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. eLife6, 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 InformationbioRxiv, 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 saccadesProceedings of the National Academy of Sciences114(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 SynchronizationarXiv 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 worldNeuropsychologia.

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 ProblemJournal of Neuroscience37(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.

MEG study in humans shows the functional significance of high alpha-band synchrony for visual attention.

Lobier, M., Palva, J. M., & Palva, S. (2017). High-alpha band synchronization across frontal, parietal and visual cortex mediates behavioral and neuronal effects of visuospatial attention. bioRxiv, 165563.

 

A study of the 100th most-cited papers in Neuroscience identified Miller and Cohen (2001) as the 5th most cited paper (by total citations; 23rd if normalized by publications/year).

Yeung, A. W. K., Goto, T. K., & Leung, W. K. (2017). At the Leading Front of Neuroscience: A Bibliometric Study of the 100 Most-cited Articles. Frontiers in Human Neuroscience, 11, 363.

Miller, E.K. and Cohen, J.D. (2001) An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24:167-202.  Designated a Current Classic by Thomson Scientific as among the most cited papers in Neuroscience and Behavior. View PDF »

Neupane et al show that alpha oscillations in area V4 link sites that encode the location of a stimulus before and after an eye movement.  The alpha oscillations can help create a stable representation of the visual world during eye movements.

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, 201701672.

A model showing how neural coherence can flexibly route information.  If you have a better idea of what underlies cognitive flexibility, I’d like to hear it.

Flexible information routing by transient synchrony
Agostina Palmigiano, Theo Geisel, Fred Wolf & Demian Battaglia

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
doi: https://doi.org/10.1101/126219

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
doi: https://doi.org/10.1101/122598

Abstract

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 discussion of how bottom-up sensory information elicits high-frequency gamma oscillations.  By contrast, top-down processing, which provides the context that coordinates cortical processing, elicits lower-frequency theta, alpha, beta oscillations.  We have drawn similar conclusions based on our own work.

The cross-frequency mediation mechanism of intracortical information transactions
RD Pascual-Marqui, P Faber, S Ikeda, R Ishii, T Kinoshita, Y Kitaura, K Kochi, P Milz, K Nishida, M Yoshimura

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.

The brain monitors simultaneous sensory input by “time division multiplexing”, a rhythmic juggling of the two streams of information.

Evidence for time division multiplexing of multiple simultaneous items in a sensory coding bottleneck
Valeria C Caruso, Jeffrey T Mohl, Chris Glynn, JungAh Lee, Shawn M Willett, Azeem Zaman, Rolando Estrada, Surya Tokdar, Jennifer M Groh

Still think that single neurons with specific functions rule the brain?  Let us persuade you otherwise.  We argue that cognitive control stems from dynamic, context-dependent population coding.

Stokes, M., Buschman, T.J., and Miller, E.K. (2017) Dynamic coding for flexible cognitive control.  The Wiley Handbook of Cognitive Control, The Wiley Handbook of Cognitive Control, Edited by Tobias Egner, John Wiley & Sons, 2017(Chichester, West Sussex, UK). View PDF