On Constructive Connectives and Systems

Canonical inference rules and canonical systems are defined in the framework of non-strict single-conclusion sequent systems, in which the succeedents of sequents can be empty. Important properties of this framework are investigated, and a general non-deterministic Kripke-style semantics is provided. This general semantics is then used to provide a constructive (and very natural), sufficient and necessary coherence criterion for the validity of the strong cut-elimination theorem in such a system. These results suggest new syntactic and semantic characterizations of basic constructive connectives

A neural model for the visual tuning properties of action-selective neurons

SUMMARY: The recognition of actions of conspecifics is crucial for survival and social interaction. Most current models on the recognition of transitive (goal-directed) actions rely on the hypothesized role of internal motor simulations for action recognition. However, these models do not specify how visual information can be processed by cortical mechanisms in order to be compared with such motor representations. This raises the question how such visual processing might be accomplished, and in how far motor processing is critical in order to account for the visual properties of action-selective neurons.
We present a neural model for the visual processing of transient actions that is consistent with physiological data and that accomplishes recognition of grasping actions from real video stimuli. Shape recognition is accomplished by a view-dependent hierarchical neural architecture that retains some coarse position information on the highest level that can be exploited by subsequent stages. Additionally, simple recurrent neural circuits integrate effector information over time and realize selectivity for temporal sequences. A novel mechanism combines information about the shape and position of object and effector in an object-centered frame of reference. Action-selective model neurons defined in such a relative reference frame are tuned to learned associations between object and effector shapes, as well as their relative position and motion. 
We demonstrate that this model reproduces a variety of electrophysiological findings on the visual properties of action-selective neurons in the superior temporal sulcus, and of mirror neurons in area F5. Specifically, the model accounts for the fact that a majority of mirror neurons in area F5 show view dependence. The model predicts a number of electrophysiological results, which partially could be confirmed in recent experiments.
We conclude that the tuning of action-selective neurons given visual stimuli can be accounted for by well-established, predominantly visual neural processes rather than internal motor simulations.

METHODS: The shape recognition relies on a hierarchy of feature detectors of increasing complexity and invariance [1]. The mid-level features are learned from sequences of gray-level images depicting segmented views of hand and object shapes. The highest hierarchy level consists of detector populations for complete shapes with a coarse spatial resolution of approximately 3.7°. Additionally, effector shapes are integrated over time by asymmetric lateral connections between shape detectors using a neural field approach [2]. These model neurons thus encode actions such as hand opening or closing for particular grip types. 
We exploit gain field mechanism in order to implement the central coordinate transformation of the shape representations to an object-centered reference frame [3]. Typical effector-object-interactions correspond to activity regions in such a relative reference frame and are learned from training examples. Similarly, simple motion-energy detectors are applied in the object-centered reference frame and encode relative motion. The properties of transitive action neurons are modeled as a multiplicative combination of relative shape and motion detectors.

RESULTS: The model performance was tested on a set of 160 unsegmented sequences of hand grasping or placing actions performed on objects of different sizes, using different grip types and views. Hand actions and objects could be reliably recognized despite their mutual occlusions. Detectors on the highest level showed correct action tuning in more than 95% of the examples and generalized to untrained views. 
Furthermore, the model replicates a number of electrophysiological as well as imaging experiments on action-selective neurons, such as their particular selectivity for transitive actions compared to mimicked actions, the invariance to stimulus position, and their view-dependence. In particular, using the same stimulus set the model nicely fits neural data from a recent electrophysiological experiment that confirmed sequence selectivity in mirror neurons in area F5, as was predicted before by the model.

References
[1] Serre, T. et al. (2007): IEEE Pattern Anal. Mach. Int. 29, 411-426.
[2] Giese, A.M. and Poggio, T. (2003): Nat. Rev. Neurosci. 4, 179-192.
[3] Deneve, S. and Pouget, A. (2003). Neuron 37: 347-359.
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Der Erfahrungsbegriff in der Didaktik - eine semiotische Analyse

Der Erfahrungsbegriff ist in erziehungswissenschaftlichen Diskursen omnipräsent. Trotzdem fehlt es bis dato an einer einheitlichen Theorie der Erfahrung, die allgemeinverbindliche Grundlage einer erfahrungsorientierten Unterrichtspraxis wäre. Es existiert i.d.S. eine merkwürdige Diskrepanz zwischen der prosperierenden Verwendung des Begriffs und seiner theoretischen bzw. unterrichtsrelevanten Aufarbeitung. Ohne - mit der Struktur des Basisphänomens inkommensurablen - erfahrungsorientierten Machbarkeitsillusionen das Wort zu reden, soll gezeigt werden, wie eine semiotische Analyse der Erfahrung helfen kann, eine konsistente und vor allem anthropologisch fundierte Theorie der Erfahrung zu formulieren, die auch die Frage nach der Genese von Erfahrungen beantwortet. Erfahrung wird dazu als überdauernde Bewusstseinsleistung Schwemmerscher Lesart verstanden. (DIPF/Orig.)The concept of experience is omnipresent in educational scientific discourses. Yet, what is still lacking is a uniform theory of experience which would constitute a universally binding basis for an experience-oriented teaching practice. In this sense, there exists a curious discrepancy between the prospering use of the concept and its theoretical or teaching-related discussion. Without wanting to put the case for experience-oriented illusions of feasibility - which are incommensurable with the structure of the basic phenomenon - the author shows how a semiotic analysis of experience may help formulate a consistent and above all anthropologically sound theory of experience which would also provide an answer to the question of the genesis of experiences. In this context, experience is conceived of as a lasting achievement of consciousness in accordance with Schwemmer\u27s approach. (DIPF/Orig.

Any two countable, densely ordered sets without endpoints are isomorphic - a formal proof with KIV

Georg Cantor in 1895 gave the first (informal) proof for the fact that any two countable, densely ordered sets without endpoints are isomorphic. Here we report on a fully formal proof of this fact constructed interactively with the KIV system (Karlsruhe Interactive Verifier)

Biologically Plausible Neural Model for the Recognition of Biological Motion and Actions

The visual recognition of complex movements and actions is crucial for communication and survival in many species. Remarkable sensitivity and robustness of biological motion perception have been demonstrated in psychophysical experiments. In recent years, neurons and cortical areas involved in action recognition have been identified in neurophysiological and imaging studies. However, the detailed neural mechanisms that underlie the recognition of such complex movement patterns remain largely unknown. This paper reviews the experimental results and summarizes them in terms of a biologically plausible neural model. The model is based on the key assumption that action recognition is based on learned prototypical patterns and exploits information from the ventral and the dorsal pathway. The model makes specific predictions that motivate new experiments

An Efficient Representation of General Qualitative Spatial Information Using Bintrees

In this paper we extend previous work on using bintrees as an efficient representation for qualitative information about spatial objects. Our approach represents each spatial object as a bintree satisfying the exact same qualitative relationships to other bintree representations as the corresponding spatial objects. We prove that such correct bintrees always exists and that they can be constructed as a sum of local representations, allowing a practically efficient construction. Our representation is both efficient, w.r.t. storage space and query time, and can represent many well-known qualitative relations, such as the relations in the Region Connection Calculus and Allen\u27s Interval Algebra

It was (not) me: Causal Inference of Agency in goal-directed actions

Summary: 
The perception of one’s own actions depends on both sensory information and predictions derived from internal forward models [1]. The integration of these information sources depends critically on whether perceptual consequences are associated with one’s own action (sense of agency) or with changes in the external world that are not related to the action. The perceived effects of actions should thus critically depend on the consistency between the predicted and the actual sensory consequences of actions. To test this idea, we used a virtual-reality setup to manipulate the consistency between pointing movements and their visual consequences and investigated the influence of this manipulation on self-action perception. We then asked whether a Bayesian causal inference model, which assumes a latent agency variable controlling the attributed influence of the own action on perceptual consequences [2,3], would account for the empirical data: if the percept was attributed to the own action, visual and internal information should fuse in a Bayesian optimal manner, while this should not be the case if the visual stimulus was attributed to external influences. The model correctly fits the data, showing that small deviations between predicted and actual sensory information were still attributed to one’s own action, while this was not the case for large deviations when subjects relied more on internal information. We discuss the performance of this causal inference model in comparison to alternative biologically feasible statistical models applying methods for Bayesian model comparison.

Experiment: 
Participants were seated in front of a horizontal board on which their right hand was placed with the index finger on a haptic marker, representing the starting point for each trial. Participants were instructed to execute straight, fast (quasi-ballistic) pointing movements of fixed amplitude, but without an explicit visual target. The hand was obstructed from the view of the participants, and visual feedback about the peripheral part of the movement was provided by a cursor. Feedback was either veridical or rotated against the true direction of the hand movement by predefined angles. After each trial participants were asked to report the subjectively experienced direction of the executed hand movement by placing a mouse-cursor into that direction.

Model: 
We compared two probabilistic models: Both include a binary random gating variable (agency) that models the sense of ‘agency’; that is the belief that the visual feedback is influenced by the subject’s motor action. The first model assumes that both the visual feedback xv and the internal motor state estimate xe are directly caused by the (unobserved) real motor state xt (Fig. 1). The second model assumes instead that the expected visual feedback depends on the perceived direction of the own motor action xe (Fig. 2). 
Results: Both models are in good agreement with the data. Fig. A shows the model fit for Model 1 superpositioned to the data from a single subject. Fig. B shows the belief that the visual stimulus was influenced by the own action, which decreases for large deviations between predicted and real visual feedback. Bayesian model comparison shows a better fit for model 1.
Citations
[1] Wolpert D.M, Ghahramani, Z, Jordan, M. (1995) Science, 269, 1880-1882.
[2] Körding KP, Beierholm E, Ma WJ, Quartz S, Tenenbaum JB, et al (2007) PLoS ONE 2(9): e943.
[3] Shams, L., Beierholm, U. (2010) TiCS, 14: 425-432.
Acknowledgements
This work was supported by the BCCN Tübingen (FKZ: 01GQ1002), the CIN Tübingen, the European Union (FP7-ICT-215866 project SEARISE), the DFG and the Hermann and Lilly Schilling Foundation

Long-distance charge transport through DNA. An extended hopping model

Long-distance transfer of a positive charge through DNA can be described by a hopping model. In double strands where the (A:T)n bridges between the guanines are short (n 3), the charge hops only between guanines, and each hopping step depends strongly upon the guanine to guanine distances. In strands where the (A:T)n sequences between the guanines are rather long (n 4), also the adenines act as charge carriers. To predict the yields of the H2O-trapping products one has to take into account not only the charge-transfer rates but also the rates of H2O-trapping reaction