Normalization model - Revision history

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	The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual Neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027\| s2cid = 22804285 }}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433 \| doi=10.1523/JNEUROSCI.17-21-08621.1997\| pmc = 6573724 \| doi-access = free }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors in the olfactory bulb,<ref name="pmid=20435004 "> {{cite journal \| title=Divisive normalization in olfactory population codes \| author=Olsen SR, Bhandawat V, Wilson R\| journal=Neuron \| year=2011 \| volume=66 \| issue=2\| pages = 287–299 \| doi=10.1016/j.neuron.2010.04.009 \| pmid=20435004 \| pmc=2866644}}</ref> the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. It has also been observed at subthreshold potentials in the hippocampus.<ref name="pmid31021319 "> {{cite journal \| title=Precise excitation-inhibition balance controls gain and timing in the hippocampus \| author=Bhatia A, Moza S, Bhalla US\| journal=eLife \| year=2019 \| volume=8 \| doi=10.7554/eLife.43415 \| pmid=31021319 \| pmc=6517031}}</ref> Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.<ref name="pmid22108672 "></ref> Divisive normalization reduces the redundancy in natural stimulus statistics<ref>{{cite journal \|last1=Schwartz \|first1=O \|last2=Simoncelli \|first2=EP \|title=Natural signal statistics and sensory gain control. \|journal=Nature Neuroscience \|date=2001 \|volume=4 \|issue=8 \|pages=819–25 \|doi=10.1038/90526 \|pmid=11477428\| doi-access = free }}</ref> and is sometimes viewed as an implementation of the [[efficient coding hypothesis\|efficient coding principle]]. Formally, divisive normalization is an [[Infomax\|information-maximizing]] code for stimuli following a [[multivariate Pareto distribution]].<ref>{{cite journal \|last1=Bucher \|first1=SF \|last2=Brandenburger \|first2=AM \|title=Divisive normalization is an efficient code for multivariate Pareto-distributed environments. \|journal=Proceedings of the National Academy of Sciences of the United States of America \|date=2022 \|volume=119 \|issue=40 \|pages=e2120581119 \|doi=10.1073/pnas.2120581119 \|pmid=36161961\|pmc=9546555 \|bibcode=2022PNAS..11920581B \| doi-access = free}}</ref>		The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual Neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027\| s2cid = 22804285 }}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433 \| doi=10.1523/JNEUROSCI.17-21-08621.1997\| pmc = 6573724 \| doi-access = free }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors in the olfactory bulb,<ref name="pmid=20435004 "> {{cite journal \| title=Divisive normalization in olfactory population codes \| author=Olsen SR, Bhandawat V, Wilson R\| journal=Neuron \| year=2011 \| volume=66 \| issue=2\| pages = 287–299 \| doi=10.1016/j.neuron.2010.04.009 \| pmid=20435004 \| pmc=2866644}}</ref> the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. It has also been observed at subthreshold potentials in the hippocampus.<ref name="pmid31021319 "> {{cite journal \| title=Precise excitation-inhibition balance controls gain and timing in the hippocampus \| author=Bhatia A, Moza S, Bhalla US\| journal=eLife \| year=2019 \| volume=8 \| doi=10.7554/eLife.43415 \| pmid=31021319 \| pmc=6517031\| doi-access=free}}</ref> Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.<ref name="pmid22108672 "></ref> Divisive normalization reduces the redundancy in natural stimulus statistics<ref>{{cite journal \|last1=Schwartz \|first1=O \|last2=Simoncelli \|first2=EP \|title=Natural signal statistics and sensory gain control. \|journal=Nature Neuroscience \|date=2001 \|volume=4 \|issue=8 \|pages=819–25 \|doi=10.1038/90526 \|pmid=11477428\| doi-access = free }}</ref> and is sometimes viewed as an implementation of the [[efficient coding hypothesis\|efficient coding principle]]. Formally, divisive normalization is an [[Infomax\|information-maximizing]] code for stimuli following a [[multivariate Pareto distribution]].<ref>{{cite journal \|last1=Bucher \|first1=SF \|last2=Brandenburger \|first2=AM \|title=Divisive normalization is an efficient code for multivariate Pareto-distributed environments. \|journal=Proceedings of the National Academy of Sciences of the United States of America \|date=2022 \|volume=119 \|issue=40 \|pages=e2120581119 \|doi=10.1073/pnas.2120581119 \|pmid=36161961\|pmc=9546555 \|bibcode=2022PNAS..11920581B \| doi-access = free}}</ref>

	==References==		==References==

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2023-01-23T03:08:55Z

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← Previous revision		Revision as of 03:08, 23 January 2023
Line 1:		Line 1:
	The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual Neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027}}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433 \| doi=10.1523/JNEUROSCI.17-21-08621.1997\| pmc = 6573724 \| doi-access = free }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors in the olfactory bulb,<ref name="pmid=20435004 "> {{cite journal \| title=Divisive normalization in olfactory population codes \| author=Olsen SR, Bhandawat V, Wilson R\| journal=Neuron \| year=2011 \| volume=66 \| issue=2\| pages = 287–299 \| doi=10.1016/j.neuron.2010.04.009 \| pmid=20435004 \| pmc=2866644}}</ref> the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. It has also been observed at subthreshold potentials in the hippocampus.<ref name="pmid31021319 "> {{cite journal \| title=Precise excitation-inhibition balance controls gain and timing in the hippocampus \| author=Bhatia A, Moza S, Bhalla US\| journal=eLife \| year=2019 \| volume=8 \| doi=10.7554/eLife.43415 \| pmid=31021319 \| pmc=6517031}}</ref> Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.<ref name="pmid22108672 "></ref> Divisive normalization reduces the redundancy in natural stimulus statistics<ref>{{cite journal \|last1=Schwartz \|first1=O \|last2=Simoncelli \|first2=EP \|title=Natural signal statistics and sensory gain control. \|journal=Nature ~~neuroscience~~ \|date=2001 \|volume=4 \|issue=8 \|pages=~~819-25~~ \|doi=10.1038/90526 \|pmid=11477428\| doi-access = free }}</ref> and is sometimes viewed as an implementation of the [[efficient coding hypothesis\|efficient coding principle]]. Formally, divisive normalization is an [[Infomax\|information-maximizing]] code for stimuli following a [[multivariate Pareto distribution]].<ref>{{cite journal \|last1=Bucher \|first1=SF \|last2=Brandenburger \|first2=AM \|title=Divisive normalization is an efficient code for multivariate Pareto-distributed environments. \|journal=Proceedings of the National Academy of Sciences of the United States of America \|date=2022 \|volume=119 \|issue=40 \|pages=e2120581119 \|doi=10.1073/pnas.2120581119 \|pmid=36161961\| doi-access = free}}</ref>		The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual Neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027\| s2cid = 22804285 }}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433 \| doi=10.1523/JNEUROSCI.17-21-08621.1997\| pmc = 6573724 \| doi-access = free }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors in the olfactory bulb,<ref name="pmid=20435004 "> {{cite journal \| title=Divisive normalization in olfactory population codes \| author=Olsen SR, Bhandawat V, Wilson R\| journal=Neuron \| year=2011 \| volume=66 \| issue=2\| pages = 287–299 \| doi=10.1016/j.neuron.2010.04.009 \| pmid=20435004 \| pmc=2866644}}</ref> the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. It has also been observed at subthreshold potentials in the hippocampus.<ref name="pmid31021319 "> {{cite journal \| title=Precise excitation-inhibition balance controls gain and timing in the hippocampus \| author=Bhatia A, Moza S, Bhalla US\| journal=eLife \| year=2019 \| volume=8 \| doi=10.7554/eLife.43415 \| pmid=31021319 \| pmc=6517031}}</ref> Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.<ref name="pmid22108672 "></ref> Divisive normalization reduces the redundancy in natural stimulus statistics<ref>{{cite journal \|last1=Schwartz \|first1=O \|last2=Simoncelli \|first2=EP \|title=Natural signal statistics and sensory gain control. \|journal=Nature Neuroscience \|date=2001 \|volume=4 \|issue=8 \|pages=819–25 \|doi=10.1038/90526 \|pmid=11477428\| doi-access = free }}</ref> and is sometimes viewed as an implementation of the [[efficient coding hypothesis\|efficient coding principle]]. Formally, divisive normalization is an [[Infomax\|information-maximizing]] code for stimuli following a [[multivariate Pareto distribution]].<ref>{{cite journal \|last1=Bucher \|first1=SF \|last2=Brandenburger \|first2=AM \|title=Divisive normalization is an efficient code for multivariate Pareto-distributed environments. \|journal=Proceedings of the National Academy of Sciences of the United States of America \|date=2022 \|volume=119 \|issue=40 \|pages=e2120581119 \|doi=10.1073/pnas.2120581119 \|pmid=36161961\|pmc=9546555 \|bibcode=2022PNAS..11920581B \| doi-access = free}}</ref>

	==References==		==References==

Rooftopology: added information on efficiency properties

2023-01-06T16:44:08Z

added information on efficiency properties

← Previous revision		Revision as of 16:44, 6 January 2023
Line 1:		Line 1:
	The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual Neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027}}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433 \| doi=10.1523/JNEUROSCI.17-21-08621.1997\| pmc = 6573724 \| doi-access = free }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors in the olfactory bulb,<ref name="pmid=20435004 "> {{cite journal \| title=Divisive normalization in olfactory population codes \| author=Olsen SR, Bhandawat V, Wilson R\| journal=Neuron \| year=2011 \| volume=66 \| issue=2\| pages = 287–299 \| doi=10.1016/j.neuron.2010.04.009 \| pmid=20435004 \| pmc=2866644}}</ref> the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. It has also been observed at subthreshold potentials in the hippocampus.<ref name="pmid31021319 "> {{cite journal \| title=Precise excitation-inhibition balance controls gain and timing in the hippocampus \| author=Bhatia A, Moza S, Bhalla US\| journal=eLife \| year=2019 \| volume=8 \| doi=10.7554/eLife.43415 \| pmid=31021319 \| pmc=6517031}}</ref> Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.		The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual Neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027}}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433 \| doi=10.1523/JNEUROSCI.17-21-08621.1997\| pmc = 6573724 \| doi-access = free }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors in the olfactory bulb,<ref name="pmid=20435004 "> {{cite journal \| title=Divisive normalization in olfactory population codes \| author=Olsen SR, Bhandawat V, Wilson R\| journal=Neuron \| year=2011 \| volume=66 \| issue=2\| pages = 287–299 \| doi=10.1016/j.neuron.2010.04.009 \| pmid=20435004 \| pmc=2866644}}</ref> the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. It has also been observed at subthreshold potentials in the hippocampus.<ref name="pmid31021319 "> {{cite journal \| title=Precise excitation-inhibition balance controls gain and timing in the hippocampus \| author=Bhatia A, Moza S, Bhalla US\| journal=eLife \| year=2019 \| volume=8 \| doi=10.7554/eLife.43415 \| pmid=31021319 \| pmc=6517031}}</ref> Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.<ref name="pmid22108672 "></ref> Divisive normalization reduces the redundancy in natural stimulus statistics<ref>{{cite journal \|last1=Schwartz \|first1=O \|last2=Simoncelli \|first2=EP \|title=Natural signal statistics and sensory gain control. \|journal=Nature neuroscience \|date=2001 \|volume=4 \|issue=8 \|pages=819-25 \|doi=10.1038/90526 \|pmid=11477428\| doi-access = free }}</ref> and is sometimes viewed as an implementation of the [[efficient coding hypothesis\|efficient coding principle]]. Formally, divisive normalization is an [[Infomax\|information-maximizing]] code for stimuli following a [[multivariate Pareto distribution]].<ref>{{cite journal \|last1=Bucher \|first1=SF \|last2=Brandenburger \|first2=AM \|title=Divisive normalization is an efficient code for multivariate Pareto-distributed environments. \|journal=Proceedings of the National Academy of Sciences of the United States of America \|date=2022 \|volume=119 \|issue=40 \|pages=e2120581119 \|doi=10.1073/pnas.2120581119 \|pmid=36161961\| doi-access = free}}</ref>

	==References==		==References==

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2021-05-24T07:23:30Z

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← Previous revision		Revision as of 07:23, 24 May 2021
Line 1:		Line 1:
	The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual ~~neuroscience~~ \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027}}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433 \| doi=10.1523/JNEUROSCI.17-21-08621.1997\| doi-access = free }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors in the olfactory bulb,<ref name="pmid=20435004 "> {{cite journal \| title=Divisive normalization in olfactory population codes \| author=Olsen SR, Bhandawat V, Wilson R\| journal=Neuron \| year=2011 \| volume=66~~(2)~~ \| pages = 287–299 \| doi=10.1016/j.neuron.2010.04.009 \| pmid=20435004 \| pmc=2866644}}</ref> the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. It has also been observed at subthreshold potentials in the hippocampus.<ref name="pmid31021319 "> {{cite journal \| title=Precise excitation-inhibition balance controls gain and timing in the hippocampus \| author=Bhatia A, Moza S, Bhalla US\| journal=eLife \| year=2019 \| volume=8 \| doi=10.7554/eLife.43415 \| pmid=31021319 \| pmc=6517031}}</ref> Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.		The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual Neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027}}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433 \| doi=10.1523/JNEUROSCI.17-21-08621.1997\| pmc = 6573724 \| doi-access = free }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors in the olfactory bulb,<ref name="pmid=20435004 "> {{cite journal \| title=Divisive normalization in olfactory population codes \| author=Olsen SR, Bhandawat V, Wilson R\| journal=Neuron \| year=2011 \| volume=66 \| issue=2\| pages = 287–299 \| doi=10.1016/j.neuron.2010.04.009 \| pmid=20435004 \| pmc=2866644}}</ref> the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. It has also been observed at subthreshold potentials in the hippocampus.<ref name="pmid31021319 "> {{cite journal \| title=Precise excitation-inhibition balance controls gain and timing in the hippocampus \| author=Bhatia A, Moza S, Bhalla US\| journal=eLife \| year=2019 \| volume=8 \| doi=10.7554/eLife.43415 \| pmid=31021319 \| pmc=6517031}}</ref> Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.

	==References==		==References==

WikiCleanerBot: v2.04b - Bot T20 CW#61 - Fix errors for CW project (Reference before punctuation)

2020-12-24T21:14:42Z

v2.04b - Bot T20 CW#61 - Fix errors for CW project (Reference before punctuation)

← Previous revision		Revision as of 21:14, 24 December 2020
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	The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027}}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433 \| doi=10.1523/JNEUROSCI.17-21-08621.1997\| doi-access = free }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors in the olfactory bulb <ref name="pmid=20435004 "> {{cite journal \| title=Divisive normalization in olfactory population codes \| author=Olsen SR, Bhandawat V, Wilson R\| journal=Neuron \| year=2011 \| volume=66(2) \| pages = 287–299 \| doi=10.1016/j.neuron.2010.04.009 \| pmid=20435004 \| pmc=2866644}}</ref>, the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. It has also been observed at subthreshold potentials in the hippocampus <ref name="pmid31021319 "> {{cite journal \| title=Precise excitation-inhibition balance controls gain and timing in the hippocampus \| author=Bhatia A, Moza S, Bhalla US\| journal=eLife \| year=2019 \| volume=8 \| doi=10.7554/eLife.43415 \| pmid=31021319 \| pmc=6517031}}</ref>. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.		The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027}}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433 \| doi=10.1523/JNEUROSCI.17-21-08621.1997\| doi-access = free }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors in the olfactory bulb,<ref name="pmid=20435004 "> {{cite journal \| title=Divisive normalization in olfactory population codes \| author=Olsen SR, Bhandawat V, Wilson R\| journal=Neuron \| year=2011 \| volume=66(2) \| pages = 287–299 \| doi=10.1016/j.neuron.2010.04.009 \| pmid=20435004 \| pmc=2866644}}</ref> the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. It has also been observed at subthreshold potentials in the hippocampus.<ref name="pmid31021319 "> {{cite journal \| title=Precise excitation-inhibition balance controls gain and timing in the hippocampus \| author=Bhatia A, Moza S, Bhalla US\| journal=eLife \| year=2019 \| volume=8 \| doi=10.7554/eLife.43415 \| pmid=31021319 \| pmc=6517031}}</ref> Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.

	==References==		==References==

106.198.141.33 at 14:59, 22 June 2020

2020-06-22T14:59:43Z

← Previous revision		Revision as of 14:59, 22 June 2020
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	The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027}}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433 \| doi=10.1523/JNEUROSCI.17-21-08621.1997\| doi-access = free }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors, the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.		The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027}}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433 \| doi=10.1523/JNEUROSCI.17-21-08621.1997\| doi-access = free }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors in the olfactory bulb <ref name="pmid=20435004 "> {{cite journal \| title=Divisive normalization in olfactory population codes \| author=Olsen SR, Bhandawat V, Wilson R\| journal=Neuron \| year=2011 \| volume=66(2) \| pages = 287–299 \| doi=10.1016/j.neuron.2010.04.009 \| pmid=20435004 \| pmc=2866644}}</ref>, the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. It has also been observed at subthreshold potentials in the hippocampus <ref name="pmid31021319 "> {{cite journal \| title=Precise excitation-inhibition balance controls gain and timing in the hippocampus \| author=Bhatia A, Moza S, Bhalla US\| journal=eLife \| year=2019 \| volume=8 \| doi=10.7554/eLife.43415 \| pmid=31021319 \| pmc=6517031}}</ref>. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.

	==References==		==References==

OAbot: Open access bot: doi added to citation with #oabot.

2020-04-15T04:22:44Z

Open access bot: doi added to citation with #oabot.

← Previous revision		Revision as of 04:22, 15 April 2020
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	The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027}}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433 \| doi=10.1523/JNEUROSCI.17-21-08621.1997}}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors, the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.		The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027}}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433 \| doi=10.1523/JNEUROSCI.17-21-08621.1997\| doi-access = free }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors, the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.

	==References==		==References==

Rjwilmsi: /* top */Journal cites:, added 1 DOI

2019-11-20T10:23:30Z

top: Journal cites:, added 1 DOI

← Previous revision		Revision as of 10:23, 20 November 2019
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	The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027}}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433}}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors, the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.		The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027}}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433 \| doi=10.1523/JNEUROSCI.17-21-08621.1997}}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors, the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.

	==References==		==References==

Dexbot: Bot: Deprecating Template:Cite pmid and some minor fixations

2015-08-16T15:12:42Z

Bot: Deprecating Template:Cite pmid and some minor fixations

← Previous revision		Revision as of 15:12, 16 August 2015
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	The '''normalization model'''<ref name="pmid22108672 ">{{Cite ~~pmid~~\|22108672 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite ~~pmid~~\|~~1504027~~ }}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite ~~pmid~~\|~~9334433~~ }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors, the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.		The '''normalization model'''<ref name="pmid22108672 ">{{Cite journal \| last1 = Carandini \| first1 = M. \| last2 = Heeger \| first2 = D. J. \| doi = 10.1038/nrn3136 \| title = Normalization as a canonical neural computation \| journal = Nature Reviews Neuroscience \| volume = 13 \| issue = 1 \| pages = 51–62 \| year = 2011 \| pmid = 22108672 \| pmc =3273486 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite journal \| doi = 10.1017/S0952523800009640 \| last1 = Heeger \| first1 = D. J. \| title = Normalization of cell responses in cat striate cortex \| journal = Visual neuroscience \| volume = 9 \| issue = 2 \| pages = 181–197 \| year = 1992 \| pmid = 1504027}}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite journal \| last1 = Carandini \| first1 = M \| last2 = Heeger \| first2 = DJ \| last3 = Movshon \| first3 = JA \| title = Linearity and normalization in simple cells of the macaque primary visual cortex \| journal = Journal of Neuroscience \| volume = 17 \| issue = 21 \| pages = 8621–44 \| year = 1997 \| pmid = 9334433}}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors, the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.

	==References==		==References==

Magioladitis: Replace unicode entity nbsp for character [NBSP] (or space) per WP:NBSP + other fixes, replaced: → (6) using AWB (10331)

2014-07-28T08:50:49Z

Replace unicode entity nbsp for character [NBSP] (or space) per WP:NBSP + other fixes, replaced: → (6) using AWB (10331)

← Previous revision		Revision as of 08:50, 28 July 2014
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	The '''normalization model'''<ref name="pmid22108672 ">{{Cite pmid\|22108672 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite pmid\|1504027 }}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite pmid\|9334433 }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors, the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.		The '''normalization model'''<ref name="pmid22108672 ">{{Cite pmid\|22108672 }}</ref> is an influential model of responses of [[neurons]] in [[primary visual cortex]]. [[David Heeger]] developed the model in the early 1990s,<ref name="pmid1504027 ">{{Cite pmid\|1504027 }}</ref> and later refined it together with [[Matteo Carandini]] and [[J. Anthony Movshon]].<ref name="pmid9334433 ">{{Cite pmid\|9334433 }}</ref> The model involves a divisive stage. In the numerator is the output of the classical [[receptive field]]. In the denominator, a constant plus a measure of local stimulus [[Contrast (vision)\|contrast]]. Although the normalization model was initially developed to explain responses in the primary visual cortex, normalization is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions, including the representation of odors, the modulatory effects of visual attention, the encoding of value, and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that normalization serves as a canonical neural computation.

	==References==		==References==