Donald Doherty's blog

Category: Brain Science

  • Chemical Inhibitory Synaptic Activity and Synchronous Activity in the Brain

    Synchronous activity is perhaps one of the clearest examples of signal organization in the brain. When electrical impulses known as action potentials appear in different neurons at nearly the same time, the brain is exhibiting synchronous activity. Research has implicated electrical connections between neurons known as gap junctions in synchronous brain activity and, as we have seen in an earlier blog post (see “Other related blog posts” below), inhibitory interneurons have also been shown to be involved. Research reported in the recent paper “Submillisecond firing synchrony between different subtypes of cortical interneurons connected chemically but not electrically” (published March 2, 2011 in the Journal of Neuroscience) specifically investigates the role of inhibitory chemical synapses in synchronous activity within a plus or minus 1 millisecond time window.

    In this research, simultaneous recordings were made of electrical activity from inside two neurons residing in layer 4 of the cerebral cortex (mouse somatosensory cortex slice setup). When one of the neurons spiked (elicited an action potential) the other neuron was considered to show synchronous firing if it spiked within 1 millisecond before or afterwards. The research team focused on fast spiking and somatostatin-containing inhibitory interneurons. Most important, the neurons they reported on in this paper had little or no electrical connections between them.

    The team saw significant synchronous firing in the 44 neuron pairs with little or no electrical connections that they reported on. Knocking out excitatory chemical synapses had no effect on synchronous activity. However, knocking out inhibitory chemical synapses significantly decreased synchronous activity. In short, this paper appears to be the most direct evidence to date that chemical inhibitory synaptic activity influences synchronous activity in the brain.


    Other related blog posts:

    The Identity of Inhibitory Interneurons Driving Gamma Oscillations in the Brain

  • Using Graph Theory in the Brain Sciences

    Graph theory has provided a new set of tools for helping us to understand signal processing networks in the brain (see “Other related blog posts” below for some earlier posts on graph theoretic based approaches). In particular, a field known as network theory or complex network theory, which is rooted in graph theory, has been helping to provide insight into the way circuits in the brain are wired and how those circuits contribute to brain function. The new review paper “Dissecting functional connectivity of neuronal microcircuits: experimental and theoretical insights” (published online April 2, 2011 in Trends in Neuroscience) provides a high-level look at using network theory in the brain sciences.

    First the authors explain key definitions for those unfamiliar with network theory. They discuss the features of networks that are typically captured in network theoretic equations. These equations are used for analyzing graphs composed of nodes and edges (links). Results of the analyses provide insights into the physical and functional organization of graphs.

    The nature of the insights provided by the analysis of a graph depend on the graph’s composition. Nodes may represent any number of brain structures. For example, nodes may represent neurons, brain areas, or dendritic spines. Edges represent the means of communication amongst the structures represented by the nodes. For example, edges may represent chemical synapses, gap junctions, or diffusible molecules.

    In network theory some general organizational principles have emerged. For instance, a scale-free network is a graph containing nodes that exhibit a wide range in their number of connections with other nodes. These graphs include rare hub nodes that have an extraordinarily large number of connections with other nodes. Hub nodes have a strong impact on signal processing within a network.

    Scale-free networks are found in neuronal circuits in the brain. For example, an important structure for learning and memory known as the hippocampus exhibits scale-free network organization during development. The inhibitory GABAergic neurons in this structure act as hubs that help orchestrate synchronous activity across the network. If these concepts or their application in the brain sciences are interesting and new to you then you may find this review paper to be a good introduction.


    Other related blog posts:

    New Analysis Methodologies and the Case for Data Sharing in Brain Research

    Sex Matters But the Brain is Like Nothing Else

    Explosive Change in Network Connectivity and Catastrophic Information Loss

    Synthetic Brain Cells and Graph Theory

  • A Virtual Fly Brain

    Figure 1. The Virtual Fly Brain beta website. Click on Show all Domains to view the controlled vocabulary displayed down the right-hand side of the page.

    This past December I wrote “I’d love to be able to use a virtual fly nervous system” (see How the Brain Works, Flies, and the FlyBase Online Data Repository). A week ago David Osumi-Sutherland from the FlyBase Consortium posted a response that “A beta version of Virtual Fly Brain is now live” (see Figure 1 above).

    In that previous blog post one of my questions was where the supraesophageal ganglion was located in the fly brain. I got a verbal description but no visual help. In the Virtual Fly Brain the supraesophageal ganglion is listed in the controlled vocabulary under Anatomy Tree and Search along the right-hand side of the page.

    Note: The Virtual Fly Brain page may display “Show all Domains” rather than list the anatomy terms. Click on “Show all Domains” to display the anatomy terms down the right-hand side of the page under the “Anatomy Tree and Search” heading.

    Figure 2. The supraesophageal ganglion includes the colorized area shown in in the fly brain displayed by the Virtual Fly Brain website.

    To highlight the supraesophageal ganglion in the fly brain image, first click on Clear all Selections to remove the terms that are selected by default. Next, click the check box to the left of the supraesophageal ganglion listing in the anatomy tree. The area defined as the supraesophageal ganglion fills with a transparent color shown in the little box to the right of the check box.

    The anatomy listing is a display of the Drosophila Brain anatomy ontology, which was developed using OWL2. The ontology provides a means to interlink fly anatomy with innumerable pieces of data. I look forward to exploring more of this promising tool as it develops.


    Other related blog posts:

    Viewing the Fly Brain Connectome with Brainbow

    How the Brain Works, Flies, and the FlyBase Online Data Repository