The Morris water maze (MWM) is a test of spatial learning for rodents that relies on distal cues to navigate from start locations around the perimeter of an open swimming arena to locate a submerged escape platform. Spatial learning is assessed across repeated trials and reference memory is determined by preference for the platform area when the platform is absent. Reversal and shift trials enhance the detection of spatial impairments. Trial-dependent, latent and discrimination learning can be assessed using modifications of the basic protocol. Search-to-platform area determines the degree of reliance on spatial versus non-spatial strategies. Cued trials determine whether performance factors that are unrelated to place learning are present. Escape from water is relatively immune from activity or body mass differences, making it ideal for many experimental models. The MWM has proven to be a robust and reliable test that is strongly correlated with hippocampal synaptic plasticity and NMDA receptor function. We present protocols for performing variants of the MWM test, from which results can be obtained from individual animals in as few as 6 days.

Morris water maze: procedures for assessing spatial and related forms of learning and memory

Excitability. Excitability of cell membranes is crucial for signaling in many types of cell. Excitation in the physiological sense means that the cell membrane potential undergoes characteristic changes which, in most cases, go in the depolarizing direction. Single depolarization from the resting potential to potentials near 0 mV has generally been called an action potential. A schematic representation of a neuronal action potential is given in Fig. 12.1 A. The action potential is triggered when the membrane potential, which was at the resting level, depolarizes and reaches the threshold of excitation. This depolarization, which triggers the action potential, is generated by depolarizing synaptic currents, or depolarizing current coming from a membrane region that is already excited (propagation of an action potential), or by pacemaker currents mediated by pacemaker channels, or by current injected externally by an electrode. The duration of different types of action potential varies from seconds to less than 1 ms.

Ion Channels in Excitable Membranes

Long-term potentiation of synaptic transmission in the hippocampus is the leading experimental model for the synaptic changes that may underlie learning and memory. This review presents a current understanding of the molecular mechanisms of this long-lasting increase in synaptic strength and describes a simple model that unifies much of the data that previously were viewed as contradictory.

/pdf/long-term-potentiation-a-decade-of-progress-1y4lo4uwwe.pdf

Long-Term Potentiation--A Decade of Progress?

Changing the strength of connections between neurons is widely assumed to be the mechanism by which memory traces are encoded and stored in the central nervous system. In its most general form, the synaptic plasticity and memory hypothesis states that "activity-dependent synaptic plasticity is induced at appropriate synapses during memory formation and is both necessary and sufficient for the infor- mation storage underlying the type of memory mediated by the brain area in which that plasticity is observed." We outline a set of criteria by which this hypothesis can be judged and describe a range of experimental strategies used to investigate it. We review both classical and newly discovered properties of synaptic plasticity and stress the importance of the neural architecture and synaptic learning rules of the network in which it is embedded. The greater part of the article focuses on types of memory mediated by the hippocampus, amygdala, and cortex. We conclude that a wealth of data supports the notion that synaptic plasticity is necessary for learning and memory, but that little data currently supports the notion of sufficiency.

Synaptic plasticity and memory: an evaluation of the hypothesis

The term non-coding RNA (ncRNA) is commonly employed for RNA that does not encode a protein, but this does not mean that such RNAs do not contain information nor have function. Although it has been generally assumed that most genetic information is transacted by proteins, recent evidence suggests that the majority of the genomes of mammals and other complex organisms is in fact transcribed into ncRNAs, many of which are alternatively spliced and/or processed into smaller products. These ncRNAs include microRNAs and snoRNAs (many if not most of which remain to be identified), as well as likely other classes of yet-to-be-discovered small regulatory RNAs, and tens of thousands of longer transcripts (including complex patterns of interlacing and overlapping sense and antisense transcripts), most of whose functions are unknown. These RNAs (including those derived from introns) appear to comprise a hidden layer of internal signals that control various levels of gene expression in physiology and development, including chromatin architecture/epigenetic memory, transcription, RNA splicing, editing, translation and turnover. RNA regulatory networks may determine most of our complex characteristics, play a significant role in disease and constitute an unexplored world of genetic variation both within and between species.

Non-coding RNA

New mechanistic insights into memory processes.

This invention pertains to the discovery that a mutation disabling the Kv beta 1.1 subunit of a A-type K channel decreases the slow afterhyperpolarization (sAHP) of hippocampal CA1 neurons and improves learning and memory in hippocampus-dependent tasks: Importantly, young mutants do not show this improvement indicating that the inihibition of Kv beta 1.1 mediates the effects of age-related loss of learning ability and memory. Thus, in one embodiment this invention provides assays for modulators of Kv beta 1.1.

Kv BETA 1.1-DEFICIENT MICE WITH IMPAIRED LEARNING

Mouse genetic approaches to investigating CaMKII function in plasticity and cognition

Neuronal activity-dependent transcription directs molecular processes that regulate synaptic plasticity, brain circuit development, behavioral adaptation, and long-term memory. Single cell RNA-sequencing technologies (scRNAseq) are rapidly developing and allow for the interrogation of activity-dependent transcription at cellular resolution. Here, we present NEUROeSTIMator, a deep learning model that integrates transcriptomic signals to estimate neuronal activation in a way that we demonstrate is associated with Patch-seq electrophysiological features and that is robust against differences in species, cell type, and brain region. We demonstrate this method’s ability to accurately detect neuronal activity in previously published studies of single cell activity-induced gene expression. Further, we applied our model in a spatial transcriptomic study to identify unique patterns of learning-induced activity across different brain regions. Altogether, our findings establish NEUROeSTIMator as a powerful and broadly applicable tool for measuring neuronal activation, whether as a critical covariate or a primary readout of interest.

/pdf/neuroestimator-using-deep-learning-to-quantify-neuronal-2u23vvuh.pdf

NEUROeSTIMator: Using Deep Learning to Quantify Neuronal Activation from Single-Cell and Spatial Transcriptomic Data

This book integrates discoveries from recent years to show the diversity of molecular mechanisms that contribute to memory consolidation, reconsolidation, extinction, and forgetting. It provides a special focus on the processes that govern functional and structural plasticity of dendritic spines.In nine chapters, new and important ideas related to learning and memory processes are presented. Themes discussed includethe role of AMPA receptors in memory, two signalling cascades involved in local spine remodelling and memory, the role of extracellular matrix proteins in memory, the regulation of gene expression and protein translation, and mechanisms of retrieval-induced memory modulation and forgetting. The editors believe that the study of these topics represents a great step toward understanding the complexity of the brain and the processes it governs

Karl Peter Giese

Papers

New mechanistic insights into memory processes.

Kv BETA 1.1-DEFICIENT MICE WITH IMPAIRED LEARNING

Mouse genetic approaches to investigating CaMKII function in plasticity and cognition

NEUROeSTIMator: Using Deep Learning to Quantify Neuronal Activation from Single-Cell and Spatial Transcriptomic Data

Novel Mechanisms of Memory