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How many neural systems does it take to change a light bulb?
Book Review
How many neural systems does it take to change a light bulb? The Mind Within the Brain – How We Make Decisions and How Those Decisions Go Wrong by A.D. Redish, Oxford University Press, 2013. US$32.58, ISBN-13: 978-0199891887
Bernard W. Balleine Brain and Mind Research Institute, University of Sydney, Sydney, Australia
In his new book, ‘The Mind Within the Brain’, David Redish argues that it takes four neural systems to change a light bulb. Decision-making is currently a popular area of research; at least in neuroscience the question of how decisions are made and implemented in the brain has become one of the core problems. This development is, at least in part, due to recognition that many older research problems, relating to such functions as selective attention, working memory, spatial learning, and so on, can be reframed as decision problems. It is also due to the fact that many broad areas of research, whether focused on issues in perception, motor learning, economics, or social psychology, have in common a concern for the way events and actions are categorized, selected, and evaluated. Beyond these functional issues it has also become widely recognized that many behavioral, psychiatric, and neurological disorders are characterized by core deficits in decision-making, and it is now more generally argued that these disorders of thought and action reflect changes in the neural processes responsible for everyday decisions. Given the breadth of the problem and its current popularity David Redish’s recent book [1] – subtitled ‘How we make decisions and how those decisions go wrong’ – is timely. The book goes beyond current research, however, and advances ambitious claims about decision-making in general and the nature of the decision-maker in particular. This is in many ways a very personal view. Redish uses anecdotes and examples from his own experience, even composes original poetry, to illustrate specific issues – and these give the book a biographical feel. The theoretically important part of the book is Section 2, in which his ‘decision-making system’ is developed. Taking seriously William James’ distinction between reflex and volition, Redish proposes there is not one decision-making system but four, each concerned with a distinct form of activity: basic reflexes, conditioned reflexes, deliberative actions, and habits. These he contends are ‘generally sufficient to explain action selection within the mammalian brain’ (p. 44). To work in the real world, however, he concedes that additional support systems are required: a motor control system producing muscle movements, a perceptual system, a situation-recognition system, and a motivational system Corresponding author: Balleine, B.W. ([email protected]). 1364-6613/ http://dx.doi.org/10.1016/j.tics.2014.06.008
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Trends in Cognitive Sciences, October 2014, Vol. 18, No. 10
that encodes goals and desires. The functions of the latter two in particular are fairly sophisticated, and Redish describes and develops their role in important and novel ways. The ‘multiple decision-maker’ is an important idea and, although it brings with it the issue of how the different behavioral and support systems interact, Redish sees in this complexity important vulnerabilities: break-points where external influences can act to produce errors in decision-making. He calls these ‘failure modes’, and develops this idea in Section 3 of the book discussing implications for disorders characterized by problems of decisionmaking, including addiction, post-traumatic stress disorder, and other psychiatric conditions. It is difficult to fault Redish’s scholarship or his courage. In an early chapter he makes a characteristically audacious claim asking: Is it fair to . . . explain people as complex machines? I’m going to argue . . . ‘yes’ – your brain is a decisionmaking machine. You are that decision-making machine Such materialism counters the dualism lurking beneath most theories linking psychological and neural processes, but it raises other issues. One of these is the relationship of mind and brain, an issue addressed in an interesting chapter on ‘The physical mind’. Using, appropriately enough, the computer analogy of the brain as hardware and the mind as some form of software, Redish sees in the ‘multiple decision-maker’ evidence for mind–brain identity. The fact that the functions mediated by particular ‘software’ are lost when specific neural circuits are damaged suggests that there is a close relationship between those functions and circuits; that the brain and its functions, if not identical, are at least highly embedded. Other surprising perspectives are developed as part of this volume: in the face of his materialist perspective Redish feels the need to explain what makes us human (language), some views on morality from the perspective of research on game theory and economic games, and views on free will and whether robots could be conscious (they can). Nevertheless, despite the welcome lack of formal computational modeling in the book, this is a computational view of decision-making put forward by a computer scientist and, as a consequence, some of the positions Redish takes will not be readily accepted by researchers with other backgrounds. Computational principles have been most successfully applied to modeling cognitive
Book Review functions; however, although decision-making is clearly concerned with these functions, cognition alone is not sufficient to determine any of the decisions we make: knowing that ‘A leads to B’ can be used to perform/desire/procure A or to avoid A. What distinguishes decisionmaking from cognition is that the former requires the integration of cognition with some form of desire, emotion, or evaluative state. It is this integrative process that we are ultimately trying to understand. As is common in most computational theories, the discussion of these motivational and emotional components of the decision process is not strongly developed, and only emerges in Chapter 13. Redish does focus on value in an early chapter, but it is the values of economics, which he links to the function of the phasic dopamine signal. However, although the role of dopamine in Pavlovian predictions and in the acquisition of habits appears to be well established, neither of these signals is key to understanding the actions that are the principle beneficiary of decision-making – deliberative or goal-directed actions – and the evaluative processes controlling these forms of action are essentially omitted here [2]. Such values could fall under what Redish calls ‘intrinsic goalfunctions’, by which we must suppose he means something like unconditioned values or unlearned values; however, current research suggests there are few, if any, of these, at
Trends in Cognitive Sciences October 2014, Vol. 18, No. 10
least at a psychological level [3]; instead, the specific values assigned to objects of desire come through experience as a form of evaluative learning that appears to involve the amygdala [4]. As a consequence, therefore, the critical integrative basis for decision-making remains incompletely specified. It is, of course, easy to take issue with the details of complex theoretical positions. Indeed, despite these technical issues, there is much to admire in Redish’s systematic development of the ‘multiple decision-maker’ hypothesis. The implications for future research that these ideas reveal are exciting, and they suggest that the importance and popularity of research in decision-making will persist and that its most important and influential findings are still to come. References 1 Redish, A.D. (2013) The Mind Within the Brain – How We Make Decisions and How Those Decisions Go Wrong, Oxford University Press 2 Dickinson, A. and Balleine, B.W. (2002) The role of learning in the operation of motivational systems. In Learning, Motivation, and Emotion (Steven’s Handbook of Experimental Psychology, Vol. 3, 3rd edn) (Gallistel, C.R., ed.), pp. 497–533, John Wiley & Sons 3 Changizi, M.A. et al. (2002) Evidence that appetitive responses for dehydration and food deprivation are learned. Physiol. Behav. 75, 295–304 4 Balleine, B.W. and Killcross, S. (2006) Parallel incentive processing: an integrated view of amygdala function. Trends Neurosci. 29, 272–279
511
How many neural systems does it take to change a light bulb? The Mind Within the Brain – How We Make Decisions and How Those Decisions Go Wrong by A.D. Redish, Oxford University Press, 2013. US$32.58, ISBN-13: 978-0199891887
Bernard W. Balleine Brain and Mind Research Institute, University of Sydney, Sydney, Australia
In his new book, ‘The Mind Within the Brain’, David Redish argues that it takes four neural systems to change a light bulb. Decision-making is currently a popular area of research; at least in neuroscience the question of how decisions are made and implemented in the brain has become one of the core problems. This development is, at least in part, due to recognition that many older research problems, relating to such functions as selective attention, working memory, spatial learning, and so on, can be reframed as decision problems. It is also due to the fact that many broad areas of research, whether focused on issues in perception, motor learning, economics, or social psychology, have in common a concern for the way events and actions are categorized, selected, and evaluated. Beyond these functional issues it has also become widely recognized that many behavioral, psychiatric, and neurological disorders are characterized by core deficits in decision-making, and it is now more generally argued that these disorders of thought and action reflect changes in the neural processes responsible for everyday decisions. Given the breadth of the problem and its current popularity David Redish’s recent book [1] – subtitled ‘How we make decisions and how those decisions go wrong’ – is timely. The book goes beyond current research, however, and advances ambitious claims about decision-making in general and the nature of the decision-maker in particular. This is in many ways a very personal view. Redish uses anecdotes and examples from his own experience, even composes original poetry, to illustrate specific issues – and these give the book a biographical feel. The theoretically important part of the book is Section 2, in which his ‘decision-making system’ is developed. Taking seriously William James’ distinction between reflex and volition, Redish proposes there is not one decision-making system but four, each concerned with a distinct form of activity: basic reflexes, conditioned reflexes, deliberative actions, and habits. These he contends are ‘generally sufficient to explain action selection within the mammalian brain’ (p. 44). To work in the real world, however, he concedes that additional support systems are required: a motor control system producing muscle movements, a perceptual system, a situation-recognition system, and a motivational system Corresponding author: Balleine, B.W. ([email protected]). 1364-6613/ http://dx.doi.org/10.1016/j.tics.2014.06.008
510
Trends in Cognitive Sciences, October 2014, Vol. 18, No. 10
that encodes goals and desires. The functions of the latter two in particular are fairly sophisticated, and Redish describes and develops their role in important and novel ways. The ‘multiple decision-maker’ is an important idea and, although it brings with it the issue of how the different behavioral and support systems interact, Redish sees in this complexity important vulnerabilities: break-points where external influences can act to produce errors in decision-making. He calls these ‘failure modes’, and develops this idea in Section 3 of the book discussing implications for disorders characterized by problems of decisionmaking, including addiction, post-traumatic stress disorder, and other psychiatric conditions. It is difficult to fault Redish’s scholarship or his courage. In an early chapter he makes a characteristically audacious claim asking: Is it fair to . . . explain people as complex machines? I’m going to argue . . . ‘yes’ – your brain is a decisionmaking machine. You are that decision-making machine Such materialism counters the dualism lurking beneath most theories linking psychological and neural processes, but it raises other issues. One of these is the relationship of mind and brain, an issue addressed in an interesting chapter on ‘The physical mind’. Using, appropriately enough, the computer analogy of the brain as hardware and the mind as some form of software, Redish sees in the ‘multiple decision-maker’ evidence for mind–brain identity. The fact that the functions mediated by particular ‘software’ are lost when specific neural circuits are damaged suggests that there is a close relationship between those functions and circuits; that the brain and its functions, if not identical, are at least highly embedded. Other surprising perspectives are developed as part of this volume: in the face of his materialist perspective Redish feels the need to explain what makes us human (language), some views on morality from the perspective of research on game theory and economic games, and views on free will and whether robots could be conscious (they can). Nevertheless, despite the welcome lack of formal computational modeling in the book, this is a computational view of decision-making put forward by a computer scientist and, as a consequence, some of the positions Redish takes will not be readily accepted by researchers with other backgrounds. Computational principles have been most successfully applied to modeling cognitive
Book Review functions; however, although decision-making is clearly concerned with these functions, cognition alone is not sufficient to determine any of the decisions we make: knowing that ‘A leads to B’ can be used to perform/desire/procure A or to avoid A. What distinguishes decisionmaking from cognition is that the former requires the integration of cognition with some form of desire, emotion, or evaluative state. It is this integrative process that we are ultimately trying to understand. As is common in most computational theories, the discussion of these motivational and emotional components of the decision process is not strongly developed, and only emerges in Chapter 13. Redish does focus on value in an early chapter, but it is the values of economics, which he links to the function of the phasic dopamine signal. However, although the role of dopamine in Pavlovian predictions and in the acquisition of habits appears to be well established, neither of these signals is key to understanding the actions that are the principle beneficiary of decision-making – deliberative or goal-directed actions – and the evaluative processes controlling these forms of action are essentially omitted here [2]. Such values could fall under what Redish calls ‘intrinsic goalfunctions’, by which we must suppose he means something like unconditioned values or unlearned values; however, current research suggests there are few, if any, of these, at
Trends in Cognitive Sciences October 2014, Vol. 18, No. 10
least at a psychological level [3]; instead, the specific values assigned to objects of desire come through experience as a form of evaluative learning that appears to involve the amygdala [4]. As a consequence, therefore, the critical integrative basis for decision-making remains incompletely specified. It is, of course, easy to take issue with the details of complex theoretical positions. Indeed, despite these technical issues, there is much to admire in Redish’s systematic development of the ‘multiple decision-maker’ hypothesis. The implications for future research that these ideas reveal are exciting, and they suggest that the importance and popularity of research in decision-making will persist and that its most important and influential findings are still to come. References 1 Redish, A.D. (2013) The Mind Within the Brain – How We Make Decisions and How Those Decisions Go Wrong, Oxford University Press 2 Dickinson, A. and Balleine, B.W. (2002) The role of learning in the operation of motivational systems. In Learning, Motivation, and Emotion (Steven’s Handbook of Experimental Psychology, Vol. 3, 3rd edn) (Gallistel, C.R., ed.), pp. 497–533, John Wiley & Sons 3 Changizi, M.A. et al. (2002) Evidence that appetitive responses for dehydration and food deprivation are learned. Physiol. Behav. 75, 295–304 4 Balleine, B.W. and Killcross, S. (2006) Parallel incentive processing: an integrated view of amygdala function. Trends Neurosci. 29, 272–279
511