Miller Lab alumnus, Andreas Nieder, shows number tuned neurons in pefrontal and parietal cortices of naive (untrained) subjects.
Viswanathan and Nieder 2013 

Andreas Nieder’s Miller Lab work on the neural substrates for numerosity:

Nieder, A., Freedman, D.J., and Miller, E.K. (2002) Representation of the quantity of visual items in the primate prefrontal cortex.  Science. 297:1708-1711. View PDF »

Nieder, A. and Miller, E.K. (2003) Coding of cognitive magnitude: Compressed scaling of numerical information in the primate prefrontal cortex. Neuron. 37:149-157. View PDF »

Nieder, A. and Miller, E.K. (2004) A parieto-frontal network for visual numerical information in the monkey. Proceedings of the National Academy of Sciences, 101:7457-7462. View PDF »

Nieder, A. and Miller, E.K. (2004) Analog numerical representations in rhesus monkeys: Evidence for parallel processing. Journal of Cognitive Neuroscience. 16:889-901. View PDF »

For years, neurophysiologists have observed that many neurons in higher-level cortex have “weird” properties.  They activate across a wide range of seemingly unrelated conditions and thus don’t  seem to fit into the traditional view of brain function in which each neuron has a single function or message.  They were often considered a “complicating nuisance” at best or dismissed at worst.  It turns out that these mixed selectivity neurons may be the most critical for complex behavior and cognition.   They greatly expand the brain’s computational power.

Read MIT press release: Complex brain function depends on flexibility

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

The human prefrontal cortex may not be special in terms of its size relative to other primates, but it is still a pretty special.
http://blogs.scientificamerican.com/beautiful-minds/2013/05/16/gorillas-agree-human-frontal-cortex-is-nothing-special/?utm_source=feedly

Want to know what it does?  Here’s a start:
Miller, E.K. and Cohen, J.D. (2001) An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24:167-202.  Designated a Current Classic by Thomson Scientific as among the most cited papers in Neuroscience and Behavior. 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.

Van Pelt and Fries show that the peak frequency of gamma-band decreases with stimulus eccentricity and that stationary and moving stimuli are similarly modulated.  These results argue that gamma is related to stimulus salience and are consistent with recent observations of increased gamma vs beta synchrony for bottom-up vs top-down attention in the frontoparietal cortical network (Buschman and Miller (2007).
http://www.sciencedirect.com/science/article/pii/S105381191300387X

For further reading:
Buschman, T.J. and Miller, E.K. (2007) Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science. 315: 1860-1862  The Scientist’s “Hot Paper” for October 2009. View PDF »

In the review, Xiao-Jing Wang deconstructs the cellular and circuit mechanisms involved in sustained “working memory” activity.  Among other things, Wang shows that these circuits do not merely latch onto a sensory input, the same circuits are involved in decision-making computations.
http://wang.medicine.yale.edu/pdf_pub/wang.pfc-book-chapter2012.pdf

Related Miller Lab work cited by Wang:
Miller, E.K. and Cohen, J.D. (2001) An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24:167-202.  Designated a Current Classic by Thomson Scientific as among the most cited papers in Neuroscience and Behavior. View PDF »

Fusi, S., Asaad, W.F., Miller, E.K., and Wang, X.J. (2007) A neural circuit model of flexible sensori-motor mapping: Learning and forgetting on multiple timescales. Neuron. 54: 319-333. View PDF »

Asaad, W.F., Rainer, G. and Miller, E.K. (1998) Neural activity in the primate prefrontal cortex during associative learning.  Neuron, 21:1399-1407. 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 »

Miller, E.K., Erickson, C.A., and Desimone, R. (1996) Neural mechanisms of visual working memory in prefrontal cortex of the macaque. Journal of Neuroscience. 16:5154-5167. View PDF »

In this paper, Miller Lab alumnus Andreas Nieder tested neurons in the prefrontal cortex while animals switched between performing “greater than” vs “less than” rules on either spatial or numerical values.  A majority of the engaged neurons were selective for either the spatial or numerical judgments.  However, a significant proportion of neurons were “generalists” in the sense that they coded both types magnitude judgments.
Eiselt and Nieder (2013) Journal of Neuroscience

This supports a growing body of evidence that many neurons in higher-level cortex  can participate in different functions.  Like LIP neurons that categorize both motion and objects (Fitzgerald et al, Nature Neurosciene, 2011), these neurons were cognitive generalists that can participate in different  magnitude judgments. We have shown that the proportion of specialists vs generalists neurons in the PFC depends on task demands.  If the two category problems are disssimilar (cats vs dog and sport cars vs sedans) and can’t be confused, the majority of PFC neurons were generalists..  If instead, the category problems are similar and can easily be confused (categorizing the same set of animals in two different ways), the modal group of PFC neurons were specialists.  It is as if the PFC was orthogonalizing the two potentially confusable categories to reduce errors.  This shows that the PFC is highly sensitive to top-down demands, more so than bottom-up information, and can adapt the way it represents information to meet current cognitive demands.

For further reading, see:
Cromer, J.A., Roy, J.E., and Miller, E.K. (2010) Representation of multiple, independent categories in the primate prefrontal cortex. Neuron, 66: 796-807. View PDF »
Roy, J.E., Riesenhuber, M., Poggio, T., and Miller, E.K. (2010) Prefrontal cortex activity during flexible categorization. Journal of Neuroscience, 30:8519-8528. View PDF »