Decoupling of brain function from structure reveals regional behavioral specialization in humans

The brain is an assembly of neuronal populations interconnected by structural pathways. Brain activity is expressed on and constrained by this substrate. Therefore, statistical dependencies between functional signals in directly connected areas can be expected higher. However, the degree to which brain function is bound by the underlying wiring diagram remains a complex question that has been only partially answered. Here, we introduce the structural-decoupling index to quantify the coupling strength between structure and function, and we reveal a macroscale gradient from brain regions more strongly coupled, to regions more strongly decoupled, than expected by realistic surrogate data. This gradient spans behavioral domains from lower-level sensory function to high-level cognitive ones and shows for the first time that the strength of structure-function coupling is spatially varying in line with evidence derived from other modalities, such as functional connectivity, gene expression, microstructural properties and temporal hierarchy

Benchmarking in cluster analysis: A white paper

To achieve scientific progress in terms of building a cumulative body of knowledge, careful attention to benchmarking is of the utmost importance. This means that proposals of new methods of data pre-processing, new data-analytic techniques, and new methods of output post-processing, should be extensively and carefully compared with existing alternatives, and that existing methods should be subjected to neutral comparison studies. To date, benchmarking and recommendations for benchmarking have been frequently seen in the context of supervised learning. Unfortunately, there has been a dearth of guidelines for benchmarking in an unsupervised setting, with the area of clustering as an important subdomain. To address this problem, discussion is given to the theoretical conceptual underpinnings of benchmarking in the field of cluster analysis by means of simulated as well as empirical data. Subsequently, the practicalities of how to address benchmarking questions in clustering are dealt with, and foundational recommendations are made

Are galaxy distributions scale invariant? A perspective from dynamical systems theory

Unless there is evidence for fractal scaling with a single exponent over distances .1 <= r <= 100 h^-1 Mpc then the widely accepted notion of scale invariance of the correlation integral for .1 <= r <= 10 h^-1 Mpc must be questioned. The attempt to extract a scaling exponent \nu from the correlation integral n(r) by plotting log(n(r)) vs. log(r) is unreliable unless the underlying point set is approximately monofractal. The extraction of a spectrum of generalized dimensions \nu_q from a plot of the correlation integral generating function G_n(q) by a similar procedure is probably an indication that G_n(q) does not scale at all. We explain these assertions after defining the term multifractal, mutually--inconsistent definitions having been confused together in the cosmology literature. Part of this confusion is traced to a misleading speculation made earlier in the dynamical systems theory literature, while other errors follow from confusing together entirely different definitions of ``multifractal'' from two different schools of thought. Most important are serious errors in data analysis that follow from taking for granted a largest term approximation that is inevitably advertised in the literature on both fractals and dynamical systems theory.Comment: 39 pages, Latex with 17 eps-files, using epsf.sty and a4wide.sty (included) <[email protected]

Fluctuations in instantaneous frequency predict alpha amplitude during visual perception.

Rhythmic neural activity in the alpha band (8-13 Hz) is thought to have an important role in the selective processing of visual information. Typically, modulations in alpha amplitude and instantaneous frequency are thought to reflect independent mechanisms impacting dissociable aspects of visual information processing. However, in complex systems with interacting oscillators such as the brain, amplitude and frequency are mathematically dependent. Here, we record electroencephalography in human subjects and show that both alpha amplitude and instantaneous frequency predict behavioral performance in the same visual discrimination task. Consistent with a model of coupled oscillators, we show that fluctuations in instantaneous frequency predict alpha amplitude on a single trial basis, empirically demonstrating that these metrics are not independent. This interdependence suggests that changes in amplitude and instantaneous frequency reflect a common change in the excitatory and inhibitory neural activity that regulates alpha oscillations and visual information processing

Reforming the Administrative Procedure Act: Democracy Index Rulemaking

This Essay argues that the current regime of administrative law should be changed by creating legal incentives for agencies to involve the public in the rulemaking process via democracy index rulemaking. Democracy index rulemaking would create a clear incentive for agencies to involve the public by requiring that the more participation that occurred during the rulemaking process, the more deference that such an agency rule would receive in court. An agency could receive this deference by using normal notice and comment procedures and receiving a large number of relevant and non-repetitive comments on a proposed rule, with the precise amount of deference then tied to the number of comments received. Alternatively, the agency could use a special procedure, called deliberative notice and comment, which would involve jury deliberations (involving a set of juries composed of stakeholders as well as of members of the general public) regarding the proposed administrative rule. An agency using this special democratic process would guarantee itself deference. Either way, democracy index rulemaking would create a system that would encourage public participation, with all of its virtues, while at the same time avoiding many of the negatives of other regimes of public participation

The Radio-to-Submm Spectral Index as a Redshift Indicator

We present models of the 1.4 GHz to 350 GHz spectral index, alpha(350/1.4), for starburst galaxies as a function of redshift. The models include a semi-analytic formulation, based on the well quantified radio-to-far infrared correlation for low redshift star forming galaxies, and an empirical formulation, based on the observed spectrum of the starburst galaxies M82 and Arp 220. We compare the models to the observed values of alpha(350/1.4) for starburst galaxies at low and high redshift. We find reasonable agreement between the models and the observations, and in particular, that an observed spectral index of alpha(350/1.4) > +0.5 indicates that the target source is likely to be at high redshift, z > 1. The evolution of alpha(350/1.4) with redshift is mainly due to the very steep rise in the Raleigh-Jeans portion of the thermal dust spectrum shifting into the 350 GHz band with increasing redshift. We also discuss situations where this relationship could be violated. We then apply our models to examine the putative identifications of submm sources in the Hubble Deep Field, and conclude that the submm sources reported by Hughes et al. are likely to be at high redshifts, z > 1.5.Comment: standard LATEX file plus 1 postscript figure. Added references and revised figure. second figure revision. Final Proof version. to appear in Astrophysical Journal Letter