| 1. |
- Arvidsson, E, et al.
(författare)
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Forebrain NgR1 Overexpression Impairs DA Release Suggesting Synergy of Local and Global Synaptic Plasticity Mechanisms
- 2020
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Ingår i: Frontiers in synaptic neuroscience. - : Frontiers Media SA. - 1663-3563. ; 12, s. 545854-
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Tidskriftsartikel (refereegranskat)abstract
- Structural synaptic reorganizations needed to permanently embed novel memories in the brain involve complex plasticity-enhancing and plasticity-inhibiting systems. Increased neural activity is linked to rapid downregulation of Nogo receptor 1 (NgR1), needed to allow local structural synaptic plasticity. This local regulation of plasticity is thought to be moderated by global systems, such as the ascending cholinergic and monoaminergic systems, adding significance to locally increased neural activity. Here we address the reverse possibility that the global systems may also be influenced by the status of local plasticity. Using NgR1-overexpressing mice, with impaired plasticity and long-term memory, we measured the ability to release dopamine (DA), implicated in regulating plasticity and memory. In vivo chronoamperometric recording with high temporal and spatial resolution revealed severe impairment of potassium chloride (KCl)-induced increase of extracellular DA in the dorsal striatum of mice overexpressing NgR1 in forebrain neurons. A similar, but lesser, impairment of DA release was seen following amphetamine delivery. In contrast, potassium chloride-evoked DA release in NgR1 knockout (KO) mice led to increased levels of extracellular DA. That NgR1 can impair DA signaling, thereby further dampening synaptic plasticity, suggests a new role for NgR1 signaling, acting in synergy with DA signaling to control synaptic plasticity.Significance Statement:The inverse correlation between local NgR1 levels and magnitude of KCl-inducible amounts of DA release in the striatum reinforces the rule of NgR1 as a regulator of structural synaptic plasticity and suggests synergy between local and global plasticity regulating systems.
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| 2. |
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| 3. |
- Brodin, ATS, et al.
(författare)
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Five Hours Total Sleep Deprivation Does Not Affect CA1 Dendritic Length or Spine Density
- 2022
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Ingår i: Frontiers in synaptic neuroscience. - : Frontiers Media SA. - 1663-3563. ; 14, s. 854160-
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Tidskriftsartikel (refereegranskat)abstract
- Sleep is essential for long term memory function. However, the neuroanatomical consequences of sleep loss are disputed. Sleep deprivation has been reported to cause both decreases and increases of dendritic spine density. Here we use Thy1-GFP expressing transgenic mice to investigate the effects of acute sleep deprivation on the dendritic architecture of hippocampal CA1 pyramidal neurons. We found that 5 h of sleep deprivation had no effect on either dendritic length or dendritic spine density. Our work suggests that no major neuroanatomical changes result from a single episode of sleep deprivation.
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| 4. |
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| 5. |
- Grant, Seth G. N., et al.
(författare)
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The Synapse Diversity Dilemma : Molecular Heterogeneity Confounds Studies of Synapse Function
- 2020
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Ingår i: Frontiers in Synaptic Neuroscience. - : Frontiers Research Foundation. - 1663-3563. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Recent studies have shown an unexpectedly high degree of synapse diversity arising from molecular and morphological differences among individual synapses. Diverse synapse types are spatially distributed within individual dendrites, between different neurons, and across and between brain regions, producing the synaptome architecture of the brain. The spatial organization of synapse heterogeneity is important because the physiological activation of heterogeneous excitatory synapses produces a non-uniform spatial output of synaptic potentials, which confounds the interpretation of measurements obtained from population-averaging electrodes, optrodes and biochemical methods that lack single-synapse resolution. Population-averaging measurements cannot distinguish between changes in the composition of populations of synapses and changing synaptic physiology. Here we consider the implications of synapse diversity and its organization into synaptome architecture for studies of synapse physiology, plasticity, development and behavior, and for the interpretation of phenotypes arising from pharmacological and genetic perturbations. We conclude that prevailing models based on population-averaging measurements need reconsideration and that single-synapse resolution physiological recording methods are required to confirm or refute the major synaptic models of behavior.
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| 6. |
- Gustafsson, B., et al.
(författare)
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The Small and Dynamic Pre-primed Pool at the Release Site; A Useful Concept to Understand Release Probability and Short-Term Synaptic Plasticity?
- 2019
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Ingår i: Frontiers in Synaptic Neuroscience. - : Frontiers Media SA. - 1663-3563. ; 11
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Forskningsöversikt (refereegranskat)abstract
- Advanced imaging techniques have revealed that synapses contain nanomodules in which pre-and post-synaptic molecules are brought together to form an integrated subsynaptic component for vesicle release and transmitter reception. Based on data from an electrophysiological study of ours in which release from synapses containing a single nanomodule was induced by brief 50 Hz trains using minimal stimulation, and on data from such imaging studies, we present a possible modus operandi of such a nanomodule. We will describe the techniques and tools used to obtain and analyze the electrophysiological data from single CA3-CA1 hippocampal synapses from the neonatal rat brain. This analysis leads to the proposal that a nanomodule, despite containing a number of release locations, operates as a single release site, releasing at most a single vesicle at a time. In this nanomodule there appears to be two separate sets of release locations, one set that is responsible for release in response to the first few action potentials and another set that produces the release thereafter. The data also suggest that vesicles at the first set of release locations are primed by synaptic inactivity lasting seconds, this synaptic inactivity also resulting in a large heterogeneity in the values for vesicle release probability among the synapses. The number of vesicles being primed at this set of release locations prior to the arrival of an action potential is small (0-3) and varies from train to train. Following the first action potential, this heterogeneity in vesicle release probability largely vanishes in a release-independent manner, shaping a variation in paired-pulse plasticity among the synapses. After the first few action potentials release is produced from the second set of release locations, and is given by vesicles that have been recruited after the onset of synaptic activity. This release depends on the number of such release locations and the recruitment to such a location. The initial heterogeneity in vesicle release probability, its disappearance after a single action potential, and variation in the recruitment to the second set of release locations are instrumental in producing the heterogeneity in short-term synaptic plasticity among these synapses, and can be seen as means to create differential dynamics within a synapse population.
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| 7. |
- Lork, A. A., et al.
(författare)
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Chemical Imaging and Analysis of Single Nerve Cells by Secondary Ion Mass Spectrometry Imaging and Cellular Electrochemistry
- 2022
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Ingår i: Frontiers in Synaptic Neuroscience. - : Frontiers Media SA. - 1663-3563. ; 14
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Tidskriftsartikel (refereegranskat)abstract
- A nerve cell is a unit of neuronal communication in the nervous system and is a heterogeneous molecular structure, which is highly mediated to accommodate cellular functions. Understanding the complex regulatory mechanisms of neural communication at the single cell level requires analytical techniques with high sensitivity, specificity, and spatial resolution. Challenging technologies for chemical imaging and analysis of nerve cells will be described in this review. Secondary ion mass spectrometry (SIMS) allows for non-targeted and targeted molecular imaging of nerve cells and synapses at subcellular resolution. Cellular electrochemistry is well-suited for quantifying the amount of reactive chemicals released from living nerve cells. These techniques will also be discussed regarding multimodal imaging approaches that have recently been shown to be advantageous for the understanding of structural and functional relationships in the nervous system. This review aims to provide an insight into the strengths, limitations, and potentials of these technologies for synaptic and neuronal analyses.
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| 8. |
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| 9. |
- Raval, NR, et al.
(författare)
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Synaptic Density and Neuronal Metabolic Function Measured by Positron Emission Tomography in the Unilateral 6-OHDA Rat Model of Parkinson's Disease
- 2021
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Ingår i: Frontiers in synaptic neuroscience. - : Frontiers Media SA. - 1663-3563. ; 13, s. 715811-
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Tidskriftsartikel (refereegranskat)abstract
- Parkinson’s disease (PD) is caused by progressive neurodegeneration and characterised by motor dysfunction. Neurodegeneration of dopaminergic neurons also causes aberrations within the cortico-striato-thalamo-cortical (CSTC) circuit, which has been hypothesised to lead to non-motor symptoms such as depression. Individuals with PD have both lower synaptic density and changes in neuronal metabolic function in the basal ganglia, as measured using [11C]UCB-J and [18F]FDG positron emission tomography (PET), respectively. However, the two radioligands have not been directly compared in the same PD subject or in neurodegeneration animal models. Here, we investigate [11C]UCB-J binding and [18F]FDG uptake in the CSTC circuit following a unilateral dopaminergic lesion in rats and compare it to sham lesioned rats. Rats received either a unilateral injection of 6-hydroxydopamine (6-OHDA) or saline in the medial forebrain bundle and rostral substantia nigra (n = 4/group). After 3 weeks, all rats underwent two PET scans using [18F]FDG, followed by [11C]UCB-J on a separate day. [18F]FDG uptake and [11C]UCB-J binding were both lower in the ipsilateral striatal regions compared to the contralateral regions. Using [11C]UCB-J, we could detect an 8.7% decrease in the ipsilateral ventral midbrain, compared to a 2.9% decrease in ventral midbrain using [18F]FDG. Differential changes between hemispheres for [11C]UCB-J and [18F]FDG outcomes were also evident in the CSTC circuit’s cortical regions, especially in the orbitofrontal cortex and medial prefrontal cortex where higher synaptic density yet lower neuronal metabolic function was observed, following lesioning. In conclusion, [11C]UCB-J and [18F]FDG PET can detect divergent changes following a dopaminergic lesion in rats, especially in cortical regions that are not directly affected by the neurotoxin. These results suggest that combined [11C]UCB-J and [18F]FDG scans could yield a better picture of the heterogeneous cerebral changes in neurodegenerative disorders.
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| 10. |
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| 11. |
- Tully, Philip, 1988-, et al.
(författare)
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Synaptic and nonsynaptic plasticity approximating probabilistic inference
- 2014
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Ingår i: Frontiers in Synaptic Neuroscience. - : Frontiers Media SA. - 1663-3563. ; 6:APR
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Tidskriftsartikel (refereegranskat)abstract
- Learning and memory operations in neural circuits are believed to involve molecular cascades of synaptic and nonsynaptic changes that lead to a diverse repertoire of dynamical phenomena at higher levels of processing. Hebbian and homeostatic plasticity, neuromodulation, and intrinsic excitability all conspire to form and maintain memories. But it is still unclear how these seemingly redundant mechanisms could jointly orchestrate learning in a more unified system. To this end, a Hebbian learning rule for spiking neurons inspired by Bayesian statistics is proposed. In this model, synaptic weights and intrinsic currents are adapted on-line upon arrival of single spikes, which initiate a cascade of temporally interacting memory traces that locally estimate probabilities associated with relative neuronal activation levels. Trace dynamics enable synaptic learning to readily demonstrate a spike-timing dependence, stably return to a set-point over long time scales, and remain competitive despite this stability. Beyond unsupervised learning, linking the traces with an external plasticity-modulating signal enables spike-based reinforcement learning. At the postsynaptic neuron, the traces are represented by an activity-dependent ion channel that is shown to regulate the input received by a postsynaptic cell and generate intrinsic graded persistent firing levels. We show how spike-based Hebbian-Bayesian learning can be performed in a simulated inference task using integrate-and-fire (IAF) neurons that are Poisson-firing and background-driven, similar to the preferred regime of cortical neurons. Our results support the view that neurons can represent information in the form of probability distributions, and that probabilistic inference could be a functional by-product of coupled synaptic and nonsynaptic mechanisms operating over several timescales. The model provides a biophysical realization of Bayesian computation by reconciling several observed neural phenomena whose functional effects are only partially understood in concert.
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