Increases in beta power associated with top-down attention. Beta seemed unite visual cortex. There was a more homogeneous pattern of beta correlation across the cortex during top-down vs bottom-up attention.
Bekisz, M., Bogdan, W., Ghazaryan, A., Waleszczyk, W. J., Kublik, E., & Wróbel, A. (2016). The Primary Visual Cortex Is Differentially Modulated by Stimulus-Driven and Top-Down Attention. PloS one, 11(1), e0145379.
Lunqvist, M., Rose, J., Herman, P, Brincat, S.L, Buschman, T.J., and Miller, E.K. (in press) Gamma and beta bursts underlie memory. Neuron
We know how to party!
The viewpoint that single neurons are the functional units of the brain rests on the hypothesis that each neuron has a single function or “message”. This notion has eroded under observations that cortical neurons do not seem to do one thing. Instead, neurons often respond to diverse combinations of task relevant variables, and often a variety of different variables with no apparent single function. Why would the brain evolve neurons with this “mixed selectivity”? In short, they add computational power. How? Read this paper and we”ll tell you.
Why neurons mix: high dimensionality for higher cognition,
Stefano Fusi, Earl K Miller, Mattia Rigotti,
Current Opinion in Neurobiology, Volume 37, April 2016, Pages 66-74, ISSN 0959-4388, http://dx.doi.org/10.1016/j.conb.2016.01.010.
Nice review of our putative neural correlate of one of the most studied cognitive functions: Working memory.
Riley, Mitchell R., and Christos Constantinidis. “Role of Prefrontal Persistent Activity in Working Memory.” Frontiers in systems neuroscience 9 (2015).
Earl Miller is scheduled to discuss the myth of multitasking on NBC’s TODAY show tomorrow morning (1/27/16). Tune in (but only if it is not a distraction).
I like to say that anatomy is the road-and-highway system, activity is the traffic, and oscillations are the traffic lights. So, here you go:
Human brain networks function in connectome-specific harmonic waves.
Selen Atasoy, Isaac Donnelly & Joel Pearson
Nature Communications 7, Article number: 10340 doi:10.1038/ncomms10340
Oscillatory synchrony of prefrontal parvalbumin plays a role in top-down control of attention.
Kim, H., Ährlund-Richter, S., Wang, X., Deisseroth, K., & Carlén, M. (2016). Prefrontal Parvalbumin Neurons in Control of Attention. Cell, 164(1), 208-218.
Pascal Fries and crew add to the mounting evidence that slow vs fast oscillations subserve feedback vs feedforward information flow in the cortex.
Michalareas, G., Vezoli, J., van Pelt, S., Schoffelen, J. M., Kennedy, H., & Fries, P. (2016). Alpha-Beta and Gamma Rhythms Subserve Feedback and Feedforward Influences among Human Visual Cortical Areas. Neuron.
Here’s the link to Neuron’s Best of 2014-2015 Special Issue:
http://info.cell.com/best-of-neuron-2014-2015
And here’s the paper:
Antzoulatos, E.G. and Miller, E.K. (2014) Increases in functional connectivity between the prefrontal cortex and striatum during category learning. Neuron, 83:216-225. View PDF
Well done, Evan!
Bichot et al find that a particular part of the prefrontal cortex is the source of information about an object when we search for it. In other words, when you look for your missing keys, this is the part of the brain that reminds you what they look like.
Excellent review of how wide-spread brain areas use synchronized rhythms form networks for focusing attention. Very comprehensive and thorough on both a maco and micro-circuit level.
Wang and colleagues present a model of the whole cortex (almost). A gradient of synaptic excitation results in sensory areas show fast responses while cognitive areas show slow integrative activity. Different temporal hierarchies/dynamics coexist in the same networks.
A Large-Scale Circuit Mechanism for Hierarchical Dynamical Processing in the Primate Cortex
Rishidev Chaudhuri, Kenneth Knoblauch, Marie-Alice Gariel, Henry Kennedy, Xiao-Jing Wang
Neuron, Volume 88, Issue 2, 21 October 2015, Pages 419–431
In general, this fits pretty well with our recent study of actual neural dynamics across the cortex:
Siegel, M., Buschman, T.J., and Miller, E.K. (2015) Cortical information flow during flexible sensorimotor decisions. Science. 19 June 2015: 1352-1355. View PDF
Samaha and Postle report on the close relationship between alpha-band oscillations and human perception, including that individuals with higher alpha frequencies have vision with a finer temporal resolution. Cool.
It is widely thought that the volitional focusing of attention on a sensory input depends on top-down influences from the prefrontal cortex (PFC) acting on sensory cortex. However, much of the evidence for this is circumstantial. Halassa et al now provide direct evidence using optogenetic manipulation in mice. When they temporarily disrupted the PFC, mice had trouble focusing on a visual input in the face of an auditory distraction and vice-versa. Moreover, they went on to show that the PFC acts on sensory cortex, not directly but, through the thalamic reticular nucleus (TRN). Manipulation of thalamocortical circuits showed that behavior depended on PFC interactions with the thalamus, not on PFC interactions with sensory cortex. Further, thalamic activity was correlated with behavioral performance and its manipulation was causal to performance. This all suggests that attention is focused when the PFC acts on sensory cortex via the thalamus.
Pascal Fries walks us through the latest in the communication through coherence theory.
Fries, Pascal. “Rhythms for Cognition: Communication through Coherence.”Neuron 88.1 (2015): 220-235.
Eriksson et al discuss working memory, not as an isolated function, but as an interaction between component processes such as attention, propsection, perception and long-term memory.
Eriksson, Johan, et al. “Neurocognitive Architecture of Working Memory.”Neuron 88.1 (2015): 33-46.
Tim Buschman and Sabine Kastner review work on visual attention and propose a new theory that ties together a wide range of observations. Here’s an outline of the theory in their own words:
- Attention can either be (a) automatically grabbed by salient stimuli or (b) guided by task representations in frontal and parietal regions to specific spatial locations or features.
- The pattern-completion nature of sensory cortex sharpens the broad top-down attentional bias, restricting it to perceptually relevant representations. Interactions with bottom-up sensory drive will emphasize specific objects.
- Interneuron-mediated lateral inhibition normalizes activity and, thus, suppresses competing stimuli. This results in increased sensitivity and decreased noise correlations.
- Lateral inhibition also leads to the generation of high-frequency synchronous oscillations within a cortical region. Inter-areal synchronization follows as these local oscillations synchronize along with the propagation of a bottom-up sensory drive. Both forms of synchrony act to further boost selected representations.
- Further buildup of inhibition acts to “reset” the network, thereby restarting the process. This reset allows the network to avoid being captured by a single stimulus and allows a positive-only selection mechanism to move over time.
Makes a lot of sense.
Buschman, Timothy J., and Sabine Kastner. “From Behavior to Neural Dynamics: An Integrated Theory of Attention.” Neuron 88.1 (2015): 127-144.
Jim DiCarlo and crew show how a weighted average of firing rates of neurons in inferior temporal cortex can explain performance on an object recognition task.
Eiselt and Nieder show that coding of numerical magnitudes is the prefrontal cortex but not the premotor or cingulate cortex.
Review: Kei Igarashi argues that learning-related changes in synchrony between oscillatory activity in the cortex and hippocampus enhances neural communication and thus supports memory storage and recall.
Nice demo showing that cues that automatically draw attention can modulate activity in primary visual cortex.
Stoianov et al show how two mechanisms interact in the prefrontal cortex to support goal-directed behavior. Categorization extracts behavioral abstractions (states) and reward-driven processes assign value to these categories
Ranganath and Jacob walk us through the role that prefrontal cortex dopamine plays in cognition.
Erez and Duncan elegantly show that the prefrontal cortex only cares about behavioral (goal) relevance. Human subjects detected whether images from one of two visual categories were present in a scene. The prefrontal cortex did not distinguish between the two categories but did distinguish whether an image was one the two categories (i.e., a target) or not (a non-target).
Ester et al use human imaging to show that the parietal and frontal cortices maintain information about specific visual stimuli held in memory. This shows that top-down control of working memory and storage functions are not so separate. We kind of knew that from the neuron level, but very nice demo in humans.
Ester, Edward F., Thomas C. Sprague, and John T. Serences. “Parietal and Frontal Cortex Encode Stimulus-Specific Mnemonic Representations during Visual Working Memory.” Neuron (2015).