J. Michael Herrmann | University of Edinburgh (original) (raw)

Uploads

Papers by J. Michael Herrmann

We will present the implementation of a recent explanation to a prominent effect in psychological... more We will present the implementation of a recent explanation to a prominent effect in psychological problems, negative priming. A typical setup to determine priming effects is the identity priming paradigm as it is shown in fig. 1. A person fixates a cross on a screen and is presented two stimuli at a time. Some feature (here: color) determines the discrimination between target and distractor. The green stimulus is the target and the red one the distractor.

Abstract Self-organisation and the phenomenon of emergence play an essential role in living syste... more Abstract Self-organisation and the phenomenon of emergence play an essential role in living systems and form a challenge to artificial life systems. This is not only because systems become more lifelike, but also since self-organisation may help in reducing the design efforts in creating complex behaviour systems. We consider agents under the close sensorimotor coupling paradigm with a certain cognitive ability realised by an internal forward model.

We study a model of feature binding in prefrontal cortex which defers specific perceptual informa... more We study a model of feature binding in prefrontal cortex which defers specific perceptual information to lower areas and merely maintains the identity of the combination. The model consists of three layers of pulse-coupled leaky integrate-and-fire neurons. Features are encoded by the location of sustained activity in the subordinate layers. The feature layers are excitatorily coupled to a superordinate layer that represents combinations of features by means of an oscillatory dynamics.

Background Autonomous robots as well as animals process sensory information for the purpose of ge... more Background Autonomous robots as well as animals process sensory information for the purpose of generating behaviors that are adapted to their respective environments. This includes the selection of behaviorally relevant perceptual features, the adaptation of control mechanisms and the storage and the recall of behavioral episodes for planning and execution.

We discuss methods for analyzing fMRI data, stimulus-based such as baseline substraction and corr... more We discuss methods for analyzing fMRI data, stimulus-based such as baseline substraction and correlation analysis versus stimulus-independent methods such as Principal Component Analysis (PCA) and Independent Component Analysis (ICA) with respect to their capabil-ities of separating noise sources from functional activity.

DOAJ Directory of Open Access Journals, SPARC Europe Award 2009 English.

Abstract: Recent studies of visual detection show a configuration dependent weak improvement of t... more Abstract: Recent studies of visual detection show a configuration dependent weak improvement of thresholds with the number of targets, which corresponds to a fourth-root power law. We find this result to be inconsistent with probability summation models, and account for it by a model of'physiological'integration that is based on excitatory lateral interactions in the visual cortex.

Self-organized criticality (SOC) is one of the key concepts for describing the emergence of compl... more Self-organized criticality (SOC) is one of the key concepts for describing the emergence of complexity in nature. In neural systems, the critical state is believed to optimize memory capacity, sensitivity to stimuli and information transmission. Critical avalanches were found in cortical cultures and slices [1] and in the motor cortex of awake monkeys [2]. Computational models of SOC often include an explicit regulatory mechanism that guides the state of the network toward criticality.

Abstract We present a biologically plausible spiking neuronal network model of free monkey scribb... more Abstract We present a biologically plausible spiking neuronal network model of free monkey scribbling that reproduces experimental findings on cortical activity and the properties of the scribbling trajectory. The model is based on the idea that synfire chains can encode movement primitives. Here, we map the propagation of activity in a chain to a linearly evolving preferred velocity, which results in parabolic segments that fulfill the two-thirds power law.

We study the extraction of nonlinear data models in high dimensional spaces with modified self-or... more We study the extraction of nonlinear data models in high dimensional spaces with modified self-organizing maps. Our algorithm maps lower dimensional lattice into a high dimensional space without topology violations by tuning the neighborhood widths locally. The approach is based on a new principle exploiting the specific dynamical properties of the first order phase transition induced by the noise of the data. The performance of the algorithm is demonstrated for one-and two-dimensional principal manifolds and for sparse data sets.

Abstract We introduce gain-based policies for exploration in active learning problems. For explor... more Abstract We introduce gain-based policies for exploration in active learning problems. For exploration in multi-armed bandits with the knowledge of reward variances, an ideal gain-maximization exploration policy is described in a unified framework which also includes error-based and counter-based exploration.

Abstract The aim of this work is to investigate the effect of the shift-twist symmetry on pattern... more Abstract The aim of this work is to investigate the effect of the shift-twist symmetry on pattern formation processes in the visual cortex. First, we describe a generic set of Riemannian metrics of the feature space of orientation preference that obeys properties of the shift-twist, translation, and reflection symmetries. Second, these metrics are embedded in a modified Swift–Hohenberg model. As a result we get a pattern formation process that resembles the pattern formation process in the visual cortex.

Summary Mobile robots face a complex environment which cannot be expected to be fully predicable.... more Summary Mobile robots face a complex environment which cannot be expected to be fully predicable. Selfdetermined exploration is a viable approach to achieve an accumulation of world knowledge by the robot. The tutorial explains how the homeokinetic principle gives rise to exploratory robot controllers that produce play-like behaviour by maximising information gain.

Abstract Localization in non-linear lattices of excitable elements is present in discrete breathe... more Abstract Localization in non-linear lattices of excitable elements is present in discrete breathers [1], and forms an interesting counterpart to localization of activity in neural systems [4]. We study the behavior of breatherlike excitations in a system of locally interacting integrate-and-fire neurons. Both numerical and analytical results justify the notion of a neural breather, which may form an element of working memory and attention.

Abstract We investigate analytically properties like stability and existence of solutions of the ... more Abstract We investigate analytically properties like stability and existence of solutions of the two dimensional neural field equation as proposed by Amari (1977) in [1] as a model of macroscopic activation dynamics in neural tissue. While the one dimensional case has been treated comprehensively, for the two dimensional case only the existence of circular solutions was shown, and stability was as well only considered for radially symmetric perturbations.

Abstract Negative priming is characterized by longer reaction times when responding to stimuli wh... more Abstract Negative priming is characterized by longer reaction times when responding to stimuli which have been actively ignored recently. A central problem of the interpretation of the NP effect is the lack of agreement about the underlying mechanisms. Over the past 20 years, various theoretical accounts have been developed to explain NP. However, empirical evidence does not clearly favour one theory over the others.

It was previously shown that an extended critical interval can be obtained in a neural network by... more It was previously shown that an extended critical interval can be obtained in a neural network by incorporation of depressive synapses [2]. In the present study we scrutinize a more realistic dynamics for the synaptic interactions that can be considered as the state-of-the-art in computational modeling of synaptic interaction (Figure 1)[2].

Abstract: Ideally, sensory information forms the only source of information to a robot. We consid... more Abstract: Ideally, sensory information forms the only source of information to a robot. We consider an algorithm for the self-organization of a controller. At short time scales the controller is merely reactive but the parameter dynamics and the acquisition of knowledge by an internal model lead to seemingly purposeful behavior on longer time scales. As a paradigmatic example, we study the simulation of an underactuated snake-like robot.

Abstract. Generalized principal curves are capable of representing complex data structures as the... more Abstract. Generalized principal curves are capable of representing complex data structures as they may have branching points or may consist of disconnected parts. For their construction using an unsupervised learning algorithm the templates need to be structurally adaptive. The present algorithm meets this goal by a combination of a competitive Hebbian learning scheme and a self-organizing map algorithm.

DOAJ Directory of Open Access Journals, SPARC Europe Award 2009 English.