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An inverse approach for elucidating dendritic function.

ABSTRACT: We outline an inverse approach for investigating dendritic function-structure relationships by optimizing dendritic trees for a priori chosen computational functions. The inverse approach can be applied in two different ways. First, we can use it as a "hypothesis generator" in which we optimize dendrites for a function of general interest. The optimization yields an artificial dendrite that is subsequently compared to real neurons. This comparison potentially allows us to propose hypotheses about the function of real neurons. In this way, we investigated dendrites that optimally perform input-order detection. Second, we can use it as a "function confirmation" by optimizing dendrites for functions hypothesized to be performed by classes of neurons. If the optimized, artificial, dendrites resemble the dendrites of real neurons the artificial dendrites corroborate the hypothesized function of the real neuron. Moreover, properties of the artificial dendrites can lead to predictions about yet unmeasured properties. In this way, we investigated wide-field motion integration performed by the VS cells of the fly visual system. In outlining the inverse approach and two applications, we also elaborate on the nature of dendritic function. We furthermore discuss the role of optimality in assigning functions to dendrites and point out interesting future directions.

SUBMITTER: Torben-Nielsen B

PROVIDER: S-EPMC2995390 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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An inverse approach for elucidating dendritic function.

Torben-Nielsen Benjamin B Stiefel Klaus M KM

Frontiers in computational neuroscience 20100923

We outline an inverse approach for investigating dendritic function-structure relationships by optimizing dendritic trees for a priori chosen computational functions. The inverse approach can be applied in two different ways. First, we can use it as a "hypothesis generator" in which we optimize dendrites for a function of general interest. The optimization yields an artificial dendrite that is subsequently compared to real neurons. This comparison potentially allows us to propose hypotheses abou ...[more]

PMID: 21258425

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Project description:Developing B lymphocytes undergo V(D)J recombination to assemble germline V, D, and J gene segments into exons that encode the antigen-binding variable region of immunoglobulin (Ig) heavy (H) and light (L) chains. IgH and IgL chains associate to form the B cell receptor (BCR), which upon antigen binding activates B cells to secrete BCR as an antibody. Each of the huge number of clonally independent B cells expresses a unique set of IgH and IgL variable regions. Ability of V(D)J recombination to generate vast primary B cell repertoires results from combinatorial assortment of large numbers of different V, D, and J segments, coupled with diversification of the junctions between them to generate the complementary determining region 3 (CDR3) for antigen contact. Approaches to evaluate in depth the content of primary antibody repertoires and, ultimately, to study how they are further molded by secondary mutation and affinity maturation processes are of great importance to the B cell development, vaccine, and antibody fields. We now describe an unbiased, sensitive, and readily accessible assay, referred to as HTGTS repertoire sequencing (HTGTS-Rep-seq), to quantify antibody repertoires. HTGTS-Rep-seq quantitatively identifies the vast majority of IgH and IgL V(D)J exons, including their unique CDR3 sequences, from progenitor and mature mouse B lineage cells via the use of specific J primers. HTGTS-Rep-seq also accurately quantifies DJH intermediates and V(D)J exons in either productive or non-productive configurations. HTGTS-Rep-seq should be useful for studies of human samples, including clonal B-cell expansions and also for following antibody affinity maturation processes. We employed high-throughput genome-wide translocation sequencing adapted repertoire sequencing (HTGTS-Rep-seq) to study antibody repertoires. For HTGTS-Rep-seq libraries, we utilize bait coding ends of J segments to identify, in unbiased fashion, mouse IgH DJH repertoires [processed tlx files] along with both productive and non-productive IgH V(D)J repertoires from both pro-B and peripheral B cells [processed xls files of samples 1-18, 21-51]. Similarly, we also identify mouse productive and non-productive Igk repertoires from peripheral B cells [processed xls files of samples 19,20,52-57].

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An inverse approach for elucidating dendritic function.

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An inverse approach for elucidating dendritic function.

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