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)

The sceptical positions philosophers have adopted with respect to neuroimaging data are based on detailed evaluations of subtraction, which is one of many data analysis techniques used with neuroimaging data. These positions are undermined when the epistemic implications of the use of a diversity of data analysis techniques are taken into account. I argue that different data analysis techniques reveal different patterns in the data. Through the use of multiple data analysis techniques, researchers can produce results that are locally robust. (...) Thus, the epistemology of neuroimaging must take into consideration the details of the different data analysis techniques that are used to evaluate neuroimaging data, and the specific theoretical aims those techniques are deployed towards. _1_ Introduction _2_ Scepticism about Neuroimaging _3_ Data Analysis and Evidence _4_ Deconvolution and Pattern Classification Analysis _4.1_ Deconvolution analysis _4.2_ Region of interest selection _4.3_ Pattern classification analysis _5_ The Strength of Multiple Analyses _6_ Conclusion. (shrink)

La resonancia magnética funcional es una de las técnicas de neuroimagen más difundidas en las neurociencias cognitivas. Su influencia tuvo un rol central en la configuración del aspecto experimental de este campo. Frente a esto, consideramos que su estatus como evidencia no ha sido suficientemente discutido en la literatura filosófica. En este trabajo nos centramos sobre este punto abordando el problema clásico de definir el alcance que puede tener la estrategia localizacionista en neurociencias. Atendemos al modo en que este problema (...) se manifiesta hoy, tomando algunos ejemplos recientes de abordajes neurocientíficos caracterizados por estudiar el carácter dinámico de la actividad a gran escala en el cerebro. Tomamos en cuenta un número de limitaciones que presenta la resonancia magnética funcional, distinguiendo aquellas cuyo tratamiento pone en juego problemáticas de una índole no meramente técnica. A partir del análisis de algunas maneras en que los investigadores les hacen frente, sostenemos que existe una medida importante en que este tipo de estudios de neuroimagen pueden ser orientados sobre la base de supuestos y consideraciones teóricas generales. Concluimos que esta particular permeabilidad teórica de la resonancia magnética funcional es un factor central que incide sobre su estatus como evidencia neurocientífica. (shrink)

'Epistemological constructivism' holds that vision is mediated by background preconceptions and is theory-laden. Hence, two persons with differing theoretical commitments see the world differently and they could agree on what they see only if they both espoused the same conceptual framework. This, in its turn, undermines the possibility of theory testing and choice on a common theory-neutral empirical basis. In this paper, I claim that the cognitive sciences suggest that a part of vision may be only indirectly penetrated by cognition (...) in a way that does not threaten retrieval of information from a visual scene in a bottom-up way. That blocks the constructivist epistemological thesis. However, since spatial attention, which can be cognitively driven, seems to permeate all stages of visual processes, one is led to conclude that there is no part of vision immune to direct cognitive interference. Against this, I elaborate on the role of spatial attention and argue that it does influence vision in a top-down manner, but it does so only in an indirect way. I then argue that the existence of visual processes that are only indirectly penetrated by cognition undermines the epistemological conclusions of constructivism. (shrink)

Psychoneural reduction has been debated extensively in the philosophy of neuroscience. In this article I will evaluate metascientific approaches that claim direct molecular and cellular explanations of cognitive functions. I will initially consider the issues involved in linking cellular properties to behaviour from the general perspective of neural circuits. These circuits that integrate the molecular and cellular components underlying cognition and behaviour, making consideration of circuit properties relevant to reductionist debates. I will then apply this general perspective to specific systems (...) where psychoneural reduction has been claimed, namely hippocampal long-term potentiation and the Aplysia gill-withdrawal reflex. (shrink)

Functional neuroimaging (NI) technologies like Positron Emission Tomography and functional Magnetic Resonance Imaging (fMRI) have revolutionized neuroscience, and provide crucial tools to link cognitive psychology and traditional neuroscientific models. A growing discipline of 'neurophilosophy' brings fMRI evidence to bear on traditional philosophical issues such as weakness of will, moral psychology, rational choice, social interaction, free will, and consciousness. NI has also attracted critical attention from psychologists and from philosophers of science. I review debates over the evidential status of fMRI, including (...) the differences between brain scans and ordinary images, the legitimacy of forward inference and reverse inference, and deductive versus probabilistic accounts of NI evidence. I conclude with a discussion of fMRI as exploratory rather than confirmatory evidence, linking this debate to the growing literature on cognitive ontology. (shrink)

fMRI promises to uncover the functional structure of the brain. I argue, however, that pictures of ‘brain activity' associated with fMRI experiments are poor evidence for functional claims. These neuroimages present the results of null hypothesis significance tests performed on fMRI data. Significance tests alone cannot provide evidence about the functional structure of causally dense systems, including the brain. Instead, neuroimages should be seen as indicating regions where further data analysis is warranted. This additional analysis rarely involves simple significance testing, (...) and so justified skepticism about neuroimages does not provide reason for skepticism about fMRI more generally. (shrink)

Since the mid‐1980s, psychologists and neuroscientists have used brain imaging to test hypotheses about human thought processes and their neural instantiation. In just three decades, functional neuroimaging has been transformed from a crude clinical tool to a widely used research method for understanding the human brain and mind. Such rapidly achieved success is bound to evoke skepticism. A degree of skepticism toward new methods and ideas is both inevitable and useful in any field. It is especially valuable in a science (...) as young as cognitive neuroscience and its even younger siblings, social and affective neuroscience. Healthy skepticism encourages us to check our assumptions, recognize the limitations of our methods, and proceed thoughtfully. Skepticism itself, however, also must be examined.In this article, I review the most commonly voiced criticisms of functional neuroimaging. In the spirit of healthy skepticism, I will critically examine these criticisms themselves. Each contains at least a kernel of truth, although I will argue that in some cases the kernel has been overextended in ways that are inaccurate or misleading. (shrink)

Many cognitive scientists, neuroscientists, and philosophers of science consider it uncontroversial that the brain processes information. In this work we broadly consider the types of experimental evidence that would support this claim, and find that although physical features of specific brain areas selectively covary with external stimuli or abilities, there is no direct evidence supporting an information processing function of any particular brain area.

This PhD thesis focuses on the philosophical foundations of Neuroeconomics, an innovative research program which combines findings and modelling tools from economics, psychology and neuroscience to account for human choice behaviour. The proponents of Neuroeconomics often manifest the ambition to foster radical modifications in the accounts of choice behaviour developed by its parent disciplines. This enquiry provides a philosophically informed appraisal of the potential for success and the relevance of neuroeconomic research for economics. My central claim is that neuroeconomists can (...) help other economists to build more predictive and explanatory models, yet are unlikely to foster revolutionary modifications in the economic theory of choice. The contents are organized as follows. In chapters 1-2, I present neuroeconomists’ investigative tools, distinguish the most influential approaches to neuroeconomic research and reconstruct the case in favour of a neural enrichment of economic theory. In chapters 3-7, I combine insights from neuro-psychology, economic methodology and philosophy of science to develop a systematic critique of Neuroeconomics. In particular, I articulate four lines of argument to demonstrate that economists are provisionally justified in retaining a methodologically distinctive approach to the modelling of decision making. My first argument points to several evidential and epistemological concerns which complicate the interpretation of neural data and cast doubt on the inferences neuroeconomists often make in their studies. My second argument aims to show that the trade-offs between the modelling desiderata that neuroeconomists and other economists respectively value severely constrain the incorporation of neural insights into economic models. My third argument questions neuroeconomists’ attempts to develop a unified theory of choice behaviour by identifying some central issues on which they hold contrasting positions. My fourth argument differentiates various senses of the term ‘revolution’ and illustrates that neuroeconomists are unlikely to provide revolutionary contributions to economic theory in any of these senses. (shrink)

The past 40 years have seen an enormous amount of research aimed at investigating human reasoning and decision-making abilities. This research has led to an extended debate about the extent to which humans meet the standards of normative theories of rationality. Recently, it has been proposed that dual-process theories, which posit that there are two distinct types of cognitive systems, offer a way to resolve this debate over human rationality. I will propose that the two systems of dual-process theories are (...) best understood as investigative kinds. I will then examine recent empirical research from the cognitive neuroscience of decision-making that lends empirical support to the theoretical claims of dual-process theorists. I will lastly argue that dual-process theories not only offer an explanation for much of the conflicting data seen in decision-making and reasoning research, but that they ultimately offer reason to be optimistic about the prospects of human rationality. (shrink)

Several developments for diverse scientific goals, mostly in physics and physiology, had to take place, which eventually gave us fMRI as one of the central research paradigms of contemporary cognitive neuroscience. This technique stands on solid foundations established by the physics of magnetic resonance and the physiology of hemodynamics and is complimented by computational and statistical techniques. I argue, and support using concrete examples, that these foundations give rise to a productive theory-ladenness in fMRI, which enables researchers to identify and (...) control for the types of methodological and inferential errors. Consequently, this makes it possible for researchers to represent and investigate cognitive phenomena in terms of hemodynamic data and for experimental knowledge to grow independently of large scale theories of cognition. (shrink)

Many of us consider it uncontroversial that information processing is a natural function of the brain. Since functions in biology are only won through empirical investigation, there should be a significant body of unambiguous evidence that supports this functional claim. Before we can interpret the evidence, however, we must ask what it means for a biological system to process information. Although a concept of information is generally accepted in the neurosciences without critique, in other biological sciences applications of information, despite (...) careful analysis, remain controversial. In this work I will review classical stimulus-response studies in neuroscience and use Claude Shannon’s mathematical information theory as a starting point to interpret information processing as a function of the brain. I will illustrate a disanalogy between Shannon’s communication model (source, encode, channel, receiver, decode) and neural systems, and will argue that the neural code is not very code-like in comparison to genetic and engineered codes. I suggest that we have conflated the act of representing neuroscientific facts—which we do to summarize and communicate our findings with others—with taking experimental facts to be representations. (shrink)

In my thesis, I challenge existing philosophical and scientific accounts of pain to explain certain constitutional, functional and empirical problems. Though difficult, some of these problems will be familiar. Unlike perceptual experiences, pains are strikingly affective and when we are in pain we are primarily concerned with the experience itself rather than mind-independent objects. The obvious explanation, that pain is not a perceptual experience, would be appealing if it were not for the fact that pains vary in quality, intensity and (...) location. These seem to be features of paradigmatic perceptual experiences. The magnitude of another problem, the weakness of the correlation between pain and the stimulus, has been under-played. It is widely observed that those with chronic conditions experience pain in the absence of the stimulus and in circumstances like sport and war severe injuries occur in the absence of pain. I argue that the variable relationship between pain and the stimulus is normal; it is not confined to abnormal cases or circumstances. As no existing account proves explanatorily adequate, I develop a novel position called ‘near-motivationalism’ from a revisionary approach to the conceptual models of pain science. This has the power to solve the problems I set. (shrink)

Neuroimaging technology is the most widely used tool to study human cognition. While originally a promising tool for mapping the content of cognitive theories onto the structures of the brain, recently developed tools for the analysis, handling and sharing of data have changed the theoretical landscape of cognitive neuroscience. Even with these advancements philosophical analyses of evidence in neuroimaging remain skeptical of the promise of neuroimaging technology. These views often treat the analysis techniques used to make sense of data produced (...) in a neuroimaging experiment as one, attributing the inferential limitations of analysis pipelines to the technology as a whole. Situated against the neuroscientists own critical assessment of their methods and the limitations of those methods, this skepticism appears based on a misunderstanding of the role data analysis techniques play in neuroimaging research. My project picks up here, examining how data analysis techniques, such as pattern classification analysis, are used to assess the evidential value of neuroimaging data. The project takes the form of three papers. In the first I identify the use of multiple data analysis techniques as an important aspect of the data interpretation process that is overlooked by critics. In the second I develop an account of inferences in neuroimaging research that is sensitive to this use of data analysis techniques, arguing that interpreting neuroimaging data is a process of isolating and explaining a variety of data patterns. In the third I argue that the development and uptake of new techniques for analyzing data must be accompanied by changes in research practices and standards of evidence if they are to promote knowledge generation. My approach to this work is both traditionally philosophical, insofar as it involves reading and analyzing the work of philosophers and neuroscientists, and embedded insofar as most of the research was conducted while engaged in attending lab meetings and participating in the work of those scientists whose work is the object of my research. (shrink)