| 1. |
- Niemi, MEK, et al.
(författare)
-
- 2021
-
swepub:Mat__t
|
|
| 2. |
- Kanai, M, et al.
(författare)
-
- 2023
-
swepub:Mat__t
|
|
| 3. |
|
|
| 4. |
- Foote, Andrew D., et al.
(författare)
-
Killer whale genomes reveal a complex history of recurrent admixture and vicariance
- 2019
-
Ingår i: Molecular Ecology. - : WILEY. - 0962-1083 .- 1365-294X. ; 28:14, s. 3427-3444
-
Tidskriftsartikel (refereegranskat)abstract
- Reconstruction of the demographic and evolutionary history of populations assuming a consensus tree-like relationship can mask more complex scenarios, which are prevalent in nature. An emerging genomic toolset, which has been most comprehensively harnessed in the reconstruction of human evolutionary history, enables molecular ecologists to elucidate complex population histories. Killer whales have limited extrinsic barriers to dispersal and have radiated globally, and are therefore a good candidate model for the application of such tools. Here, we analyse a global data set of killer whale genomes in a rare attempt to elucidate global population structure in a nonhuman species. We identify a pattern of genetic homogenisation at lower latitudes and the greatest differentiation at high latitudes, even between currently sympatric lineages. The processes underlying the major axis of structure include high drift at the edge of species' range, likely associated with founder effects and allelic surfing during postglacial range expansion. Divergence between Antarctic and non-Antarctic lineages is further driven by ancestry segments with up to fourfold older coalescence time than the genome-wide average; relicts of a previous vicariance during an earlier glacial cycle. Our study further underpins that episodic gene flow is ubiquitous in natural populations, and can occur across great distances and after substantial periods of isolation between populations. Thus, understanding the evolutionary history of a species requires comprehensive geographic sampling and genome-wide data to sample the variation in ancestry within individuals.
|
|
| 5. |
|
|
| 6. |
- Brette, Romain, et al.
(författare)
-
Simulation of networks of spiking neurons : A review of tools and strategies
- 2007
-
Ingår i: Journal of Computational Neuroscience. - : Springer Science and Business Media LLC. - 0929-5313 .- 1573-6873. ; 23:3, s. 349-398
-
Forskningsöversikt (refereegranskat)abstract
- We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, including Hodgkin-Huxley type, integrate-and-fire models, interacting with current-based or conductance-based synapses, using clock-driven or event-driven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integration strategy and simulation tool to use for a given modeling problem related to spiking neural networks.
|
|
| 7. |
- Bruederle, Daniel, et al.
(författare)
-
A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems
- 2011
-
Ingår i: Biological Cybernetics. - : Springer Science and Business Media LLC. - 0340-1200 .- 1432-0770. ; 104:4-5, s. 263-296
-
Tidskriftsartikel (refereegranskat)abstract
- In this article, we present a methodological framework that meets novel requirements emerging from upcoming types of accelerated and highly configurable neuromorphic hardware systems. We describe in detail a device with 45 million programmable and dynamic synapses that is currently under development, and we sketch the conceptual challenges that arise from taking this platform into operation. More specifically, we aim at the establishment of this neuromorphic system as a flexible and neuroscientifically valuable modeling tool that can be used by non-hardware experts. We consider various functional aspects to be crucial for this purpose, and we introduce a consistent workflow with detailed descriptions of all involved modules that implement the suggested steps: The integration of the hardware interface into the simulator-independent model description language PyNN; a fully automated translation between the PyNN domain and appropriate hardware configurations; an executable specification of the future neuromorphic system that can be seamlessly integrated into this biology-to-hardware mapping process as a test bench for all software layers and possible hardware design modifications; an evaluation scheme that deploys models from a dedicated benchmark library, compares the results generated by virtual or prototype hardware devices with reference software simulations and analyzes the differences. The integration of these components into one hardware-software workflow provides an ecosystem for ongoing preparative studies that support the hardware design process and represents the basis for the maturity of the model-to-hardware mapping software. The functionality and flexibility of the latter is proven with a variety of experimental results.
|
|
| 8. |
- Djurfeldt, Mikael, et al.
(författare)
-
Efficient generation of connectivity in neuronal networks from simulator-independent descriptions
- 2014
-
Ingår i: Frontiers in Neuroinformatics. - : Frontiers Media SA. - 1662-5196. ; 8, s. 43-
-
Tidskriftsartikel (refereegranskat)abstract
- Simulator-independent descriptions of connectivity in neuronal networks promise greater ease of model sharing, improved reproducibility of simulation results, and reduced programming effort for computational neuroscientists. However, until now, enabling the use of such descriptions in a given simulator in a computationally efficient way has entailed considerable work for simulator developers, which must be repeated for each new connectivity-generating library that is developed. We have developed a generic connection generator interface that provides a standard way to connect a connectivity-generating library to a simulator, such that one library can easily be replaced by another, according to the modeler's needs. We have used the connection generator interface to connect C++ and Python implementations of the previously described connection-set algebra to the NEST simulator. We also demonstrate how the simulator-independent modeling framework PyNN can transparently take advantage of this, passing a connection description through to the simulator layer for rapid processing in C++ where a simulator supports the connection generator interface and falling-back to slower iteration in Python otherwise. A set of benchmarks demonstrates the good performance of the interface.
|
|
