Repositório Comunidade: OFFMATHOFFMATHhttps://hdl.handle.net/1822/12572024-03-29T13:22:32Z2024-03-29T13:22:32ZUsing the generalised invariant formalism: a class of conformally flat pure radiation metrics with a negative cosmological constantEdgar, S. BrianRamos, M. P. Machadohttps://hdl.handle.net/1822/661862020-07-30T12:07:26Z2020-07-30T09:57:28ZTítulo: Using the generalised invariant formalism: a class of conformally flat pure radiation metrics with a negative cosmological constant
Autor: Edgar, S. Brian; Ramos, M. P. Machado
Resumo: We demonstrate an integration procedure for the generalised invariant formalism by obtaining a subclass of conformally flat pure radiation spacetimes with a negative cosmological constant. The method used is a development of the methods used earlier for pure radiation spacetimes of Petrov types O and N respectively. This subclass of spacetimes turns out to have one degree of isotropy freedom, so in this paper we have extended the integration procedure for the generalised invariant formalism to spacetimes with isotropy freedom,
<b>Tipo</b>: conferencePaper2020-07-30T09:57:28ZImplementing Bayes’ rule with neural fieldsCuijpers, Raymond H.Erlhagen, Wolframhttps://hdl.handle.net/1822/109542017-12-15T16:11:35Z2010-10-21T15:32:53ZTítulo: Implementing Bayes’ rule with neural fields
Autor: Cuijpers, Raymond H.; Erlhagen, Wolfram
Resumo: Bayesian statistics is has been very successful in describing behavioural data on decision making and cue integration under noisy circumstances. However, it is still an open question how the human brain actually incorporates this functionality. Here we compare three ways in which Bayes rule can be implemented using neural fields. The result is a truly dynamic framework that can easily be extended by non-Bayesian mechanisms such as learning and memory.
<b>Tipo</b>: conferencePaper2010-10-21T15:32:53ZOn the development of intention understanding for joint action tasksErlhagen, WolframMukovskiy, AlbertChersi, FabianBicho, E.https://hdl.handle.net/1822/109532017-12-15T16:11:35Z2010-10-21T14:30:47ZTítulo: On the development of intention understanding for joint action tasks
Autor: Erlhagen, Wolfram; Mukovskiy, Albert; Chersi, Fabian; Bicho, E.
Resumo: Our everyday, common sense ability to discern the intentions of others’ from their motions is fundamental for a successful cooperation in joint action tasks. In this paper we address in a modeling study the question of how the ability to understand complex goal-directed action sequences may develop
during learning and practice. The model architecture reflects recent neurophysiological findings that suggest the existence of chains of mirror neurons associated with specific goals.
These chains may be activated by external events to simulate the consequences of observed actions. Using the mathematical
framework of dynamical neural fields to model the dynamics of different neural populations representing goals, action means
and contextual cues, we show that such chains may develop based on a local, Hebbian learning rule. We validate the
functionality of the learned model in a joint action task in which an observer robot infers the intention of a partner to chose a complementary action sequence.
<b>Tipo</b>: conferencePaper2010-10-21T14:30:47ZRelative mislocalization of successively presented stimuliBocianski, DianaMüsseler, JochenErlhagen, Wolframhttps://hdl.handle.net/1822/109522018-01-10T10:47:28Z2010-10-21T13:32:11ZTítulo: Relative mislocalization of successively presented stimuli
Autor: Bocianski, Diana; Müsseler, Jochen; Erlhagen, Wolfram
Resumo: When observers were asked to localize the peripheral position of a briefly presented target with respect to a previously presented comparison stimulus, they tended to judge the target as being more towards the fovea than the comparison stimulus. Three experiments revealed that the mislocalization only emerged when the comparison stimulus and the target were presented successively. Varying the temporal interval between stimuli showed that the mislocalization reversed with longer stimulus-onset asynchronies. Further, the mislocalization was increased with a decrease of the spatial distance between
stimuli. These findings suggested that the mislocalization originated from local excitatory and inhibitory mechanisms. Corroborating this idea a neuronal dynamic field model was successfully developed to account for the findings.
<b>Tipo</b>: article2010-10-21T13:32:11ZGoals and means in action observation : a computational approachCuijpers, Raymond H.Schie, Hein T. vanKoppen, MathieuErlhagen, WolframBekkering, Haroldhttps://hdl.handle.net/1822/109512017-12-15T16:11:35Z2010-10-21T11:41:59ZTítulo: Goals and means in action observation : a computational approach
Autor: Cuijpers, Raymond H.; Schie, Hein T. van; Koppen, Mathieu; Erlhagen, Wolfram; Bekkering, Harold
Resumo: Many of our daily activities are supported by behavioural goals that guide the selection of actions, which allow us to reach these goals
effectively. Goals are considered to be important for action observation since they allow the observer to copy the goal of the action without the need to use the exact same means. The importance of being able to use different action means becomes evident when the observer and observed actor have different bodies (robots and humans) or bodily measurements (parents and children), or when the environments of actor and observer differ substantially (when an obstacle is present or absent in either environment). A selective focus on the action goals instead of the action means furthermore circumvents the need to consider the vantage point of the actor, which is consistent with recent findings that people prefer to represent
the actions of others from their own individual perspective. In this paper, we use a computational approach to investigate how knowledge about action goals and means are used in action observation. We hypothesise that in action observation human agents are primarily interested in identifying the goals of the observed actor’s behaviour. Behavioural cues (e.g. the way an object is grasped) may help to disambiguate the goal of the actor (e.g. whether a cup is grasped for drinking or handing it over). Recent advances in cognitive neuroscience are cited in support of the model’s architecture.
<b>Tipo</b>: article2010-10-21T11:41:59Z