Van der Linden et al used computer generated images to study categorization in the human brain. They found that the frontal cortex showed sensitivity to the features diagnostic for the categories, which is consistent with results from animal studies at the neuron level.
Psychedelic drugs desynchronize oscillatory rhythms in the cortex. Like, wow.
Jack Gallant and crew used FMRI to examine scene processing in the human brain. They found that scenes activated many regions of anterior visual cortex and that the scene categories capture the co-occurrence of the objects that compose the scenes.
Adam Gazzaley and company show, for the first time, that training on a video game results in benefits that transfer to other tests of cognition. Training on the NeuroRacer game produced long-lasting improvements in cognitive abilities of older adults (age 65-80). How did they do it? Their trick was to focus on multitasking and attention.
Anguera et al (2013) Nature
Matt Chafee and colleagues used multiple-electrode recording in the prefrontal and parietal cortices to examine the temporal dynamics of their neural activity during a categorization task. They decoded category signals from patterns of simultaneously recorded in small bins and asked whether the resulting information time series in one area could predict the other. This showed that “executive” top-down signals flow from the prefrontal to parietal cortex.
Max Riesenhuber and colleagues used EEG to examine the time course of shape and category signals in the human brain. Neural adaptation for category changes was seen in frontal cortex and then subsequently in temporal cortex. This supports the hypothesis that shape categories are formed by shape signals from temporal cortex that converge and form explicit category representations in frontal cortex. A late category signal in temporal cortex is consistent with category signals feeding back from frontal to temporal cortex.
Markov et al provide an excellent review and analysis of the anatomy of visual cortex and beyond. The show that supragranular layers contain highly segregated feedforward and feedback pathways. Their analysis of the detailed anatomy revealed that feedback connections are more numerous and have more levels than feedforward connections. By contrast, infragranular layers are less hierarchical and may be more involved in point-to-point cross-talk than feedforward or feedback processing. Markov et al map the feedforward and feedback pathways to recent observations that feedforward vs feedback communication is supported by gamma vs beta cortical oscillations.
For more on the role of oscillations in feedforward and feedback cortical communication, see our review:
Miller, E.K. and Buschman, T.J. (2013) Cortical circuits for the control of attention. Current Opinion in Neurobiology. 23:216–222 View PDF »
Miller Lab alumnus Andreas Nieder shows that dopamine (DA) has different effects on two different classes of neurons in the prefrontal cortex. For neurons with a short latency visual response, DA suppressed activity but preserved their signal to noise ratio. For neurons with a longer visual latency (exclusively broad-spiking, putative pyramidal neurons), DA increased excitability and enhanced signal/noise ratio. Thus, DA can shape how the prefrontal cortex processes bottom-up sensory inputs.
Jacob et al
A review of the groundbreaking work of Patricia Goldman-Rakic by Amy Arnsten
Vinck, Womelsdorf, Fries review the role of gamma band synchronization in information transfer in the cortex. They argue that due to feedforward coincidence detection and phase-coupling, gamma synchronization is important for flexible routing of information and may be an important determinant of spike rate coding.
Christian Ruff pays tribute to the late, great, Jon Driver by reviewing neural mechanisms of top-down control of attention and memory.
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.
Eldar et al show that neural gain influences learning style. Subjects learned associations between pictures and reward. The association could be based on different stimulus dimensions and different people had different predispositions for one dimension or the other. Eldar et al assessed neural gain by pupil dilation (which is correlated with locus coeruleus norepinephrine activity) and found that the higher the gain, the more likely subjects were to follow their predispositions. The increase in gain was thought to boost the asymmetry of strength between different functional networks which are responsible for the predisposition in learning style.
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. 🙂
Shenhav, Botvinick, and Cohen tie together a number of observations and notions into a new theory of ACC function: allocation of control based on an evaluation of the expected value of control (EVC).
Pinto et al, despite enough statistical power, fail to see any correlation between performance of a top-down attention task (search) and a bottom-up attention task (singleton capture). They argue that top-down and bottom-up attention systems operate independently.
They cite our work, which suggests that top-down vs bottom up attention signals originate from prefrontal vs parietal cortex:
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 »
Dipoppa and Gutkin propose a model of working memory in which gamma-beta oscillations gates access, theta oscillations protects working memory from distractions, and alpha oscillations clears out old memories.
This is consistent with our observations that beta helps from ensembles for rules held in working memory while alpha clears out a dominant ensemble so that a weaker one can be used:
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 PDF
Zhang et al studied rule-based behavior by either having human subjects choose the rule themselves or by instructing them to the rule. They found context-dependent and context-independent (chosen vs instructed) rule representations in frontal and parietal cortex. This gives insight into the architecture of cognitive control.
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.
Excellent review of an important topic: Working memory capacity. The limitation in working memory capacity is the most objective, easily measured, and tractable property of conscious thought..
Luck and Vogel (2013)
Miller Lab work cited:
Siegel, 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 »
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.
Your prefrontal cortex becomes less resistant to stress as you age. McEwen and Morrison tell you all about it.
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
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.
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.