Up-State signaling and Coincidence Detection in Striatal Fast Spiking Interneurons Coupled through Gap Junctions
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The basal ganglia form an important structure centrally placed in the brain. They receive input from motor, associative and limbic areas, and produce output mainly to the thalamus and the brain stem. The basal ganglia have been implied in cognitive and motor functions. One way to understand the basal ganglia is to take a look at the diseases that affect them. Both Parkinson's disease and Huntington's disease with their motor problems are results of malfunctioning basal ganglia. There are also indications that these diseases affect cognitive functions. Drug addiction is another example that involves this structure, which is also important for motivation and selection of behaviour. In this licentiate thesis I am laying the groundwork for a detailed model of the striatum, which is the input stage of the basal ganglia. The striatum receives glutamatergic input from the cortex and thalamus, as well as dopaminergic input from substantia nigra. The majority of the neurons in the striatum are medium spiny (MS) projection neurons that project mainly to globus pallidus but also to other neurons in the striatum and to both dopamine producing and GABAergic neurons in substantia nigra. In addition to the MS neurons there are fast spiking (FS) interneurons that are in a position to regulate the firing of the MS neurons. These FS neurons are few, but connected into large networks through electrical synapses that could synchronise their effect. By forming strong inhibitory synapses on the MS neurons the FS neurons have a powerful influence on the striatal output. The inhibitory output of the basal ganglia on the thalamus is believed to keep prepared motor commands on hold, but once one of them is disinhibited, then the selected motor command is executed. This disinhibition is initiated in the striatum by the MS neurons. Both MS and FS neurons are active during so called up-states, which are periods of elevated cortical input to striatum. Here I have studied the FS neurons and their ability to detect such up-states. This is important because FS neurons can delay spikes in MS neurons and the time between up-state onset and the first spike in the MS neurons is correlated with the amount of calcium entering the MS neuron, which in turn might have implications for plasticity and learning of new behaviours. The effect of different combinations of electrical couplings between two FS neurons has been tested, where the location, number and strength of these gap junctions have been varied. I studied both the ability of the FS neurons to fire action potentials during the up-state, and the synchronisation between neighbouring FS neurons due to electrical coupling. I found that both proximal and distal gap junctions synchronised the firing, but the distal gap junctions did not have the same temporal precision. The ability of the FS neurons to detect an up-state was affected by whether the neighbouring FS neuron also received up-state input or not. This effect was more pronounced for distal gap junctions than proximal ones, due to a stronger shunting effect of distal gap junctions when the dendrites were synaptically activated. We have also performed initial stochastic simulations of the Ca2+-calmodulin-dependent protein kinase II (CaMKII). The purpose here is to build the knowledge as well as the tools necessary for biochemical simulations of intracellular processes that are important for plasticity in the MS neurons. The simulated biochemical pathways will then be integrated into an existing model of a full MS neuron. Another venue to explore is to build striatal network models consisting of MS and FS neurons and using experimental data of the striatal microcircuitry. With these different approaches we will improve our understanding of striatal information processing.Keywords:
Medium spiny neuron
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The striatum is the main input stage of the basal ganglia system, which is involved in executive functions of the forebrain, such as the planning and the selection of motor behavior. Feedforward inhibition of medium-sized spiny projection neurons in the striatum by fast-spiking interneurons is supposed to be an important determinant of controlling striatal output to later stages of the basal ganglia[1]. Striatal fast-spiking interneurons, which constitute approximately 1–2% of all striatal neurons, show many similarities to cortical fast-spiking cells. In response to somatic current injection, for example, some of these neurons exhibit spike bursts with a variable number of action potentials (so called stuttering)[2-4]. Interestingly, the membrane potential between such stuttering episodes oscillates in the range of 20–100 Hz[3,5]. The first spike of each stuttering episode invariably occurs at a peak of the underlying subthreshold oscillation. In both cortex and striatum, fast-spiking cells are inter-connected by gap junctions[6,7]. In vitro measurements as well as theoretical studies indicate that electrical coupling via gap junctions might be able to promote synchronous activity among these neurons[6,8]. Here we investigate the possible role of subthreshold oscillations on the synchronization of sub- and suprathreshold activity in a model of electrically coupled fast-spiking neurons. We use the model of Golomb et al.[3], which we extended with a dendritic tree so as to be able to simulate distal synaptic input. We show that gap junctions are able to synchronize subthreshold membrane potential fluctuations in response to somatic current injection. However, the oscillations are only prevalent in the subthreshold range and therefore require enough membrane potential depolarization[5]. In response to synaptic input, our model neuron only enters the subthreshold oscillatory regime with AMPA and NMDA synapses located at distal dendrites. Proximal synaptic input leads to more random fluctuations of the membrane potential, reflecting a smaller extent of dendritic filtering of the Poisson-distributed postsynaptic potentials. We furthermore investigate the effect of GABAergic (i.e. inhibitory) input to the model of the fast-spiking neuron and predict that inhibitory input is able to induce a stuttering episode in these cells. We finally discuss our results in the context of the feedforward inhibitory network, which is likely to play an important role in striatal and basal ganglia function.
Neocortex
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Action Potential (APs) patterns of sensory cortex neurons encode a variety of stimulus features, but how can a neuron change the feature to which it responds? Here, we show that in vivo a spike-timing-dependent plasticity (STDP) protocol—consisting of pairing a postsynaptic AP with visually driven presynaptic inputs—modifies a neurons' AP-response in a bidirectional way that depends on the relative AP-timing during pairing. Whereas postsynaptic APs repeatedly following presynaptic activation can convert subthreshold into suprathreshold responses, APs repeatedly preceding presynaptic activation reduce AP responses to visual stimulation. These changes were paralleled by restructuring of the neurons response to surround stimulus locations and membrane-potential time-course. Computational simulations could reproduce the observed subthreshold voltage changes only when presynaptic temporal jitter was included. Together this shows that STDP rules can modify output patterns of sensory neurons and the timing of single-APs plays a crucial role in sensory coding and plasticity.
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Spike-timing-dependent plasticity
Subthreshold conduction
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The common view that stopping action plans by the basal ganglia is achieved mainly by the subthalamic nucleus alone due to its direct excitatory projection onto the output nuclei of the basal ganglia has been challenged by recent findings. The proposed "pause-then-cancel" model suggests that the subthalamic nucleus provides a rapid stimulus-unspecific "pause" signal, followed by a stop-cue-specific "cancel" signal from striatum-projecting arkypallidal neurons. To determine more precisely the relative contribution of the different basal ganglia nuclei in stopping, we simulated a stop-signal task with a spiking neuron model of the basal ganglia, considering recently discovered connections from the arkypallidal neurons, and cortex-projecting GPe neurons. For the arkypallidal and prototypical GPe neurons, we obtained neuron model parameters by fitting their neuronal responses to published experimental data. Our model replicates findings of stop-signal tasks at neuronal and behavioral levels. We provide evidence for the existence of a stop-related cortical input to the arkypallidal and cortex-projecting GPe neurons such that the stop responses of the subthalamic nucleus, the arkypallidal neurons, and the cortex-projecting GPe neurons complement each other to achieve functional stopping behavior. Particularly, the cortex-projecting GPe neurons may complement the stopping within the basal ganglia caused by the arkypallidal and STN neurons by diminishing cortical go-related processes. Furthermore, we predict effects of lesions on stopping performance and propose that arkypallidal neurons mainly participate in stopping by inhibiting striatal neurons of the indirect rather than the direct pathway.
Subthalamic Nucleus
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Neocortical microcircuits are thought to contribute importantly to the sophisticated processing abilities of the mammalian brain. Neurons within the neocortex communicate with each other through releasing the excitatory neurotransmitter glutamate or the inhibitory neurotransmitter GABA. In order to begin to understand the functional operation of the neocortex, it will clearly be important to establish the basic organizing principles of synaptic connectivity between different classes of cortical neurons. Here I specifically investigate excitatory and GABAergic neuronal networks within layer 2/3 of mouse somatosensory cortex in vitro. In order to analyze synaptic connectivity I made multiple simultaneous whole-cell recordings from GFP expressing GABAergic neurons and from GFP-negative pyramidal neurons targeted by two-photon microscopy. Additionally, I express channelrhodopsin-2 (ChR2), a light-activated cation channel, in genetically defined populations of excitatory neurons which allows optically control of neuronal networks with millisecond precision. I show that optically evoked, near synchronous action potentials in excitatory neurons are sufficient to drive rapid and reliable disynaptic local inhibition onto neighboring pyramidal neurons. Local inhibition was mediated by parvalbumin expressing, fast-spiking (FS) GABAergic neurons, which responded to excitatory network input with significantly larger amplitude depolarizing PSPs compared to both non-fast-spiking (NFS) GABAergic and excitatory pyramidal neurons. The strong excitatory drive onto FS neurons can partially be explained with the finding that pyramidal neurons in cortical layer 2/3 synaptically connect to FS neurons with a higher probabilities and larger unitary EPSPs. Furthermore, FS neurons provided strong unitary inhibitory feedback onto pyramidal neurons and other FS neurons in layer 2/3. These results suggest an important role of FS GABAergic neurons in mediating strong local inhibition to control the extent of excitatory layer 2/3 network activity.
Neocortex
Barrel cortex
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Interneuron
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The striatum is the key site for cortical input to the basal ganglia. Cortical input to striatal microcircuits has been previously studied only in the context of one or two types of neurons. Here, we provide the first description of four putative types of striatal neurons (medium spiny, fast spiking, tonically active, and low-threshold spiking) in a single data set by separating extracellular recordings of sorted single spikes recorded under halothane anesthesia using waveform and burst parameters. Under halothane, the electrocorticograms and striatal local field potential displayed spontaneous oscillations at both low (2–9 Hz) and high (35–80 Hz) frequencies. Putative fast spiking interneurons were significantly more likely to phase lock to high-frequency cortical oscillations and displayed significant cross-correlations in this frequency range. These findings suggest that, as in neocortex and hippocampus, the coordinated activity of fast spiking interneurons may specifically be involved in mediating oscillatory synchronization in the striatum.
Cortical neurons
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The brain is a network system in which excitatory and inhibitory neurons keep activity balanced in the highly non-random connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neurons in the cortex. So, in general, how inhibitory neurons can keep the balance with the surrounding excitatory neurons is an important question. There is much accumulated knowledge about this fundamental question. This study quantitatively evaluated the relatively higher functional contribution of inhibitory neurons in terms of not only properties of individual neurons, such as firing rate, but also in terms of topological mechanisms and controlling ability on other excitatory neurons. We combined simultaneous electrical recording (~2.5 hours) of ~1000 neurons in vitro, and quantitative evaluation of neuronal interactions including excitatory-inhibitory categorization. This study accurately defined recording brain anatomical targets, such as brain regions and cortical layers, by inter-referring MRI and immunostaining recordings. The interaction networks enabled us to quantify topological influence of individual neurons, in terms of controlling ability to other neurons. Especially, the result indicated that highly influential inhibitory neurons show higher controlling ability of other neurons than excitatory neurons, and are relatively often distributed in deeper layers of the cortex. Furthermore, the neurons having high controlling ability are more effectively limited in number than central nodes of k-cores, and these neurons also participate in more clustered motifs. In summary, this study suggested that the high controlling ability of inhibitory neurons is a key mechanism to keep balance with a large number of other excitatory neurons beyond simple higher firing rate. Application of the selection method of limited important neurons would be also applicable for the ability to effectively and selectively stimulate E/I imbalanced disease states.
Cellular neuroscience
Cortical neurons
Nerve net
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Abstract It is unclear how different types of cortical projection neurons work together to support diverse cortical functions. We examined the discharge characteristics and inactivation effects of intratelencephalic (IT) and pyramidal tract (PT) neurons—two major types of cortical excitatory neurons that project to cortical and subcortical structures, respectively—in the medial prefrontal cortex of mice performing a delayed response task. We found that IT neurons, but not PT neurons, convey significant working memory-related signals. We also found that the inactivation of IT neurons, but not PT neurons, impairs behavioral performance. In contrast, PT neurons convey far more temporal information than IT neurons during the delay period. Our results indicate a division of labor between IT and PT projection neurons in the prefrontal cortex for the maintenance of working memory and for tracking the passage of time, respectively.
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In the striatal microcircuit, fast-spiking (FS) interneurons have an important role in mediating inhibition onto neighboring medium spiny (MS) projection neurons. In this study, we combined computational modeling with in vitro and in vivo electrophysiological measurements to investigate FS cells in terms of their discharge properties and their synaptic efficacies onto MS neurons. In vivo firing of striatal FS interneurons is characterized by a high firing variability. It is not known, however, if this variability results from the input that FS cells receive, or if it is promoted by the stuttering spike behavior of these neurons. Both our model and measurements in vitro show that FS neurons that exhibit random stuttering discharge in response to steady depolarization do not show the typical stuttering behavior when they receive fluctuating input. Importantly, our model predicts that electrically coupled FS cells show substantial spike synchronization only when they are in the stuttering regime. Therefore, together with the lack of synchronized firing of striatal FS interneurons that has been reported in vivo, these results suggest that neighboring FS neurons are not in the stuttering regime simultaneously and that in vivo FS firing variability is more likely determined by the input fluctuations. Furthermore, the variability in FS firing is translated to variability in the postsynaptic amplitudes in MS neurons due to the strong synaptic depression of the FS-to-MS synapse. Our results support the idea that these synapses operate over a wide range from strongly depressed to almost fully recovered. The strong inhibitory effects that FS cells can impose on their postsynaptic targets, and the fact that the FS-to-MS synapse model showed substantial depression over extended periods of time might indicate the importance of cooperative effects of multiple presynaptic FS interneurons and the precise orchestration of their activity.
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