Productive Theory-Ladenness in fMRI

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

On the primacy and irreducible nature of first-person versus third-person information

In\ua0this\ua0essay,\ua0we\ua0will\ua0support\ua0the\ua0claim\ua0that\ua0at\ua0the\ua0current\ua0level\ua0of\ua0scientific advancement\ua0a)\ua0some\ua0first-person\ua0accounts\ua0cannot\ua0be\ua0reduced\ua0to\ua0their third-person\ua0neural\ua0and\ua0psychophysiological\ua0correlates\ua0and\ua0b)\ua0that\ua0these first-person\ua0accounts\ua0are\ua0the\ua0only\ua0information\ua0to\ua0reckon\ua0when\ua0it\ua0is\ua0necessary\ua0to analyse\ua0qualia\ua0contents. Consequently,\ua0for\ua0many\ua0phenomena,\ua0first-person\ua0accounts\ua0are\ua0the\ua0only\ua0reliable source\ua0of\ua0information\ua0available\ua0and\ua0the\ua0knowledge\ua0of\ua0their\ua0neural\ua0and psychophysical\ua0correlates\ua0don\u2019t\ua0offer\ua0any\ua0additional\ua0information\ua0about\ua0them

Getting to know you: Accuracy and error in judgments of character

Character judgments play an important role in our everyday lives. However, decades of empirical research on trait attribution suggest that the cognitive processes that generate these judgments are prone to a number of biases and cognitive distortions. This gives rise to a skeptical worry about the epistemic foundations of everyday characterological beliefs that has deeply disturbing and alienating consequences. In this paper, I argue that this skeptical worry is misplaced: under the appropriate informational conditions, our everyday character-trait judgments are in fact quite trustworthy. I then propose a mindreading-based model of the socio-cognitive processes underlying trait attribution that explains both why these judgments are initially unreliable, and how they eventually become more accurate

Reflexive Monism

Reflexive monism is, in essence, an ancient view of how consciousness relates to the material world that has, in recent decades, been resurrected in modern form. In this paper I discuss how some of its basic features differ from both dualism and variants of physicalist and functionalist reductionism, focusing on those aspects of the theory that challenge deeply rooted presuppositions in current Western thought. I pay particular attention to the ontological status and seeming “out-thereness” of the phenomenal world and to how the “phenomenal world” relates to the “physical world”, the “world itself”, and processing in the brain. In order to place the theory within the context of current thought and debate, I address questions that have been raised about reflexive monism in recent commentaries and also evaluate competing accounts of the same issues offered by “transparency theory” and by “biological naturalism”. I argue that, of the competing views on offer, reflexive monism most closely follows the contours of ordinary experience, the findings of science, and common sense

Productive Theory-Ladenness in fMRI

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

Productive Theory-Ladenness in fMRI

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 that may arise in the use of fMRI. 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

Cross-Validation of Functional MRI and Paranoid-Depressive Scale: Results From Multivariate Analysis.

Introduction: There exists over the past decades a constant debate driven by controversies in the validity of psychiatric diagnosis. This debate is grounded in queries about both the validity and evidence strength of clinical measures. Materials and Methods: The objective of the study is to construct a bottom-up unsupervised machine learning approach, where the brain signatures identified by three principal components based on activations yielded from the three kinds of diagnostically relevant stimuli are used in order to produce cross-validation markers which may effectively predict the variance on the level of clinical populations and eventually delineate diagnostic and classification groups. The stimuli represent items from a paranoid-depressive self-evaluation scale, administered simultaneously with functional magnetic resonance imaging (fMRI). Results: We have been able to separate the two investigated clinical entities - schizophrenia and recurrent depression by use of multivariate linear model and principal component analysis. Following the individual and group MLM, we identified the three brain patterns that summarized all the individual variabilities of the individual brain patterns. Discussion: This is a confirmation of the possibility to achieve bottom-up classification of mental disorders, by use of the brain signatures relevant to clinical evaluation tests