Woolgar et al show preferential engagement of human frontoparietal networks with an increase in the complexity of task rules.  Plus, the frontoparietal cortex adjusts representations to make rules that are more behavioral confusable easier to discriminate.

More evidence for domain-general processing in higher-level cortex.  Federenko et al tested human subjects with seven tasks with different cognitive demands.  FMRI revealed overlapping activation zones in the frontal and parietal cortex.  This is consistent with neurophysiological studies showing that many neurons in these areas are multifunctional.  Rigotti et al recently demonstrated that these multifunctional “mixed selectivity” neurons provide the computational power needed for high-level cognition.

For further reading:

Rigotti, M., Barak, O., Warden, M.R., Wang, X., Daw, N.D., Miller, E.K., & Fusi, S. “The importance of mixed selectivity in complex cognitive tasks”. Nature, 497, 585-590, 2013 doi:10.1038/nature12160. View PDF

Miller, E.K. and Fusi, S. (2013) Limber neurons for a nimble mind. Neuron. 78:211-213. View PDF

Rhythmic synchrony between neurons has been suggested as a mechanism for establishing communication channels between neurons.  However, this hypothesis has been criticized because of observations that the exact frequency of gamma oscillations bounces around too much to provide a stable communication channel.  (BTW, it doesn’t seem to bother anyone that single neuron activity also bounces around).

In this study, Roberts et al record from V1 and V2 simultaneously while presenting gratings of varying contrast.  Even though the gamma frequencies changed with stimulus contrast and fluctuated over time, coherence remained stable between V1 and V2.   Thus, rhythmic synchrony can provide a stable channel for neural communication.
http://www.cell.com/neuron/abstract/S0896-6273(13)00227-4?utm_source=feedly

For further reading on the role of rhythmic synchrony in neural communication see:
Miller, E.K. and Buschman, T.J. (2013) Cortical circuits for the control of attention.  Current Opinion in Neurobiology.  23:216–222  View PDF »

Buschman, T.J., Denovellis, E.L., Diogo, C., Bullock, D. and Miller, E.K. (2012) Synchronous oscillatory neural ensembles for rules in the prefrontal cortex. Neuron, 76: 838-846.  View PDF

Two different features of a vibrotactile stimulus are encoded by rate and temporal codes in primary sensory cortex.  The amplitude was reflected in the overall firing rate of neurons whereas the frequency was reflected in the oscillatory phase-locking of spikes.
Harvey et al, 2013 PLOS Biology

The two coding schemes, rate vs temporal codes, are often debated as if they are in opposition and mutually exclusive.  They are not and this paper elegantly demonstrates this important point.  And this is not just limited to vibratory tactile stimuli.  Schroeder and colleagues have argued that all sensory processing involves periodic sampling and rhythmic entrainment of cortical neurons.  (We, for example, periodically sample vision via periodic eye movements and shifts of attention.)

Plus, rhythmic synchrony allows multiplexing, not only by adding another coding dimension as shown here, but also by allowing neurons to communicate different messages to different targets depending on whom they are synchronized with (and how, e.g., phase, frequency).  That way, the same neurons can participate in different functions yet still convey unambiguous messages.  For a brief discussion of this latter point and why we need multiplexing in the cortex see: Miller, E.K. and Fusi, S. (2013) Limber neurons for a nimble mind. Neuron. 78:211-213. View PDF

This paper reports FMRI in humans performing a task requiring first-order rules (S-R associations with a specific motor output) and second order rules that govern the use of the first-order rules.  Cerebellum lobules that project to the prefrontal cortex show activation for both types of rules.  This suggests that the cerebellum contributes to rule-based behaviors even when the rules are higher-order and don’t directly involve a motor command.
http://cercor.oxfordjournals.org/content/23/6/1433.abstract

For further reading on the role of rules in cognition and their neural implementation see:
Miller, E.K. and Cohen, J.D. (2001) An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24:167-202.  View PDF »

Buschman, T.J., Denovellis, E.L., Diogo, C., Bullock, D. and Miller, E.K. (2012) Synchronous oscillatory neural ensembles for rules in the prefrontal cortex. Neuron, 76: 838-846.  View PDF

Wallis, J.D., Anderson, K.C., and Miller, E.K. (2001) Single neurons in the prefrontal cortex encode abstract rules. Nature, 411:953-956. View PDF »

A nice article in the Wall Street Journal describing Jack Gallant’s recent FMRI work.  They didn’t just  subtract conditions and come up with a typical imaging map with one or a few isolated bits of activation.  Jack L. Gallant, Tolga Çukur and colleagues used sophisticated  analyses to find the relationship between the patterns of whole brain activity and the content of videos watched by the subjects.  This revealed wide networks, not isolated patches, of neurons engaged by attention to different things in the video (humans vs vehicles, etc).

It also showed how dynamic and flexible the brain is.  When subjects looked for humans, large portions of the cortex were sensitive to humans and less sensitive to vehicles. When subjects looked for vehicles, large portions of the cortex became vehicle detectors.  Many of the same brain areas were involved in multiple networks, changing when people changed the focus of their attention.  Thus, rather than the cortex being composed of modules with strict specializations, high-level information is spread across wide-ranging cortical networks of neurons that participate in many different functions, adapting their properties to current cognitive demands.

We have long argued that mixed selectivity, adaptive coding neurons are crucial for hallmarks of cognition like flexibility.  And in forthcoming paper (Rigotti et al), we show computationally that you can’t build a complex brain w/o them.

For a brief discussion of this issue, read this Preview of a paper by Stokes et al:
Miller, E.K. and Fusi, S. (2013) Limber neurons for a nimble mind. Neuron. 78:211-213. View PDF

And stay tuned for this paper:
Rigotti, M., Barak, O., Warden, M.R., Wang, X., Daw, N.D., Miller, E.K., & Fusi, S. (in press) The importance of mixed selectivity in complex cognitive tasks. Nature.