The neocortical microcircuit as a tabula rasa

The neocortex has a high capacity for plasticity. To understand the full scope of this capacity, it is essential to know how neurons choose particular partners to form synaptic connections. By using multineuron whole-cell recordings and confocal microscopy we found that axons of layer V neocortical pyramidal neurons do not preferentially project toward the dendrites of particular neighboring pyramidal neurons; instead, axons promiscuously touch all neighboring dendrites without any bias. Functional synaptic coupling of a small fraction of these neurons is, however, correlated with the existence of synaptic boutons at existing touch sites. These data provide the first direct experimental evidence for a tabula rasa-like structural matrix between neocortical pyramidal neurons and suggests that pre- and postsynaptic interactions shape the conversion between touches and synapses to form specific functional microcircuits. These data also indicate that the local neocortical microcircuit has the potential to be differently rewired without the need for remodeling axonal or dendritic arbors.

Emergent Properties of in silico Synaptic Transmission in a Model of the Rat Neocortical Column

Srikanth Ramaswamy

The cerebral cortex occupies nearly 80% of the entire volume of the mammalian brain and is thought to subserve higher cognitive functions like memory, attention and sensory perception. The neocortex is the newest part in the evolution of the cerebral cortex and is perhaps the most intricate brain region ever studied. The neocortical microcircuit is the smallest Œecosystem‚ of the neocortex that consists of a rich assortment of neurons, which are diverse in both their morphological and electrical properties. In the neocortical microcircuit, neurons are horizontally arranged in 6 distinct sheets called layers. The fundamental operating unit of the neocortical microcircuit is believed to be the Neocortical Column (NCC). Functionally, a single NCC is an arrangement of thousands of neurons in a vertical fashion spanning across all the 6 layers. The structure of the entire neocortex arises from a repeated and stereotypical arrangement of several thousands of such columns, where neurons transmit information to each other through specialized points of information transfer called synapses. The dynamics of synaptic transmission can be as diverse as the neurons defining a connection and are crucial to foster the functional properties of the neocortical microcircuit. The Blue Brain Project (BBP) is the first comprehensive endeavour to build a unifying model of the NCC by systematic data integration and biologically detailed simulations. Through the past 5 years, the BBP has built a facility for a data-constraint driven approach towards modelling and integrating biological information across multiple levels of complexity. Guided by fundamental principles derived from biological experiments, the BBP simulation toolchain has undergone a process of continuous refinement to facilitate the frequent construction of detailed in silico models of the NCC. The focus of this thesis lies in characterizing the functional properties of in silico synaptic transmission by incorporating principles of synaptic communication derived through biological experiments. In order to study in silico synaptic transmission it is crucial to gain an understanding of the key players influencing the manner in which synaptic signals are processed in the neocortical microcircuit - ion channel kinetics and distribution profiles, single neuron models and dynamics of synaptic pathways. First, by means of exhaustive literature survey, I identified ion channel kinetics and their distribution profiles on neocortical neurons to build in silico ion channel models. Thereafter, I developed a prototype framework to analyze the somatic and dendritic features of single neuron models constrained by ion channel kinetics. Finally, within a simulation framework integrating the ion channels, single neuron models and dynamics of synaptic transmission, I replicated in vitro experimental protocols in silico, to characterize the transmission properties of monosynaptic connections. These synaptic connections, arising from the axo-dendritric apposition of neuronal arbours were sampled across many instances of in silico NCC models constructed a priori through the BBP simulation toolchain. In this thesis, I show that when principles of synaptic transmission derived from in vitro experiments are incorporated to model in silico synaptic connections, the resulting anatomy and physiology of synaptic connections modelled from elementary biological rules closely match in vitro data. This thesis work demonstrates that the average synaptic response properties in silico are robust to perturbations in the anatomical and physiological properties of modelled connections in the local neocortical microcircuit. A fundamental discovery through this thesis is an insight into the function of the local neocortical microcircuit by examining the effect of morphological diversity on in silico synaptic transmission. I demonstrate here that intrinsic morphological diversity confers an invariance to the average synaptic response properties in silico in the local neocortical microcircuit, termed "microcircuit level robustness and invariance".

EPFL2011

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

Models of neocortical layer 5b pyramidal cells capturing a wide range of dendritic and perisomatic active properties

Sean Lewis Hill, Henry Markram, Felix Schürmann, Idan Segev

The thick-tufted layer 5b pyramidal cell extends its dendritic tree to all six layers of the mammalian neocortex and serves as a major building block for the cortical column. L5b pyramidal cells have been the subject of extensive experimental and modeling studies, yet conductance-based models of these cells that faithfully reproduce both their perisomatic Na(+)-spiking behavior as well as key dendritic active properties, including Ca(2+) spikes and back-propagating action potentials, are still lacking. Based on a large body of experimental recordings from both the soma and dendrites of L5b pyramidal cells in adult rats, we characterized key features of the somatic and dendritic firing and quantified their statistics. We used these features to constrain the density of a set of ion channels over the soma and dendritic surface via multi-objective optimization with an evolutionary algorithm, thus generating a set of detailed conductance-based models that faithfully replicate the back-propagating action potential activated Ca(2+) spike firing and the perisomatic firing response to current steps, as well as the experimental variability of the properties. Furthermore, we show a useful way to analyze model parameters with our sets of models, which enabled us to identify some of the mechanisms responsible for the dynamic properties of L5b pyramidal cells as well as mechanisms that are sensitive to morphological changes. This automated framework can be used to develop a database of faithful models for other neuron types. The models we present provide several experimentally-testable predictions and can serve as a powerful tool for theoretical investigations of the contribution of single-cell dynamics to network activity and its computational capabilities.