A neural network model of normal and abnormal learning and memory consolidation

The amygdala and hippocampus interact with thalamocortical systems to regulate cognitive-emotional learning, and lesions of amygdala, hippocampus, thalamus, and cortex have different effects depending on the phase of learning when they occur. In examining eyeblink conditioning data, several questions arise: Why is the hippocampus needed for trace conditioning where there is a temporal gap between the conditioned stimulus offset and the onset of the unconditioned stimulus, but not needed for delay conditioning where stimuli temporally overlap and co-terminate? Why do amygdala lesions made before or immediately after training decelerate conditioning while those made later have no impact on conditioned behavior? Why do thalamic lesions degrade trace conditioning more than delay conditioning? Why do hippocampal lesions degrade recent learning but not temporally remote learning? Why do cortical lesions degrade temporally remote learning, and cause amnesia, but not recent or post-lesion learning? How is temporally graded amnesia caused by ablation of medial prefrontal cortex? How are mechanisms of motivated attention and the emergent state of consciousness linked during conditioning? How do neurotrophins, notably Brain Derived Neurotrophic Factor (BDNF), influence memory formation and consolidation? A neural model, called neurotrophic START, or nSTART, proposes answers to these questions. The nSTART model synthesizes and extends key principles, mechanisms, and properties of three previously published brain models of normal behavior. These three models describe aspects of how the brain can learn to categorize objects and events in the world; how the brain can learn the emotional meanings of such events, notably rewarding and punishing events, through cognitive-emotional interactions; and how the brain can learn to adaptively time attention paid to motivationally important events, and when to respond to these events, in a context-appropriate manner. The model clarifies how hippocampal adaptive timing mechanisms and BDNF may bridge the gap between stimuli during trace conditioning and thereby allow thalamocortical and corticocortical learning to take place and be consolidated. The simulated data arise as emergent properties of several brain regions interacting together. The model overcomes problems of alternative memory models, notably models wherein memories that are initially stored in hippocampus move to the neocortex during consolidation

Astrocytic modulation of neuronal network oscillations

The synchronization of the neuron’s membrane potential results in the emergence of neuronal oscillations at multiple frequencies that serve distinct physiological functions (e.g. facilitation of synaptic plasticity) and correlate with different behavioural states (e.g. sleep, wakefulness, attention). It has been postulated that at least ten distinct mechanisms are required to cover the large frequency range of neuronal oscillations in the cortex, including variations in the concentration of extracellular neurotransmitters and ions, as well as changes in cellular excitability. However, the mechanism that gears the transition between different oscillatory frequencies is still unknown. Over the past decade, astrocytes have been the focus of much research, mainly due to (1) their close association with synapses forming what is known today as the “tripartite synapse”, which allows them to bidirectionally interact with neurons and modulate synaptic transmission; (2) their syncytium-like activity, as they are electrically coupled via gap junctions and actively communicate through Ca2+ waves; and (3) their ability to regulate neuronal excitability via glutamate uptake and tight control of the extracellular K+ levels via a process termed K+ clearance. In this thesis we hypothesized that astrocytes, in addition to their role as modulators of neuronal excitability, also act as “network managers” that can modulate the overall network oscillatory activity within their spatial domain. To do so, it is proposed that astrocytes fine-tune their K+ clearance capabilities to affect neuronal intrinsic excitability properties and synchronization with other neurons, thus mediating the transitions between neuronal network oscillations at different frequencies. To validate or reject this hypothesis I have investigated the potential role of astrocytes in modulating cortical oscillations at both cellular and network levels, aiming at answering three main research questions: a) what is the impact of alterations in astrocytic K+ clearance mechanisms on cortical networks oscillatory dynamics? b) what specific neuronal properties underlying the generation of neuronal oscillations are affected as a result of impairments in the astrocytic K+ clearance process? and c) what are the bidirectional mechanisms between neurons and astrocytes (i.e. neuromodulators) that specifically affect the K+ clearance process to modulate the network activity output? In the first experimental chapter I used electrophysiological recordings and pharmacological manipulations to dissect the contribution of the different astrocytic K+ clearance mechanisms to the modulation of neuronal network oscillations at multiple frequencies. A key finding was that alterations in membrane properties of layer V pyramidal neurons strongly correlated with the network behaviour following impairments in astrocytic K+ clearance capabilities, depicted as enhanced excitability underlying the amplification of high-frequency oscillations, especially within the beta and gamma range. The second experimental chapter describes a combinatorial approach based on K+-selective microelectrode recordings and optical imaging of K+ ions used to quantitatively determine extracellular K+ changes and to follow the spatiotemporal distribution of K+ ions under both physiological and altered K+ clearance conditions, which affected the K+ clearance rate. The impact of different neuromodulators on astrocytic function is discussed in the third experimental chapter. Using extracellular K+ recordings and Ca2+ imaging I found that some neuromodulators act specifically on astrocytic receptors to affect both K+ clearance mechanisms and Ca2+ signalling, as evidenced by reduced K+ clearance rates and altered evoked Ca2+ signals. Overall, this thesis provides new insights regarding the impact of astrocytic K+ clearance mechanisms on modulating neuronal properties at both cellular and network levels, which in turn imposes alterations on neuronal oscillations that are associated with different behavioural states