Editing Computational neuroscience (section)

===Cognition, discrimination, and learning===
Computational modeling of higher cognitive functions has only recently{{When|date=February 2016}} begun. Experimental data comes primarily from [[single-unit recording]] in [[primates]].  The [[frontal lobe]] and [[parietal lobe]] function as integrators of information from multiple sensory modalities. There are some tentative ideas regarding how simple mutually inhibitory functional circuits in these areas may carry out biologically relevant computation.<ref>{{cite journal |vauthors=Machens CK, Romo R, Brody CD |title=Flexible control of mutual inhibition: a neural model of two-interval discrimination |journal=Science |volume=307 |issue=5712 |pages=1121–4 |year=2005 |pmid=15718474 |doi=10.1126/science.1104171 |bibcode = 2005Sci...307.1121M |citeseerx=10.1.1.523.4396 |s2cid=45378154 }}</ref>

The [[brain]] seems to be able to discriminate and adapt particularly well in certain contexts. For instance, human beings seem to have an enormous capacity for memorizing and [[face perception|recognizing faces]]. One of the key goals of computational neuroscience is to dissect how biological systems carry out these complex computations efficiently and potentially replicate these processes in building intelligent machines.

The brain's large-scale organizational principles are illuminated by many fields, including biology, psychology, and clinical practice. [[Integrative neuroscience]] attempts to consolidate these observations through unified descriptive models and databases of behavioral measures and recordings. These are the bases for some quantitative modeling of large-scale brain activity.<ref>{{cite journal |vauthors=Robinson PA, Rennie CJ, Rowe DL, O'Connor SC, Gordon E | title=Multiscale brain modelling | journal=Philosophical Transactions of the Royal Society B | volume=360 | issue=1457|pages=1043–1050|year=2005|doi=10.1098/rstb.2005.1638 |pmid=16087447 |pmc=1854922 }}</ref>

The Computational Representational Understanding of Mind ([[CRUM]]) is another attempt at modeling human cognition through simulated processes like acquired rule-based systems in decision making and the manipulation of visual representations in decision making.