Video of Earl Miller for the 2015 Professional Achievement Award from the Kent State University Alumni Association.
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Advance copy of our new paper:
Kornblith, S. Buschman, T.J., and Miller, E.K. (2015) Stimulus Load and Oscillatory Activity in Higher Cortex. Cerebral Cortex. doi: 10.1093/cercor/bhv182 Journal linkAbstract:
Exploring and exploiting a rich visual environment requires perceiving, attending, and remembering multiple objects simultaneously. Recent studies have suggested that this mental “juggling” of multiple objects may depend on oscillatory neural dynamics. We recorded local field potentials from the lateral intraparietal area, frontal eye fields, and lateral prefrontal cortex while monkeys maintained variable numbers of visual stimuli in working memory. Behavior suggested independent processing of stimuli in each hemifield. During stimulus presentation, higher-frequency power (50–100 Hz) increased with the number of stimuli (load) in the contralateral hemifield, whereas lower-frequency power (8–50 Hz) decreased with the total number of stimuli in both hemifields. During the memory delay, lower-frequency power increased with contralateral load. Load effects on higher frequencies during stimulus encoding and lower frequencies during the memory delay were stronger when neural activity also signaled the location of the stimuli. Like power, higher-frequency synchrony increased with load, but beta synchrony (16–30 Hz) showed the opposite effect, increasing when power decreased (stimulus presentation) and decreasing when power increased (memory delay). Our results suggest roles for lower-frequency oscillations in top-down processing and higher-frequency oscillations in bottom-up processing. -
Micheli et al find that during sustained attention, successful near-threshold visual detection is predicted by increased phase synchrony between the frontal and temporal/parietal cortex. They suggest that beta coherent states in the prefrontal cortex regulate top-down expectancy and coupling with posterior cortex facilitates the gating of that information.
Evidence for the role of beta in top-down selection continues to mount.
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Siegel, M., Buschman, T.J., and Miller, E.K. (2015) Cortical information flow during flexible sensorimotor decisions. Science. 19 June 2015: 1352-1355.
During flexible behavior, multiple brain regions encode sensory inputs, the current task, and choices. It remains unclear how these signals evolve. We simultaneously recorded neuronal activity from six cortical regions (MT, V4, IT, LIP, PFC and FEF) of monkeys reporting the color or motion of stimuli. Following a transient bottom-up sweep, there was a top-down flow of sustained task information from frontoparietal to visual cortex. Sensory information flowed from visual to parietal and prefrontal cortex. Choice signals developed simultaneously in frontoparietal regions and travelled to FEF and sensory cortex. This suggests that flexible sensorimotor choices emerge in a frontoparietal network from the integration of opposite flows of sensory and task information.
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Earl Miller is quoted in a Time article about the dangers of multitasking:
You Asked: Are My Devices Messing With My Brain? Time (May 13, 2015)
http://time.com/3855911/phone-addiction-digital-distraction/““Every time you switch your focus from one thing to another, there’s something called a switch-cost,” says Dr. Earl Miller, a professor of neuroscience at Massachusetts Institute of Technology. “Your brain stumbles a bit, and it requires time to get back to where it was before it was distracted.” ““You’re not able to think as deeply on something when you’re being distracted every few minutes,” Miller adds. “And thinking deeply is where real insights come from.”
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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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Miller Lab alumnus David Freedman and colleagues present a model that shows how categorical neural activity can develop through learning. As a result of top-down influences from decision neurons, categorical representations develop in neurons that show choice-correlated activity fluctuations. They test the model via recordings from parietal cortex.
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Miller Lab alumnus Melissa Warden has been awarded a Sloan Research Fellowship.
2015 Sloan Research FellowsWe could not be prouder of her if she were a Little Lebowski Urban Achiever.
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Frequency-specific hippocampal-prefrontal interactions during associative learning
Brincat, S.L. and Miller, E.K. (2015) Nature Neuroscience, advanced online publicationAbstract:
Much of our knowledge of the world depends on learning associations (for example, face-name), for which the hippocampus (HPC) and prefrontal cortex (PFC) are critical. HPC-PFC interactions have rarely been studied in monkeys, whose cognitive and mnemonic abilities are akin to those of humans. We found functional differences and frequency-specific interactions between HPC and PFC of monkeys learning object pair associations, an animal model of human explicit memory. PFC spiking activity reflected learning in parallel with behavioral performance, whereas HPC neurons reflected feedback about whether trial-and-error guesses were correct or incorrect. Theta-band HPC-PFC synchrony was stronger after errors, was driven primarily by PFC to HPC directional influences and decreased with learning. In contrast, alpha/beta-band synchrony was stronger after correct trials, was driven more by HPC and increased with learning. Rapid object associative learning may occur in PFC, whereas HPC may guide neocortical plasticity by signaling success or failure via oscillatory synchrony in different frequency bands.