Neurons in the prefrontal cortex keeps track of elapsed time (even though time was not explicitly relevant) via sequential firing of neurons. The overlap of sequences depended on the degree of similarity of the item being held in memory. The time-keeping showed a Weber-fraction-like decrease in precision as time passed.
Compressed timeline of recent experience in monkey lPFC
Zoran Tiganj, Jason A Cromer, Jefferson E Roy, Earl K Miller, Marc W Howard
Well said, Howard Eichenbaum. Could agree more. The time is nigh.
Eichenbaum, H. (2017). Barlow versus Hebb: When is it time to abandon the notion of feature detectors and adopt the cell assembly as the unit of cognition?. Neuroscience Letters.
New result on bioRxiv:
Gamma and beta bursts during working memory read-out suggest roles in its volitional control
Mikael Lundqvist, Pawel Herman, Melissa R Warden, Scott L Brincat, Earl K Miller
Working memory (WM) activity is not as stationary or sustained as previously thought. There are brief bursts of gamma (55 to 120 Hz) and beta (20 to 35 Hz) oscillations, the former linked to stimulus information in spiking. We examine these dynamics in relation to read-out from WM, which is still not well understood. Monkeys held a sequence of two objects and had to decide if they matched a subsequent sequence. Changes in the balance of beta/gamma suggested their role in WM control. In anticipation of having to use an object for the match decision, there was an increase in spiking information about that object along with an increase in gamma and a decrease in beta. When an object was no longer needed, beta increased and gamma as well as spiking information about that object decreased. Deviations from these dynamics predicted behavioral errors. Thus, turning up or down beta could regulate gamma and the information in working memory.
A recurrent network model captures the dynamics of frontal and parietal cortex activity during a categorization task. It reveals cortical motifs that underlie computations for categorical decision-making.
Chaisangmongkon, W., Swaminathan, S. K., Freedman, D. J., & Wang, X. J. (2017). Computing by Robust Transience: How the Fronto-Parietal Network Performs Sequential, Category-Based Decisions. Neuron, 93(6), 1504-1517.
Neurons in LIP contribute to two distinct stages of processing during a search task. The working memory for the sought-after feature and then the focusing of attention on target location.
Levichkina, E., Saalmann, Y. B., & Vidyasagar, T. R. (2017). Coding of spatial attention priorities and object features in the macaque lateral intraparietal cortex. Physiological Reports, 5(5), e13136.
A review on issues to consider when studying the brain by perturbing (and measuring) it. Very thoughtful.
Navigating the Neural Space in Search of the Neural Code
Mehrdad Jazayer and Arash Afraz
An excellent and comprehensive review of the brain basis of visual attention. Worthy of yours.
Moore, T., & Zirnsak, M. (2017). Neural Mechanisms of Selective Visual Attention. Annual Review of Psychology, 68, 47-72.
A model of the collaboration and distribution of function between the prefrontal cortex and parietal cortex.
Working memory and decision making in a fronto-parietal circuit model
John D Murray, Jorge H Jaramillo, Xiao-Jing Wang
The anterior cingulate and FEF coordinate through theta and beta phase synchronization between spikes in one and local field potential in the other.
Babapoor-Farrokhran, S., Vinck, M., Womelsdorf, T., & Everling, S. (2017). Theta and beta synchrony coordinate frontal eye fields and anterior cingulate cortex during sensorimotor mapping. Nature Communications, 8, 13967.