A Neuron Preview for Miller Lab graduate student Simon Kornblith’s paper on a network for scene processing:
Scene Areas in Humans and Macaques by Epstein and Julian
Here’s the original post on Simon’s paper and a link to it:
A Network For Scene Processing
Jutras et al find a relationship between hippocampal theta and visual exploration via saccadic eye movements. Saccades caused a theta reset that was predictive of subsequent recognition of visual images. Enhanced theta power before stimulus onset was also predictive of recognition.
Miller Lab graduate student Simon Kornblith publishes a paper in Neuron from work in his old lab. By combining FMRI with electrode recording and stimulation, they found an area in the occipitotemporal cortex that has many scene-selective neurons, the lateral place patch (LPP). By stimulating it, they discover connections to several other cortical areas, including a medial place patch (MPP) in the parahippocampal gyrus. Elegant and important work, Simon, congratulations! Now, get back to work. ?
Cowell and Cottrell trained a computational model on images used in fMRI studies of object and face processing. They used multivariate pattern analysis and were able to replicate evidence for a specialized face area even though the model had no specialized processing for faces. The authors suggest that fMRI evidence for a specialized face area should be interpreted with caution.
Hohl et al use a task with richer behavioral output to better establish a link between neural activity and behavior.
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)
Pannunzi et al propose a model of visual category learning in which bottom-up sensory inputs to the inferior temporal cortex are sculpted by top-down inputs from the prefrontal cortex (PFC). The PFC improves signal to noise by enhancing the category-relevant features of the stimuli.
Miller 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 »
Freedman, D.J., Riesenhuber, M., Poggio, T., and Miller, E.K (2003) A comparison of primate prefrontal and inferior temporal cortices during visual categorization. Journal of Neuroscience, 23(12):5235-5246. View PDF »
Meyers, E.M., Freedman, D.J., Kreiman, G., Miller, E.K., and Poggio, T. (2008) Dynamic population coding of category information in the inferior temporal cortex and prefrontal cortex. Journal of Neurophysiology. 100:1407-1419. View PDF »
Muhammad, R., Wallis, J.D., and Miller, E.K. (2006) A comparison of abstract rules in the prefrontal cortex, premotor cortex, the inferior temporal cortex and the striatum. Journal of Cognitive Neuroscience, 18: 974-989. View PDF »
Seger, C.A. and Miller, E.K. (2010) Category learning in the brain. Annual Review of Neuroscience, Vol. 33: 203-219. View PDF »
Visual attention modulates several aspects of neural coding. There is an increase in firing rate and changes in temporal dynamics: a reduction of neural variance and noise correlation as well as changes in oscillatory synchronization. The authors used glutamatergic receptor activation, combined with neurophysiological recording to show that the NMDA receptor is responsible for attention -related changes in neural temporal dynamics but not for increases in firing rate. Thus, different neurophysiological mechanisms that underlie attention can be dissociated at the receptor level. This supports the hypothesis that attention is mediated in part by the temporal dynamics of neural activity, not merely changes in the firing rate of neurons, and that the changes temporal dynamics are not simply a byproduct of changes in firing rate.
Herrero et al (2013) Neuron
For a further discussion of the role of temporal dynamics in attention see:
Miller, E.K. and Buschman, T.J. (2013) Cortical circuits for the control of attention. Current Opinion in Neurobiology. 23:216–222 View PDF »
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 . 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 »
This paper uses EEG to examine the timecourse of synchronization patterns across the brain during a simple cognitive task. First, there was low frequency (delta) synchrony, which may reflect global, long-range synchronization and may help organize the higher frequency synchrony that followed. Then, there was higher frequency (gamma) synchrony, which may reflect reorganization of local circuits for bottom-up processing of sensory inputs. Finally, there was beta synchrony, which may reflect the final stage of top-down processing in the task. Gamma and beta synchronization has been shown to be correlated with bottom-up vs top-down cortical processing (Buschman and Miller, 2007; Chanes et al, 2013; Ibos et al, 2013). This study identifies and confirms some of the proposed mechanisms of global information integration in the brain.
Brazdil et al (2013)
For further reading:
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 »
Chanes et al (2013) Journal of Neuroscience
Ibos et al (2013) Journal of Neuroscience
In this week’s NY Times, Susana Martinez-Conde reminds us that our visual system works by detecting change.
http://www.nytimes.com/2013/05/19/opinion/sunday/vision-is-all-about-change.html