Long-term potentiation of synaptic transmission in the hippocampus is the primary experimental model for investigating the synaptic basis of learning and memory in vertebrates. The best understood form of long-term potentiation is induced by the activation of the N-methyl-D-aspartate receptor complex. This subtype of glutamate receptor endows long-term potentiation with Hebbian characteristics, and allows electrical events at the postsynaptic membrane to be transduced into chemical signals which, in turn, are thought to activate both pre- and postsynaptic mechanisms to generate a persistent increase in synaptic strength.

A synaptic model of memory: long-term potentiation in the hippocampus

A complementary DNA for the Aequorea victoria green fluorescent protein (GFP) produces a fluorescent product when expressed in prokaryotic (Escherichia coli) or eukaryotic (Caenorhabditis elegans) cells. Because exogenous substrates and cofactors are not required for this fluorescence, GFP expression can be used to monitor gene expression and protein localization in living organisms.

http://science.sciencemag.org/content/sci/263/5148/802.full.pdf

Green fluorescent protein as a marker for gene expression

Theoretical neuroscience provides a quantitative basis for describing what nervous systems do, determining how they function, and uncovering the general principles by which they operate This text introduces the basic mathematical and computational methods of theoretical neuroscience and presents applications in a variety of areas including vision, sensory-motor integration, development, learning, and memory The book is divided into three parts Part I discusses the relationship between sensory stimuli and neural responses, focusing on the representation of information by the spiking activity of neurons Part II discusses the modeling of neurons and neural circuits on the basis of cellular and synaptic biophysics Part III analyzes the role of plasticity in development and learning An appendix covers the mathematical methods used, and exercises are available on the book's Web site

Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems

Interneurons of the hippocampus

Neurons in the brain communicate by short electrical pulses, the so-called action potentials or spikes. How can we understand the process of spike generation? How can we understand information transmission by neurons? What happens if thousands of neurons are coupled together in a seemingly random network? How does the network connectivity determine the activity patterns? And, vice versa, how does the spike activity influence the connectivity pattern? These questions are addressed in this 2002 introduction to spiking neurons aimed at those taking courses in computational neuroscience, theoretical biology, biophysics, or neural networks. The approach will suit students of physics, mathematics, or computer science; it will also be useful for biologists who are interested in mathematical modelling. The text is enhanced by many worked examples and illustrations. There are no mathematical prerequisites beyond what the audience would meet as undergraduates: more advanced techniques are introduced in an elementary, concrete fashion when needed.

/pdf/spiking-neuron-models-single-neurons-populations-plasticity-58gzrd6ih6.pdf

Spiking Neuron Models: Single Neurons, Populations, Plasticity

SENSORY systems are often required to detect a small amplitude signal embedded in broadband background noise. Traditionally, ambient noise is regarded as detrimental to encoding accuracy. Recently, however, a phenomenon known as stochastic resonance has been described in which, for systems with a nonlinear threshold, increasing the input noise level can actually improve the output signal-to-noise ratio over a limited range of signal and noise strengths. Previous theoretical and experimental studies of stochastic resonance in physical1–7and biological6–10 systems have dealt exclusively with single-frequency sine stimuli embedded in a broadband noise background. In the past year it has been shown in a theoretical and modelling study that stochastic resonance can be observed with broadband signals11,12. Here we demonstrate that broadband stochastic resonance is manifest in the peripheral layers of neural processing in a simple sensory system, and that it plays a role over a wide range of biologically relevant stimulus parameters. Further, we quantify the functional significance of the phenomenon within the context of signal processing, using information theory.

Broadband neural encoding in the cricket cercal sensory system enhanced by stochastic resonance.

The stomatogastric nervous system: structure and function of a small neural network.

We propose a rigorous definition for the term temporal encoding as it is applied to schemes for the representation of information within patterns of neuronal action potentials, and distinguish temporal encoding schemes from those based on window-averaged mean rate encoding. The definition relies on the identification of an encoding time window, defined as the duration of a neuron's spike train assumed to correspond to a single symbol in the neural code. The duration of the encoding time window is dictated by the time scale of the information being encoded. We distinguish between the concepts of the encoding time window and the integration time window, the latter of which is defined as the duration of a stimulus signal that affects the response of the neuron. We note that the duration of the encoding and integration windows might be significantly different. We also present objective, experimentally assessable criteria for identifying neurons and neuronal ensembles that utilize temporal encoding to any significant extent. The definitions and criteria are made rigorous within the contexts of several commonly used analytical approaches, including the stimulus reconstruction analysis technique. Several examples are presented to illustrate the distinctions between and relative capabilities of rate encoding and temporal encoding schemes. We also distinguish our usage of temporal encoding from the term temporal coding, which is commonly used in reference to the representation of information about the timing of events by rate encoding schemes.

Temporal encoding in nervous systems: A rigorous definition

A simple technique for rapidly killing all or part of single neurons consists of filling the cell with Lucifer Yellow CH and irradiating all or part of it with intense blue light. Such treatment kills the irradiated part of the cell within a few minutes. Adjacent cells are not affected.

https://science.sciencemag.org/content/sci/206/4419/702.full.pdf

Rapid killing of single neurons by irradiation of intracellularly injected dye.

Activity-induced changes in the efficacy of synaptic transmission between neurones are central to several prominent theories of learning1–4. In both in vivo and in vitro preparations of the hippocampus, a conditioning high-frequency stimulus delivered to afferent fibres results in a long-term potentiation of synaptic transmission at those inputs5–8. Evidence has been provided supporting both presynaptic5,9–11 and postsynaptic12–14 sites as loci where critical events occur in the development of potentiation. In this study we report that long-term potentiation is reversibly blocked by intracellular injection of hyperpolarizing current in the postsynaptic cell during the conditioning high-frequency stimulus, suggesting the involvement of a voltage-dependent postsynaptic mechanism.

John P. Miller

Papers

Broadband neural encoding in the cricket cercal sensory system enhanced by stochastic resonance.

The stomatogastric nervous system: structure and function of a small neural network.

Temporal encoding in nervous systems: A rigorous definition

Rapid killing of single neurons by irradiation of intracellularly injected dye.

Postsynaptic hyperpolarization during conditioning reversibly blocks induction of long-term potentiation