Deus et machina

Diese Arbeit zeigt unter einem naturwissenschafltichen Blickwinkel, wie und warum jede materialistische Theorie des Geistes, warum ein physikalischer Monismus unhaltbar ist und damit auch das Verständnis des Gehirns unmöglich macht. Mit Hilfe einer *vollständigen* Computer-Analogie legt die Arbeit dar, wie Gehirn und Geist, wie ein interaktionistischer Dualismus verstanden werden kann.This work demonstrates from a scientific point of view why any materialistic theory of mind, why any physical monism is inadequate and thus disables as well the possibility to understand the brain. With the support of a *complete* computer analogy the work outlines further on how it could be possible to understand dualism and thus an interaction between mind and brain

Computers, Brains and Minds: Where are the ghosts within the machines?

Abstract This work opens a new perspective in the debate regarding the relationship between brain and mind. It puts the central question whether in our days, dominated by a scientific view of the world, we really do have an adequate idea of what could be actually meant by terms like "mind", "self" or even "perceptions". Based on the consideration that any "non-material" or "mind" stuff can never be able to move particles around the world we found ourselves forced to believe in a physical monism as the premise for all plausible theories of mind. However, now we face different but still persisting kinds of problems: Why do we have "phenomenal" states? Do we really have them at all? How could phenomenal states be related to neuronal states? The still ongoing heavy debates about these issues demonstrate at least one thing: So far there is no commonly accepted explanation detectable at the horizon. To understand all scientifically possible relationships between the world, the brain, perceptions and what some people tend to call "self" we suggest the support of a "Complete Computer Analogy" (CCA). The CCA takes all relevant aspects of human and "computer" life into account: Neuronal states (or binary states for the computer), phenomenal states (or the screen for the computer) and the connections brains and computers have to "the world": Exemplarily visual and auditory interfaces i.e. eyes and ears for our brains, a scanner and a microphone for the computer. Empirical evidence (e.g. the famous "color phi" experiment) demonstrates in the first instance the necessary differentiation between phenomenal states, neuronal states and the "outside world" though they are of course correlated, as are the screen, the computer and "his" world. Further on we are able to consider different options for the realization of the "self" within this analogy and according empirical hints (i.e. neurological diseases, empirical findings around the issue of "free will" and "attention"). These investigations finally reveal an astonishing aspect: It is possible to understand an interactive substance dualism based on a scientific view of the world but beyond the idea of a ghost moving particles around the brain

Neurons and the synaptic basis of the fMRI signal associated with cognitive flexibility

The Wisconsin Card Sorting Test (WCST) is well known to test cognitive flexibility in terms of set-shifting capabilities. Many fMRI studies with behaving monkeys as well as human subjects have shown transient neural activity in the Prefrontal Cortex (PFC), as indicated by an increase in the fMRI signal, following a rule change in the WCST or when using a WCST-like paradigm. We present a computational model, covering a limited number of PFC neurons and using precise biophysical descriptions, which is able to simulate WCS-like tests. Further, the detailed neuronal representation of the model allows us to calculate the resulting fMRI signal. Thus, we are able to analyze the adequacy of the model and its structure by comparing the calculated fMRI signal with the experimental data which in turn provides promising insights into the neural base of the increase in the fMRI signal

Perceptual learning with perceptions

In this work we present an approach to understand neuronal mechanisms underlying perceptual learning. Experimental results achieved with stimulus patterns of coherently moving dots are considered to build a simple neuronal model. The design of the model is made transparent and underlying behavioral assumptions made explicit. The key aspect of the suggested neuronal model is the learning algorithm used: We evaluated an implementation of Hebbian learning and are thus able to provide a straight-forward model capable to explain the neuronal dynamics underlying perceptual learning. Moreover, the simulation results suggest a very simple explanation for the aspect of “sub-threshold” learning (Watanabe et al. in Nature 413:844–884, 2001) as well as the relearning of motion discrimination after damage to primary visual cortex as recently reported (Huxlin et al. in J Neurosci 29:3981–3991, 2009) and at least indicate that perceptual learning might only occur when accompanied by conscious percepts

Cantilever-like micromechanical sensors

The field of cantilever-based sensing emerged in the mid-1990s and is today a well-known technology for label-free sensing which holds promise as a technique for cheap, portable, sensitive and highly parallel analysis systems. The research in sensor realization as well as sensor applications has increased significantly over the past 10 years. In this review we will present the basic modes of operation in cantilever-like micromechanical sensors and discuss optical and electrical means for signal transduction. The fundamental processes for realizing miniaturized cantilevers are described with focus on silicon- and polymer-based technologies. Examples of recent sensor applications are given covering such diverse fields as drug discovery, food diagnostics, material characterizations and explosives detection

La \uabmetaf\uedsica de la experiencia interior\ubb clave teor\ue9tica de la estructura relacional de la persona.

Riflessione sull'esperienza interiore come esperienza metafisica della relazionalit\ue0 accessibile all'essere uman