Learning flexible sensori-motor mappings in a complex network

Given the complex structure of the brain, how can synaptic plasticity explain the learning and forgetting of associations when these are continuously changing? We address this question by studying different reinforcement learning rules in a multilayer network in order to reproduce monkey behavior in a visuomotor association task. Our model can only reproduce the learning performance of the monkey if the synaptic modifications depend on the pre- and postsynaptic activity, and if the intrinsic level of stochasticity is low. This favored learning rule is based on reward modulated Hebbian synaptic plasticity and shows the interesting feature that the learning performance does not substantially degrade when adding layers to the network, even for a complex problem.

Functional neuroimaging of emotional learning and autonomic reactions

This article provides a selective overview of the functional neuroimaging literature with an emphasis on emotional activation processes. Emotions are fast and flexible response systems that provide basic tendencies for adaptive action. From the range of involved component functions, we first discuss selected automatic mechanisms that control basic adaptational changes. Second, we illustrate how neuroimaging work has contributed to the mapping of the network components associated with basic emotion families (fear, anger, disgust, happiness), and secondary dimensional concepts that organise the meaning space for subjective experience and verbal labels (emotional valence, activity/intensity, approach/withdrawal, etc.). Third, results and methodological difficulties are discussed in view of own neuroimaging experiments that investigated the component functions involved in emotional learning. The amygdala, prefrontal cortex, and striatum form a network of reciprocal connections that show topographically distinct patterns of activity as a correlate of up and down regulation processes during an emotional episode. Emotional modulations of other brain systems have attracted recent research interests. Emotional neuroimaging calls for more representative designs that highlight the modulatory influences of regulation strategies and socio-cultural factors responsible for inhibitory control and extinction. We conclude by emphasising the relevance of the temporal process dynamics of emotional activations that may provide improved prediction of individual differences in emotionality.

The Evolution of Routines under flexible Information Technology

Many technological developments of the past two decades come with the promise of greater IT flexi-bility, i.e. greater capacity to adapt IT. These technologies are increasingly used to improve organiza-tional routines that are not affected by large, hard-to-change IT such as ERP. Yet, most findings on the interaction of routines and IT stem from contexts where IT is hard to change. Our research ex-plores how routines and IT co-evolve when IT is flexible. We review the literatures on routines to sug-gest that IT may act as a boundary object that mediates the learning process unfolding between the ostensive and the performative aspect of the routine. Although prior work has concluded from such conceptualizations that IT stabilizes routines, we qualify that flexible IT can also stimulate change because it enables learning in short feedback cycles. We suggest that, however, such change might not always materialize because it is contingent on governance choices and technical knowledge. We de-scribe the case-study method to explore how routines and flexible IT co-evolve and how governance and technical knowledge influence this process. We expect to contribute towards stronger theory of routines and to develop recommendations for the effective implementation of flexible IT in loosely coupled routines.