The interplay between voltage-dependent plasticity, inhibition and network structure in spiking neuronal network models

Synaptic plasticity, the process by which synapses change in an activity-dependent manner, is assumed to be the basis of learning in the brain. Experimental evidence demonstrates that activity originating from other synapses in close proximity to an observed one can influence the outcome of plasticity. One of those di-synaptic effects is the influence of inhibitory activity. In this work, I hypothesise that di-synaptic regulation of plasticity by inhibition is caused by voltage-dependent effects, and develop a computational model to investigate these effects. This thesis is comprised of three parts. The first part introduces a novel voltagedependent plasticity model, the Voltage-Dependent Pathway model (VDP). Unlike previous models, the VDP has separate pathways with distinct dynamics for depression and potentiation. Additionally, the VDP is sensitive to instantaneous changes in membrane potential, allowing single excitatory and inhibitory inputs to affect the plasticity outcome. The model reproduces experimental results on the effect of inhibition, and presents new experimentally testable predictions. The second part explores network level effects of fast inhibitory regulation. I show that in excitatory-inhibitory network simulations inhibitory plasticity regulation effective on short time scales enhances competition. When these networks are presented with structured input, they perform input source separation and factorisation similar to Independent Component Analysis. Naturalistic input leads to development of receptive fields indicating that the increased competition between synaptic weights leads to the development of functionally relevant structures. Finally, the third part of the thesis explores possible mechanisms for third-factor feedback signalling in recurrent excitatory-inhibitory networks. Disinhibition mediated by inhibitory interneurons as well as broad signals originating from neuromodulators have been experimentally implicated in gating learning and plasticity in cortical circuits. The simulations show that either mechanism in combination with the VDP can promote learning of associative memory engrams. I characterise differences between them based on the spatial scope of the plasticity modulation within the network weights. Furthermore, I propose a biologically plausible mechanism for multi-synaptic self-derived supervised modulation signals within the associative learning paradigm. To summarise, this thesis investigates fast-acting inhibition as a form of di-synaptic plasticity regulation and the influences of multi-synaptic plasticity modulation. It introduces a novel voltage-based plasticity model and shows that inhibitory regulation of plasticity increases competition in recurrent networks. Moreover, disinhibition alongi side global neuromodulatory signalling as form of multisynaptic network effects can be used to implement supervised feedback signalling. In conclusion, this thesis demonstrates that plasticity models sensitive to di-synaptic inhibitory influences are sufficient to learn nonlinear network computations and highlights the importance of the detailed study of di- and multisynaptic influences on plasticity

How is modern bedside teaching structured? A video analysis of learning content, social and spatial structures

BACKGROUND: Bedside teaching (BST) is an essential and traditional clinical teaching format. It has been subject to various impediments and has transformed over time. Besides a decrease in bedside time, there has also been a didactic diversification. In order to use time at the bedside effectively and understand the current design of BST, we here offer an evidence-based insight into how BST is practiced. This may serve as a basis for a refinement of its didactic design. METHODS: In the current study, we investigate the interrelationships between learning content and the social as well as spatial structures of BST. To this end, we have empirically analysed almost 80 hours of video material from a total of 36 BST sessions with good interrater reliability. RESULTS: BST lasted on average 125 min, most of which was spent in plenary and less than a third of the time at the patient’s bedside. History taking was primarily practiced at the bedside while case presentations, clinical reasoning and theoretical knowledge were largely taught away from the patient. Clinical examination took place to a similar extent in the patient’s room and in the theory room. CONCLUSIONS: Even though the filmed BSTs are not purely “bedside”, the teaching format investigated here is a typical example of undergraduate medical education. In order to maximize the teaching time available, a suitable learning space should be provided in addition to the bedside. Moreover, the clinical examination should be revised in its general sequence prior to the BST, and conscious decisions should be made regarding the social structure so as to optimize the potential of small groups and plenary sessions