Optogenetic techniques are described as “revolutionary” for the unprecedented causal control they allow neuroscientists to exert over neural activity in awake behaving animals. In this paper, I demonstrate by means of a case study that optogenetic techniques will only illuminate causal links between the brain and behavior to the extent that their error characteristics are known and, further, that determining these error characteristics requires comparison of optogenetic techniques with techniques having well known error characteristics and consideration of the broader neural (...) and behavioral context in which the targets of optogenetic interventions are situated. (shrink)

The use of neuroscientific evidence in criminal trials has been steadily increasing. Despite progress made in recent decades in understanding the mechanisms of psychological and behavioral functioning, neuroscience is still in an early stage of development and its potential for influencing legal decision-making is highly contentious. Scholars disagree about whether or how neuroscientific evidence might impact prescriptions of criminal culpability, particularly in instances in which evidence of an accused’s history of mental illness or brain abnormality is offered to support a (...) plea of not criminally responsible. In the context of these debates, philosophers and legal scholars have identified numerous problems with admitting neuroscientific evidence in legal contexts. To date, however, less has been said about the challenges of evaluating the evidence upon which integrative mechanistic explanations that bring together evidence from different areas of neuroscience are based. As we explain, current criteria for evaluating such evidence to determine its admissibility in legal contexts are inadequate. Appealing to literature in the philosophy of scientific experimentation and theoretical work in the social, cognitive and behavioral sciences, we lay the groundwork for reforming these criteria and identify some of the implications of modifying them. (shrink)

In this volume, leading philosophers of psychiatry examine psychiatric classification systems, including the Diagnostic and Statistical Manual of Mental Disorders, asking whether current systems are sufficient for effective diagnosis, treatment, and research. Doing so, they take up the question of whether mental disorders are natural kinds, grounded in something in the outside world. Psychiatric categories based on natural kinds should group phenomena in such a way that they are subject to the same type of causal explanations and respond similarly to (...) the same type of causal interventions. When these categories do not evince such groupings, there is reason to revise existing classifications. The contributors all question current psychiatric classifications systems and the assumptions on which they are based. They differ, however, as to why and to what extent the categories are inadequate and how to address the problem. Topics discussed include taxometric methods for identifying natural kinds, the error and bias inherent in DSM categories, and the complexities involved in classifying such specific mental disorders as "oppositional defiance disorder" and pathological gambling. -/- Contributors George Graham, Nick Haslam, Allan Horwitz, Harold Kincaid, Dominic Murphy, Jeffrey Poland, Nancy Nyquist Potter, Don Ross, Dan Stein, Jacqueline Sullivan, Serife Tekin, Peter Zachar. (shrink)

In this chapter I investigate the kinds of changes that psychiatric kinds undergo when they become explanatory targets of areas of sciences that are not “mature” and are in the early stages of discovering mechanisms. The two areas of science that are the targets of my analysis are cognitive neuroscience and cognitive neurobiology.

This study aimed to understand the preserved elements of self-identity in persons with moderate to severe dementia attributable to Alzheimer’s disease. A semi-structured interview was developed to explore the narrative self among residents with dementia in a residential care facility and residents without dementia in an independent living setting. The interviews were transcribed verbatim from audio recordings and analyzed for common themes, while being sensitive to possible differences between the groups. The participants with dementia showed evidence of self-reference even though (...) losses in explicit memory were evident. The most noticeable difference between the two groups was time frame reference. Nonetheless, all participants showed understanding of their role in relationships and exhibited concrete preferences. Our findings suggest that memory loss and other cognitive deficits associated with moderate to severe dementia do not necessarily lead to a loss of “self.”. (shrink)

Neuroscience is a laboratory-based science that spans multiple levels of analysis from molecular genetics to behavior. At every level of analysis experiments are designed in order to answer empirical questions about phenomena of interest. Understanding the nature and structure of experimentation in neuroscience is fundamental for assessing the quality of the evidence produced by such experiments and the kinds of claims that are warranted by the data. This article provides a general conceptual framework for thinking about evidence and experimentation in (...) neuroscience with a particular focus on two research areas: cognitive neuroscience and cognitive neurobiology. (shrink)

In this chapter, I argue that scientific practice in the neurosciences of cognition is not conducive to the discovery of natural kinds of cognitive capacities. The “neurosciences of cognition” include cognitive neuroscience and cognitive neurobiology, two research areas that aim to understand how the brain gives rise to cognition and behavior. Some philosophers of neuroscience have claimed that explanatory progress in these research areas ultimately will result in the discovery of the underlying mechanisms of cognitive capacities. Once such mechanistic understanding (...) is achieved, cognitive capacities purportedly will be relegated into natural kind categories that correspond to real divisions in the causal structure of the world. I provide reasons here, however, in support of the claim that the neurosciences of cognition currently are not on a trajectory for discovering natural kinds. As I explain, this has to do with how mechanistic explanations of cognitive capacities are developed. Mechanistic explanations and the kinds they explain are abstract representational byproducts of the conceptual, experimental and integrative practices of neuroscientists. If these practices are not coordinated towards developing mechanistic explanations that mirror the causal structure of the world, then natural kinds of cognitive capacities will not be discovered. I provide reasons to think that such coordination is currently lacking in the neurosciences of cognition and indicate where changes in these practices appropriate to the natural kinds ideal would be required if achieving this ideal is indeed the goal. However, I suggest that an evaluation of current practices in these research areas is suggestive that discovering natural kinds of cognitive capacities is not the goal. (shrink)

What role does the concept of representation play in the contexts of experimentation and explanation in cognitive neurobiology? In this article, a distinction is drawn between minimal and substantive roles for representation. It is argued by appeal to a case study that representation currently plays a role in cognitive neurobiology somewhere in between minimal and substantive and that this is problematic given the ultimate explanatory goals of cognitive neurobiological research. It is suggested that what is needed is for representation to (...) instead play a more substantive role. (shrink)

This chapter has two aims. The first aim is to compare and contrast three different conceptual-explanatory models for thinking about mental illness with an eye towards identifying the assumptions upon which each model is based, and exploring the model’s advantages and limitations in clinical contexts. Major Depressive Disorder is used as an example to illustrate these points. The second aim is to address the question of what conceptual-theoretical framework for thinking about mental illness is most likely to facilitate the discovery (...) of causes and treatments of mental illness in research contexts. To this end, the National Institute of Mental Health’s Research Domain Criteria (RDoC) Project is briefly considered. (shrink)

Biomedical science has been remarkably successful in explaining illness by categorizing diseases and then by identifying localizable lesions such as a virus and neoplasm in the body that cause those diseases. Not surprisingly, researchers have aspired to apply this powerful paradigm to addiction. So, for example, in a review of the neuroscience of addiction literature, Hyman and Malenka (2001, p. 695) acknowledge a general consensus among addiction researchers that “[a]ddiction can appropriately be considered as a chronic medical illness.” Like other (...) diseases, “Once addiction has taken hold, it tends to follow a chronic course.” (Koob and La Moal 2006, p. ?). Working from this perspective, much effort has gone into characterizing the symptomology of addiction and the brain changes that underlie them. Evidence for involvement of dopamine transmission changes in the ventral tegmental area (VTA) and nucleus accumbens (NAc) have received the greatest attention. Kauer and Malenka (2007, p. 844) put it well: “drugs of abuse can co-opt synaptic plasticity mechanisms in brain circuits involved in reinforcement and reward processing”. Our goal in this chapter to provide an explicit description of the assumptions of medical models, the different forms they may take, and the challenges they face in providing explanations with solid evidence of addiction. <br>. (shrink)

In 2007, ten world-renowned neuroscientists proposed “A Decade of the Mind Initiative.” The contention was that, despite the successes of the Decade of the Brain, “a fundamental understanding of how the brain gives rise to the mind [was] still lacking” (2007, 1321). The primary aims of the decade of the mind were “to build on the progress of the recent Decade of the Brain (1990-99)” by focusing on “four broad but intertwined areas” of research, including: healing and protecting, understanding, enriching, (...) and modeling the mind. These four aims were to be the result of “transdisciplinary and multiagency” research spanning “across disparate fields, such as cognitive science, medicine, neuroscience, psychology, mathematics, engineering, and computer science.” The proposal for a decade of the mind prompted many questions (See Spitzer 2008). In this chapter, I address three of them: (1) How do proponents of this new decade conceive of the mind? (2) Why should a decade be devoted to understanding it? (3) What should this decade look like? (shrink)