A critical role for CaMKII in behavioral timescale synaptic plasticity in hippocampal CA1 pyramidal neurons

Non-spatial hippocampal behavioral timescale synaptic plasticity during working memory is gated by entorhinal inputs

Behavioral timescale synaptic plasticity (BTSP) is a form of synaptic potentiation where the occurrence of a single large plateau potential in CA1 hippocampal neurons leads to the formation of reliable place fields during spatial learning tasks. We asked whether BTSP could also be a plasticity mechanism for generation of non-spatial responses in the hippocampus and what roles the medial and lateral entorhinal cortex (MEC and LEC) play in driving non-spatial BTSP. By performing simultaneous calcium imaging of dorsal CA1 neurons and chemogenetic inhibition of LEC or MEC while mice performed an olfactory working memory task' we discovered BTSP-like events which formed stable odor-specific fields. Critically' the success rate of calcium events generating a significant odor-field increased with event amplitude' and large events exhibited asymmetrical formation with the newly formed odor-fields preceding the timepoint of their induction event. We found that MEC and LEC play distinct roles in modulating BTSP: MEC inhibition reduced the frequency of large calcium events' while LEC inhibition reduced the success rate of odor-field generation. Using two-photon calcium imaging of LEC and MEC temporammonic axons projecting to CA1 we found that LEC projections to CA1 were strongly odor selective even early in task learning' while MEC projection odor-selectivity increased with task learning but remained weaker than LEC. Finally' we found that LEC and MEC inhibition both slowed representational drift of odor representations in CA1 across 48 hours. Altogether' odor-specific information from LEC and strong odor-timed activity from MEC are crucial for driving BTSP in CA1 which is a synaptic plasticity mechanism for generation of both spatial and non-spatial responses in the hippocampus that may play a role in explaining representational drift and one-shot learning of non-spatial information.

Learning, Fast and Slow: Single- and Many-Shot Learning in the Hippocampus

The hippocampus is critical for memory and spatial navigation. The ability to map novel environments, as well as more abstract conceptual relationships, is fundamental to the cognitive flexibility that humans and other animals require to survive in a dynamic world. In this review, we survey recent advances in our understanding of how this flexibility is implemented anatomically and functionally by hippocampal circuitry, during both active exploration (online) and rest (offline). We discuss the advantages and limitations of spike timing-dependent plasticity and the more recently discovered behavioral timescale synaptic plasticity in supporting distinct learning modes in the hippocampus. Finally, we suggest complementary roles for these plasticity types in explaining many-shot and single-shot learning in the hippocampus and discuss how these rules could work together to support the learning of cognitive maps.

CaMKII autophosphorylation is the only enzymatic event required for synaptic memory

Ca2+/calmodulin (CaM)-dependent kinase II (CaMKII) plays a critical role in long-term potentiation (LTP), a well-established model for learning and memory through the enhancement of synaptic transmission. Biochemical studies indicate that CaMKII catalyzes a phosphotransferase (kinase) reaction of both itself (autophosphorylation) and of multiple downstream target proteins. However, whether either type of phosphorylation plays any role in the synaptic enhancing action of CaMKII remains hotly contested. We have designed a series of experiments to define the minimal requirements for the synaptic enhancement by CaMKII. We find that autophosphorylation of T286 and further binding of CaMKII to the GluN2B subunit are required both for initiating LTP and for its maintenance (synaptic memory). Once bound to the NMDA receptor, the synaptic action of CaMKII occurs in the absence of target protein phosphorylation. Thus, autophosphorylation and binding to the GluN2B subunit are the only two requirements for CaMKII in synaptic memory.

CaMKII activity and metabolic imbalance-related neurological diseases: Focus on vascular dysfunction, synaptic plasticity, amyloid beta accumulation, and lipid metabolism

Metabolic syndrome (MetS) is characterized by insulin resistance, hyperglycemia, excessive fat accumulation and dyslipidemia, and is known to be accompanied by neuropathological symptoms such as memory loss, anxiety, and depression. As the number of MetS patients is rapidly increasing globally, studies on the mechanisms of metabolic imbalance-related neuropathology are emerging as an important issue. Ca2+/calmodulin-dependent kinase II (CaMKII) is the main Ca2+ sensor and contributes to diverse intracellular signaling in peripheral organs and the central nervous system (CNS). CaMKII exerts diverse functions in cells, related to mechanisms such as RNA splicing, reactive oxygen species (ROS) generation, cytoskeleton, and protein-protein interactions. In the CNS, CaMKII regulates vascular function, neuronal circuits, neurotransmission, synaptic plasticity, amyloid beta toxicity, lipid metabolism, and mitochondrial function. Here, we review recent evidence for the role of CaMKII in neuropathologic issues associated with metabolic disorders.

A biochemical description of postsynaptic plasticity-with timescales ranging from milliseconds to seconds

Synaptic plasticity [long-term potentiation/depression (LTP/D)], is a cellular mechanism underlying learning. Two distinct types of early LTP/D (E-LTP/D), acting on very different time scales, have been observed experimentally-spike timing dependent plasticity (STDP), on time scales of tens of ms; and behavioral time scale synaptic plasticity (BTSP), on time scales of seconds. BTSP is a candidate for a mechanism underlying rapid learning of spatial location by place cells. Here, a computational model of the induction of E-LTP/D at a spine head of a synapse of a hippocampal pyramidal neuron is developed. The single-compartment model represents two interacting biochemical pathways for the activation (phosphorylation) of the kinase (CaMKII) with a phosphatase, with ion inflow through channels (NMDAR, CaV1,Na). The biochemical reactions are represented by a deterministic system of differential equations, with a detailed description of the activation of CaMKII that includes the opening of the compact state of CaMKII. This single model captures realistic responses (temporal profiles with the differing timescales) of STDP and BTSP and their asymmetries. The simulations distinguish several mechanisms underlying STDP vs. BTSP, including i) the flow of [Formula: see text] through NMDAR vs. CaV1 channels, and ii) the origin of several time scales in the activation of CaMKII. The model also realizes a priming mechanism for E-LTP that is induced by [Formula: see text] flow through CaV1.3 channels. Once in the spine head, this small additional [Formula: see text] opens the compact state of CaMKII, placing CaMKII ready for subsequent induction of LTP.

Neuronal calcium spikes enable vector inversion in the Drosophila brain

A typical neuron signals to downstream cells when it is depolarized and firing sodium spikes. Some neurons, however, also fire calcium spikes when hyperpolarized. The function of such bidirectional signaling remains unclear in most circuits. Here we show how a neuron class that participates in vector computation in the fly central complex employs hyperpolarization-elicited calcium spikes to invert two-dimensional mathematical vectors. When cells switch from firing sodium to calcium spikes, this leads to a ~180° realignment between the vector encoded in the neuronal population and the fly's internal heading signal, thus inverting the vector. We show that the calcium spikes rely on the T-type calcium channel Ca-α1T, and argue, via analytical and experimental approaches, that these spikes enable vector computations in portions of angular space that would otherwise be inaccessible. These results reveal a seamless interaction between molecular, cellular and circuit properties for implementing vector math in the brain.