Bahlmann et al studied the human prefrontal cortex using a task with two different types of stimuli (spatial vs language) and three levels of abstraction. They found a rostro-caudal organization based on level abstraction (more anterior = more abstract).
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The modal model of working memory (WM) is that of sustained activity in the prefrontal cortex. Sreenivasan et al argue for a more complex model. High-fidelity WM representations are maintained in sensory cortex while the prefrontal cortex instead maintains representations of multiple goal-related variables. These PFC representations serve to bias stimulus-specific activity in sensory cortex.
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Roy et al show that the activity of neurons in the prefrontal cortex (pFC) are linked to categorical decisions. Monkeys were trained to categorize a set of computer-generated images as “cats” vs “dogs”. Then, they were shown ambiguous images were centered on a category boundary, that is, they were a mix of 50% of cats and dogs and therefore had no category information. The monkeys guessed at their category membership. Activity to the same ambiguous image differed significantly, depending on the monkey’s decision about the image’s category. Thus, pFC activity reflects categorical decisions.
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Eiselt and Nieder trained monkeys to make greater/less than judgments to line lengths and dot numerosities. They compared neural activity in the prefrontal cortex (PFC), anterior cingulate (AC), and premotor cortex (PMC). The greatest proportion of greater/less than rule neurons were found in the PFC. Further, only the PFC had neurons that were “generalists”; they signaled the greater/less than rules for both judgments. Neurons in other areas were specialized for one judgment or the other.
This is consistent with our work showing that a large proportion of PFC neurons are multifunction, mixed selectivity neurons. They may be key in providing the computational power for complex, flexible behavior. For further reading see:
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, 497, 585-590, doi:10.1038/nature12160. View PDF
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 »
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Ardid and Wang propose a model for task switching in which a weak rule signal provides a small bias that is dramatically amplified by reverberating dynamics in neural circuits. This leads to complete reconfiguration of sensory to motor mapping. It seems to explain many observations in the extant literature. Rules signals are often weak (but ubiquitous in frontal cortex), yet somehow manage to gain control over behavior
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Our work with Stefano Fusi’s Lab makes The Wall Street Journal.
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Blogger John Borghi lists the most highly cited papers in neuroscience and has kind words for Miller and Cohen (2001). Thanks, John!
- 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 »
- Miller, E.K. and Cohen, J.D. (2001) An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24:167-202.
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Behavior can be fast and automatic, but inflexible (model-free) vs slower, more deliberate, and flexible (model-based) Ray Dolan and crew show that disruption of the prefrontal cortex by transcranial magnetic stimulation (TMS) pushes humans towards more inflexible, model-free, behavior.
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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
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Van der Linden et al used computer generated images to study categorization in the human brain. They found that the frontal cortex showed sensitivity to the features diagnostic for the categories, which is consistent with results from animal studies at the neuron level.