Miller Lab alumnus, Andreas Nieder, continues his epic investigations into the neural basis of number sense. Here, Viswanathan and Nieder show that training to make numerosity judgments sharpens neural selectivity in frontal cortex but not in parietal cortex. It seems that the number representations in parietal cortex are innate whereas in the frontal cortex, they are learned.
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Ardid et al use spike shape and firing variability to identify different classes in the primate prefrontal cortex. They ID four classes of broad spiking neurons and three classes of narrow spiking (inhibitory) neurons. These cell classes show different strength of synchrony to local field potential oscillations at specific frequencies. The authors suggest this reflects canonical cortical circuits with different functions.
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Virtually all studies of the neural basis of attention to date average effects across independently recorded neurons and across multiple trials. This is obviously artificial because attention has to be allocated on-the-fly, from moment-to-moment, not averaged across time. Trembly et al show that the current locus of attention can be decoded from ensembles of simultaneously recorded prefrontal cortex neurons from single trials. Decoding of these ensembles was stable over weeks. Nice.
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Task Dependence of Visual and Category Representations in Prefrontal and Inferior Temporal Cortices
Jillian L. McKee, Maximilian Riesenhuber, Earl K. Miller, and David J. FreedmanVisual categorization is an essential perceptual and cognitive process for assigning behavioral significance to incoming stimuli. Categorization depends on sensory processing of stimulus features as well as flexible cognitive processing for classifying stimuli according to the current behavioral context. Neurophysiological studies suggest that the prefrontal cortex (PFC) and the inferior temporal cortex (ITC) are involved in visual shape categorization. However, their precise roles in the perceptual and cognitive aspects of the categorization process are unclear, as the two areas have not been directly compared during changing task contexts. To address this, we examined the impact of task relevance on categorization-related activity in PFC and ITC by recording from both areas as monkeys alternated between a shape categorization and passive viewing tasks. As monkeys viewed the same stimuli in both tasks, the impact of task relevance on encoding in each area could be compared. While both areas showed task-dependent modulations of neuronal activity, the patterns of results differed markedly. PFC, but not ITC, neurons showed a modest increase in firing rates when stimuli were task relevant. PFC also showed significantly stronger category selectivity during the task compared with passive viewing, while task-dependent modulations of category selectivity in ITC were weak and occurred with a long latency. Finally, both areas showed an enhancement of stimulus selectivity during the task compared with passive viewing. Together, this suggests that the ITC and PFC show differing degrees of task-dependent flexibility and are preferentially involved in the perceptual and cognitive aspects of the categorization process, respectively.
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Dotson et al report both 0 and 180 deg phase synchrony between the prefrontal and parietal cortices during a working memory task, suggestion both formation and segregation of different functional networks by neural synchrony.
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Womeldorf et al observed bursts of firing in the anterior cingulate and prefrontal cortex during shifts of attention. These bursts (but not non-burst firing) synchronized over long distances (between the AC and PFC) to local field field potentials at beta and gamma frequencies. These bursts were proceeded by bursts of inhibitory neurons. The authors propose burst firing mechanisms help form functional networks to coordinate shifts of attention.
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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.
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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.
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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 » -
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.