Changing the responses of cortical neurons from sub- to suprathreshold using single spikes in vivo

Action Potential (APs) patterns of sensory cortex neurons encode a variety of stimulus features, but how can a neuron change the feature to which it responds? Here, we show that in vivo a spike-timing-dependent plasticity (STDP) protocol-consisting of pairing a postsynaptic AP with visually driven presynaptic inputs-modifies a neurons' AP-response in a bidirectional way that depends on the relative AP-timing during pairing. Whereas postsynaptic APs repeatedly following presynaptic activation can convert subthreshold into suprathreshold responses, APs repeatedly preceding presynaptic activation reduce AP responses to visual stimulation. These changes were paralleled by restructuring of the neurons response to surround stimulus locations and membrane-potential time-course. Computational simulations could reproduce the observed subthreshold voltage changes only when presynaptic temporal jitter was included. Together this shows that STDP rules can modify output patterns of sensory neurons and the timing of single-APs plays a crucial role in sensory coding and plasticity.

Microcircuits of excitatory and inhibitory neurons in layer 2/3 of mouse barrel cortex

Michael Avermann, Wulfram Gerstner, Céline Matéo, Carl Petersen, Christian Tomm

Avermann M, Tomm C, Mateo C, Gerstner W, Petersen CC. Microcircuits of excitatory and inhibitory neurons in layer 2/3 of mouse barrel cortex. J Neurophysiol 107: 3116-3134, 2012. First published March 7, 2012; doi:10.1152/jn.00917.2011.-Synaptic interactions between nearby excitatory and inhibitory neurons in the neocortex are thought to play fundamental roles in sensory processing. Here, we have combined optogenetic stimulation, whole cell recordings, and computational modeling to define key functional microcircuits within layer 2/3 of mouse primary somatosensory barrel cortex. In vitro optogenetic stimulation of excitatory layer 2/3 neurons expressing channelrhodopsin-2 evoked a rapid sequence of excitation followed by inhibition. Fast-spiking (FS) GABAergic neurons received large-amplitude, fast-rising depolarizing postsynaptic potentials, often driving action potentials. In contrast, the same optogenetic stimulus evoked small-amplitude, subthreshold postsynaptic potentials in excitatory and non-fast-spiking (NFS) GABAergic neurons. To understand the synaptic mechanisms underlying this network activity, we investigated unitary synaptic connectivity through multiple simultaneous whole cell recordings. FS GABAergic neurons received unitary excitatory postsynaptic potentials with higher probability, larger amplitudes, and faster kinetics compared with NFS GABAergic neurons and other excitatory neurons. Both FS and NFS GABAergic neurons evoked robust inhibition on postsynaptic layer 2/3 neurons. A simple computational model based on the experimentally determined electrophysiological properties of the different classes of layer 2/3 neurons and their unitary synaptic connectivity accounted for key aspects of the network activity evoked by optogenetic stimulation, including the strong recruitment of FS GABAergic neurons acting to suppress firing of excitatory neurons. We conclude that FS GABAergic neurons play an important role in neocortical microcircuit function through their strong local synaptic connectivity, which might contribute to driving sparse coding in excitatory layer 2/3 neurons of mouse barrel cortex in vivo.

American Physiological Society2012

Phenomenological models of synaptic plasticity based on spike timing

Wulfram Gerstner

Synaptic plasticity is considered to be the biological substrate of learning and memory. In this document we review phenomenological models of short-term and long-term synaptic plasticity, in particular spike-timing dependent plasticity (STDP). The aim of the document is to provide a framework for classifying and evaluating different models of plasticity. We focus on phenomenological synaptic models that are compatible with integrate-and-fire type neuron models where each neuron is described by a small number of variables. This implies that synaptic update rules for short-term or long-term plasticity can only depend on spike timing and, potentially, on membrane potential, as well as on the value of the synaptic weight, or on low-pass filtered (temporally averaged) versions of the above variables. We examine the ability of the models to account for experimental data and to fulfill expectations derived from theoretical considerations. We further discuss their relations to teacher-based rules (supervised learning) and reward-based rules (reinforcement learning). All models discussed in this paper are suitable for large-scale network simulations.

Springer Verlag2008

Timed Synaptic Inhibition Shapes NMDA Spikes, Influencing Local Dendritic Processing and Global I/O Properties of Cortical Neurons

Giuseppe Chindemi, Michael Doron, Henry Markram, Eilif Benjamin Muller, Idan Segev

The NMDA spike is a long-lasting nonlinear phenomenon initiated locally in the dendritic branches of a variety of cortical neurons. It plays a key role in synaptic plasticity and in single-neuron computations. Combining dynamic system theory and computational approaches, we now explore how the timing of synaptic inhibition affects the NMDA spike and its associated membrane current. When impinging on its early phase, individual inhibitory synapses strongly, but transiently, dampen the NMDA spike; later inhibition prematurely terminates it. A single inhibitory synapse reduces the NMDA-mediated Ca2+ current, a key player in plasticity, by up to 45%. NMDA spikes in distal dendritic branches/spines are longer-lasting and more resilient to inhibition, enhancing synaptic plasticity at these branches. We conclude that NMDA spikes are highly sensitive to dendritic inhibition; sparse weak inhibition can finely tune synaptic plasticity both locally at the dendritic branch level and globally at the level of the neuron's output.

2017

Microcircuits of excitatory and inhibitory neurons in layer 2/3 of mouse barrel cortex

Michael Avermann, Wulfram Gerstner, Céline Matéo, Carl Petersen, Christian Tomm

American Physiological Society2012