Biology subjects

Kennedy, H.

Publications and source records attributed to Kennedy, H..

4 recordsLinked to original sources

bioRxiv2018

A Gene Regulatory Model of Cortical Neurogenesis

Sparse data describing mouse cortical neurogenesis were used to derive a model gene regulatory network (GRN) that is then able to control the quantitative cellular dynamics of the observed neurogenesis. Derivation of the network begins by estimating from the biological data a set of cell states and transition probabilities necessary to explain neurogenesis. We show that the stochastic transition between states can be implemented by the dynamics of a GRN comprising only 36 abstract genes. Finally, we demonstrate using detailed physical simulations of cell mitosis, and differentiation that this GRN is able to steer a population of neuroepithelial precursors through mitotic expansion and differentiation to form the quantitatively correct complex multicellular architectures of mouse cortical areas 3 and 6. We find that the same GRN is able to generate both areas though modulation of only one gene, suggesting that arealization of the cortical sheet may require only simple improvisations on a fundamental gene network. We conclude that even sparse phenotypic and cell lineage data can be used to infer fundamental properties of neurogenesis and its organization.\n\n1. HighlightsO_LIEstimation of the cell states and transition probabilities of neurogenesis from experimental data.\nC_LIO_LIDesign of an abstract gene regulatory network (GRN) whose dynamics implement cell states and their stochastic transitions.\nC_LIO_LIDetailed simulation of GRN-guided neurogenesis for mouse cortical areas 3 and 6.\nC_LIO_LIDifferent dynamics of neurogenesis of distinct cortical areas arise through modulation of only a single gene.\nC_LI\n\n2. In briefPfister et al. show how sparse phenotypic and cell lineage data can be used to infer a small abstract gene regulatory network (GRN), which, when inserted into model precursor cells, is able to control in a distributed manner the quantitative cellular dynamics of neocortical neurogenesis.

neuroscience↗

bioRxiv2017

Neural circuits for long-range color filling-in

Surface color appearance depends on both local surface chromaticity and global context. How are these inter-dependencies supported by cortical networks? Combining functional imaging and psychophysics, we examined if color from long-range filling-in engages distinct pathways from responses caused by a field of uniform chromaticity. We find that color from filling-in is best classified and best correlated with appearance by two dorsal areas, V3A and V3B/KO. In contrast, a field of uniform chromaticity is best classified by ventral areas hV4 and LO. Dynamic causal modeling revealed feedback modulation from area V3A to areas V1 and LO for filling-in, contrasting with feedback from LO modulating areas V1 and V3A for a matched uniform chromaticity. These results indicate a dorsal stream role in color filling-in via feedback modulation of area V1 coupled with a cross-stream modulation of ventral areas suggesting that local and contextual influences on color appearance engage distinct neural networks.

neuroscience↗

bioRxiv2017

Cortical Connectivity In A Macaque Model Of Congenital Blindness

AbstractBrain-mapping of the congenitally blind human reveals extensive plasticity(1). The visual cortex of the blind has been observed to support higher cognitive functions including language and numerical processing(2, 3). This functional shift is hypothesized to reflect a metamodal cortical function, where computations are defined by the local network. In the case of developmental deafferentation, local circuits are considered to implement higher cognitive functions by accommodating diverse long-distance inputs(4-7). However, the extent to which visual deprivation triggers a reorganization of the large-scale network in the cortex is still controversial(8). Here we show that early prenatal ablation of the retina, an experimental model of anophthalmia in macaque, leads to a major reduction of area V1 and the creation of a default extrastriate cortex (DEC)(9, 10). Anophthalmic and normal macaques received retrograde tracer injections in DEC, as well as areas V2 and V4 post-natally. This revealed a six-fold expansion of the spatial extent of local connectivity in the DEC and a surprisingly high location of the DEC derived from a computational model of the cortical hierarchy(11). In the anophthalmic the set of areas projecting to the DEC, area V2 and V4 does not differ from that of normal adult controls, but there is a highly significant increase in the relative cumulative weight of the ventral stream areas input to the early visual areas. These findings show that although occupying the territory that would have become primary visual cortex the DEC exhibits features of a higher order area, thus reflecting a combination of intrinsic and extrinsic factors on cortical specification. Understanding the interaction of these contributing factors will shed light on cortical plasticity during primate development and the neurobiology of blindness.

neuroscience↗

bioRxiv2017

The Mouse Cortical Interareal Network Reveals Well Defined Connectivity Profiles and an Ultra Dense Cortical Graph

The inter-areal wiring pattern of mouse cerebral cortex was analyzed in relation to an accurate parcellation of cortical areas. Twenty-seven retrograde tracer injections were made in 19 areas of a 41 area (plus 7 sub-area) parcellation of the mouse neo-, parahippocampal and perirhinal cortex. Flat mounts of the cortex and multiple histological markers enabled detailed counts of labeled neurons in individual areas. A weight index was determined for each area-to-area pathway based on the Fraction of Extrinsically Labeled Neurons (FLNe). Data analysis allowed cross species comparison with the macaque. Estimation of FLNe statistical variability based on repeat injections revealed high consistency across individuals and justifies using a single injection per area to characterize connectivity. The observed lognormal distribution of connections to each cortical area spanned 5 orders of magnitude and revealed a distinct connectivity profile for each area, analogous to that observed in macaque. The resulting graph has a density of 97% (i.e. 97% of connections that can exist do exist), considerably higher than the 66% density reported for the macaque. Our results provide more sharply defined connectivity profiles and a markedly higher graph density than shown in a recent probabilistic mouse connectome.

neuroscience↗