Perineuronal nets (PNNs) enwrap mature neurons, playing a role in the control of plasticity and synapse dynamics. PNNs have been shown to have effects on memory formation, retention and extinction in a variety of animal models. It has been proposed that the cavities in PNNs, which contain synapses, can act as a memory store and that they remain stable after events that cause synaptic withdrawal such as anoxia or hibernation. We examine this idea by monitoring place memory before and after synaptic withdrawal caused by acute hibernation-like state (HLS). Animals lacking hippocampal PNNs due to enzymatic digestion by chondroitinase ABC or knockout of the PNN component aggrecan were compared with wild type controls. HLS-induced synapse withdrawal caused a memory deficit, but not to the level of untreated naïve animals and not worsened by PNN attenuation. After HLS, only animals lacking PNNs showed memory restoration or relearning. Absence of PNNs affected the restoration of excitatory synapses on PNN-bearing neurons. The results support a role for hippocampal PNNs in learning, but not in long-term memory storage for correction of deficits.

• MeSH
• extracelulární matrix - proteiny MeSH
• extracelulární matrix * MeSH
• neurony fyziologie   MeSH
• synapse * MeSH
• učení MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• extracelulární matrix - proteiny MeSH

All components of the CNS are surrounded by a diffuse extracellular matrix (ECM) containing chondroitin sulphate proteoglycans (CSPGs), heparan sulphate proteoglycans (HSPGs), hyaluronan, various glycoproteins including tenascins and thrombospondin, and many other molecules that are secreted into the ECM and bind to ECM components. In addition, some neurons, particularly inhibitory GABAergic parvalbumin-positive (PV) interneurons, are surrounded by a more condensed cartilage-like ECM called perineuronal nets (PNNs). PNNs surround the soma and proximal dendrites as net-like structures that surround the synapses. Attention has focused on the role of PNNs in the control of plasticity, but it is now clear that PNNs also play an important part in the modulation of memory. In this review we summarize the role of the ECM, particularly the PNNs, in the control of various types of memory and their participation in memory pathology. PNNs are now being considered as a target for the treatment of impaired memory. There are many potential treatment targets in PNNs, mainly through modulation of the sulphation, binding, and production of the various CSPGs that they contain or through digestion of their sulphated glycosaminoglycans.

• MeSH
• chondroitinsulfát proteoglykany * metabolismus   MeSH
• dendrity metabolismus   MeSH
• extracelulární matrix * metabolismus   MeSH
• neurony metabolismus   MeSH
• neuroplasticita fyziologie   MeSH
• synapse metabolismus   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• přehledy MeSH
• Research Support, N.I.H., Extramural MeSH
• Názvy látek
• chondroitinsulfát proteoglykany * MeSH

Perineuronal nets (PNNs) are mesh-like structures, composed of a hierarchical assembly of extracellular matrix molecules in the central nervous system (CNS), ensheathing neurons and regulating plasticity. The mechanism of interactions between PNNs and neurons remain uncharacterized. In this review, we pose the question: how do PNNs regulate communication to and from neurons? We provide an overview of the current knowledge on PNNs with a focus on the cellular interactions. PNNs ensheath a subset of the neuronal population with distinct molecular aspects in different areas of the CNS. PNNs control neuronal communication through molecular interactions involving specific components of the PNNs. This review proposes that the PNNs are an integral part of neurons, crucial for the regulation of plasticity in the CNS.

• Klíčová slova
• chondroitin sulfates, hyaluronan, interneurons, neuronal communication, perineuronal nets, plasticity,
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH