SUMMARY Polymorphism in an animal communication channel provides a framework for studying proximate rules of signal design as well as ultimate mechanisms of signal diversification. Reproductively isolated mormyrid fishes from Gabon's Brienomyrus species flock emit distinctive electric organ discharges(EODs) thought to function in species and sex recognition. Species boundaries and EODs appear congruent in these fishes, with the notable exception of three morphs designated types I, II and III. Within the species flock, these morphs compose a monophyletic group that has recently been called the magnostipes complex. Co-occurring morphs of this complex express distinctive EODs, yet they appear genetically indistinguishable at several nuclear loci. In this study, we investigated EOD discrimination by these morphs using both behavioral and physiological experiments. During the breeding season, wild-caught type I and type II males showed evidence that they can discriminate their own morph's EOD waveform from that of a sympatric and genetically distinct reference species. However, we found that type I and type II males exhibited an asymmetry in unconditioned responses to paired playback of EODs recorded from type I versus type II females. Males of the type II morph responded preferentially to EODs of type II females,whereas type I males did not appear to discriminate homotypic and heterotypic EODs in our experimental paradigm. Part of this behavioral asymmetry may have resulted from a previously undetected difference in adult size, which may have enhanced apparent discrimination by the smaller morph (type II) due to a relatively higher risk of injury from the larger morph (type I). Knollenorgan receptors, which mediate electrical communication in mormyrids, showed similar spectral tuning in type I and type II. These electroreceptors coded temporal features of any single magnostipes-complex EOD with similar patterns of time-locked spikes in both morphs. By contrast, Knollenorgans exhibited distinctive responses to different EOD waveforms. These results suggest that discrete EOD variation in this rapidly diversifying complex is functional in terms of morph-specific advertisement and recognition. Time-domain signal divergence has outpaced frequency-domain divergence between sympatric morphs,requiring little to no change in receptor response properties. We discuss our findings in light of a model for EOD time-coding by the Knollenorgan pathway,as well as evolutionary hypotheses concerning sympatric signal diversification in the magnostipes complex.
It is crucial for refugee service providers to understand the family planning knowledge, attitudes, and practices of refugee women following third country resettlement. Using an ethnographic approach rooted in Reproductive Justice, we conducted six focus groups that included 66 resettled Somali and Congolese women in a western United States (US) metropolitan area. We analyzed data using modified grounded theory. Three themes emerged within the family planning domain: (a) concepts of family, (b) fertility management, and (c) unintended pregnancy. We contextualized these themes within existing frameworks for refugee cultural transition under the analytic paradigms of “pronatalism and stable versus evolving family structure” and “active versus passive engagement with family planning.” Provision of just and equitable family planning care to resettled refugee women requires understanding cultural relativism, social determinants of health, and how lived experiences influence family planning conceptualization. We suggest a counseling approach and provider practice recommendations based on our study findings.
Estimates of the spontaneous discharge rate (SR) of auditory-nerve (AN) fibers are often based on measurements of the average rate over a long (e.g., 30 s) interval. These measurements are important because SR is apparently correlated with other AN properties, such as threshold to acoustic stimuli, shape of ratelevel function, recovery from prior stimulation, and certain anatomical characteristics. Furthermore, histograms of SR estimates from large numbers of fibers suggest that they can be divided into two (i.e., low and high) or three (i.e., low, medium, and high) SR classes. Yet, even Bsimple^statistical estimates, such as average rate, can behave surprisingly poorly for processes with long-range dependence (LRD), which has been found in the spontaneous activity of AN fibers. In particular, LRD greatly increases the variability of estimates of mean discharge rate. We investigated the implications of this effect of LRD for our understanding of the SRs of AN fibers. The fractional-Gaussian-noise-driven Poisson process (fGnDP) was originally developed to model the LRD action-potential trains of AN fibers. Using rate estimates computed from this model, we were able to reproduce the shape of published histograms of SR using only three fixed SR values. Moreover, by using a Poisson-equivalent integrate-and-fire (IF) model in place of the inhomogeneous Poisson process in the fGnDP model, we were able to reproduce SR histograms using only two fixed SR values. These results suggest that AN fibers may have only two or three possible values for their long-term average spontaneous discharge rates. In other words, all Bhigh-SRn eurons may actually have the same underlying SR. Furthermore, both Blow-SR^and Bmedium-SR^neu-rons may have a single Btrue^SR value, or these two classes may have two different Btrue^SR values. Furthermore, the Poisson-equivalent IF model may prove useful in other applications involving the modeling of trains of action potentials.
Many different types of integrate-and-fire models have been designed in order to explain how it is possible for a cortical neuron to integrate over many independent inputs while still producing highly variable spike trains. Within this context, the variability of spike trains has been almost exclusively measured using the coefficient of variation of interspike intervals. However, another important statistical property that has been found in cortical spike trains and is closely associated with their high firing variability is long-range dependence. We investigate the conditions, if any, under which such models produce output spike trains with both interspike-interval variability and long-range dependence similar to those that have previously been measured from actual cortical neurons. We first show analytically that a large class of high-variability integrate-and-fire models is incapable of producing such outputs based on the fact that their output spike trains are always mathematically equivalent to renewal processes. This class of models subsumes a majority of previously published models, including those that use excitation-inhibition balance, correlated inputs, partial reset, or nonlinear leakage to produce outputs with high variability. Next, we study integrate-and-fire models that have (nonPoissonian) renewal point process inputs instead of the Poisson point process inputs used in the preceding class of models. The confluence of our analytical and simulation results implies that the renewal-input model is capable of producing high variability and long-range dependence comparable to that seen in spike trains recorded from cortical neurons, but only if the interspike intervals of the inputs have infinite variance, a physiologically unrealistic condition. Finally, we suggest a new integrate-and-fire model that does not suffer any of the previously mentioned shortcomings. By analyzing simulation results for this model, we show that it is capable of producing output spike trains with interspike-interval variability and long-range dependence that match empirical data from cortical spike trains. This model is similar to the other models in this study, except that its inputs are fractional-gaussian-noise-driven Poisson processes rather than renewal point processes. In addition to this model's success in producing realistic output spike trains, its inputs have long-range dependence similar to that found in most subcortical neurons in sensory pathways, including the inputs to cortex. Analysis of output spike trains from simulations of this model also shows that a tight balance between the amounts of excitation and inhibition at the inputs to cortical neurons is not necessary for high interspike-interval variability at their outputs. Furthermore, in our analysis of this model, we show that the superposition of many fractional-gaussian-noise-driven Poisson processes does not approximate a Poisson process, which challenges the common assumption that the total effect of a large number of inputs on a neuron is well represen...
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