Nice result from Buschman Lab. Error-correcting dynamics introduce bias into working memory while reducing noise.
Error-correcting dynamics in visual working memory
Matthew F Panichello, Brian DePasquale, Jonathan W Pillow, Timothy Buschman
doi: https://doi.org/10.1101/319103
Press release for our new paper:
A heavy working memory load may sink brainwave ‘synch’
The paper:
Pinotsis, D.A., Buschman, T.J. and Miller, E.K. (2018) Working Memory Load Modulates Neuronal Coupling. Cerebral Cortex. https://doi.org/10.1093/cercor/bhy065 View PDF
Pinotsis, D.A., Buschman, T.J. and Miller, E.K. (2018) Working Memory Load Modulates Neuronal Coupling. Cerebral Cortex, 2018 https://doi.org/10.1093/cercor/bhy065
Abstract: There is a severe limitation in the number of items that can be held in working memory. However, the neurophysiological limits remain unknown. We asked whether the capacity limit might be explained by differences in neuronal coupling. We developed a theoretical model based on Predictive Coding and used it to analyze Cross Spectral Density data from the prefrontal cortex (PFC), frontal eye fields (FEF), and lateral intraparietal area (LIP). Monkeys performed a change detection task. The number of objects that had to be remembered (memory load) was varied (1–3 objects in the same visual hemifield). Changes in memory load changed the connectivity in the PFC–FEF–LIP network. Feedback (top-down) coupling broke down when the number of objects exceeded cognitive capacity. Thus, impaired behavioral performance coincided with a break-down of Prediction signals. This provides new insights into the neuronal underpinnings of cognitive capacity and how coupling in a distributed working memory network is affected by memory load.
Freedman and Ibos give us a new general framework to think about the functions of the parietal cortex.
Freedman, D. J., & Ibos, G. (2018). An Integrative Framework for Sensory, Motor, and Cognitive Functions of the Posterior Parietal Cortex. Neuron, 97(6), 1219-1234.
Miller Lab alumnus Jonas Rose compares cognitive capacity across species. Note that cognitive capacity correlates with intelligence but it is not the same thing.
Balakhonov, D., & Rose, J. (2017). Crows Rival Monkeys in Cognitive Capacity. Scientific reports, 7(1), 8809.
The effects of attention in the brain can be partitioned into changes in sensitivity of in the subject’s criterion. In visual cortex, only changes in sensitivity are seen. Here, Luo and Maunsell show that neurons in frontal cortex are sensitive to changes in sensitivity as well as criterion.
Luo, T. Z., & Maunsell, J. H. (2018). Attentional Changes in Either Criterion or Sensitivity Are Associated with Robust Modulations in Lateral Prefrontal Cortex. Neuron.
An article in Science News about new ideas on the role of brain waves. It also discuss three new papers from the Miller Lab.
Brain waves may focus attention and keep information flowing Science New March 13, 2018
Here are the papers that are discussed:
Lundqvist, M., Herman, P. Warden, M.R., Brincat, S.L., and Miller, E.K. (2018) Gamma and beta bursts during working memory read-out suggest roles in its volitional control. Nature Communications. 9, 394 View PDF
Wutz, A., Loonis, R., Roy, J.E., Donoghue, J.A., and Miller, E.K. (2018) Different levels of category abstraction by different dynamics in different prefrontal areas. Neuron 97: 1-11. View PDF
Bastos, A.M., Loonis, R., Kornblith, S., Lundqvist, M., and Miller, E.K. (2018) Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory. Proceedings of the National Academy of Sciences. View PDF
Alexander and Brown show how frontal lobe function can be explained by a hierarchical stack of a computational motif based on predictive coding.
Alexander, W. H., & Brown, J. W. (2018). Frontal cortex function as derived from hierarchical predictive coding. Scientific reports, 8(1), 3843.
Dopamine alters the neural oscillations associated with executive functions but leave sensory-related evoked potential unchanged.
Ott, T., Westendorff, S., & Nieder, A. (2018). Dopamine Receptors Influence Internally Generated Oscillations during Rule Processing in Primate Prefrontal Cortex. Journal of cognitive neuroscience, (Early Access), 1-15.
A very nice review of how neuromodulation affects the mechanisms and circuits underlying attention.
Thiele, A., & Bellgrove, M. A. (2018). Neuromodulation of Attention. Neuron, 97(4), 769-785.
Martínez-Vázquez and Gail show different channels of influence in different frequency bands between frontal and parietal cortex.
Martínez-Vázquez, P., & Gail, A. (2018). Directed Interaction Between Monkey Premotor and Posterior Parietal Cortex During Motor-Goal Retrieval from Working Memory. Cerebral Cortex.
Interesting new study from the Moore Lab showing how spatial information is evident in different frequency bands in the prefrontal cortex. They also show a dissociation between high gamma/spiking and alpha.
Chen, X., Zirnsak, M., & Moore, T. (2018). Dissonant Representations of Visual Space in Prefrontal Cortex during Eye Movements. Cell Reports, 22(8), 2039-2052.
Interesting new work from Ito and Cole showing how network connectivity patterns is associated with representational flexibility.
Ito, T., & Cole, M. W. (2018). Network dimensionality underlies flexible representation of cognitive information. bioRxiv, 262626.
Interesting study showing that there are decreases in the frequency of alpha oscillations when a task requires require integration of two inputs that are separated in time. The slowing fosters integration by making it more likely that two stimuli fall within one alpha cycle and are thus integrated. Cool.
Wutz, A., Melcher, D., & Samaha, J. (2018). Frequency modulation of neural oscillations according to visual task demands. Proceedings of the National Academy of Sciences, 201713318.
Lundqvist, M., Herman, P. Warden, M.R., Brincat, S.L., and Miller, E.K. (2018) Gamma and beta bursts during working memory read-out suggest roles in its volitional control. Nature Communications. 9, Article number: 394 doi:10.1038/s41467-017-02791-8
Abstract:
Working memory (WM) activity is not as stationary or sustained as previously thought. There are brief bursts of gamma (~50–120 Hz) and beta (~20–35 Hz) oscillations, the former linked to stimulus information in spiking. We examined these dynamics in relation to readout and control mechanisms of WM. Monkeys held sequences of two objects in WM to match to subsequent sequences. Changes in beta and gamma bursting suggested their distinct roles. In anticipation of having to use an object for the match decision, there was an increase in gamma and spiking information about that object and reduced beta bursting. This readout signal was only seen before relevant test objects, and was related to premotor activity. When the objects were no longer needed, beta increased and gamma decreased together with object spiking information. Deviations from these dynamics predicted behavioral errors. Thus, beta could regulate gamma and the information in WM.
Wutz, A., Loonis, R., Roy, J.E., Donoghue, J.A., and Miller, E.K. (2018) Different levels of category abstraction by different dynamics in different prefrontal areas. Neuron published online Jan 25 2018.
SUMMARY
Categories can be grouped by shared sensory attributes (i.e. cats) or by a more abstract rule (i.e. animals). We explored the neural basis of abstraction by recording from multi-electrode arrays in prefrontal cortex (PFC) while monkeys performed a dot-pattern categorization task. Category abstraction was varied by the degree of exemplar distortion from the prototype pattern. Different dynamics in different PFC regions processed different levels of category abstraction. Bottom-up dynamics (stimulus-locked gamma power and spiking) in ventral PFC processed more low-level abstractions whereas top-down dynamics (beta power and beta spike-LFP coherence) in dorsal PFC processed more high-level abstractions. Our results suggest a two-stage, rhythm-based model for abstracting categories.
A new addition to the proposed circuitry for top-down control.
White, M. G., Panicker, M., Mu, C., Carter, A. M., Roberts, B. M., Dharmasri, P. A., & Mathur, B. N. (2018). Anterior Cingulate Cortex Input to the Claustrum Is Required for Top-Down Action Control. Cell reports, 22(1), 84-95.
The authors find that dopamine increased power of beta-low gamma oscillations in cortex. During visual stimulation, dopamine increased information encoding over a wide range of frequencies but most prominently in the feedforward supragranular layers and in the gamma band (50-100 Hz).
Zaldivar, D., Goense, J., Lowe, S. C., Logothetis, N. K., & Panzeri, S. (2018). Dopamine Is Signaled by Mid-frequency Oscillations and Boosts Output Layers Visual Information in Visual Cortex. Current Biology.
This must be correct. It is very remarkably consistent with our recent study 🙂
Bastos, A.M., Loonis, R., Kornblith, S., Lundqvist, M., and Miller, E.K. (2018) Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory. Proceedings of the National Academy of Sciences. doi:10.1073/pnas.1710323115 View PDF
as well as with our previous work showing that gamma is associated with bottom-up processing:
Buschman, T.J. and Miller, E.K. (2007) Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science. 315: 1860-1862 View PDF »
High frequency waves (Davis on trumpet) carry sensory inputs from the back of the brain to the front. Low frequency waves (Mingus on bass) carry executive (top-down) information from the front to the back of the brain. The low frequencies control the expression of high frequencies. That’s how you choose what sensory inputs to hold in mind (working memory). (Image: Andre Bastos)
It makes sense because we all know that the bass should guide the lead instruments. Am I right?
Bastos, A.M., Loonis, R., Kornblith, S., Lundqvist, M., and Miller, E.K. (2018) Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory. Proceedings of the National Academy of Sciences. published ahead of print January 16, 2018, doi:10.1073/pnas.1710323115
Read MIT press release here.
Persistent activity (indexed by broadband gamma) across human cortex encodes stimulus features and predicts motor output.
Haller, Matar, John Case, Nathan E. Crone, Edward F. Chang, David King-Stephens, Kenneth D. Laxer, Peter B. Weber, Josef Parvizi, Robert T. Knight, and Avgusta Y. Shestyuk. “Persistent neuronal activity in human prefrontal cortex links perception and action.” Nature Human Behaviour (2017): 1.
But how persistent is it?
Lundqvist, M., Rose, J., Herman, P, Brincat, S.L, Buschman, T.J., and Miller, E.K. (2016) Gamma and beta bursts underlie working memory. Neuron, published online March 17, 2016. View PDF »
Coarse visuospatial categories are represented in the posterior parietal cortex whereas fine-scale discrimination are in primary visual cortex with the latter depending on feedback from the former.
Li, Y., Hu, X., Yu, Y., Zhao, K., Saalmann, Y. B., & Wang, L. (2017). Feedback from human posterior parietal cortex enables visuospatial category representations as early as primary visual cortex. Brain and Behavior.
The authors report different effects of stimulation of the lateral prefrontal cortex. Stimulation at or near the FEF prolonged or decreased saccade reaction time, depending on task instructions. More rostral stimulation affected the attention weighting of saccade targets.
Schwedhelm, P., Baldauf, D., & Treue, S. (2017). Electrical stimulation of macaque lateral prefrontal cortex modulates oculomotor behavior indicative of a disruption of top-down attention. Scientific reports, 7(1), 17715.
Gamma and beta bursts during working memory readout suggest roles in its volitional control
Lundqvist et al Nature Communications, in press.
Laminar recordings in frontal cortex suggest distinct layers for maintenance and control of working memory
Bastos et al PNAS, in press
Different levels of category abstraction by different dynamics in different prefrontal areas
Wutz et al Neuron, in press
Stay tuned for what they are about and what they mean. They add up to a new model of working memory.
The authors suggest a hybrid model of working memory. The current focus of attention is encoded by spiking activity. Other items held in the working memory that are not the current focus of attention are held by temporary changes in synaptic weights per the activity-silent models of Lundqvist and Stokes.
Manohar, S. G., Zokaei, N., Fallon, S. J., Vogels, T., & Husain, M. (2017). A neural model of working memory. bioRxiv, 233007.
For more on activity-silent models, see:
Lunqvist, M., Rose, J., Herman, P, Brincat, S.L, Buschman, T.J., and Miller, E.K. (2016) Gamma and beta bursts underlie working memory. Neuron, published online March 17, 2016. View PDF »
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, (Chichester, West Sussex, UK). View PDF
Wasmuht, D. F., Spaak, E., Buschman, T. J., Miller, E. K., & Stokes, M. G. (2017). Intrinsic neuronal dynamics predict distinct functional roles during working memory. bioRxiv, 233171.
Stokes, M. G. (2015). ‘Activity-silent’working memory in prefrontal cortex: a dynamic coding framework. Trends in Cognitive Sciences, 19(7), 394-405.