Scientific Understanding of Consciousness
Consciousness as an Emergent Property of Thalamocortical Activity

Plasticity of Neural Connections — Recent Research


Neural Computation, March 2004, Vol. 16, No. 3, Pages 595-625

How the Shape of Pre- and Postsynaptic Signals Can Influence STDP: A Biophysical Model

Ausra Saudargiene

Department of Psychology, University of Stirling, Stirling FK9 4LA, Scotland, and Department of Informatics, Vytautas Magnus University, Kaunas, Lithuania,

Bernd Porr, Florentin Wörgötter

Department of Psychology, University of Stirling, Stirling FK9 4LA, Scotland,

Spike-timing-dependent plasticity (STDP) is described by long-term potentiation (LTP), when a presynaptic event precedes a postsynaptic event, and by long-term depression (LTD), when the temporal order is reversed. In this article, we present a biophysical model of STDP based on a differential Hebbian learning rule (ISO learning). This rule correlates presynaptically the NMDA channel conductance with the derivative of the membrane potential at the synapse as the postsynaptic signal. The model is able to reproduce the generic STDP weight change characteristic. We find that (1) The actual shape of the weight change curve strongly depends on the NMDA channel characteristics and on the shape of the membrane potential at the synapse. (2) The typical antisymmetrical STDP curve (LTD and LTP) can become similar to a standard Hebbian characteristic (LTP only) without having to change the learning rule. This occurs if the membrane depolarization has a shallow onset and is long lasting. (3) It is known that the membrane potential varies along the dendrite as a result of the active or passive backpropagation of somatic spikes or because of local dendritic processes. As a consequence, our model predicts that learning properties will be different at different locations on the dendritic tree. In conclusion, such site-specific synaptic plasticity would provide a neuron with powerful learning capabilities.


Neural Computation, November 2007, Vol. 19, No. 11, Pages 2881-2912

Learning Real-World Stimuli in a Neural Network with Spike-Driven Synaptic Dynamics

Joseph M. Brader, ­Walter Senn

Institute of Physiology, University of Bern, Bern, Switzerland

Stefano Fusi

Institute of Physiology, University of Bern, Bern, Switzerland, and Institute of Neuroinformatics, ETH|UNI Zurich, 8059, Zurich, Switzerland

We present a model of spike-driven synaptic plasticity inspired by experimental observations and motivated by the desire to build an electronic hardware device that can learn to classify complex stimuli in a semisupervised fashion. During training, patterns of activity are sequentially imposed on the input neurons, and an additional instructor signal drives the output neurons toward the desired activity. The network is made of integrate-and-fire neurons with constant leak and a floor. The synapses are bistable, and they are modified by the arrival of presynaptic spikes. The sign of the change is determined by both the depolarization and the state of a variable that integrates the postsynaptic action potentials. Following the training phase, the instructor signal is removed, and the output neurons are driven purely by the activity of the input neurons weighted by the plastic synapses. In the absence of stimulation, the synapses preserve their internal state indefinitely. Memories are also very robust to the disruptive action of spontaneous activity. A network of 2000 input neurons is shown to be able to classify correctly a large number (thousands) of highly overlapping patterns (300 classes of preprocessed Latex characters, 30 patterns per class, and a subset of the NIST characters data set) and to generalize with performances that are better than or comparable to those of artificial neural networks. Finally we show that the synaptic dynamics is compatible with many of the experimental observations on the induction of long-term modifications (spike-timing-dependent plasticity and its dependence on both the postsynaptic depolarization and the frequency of pre- and postsynaptic neurons).


Science 20 February 2009: Vol. 323. no. 5917, pp. 1074 - 1077

Neuronal Activity–Induced Gadd45b Promotes Epigenetic DNA Demethylation and Adult Neurogenesis

Dengke K. Ma,1,2 Mi-Hyeon Jang,1,3 Junjie U. Guo,1,2 Yasuji Kitabatake,1,3 Min-lin Chang,1,3 Nattapol Pow-anpongkul,1 Richard A. Flavell,4 Binfeng Lu,5 Guo-li Ming,1,2,3 Hongjun Song1,2,3

1 Institute for Cell Engineering, Johns Hopkins University School of Medicine, 733 North Broadway, Baltimore, MD 21205, USA.
2 The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, 733 North Broadway, Baltimore, MD 21205, USA.
3 Department of Neurology, Johns Hopkins University School of Medicine, 733 North Broadway, Baltimore, MD 21205, USA.
4 Department of Immunobiology, Howard Hughes Medical Institute, Yale University School of Medicine, 300 Cedar Street, New Haven, CT 06520, USA.
5 Department of Immunology, University of Pittsburgh, School of Medicine, Pittsburgh, PA 15261, USA.

The mammalian brain exhibits diverse types of neural plasticity, including activity-dependent neurogenesis in the adult hippocampus. How transient activation of mature neurons leads to long-lasting modulation of adult neurogenesis is unknown. Here we identify Gadd45b as a neural activity–induced immediate early gene in mature hippocampal neurons. Mice with Gadd45b deletion exhibit specific deficits in neural activity–induced proliferation of neural progenitors and dendritic growth of newborn neurons in the adult hippocampus. Mechanistically, Gadd45b is required for activity-induced DNA demethylation of specific promoters and expression of corresponding genes critical for adult neurogenesis, including brain-derived neurotrophic factor and fibroblast growth factor. Thus, Gadd45b links neuronal circuit activity to epigenetic DNA modification and expression of secreted factors in mature neurons for extrinsic modulation of neurogenesis in the adult brain.

Adult neurogenesis represents a prominent form of structural plasticity through continuous generation of new neurons in the mature mammalian brain. Similar to other neural activity-induced plasticity with fine structural changes within individual neurons, adult neurogenesis is modulated by a plethora of external stimuli. Synchronized activation of mature dentate neurons by electro-convulsive treatment (ECT) in adult mice causes sustained up-regulation of hippocampal neurogenesis without any detectable cell damage. How transient activation of mature neuronal circuits modulates adult neurogenesis over days and weeks is largely unknown.

Epigenetic mechanisms potentially provide a basis for such long-lasting modulation. Analysis of microdissected dentate gyrus tissue showed robust, transient induction of Gadd45b expression. Spatial exploration of a novel environment, a behavioral paradigm that activates immediate early genes (IEGs), also led to significant induction of Gadd45b.

How transient neuronal activation achieves long-lasting effects in neural plasticity and memory has been a long-standing question. DNA demethylation in neurons represents an extra layer of activity-dependent regulation, in addition to transcription factors and histone-modifying enzymes. Gadd45b may represent a common target of physiological stimuli in different neurons in vivo, and mechanisms involving epigenetic DNA modification may be fundamental for activity-dependent neural plasticity.


Science 4 January 2008: Vol. 319. no. 5859, pp. 101 - 104

Ongoing in Vivo Experience Triggers Synaptic Metaplasticity in the Neocortex

Roger L. Clem,1 Tansu Celikel,2* Alison L. Barth1

In vivo experience can occlude subsequent induction of long-term potentiation and enhance long-term depression of synaptic responses. Although a reduced capacity for synaptic strengthening may function to prevent excessive excitation, such an effect paradoxically implies that continued experience or training should not improve and may even degrade neural representations. In mice, we examined the effect of ongoing whisker stimulation on synaptic strengthening at layer 4-2/3 synapses in the barrel cortex. Although N-methyl-D-aspartate receptors were required to initiate strengthening, they subsequently suppressed further potentiation at these synapses in vitro and in vivo. Despite this transition, synaptic strengthening continued with additional sensory activity but instead required the activation of metabotropic glutamate receptors, suggesting a mechanism by which continued experience can result in increasing synaptic strength over time.

1 Department of Biological Sciences and Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
2 Department of Cell Physiology, Max Planck Institute for Medical Research, Jahnstrasse 29, 69120 Heidelberg, Germany.

* Present address: Laboratory of Neural Circuits and Plasticity, University of Southern California, 3641 Watt Way, HNB 501, Los Angeles, CA 90089-2520, USA.


Nature 448, 709-713 (9 August 2007)

Hebbian STDP in mushroom bodies facilitates the synchronous flow of olfactory information in locusts

Stijn Cassenaer1 & Gilles Laurent1

California Institute of Technology, Division of Biology, 139-74, Pasadena, California 91125, USA

Odour representations in insects undergo progressive transformations and decorrelation1, 2, 3 from the receptor array to the presumed site of odour learning, the mushroom body. There, odours are represented by sparse assemblies of Kenyon cells in a large population. Using intracellular recordings in vivo, we examined transmission and plasticity at the synapse made by Kenyon cells onto downstream targets in locusts. We find that these individual synapses are excitatory and undergo hebbian spike-timing dependent plasticity (STDP) on a plusminus25 ms timescale. When placed in the context of odour-evoked Kenyon cell activity (a 20-Hz oscillatory population discharge), this form of STDP enhances the synchronization of the Kenyon cells' targets and thus helps preserve the propagation of the odour-specific codes through the olfactory system.



    Return to — Plasticity of Neural Connections