Decorrelating Action of Inhibition in Neocortical Networks

Inhibitory GABAergic interneurons have been extensively studied but their contribution to circuit dynamics remain poorly understood. Although it has been suggested that interneurons, especially those belonging to the same subclass, synchronize their activity and impart this synchrony onto their local network, recent theoretical and experimental work have challenged this view. To better understand the activity of interneurons during cortical activity, we combined molecular identification, two-photon imaging, and electrophysiological recordings in thalamocortical slices from mouse somatosensory cortex. Using calcium imaging to monitor cortical activity, we found low spiking correlations among parvalbumin or somatostatin interneurons during cortical UP states, indicating that interneurons do not synchronize their firing. Intracellular recordings confirmed that nearby interneurons do not display more synchronous spiking than excitatory cells. The lack of interneuron synchrony was also evident during slow oscillations, even among interneurons that were electrically coupled via gap junctions, suggesting that their coupling does not function to synchronize their activity. Using voltage-clamp recordings from nearby pyramidal cells, we found that inhibitory currents (IPSCs) are more correlated than excitatory ones, but that correlated IPSCs arise from the activation of common presynaptic inhibitory cells, rather than from synchronization of interneuron activity. Finally, we demonstrate that pharmacologically reducing inhibitory currents increases correlated excitatory activity. We conclude that inhibitory interneurons do not have synchronous activity during UP states, and that their function may be to decorrelate rather than to synchronize the firing of neurons within the local network.

Network Activity and Plasticity

Vincent Delattre

The cortex must maintain balanced levels of neural activity to correctly integrate inputs and to provide contextually meaningful outputs. Neuronal excitation is counterbalanced by various forms of inhibition such as spike frequency adaptation, short- and long-term depression at excitatory synapses, and inhibitory cell coupling. When excitatory activity is low, homeostatic mechanisms enhance network excitability. When excitation is stronger than inhibition, network bursts of activity arise that also need to be dampened lest they run out of control. A disruption of the fine balance between excitatory and inhibitory systems is observed in an increasing numbers of brain disorders such as epilepsy, mental retardation and autism. This thesis aims to study aspects of the regulation of excitation in cortical networks at a molecular, cellular, network and disease level of investigation. We present in the first chapter an investigation of the impact of network bursts on standard spike-timing dependent plasticity (STDP) events in acute cortical brain slices. We discovered that these two kinds of events, which are the most well-established ways to induce synaptic plasticity in vitro, can block each other as well as cooperate to change the amplitude and direction of plasticity. Because the outcome of the interaction depends on the precise timing of network bursts relative to a STDP event in a single synaptic pathway, the observed network-timing dependent plasticity provides a novel mechanism for the modulation of local synaptic plasticity by the network level of activity, a form of global control of local synaptic plasticity. We hypothesized that network bursts consume extracellular resources needed to potentiate, restricting potentiation to active synapses at the burst onset while yielding depression of synapses activated at later times. As we demonstrate with simulation, this simple mechanism supports paradigm-shifting implications for models of learning, solving a persistent and fundamental problem since BCM (Bienenstock Cooper Munro, 1981) to incorporate synaptic learning into realistic neuronal networks while simultaneously establishing and maintaining excitatory-inhibitory balance. The proposed mechanism also links experimental evidence for interactions between STDP and network activity to observations of self-organized criticality in neural systems, a regime known to be optimal for information coding. In the second chapter, we investigated the effect of the loss of NLGN4 protein on synapse function and on network response to electrical stimulation. The neuroligin family of genes encodes for trans-synaptic proteins involved in synaptic differentiation and maturation. Former studies have reported that both NLGN1-KO and NLGN2-KO give rise to pathologic deregulations of the balance between excitation and inhibition in neural networks, and the presence of loss-of-function mutations in NLGN4 in a small number of autistic patients indicates a possible link between Neuroligin-4 gene and autism. Using extra-cellular stimulation and intra-cellular recordings in acute brain slices, we observed a decreased response of both excitatory and inhibitory response in NLGN4-KO animals, suggesting that NLGN4 is expressed at both excitatory and inhibitory synapses. Furthermore, we observed that the NLGN4-KO resulted in a significantly larger decrease of the excitatory response than of the inhibitory response, thus yielding a hypo-excitable network. The final chapter consists of the characterization of excitatory pathways in acute slices of the somato-sensory cortex. In the first study, we used chemical stimulation to promote the emergence of spontaneous recurrent activity and observed waves of activity originating from the cortical layer five. In the second study, we performed whole-cell patch-clamping of layer five pyramidal cells along with recording local field potentials (LFP). With the systematic layer-wise application of electrical stimulation at various frequencies coupled with LFP recordings, we obtained a frequency-dependent mapping of cortical inputs at all cortical layers at both the cellular and the network levels. Using this data, we developed a virtual framework for performing an analogous mapping in the virtual cortical column of the Blue Brain Project (BBP). This helped us understand the contribution of each cell population in the network response to stimulation. The framework also served as a validation test for the BBP cortical models.

EPFL2013

Structure and dynamics of the neocortical microcircuit connectivity

Jean-Vincent Le Bé

The neocortex is the most computationally advanced portion of the brain. It is currently assumed to be composed of a large number of "cortical columns" – intricate arrangements of cortical neurons approximately 300-500 µm in diameter and 2-5 mm in height in humans – that might serve as the elementary computational unit of the neocortex. Understanding the computation performed by this microcircuit is one of the keys to our comprehension of the brain. The so-called cortical column is not a static entity, however, and it evolves throughout a lifetime and continually adapts to the information from its cortical environment. Despite the differences between cortical columns across the cortex, a number of common features have been identified: a laminar structure, the dynamics of connections between identified neurons or the mechanisms for these connections to be modified (that give its specificity to each microcircuit). This thesis presents the description of the differential connectivity and synaptic dynamics across cell populations and the long term neuronal rewiring in a particular neuronal population within the cortical column. Somatic whole cell recordings have been performed to probe the connectivity, synaptic dynamics and plasticity of the connections in the rat neocortex. Two populations of layer V pyramidal neurons were studied in particular: cortico-callosally projecting pyramidal cells (CCPs) and thick tufted pyramidal cells (TTCs). The first major results from this work revealed the degree of connectivity and the linear dynamics of the CCPs population when compared to the TTCs. CCPs have nearly 4 times fewer interconnections and subsequent post-synaptic potentials were less decreasing in amplitude along a pre-synaptic series of action potentials. Long term configuration of TTC networks was explored. These experiments show for the first time the emergence of new functional synaptic connections between TTCs within hours. Activation of the slice by glutamate greatly increases their rate of emergence and this work demonstrated that metabotropic glutamate receptor 5 (mGluR5) activation and action potential firing are required for new connections to be formed in this experimental protocol. Newly formed connections respond in a more linear fashion and have weaker post-synaptic influence than already existing connections. Pre-existing connections are also modified after stimulation, requiring mGluR5, action potentials as well as α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid (AMPA) and N-methyl-D-aspartic acid (NMDA) receptors activation. The activation of group III metabotropic glutamate receptors (mGluRs) however results in a decrease in the strength of connections. Finally, the influence of inhibitory interneurons on the activity and connectivity between TTCs was also investigated. The results of this study show that firing of inhibitory interneurons can be triggered by the input of only one pyramidal cell. They further show that stimulation of a single TTC can result in an hyperpolarization of the post-synaptic TTC mediated by an interneurone. When the pre-synaptic neuron is also directly connected to the post-synaptic neuron with an excitatory synapse, the indirect inhibitory connection serves to curtail the excitatory response. This work has provided a new insight into the dynamic nature of the cortical microcircuitry, showing that it evolves rapidly and can adapt, reconfigure and rewire itself in remarkably short time-spans. It also describes the variety of dynamics exhibited by the different types of pyramidal cells, due to either the projecting site specificity or to the action of an intermediate interneuron.

EPFL2007

Disynaptic inhibition between neocortical pyramidal cells mediated by Martinotti cells

Henry Markram, Gilad Silberberg

Reliable activation of inhibitory pathways is essential for maintaining the balance between excitation and inhibition during cortical activity. Little is known, however, about the activation of these pathways at the level of the local neocortical microcircuit. We report a disynaptic inhibitory pathway among neocortical pyramidal cells (PCs). Inhibitory responses were evoked in layer 5 PCs following stimulation of individual neighboring PCs with trains of action potentials. The probability for inhibition between PCs was more than twice that of direct excitation, and inhibitory responses increased as a function of rate and duration of presynaptic discharge. Simultaneous somatic and dendritic recordings indicated that inhibition originated from PC apical and tuft dendrites. Multineuron whole-cell recordings from PCs and interneurons combined with morphological reconstructions revealed the mediating interneurons as Martinotti cells. Martinotti cells received facilitating synapses from PCs and formed reliable inhibitory synapses onto dendrites of neighboring PCs. We describe this feedback pathway and propose it as a central mechanism for regulation of cortical activity.