Micheli et al find that during sustained attention, successful near-threshold visual detection is predicted by increased phase synchrony between the frontal and temporal/parietal cortex. They suggest that beta coherent states in the prefrontal cortex regulate top-down expectancy and coupling with posterior cortex facilitates the gating of that information.
Evidence for the role of beta in top-down selection continues to mount.
Siegel, M., Buschman, T.J., and Miller, E.K. (2015) Cortical information flow during flexible sensorimotor decisions. Science. 19 June 2015: 1352-1355.
During flexible behavior, multiple brain regions encode sensory inputs, the current task, and choices. It remains unclear how these signals evolve. We simultaneously recorded neuronal activity from six cortical regions (MT, V4, IT, LIP, PFC and FEF) of monkeys reporting the color or motion of stimuli. Following a transient bottom-up sweep, there was a top-down flow of sustained task information from frontoparietal to visual cortex. Sensory information flowed from visual to parietal and prefrontal cortex. Choice signals developed simultaneously in frontoparietal regions and travelled to FEF and sensory cortex. This suggests that flexible sensorimotor choices emerge in a frontoparietal network from the integration of opposite flows of sensory and task information.
Miller Lab alumnus, Andreas Nieder, continues his epic investigations into the neural basis of number sense. Here, Viswanathan and Nieder show that training to make numerosity judgments sharpens neural selectivity in frontal cortex but not in parietal cortex. It seems that the number representations in parietal cortex are innate whereas in the frontal cortex, they are learned.
Miller Lab alumnus David Freedman and colleagues present a model that shows how categorical neural activity can develop through learning. As a result of top-down influences from decision neurons, categorical representations develop in neurons that show choice-correlated activity fluctuations. They test the model via recordings from parietal cortex.
Braunlich et al compared stimulus identity vs categorization tasks using fMRI in humans. They applied a Constrained Principal Components Analysis. They found evidence for two distinct frontoparietal networks. One that rapidly analyzes the stimuli and a second one that more slowly categorizes them.
Dotson et al report both 0 and 180 deg phase synchrony between the prefrontal and parietal cortices during a working memory task, suggestion both formation and segregation of different functional networks by neural synchrony.
Quentin et al examined the relationship between white matter connectivity between the frontal and parietal cortices and the improvement of visual perception by beta oscillatory synchrony between them. They used diffusion imaging to examine the white matter connectivity and used transcranial magnetic stimulation (TMS) over the right frontal eye fields (FEF) to induce beta oscillations. Individuals that showed greater perceptual improvement with the beta TMS also had stronger white matter connectivity.
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
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.