Soltani A, Noudoost B, Moore T (2013). Dissociable dopaminergic control of saccadic target selection and its implications for reward modulation...

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Soltani A, Noudoost B, Moore T (2013). Dissociable dopaminergic control of saccadic target selection and its implications for reward modulation. Proceedings of the National Academy of Sciences of the USA, 110(9):3579-84.

Abstract

To investigate mechanisms by which reward modulates target selection, we studied the behavioral effects of perturbing dopaminergic activity within the frontal eye field (FEF) of monkeys performing a saccadic choice task and simulated the effects using a plausible cortical network. We found that manipulation of FEF activity either by blocking D1 receptors (D1Rs) or by stimulating D2 receptors (D2Rs) increased the tendency to choose targets in the response field of the affected site. However, the D1R manipulation decreased the tendency to repeat choices on subsequent trials, whereas the D2R manipulation increased that tendency. Moreover, the amount of shift in target selection resulting from the two manipulations correlated in opposite ways with the baseline stochasticity of choice behavior. Our network simulation results suggest that D1Rs influence target selection mainly through their effects on the strength of inputs to the FEF and on recurrent connectivity, whereas D2Rs influence the excitability of FEF output neurons. Altogether, these results reveal dissociable dopaminergic mechanisms influencing target selection and suggest how reward can influence adaptive choice behavior via prefrontal dopamine.

Salazar RF, Dotson NM, Bressler SL, Gray CM (2012). Content specific fronto-parietal synchronization during visual working memory. Science, 338:1097-1100.

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Abstract

Lateral prefrontal and posterior parietal cortical areas exhibit task-dependent activation during working memory tasks in humans and monkeys. Neurons in these regions become synchronized during attention-demanding tasks, but the contribution of these interactions to working memory is largely unknown. Using simultaneous recordings of neural activity from multiple areas in both regions, we find widespread, task-dependent, and content-specific synchronization of activity across the fronto-parietal network during visual working memory. The patterns of synchronization are prevalent among stimulus-selective neurons and are governed by influences arising in parietal cortex. These results indicate that short-term memories are represented by large-scale patterns of synchronized activity across the fronto-parietal network.

Markowitz DA, Wong YT, Gray CM, Pesaran B (2011). Optimizing the decoding of movement goals from local field potentials in macaque cortex. J Neuroscience, 31:18412-18422.

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Abstract

The successful development of motor neuroprosthetic devices hinges on the ability to accurately and reliably decode signals from the brain. Motor neuroprostheses are widely investigated in behaving non-human primates, but technical constraints have limited progress in optimizing performance. In particular, the organization of movement-related neuronal activity across cortical layers remains poorly understood due, in part, to the widespread use of fixed-geometry multielectrode arrays. In this study, we use chronically implanted multielectrode arrays with individually movable electrodes to examine how the encoding of movement goals depends on cortical depth. In a series of recordings spanning several months, we varied the depth of each electrode in the prearcuate gyrus of frontal cortex in two monkeys as they performed memory-guided eye movements. We decode eye movement goals from local field potentials (LFPs) and multiunit spiking activity recorded across a range of depths up to 3 mm from the cortical surface. We show that both LFP and multiunit signals yield the highest decoding performance at superficial sites, within 0.5 mm of the cortical surface, while performance degrades substantially at sites deeper than 1 mm. We also analyze performance by varying bandpass filtering characteristics and simulating changes in microelectrode array channel count and density. The results indicate that the performance of LFP-based neuroprostheses strongly depends on recording configuration and that recording depth is a critical parameter limiting system performance.