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.
Rapid advances have recently been made in understanding how value-based decision-making processes are implemented in the brain. We integrate neuroeconomic and computational approaches with evidence on the neural correlates of value and experienced pleasure to describe how systems for valuation and decision-making are organized in the prefrontal cortex of humans and other primates. We show that the orbitofrontal and ventromedial prefrontal (VMPFC) cortices compute expected value, reward outcome and experienced pleasure for different stimuli on a common value scale. Attractor networks (...) in VMPFC area 10 then implement categorical decision processes that transform value signals into a choice between the values, thereby guiding action. This synthesis of findings across fields provides a unifying perspective for the study of decision-making processes in the brain. (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)
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)
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.
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)
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)
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.
The representation of objects and faces by neurons in the temporal lobe visual cortical areas of primates has the property that the neurons encode relatively independent information in their firing rates. This means that the number of stimuli that can be encoded increases exponentially with the number of neurons in an ensemble. Moreover, the information can be read by receiving neurons that perform just a synaptically weighted sum of the firing rates being received. Some ways in which these representations become (...) grounded in the world are described. The issue of syntactic binding in representations, and of its value for a higher order thought system, is discussed. (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)
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 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 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 , les pensées étant ancrées dans le monde.In this paper I show that computational neuroscience provides an important new approach to traditional problems in philosophy such as the relation between mental states and brain states , to determinism and free will, and helps one with the ‘hard’ problem, the phenomenal aspects of consciousness.One of the themes of the paper and of my book Neuroculture: on the Implications of Brain Science is that by understanding the computations performed by neurons and neuronal networks, and the effects of noise in the brain on these, we will gain a true understanding of the mechanisms that underlie brain function. Part of the solution proposed to the mind-body problem is that the mind and the brain are different levels of explanation of information processing, the correspondence between which can be understood by understanding the mechanisms involved using the approach of computational neuroscience.But this does leave some ‘hard’ problems, such as the problem of phenomenal consciousness, and while I have provided new suggestions about this in this paper, one must recognise that there is still somewhat of a gap in our understanding of events in the brain and the subjective experiences that may accompany them. The explanation I offer is that when it ‘feels like something’ this is just a property of a computational process that has thoughts about its own thoughts , and with the thoughts grounded in the world. (shrink)
Understanding consciousness is a truly multidisciplinary project, attracting intense interest from researchers and theorists from diverse backgrounds. Thus, we now have computational scientists, neuroscientists, and philosophers all engaged in the same effort. This book draws together the work of leading researchers around the world, providing insights from these three general perspectives. The work is highlighted by a rare look at work being conducted by Japanese researchers.