On the role of cortex-basal ganglia interactions for category learning: A neuro-computational approach
Francesc Villagrasa, Javier Baladron, Julien Vitay, Henning Schroll, Evan G. Antzoulatos, Earl K. Miller and Fred H. Hamker
Journal of Neuroscience 18 September 2018, 0874-18; DOI: https://doi.org/10.1523/JNEUROSCI.0874-18.2018

Abstract
In addition to the prefrontal cortex (PFC), the basal ganglia (BG) have been increasingly often reported to play a fundamental role in category learning, but the systems-level circuits of how both interact remain to be explored. We developed a novel neuro-computational model of category learning that particularly addresses the BG-PFC interplay. We propose that the BG bias PFC activity by removing the inhibition of cortico-thalamo-cortical loop and thereby provide a teaching signal to guide the acquisition of category representations in the cortico-cortical associations to the PFC. Our model replicates key behavioral and physiological data of macaque monkey learning a prototype distortion task from Antzoulatos and Miller (2011). Our simulations allowed us to gain a deeper insight into the observed drop of category selectivity in striatal neurons seen in the experimental data and in the model. The simulation results and a new analysis of the experimental data, based on the model’s predictions, show that the drop in category selectivity of the striatum emerges as the variability of responses in the striatum rises when confronting the BG with an increasingly larger number of stimuli to be classified. The neuro-computational model therefore provides new testable insights of systems-level brain circuits involved in category learning which may also be generalized to better understand other cortico-basal ganglia-cortical loops

Nice study showing that anterior parts of the prefrontal cortex and more plastic than posterior parts.

Anterior-posterior gradient of plasticity in primate prefrontal cortex
Mitchell R. Riley, Xue-Lian Qi, Xin Zhou & Christos Constantinidis
Nature Communications volume 9, Article number: 3790 (2018)

Zanos et al show that beta oscillations play a role in short-term synaptic plasticity in primate neocortex that may explain the role of oscillations in attention, learning, and cortical reorganization.

Zanos, S., Rembado, I., Chen, D., & Fetz, E. E. (2018). Phase-locked stimulation during cortical beta oscillations produces bidirectional synaptic plasticity in awake monkeys. Current Biology.

See discussion of this paper by Womelsdorf and Hoffman:
Latent Connectivity: Neuronal Oscillations Can Be Leveraged for Transient Plasticity

Bouchacourt and Buschman describe a two-layer model of working memory. A sensory layer feeds into an unstructured layer of neurons with random connections (i.e., “mixed-selectivity” type neurons).  It is flexible but interference between representations results in a capacity limit.  Sounds like working memory to me.

Bouchacourt, F., & Buschman, T. J. (2018). A Flexible Model of Working Memory. bioRxiv, 407700.

More about mixed-selectivity:
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 »

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 »

Congrats to Miller Lab postdoc Andre Bastos for being awarded a prestigious K99 Award from the National Institutes of Health.

 

04 Sep 2018
September 4, 2018

Phase-coding memories in mind

Neuroscience

Nice summary of phase coding models of working memory by Hakim and Vogel, including a recent paper by Bahramisharif et al.

Hakim, N., & Vogel, E. K. (2018). Phase-coding memories in mindPLoS biology16(8), e3000012.

Bahramisharif, A., Jensen, O., Jacobs, J., & Lisman, J. (2018). Serial representation of items during working memory maintenance at letter-selective cortical sitesPLoS biology16(8), e2003805.

Wasmuht, D. F., Spaak, E., Buschman, T. J., Miller, E. K., & Stokes, M. G. (2018). Intrinsic neuronal dynamics predict distinct functional roles during working memory. Nature Communications.

Abstract:
Working memory (WM) is characterized by the ability to maintain stable representations over time; however, neural activity associated with WM maintenance can be highly dynamic. We explore whether complex population coding dynamics during WM relate to the intrinsic temporal properties of single neurons in lateral prefrontal cortex (lPFC), the frontal eye fields (FEF), and lateral intraparietal cortex (LIP) of two monkeys (Macaca mulatta). We find that cells with short timescales carry memory information relatively early during memory encoding in lPFC; whereas long-timescale cells play a greater role later during processing, dominating coding in the delay period. We also observe a link between functional connectivity at rest and the intrinsic timescale in FEF and LIP. Our results indicate that individual differences in the temporal processing capacity predict complex neuronal dynamics during WM, ranging from rapid dynamic encoding of stimuli to slower, but stable, maintenance of mnemonic information.

28 Aug 2018
August 28, 2018

Attention is rhythmic!

Neuroscience

Two new, exciting papers in Neuron that “put the last nail(s) in the coffin of sustained attention.”  They present compelling evidence that sustained attention is not sustained at all but fluctuates with theta rhythms and alpha/beta rhythms. This provides yet more evidence that the brain works by rhythmic switching between representations.

Ian C. Fiebelkorn, Mark A. Pinsk, Sabine Kastner

A Dynamic Interplay within the Frontoparietal Network Underlies Rhythmic Spatial Attention
Neuron, Volume 99, Issue 4, 22 August 2018, Pages 842-853.e8

Randolph F. Helfrich, Ian C. Fiebelkorn, Sara M. Szczepanski, Jack J. Lin, Josef Parvizi, Robert T. Knight, Sabine Kastner

Neural Mechanisms of Sustained Attention Are Rhythmic
Neuron, Volume 99, Issue 4, 22 August 2018, Pages 854-865.e5

An excellent Preview by Rufin VanRullen: Attention Cycles

For further reading:
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 »

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 »

Beta rhythms play a role in synaptic plasticity.

Zanos, S., Rembado, I., Chen, D., & Fetz, E. E. (2018). Phase-Locked Stimulation during Cortical Beta Oscillations Produces Bidirectional Synaptic Plasticity in Awake MonkeysCurrent Biology.

Super-cool paper by Andreas Nieder and crew.  Frontal-parietal beta synchrony encodes the most recent numerical input.  Theta synchrony distinguishes between different numerosities held in working memory.  The spiking of mixed-selectivity neurons multiplexed both task-relevant and irrelevant stimuli but they were separated in different phases of theta oscillations.  Powerful support that neural oscillations functionally organize spiking activty.

Jacob, S. N., Hähnke, D., & Nieder, A. (2018). Structuring of Abstract Working Memory Content by Fronto-parietal Synchrony in Primate CortexNeuron99(3), 588-597.