Filter Results
10 results
simulation data from lattice phase-oscillator model part 2... simulation data from lattice phase-oscillator model part 4... simulation data from lattice phase-oscillator model part 5... simulation data from lattice phase-oscillator model part 6... gamma oscillation... Matlab Code of a ring-shaped phase-oscillator model (Fig.6)
Data Types:
  • Software/Code
  • Dataset
  • Text
  • File Set
With shifts in island area, isolation, and cycles of island fusion-fission, the role of Quaternary sea-level oscillations as drivers of diversification is complex and not well understood. Here we conduct parallel comparisons of population and species divergence between two island areas of equivalent size that have been affected differently by sea-level oscillations, with the aim to understand the micro- and macroevolutionary dynamics associated with sea-level change. Using genome-wide datasets for a clade of seven Amphiacusta ground cricket species endemic to the Puerto Rico Bank (PRB), we found consistently deeper interspecific divergences and higher population differentiation across the unfragmented Western PRB, in comparison to the currently fragmented Eastern PRB that has experienced extreme changes in island area and connectivity during the Quaternary. We evaluate alternative hypotheses related to the microevolutionary processes (population splitting, extinction and merging) that regulate the frequency of completed speciation across the PRB. Our results suggest that under certain combinations of archipelago characteristics and taxon traits the repeated changes in island area and connectivity may create an opposite effect to the hypothesized “species pump” action of oscillating sea levels. Our study highlights how a microevolutionary perspective can complement current macroecological work on the Quaternary dynamics of island biodiversity.
Data Types:
  • Software/Code
  • Sequencing Data
  • Dataset
Datasets with results from all simulations of trajectories in 40 different conditions of oscillating optimum for d = 70.... Datasets with results from all simulations of trajectories in 40 different conditions of oscillating optimum for d = 40.... Dataset with the frequency of chaos at each simulation time point for different values of dimensionality (number of traits) d.
Data Types:
  • Other
  • Software/Code
  • Tabular Data
  • Dataset
The code and data file provided to us by Janz et al. (2016) and used for their response. Note, that one will need to adjust the sampling frequencies to reflect accurate proportions of specialists and herbivores.
Data Types:
  • Software/Code
  • Dataset
  • Text
  • File Set
A fundamental question in evolutionary biology is what promotes genetic variation at non-neutral loci, a major precursor to adaptation in changing environments. In particular, balanced polymorphism under realistic evolutionary models of temporally varying environments in finite natural populations remains to be demonstrated. Here, we propose a novel mechanism of balancing selection under temporally varying fitnesses. Using forward-in-time computer simulations and mathematical analysis, we show that cyclic selection that spatially varies in magnitude, such as along an environmental gradient, can lead to elevated levels of non-neutral genetic polymorphism in finite populations. Balanced polymorphism is more likely with an increase in gene flow, magnitude and period of fitness oscillations, and spatial heterogeneity. This polymorphism-promoting effect is robust to small systematic fitness differences between competing alleles or to random environmental perturbation. Furthermore, we demonstrate analytically that protected polymorphism arises as spatially heterogeneous cyclic fitness oscillations generate a type of storage effect that leads to negative frequency-dependent selection. Our findings imply that spatially variable cyclic environments can promote elevated levels of non-neutral genetic variation in natural populations.
Data Types:
  • Other
  • Software/Code
  • Dataset
Place cells of the rodent hippocampus fire action potentials when the animal traverses a particular spatial location in any environment. Therefore for any given trajectory one observes a repeatable sequence of place cell activations. When the animal is quiescent or sleeping, one can observe similar sequences of activation known as replay, which underlie the process of memory consolidation. However, it remains unclear how replay is generated. Here we show how a temporally asymmetric plasticity rule during spatial exploration gives rise to spontaneous replay in a model network by shaping the recurrent connectivity to reflect the topology of the learned environment. Crucially, the rate of this encoding is strongly modulated by ongoing rhythms. Oscillations in the theta range optimize learning by generating repeated pre-post pairings on a time-scale commensurate with the window for plasticity, while lower and higher frequencies generate learning rates which are lower by orders of magnitude.
Data Types:
  • Other
  • Software/Code
  • Dataset
What determines how we move in the world? Motor neuroscience often focusses either on intrinsic rhythmical properties of motor circuits or extrinsic sensorimotor feedback loops. Here we show that the interplay of both intrinsic and extrinsic dynamics is required to explain the intermittency observed in continuous tracking movements. Using spatiotemporal perturbations in humans, we demonstrate that apparently discrete submovements made 2-3 times per second reflect constructive interference between motor errors and continuous feedback corrections that are filtered by intrinsic circuitry in the motor system. Local field potentials in monkey motor cortex revealed characteristic signatures of a Kalman filter, giving rise to both low-frequency cortical cycles during movement, and delta oscillations during sleep. We interpret these results within the framework of optimal feedback control, and suggest that the intrinsic rhythmicity of motor cortical networks reflects an internal model of external dynamics, which is used for state estimation during feedback-guided movement.
Data Types:
  • Other
  • Software/Code
  • Dataset
Circadian clocks give rise to daily oscillations in behavior and physiological functions that often anticipate upcoming environmental changes generated by the Earth rotation. In model organisms a relationship exists between several genes affecting the circadian rhythms and latitude. We investigated the allele distributions at 116 000 single-nucleotide polymorphisms (SNPs) of 25 human clock and clock-related genes from the 1000Genomes Project, and at a reference data set of putatively neutral polymorphisms. The global genetic structure at the clock genes did not differ from that observed at the reference data set. We then tested for evidence of local adaptation searching for FST outliers under both an island and a hierarchical model, and for significant association between allele frequencies and environmental variables by a Bayesian approach. A total of 230 SNPs in 23 genes, or 84 SNPs in 19 genes, depending on the significance thresholds chosen, showed signs of local adaptation, whereas a maximum of 190 SNPs in 23 genes had significant covariance with one or more environmental variables. Only two SNPs from two genes (NPAS2 and AANAT) exhibit both elevated population differentiation and covariance with at least one environmental variable. We then checked whether the SNPs emerging from these analyses fall within a set of candidate SNPs associated with different chronotypes or sleep disorders. Correlation of five such SNPs with environmental variables supports a selective role of latitude or photoperiod, but certainly not a major one.
Data Types:
  • Other
  • Software/Code
  • Geospatial Data
  • Sequencing Data
  • Tabular Data
  • Dataset
The human movement repertoire is characterized by the smooth coordination of several body parts, including arm movements and whole body motion. The neural control of this coordination is quite complex because the various body parts have their own kinematic and dynamic properties. Behavioral inferences about the neural solution to the coordination problem could be obtained by examining the emerging phase relationship and its stability. Here, we studied the phase relationships that characterize the coordination of arm-reaching movements with passively-induced whole-body motion. Participants were laterally translated using a vestibular chair that oscillated at a fixed frequency of 0.83 Hz. They were instructed to reach between two targets that were aligned either parallel or orthogonal to the whole body motion. During the first cycles of body motion, a metronome entrained either an in-phase or an anti-phase relationship between hand and body motion, which was released at later cycles to test phase stability. Results suggest that inertial forces play an important role when coordinating reaches with cyclic whole-body motion. For parallel reaches, we found a stable in-phase and an unstable anti-phase relationship. When the latter was imposed, it readily transitioned or drifted back toward an in-phase relationship at cycles without metronomic entrainment. For orthogonal reaches, we did not find a clear difference in stability between in-phase and anti-phase relationships. Computer simulations further show that cost models that minimize energy expenditure (i.e. net torques) or endpoint variance of the reach cannot fully explain the observed coordination patterns. We discuss how predictive control and impedance control processes could be considered important mechanisms underlying the rhythmic coordination of arm reaches and body motion.
Data Types:
  • Software/Code
  • Dataset
  • Text
Time-Frequency data of the ASD group, related to Figure 2... Time-Frequency data of the control group, related to Figure 2
Data Types:
  • Software/Code
  • Tabular Data
  • Dataset