Past events

Neuronal networks can generate complex patterns of activity that depend on membrane properties of individual neurons as well as on functional synapses. To decipher the impact of synaptic properties and connectivity on neuronal network behavior, we studied using a combination of electrophysiological recordings and the synaptic depression-facilitation model, the responses of neuronal ensembles from small (between 5-30 cells in a restricted sphere) and large (acute hippocampal slice) networks to single electrical stimulation. Interestingly, in both cases, a single stimulus generated a synchronous long-lasting bursting activity. We characterized this activity in neuronal populations using electrophysiological recordings and we also extract the network time constant parameters using the mean-field model based on synaptic facilitation/depression. While the initial spikes triggered a reverberating network activity that lasted 2-5 seconds for small networks, it lasted only up to 300 milliseconds in slices, a phenomena that was also present in our simulations. We found here that the reverberation time has a bell shaped relation with the synaptic density. In addition, before reaching its maximum, this reverberation time increased sub-linearly with the network connectivity parameter. We conclude that synaptic properties and the network connectivity shape the mean burst duration, which persists across various network scales. This synchronization is an inherent property of sufficiently connected neural networks based on synaptic depression and facilitation.

Angelman syndrome (AS) is a human neuropsychiatric disorder associated with autism, mental retardation, motor dysfunction, and epilepsy. In most cases, AS is caused by the deletion of small portions of chromosome 15, which includes the UBE3A gene. The UBE3A gene encodes an enzyme termed ubiquitin ligase E3A. A mouse model of AS has been generated and these mice exhibit abnormalities that correlate with neurological alterations observed in humans with AS. One of the prominent affected brain regions in AS is the hippocampus. We characterized the CA1 pyramidal neurons in the AS mice, and observed alterations in the intrinsic membrane properties of these cells between AS mice and their wild-type littermates. These alterations were correlated with increased expression of specific proteins, mainly related to the axon initial segment (AIS). Furthermore, the AIS morphology of these neurons in the AS mice was also found to be altered. By determining the temporal sequence for the increased expression of these proteins we have discovered the precipitating event for the observed AIS alterations which coincides with the homeostatic model of the neuron. Finally, we rescued the hippocampal pathology via a genetic manipulation based on this understanding. Taken together, our findings are the first to suggest that AIS plasticity alterations exist in mammalian brain in-vivo and could be involved in neuropsychiatric disorders such as AS. They also offer a novel conceptualization of neuropsychiatric disorders and propose the option for an innovative therapeutic strategy.

Uncertainty is inherent to any situation we encounter. Our individual attitudes towards uncertainty strongly affect our evaluation of different available options and our behavior based on these evaluations. In the talk I will describe a series of studies in which we combine experimental economics and other behavioral methods with functional MRI to study the behavioral and neural characteristics of attitudes towards uncertainty and learning under uncertainty.

In Huntington’s disease (HD) – a devastating autosomal-dominant neurodegenerative disease – the striatum displays reduced cholinergic markers, despite the resiliency of cholinergic interneurons (ChIs) – the source of striatal acetylcholine – to the neurodegeneration that decimates striatal projection neurons. Autonomous spiking of ChIs is unchanged in transgenic HD mice, suggesting a functional deficit in extrinsically driven activity. Using two transgenic mouse models of HD, we show that ChI responses to cortical input are boosted by a post-synaptic up-regulation of the persistent sodium current. This boosting is replicated by in wild-type mice by diminished activation of group I metabotropic glutamate receptors (mGluRs). Activation of group I mGluRs in HD mice counters the boosting. We propose that the recently described loss of thalamic synapses in striatum, reduces group I mGluR activation in ChIs which promotes boosting of cortical inputs. The augmentation of cortical inputs may function to compensate for the lost thalamic glutamatergic drive.

Neuronal networks can generate complex patterns of activity that depend on membrane properties of individual neurons as well as on functional synapses. To decipher the impact of synaptic properties and connectivity on neuronal network behavior, we studied using a combination of electrophysiological recordings and the synaptic depression-facilitation model, the responses of neuronal ensembles from small (between 5-30 cells in a restricted sphere) and large (acute hippocampal slice) networks to single electrical stimulation. Interestingly, in both cases, a single stimulus generated a synchronous long-lasting bursting activity. We characterized this activity in neuronal populations using electrophysiological recordings and we also extract the network time constant parameters using the mean-field model based on synaptic facilitation/depression. While the initial spikes triggered a reverberating network activity that lasted 2-5 seconds for small networks, it lasted only up to 300 milliseconds in slices, a phenomena that was also present in our simulations. We found here that the reverberation time has a bell shaped relation with the synaptic density. In addition, before reaching its maximum, this reverberation time increased sub-linearly with the network connectivity parameter. We conclude that synaptic properties and the network connectivity shape the mean burst duration, which persists across various network scales. This synchronization is an inherent property of sufficiently connected neural networks based on synaptic depression and facilitation.

Angelman syndrome (AS) is a human neuropsychiatric disorder associated with autism, mental retardation, motor dysfunction, and epilepsy. In most cases, AS is caused by the deletion of small portions of chromosome 15, which includes the UBE3A gene. The UBE3A gene encodes an enzyme termed ubiquitin ligase E3A. A mouse model of AS has been generated and these mice exhibit abnormalities that correlate with neurological alterations observed in humans with AS. One of the prominent affected brain regions in AS is the hippocampus. We characterized the CA1 pyramidal neurons in the AS mice, and observed alterations in the intrinsic membrane properties of these cells between AS mice and their wild-type littermates. These alterations were correlated with increased expression of specific proteins, mainly related to the axon initial segment (AIS). Furthermore, the AIS morphology of these neurons in the AS mice was also found to be altered. By determining the temporal sequence for the increased expression of these proteins we have discovered the precipitating event for the observed AIS alterations which coincides with the homeostatic model of the neuron. Finally, we rescued the hippocampal pathology via a genetic manipulation based on this understanding. Taken together, our findings are the first to suggest that AIS plasticity alterations exist in mammalian brain in-vivo and could be involved in neuropsychiatric disorders such as AS. They also offer a novel conceptualization of neuropsychiatric disorders and propose the option for an innovative therapeutic strategy.

Uncertainty is inherent to any situation we encounter. Our individual attitudes towards uncertainty strongly affect our evaluation of different available options and our behavior based on these evaluations. In the talk I will describe a series of studies in which we combine experimental economics and other behavioral methods with functional MRI to study the behavioral and neural characteristics of attitudes towards uncertainty and learning under uncertainty.

In Huntington’s disease (HD) – a devastating autosomal-dominant neurodegenerative disease – the striatum displays reduced cholinergic markers, despite the resiliency of cholinergic interneurons (ChIs) – the source of striatal acetylcholine – to the neurodegeneration that decimates striatal projection neurons. Autonomous spiking of ChIs is unchanged in transgenic HD mice, suggesting a functional deficit in extrinsically driven activity. Using two transgenic mouse models of HD, we show that ChI responses to cortical input are boosted by a post-synaptic up-regulation of the persistent sodium current. This boosting is replicated by in wild-type mice by diminished activation of group I metabotropic glutamate receptors (mGluRs). Activation of group I mGluRs in HD mice counters the boosting. We propose that the recently described loss of thalamic synapses in striatum, reduces group I mGluR activation in ChIs which promotes boosting of cortical inputs. The augmentation of cortical inputs may function to compensate for the lost thalamic glutamatergic drive.