Interesting new work from Ito and Cole showing how network connectivity patterns is associated with representational flexibility.
Ito, T., & Cole, M. W. (2018). Network dimensionality underlies flexible representation of cognitive information. bioRxiv, 262626.
Due to a disruption of top-down attentional amplification.
Berkovitch, L., Dehaene, S., & Gaillard, R. (2017). Disruption of Conscious Access in Schizophrenia. Trends in Cognitive Sciences.
Well said, Howard Eichenbaum. Could agree more. The time is nigh.
Eichenbaum, H. (2017). Barlow versus Hebb: When is it time to abandon the notion of feature detectors and adopt the cell assembly as the unit of cognition?. Neuroscience Letters.
The multidemand network is a set of frontoparietal areas in humans that are recruited for a wide range of cognitive-demanding tasks. Mitchell et al use FMRI connectivity analysis to identify a putative homolog in monkeys.
For much of the history of modern neuroscience, it has been a assumed that the neuron is the functional unit of the brain. But now there is increasing evidence that ensembles of neurons, not individuals, are the functional units. One line of evidence is that many neurons in higher cortical areas have “mixed selectivity” , responses to diverse combinations of variables; they don’t signal one “message”. Thus, their activity only makes sense when simultaneously considering the activity of other neurons. In fact, we (Rigotti et al., 2013; Fusi et al., 2016) have shown that mixed selectivity gives the brain the computational horsepower needed for complex behavior.
In this paper, Dehaqani et al show that simultaneously recorded prefrontal cortex neurons have high-dimensional, mixed-selectivity, representations and convey more information as a population than even individuals. This was especially true for parts of visual space that were weakly encoded by single neurons. Less-informative neurons were recruited into ensemble to fully encode visual space.
Prefrontal neurons expand their representation of space by increase in dimensionality and decrease in noise correlation. Mohammad-Reza Dehaqani, Abdol-Hossein Vahabie, Mohammadbagher Parsa, Behrad Noudoost, Alireza Soltani
doi: http://dx.doi.org/10.1101/065581
Further reading:
Fusi, S., Miller, E.K., and Rigotti, M. (2016) Why neurons mix: High dimensionality for higher cognition. Current Opinion in Neurobiology. 37:66-74 doi:10.1016/j.conb.2016.01.010. View PDF »
Rigotti, M., Barak, O., Warden, M.R., Wang, X., Daw, N.D., Miller, E.K., & Fusi, S. (2013) The importance of mixed selectivity in complex cognitive tasks. Nature, 497, 585-590, doi:10.1038/nature12160. View PDF »
Yuste, Rafael. “From the neuron doctrine to neural networks.” Nature Reviews Neuroscience 16.8 (2015): 487-497.
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.
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.
Ranganath and Jacob walk us through the role that prefrontal cortex dopamine plays in cognition.
One person’s (John Lisman) take on the state of the art of neuroscience in 2015.
The Challenge of Understanding the Brain: Where We Stand in 2015
Woolgar et al show preferential engagement of human frontoparietal networks with an increase in the complexity of task rules. Plus, the frontoparietal cortex adjusts representations to make rules that are more behavioral confusable easier to discriminate.