Working memory for different items in a sequence is prioritized by how much attention is paid to the item at encoding.
Jafarpour, A., Penny, W., Barnes, G., Knight, R. T., & Duzel, E. (2017). Working Memory Replay Prioritizes Weakly Attended Events. eNeuro, 4(4), ENEURO-0171.
Context-dependent attractor dynamics can underlie mental flexibility.
Tajima, S., Koida, K., Tajima, C. I., Suzuki, H., Aihara, K., & Komatsu, H. (2017). Task-dependent recurrent dynamics in visual cortex. eLife, 6, e26868.
Marc Howard reviews “time cells” in the brain. Time cells show Weber-fraction like decreases in accuracy the further in the past you go. Interestingly, these cells keep track of time even when tasks do not require it. You can’t escape time.
Howard, M. W. Memory as perception of the past: Compressed time in mind and brain.
Increased theta synchrony between the prefrontal cortex and hippocampus when subjects encoded unexpected study items. This is further evidence that theta-band (6-10 Hz) oscillations orchestrate communication between these brain areas.
Gruber, M. J., Hsieh, L. T., Staresina, B., Elger, C., Fell, J., Axmacher, N., & Ranganath, C. (2017). Theta Phase Synchronization Between The Human Hippocampus And The Prefrontal Cortex Supports Learning Of Unexpected Information. bioRxiv, 144634.
For further reading:
Brincat, S.L. and Miller, E.K. (2015) Frequency-specific hippocampal-prefrontal interactions during associative learning. Nature Neuroscience. Published online 23 Feb 2015 doi:10.1038/nn.3954. View PDF »
Brincat, S.L. and Miller, E.K (2016) Prefrontal networks shift from external to internal modes during learning Journal of Neuroscience. 36(37): 9739-9754, 2016 doi: 10.1523/JNEUROSCI.0274-16.2016. View PDF
Alpha-band oscillations in visual cortex (area 4) link sites that encode the location of a stimulus before and after an eye movement. This shows how brain rhythms can construct a stable representation of a visual scene as our eyes move,
Neupane, S., Guitton, D., & Pack, C. C. (2017). Coherent alpha oscillations link current and future receptive fields during saccades. Proceedings of the National Academy of Sciences, 114(29), E5979-E5985.
Loops between the basal ganglia and the cerebral cortex allow the basal ganglia to control functional connectivity in the cortex by synchronizing its rhythms.
Pouzzner, D. (2017). Control of Functional Connectivity in Cerebral Cortex by Basal Ganglia Mediated Synchronization. arXiv preprint arXiv:1708.00779.
For further reading:
Antzoulatos, E.G. and Miller, E.K. (2014) Increases in functional connectivity between the prefrontal cortex and striatum during category learning. Neuron, 83:216-225. View PDF »
Selected as one of Neuron’s Best of 2014-2015
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. 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 »
Your eyes dart about rhythmically sampling different parts of a scene in little bites. Your memory system papers this over to create a illusion of seamless perception. Let Parr and Friston break it down for you:
Parr, T., & Friston, K. J. (2017). The active construction of the visual world. Neuropsychologia.
For further reading:
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 »
Buschman, T.J. and Miller, E.K. (2009) Serial, covert, shifts of attention during visual search are reflected by the frontal eye fields and correlated with population oscillations. Neuron, 63: 386-396. View PDF
Miller Lab Alumnus, Wael Asaad, shows that neurons in the prefrontal cortex can figure out which prior events get credit for the consequences of our actions.
Asaad, W. F., Lauro, P. M., Perge, J. A., & Eskandar, E. N. (2017). Prefrontal Neurons Encode a Solution to the Credit-Assignment Problem. Journal of Neuroscience, 37(29), 6995-7007.
More evidence for mixed selectivity. Mixed selectivity is “a neural encoding scheme in which different task variables and behavioral choices are combined indiscriminately in a non-linear fashion within the same population of neurons. This scheme generates a high-dimensional non-linear representational code that allows for a simple linear readout of multiple variables from the same network of neurons” (Fusi et al., 2016). It adds computational horsepower to the brain. In this case, the evidence is from human parietal cortex.
Zhang, C. Y., Aflalo, T., Revechkis, B., Rosario, E. R., Ouellette, D., Pouratian, N., & Andersen, R. A. (2017). Partially Mixed Selectivity in Human Posterior Parietal Association Cortex. Neuron.
For further reading:
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 »
Fusi, S., Miller, E.K., and Rigotti, M. (2016) Why neurons mix: High dimensionality for higher cognition. Current Opinion in Neurobiology. 37:66-74 doi:10.1016/j.conb.2016.01.010. View PDF »
A recent review by the late, great Howard Eichenbaum. You’ll be missed, Howard.
Eichenbaum, H. (2017). Memory: organization and control. Annual review of psychology, 68, 19-45.