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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This review examines evidence for a neurobiological explanation of executive functions of working memory. We suggest that executive control stems from information about task rules acquired by mixed selective, adaptive coding, multifunction neurons in the prefrontal cortex. Their output dynamically links the cortical-wide networks needed to complete the task. The linking may occur via synchronizing of neural rhythms, which may explain why we have a limited capacity for simultaneous thought.
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Is conscious perception continuous or discrete? Asplund et al use the attentional blink paradigm to demonstrate that conscious perception is discrete and quantal. Attention increases the probability that a representation will reach awareness.
We have argued that cognition is discrete and quantal because the backbone of neural communication used for cognition is oscillatory. For this discussion see:
- Buschman,T.J. and Miller, E.K. (2010) Shifting the Spotlight of Attention: Evidence for Discrete Computations in Cognition. Frontiers in Human Neuroscience. 4(194): 1-9. View PDF »
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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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Cannon et al review the contributions of brain oscillations to neural computations and relate them to a variety of cognitive functions.
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Corbetta and colleagues studied attention by recording from patients undergoing surgery for epilepsy. They found evidence for frequency-based attention mechanisms, in particular phase modulation at lower frequencies. Different types of attentional operations (holding vs shifting attention) were associated with synchrony at different frequencies.
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Everybody agrees that we can only hold a few things in mind simultaneously. However, there is disagreement about why. One theory is that limited cognitive resources are flexible and spread among the items held in mind; the more items, the “thinner” the information about each. Another theory is more of a fixed limit model: Resources are allocated in a discrete fashion and there is a fixed number of items that can be held in mind. Ester et al provide evidence for the latter, fixed, model. Subjects monitored a number of locations and then asked details about one of the locations. The subject’s performance and neural data was best described by a fixed limit model.
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Wolf Singer reviews recent work on cortical dynamics. He concludes that precise temporal coordination between neurons dynamically forms networks and provides a high-dimensional space for neural computations.
For further reading see:
- 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
- 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
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Everybody knows that we can only hold a limited number of things in mind simultaneously. Is this capacity limit due to a limited number of “slots” in working memory or due a limited resource pool that is divided among the items held in mind? We found evidence for both (Buschman et al, 2011). Now, Roggeman et al use computational modeling to provide further evidence for a hybrid model for capacity limits of working memory.
Further reading:
Buschman,T.J., Siegel, M., Roy, J.E. and Miller, E.K. (2011) Neural substrates of cognitive capacity limitations. Proceedings of the National Academy of Sciences. 108(27):11252-5. View PDF »