Gradient estimation in dendritic reinforcement learning

We study synaptic plasticity in a complex neuronal cell model where NMDA-spikes can arise in certain dendritic zones. In the context of reinforcement learning, two kinds of plasticity rules are derived, zone reinforcement (ZR) and cell reinforcement (CR), which both optimize the expected reward by stochastic gradient ascent. For ZR, the synaptic plasticity response to the external reward signal is modulated exclusively by quantities which are local to the NMDA-spike initiation zone in which the synapse is situated. CR, in addition, uses nonlocal feedback from the soma of the cell, provided by mechanisms such as the backpropagating action potential. Simulation results show that, compared to ZR, the use of nonlocal feedback in CR can drastically enhance learning performance. We suggest that the availability of nonlocal feedback for learning is a key advantage of complex neurons over networks of simple point neurons, which have previously been found to be largely equivalent with regard to computational capability.

Synesthetic experiences enhance unconscious learning

Synesthesia is characterized by consistent extra perceptual experiences in response to normal sensory input. Recent studies provide evidence for a specific profile of enhanced memory performance in synesthesia, but focus exclusively on explicit memory paradigms for which the learned content is consciously accessible. In this study, for the first time, we demonstrate with an implicit memory paradigm that synesthetic experiences also enhance memory performance relating to unconscious knowledge.

Using technology to enhance decision making

We focus here on decision making in the everyday clinical situation and do not address decision making in politics and administration, although obviously it affects clinical practice and vice versa. For example, decisions against providing sufficient face-to-face psychotherapy is one factor that may increase the demand for Internet therapy, and vice versa—that is, the use of technology for therapy, as in Internet therapy, might influence to what extent face-to-face therapy needs to be provided. It is obvious that the aggregation of information for political and administrative decisions can take advantage of technology. If technology is used professionally, this should contribute to better informed decisions and less dependency on information provided by lobbyists who might not work in the interest of high-quality service for those who need it. An optimistic view is thus that technology works in favor of patients on this level as well. In the interest of keeping the focus of this chapter manageable, we also do not address treatments fully delivered over the Internet or computers, as for the example described in Comer and Barlow (2014), although such treatments, as they unfold, of course also include decision making.