Hirabayashi et al observed microcircuits for object association using multiple single-unit recordings in temporal cortex. This suggests that microcircuits creates precursor representations for a given feature in previous areas in the cortical hierarchy.
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Your prefrontal cortex becomes less resistant to stress as you age. McEwen and Morrison tell you all about it.
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The 2013 Annual Review of Neuroscience is here. It includes a very nice review of the role of the prefrontal cortex in visual attention by Squire et al
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Boot et al show that it is important for psychology studies to have active controls. To exclude placebo effects, the control should include the expectation of change without the actual manipulation.
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Propofol-induced unconsciousness decreases posterior alpha rhythms and increases frontal alpha rhythms. Vijayan et al show that this may be due to different actions on posterior vs anterior projecting thalamic nuclei.
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DiQuattro et al use dynamic causal modeling (DCM) of FMRI signals to show that the frontal eye fields (FEF) are more involved initiating shifts of attention than the temporoparietal junction (TPJ, another leading candidate). The FEF received sensory signals earlier than the TPJ and FEF to TPJ connectivity was modulated by appearance of a target.
Miller Lab work cited:
Buschman, T.J. and Miller, E.K. (2007) Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science. 315: 1860-1862 The Scientist’s “Hot Paper” for October 2009. View PDF »Buschman, T.J. and Miller, E.K. (2009) Serial, covert, shifts of attention during visual search are reflected by the frontal eye fields and correlated with population oscillations. Neuron, 63: 386-396. View PDF »
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Kraus et al required rats to run on a treadmill during a working memory task. They dissociated distance traveled vs time spent running by requiring the rats to run for a fixed distance or a fixed amount of time. This revealed “time cells” in the hippocampus that reflect the passage of time.
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Miller Lab alumnus, Andreas Nieder, finds that abstract decisions divorced from motor plans are distributed across frontal areas, even those traditionally thought of as motor areas. In fact, they are more strongly encoded in the presupplementary motor area than the prefrontal cortex.
Merten and Nieder 2013Miller Lab work cited:
Freedman, D.J., Riesenhuber, M., Poggio, T., and Miller, E.K. (2001) Categorical representation of visual stimuli in the primate prefrontal cortex. Science, 291:312-316. View PDF »Miller, E.K. and Cohen, J.D. (2001) An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24:167-202. Designated a Current Classic by Thomson Scientific as among the most cited papers in Neuroscience and Behavior. View PDF »
Miller, E.K. (2000) The prefrontal cortex and cognitive control. Nature Reviews Neuroscience, 1:59-65.
Wallis, J.D., Anderson, K.C., and Miller, E.K. (2001) Single neurons in the prefrontal cortex encode abstract rules. Nature, 411:953-956. View PDF »
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Nicole Rust and crew show how the perirhinal cortex can take signals from the inferior temporal cortex and sort out visual targets from distractors.
Pagan et al (2013) -
Totah et al find that increased synchrony between the prelimbic cortex and anterior cingulate cortex before stimulus onset predicted behavioral choices. Further, there was a switch from beta synchrony during attention to delta synchrony before the behavioral response. This shows, among other things, that the same neurons can participate in different functional networks by virtue of how that synchronize with other neurons.
This paper is one of several recent studies providing evidence that oscillatory synchrony allows multiplexing of neural function. Here’s an excerpt from Miller and Fusi (2013) that summarizes this point:
“It (oscillatory synchrony) could allow neurons to communicate different messages to different targets depending on whom they are synchronized with (and how, e.g., phase, frequency). For example, rat hippocampal CA1 neurons preferentially synchronize to the entorhinal or CA3 neurons at different gamma frequencies and theta phases (Colgin et al, 2009). Different frequency synchronization between human cortical areas supports recollection of spatial vs temporal information (Watrous et al., 2013). Different phases of cortical oscillations preferentially signal different pictures simultaneously held in short-term memory (Siegel et al., 2009). Monkey frontal and parietal cortices synchronize more strongly at lower vs higher frequency for top-down vs bottom-up attention, respectively (Buschman and Miller, 2007). Entraining the human frontal cortex at those frequencies produces the predicted top-down vs bottom-up effects on behavior (Chanes et al., 2013). Thus, activity from the same neurons has different functional outcomes depending on their rhythmic dynamics.”
Miller, E.K. and Fusi, S. (2013) Limber neurons for a nimble mind. Neuron. 78:211-213. View PDF