Zhang et al optogenetically activated the mouse cingulate region and found that it enhanced activity in primary visual cortex (V1), improved visual discrimination and increased center-surround effects. This modulation was mediated by long-range projections that activated GABAergic (inhibitory) circuits in V1. Thus, long-range projection from the frontal lobe may modulate sensory cortex via excitatory action on local inhibitory circuits.
-
According to the press release, Kay made a “list of exceptionally talented technologists whose work has great potential to transform the world.” It won’t be through her poker play, I’ll tell you that much.
Congrats Kay! Well deserved. -
Bob Desimone and crew find that removal of the prefrontal cortex (PFC) reduces (but, notably, does not eliminate) the effects of attention on neurons in visual cortical area V4. The modulation of attention on firing rates was weaker and onset was delayed relative to the hemisphere with an intact PFC and there was a reduction of gamma power and synchrony. Thus, PFC is an important, but not the only, source of top-down modulation on visual cortex.
-
Chan et al show that the prefrontal cortex (PFC) may exert top-down influences on the superior colliculus (SC) via oscillatory synchrony. Animals performed both pro- and anti-saccade trials. Anti-saccades are highly dependent on the PFC because they involve inhibiting a highly prepotent response (a pro-saccade). Bilateral deactivation of the PFC attenuated beta and gamma power in the SC around the time the animals were preparing to respond. The gamma power was correlated with spiking activity whereas beta was tonic (and reduced after PFC deactivation) and may facilitate communication between the PFC and SC.
-
The evidence is mounting that the primate brain has separate, independent attentional/working memory capacities in the right and left visual hemifields. In this study, Matushima and Tanaka trained monkeys to track single or multiple objects across both visual hemifields. Neural activity to a given object was only degraded when another object was in the same hemifield, not when another object was in the opposite hemifield. This could not be explained by distance between objects; there was no difference between upper and lower visual fields, for example. This suggests that the anatomical separation of the right and left visual hemifields into the left vs right cerebral hemispheres results in separate cognitive capacities for the right vs left sides of vision. Buschman et al (2011) found similar effects for object identity.
For further reading:
Buschman,T.J., Siegel, M., Roy, J.E. and Miller, E.K. (2011) Neural substrates of cognitive capacity limitations. Proceedings of the National Academy of Sciences. 108(27):11252-5. View PDF » -
We (Antoulatos and Miller) show increased beta-band synchrony between (but not within) the prefrontal cortex and striatum during category learning. By the time the categories were fully learned, the beta synchrony became category-specific. That is, different patterns of prefrontal cortex-striatum recording sites showed increased beta synchrony for one category or the other. Thus, category learning may depend on formation of oscillatory synchrony-aided functional circuits between the prefrontal cortex and striatum. Further, causality analysis suggested that the striatum exerted a greater influence on the prefrontal cortex than the other way around. This supports models positing that the basal ganglia “train” the prefrontal cortex (Pasupathy and Miller, 2005; Seger and Miller, 2010).
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 DOI: http://dx.doi.org/10.1016/j.neuron.2014.05.005 View PDF
For further reading:
Pasupathy, A. and Miller, E.K. (2005) Different time courses for learning-related activity in the prefrontal cortex and striatum. Nature, 433:873-876. View PDF »
Antzoulatos,E.G. and Miller, E.K. (2011) Differences between neural activity in prefrontal cortex and striatum during learning of novel, abstract categories. Neuron. 71(2): 243-249. View PDF »
Seger, C.A. and Miller, E.K. (2010) Category learning in the brain. Annual Review of Neuroscience, Vol. 33: 203-219. View PDF »
-
“Frequency sliding” (temporal fluctuations in peak oscillatory frequency is consider as a neural mechanism. Neuron models are used to show how it can change spiking threshold and coincidence detection, and used to identify networks from EEG activity.
Fluctuations in Oscillation Frequency Control Spike Timing and Coordinate Neural Networks
Michael X Cohen
The Journal of Neuroscience, 2 July 2014, 34(27): 8988-8998; doi: 10.1523/JNEUROSCI.0261-14.2014 -
IFLScience: Brain Waves Synchronize for Faster Learning
Summary:
As our thoughts dart from this to that, our brains absorb and analyze new information at a rapid pace. According to a new study, these quickly changing brain states may be encoded by the synchronization of brain waves across different brain regions. Waves originating from two areas involved in learning couple to form new communication circuits when monkeys learn to categorize different patterns of dots. -
A (very brief) mention of the new paper by Antzoulatos and Miller (2014) on National Public Radio.
The paper:
Antzoulatos, E.G. and Miller, E.K. (in press) “Increases in functional connectivity between the prefrontal cortex and striatum during category learning.” Neuron. View PDF -
Huffington Post article about the evils of multitasking.
You’re Not Busy, You Just Think You Are: 7 Ways To Find More Time The Huffington Post UK | By Georgia James Posted: 13/06/2014 15:00 BST
(with quotes from Earl Miller)