Explanation in Neuroscience

The following paper pertains to the area of philosophy of mind. Specifically, this paper examines the debate between the reductionist and the anti reductionist about mechanisms. This topic is elucidated and discussed in the literature of several outstanding philosophers in the field, namely: Bechtel, Couch, Craver and Lipton. It is important to note that this paper takes aim at entity reduction rather than theory reduction and examines two distinct views of levels of entities. This paper will go beyond examining the (...) two views, I will offer my own rationale for why one of the two views is the better way to think about reduction of entities to lower level ones. (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)

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.

Functional robustness refers to a system’s ability to maintain a function in the face of perturbations to the causal structures that support performance of that function. Modularity, a crucial element of standard methods of causal inference and difference-making accounts of causation, refers to the independent manipulability of causal relationships within a system. Functional robustness appears to be at odds with modularity. If a function is maintained despite manipulation of some causal structure that supports that function, then the relationship between that (...) structure and function fails to be manipulable independent of other causal relationships within the system. Contrary to this line of reasoning, I argue that functional robustness often attends feedback control, rather than failures of modularity. Feedback control poses its own challenges to causal explanation and inference, but those challenges do not undermine modularity—and indeed, modularity is crucial to grappling with them. (shrink)

The traditional approach to explanation in cognitive neuroscience is realist about psychological constructs, and treats them as explanatory. On the “standard framework,” cognitive neuroscientists explain behavior as the result of the instantiation of psychological functions in brain activity. This strategy is questioned by results suggesting the distribution of function in the brain, the multifunctionality of individual parts of the brain, and the overlap in neural realization of purportedly distinct psychological constructs. One response to this in the field has been to (...) employ the tools of databasing and machine learning to attempt to find and quantify specific correlations between psychological kinds such as ‘memory’ or ‘attention’ (or sub-kinds thereof) and patterns of activity in the brain. I assess the status and prospects of these projects. I argue that current proponents of the project are vague about their aims, vis-à-vis the standard framework, sometimes suggesting substantiation of the framework, sometimes suggesting retaining the framework but revising the ontology of mental constructs, and sometimes suggesting abandonment of the framework. I argue that extant results from within the projects fail to substantiate the standard framework, and propose an alternative. On my view, psychological constructs should not be viewed as explanantia, but instead as heuristic concepts that help us uncover ways that behaviors can vary and the ways that the brain implements those distinctions. I then discuss the normative upshot of these views for databasing and brain mapping projects. (shrink)

Debate on the nature of representation in cognitive systems tends to oscillate between robustly realist views and various anti-realist options. I defend an alternative view, deflationary realism, which sees cognitive representation as an offshoot of the extended application to cognitive systems of an explanatory model whose primary domain is public representation use. This extended application, justified by a common explanatory target, embodies idealisations, partial mismatches between model and reality. By seeing representation as part of an idealised model, deflationary realism avoids (...) the problems with robust realist views, whilst keeping allegiance to realism. (shrink)

At its core this book is concerned with logic and computation with respect to the mathematical characterization of sentient biophysical structure and its behavior. -/- Three related theories are presented: The first of these provides an explanation of how sentient individuals come to be in the world. The second describes how these individuals operate. And the third proposes a method for reasoning about the behavior of individuals in groups. -/- These theories are based upon a new explanation of experience in (...) nature, the construction of senses, and motile behavior. This new approach is developed from first principles to enable a rigorous and systematic explanation of the variety of associated intelligent behaviors. -/- Alongside this development is a further account that focuses upon the nature of our work. It discusses the existential aspects of scientific inquiry, its epistemology and logic. It seeks to clarify the nature of the mathematical characterization and computation of natural behaviors, dealing with questions in the foundations of logic. It explores methodological issues related to reduction and the refinement of ideas from intuition to formal logical structure. -/- In support of this inquiry we work toward the development of a calculus for biophysical construction and its dynamics. If successful this mechanics mathematically characterizes sensory and motile behavior. -/- Upon this foundation we propose a model of apprehension and explore how its products are processed by the organism. Finally, we develop a probabilistic theory that enables us to reason about inaccessible factors in group behavior. -/- The mechanics we propose suggests the design and physical realization of a new model of computation; one in which structure and the concurrency of action are a first-order consideration. -/- We identify opportunities for experimental verification of the theory and we suggest a proof of our results in practice by the identification of this mechanism, allowing the construction of machines that experience. (shrink)

Neuroscientists are searching for the engram within the conceptual framework established by John Locke's theory of mind. This framework was elaborated before the development of information theory, before the development of information processing machines and the science of computation, before the discovery that molecules carry hereditary information, before the discovery of the codon code and the molecular machinery for editing the messages written in this code and translating it into transcription factors that mark abstract features of organic structure such as (...) anterior and distal. The search for the engram needs to abandon Locke's conceptual framework and work within a framework informed by these developments. The engram is the medium by which information extracted from past experience is transmitted to the computations that inform future behavior. The information-conveying symbols in the engram are rapidly generated in the course of computations, which implies that they are molecules. (shrink)

Over the last decades, network-based approaches have become highly popular in diverse fields of biology, including neuroscience, ecology, molecular biology and genetics. While these approaches continue to grow very rapidly, some of their conceptual and methodological aspects still require a programmatic foundation. This challenge particularly concerns the question of whether a generalized account of explanatory, organisational and descriptive levels of networks can be applied universally across biological sciences. To this end, this highly interdisciplinary theme issue focuses on the definition, motivation (...) and application of key concepts in biological network science, such as explanatory power of distinctively network explanations, network levels, and network hierarchies. (shrink)

This chapter will be a brief survey of the concepts from general philosophy of science for those interested in cognitive science. It covers several major topics in the philosophy of science: scientific explanation and underdetermination, reductionism and levels of nature, and scientific realism. We will discuss the goals of science, the methods of science, and the most plausible interpretations of science. To demonstrate the importance of these topics, the chapter includes cases in which confusion over these issues has led scientists (...) astray. These cases include instances in which cognitive neuroscience has failed to discover adequate explanations for phenomena, when previously established research did not withstand further scrutiny, and the increasingly complex and bewildering interrelationship between the study of the mind and the study of the brain and its parts. These issues are common to many areas of science, but they can be particularly fraught in a field like cognitive neuroscience, as researchers from a wide variety of disciplinary backgrounds and research foci come together to develop a systematic understanding of the mind. (shrink)

In this Handbook entry, I review how colour similarity spaces are constructed, first for physical sources of colour and secondly for colour as it is perceptually experienced. The unique hues are features of one of the latter constructions, due initially to Hering and formalized in the Swedish Natural Colour System. I review the evidence for a physiological basis for the unique hues. Finally, I argue that Tye's realist approach to the unique hues is a mistake.

Neuroclassicism is the view that cognition is explained by “classical” computing mechanisms in the nervous system that exhibit a clear demarcation between processing machinery and read–write memory. The psychologist C. R. Gallistel has mounted a sophisticated defense of neuroclassicism by drawing from ethology and computability theory to argue that animal brains necessarily contain read–write memory mechanisms. This argument threatens to undermine the “connectionist” orthodoxy in contemporary neuroscience, which does not seem to recognize any such mechanisms. In this paper I argue (...) that the neuroclassicist critique rests on a misunderstanding of how computability theory constrains theorizing about natural computing mechanisms. (shrink)

According to a standard view in psychology and neuroscience, there are multiple memory systems in the brain. Philosophers and scientists of memory rely on the idea that there are multiple memory systems in the brain to infer that procedural memory is not a cognitive form of memory. As a result, memory is considered to be a disunified capacity. In this paper, I evaluate two criteria used by Michaelian to demarcate between cognitive and non-cognitive memory systems: appeal to stored content and (...) retrieval flexibility. By considering several empirical cases I argue that the criteria offered ultimately fail to distinguish between memory systems. The procedural memory the system is neither contentless nor inflexible. (shrink)

In this paper, I suggest that some tales developed in the literature of embodied and radical embodied cognitive science can contribute to the solution of two longstanding issues in the cognitive neuroscience of perception and action. The two issues are the fundamental problem of perception, or how to bridge the gap between sensations and the environment, and the fundamental problem of motor control, or how to better characterize the relationship between brain activity and behavior. In both cases, I am going (...) to propose that cognitive neuroscience could incorporate embodied insights—coming from the sensorimotor approach to perception and action, and from ecological psychology—to advance the solution for each issue without the need for abandoning or undergoing a substantial revision of its core assumptions. Namely, cognitive neuroscience could incorporate the forgotten tales of embodiment without undergoing through a complete revolution. In this sense, I am proposing not a call but a farewell to arms. (shrink)

The readiness potential (RP), a slow buildup of electrical potential recorded at the scalp using electroencephalography, has been associated with neural activity involved in movement preparation. It became famous thanks to Benjamin Libet (Brain 1983;106:623–642), who used the time difference between the RP and self-reported time of conscious intention to move to argue that we lack free will. The RP’s informativeness about self-generated action and derivatively about free will has prompted continued research on this neural phenomenon. Here, we argue that (...) recent advances in our understanding of the RP, including computational modeling of the phenomenon, call for a reassessment of its relevance for understanding volition and the philosophical problem of free will. (shrink)

This chapter provides an overview of the basic research strategies and analytic techniques deployed in computational cognitive neuroscience. On the one hand, “top-down” strategies are used to infer, from formal characterizations of behavior and cognition, the computational properties of underlying neural mechanisms. On the other hand, “bottom-up” research strategies are used to identify neural mechanisms and to reconstruct their computational capacities. Both of these strategies rely on experimental techniques familiar from other branches of neuroscience, including functional magnetic resonance imaging, single-cell (...) recording, and electroencephalography. What sets computational cognitive neuroscience apart, however, is the explanatory role of analytic techniques from disciplines as varied as computer science, statistics, machine learning, and mathematical physics. These techniques serve to describe neural mechanisms computationally, but also to drive the process of scientific discovery by influencing which kinds of mechanisms are most likely to be identified. For this reason, understanding the nature and unique appeal of computational cognitive neuroscience requires not just an understanding of the basic research strategies that are involved, but also of the formal methods and tools that are being deployed, including those of probability theory, dynamical systems theory, and graph theory. (shrink)

Over the last 30 years, representationalist and dynamicist positions in the philosophy of cognitive science have argued over whether neurocognitive processes should be viewed as representational or not. Major scientific and technological developments over the years have furnished both parties with ever more sophisticated conceptual weaponry. In recent years, an enactive generalization of predictive processing – known as active inference – has been proposed as a unifying theory of brain functions. Since then, active inference has fueled both representationalist and dynamicist (...) campaigns. However, we believe that when diving into the formal details of active inference, one should be able to find a solution to the war; if not a peace treaty, surely an armistice of a sort. Based on an analysis of these formal details, this paper shows how both representationalist and dynamicist sensibilities can peacefully coexist within the new territory of active inference. (shrink)

I propose a dynamic causal approach to characterizing the notion of a mechanism. Levy and Bechtel, among others, have pointed out several critical limitations of the new mechanical philosophy, and pointed in a new direction to extend this philosophy. Nevertheless, they have not fully fleshed out what that extended philosophy would look like. Based on a closer look at neuroscientific practice, I propose that a mechanism is a dynamic causal system that involves various components interacting, typically nonlinearly, with one another (...) to produce a phenomenon of interest. (shrink)

Proponents of ontic conceptions of explanation require all explanations to be backed by causal, constitutive, or similar relations. Among their justifications is that only ontic conceptions can do justice to the ‘directionality’ of explanation, i.e., the requirement that if X explains Y , then not-Y does not explain not-X . Using topological explanations as an illustration, we argue that non-ontic conceptions of explanation have ample resources for securing the directionality of explanations. The different ways in which neuroscientists rely on multiplexes (...) involving both functional and anatomical connectivity in their topological explanations vividly illustrate why ontic considerations are frequently (if not always) irrelevant to explanatory directionality. Therefore, directionality poses no problem to non-ontic conceptions of explanation. (shrink)

The discovery of the engram, the physical substrate of memory, is a central challenge for the sciences of memory. Following the application of optogenetics to the neurobiological study of memory, scientists and philosophers claim that the engram has been found. In this paper, I evaluate the implications of applying optogenetic tools to the localization of the engram. I argue that conceptions of engram localization need to be revised to be made consistent with optogenetic studies of the engram. I distinguish between (...) challenges to vehicle and content localization. First, I consider the silent engram hypothesis. According to this hypothesis, optogenetic studies indicate that synaptic efficacy, the traditional engram-bearing vehicle, is important merely for retrieval. I argue that this interpretation rests upon a misunderstanding of accessibility. Second, I argue that optogenetic-based strategies and findings conflict with preservationist and constructivist views on memory storage. There is an enduring trace, but stored content may change over time and experience, resulting in doubt about what constitutes a single engram. (shrink)

Optogenetics and DREADDs (Designer Receptors Exclusively Activated by Designer Drugs) are important research tools in recent neurobiology. These tools allow unprecedented control over activity in specifically targeted neurons in behaving animals. Two approaches in philosophy of neuroscience, mechanism and ruthless reductionism, provide explicit accounts of experiments and results using tools like these, but each offers a different picture about how levels of mechanisms relate. I argue here that the ruthless reductionist’s direct mind‐to‐cellular/molecular activities linkages “in a single bound” better fits (...) with both the experimental designs using these tools and some of the scientists’ own judgments about their results than does the mechanist’s “nested hierarchies of mechanisms‐within‐mechanisms.” So at least some important work in current neuroscience appears to be ruthlessly reductive. Mechanism may not correctly characterize all current work in neuroscience, despite its recent popularity. (shrink)

An estimated 15% of patients seen by neurologists have neurological symptoms, such as paralysis, tremors, dystonia, or seizures, that cannot be medically explained. For a long time, such patients were diagnosed as having conversion disorder and referred to psychiatrists, but for the last two decades or so, neurologists have started to pay more serious attention to this patient group. Instead of maintaining the commonly used label of conversion disorder – which refers to Freud’s idea that traumatic events can be converted (...) into deviant behaviour – these neurologists use the term functional neurological disorder and explain that the problems are due to abnormal central nervous system functioning. The situation that some patients with medically unexplained neurological symptoms are diagnosed with CD and treated by psychiatrists while others are diagnosed with FND and stay under the control of neurologists provides a unique case for analysing how neurological and psychological explanations affect subjectivity. In this article, I compare patient reports from English-language websites from the past 15 years to find out how minds, bodies, brains, and selves act and interact in the accounts of both patient groups. I conclude that the change in label from CD to FND has not only influenced ideas of medically unexplained disorders, but also affected ideas of the self and the body; of self-control and accountability. (shrink)

Philosophical proponents of predictive processing cast the novelty of predictive models of perception in terms of differences in the functional role and information content of neural signals. However, they fail to provide constraints on how the crucial semantic mapping from signals to their informational contents is determined. Beyond a novel interpretative gloss on neural signals, they have little new to say about the causal structure of the system, or even what statistical information is carried by the signals. That means that (...) the predictive framework for perception can be relabeled in traditional, non-predictive terms, with no empirical consequences relevant to existing or future data. To the extent that neuroscientific research based on predictive processing is both innovative and productive, it will be due to the framework’s suggestive heuristic effects, or perhaps auxiliary empirical claims about implementation, rather than a difference in the information-processing structure that it describes. (shrink)

A cognitive assessment strategy that is not limited to examining a set of summary test scores may be more helpful for early detection of emergent illness such as Alzheimer’s disease (AD) and may permit a better understanding of cognitive functions and dysfunctions in those with AD and other dementia disorders. A revisit of the work already undertaken by Kaplan and colleagues using the Boston Process-Approach provides a solid basis for identifying new opportunities to capture data on neurocognitive processes, test-taking strategies (...) and response styles. Thus, this critical review will combine traditional process-based assessment strategies with support provided or offered by newer technologies that have the potential to add value to data collection and interpretation. There is now considerable interest in neuropsychological test administration using computer/digital technology, both in research and in clinical settings. To add value, any computerized version of an existing cognitive test should respect the administration procedure for which normative data were obtained, should be time-saving in terms of scoring and interpretation, and should, we argue, facilitate gathering information about the processes and strategies followed in test completion. This article will offer an overview of the steps needed when implementing computerization of neuropsychological tests using a Process-Based Approach (PBA) to these technology-based adaptations and will discuss further developments in this area by linking it to future technological developments that may be possible in the area of neuropsychological assessment. Additionally, an overview of neuropsychological tests that may benefit from computerization will be presented, together with suggestions on the specific processes, strategies and features that may be captured with the aid of such computerization. Finally, hypotheses on how virtual reality could be an asset for the future of the PBA to neuropsychological assessment will also be discussed. (shrink)

Although there is a substantial philosophical literature on dynamical systems theory in the cognitive sciences, the same is not the case for neuroscience. This paper attempts to motivate increased discussion via a set of overlapping issues. The first aim is primarily historical and is to demonstrate that dynamical systems theory is currently experiencing a renaissance in neuroscience. Although dynamical concepts and methods are becoming increasingly popular in contemporary neuroscience, the general approach should not be viewed as something entirely new to (...) neuroscience. Instead, it is more appropriate to view the current developments as making central again approaches that facilitated some of neuroscience’s most significant early achievements, namely, the Hodgkin–Huxley and FitzHugh–Nagumo models. The second aim is primarily critical and defends a version of the “dynamical hypothesis” in neuroscience. Whereas the original version centered on defending a noncomputational and nonrepresentational account of cognition, the version I have in mind is broader and includes both cognition and the neural systems that realize it as well. In view of that, I discuss research on motor control as a paradigmatic example demonstrating that the concepts and methods of dynamical systems theory are increasingly and successfully being applied to neural systems in contemporary neuroscience. More significantly, such applications are motivating a stronger metaphysical claim, that is, understanding neural systems as being dynamical systems, which includes not requiring appeal to representations to explain or understand those phenomena. Taken together, the historical claim and the critical claim demonstrate that the dynamical hypothesis is undergoing a renaissance in contemporary neuroscience. (shrink)

Researchers in the cognitive sciences often seek neural correlates of psychological constructs. In this paper, I argue that even when these correlates are discovered, they do not always lead to reductive outcomes. To this end, I examine the psychological construct of a critical period and briefly describe research identifying its neural correlates. Although the critical period is correlated with certain neural mechanisms, this does not imply that there is a reductionist relationship between this psychological construct and its neural correlates. Instead, (...) this case study suggests that there may be many-to-many psychological-neural mappings, not just one-to-one or even one-to-many relations between psychological kinds and types of neural mechanisms. (shrink)

ABSTRACT LeDoux's pioneering work on the neurobiology of fear has played a crucial role in informing debates in the philosophy of emotion. For example, it plays a key part in Griffiths’ argument for why emotions don’t form a natural kind. Likewise, it is employed by Faucher and Tappolet to defend pro-emotion views, which claim that emotions aid reasoning. LeDoux, however, now argues that his work has been misread. He argues that using emotion terms, like ‘fear’, to describe neurocognitive data adds (...) a ‘surplus meaning’: it attributes phenomenal properties to survival circuits which they don’t possess. This paper aims to explore LeDoux's new proposal, and examine the potentially devastating consequences that ensue for the aforementioned views. I end by addressing the worry that these lessons are conditional on LeDoux's own higher-order theory of emotional consciousness being true. (shrink)

There is a vast literature within philosophy of mind that focuses on artificial intelligence, but hardly mentions methodological questions. There is also a growing body of work in philosophy of science about modeling methodology that hardly mentions examples from cognitive science. Here these discussions are connected. Insights developed in the philosophy of science literature about the importance of idealization provide a way of understanding the neural implausibility of connectionist networks. Insights from neurocognitive science illuminate how relevant similarities between models and (...) targets are picked out, how modeling inferences are justified, and the metaphysical status of models. (shrink)

This paper examines the explanatory distinctness of wiring optimization models in neuroscience. Wiring optimization models aim to represent the organizational features of neural and brain systems as optimal (or near-optimal) solutions to wiring optimization problems. My claim is that that wiring optimization models provide design explanations. In particular, they support ideal interventions on the decision variables of the relevant design problem and assess the impact of such interventions on the viability of the target system.

Joint actions often require agents to track others’ actions while planning and executing physically incongruent actions of their own. Previous research has indicated that this can lead to visuomotor interference effects when it occurs outside of joint action. How is this avoided or overcome in joint actions? We hypothesized that when joint action partners represent their actions as interrelated components of a plan to bring about a joint action goal, each partner’s movements need not be represented in relation to distinct, (...) incongruent proximal goals. Instead they can be represented in relation to a single proximal goal – especially if the movements are, or appear to be, mechanically linked to a more distal joint action goal. To test this, we implemented a paradigm in which participants produced finger movements that were either congruent or incongruent with those of a virtual partner, and either with or without a joint action goal (the joint flipping of a switch, which turned on two light bulbs). Our findings provide partial support for the hypothesis that visuomotor interference effects can be reduced when two physically incongruent actions are represented as mechanically interdependent contributions to a joint action goal. (shrink)

Introduction: The objective of this investigation is to analyse the informational circuits of the brain connections with the body from neurologic and neuroscience point of view, on the basis of the concepts of information promoted by the Informational Model of Consciousness. Analysis: Distinguishing between the virtual and matter-related information promoted by the Informational Model of Consciousness, the main specific features of consciousness are analyzed from the informational perspective, showing that the informational architecture of consciousness consists in seven groups of specific (...) activities, defined as cognitive centres, each of them with specific distinct tasks, but correlated each other: centre of acquisition and storing of information (memory), centre of decision and command (decision), centre of the emotional states (emotions), centre of the body maintenance (power and health), centre of the genetic elaboration/transmission (reproduction) and the info-genetic generator, inherited from the parents (predispositions, talents and skills). A special centre, dedicated to the connectivity with some extra-power properties of the mind is also introduced, assuring an intimate supra-sensitive detection of the world to explain the associated phenomena of the near-death experiences. Result: The activity of all these centres should be supported neurologically by the brain neuro-connectivity to the body and to external and internal info-signals. On the basis of the informational analysis, the neuro-connections of the brain regions associated to the main characteristics of the cognitive centres are highlighted, showing the anatomic and neuro-functional relation between the distinct components of the brain and the specific operating body regions. These connections describe in terms of information the brain-body neuro-activities as informational specific circuits, composed by the info-operational subsystems managed by the brain, and sensors, transducer and execution elements. Conclusion: The components and connections mind-body stipulated by the Informational Model of Consciousness are supported by the neurologic/neuroscience evidence. (shrink)

Integrated information theory is a theory of consciousness that was originally formulated, and is standardly still expressed, in terms of controversial interpretations of its own ontological and epistemological basis. These form the orthodox interpretation of IIT. The orthodox epistemological interpretation is the axiomatic method, whereby IIT is ultimately derived from, justified by, and beholden to a set of phenomenological axioms. The orthodox ontological interpretation is panpsychism, according to which consciousness is fundamental, intrinsic, and pervasive. In this paper it is argued (...) that both components of the orthodox interpretation should be rejected. But IIT should not be rejected since an interpretation-neutral formulation is available. After explaining the neutral formulation, more plausible non-axiomatic epistemologies are defended. The neutral formulation is then shown to be consistent with various contemporary physicalist ontologies of consciousness, including the phenomenal concept strategy, representationalism, and even illusionism. Along the way, instructive connections between interpretations of IIT and interpretations of quantum mechanics are noted. (shrink)

La hipótesis del marcador somático (SMH) ha sido una de las teorías más influyentes en las neurociencias desde principios de los años 90s en que fue formulada por Antonio Damasio en su libro El error de Descartes (1994). Desde entonces, diversos estudios, a favor y en contra se han escrito, sin un veredicto. En este trabajo se propone una explicación abarcadora de lo que es la hipótesis del marcador somático. En segundo lugar, se hace una valoración sucinta del peso que (...) la amígdala pueda tener en el proceso de toma de decisiones inconscientes. En contraste, se citan algunos resultados que apuntan que la corteza prefrontal ventromedial estaría comprometida con nuestras decisiones racionales. Finalmente, se recuperan algunas críticas de otros investigadores a la hipótesis del marcador somático a partir de resultados mixtos obtenidos en el juego de azar y apuestas de Iowa. Se concluye que la mayor valía de la SMH es haber terminado con la dualidad cerebro-cuerpo, pero que la hipótesis por sí misma, no es suficiente para sostener que el proceso de toma de decisiones se realice principalmente a partir de lo que sentimos. El proceso de toma de decisiones, si bien se vale de respuestas inconscientes somatosensoriales, es un proceso físico-emocional-racional más complejo, que carece aún de suficientes evidencias para ser situado. The somatic marker hypothesis (SMH) has been one of the most influential theories in the neurosciences since the early 1990s, when it was formulated by Antonio Damasio in his book Descartes’ Error (1994). Since then, various studies, for and against, have been written without a verdict. Firstly, this study provides a comprehensive explanation of the SMH. Secondly, it provides a detailed assessment of the relevance of the amygdala in the process of making unconscious decisions. In contrast, we cite some results that suggest that the ventromedial prefrontal cortex would be involved in our rational decisions. Finally, we review some of the criticism of the SMH that was based on the mixed results obtained in the Iowa Gambling Task. We suggest that the main value of the SMH is that it resolves the brain-body duality problem. However, the hypothesis by itself is insufficient to claim that the decision-making process is mainly based on our feelings. Although the decision-making process uses unconscious somatosensory responses, it is a more complex physical-emotional-rational process, which still lacks sufficient evidence to be located. (shrink)

Autonomist accounts of cognitive science suggest that cognitive model building and theory construction (can or should) proceed independently of findings in neuroscience. Common functionalist justifications of autonomy rely on there being relatively few constraints between neural structure and cognitive function (e.g., Weiskopf, 2011). In contrast, an integrative mechanistic perspective stresses the mutual constraining of structure and function (e.g., Piccinini & Craver, 2011; Povich, 2015). In this paper, I show how model-based cognitive neuroscience (MBCN) epitomizes the integrative mechanistic perspective and concentrates (...) the most revolutionary elements of the cognitive neuroscience revolution (Boone & Piccinini, 2016). I also show how the prominent subset account of functional realization supports the integrative mechanistic perspective I take on MBCN and use it to clarify the intralevel and interlevel components of integration. (shrink)

Similarity-based cognition is commonplace. It occurs whenever an agent or system exploits the similarities that hold between two or more items—e.g., events, processes, objects, and so on—in order to perform some cognitive task. This kind of cognition is of special interest to cognitive neuroscientists. This paper explicates how similarity-based cognition can be understood through the lens of radical enactivism and why doing so has advantages over its representationalist rival, which posits the existence of structural representations or S-representations. Specifically, it is (...) argued that there are problems both with accounting for the content of S-representations and with understanding how neurally-based structural similarities can work as representations in guiding intelligent behavior. Finally, with these clarifications in place, it is revealed how radical enactivism can commit to an account of similarity-based cognition in its understanding of neurodynamics. (shrink)

I will review the most widely held account of phantom sensations; the “re-mapping hypothesis.” According to the re-mapping hypothesis, amputation is followed by significant neural reorganization that, over time, restores the alignment between the brain’s representation of and the actual condition of the body. Implicit in the re-mapping hypothesis is the view that the brain’s primary function is to accurately represent the body. In response, I propose an alternative theory, the “preservation hypothesis.” The preservation hypothesis argues that the primary function (...) of the brain is to preserve the entirety of the brain’s structures and functional capacities. While these issues concern empirical matters, assessing our views on the subject discloses deeply held assumptions regarding the brain’s primary function; does the brain operate to provide an accurate representation of the body? Or, does the brain operate solely to preserve its structures and functional capacities in their entirety? (shrink)

In both philosophy and the sciences of the mind there is a shared commitment to the idea that there is a center— the seat of consciousness, the source of deliberation and reflection, and the core of personal identity —in the mind. My dissertation challenges this deeply entrenched view. I review the empirical literature on working memory, psychology’s best candidate for the workspace of the mind, and argue that it is not a natural kind and cannot inform these central cognitive processes. (...) This deflationary view directly imperils many naturalistic theories of consciousness that rely on working memory, which are reviewed in this project. This dissertation thus serves as the necessary first negative step required to begin the process of articulating socially-embedded accounts of many central cognitive processes that dominate the contemporary philosophical literature, including consciousness and reasoning. (shrink)

In fMRI research, the goal of correcting for multiple comparisons is to identify areas of activity that reflect true effects, and thus would be expected to replicate in future studies. Finding an appropriate balance between trying to minimize false positives (Type I error) while not being too stringent and omitting true effects (Type II error) can be challenging. Furthermore, the advantages and disadvantages of these types of errors may differ for different areas of study. In many areas of social neuroscience (...) that involve complex processes and considerable individual differences, such as the study of moral judgment, effects are typically smaller and statistical power weaker, leading to the suggestion that less stringent corrections that allow for more sensitivity may be beneficial, but also result in more false positives. Using moral judgment fMRI data, we evaluated four commonly used methods for multiple comparison correction implemented in SPM12 by examining which method produced the most precise overlap with results from a meta-analysis of relevant studies and with results from nonparametric permutation analyses. We found that voxel-wise thresholding with family-wise error correction based on Random Field Theory provides a more precise overlap (i.e., without omitting too few regions or encompassing too many additional regions) than either clusterwise thresholding, Bonferroni correction, or false discovery rate correction methods. (shrink)

In this paper, I argue that looking at the concept of neural function through the lens of cognition alone risks cognitive myopia: it leads neuroscientists to focus only on mechanisms with cognitive functions that process behaviorally relevant information when conceptualizing “neural function”. Cognitive myopia tempts researchers to neglect neural mechanisms with noncognitive functions which do not process behaviorally relevant information but maintain and repair neural and other systems of the body. Cognitive myopia similarly affects philosophy of neuroscience because scholars overlook (...) noncognitive functions when analyzing issues surrounding e.g., functional decomposition or the multifunctionality of neural structures. I argue that we can overcome cognitive myopia by adopting a patchwork approach that articulates cognitive and noncognitive “patches” of the concept of neural function. Cognitive patches describe mechanisms with causally specific effects on cognition and behavior which are likely operative in transforming sensory or other inputs into motor outputs. Noncognitive patches describe mechanisms that lack such specific effects; these mechanisms are enabling conditions for cognitive functions to occur. I use these distinctions to characterize two noncognitive functions at the mesoscale of neural circuits: subsistence functions like breathing are implemented by central pattern generators and are necessary to maintain the life of the organism. Infrastructural functions like gain control are implemented by canonical microcircuits and prevent neural system damage while cognitive processing occurs. By adding conceptual patches that describe these functions, a patchwork approach can overcome cognitive myopia and help us explain how the brain’s capacities as an information processing device are constrained by its ability to maintain and repair itself as a physiological apparatus. (shrink)

In this paper, I argue that the newly developed network approach in neuroscience and biology provides a basis for formulating a unique type of realization, which I call topological realization. Some of its features and its relation to one of the dominant paradigms of realization and explanation in sciences, i.e. the mechanistic one, are already being discussed in the literature. But the detailed features of topological realization, its explanatory power and its relation to another prominent view of realization, namely the (...) semantic one, have not yet been discussed. I argue that topological realization is distinct from mechanistic and semantic ones because the realization base in this framework is not based on local realisers, regardless of the scale but on global realizers. In mechanistic approach, the realization base is always at the local level, in both ontic and epistemic accounts. The explanatory power of realization relation in mechanistic approach comes directly from the realization relation-either by showing how a model is mapped onto a mechanism, or by describing some ontic relations that are explanatory in themselves. Similarly, the semantic approach requires that concepts at different scales logically satisfy microphysical descriptions, which are at the local level. In topological framework the realization base can be found at different scales, but whatever the scale the realization base is global, within that scale, and not local. Furthermore, topological realization enables us to answer the “why” questions, which according to Polger 2010 make it explanatory. The explanatoriness of topological realization stems from understanding mathematical consequences of different topologies, not from the mere fact that a system realizes them. (shrink)

Constitutive mechanistic explanations are said to refer to mechanisms that constitute the phenomenon-to-be-explained. The most prominent approach of how to understand this constitution relation is Carl Craver’s mutual manipulability approach to constitutive relevance. Recently, the mutual manipulability approach has come under attack (Leuridan 2012; Baumgartner and Gebharter 2015; Romero 2015; Harinen 2014; Casini and Baumgartner 2016). Roughly, it is argued that this approach is inconsistent because it is spelled out in terms of interventionism (which is an approach to causation), whereas (...) constitutive relevance is said to be a non-causal relation. In this paper, I will discuss a strategy of how to resolve this inconsistency, so-called fat-handedness approaches (Baumgartner and Gebharter 2015; Casini and Baumgartner 2016; Romero 2015). I will argue that these approaches are problematic. I will present a novel suggestion of how to consistently define constitutive relevance in terms of interventionism. My approach is based on a causal interpretation of mutual manipulability, where manipulability is interpreted as a causal relation between the mechanism’s components and temporal parts of the phenomenon. (shrink)

Replicability and reproducibility of computational models has been somewhat understudied by “the replication movement.” In this paper, we draw on methodological studies into the replicability of psychological experiments and on the mechanistic account of explanation to analyze the functions of model replications and model reproductions in computational neuroscience. We contend that model replicability, or independent researchers' ability to obtain the same output using original code and data, and model reproducibility, or independent researchers' ability to recreate a model without original code, (...) serve different functions and fail for different reasons. This means that measures designed to improve model replicability may not enhance (and, in some cases, may actually damage) model reproducibility. We claim that although both are undesirable, low model reproducibility poses more of a threat to long-term scientific progress than low model replicability. In our opinion, low model reproducibility stems mostly from authors' omitting to provide crucial information in scientific papers and we stress that sharing all computer code and data is not a solution. Reports of computational studies should remain selective and include all and only relevant bits of code. (shrink)

We situate the debate on intentionality within the rise of cognitive neuroscience and argue that cognitive neuroscience can explain intentionality. We discuss the explanatory significance of ascribing intentionality to representations. At first, we focus on views that attempt to render such ascriptions naturalistic by construing them in a deflationary or merely pragmatic way. We then contrast these views with staunchly realist views that attempt to naturalize intentionality by developing theories of content for representations in terms of information and biological function. (...) We echo several other philosophers by arguing that these theories over-generalize unless they are constrained by a theory of the functional role of representational vehicles. This leads to a discussion of the functional roles of representations, and how representations might be realized in the brain. We argue that there’s work to be done to identify a distinctively mental kind of representation. We close by sketching a way forward for the project of naturalizing intentionality. This will not be achieved simply by ascribing the content of mental states to generic neural representations, but by identifying specific neural representations that explain the puzzling intentional properties of mental states. (shrink)

Some recent arguments defending the genuine causal efficacy of the mental have been relying on empirical research on neuroprosthetics. This essay presents a critical analysis of these arguments. The problem of mental causation, and the basic idea and results of neuroprosthetics are reviewed. It is shown how appealing to the research on neuroprosthetics can be interpreted to give support to the idea of mental causation. However, it does so only in a rather deflationary sense: by holding the mental identical with (...) the neural. So contrary to what the arguments have been assuming, neuroprosthetics cannot be used to argue for nonreductive physicalism. It can rather be taken to illustrate just the opposite: how the mental and the physical are identical. (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)

This paper considers the way mathematical and computational models are used in network neuroscience to deliver mechanistic explanations. Two case studies are considered: Recent work on klinotaxis by Caenorhabditis elegans, and a longstanding research effort on the network basis of schizophrenia in humans. These case studies illustrate the various ways in which network, simulation and dynamical models contribute to the aim of representing and understanding network mechanisms in the brain, and thus, of delivering mechanistic explanations. After outlining this mechanistic construal (...) of network neuroscience, two concerns are addressed. In response to the concern that functional network models are non-explanatory, it is argued that functional network models are in fact explanatory mechanism sketches. In response to the concern that models which emphasize a network’s organization over its composition do not explain mechanistically, it is argued that this emphasis is both appropriate and consistent with the principles of mechanistic explanation. What emerges is an improved understanding of the ways in which mathematical and computational models are deployed in network neuroscience, as well as an improved conception of mechanistic explanation in general. (shrink)