of science than has been claimed by a new paradigm of science studies and politics during recent decades. (shrink)

I call an experiment “crucial” when it makes possible a decisive choice between conflicting hypotheses. Joharmsen's selection for size and weight within pure lines of beans played a central role in the controversy over continuity or discontinuity in hereditary change, often known as the Biometrician-Mendelian controversy. The “crucial” effect of this experiment was not an instantaneous event, but an extended process of repeating similar experiments and discussing possible objections. It took years before Johannsen's claim about the genetic stability of pure (...) lines was accepted as conclusively demonstrated by the community of geneticists. The paper also argues that crucial experiments thus interpreted contradict certain ideas about the underdetermination of theories by facts and the theory-ladenness of facts which have been influential in recent history and sociology of science. The acceptance of stability in the pure lines did not rest on prior preference for continuity or discontinuity. And this fact permitted a final choice between the two theories. When such choice is characterized as “decisive” or “final”, this is not meant in an absolute philosophical sense. What we achive in these cases is highly reliable empirical knowledge. The philosophical possibility of drawing (almost) any conclusion in doubt should be distinguished from reasonable doubt in empirical science. (shrink)

Maintaining two full-time careers has required sacrifice, of course. On a recent Saturday Night Live, as an obvious plug, one of the actors carried a copy of The Chomsky Reader throughout a skit. Albert telephoned Chomsky to say, "Hey, you're on television!" and found himself having to explain what Saturday Night Live is. So Chomsky doesn't know anything about popular culture. He doesn't watch TV. He doesn't listen to rock & roll. He goes to maybe one movie a year. He (...) has little time for a private life. (shrink)

There are many advantages to defining emotions as states elicited by reinforcers, with the states having a set of different functions. This approach leads towards an understanding of the nature of emotion, of its evolutionary adaptive value, and of many principles of brain design. It also leads towards a foundation for many of the processes that underlie evolutionary psychology and behavioral ecology. It is shown that recent as well as previous evidence implicates the amygdala and orbitofrontal cortex in positive as (...) well as negative emotions. The issue of why emotional states feel like something is part of the much larger problem of phenomenal consciousness. It is argued that thinking about one's own thoughts would have adaptive value by enabling first order linguistic thoughts to be corrected. It is suggested that reflecting on and correcting one's own thoughts and plans would feel like something, and that phenomenal consciousness may occur when this type of monitoring process is taking place. (shrink)

This paper describes the historical background and early formation of Wilhelm Johannsen's distinction between genotype and phenotype. It is argued that contrary to a widely accepted interpretation his concepts referred primarily to properties of individual organisms and not to statistical averages. Johannsen's concept of genotype was derived from the idea of species in the tradition of biological systematics from Linnaeus to de Vries: An individual belonged to a group - species, subspecies, elementary species - by representing a certain underlying type. (...) Johannsen sharpened this idea theoretically in the light of recent biological discoveries, not least those of cytology. He tested and confirmed it experimentally combining the methods of biometry, as developed by Francis Galton, with the individual selection method and pedigree analysis, as developed for instance by Louis Vilmorin. The term "genotype" was introduced in W. Johannsen's 1909 treatise, but the idea of a stable underlying biological "type" distinct from observable properties was the core idea of his classical bean selection experiment published 6 years earlier. The individual ontological foundation of population analysis was a self-evident presupposition in Johannsen's studies of heredity in populations from their start in the early 1890s till his death in 1927. The claim that there was a "substantial but cautious modification of Johannsen's phenotype-genotype distinction" from a statistical to an individual ontological perspective derives from a misreading of the 1903 and 1909 texts. The immediate purpose of this paper is to correct this reading of the 1903 monograph by showing how its problems and results grow out of Johannsen's earlier work in heredity and plant breeding. Johannsen presented his famous selection experiment as the culmination of a line of criticism of orthodox Darwinism by William Bateson, Hugo de Vries, and others. They had argued that evolution is based on stepwise rather than continuous change in heredity. Johannsen's paradigmatic experiment showed how stepwise variation in heredity could be operationally distinguished from the observable, continuous morphological variation. To test Galton's law of partial regression, Johannsen deliberately chose pure lines of self-fertilizing plants, a pure line being the descendants in successive generations of one single individual. Such a population could be assumed to be highly homogeneous with respect to hereditary type, and Johannsen found that selection produced no change in this type. Galton, he explained, had experimented with populations composed of a number of stable hereditary types. The partial regression which Galton found was simply an effect of selection between types, increasing the proportion of some types at the expense of others. (shrink)

This paper describes the historical background and early formation of Wilhelm Johannsen's distinction between genotype and phenotype. It is argued that contrary to a widely accepted interpretation his concepts referred primarily to properties of individual organisms and not to statistical averages. Johannsen's concept of genotype was derived from the idea of species in the tradition of biological systematics from Linnaeus to de Vries: An individual belonged to a group - species, subspecies, elementary species - by representing a certain underlying type. (...) Johannsen sharpened this idea theoretically in the light of recent biological discoveries, not least those of cytology. He tested and confirmed it experimentally combining the methods of biometry, as developed by Francis Galton, with the individual selection method and pedigree analysis, as developed for instance by Louis Vilmorin. The term "genotype" was introduced in W. Johannsen's 1909 treatise, but the idea of a stable underlying biological "type" distinct from observable properties was the core idea of his classical bean selection experiment published 6 years earlier. The individual ontological foundation of population analysis was a self-evident presupposition in Johannsen's studies of heredity in populations from their start in the early 1890s till his death in 1927. The claim that there was a "substantial but cautious modification of Johannsen's phenotype-genotype distinction" from a statistical to an individual ontological perspective derives from a misreading of the 1903 and 1909 texts. The immediate purpose of this paper is to correct this reading of the 1903 monograph by showing how its problems and results grow out of Johannsen's earlier work in heredity and plant breeding. Johannsen presented his famous selection experiment as the culmination of a line of criticism of orthodox Darwinism by William Bateson, Hugo de Vries, and others. They had argued that evolution is based on stepwise rather than continuous change in heredity. Johannsen's paradigmatic experiment showed how stepwise variation in heredity could be operationally distinguished from the observable, continuous morphological variation. To test Galton's law of partial regression, Johannsen deliberately chose pure lines of self-fertilizing plants, a pure line being the descendants in successive generations of one single individual. Such a population could be assumed to be highly homogeneous with respect to hereditary type, and Johannsen found that selection produced no change in this type. Galton, he explained, had experimented with populations composed of a number of stable hereditary types. The partial regression which Galton found was simply an effect of selection between types, increasing the proportion of some types at the expense of others. (shrink)

Why do we have emotions? What is the relationship between mind and brain? Why do we appreciate art? How do we make decisions? Why do so many people follow religions? Neuroculture considers the implications of our modern understanding of how the brain works, and how it can help us understand many mental issues central to everyday life.

What produces emotions? Why do we have emotions? How do we have emotions? Why do emotional states feel like something? The Brain, Emotion, and Depression addresses these issues and more, providing a unified approach to emotion, reward value, economic value, decision-making, and their brain mechanisms.

A neuroscience-based approach has recently been proposed for the relation between the mind and the brain. The proposal is that events at the sub-neuronal, neuronal, and neuronal network levels take place simultaneously to perform a computation that can be described at a high level as a mental state, with content about the world. It is argued that as the processes at the different levels of explanation take place at the same time, they are linked by a non-causal supervenient relationship: causality (...) can best be described in brains as operating within but not between levels. This mind-brain theory allows mental events to be different in kind from the mechanistic events that underlie them; but does not lead one to argue that mental events cause brain events, or vice versa: they are different levels of explanation of the operation of the computational system. Here, some implications are developed. It is proposed that causality, at least as it applies to the brain, should satisfy three conditions. First, interventionist tests for causality must be satisfied. Second, the causally related events should be at the same level of explanation. Third, a temporal order condition must be satisfied, with a suitable time scale in the order of 10 ms. Next, although it may be useful for different purposes to describe causality involving the mind and brain at the mental level, or at the brain level, it is argued that the brain level may sometimes be more accurate, for sometimes causal accounts at the mental level may arise from confabulation by the mentalee, whereas understanding exactly what computations have occurred in the brain that result in a choice or action will provide the correct causal account for why a choice or action was made. Next, it is argued that possible cases of “downward causation” can be accounted for by a within-levels-of-explanation account of causality. This computational neuroscience approach provides an opportunity to proceed beyond Cartesian dualism and physical reductionism in considering the relations between the mind and the brain. (shrink)

Memory, attention, and decision-making are three major areas of cognitive neuroscience. They are however frequently studied in isolation, using a range of models to understand them. This book brings a unified approach to understanding these three processes, showing how these fundamental functions can be understood in a common and unifying framework.

Problems are raised with the global workspace hypothesis of consciousness, for example about exactly how global the workspace needs to be for consciousness to suddenly be present. Problems are also raised with Carruthers's version that excludes conceptual representations, and in which phenomenal consciousness can be reduced to physical processes, with instead a different levels of explanation approach to the relation between the brain and the mind advocated. A different theory of phenomenal consciousness is described, in which there is a particular (...) computational system involved in which Higher Order Syntactic Thoughts are used to perform credit assignment on first order thoughts of multiple step plans to correct them by manipulating symbols in a syntactic type of working memory. This provides a good evolutionary reason for the evolution of this kind of computational module, with which, it is proposed, phenomenal consciousness is associated. Some advantages of this HOST approach to phenomenal consciousness are then described with reference not only to the global workspace approach, but also to Higher Order Thought theories. It is hypothesized that the HOST system which requires the ability to manipulate first order symbols in working memory might utilize parts of the prefrontal cortex implicated in working memory, and especially the left inferior frontal gyrus, which is involved in language and probably syntactical processing. Overall, the approach advocated is to identify the computations that are linked to consciousness, and to analyze the neural bases of those computations. [copyright: Copyright © 2020 Rolls.]. (shrink)

Present science policy discourse is focused on a broad concept of “techno-science” and emphasizes practical economic goals and gains. At the same time scientists are worried about the freedom of research and the autonomy of science. Half a century ago the difference between basic and applied science was widely taken for granted and autonomy was a value in high esteem. Most recent accounts of the history of science policy start abruptly from World War II, emphasize the Cold War context, and (...) neglect the pioneering role of the Soviet Union in forming todays “big science.” This paper claims that a closer look into the intellectual heritage from the early twentieth century will be helpful in navigating present issues of science policy. The “Lysenko affair” was a paradigmatic case in forming Cold War views on science and politics. (shrink)

Dans cet article, je montre que les neurosciences computationnelles fournissent une nouvelle approche pertinente à des problèmes traditionnels en philosophie tels que la relation entre les états mentaux et cérébraux (le problème esprit–corps ou corps–esprit), le déterminisme et le libre arbitre, et peut nous aider à traiter le problème « difficile » des aspects phénoménaux de la conscience. Un des thèmes de cet article et de mon livre Neuroculture: on the Implications of Brain Science ([Rolls 2012c]) est qu’en comprenant les (...) calculs effectués par les neurones et les réseaux neuronaux, et les effets du bruit dans le cerveau sur ceux-ci, nous gagnerons une vraie compréhension des mécanismes qui sous-tendent le fonctionnement du cerveau. Une partie de notre solution au problème esprit–corps est que l’esprit et le cerveau sont différents niveaux d’explication du traitement de l’information, leur relation pouvant être appréhendée par la compréhension des mécanismes en jeu à l’aide de l’approche fournie par les neurosciences computationnelles. Mais cette solution ne traite pas certains problèmes « difficiles » tels que le problème de la conscience phénoménale, et, même si j’ai fourni de nouvelles suggestions sur ce point dans cet article, il faut reconnaître qu’il y a toujours une brèche dans notre compréhension entre les événements dans le cerveau et les expériences subjectives qui peuvent les accompagner. L’explication que je propose est que, lorsque cela « fait quelque chose », il ne s’agit que d’une propriété d’un processus computationnel qui a des pensées sur ses propres pensées (pensées d’ordre supérieur), les pensées étant ancrées dans le monde. (shrink)

Dans cet article, je montre que les neurosciences computationnelles fournissent une nouvelle approche pertinente à des problèmes traditionnels en philosophie tels que la relation entre les états mentaux et cérébraux (le problème esprit–corps ou corps–esprit), le déterminisme et le libre arbitre, et peut nous aider à traiter le problème « difficile » des aspects phénoménaux de la conscience. Un des thèmes de cet article et de mon livre Neuroculture: on the Implications of Brain Science ([Rolls 2012c]) est qu’en comprenant les (...) calculs effectués par les neurones et les réseaux neuronaux, et les effets du bruit dans le cerveau sur ceux-ci, nous gagnerons une vraie compréhension des mécanismes qui sous-tendent le fonctionnement du cerveau. Une partie de notre solution au problème esprit–corps est que l’esprit et le cerveau sont différents niveaux d’explication du traitement de l’information, leur relation pouvant être appréhendée par la compréhension des mécanismes en jeu à l’aide de l’approche fournie par les neurosciences computationnelles. Mais cette solution ne traite pas certains problèmes « difficiles » tels que le problème de la conscience phénoménale, et, même si j’ai fourni de nouvelles suggestions sur ce point dans cet article, il faut reconnaître qu’il y a toujours une brèche dans notre compréhension entre les événements dans le cerveau et les expériences subjectives qui peuvent les accompagner. L’explication que je propose est que, lorsque cela « fait quelque chose », il ne s’agit que d’une propriété d’un processus computationnel qui a des pensées sur ses propres pensées (pensées d’ordre supérieur), les pensées étant ancrées dans le monde. (shrink)