A new review by Sprague et al provides an interesting take on cognitive capacity, information loss and attention.
Visual attention mitigates information loss in small- and large-scale neural codes
Thomas C. Sprague, , Sameer Saproo, John T. Serences
Ruff and Cohen report evidence that attention can increase or decrease neural correlations depending on whether the neurons have the same or different functions.
Our lab and others (e.g., Buschman and Miller, 2007; Bastos et al 2012) has suggested that top-down (feedback) vs bottom-up (feedforward) cortical processing is mediated by synchrony between cortical areas at different frequencies: lower (e.g., beta band) for top-down vs higher (e.g., gamma band) for bottom-up. These two different frequency bands allow top-down vs bottom-signals to multiplex through the same circuits, much as different FM radio stations multiplex through the airwaves. They may also allow cortical microcircuits to engage in helpful things like predictive coding (Bastos et al., 2012).
Schmiedt et al (2014) provide new evidence for this. They recorded neural activity in visual area V4 after damage to primary visual area V1. V4 is higher in the cortical hierarchy, so V1 has a bottom-up influence on V4. They found that damage to V1 decreased the gamma in V4 that follows appearance of a visual stimulus. That is consistent with gamma carrying bottom-up or feedforward signals, lost after V1 damage. By contrast, V4 beta activity was minimally affected, reflecting the unaffected top-down influence on V4 Normally there is beta suppression during visual stimulation, presumably because the bottom-up inputs overwhelm or suppress beta-mediated top-down processing. After V1 damage, this suppression of top-down beta rhythms was diminished, presumably because it was no longer suppressed by bottom-up influences from V1.
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 »
Bastos AM, Usrey WM, Adams RA, Mangun GR, Fries P, Friston KJ. Canonical microcircuits for predictive coding. Neuron. 2012 Nov 21;76(4):695-711. doi:
10.1016/j.neuron.2012.10.038. Review.
Quentin et al examined the relationship between white matter connectivity between the frontal and parietal cortices and the improvement of visual perception by beta oscillatory synchrony between them. They used diffusion imaging to examine the white matter connectivity and used transcranial magnetic stimulation (TMS) over the right frontal eye fields (FEF) to induce beta oscillations. Individuals that showed greater perceptual improvement with the beta TMS also had stronger white matter connectivity.
Visual attention increases synchrony of neural activity in visual cortex. Fries and colleagues showed that synchronization differs for putative excitatory (broad-spiking) and inhibitory (narrow-spiking) neurons. The inhibitory neurons synchronize in the gamma band twice as strongly as excitatory neurons but the excitatory neurons synchronize to an earlier phase than inhibitory neurons. Further, attention increases gamma synchrony for the most active neurons but decreases synchrony for the least active neurons. These results show that attention-related neural synchrony is not uniform but instead an orchestration between different neuron types showing different types of synchrony. This lends further support for the role of neural synchrony in attention.
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.
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.
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