Spike frequency adaptation supports network computations on temporally dispersed information

For solving tasks such as recognizing a song, answering a question, or inverting a sequence of symbols, cortical microcircuits need to integrate and manipulate information that was dispersed over time during the preceding seconds. Creating biologically realistic models for the underlying computations, especially with spiking neurons and for behaviorally relevant integration time spans, is notoriously difficult. We examine the role of spike frequency adaptation in such computations and find that it has a surprisingly large impact. The inclusion of this well-known property of a substantial fraction of neurons in the neocortex - especially in higher areas of the human neocortex - moves the performance of spiking neural network models for computations on network inputs that are temporally dispersed from a fairly low level up to the performance level of the human brain.

Emergent Connectivity Principles in the Neocortex

Imad Riachi

The neocortex makes up over 80% of the mammalian brain and is responsible for higher cognitive functions, processing of sensory inputs and orchestration of complex motor outputs. It is a 6-layered structure composed of billions of morphologically and electrically diverse neurons. Functionally, the basic unit is the neocortical column (NCC), a vertical structure of 0.5 mm wide, repeated millions of times across the neocortex and connected in an intricate but consistent way. In this thesis I investigated the role of morphologies (neurogeometry) in shaping the elaborate connectivity scheme within a column. First, I suggest a morphological basis for the higher than expected reciprocal connectivity reported experimentally between connected pairs, using a newly defined measure: the Reciprocity Index (RI), which arises from a purely mathematical concept and can be derived from the morphometric statistics of neurons. Second, I show that most experimentally reported synaptic patterns between different classes of neurons can be directly computed from the statistics of their morphologies, while some pathways would require additional functional mechanisms to refine an even more specific synaptic pattern. My thesis is done within the Blue Brain Project, the first comprehensive attempt to reverse-engineer the mammalian brain, starting with the somatosensory NCC of a P14 rat. I present in this thesis my contribution in constructing the framework for building biologically accurate circuitry. I explain how we start from 3D neuron morphologies obtained in vitro, repair them for slicing artefacts, build circuits and accurately detect potential synapses. I also explore how modelling of the experimental procedures can help us characterize biases and predict in vivo data from in vitro data. I finally present recent exploratory work on how to use the supercomputing power to design novel in silico protocols to investigate the emergent dynamics of the neocortical column.

EPFL2010

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

Large Volume Imaging of Rodent Brain Anatomy with Emphasis on Selective Plane Illumination Microscopy

Jean Pierre Ghobril

Inside the human brain there are 86 Billion neurons exchanging electrical impulses to allow reaction, homoeostasis and intelligence. Their coarse organization has been described, leaving us with a fair understanding of macrocircuitry. The microcircuitry of the brain is also being explored with patch clamp recordings. But a more integrative view on mesoscale organization of the central nervous system is still lacking. Recent developments in microscopy methods have opened new windows to address this point. It is the goal of this thesis to analyze and compare anatomical features of the brain with current routine techniques as well as explore light sheet microscopy for large scale quantitative reconstructions of rodent brains. Integration efforts of the cortical column model of the Blue Brain project into more detailed cortical circuitry sparked the search of acute slice preparations suitable for long range electrophysiology. Serial section reconstruction of the rat S1 hindlimb anterograde projections was performed with special attention to the anatomical relationship between S1 hindlimb region and VPL nucleus of thalamus. It was found that a functional electrophysiological slice preparation between S1-HL and VPL is feasible. The subsequent experimental exploration proved the intact fiber path in acute slice preparations based on the morphometric measurements of the previous serial sectioning reconstruction. Another mesoscale trait investigated was the excitatory to inhibitory ratio of the juvenile rat cortex. The measured numbers for the cellular density are higher than previously published. Cellular density for S1-HL is 84535

\pm

4400 neurons/mm

^{3}

high with an E-I ratio of 8.3. Like in other brains the cellular density is a continuously adapting function of the distance from pia and the current brain region. In the second part of this dissertation Selective Plane Illumination Microscopy(SPIM) and tissue clearing are evaluated as novel tools for whole mount rodent brain scanning, with emphasis on somata, fibers and vasculature as quantifiable brain features. Clearing methods are evaluated and a novel embedding medium for cleared tissues is presented: Thiodiethanol(TDE). Index matched brains with TDE show high degree of fluorescence conservation and transparency. Whole mount mouse and rat brains are imaged and reconstructed. The results show that whole mount microscopy is a potent tool that allows routine quantification of anatomic features on a whole brain level.

EPFL2015