The title pretty much says it all. Attentional effects in honeybee brains. Neural responding to an object was enhanced relative to a competing object when the former object was chosen.
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Song et al examined oscillatory activity in humans performing an attention task. They found that phase-locking between theta and alpha bands. An uninformative cue initiated alpha pulse at a theta rhythm that seemed to reflect alternating sampling of the uninformative and informative cues.
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Tirin Moore and colleagues challenge the idea that neuron receptive fields shift in anticipation of eye movements, remapping from the pre-movement location to the post-movement location before the eye actually moves. They used multiple-electrode recording to provide a detailed maps of the receptive fields before and after movements. The receptive fields did not remap to reflect the post-movement location. Instead, all the receptive fields converged toward movement target. This suggest that the receptive field do not remap, they reflect attention to the movement target.
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Recent studies have suggested that beta-band oscillatory synchrony plays a role in cognition. For example, different networks of neurons in the prefrontal cortex dynamically synchronize at beta as animals switch between two different task rules (Buschman et al., 2012) suggesting that beta synchrony is forming the neural ensembles for the rules. Different items simultaneously held in working memory line-up on different phases of beta/low-gamma oscillations, as if the brain is juggling the two items 30 times a second (Siegel et al., 2009). Hanslmayr et al disrupted these fine temporal relations by stimulating the human with beta-band TMS pulses. Beta stimulation of the left inferior frontal gyrus impaired memory formation while stimulation at other frequencies did not. There was a beta “echo” that outlasted the stimulation. Subjects with better beta entrainment showed more memory impairment. This lends support for the role of beta rhythms in cognition by showing a causal relationship between beta desynchrony and memory.
This paper:
Simon Hanslmayr, Jonas Matuschek, Marie-Christin Fellner, Entrainment of Prefrontal Beta Oscillations Induces an Endogenous Echo and Impairs Memory Formation, Current Biology, Available online 27 March 2014, ISSN 0960-9822References
Buschman, T.J., Denovellis, E.L., Diogo, C., Bullock, D. and Miller, E.K. (2012) Synchronous oscillatory neural ensembles for rules in the prefrontal cortex. Neuron, 76: 838-846. View PDFSiegel, M., Warden, M.R., and Miller, E.K. (2009) Phase-dependent neuronal coding of objects in short-term memory. Proceedings of the National Academy of Sciences, 106: 21341-21346. View PDF » Read commentary by Vogel and Fukuda
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Mike Hasselmo and colleagues examined how the brain generalizes and infers new behaviors from previous experience. They trained different styles of neural network models to learn context-dependent behaviors (i.e., the response to four stimuli, A B C D, mapped onto two different responses X Y differently in different contexts). There were previously unseen stimuli whose response could be inferred from the other stimuli. They analyzed a Deep Belief Network, a Multi-Layer Perceptron, and the combination of a Deep Belief Network with a Linear Perceptron. The combination of the Deep Belief Network with Linear Perceptron worked best.
A Deep Belief Network has multiple layers of hidden units with connections between, but not within, the layers.
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Peelen and Kastner extend studies of attention in the lab (using simple, neutral displays) to the real world (complex, meaningful scenes). They discuss interactions between what and where templates shaped by object familiarity, scene context, and memory
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Think you can multitask well? Watanabe and Funahasi show that task information signaled by neurons in the prefrontal cortex degrade when animals perform a competing, concurrent task.
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An excellent review by Matt Shapiro and crew on an important topic. They discuss complementary roles and bidirectional interactions between the prefrontal cortex and hippocampus.
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Working memory is limited in capacity. As you load more “stuff” into working memory, errors increase. Bays shows how this may happen. Errors with increasing working memory load may be due to decreased signal strength of spiking neurons. Humans can increase the precision of high priority stimuli in working memory at the expense of low priority stimuli. The reduction in drive to neurons representing high priority stimuli can explain this tradeoff.
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Noudoost, Clark, and Moore deactivated the frontal eye fields (FEF) and recorded from visual cortical area V4. This disrupted saccades to targets but *increased* pre-saccade activity in V4. V4 neurons, however, showed reduced discrimination of the target stimulus. It seems that the FEF provides details about the saccade target to visual cortex.