Dendritic Slow Dynamics Enables Localized Cortical Activity to Switch between Mobile and Immobile Modes with Noisy Background Input

Mounting lines of evidence suggest the significant computational ability of a single neuron empowered by active dendritic dynamics. This motivates us to study what functionality can be acquired by a network of such neurons. The present paper studies how such rich single-neuron dendritic dynamics affects the network dynamics, a question which has scarcely been specifically studied to date. We simulate neurons with active dendrites networked locally like cortical pyramidal neurons, and find that naturally arising localized activity – called a bump – can be in two distinct modes, mobile or immobile. The mode can be switched back and forth by transient input to the cortical network. Interestingly, this functionality arises only if each neuron is equipped with the observed slow dendritic dynamics and with in vivo-like noisy background input. If the bump activity is considered to indicate a point of attention in the sensory areas or to indicate a representation of memory in the storage areas of the cortex, this would imply that the flexible mode switching would be of great potential use for the brain as an information processing device. We derive these conclusions using a natural extension of the conventional field model, which is defined by combining two distinct fields, one representing the somatic population and the other representing the dendritic population. With this tool, we analyze the spatial distribution of the degree of after-spike adaptation and explain how we can understand the presence of the two distinct modes and switching between the modes. We also discuss the possible functional impact of this mode-switching ability

Choice and Value Flexibility Jointly Contribute to the Capacity of a Subsampled Quadratic Classifier

Biophysical modeling studies have suggested that neurons with active dendrites can be viewed as linear units augmented by product terms which arise from interactions between synaptic inputs within the same dendritic subregions. However, the degree to which local nonlinear synaptic interactions augment the memory capacity of a neuron is not known in a quantitative sense. To approach this question, we have studied the family of subsampled quadratic classiers, i.e. linear classiers augmented by the best k terms from the set of K = (d 2 + d)=2 second-order product terms available in d dimensions. We developed an expression for the total parameter entropy of an SQ classier, whose form shows that the capacity of an SQ classier does not reside solely in its conventional weight values|i.e. the explicit memory used to store constant, linear, and higher-order coeÆcients. Rather, we identify a second type of parameter exibility which jointly contributes to an SQ classier's capacity: the ..

Placental morphology and the cellular brain in mammalian evolution

A major focus of evolutionary neurobiology has been on whether different regions of the eutherian brain evolve in concert, and how free the brain is to evolve independently of body plans. Since the eutherian brain is loosely modularized, such that one region is rarely isolated for specialization at the expense of others, but the design of modularization itself can be adapted by tweaking developmental programs, the degree to which brain regions must evolve in concert and can evolve independently may carry a deep phylogenetic signal. Using data collected from preserved brain tissue of 37 primate, 21 carnivore, and 15 other eutherian species (spanning 11 orders), I examined the phylogenetic level at which the proliferation of neurons and glia in the primary visual cortex and hippocampus proper, as well as granular layer volumes of the dentate gyrus and cerebellum, may be constrained by conserved developmental programs. In doing so, I was able to test for cellular signatures of (1) evolutionary changes in metabolic activity, (2) phylogenetic divergences, (3) specializations in behavior, and (4) developmental constraints. The degree to which disparate brain regions evolve in concert is shown to be generally conserved in Eutheria, although a derived ability to evolve regions independently is observed along the primate lineage. Using a separate dataset on placental and life-histroy character states, a comprehensive comparative phylogenetic approach was used to resolve relationships among five aspects of placental structure and to identify syndromes of placental morphology with life-history variables. My results support two discrete biological phenotypes of placental morphology and life-history, which are shown to have an evolutionary affect on allocortical, but not neocortical, brain organization. I have provided a new perspective on exploring how developmental constraints – acting both within and without the brain – may affect brain organization at the cellular level, and the extent to which those constraints have been adapted along certain eutherian lineages