Shunting Inhibition Controls the Gain Modulation Mediated by Asynchronous Neurotransmitter Release in Early Development

The sensitivity of a neuron to its input can be modulated in several ways. Changes in the slope of the neuronal input-output curve depend on factors such as shunting inhibition, background noise, frequency-dependent synaptic excitation, and balanced excitation and inhibition. However, in early development GABAergic interneurons are excitatory and other mechanisms such as asynchronous transmitter release might contribute to regulating neuronal sensitivity. We modeled both phasic and asynchronous synaptic transmission in early development to study the impact of activity-dependent noise and short-term plasticity on the synaptic gain. Asynchronous release decreased or increased the gain depending on the membrane conductance. In the high shunt regime, excitatory input due to asynchronous release was divisive, whereas in the low shunt regime it had a nearly multiplicative effect on the firing rate. In addition, sensitivity to correlated inputs was influenced by shunting and asynchronous release in opposite ways. Thus, asynchronous release can regulate the information flow at synapses and its impact can be flexibly modulated by the membrane conductance

Structure and Function in the Inferior Olivary Nucleus

The inferior olivary nucleus is the source of the climbing fibres, one of the two major afferent pathways into the cerebellum. This thesis is concerned with aspects of the cellular anatomy and physiology of neurons in the inferior olive. In the first chapter, I report on the first direct patch-clamp recordings from olivary axons, and show that they fire in short bursts that can relay information about the state of olivary network and modulate plasticity in the cerebellar cortex. A remarkable feature of the olive is the widespread electrotonic coupling between neurons underlying their synchronous firing. In the second chapter I combine electrophysiological and immunohistological methods to characterize the coupling. I reveal the first morphological reconstructions of coupled pairs of olivary neurons, and show that the dendritic spines responsible for coupling neurons have very heterogeneous morphologies. Furthermore, I show that olivary dendrites may contact olivary somata and oligodendrocytes. In the third chapter, I use pharmacology and modelling to study the effect of inhibitory synapses on the coupling between olivary neurons. Confirming a popular theory, I show that GABA-A receptor activation reduces coupling between neurons, and use models to study the effect of location, timing and stochastic properties of the inhibitory input on electrical coupling. The common theme for all our findings is that the remarkable interplay between the anatomy and electrophysiological characteristics of the inferior olive underlies a unique computational unit in the central nervous system

Investigation into functional large-scale networks in individuals with schizophrenia using fMRI data and Dynamic Causal Modelling

Schizophrenia is a complex and severe psychiatric disorder with positive symptoms, negative symptoms and cognitive deficits. Preclinical neurobiological studies showed that alterations of dopaminergic and glutamatergic neurotransmitter circuits involving the prefrontal cortex resulted in cognitive impairment such as working memory. Functional activation and functional connectivity findings of functional Magnetic Resonance Imaging (fMRI) data provided support for prefrontal dysfunction during fMRI working memory tasks in individuals with schizophrenia. However, these findings do not offer a neurobiological interpretation of the fMRI data. Biophysical modelling of functional large-scale networks has been designed for the analysis of fMRI data, which can be interpreted in a mechanistic way. This approach may enable the interpretation of fMRI data in terms of altered synaptic plasticity processes found in schizophrenia. One such process is gating mechanism, which has been shown to be altered for the thalamo-cortical and meso-cortical connection in schizophrenia. The primary aim of the thesis was to investigate altered synaptic plasticity and gating mechanisms with Dynamic Causal Modelling (DCM) within functional large-scale networks during two fMRI tasks in individuals with schizophrenia. Applying nonlinear DCM to the verbal fluency fMRI task of the Edinburgh High Risk Study, we showed that the connection strengths with nonlinear modulation for the thalamo-cortical connection was reduced in subjects at high familial risk of schizophrenia when compared to healthy controls. These results suggest that nonlinear DCM enables the investigation of altered synaptic plasticity and gating mechanism from fMRI data. For the Scottish Family Mental Health Study, we reported two different optimal linear models for individuals with established schizophrenia (EST) and healthy controls during working memory function. We suggested that this result may indicate that EST and healthy controls used different functional large-scale networks. The results of nonlinear DCM analyses may suggest that gating mechanism was intact in EST and healthy controls. In conclusion, the results presented in this thesis give evidence for the role of synaptic plasticity processes as assessed in functional large-scale networks during cognitive tasks in individuals with schizophrenia