Unraveling the mysteries of dendritic spine dynamics: Five key principles shaping memory and cognition

Stabilizing sequence learning in stochastic spiking networks with GABA-Modulated STDP

Cortical networks are capable of unsupervised learning and spontaneous replay of complex temporal sequences. Endowing artificial spiking neural networks with similar learning abilities remains a challenge. In particular, it is unresolved how different plasticity rules can contribute to both learning and the maintenance of network stability during learning. Here we introduce a biologically inspired form of GABA-Modulated Spike Timing-Dependent Plasticity (GMS) and demonstrate its ability to permit stable learning of complex temporal sequences including natural language in recurrent spiking neural networks. Motivated by biological findings, GMS utilizes the momentary level of inhibition onto excitatory cells to adjust both the magnitude and sign of Spike Timing-Dependent Plasticity (STDP) of connections between excitatory cells. In particular, high levels of inhibition in the network cause depression of excitatory-to-excitatory connections. We demonstrate the effectiveness of this mechanism during several sequence learning experiments with character- and token-based text inputs as well as visual input sequences. We show that GMS maintains stability during learning and spontaneous replay and permits the network to form a clustered hierarchical representation of its input sequences. Overall, we provide a biologically inspired model of unsupervised learning of complex sequences in recurrent spiking neural networks.

Associative learning and recollection of olfactory memory during the respiratory cycle in mammals: how is the self cognized in consciousness?

When we are awake and relaxed, various memory-scenes come up in our mind by spontaneous activation of memory engrams. We find ourselves in the memory-scene longing for it by the present self. The memory scene is also recollected by sensory inputs from the surrounding world for learned behavioral decisions. It is well experienced that odorants act as strong cues in remembering associated memory. Associative learning of odor signals and object cognition enables us to predict cognitive imagery of an environmental object. Here, we discuss the neural network connecting the olfactory cortices to the higher cognitive areas that dynamically switches the processing mode from feedforward to top-down. These processes are correlated with the respiratory cycle to form and recollect odor-object associative memory. We infer that during the inhalation phase, feedforward odor signals drive burst firings of a specific subset of pyramidal cells in the olfactory cortex. In contrast, during the subsequent late-exhalation phase, top-down cognitive scene-signals from the higher areas activate again the same pyramidal cells as those activated by the feedforward signals. Reactivation of pyramidal cells during the exhalation phase may induce plastic changes in the inter-areal synaptic connections in the neural network to form associative-learning memory. In this perspective article, we will discuss associative learning and cognition of self in the mammalian olfactory system.

Dendritic Spines of Layer 5 Pyramidal Neurons of the Aging Somatosensory Cortex Exhibit Reduced Volumetric Remodeling

Impairments in synaptic dynamics and stability are observed both in neurodegenerative disorders and in the healthy aging cortex, which exhibits elevated dendritic spine turnover and decreased long-term stability of excitatory connections at baseline, as well as an altered response to plasticity induction. In addition to the discrete gain and loss of synapses, spines also change in size and strength both during learning and in the absence of neural activity, and synaptic volume has been associated with stability and incorporation into memory traces. Furthermore, intrinsic dynamics, an apparently stochastic component of spine volume changes, may serve as a homeostatic mechanism to prevent stabilization of superfluous connections. However, the effects of age on modulation of synaptic weights remain unknown. Using two-photon excitation (2PE) microscopy of spines during chemical plasticity induction in vitro and analyzing longitudinal in vivo 2PE images after a plasticity-inducing manipulation, we characterize the effects of age on volumetric changes of spines of the apical tuft of layer 5 pyramidal neurons of mouse primary somatosensory cortex. Aged mice exhibit decreased volumetric volatility and delayed rearrangement of synaptic weights of persistent connections, as well as greater susceptibility to spine shrinkage in response to chemical long-term depression. These results suggest a deficit in the aging brain's ability to fine-tune synaptic weights to properly incorporate and retain novel memories. This research provides the first evidence of alterations in spine volumetric dynamics in healthy aging and may support a model of impaired processing and learning in the aged somatosensory system.

Plasticity-induced actin polymerization in the dendritic shaft regulates intracellular AMPA receptor trafficking

AMPA-type receptors (AMPARs) are rapidly inserted into synapses undergoing plasticity to increase synaptic transmission, but it is not fully understood if and how AMPAR-containing vesicles are selectively trafficked to these synapses. Here, we developed a strategy to label AMPAR GluA1 subunits expressed from their endogenous loci in cultured rat hippocampal neurons and characterized the motion of GluA1-containing vesicles using single-particle tracking and mathematical modeling. We find that GluA1-containing vesicles are confined and concentrated near sites of stimulation-induced structural plasticity. We show that confinement is mediated by actin polymerization, which hinders the active transport of GluA1-containing vesicles along the length of the dendritic shaft by modulating the rheological properties of the cytoplasm. Actin polymerization also facilitates myosin-mediated transport of GluA1-containing vesicles to exocytic sites. We conclude that neurons utilize F-actin to increase vesicular GluA1 reservoirs and promote exocytosis proximal to the sites of synaptic activity.

Synapse-specific structural plasticity that protects and refines local circuits during LTP and LTD

Synapses form trillions of connections in the brain. Long-term potentiation (LTP) and long-term depression (LTD) are cellular mechanisms vital for learning that modify the strength and structure of synapses. Three-dimensional reconstruction from serial section electron microscopy reveals three distinct pre- to post-synaptic arrangements: strong active zones (AZs) with tightly docked vesicles, weak AZs with loose or non-docked vesicles, and nascent zones (NZs) with a postsynaptic density but no presynaptic vesicles. Importantly, LTP can be temporarily saturated preventing further increases in synaptic strength. At the onset of LTP, vesicles are recruited to NZs, converting them to AZs. During recovery of LTP from saturation (1-4 h), new NZs form, especially on spines where AZs are most enlarged by LTP. Sentinel spines contain smooth endoplasmic reticulum (SER), have the largest synapses and form clusters with smaller spines lacking SER after LTP recovers. We propose a model whereby NZ plasticity provides synapse-specific AZ expansion during LTP and loss of weak AZs that drive synapse shrinkage during LTD. Spine clusters become functionally engaged during LTP or disassembled during LTD. Saturation of LTP or LTD probably acts to protect recently formed memories from ongoing plasticity and may account for the advantage of spaced over massed learning. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

Morphological heterogeneity of neurons in the human central amygdaloid nucleus

The central amygdaloid nucleus (CeA) has an ancient phylogenetic development and functions relevant for animal survival. Local cells receive intrinsic amygdaloidal information that codes emotional stimuli of fear, integrate them, and send cortical and subcortical output projections that prompt rapid visceral and social behavior responses. We aimed to describe the morphology of the neurons that compose the human CeA (N = 8 adult men). Cells within CeA coronal borders were identified using the thionine staining and were further analyzed using the "single-section" Golgi method followed by open-source software procedures for two-dimensional and three-dimensional image reconstructions. Our results evidenced varied neuronal cell body features, number and thickness of primary shafts, dendritic branching patterns, and density and shape of dendritic spines. Based on these criteria, we propose the existence of 12 morphologically different spiny neurons in the human CeA and discuss the variability in the dendritic architecture within cellular types, including likely interneurons. Some dendritic shafts were long and straight, displayed few collaterals, and had planar radiation within the coronal neuropil volume. Most of the sampled neurons showed a few to moderate density of small stubby/wide spines. Long spines (thin and mushroom) were observed occasionally. These novel data address the synaptic processing and plasticity in the human CeA. Our morphological description can be combined with further transcriptomic, immunohistochemical, and electrophysiological/connectional approaches. It serves also to investigate how neurons are altered in neurological and psychiatric disorders with hindered emotional perception, in anxiety, following atrophy in schizophrenia, and along different stages of Alzheimer's disease.