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PLoS Computational Biology (1)
The Journal of Neuroscience (1)
The Journal of neuroscience : the official journal of the Society for Neuroscience (1)
Markowitz, David A. (3)
Pesaran, Bijan (2)
Wong, Yan T. (2)
Gray, Charles W. (1)
Martin, Robert G. (1)
Rosner, Judah L. (1)
Shewcraft, Ryan A. (1)
Stormo, Gary D. (1)
Wall, Michael E. (1)
Year of Publication
Optimizing the decoding of movement goals from local field potentials in Macaque cortex
Wong, Yan T.
Gray, Charles W.
The Journal of Neuroscience
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 pre-arcuate 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.
planning; oculomotor; frontal; decoding; LFP; brain-machine interface
Competition for visual selection in the oculomotor system
Shewcraft, Ryan A.
Wong, Yan T.
The Journal of neuroscience : the official journal of the Society for Neuroscience
During behavior, the oculomotor system is tasked with selecting objects from an ever-changing visual field and guiding eye movements to these locations. The attentional priority given to visual targets during selection can be strongly influenced by external stimulus properties or internal goals based on previous experience. Although these exogenous and endogenous drivers of selection are known to operate across partially overlapping time scales, the form of their interaction over time remains poorly understood. Using a novel choice task that simultaneously manipulates stimulus- and goal-driven attention, we demonstrate that exogenous and endogenous attentional biases change linearly as a function of time after stimulus onset and have an additive influence on the visual selection process in rhesus macaques (Macaca mulatta). We present a family of computational models that quantify this interaction over time and detail the history-dependence of both processes. The computational models reveal the existence of a critical 140-180 ms attentional “switching” time, when stimulus and goal-driven processes simultaneously favor competing visual targets. These results suggest that the brain uses a linear sum of attentional biases to guide visual selection.
priority map; attention; endogeneous; exogeneous; utility; decision
Model of Transcriptional Activation by MarA in Escherichia coli
Wall, Michael E.
Rosner, Judah L.
Martin, Robert G.
Stormo, Gary D.
PLoS Computational Biology
The AraC family transcription factor MarA activates ∼40 genes (the marA/soxS/rob regulon) of the Escherichia coli chromosome resulting in different levels of resistance to a wide array of antibiotics and to superoxides. Activation of marA/soxS/rob regulon promoters occurs in a well-defined order with respect to the level of MarA; however, the order of activation does not parallel the strength of MarA binding to promoter sequences. To understand this lack of correspondence, we developed a computational model of transcriptional activation in which a transcription factor either increases or decreases RNA polymerase binding, and either accelerates or retards post-binding events associated with transcription initiation. We used the model to analyze data characterizing MarA regulation of promoter activity. The model clearly explains the lack of correspondence between the order of activation and the MarA-DNA affinity and indicates that the order of activation can only be predicted using information about the strength of the full MarA-polymerase-DNA interaction. The analysis further suggests that MarA can activate without increasing polymerase binding and that activation can even involve a decrease in polymerase binding, which is opposite to the textbook model of activation by recruitment. These findings are consistent with published chromatin immunoprecipitation assays of interactions between polymerase and the E. coli chromosome. We find that activation involving decreased polymerase binding yields lower latency in gene regulation and therefore might confer a competitive advantage to cells. Our model yields insights into requirements for predicting the order of activation of a regulon and enables us to suggest that activation might involve a decrease in polymerase binding which we expect to be an important theme of gene regulation in E. coli and beyond.
When environmental conditions change, cell survival can depend on sudden production of proteins that are normally in low demand. Protein production is controlled by transcription factors which bind to DNA near genes and either increase or decrease RNA production. Many puzzles remain concerning the ways transcription factors do this. Recently we collected data relating the intracellular level of a single transcription factor, MarA, to the increase in expression of several genes related to antibiotic and superoxide resistance in Escherichia coli. These data indicated that target genes are turned on in a well-defined order with respect to the level of MarA, enabling cells to mount a response that is commensurate to the level of threat detected in the environment. Here we develop a computational model to yield insight into how MarA turns on its target genes. The modeling suggests that MarA can increase the frequency with which a transcript is made while decreasing the overall presence of the transcription machinery at the start of a gene. This mechanism is opposite to the textbook model of transcriptional activation; nevertheless it enables cells to respond quickly to environmental challenges and is likely of general importance for gene regulation in E. coli and beyond.
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