Kramer and Eden offer a new method for assessing cross-frequency coupling between oscillatory neural signals.
-
Mirpour and Bisley recorded neural responses and local field potentials from the lateral intraparietal cortex (LIP) during visual search. Previously fixated non-target stimuli elicited greater lower frequency (alpha and beta) oscillations. This suggested that reduced neural responses (and attention) to previously seen stimuli results from oscillatory-based top-down influences from the frontal cortex.
-
John Duncan and colleagues examined dynamic allocation of attention in the prefrontal cortex. A behaviorally relevant target and non-target were simultaneously presented in both visual hemifields. At first, activity in each hemifield was dominated by the stimulus in the contralateral field but then all activity became dominated by the target alone. The speed and degree of attentional reallocation depend on relative attentional weights; more experience with a target led to faster and greater allocation to the target. Because neurons rapidly shifted their representation from an irrelevant to relevant stimulus in the opposite hemifield, these results are consistent with adaptive coding models of neural representation.
Kadohisa et al (2013) Dynamic Construction of a Coherent Attentional State in a Prefrontal Cell PopulationFurther reading on adaptive coding:
Miller, E.K. and Cohen, J.D. (2001) An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24:167-202. View PDF »Duncan, J. and Miller, E.K. (2013) Adaptive neural coding in frontal and parietal cortex. In: Stuss, D.T. and Knight, R.T. (Eds). Principles of Frontal Lobe Function: Second Edition.
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
-
Bea Luna and colleagues used graph theory to examine the development of functional hubs in the human brain. The hub architecture develops earlier, but connections between the hubs and “spokes” continue to develop and change into adulthood.
-
Jack Gallant and crew used FMRI to examine scene processing in the human brain. They found that scenes activated many regions of anterior visual cortex and that the scene categories capture the co-occurrence of the objects that compose the scenes.
-
Adam Gazzaley and company show, for the first time, that training on a video game results in benefits that transfer to other tests of cognition. Training on the NeuroRacer game produced long-lasting improvements in cognitive abilities of older adults (age 65-80). How did they do it? Their trick was to focus on multitasking and attention.
Anguera et al (2013) Nature -
Matt Chafee and colleagues used multiple-electrode recording in the prefrontal and parietal cortices to examine the temporal dynamics of their neural activity during a categorization task. They decoded category signals from patterns of simultaneously recorded in small bins and asked whether the resulting information time series in one area could predict the other. This showed that “executive” top-down signals flow from the prefrontal to parietal cortex.
-
Max Riesenhuber and colleagues used EEG to examine the time course of shape and category signals in the human brain. Neural adaptation for category changes was seen in frontal cortex and then subsequently in temporal cortex. This supports the hypothesis that shape categories are formed by shape signals from temporal cortex that converge and form explicit category representations in frontal cortex. A late category signal in temporal cortex is consistent with category signals feeding back from frontal to temporal cortex.
-
Ranulfo Romo and crew show delta band (1-4 Hz) synchrony between frontal and parietal cortex that varies with decisions. When there were no decisions to be made, frontal-parietal delta was reduced.
-
An article in MIT’s Technology Review magazine about our work on how multitasking “mixed selectivity” neurons may be key for cognition.
Do-It-All Neurons – A key to cognitive flexibility by Anne Trafton