Fukushima et al. (2012) are inclined toward the position that the signal arises primarily

from neuronal spiking in the superficial layers of auditory cortex, based on a proximity argument and on a prior study in rodent auditory cortex. This seems to us to be unlikely, given that in the auditory cortices Proteases inhibitor of the awake monkey, the massive weight of both stimulus-evoked and spontaneous firing is in the granular layers compared to the relatively sparse firing seen in the more superficial layers (see e.g., Kajikawa and Schroeder, 2011). Assuming, as the authors do, that high-gamma power is related to multiunit firing, high gamma generated by high-volume firing in the middle layers is likely to overwhelm any generated by the much more sparse firing in supragranular sites. Fukushima et al. (2012) raise a number of logical possibilities regarding underlying causes of structure in ongoing auditory cortical activity, based on a detailed consideration of the relevant anatomical connectivity

patterns between core and higher-order PARP inhibitor cortices and between auditory core and thalamic regions. They also discuss a provocative idea that ongoing activity in auditory cortex represents a playback of recently experienced stimulation. Continuing down this path to longer time scales, it is noteworthy that the dynamical structure of spontaneous activity across the spectrum in auditory cortex bears a remarkable, and likely noncoincidental, resemblance to the 1/f statistics of the natural auditory environment (Garcia-Lazaro et al., 2006). This fits with the idea that the

blueprint for macaque auditory cortex evolved under the pressures of this natural environment and that in ontogeny, individuals’ auditory Florfenicol cortices further tune to the statistics of that same environment (Berkes et al., 2011). It will be interesting to investigate these relationships further and to see how nature and nurture collaborate in this arena. Needless to say, the causes of “spontaneous order” in auditory as well as other cortices are a prime area for future research, as currently there are many more questions than answers. For example, the authors note work by Raichle and colleagues on so-called “resting state” fMRI as evidence that the brain is constantly active, a line of work that has virtually exploded as a means of mapping large-scale brain functional connectivity networks using graph theoretic analyses (Bullmore and Sporns, 2009). To connect the dots, it is interesting to note that this approach is in principle applicable at smaller scales such as those dealt with here, which would in effect represent subsets or nodes in a larger network. This in turn underscores the point (see also below) that it will be important to relate high-gamma to lower-frequency dynamics, extending down to the infraslow ranges that approximate the time frame of hemodynamic oscillations.