This article develops and tests an evolutionary model of the growth, decline, and demographic dynamics of voluntary organizations. The model demonstrates a strong analogy between the adaptive landscape of Sewall Wright (1931) and the exploitation surfaces generated by a model of member selection and retention for voluntary associations. The article connects the processes of membership recruitment and loss to the social networks connecting individuals. The model generates dynamic hypotheses about the time path of organizations in sociodemographic dimensions. A key idea in this model is that membership selection processes at the individual level produce adaptation in communities of organizations. The article concludes with an empirical example and some discussion of the implications of the model for a variety of research literatures. Predicting the behavior of empirical systems has proven to be an elusive goal for the social sciences. This article outlines a theory that predicts the growth, decline, and demographic changes of social groups. The theory posits a Darwinian mechanism of systematic variation, selection, and retention of members in groups. Social network theory provides a framework for understanding how social evolution (the transitions from hunting and gathering societies through the intervening stages to the contemporary industrial stage) has created the conditions for the Darwinian mechanism of the model. This study takes a brief tour through the macroevolutionary foundations of the theory to set the stage for the microevolutionary test of the model. The predictions tested in the article are in the short term - over a period of less * Work on this article was supported by National Science Foundation grants SES-8120666, SES

Evolution on a Dancing Landscape: Organizations and Networks in Dynamic Blau Space

An extension to classical stochastic estimation techniques is presented, following the formulations of Ewing and Citriniti (1999), whereby spectral based estimation coefficients are derived from the cross spectral relationship between unconditional and conditional events. This is essential where accurate modeling using conditional estimation techniques are considered. The necessity for this approach stems from instances where the conditional estimates are generated from unconditional sources that do not share the same grid subset, or possess different spectral behaviors than the conditional events. In order to filter out incoherent noise from coherent sources, the coherence spectra is employed, and the spectral estimation coefficients are only determined when a threshold value is achieved. A demonstration of the technique is performed using surveys of the dynamic pressure field surrounding a Mach 0.30 and 0.60 axisymmetric jet as the unconditional events, to estimate a combination of turbulent velocity and turbulent pressure signatures as the conditional events. The estimation of the turbulent velocity shows the persistence of compact counter-rotating eddies that grow with quasi-periodic spacing as they convect downstream. These events eventually extend radially past the jet axis where the potential core is known to collapse.

On spectral linear stochastic estimation

The suprachiasmatic nuclei (SCN) of the hypothalamus are necessary for the persistence of free running circadian activity rhythms in house sparrows. Suprachiasmatic lesions abolish circadian locomotor rhythms in constant darkness. The locomotor activity of lesioned sparrows was analyzed with two different power spectral analysis methods and was found to be arrhythmic. There was a weak correlation between the extent of damage to the SCN and the relative amplitude of the power spectral density in the circadian frequency range. In light-dark cycles (LD 12:12), the locomotor behavior of lesioned sparrows was rhythmic and similar to that of intact birds. However, entrainment was disrupted in SCN-lesioned sparrows exposed to a short photoperiod light cycle (LD 1:24). These results demonstrate that the SCN are crucial for the generation of overt circadian rhythmicity in birds. The fact that SCN lesions abolish circadian rhythms in sparrows and several mammalian species suggests that vertebrate circadian organization may be based on differentially weighted interactions among the pineal, the SCN, and perhaps other brain regions.

https://www.jneurosci.org/content/jneuro/2/6/815.full.pdf

Role of the suprachiasmatic nuclei in the circadian system of the house sparrow, Passer domesticus.

Successful behavior depends on effective communication between distant brain regions. Moreover, disturbance of effective communication can cause neurological symptoms like apraxia, dyslexia or object agnosia. Interregional communication can be assessed by coherence analysis of synchronized neuronal oscillations, and has been referred to as synchrony or "binding". The concept of synchrony as a means of information coding is attractive, but its functional relevance has been challenged. We hypothesized that if synchrony is functionally relevant in humans, then more synchrony should determine better behavioral performance. Here, we show in a visuotactile integration task that the amount of low-frequency (7-13Hz), long-range electroencephalographic coherence between visual and sensorimotor cortex is significantly correlated with the level of performance. Trials with highest coherences were the most successful ones and vice versa in the absence of differences in regional activation measured as task-related spectral power. In summary, quantitatively linking the amount of long-range synchrony with the degree of behavioral success in humans, the present data suggest that the ability to generate topographically specific synchrony of high amplitude is functionally relevant for behavioral success. They also raise the possibility that the magnitude of regional activation is less representative of the efficacy of brain functioning than interregional synchrony.

Larger Interregional Synchrony is Associated with Greater Behavioral Success in a Complex Sensory Integration Task in Humans

http://jtoomim.org/files/Jau%9aovec%20and%20Jau%9aovec%20-%202012%20-%20Working%20memory%20training%20Improving%20intelligence.pdf

R. K. Otnes

Papers

Applied Time Series Analysis, Vol. 1