Biology subjects

Weber, D.

Publications and source records attributed to Weber, D..

21 records · Page 2Linked to original sources

bioRxiv2020

The genus Microniphargus (Crustacea, Amphipoda): evidence for three lineages distributed across northwestern Europe and transfer to Pseudoniphargidae

Microniphargus leruthi Schellenberg, 1934 (Amphipoda: Niphargidae) was first described based on samples collected in Belgium and placed in a monotypic genus within the family Niphargidae. However, some details of its morphology as well as recent phylogenetic studies suggest that Microniphargus may be more closely related to Pseudoniphargus (Amphipoda: Pseudoniphargidae) than to Niphargus. Moreover, M. leruthi ranges over 1,469km from Ireland to Germany, which is striking since only a few niphargids have confirmed ranges in excess of 200km. To find out the phylogenetic position of M. leruthi and check whether it may be a complex of cryptic species, we collected material from Ireland, England and Belgium then sequenced fragments of the mitochondrial cytochrome c oxidase subunit 1 gene as well as of the nuclear 28S ribosomal gene. Phylogenetic analyses of both markers confirm that Microniphargus is closer to Pseudoniphargus than to Niphargus, leading us to reallocate Microniphargus to Pseudoniphargidae. We also identify three congruent mito-nuclear lineages present respectively in Ireland, in both Belgium and England, and in England only (with the latter found in sympatry at one location), suggesting that M. leruthi is a complex of at least three species with a putative centre of origin in England.

zoology↗

bioRxiv2020

Heuristic Spike Sorting Tuner (HSST), a framework to determine optimal parameter selection for a generic spike sorting algorithm

Bj[a]nes DA, Fisher LE, Gaunt RA, Weber DJHeuristic Spike Sorting Tuner (HSST), a framework to determine optimal parameter selection for a generic spike sorting algorithm. bioRxiv First published May 21, 2020. Extracellular microelectrodes frequently record neural activity from more than one neuron in the vicinity of the electrode. The process of labeling each recorded spike waveform with the identity of its source neuron is called spike sorting and is often approached from an abstracted statistical perspective. However, these approaches do not consider neurophysiological realities and may ignore important features that could improve the accuracy of these methods. Further, standard algorithms typically require selection of at least one free parameter, which can have significant effects on the quality of the output. We describe a Heuristic Spike Sorting Tuner (HSST) that determines the optimal choice of the free parameters for a given spike sorting algorithm based on the neurophysiological qualification of unit isolation and signal discrimination. A set of heuristic metrics are used to score the output of a spike sorting algorithm over a range of free parameters resulting in optimal sorting quality. We demonstrate that these metrics can be used to tune parameters in several spike sorting algorithms. The HSST algorithm shows robustness to variations in signal to noise ratio, number and relative size of units per channel. Moreover, the HSST algorithm is computationally efficient, operates unsupervised, and is parallelizable for batch processing. NEW & NOTEWORTHYHSST incorporates known neurophysiological priors of extracellular neural recordings while simultaneously taking advantage of powerful abstract mathematical tools. Rather than simply selecting free parameters prior to running a sorting algorithm, HSST executes a sorting algorithm across a range of input parameters, using heuristic metrics to detect which spike-sorting output is most physiologically plausible. This novel approach enables unsupervised spike-sorting exceeding the performance of previous methods, thereby enabling the processing of large data sets with confidence.

neuroscience↗

bioRxiv2019

Genetic variation in herbivore resistance within a strawberry crop wild relative (Fragaria vesca L.)

To decrease the dependency on chemical pesticides, the resistance of cultivated strawberry to pests needs to be increased. While genetic resources within domesticated varieties are limited, wild genotypes are predicted to show high heritable variation in useful resistance traits. We collected 86 wild accessions of Fragaria vesca L. from central Sweden and screened this germplasm for antibiosis (pest survival and performance) and antixenosis (pest preference) traits active against the strawberry leaf beetle (Galerucella tenella L.). First, extensive common garden experiments were used to study antibiosis traits in the sampled plant genotypes. Heritable genetic variation among plant genotypes was found for several antibiosis traits. Second, controlled cafeteria experiments were used to test for plant genetic variation in antixenosis traits. The leaf beetles avoided egg laying on plant genotypes possessing high antibiosis. This indicates a high degree of concordance between antibiosis and antixenosis, and that the beetles egg-laying behaviour optimizes the fitness of their offspring. The existence of high genetic variation in key resistance traits suggests that wild woodland strawberry contains untapped resources that are sought to reduce pesticide-dependence in cultivated strawberry. Given that only a very small portion of the species distribution area was sampled, even higher variation may be expected at the continental scale. As a whole, the genetic resources identified in this study serve to strengthen the position of woodland strawberry as a key crop wild relative.

plant biology↗