Klaus Pawelzik

Mahbod Nouri, David Rotermund, Alberto Garcia-Ortiz et al.

The brain uses positive signals as a means of signaling. Forward interactions in the early visual cortex are also positive, realized by excitatory synapses. Only local interactions also include inhibition. Non-negative matrix factorization (NMF) captures the biological constraint of positive long-range interactions and can be implemented with stochastic spikes. While NMF can serve as an abstract formalization of early neural processing in the visual system, the performance of deep convolutional networks with NMF modules does not match that of CNNs of similar size. However, when the local NMF modules are each followed by a module that mixes the NMF's positive activities, the performances on the benchmark data exceed that of vanilla deep convolutional networks of similar size. This setting can be considered a biologically more plausible emulation of the processing in cortical (hyper-)columns with the potential to improve the performance of deep networks.

Martin Spanknebel, Klaus Pawelzik

Human decision behaviour is quite diverse. In many games humans on average do not achieve maximal payoff and the behaviour of individual players remains inhomogeneous even after playing many rounds. For instance, in repeated prisoner dilemma games humans do not always optimize their mean reward and frequently exhibit broad distributions of cooperativity. The reasons for these failures of maximization are not known. Here we show that the dynamics resulting from the tendency to shift choice probabilities towards previously rewarding choices in closed loop interaction with the strategy of the opponent can not only explain systematic deviations from 'rationality', but also reproduce the diversity of choice behaviours. As a representative example we investigate the dynamics of choice probabilities in prisoner dilemma games with opponents using strategies with different degrees of extortion and generosity. We find that already a simple model for human learning can account for a surprisingly wide range of human decision behaviours. It reproduces suppression of cooperation against extortionists and increasing cooperation when playing with generous opponents, explains the broad distributions of individual choices in ensembles of players, and predicts the evolution of individual subjects' cooperation rates over the course of the games. We conclude that important aspects of human decision behaviours are rooted in elementary learning mechanisms realised in the brain.