A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex

de Vries, Lecoq, Buice, Groblewski, Ocker, Oliver, Feng, Cain · Nature Neuroscience · 2020 · neuroscience · 10.1038/s41593-019-0550-9 · record de-Vries2020-a-large-scale-standardized-physiological-sur
tag layer · index · concepts · authors · עברית
Where this record's text came from. faceted 2026-08 by reading the locally held text (xml); every evidence string verified as an exact substring of that text before merging. method does not fit the suggested list: the recording modality is in vivo two-photon calcium imaging, not electrophysiology, so a precise lowercase-hyphenated value was used; the paper is also partly a resource/pipeline paper ("Here we report an open, large-scale physiological survey of activity in the awake mouse visual cortex: the Allen Brain Observatory Visual Coding dataset."). Claim relations is restricted to the three places where prior work is named in words — nearly all other citations in this article are bare superscript numbers (e.g. "While previous literature has found higher direction selectivity in layer 4 within V1 18"), which the rules say must not be turned into relations. Replication status left untested: the paper reports a new survey and does not state that its classification has been independently reproduced. 2026-08-13 and 2026-08-15 schema-0.3 passes: every quote verified as an exact substring of the staged text and anchored at merge time; concept terms verified present; every edge endpoint an existing node.
32 quotations on this page contain a reference number where the paper printed a superscript. This journal style prints citations as raised numerals — parameters12,13 — and the extraction flattened them into the line, so the sentence reads parameters 12 , 13 . The digits are citation markers and not part of what the author wrote. The quotes keep them for the same reason they keep every other extraction fault: a quote is reproduced exactly or it proves nothing.
How to read this page. The article itself is not reproduced here — this paper is not cleared for redistribution, so what follows is the tag layer alone. The evidence sentences are withheld with the article. The table at the foot lists every tag the record carries; each row names the facet it belongs to, and the whose words column says whether the tag records the paper's own wording or the tagger's sentence about the paper. Every tag links to each other paper in the corpus carrying it. The machine-readable edition of the same thing is the TEI file beside this one, where the tags live in standOff, and the article is at its publisher via the link below. When we have changed our mind. Some entries in the table begin with a word in capitals and the reason for it. EVIDENCE CORRECTED — the finding still stands, but we had quoted the wrong sentence from the paper, and the quotation has been replaced with the right one. RETRACTED — the entry itself was wrong; it stays on the page, marked, with the reason, rather than being deleted. WITHDRAWN AND REPLACED — the entry was wrong, and a corrected version of it appears in the entries below. Each mark carries its own reason, in brackets, because the reasons differ from one entry to the next. An entry we have WITHDRAWN is removed from this page and kept in the record, with its reason. A line reading Audit and a date is a later re-reading of the entry against its whole sentence: DOUBTFUL means it was kept, and the reason says what is loose about it. Quotation marks inside the tagger's sentence. Where a tag is the tagger's own sentence, a phrase in quotation marks inside it is borrowed from the paper — the tagger's wording around it is not. The paper's own sentence is the evidence quote for that row; on this page it is withheld with the article, and the article is at its publisher. Nothing inside quotation marks anywhere on this page is ours: if it is quoted, it is the paper's. Whose words a concept carries. A concept entry records a term the paper itself uses, so the term, the sense given for it, and its evidence are the paper's own words, quoted where the paper fixes them. This is the opposite of a sense entry in the tag table, which is the tagger's sentence about how the paper uses a term. Where a concept entry could not be grounded in the paper's words, the entry says so on its own row.
Other fields define these differently the same word, defined another way in another discipline
bias 38 fields · reliability 5 fields · coefficient of variation 4 fields · model 4 fields · quality control 3 fields · class 3 fields · and 2 more →

Tags on this paper

Every tag the record carries, each linking to every other paper in the corpus that carries it. A tag appears here whether or not its words occur in the article — the spans below are only the ones a sentence in this paper licenses. Of the 18 concept tags on this paper, 1 are grounded in a quoted sentence. All carry the tagger's gloss of what the term means in this paper, which is not something the article can license.
none class model bias quality control survey receptive field natural gratings Vip Sst Cre line V1 RL visual cortex running area sparseness Hand-tuning stimuli to each recorded neuron builds selection bias into the classical literature, which is why the standard model looks better in small studies than in an unbiased survey. The unresponsive 'none' neurons may in fact be visually driven but tuned to highly sparse, specific natural features constructed by hierarchical processing, which the presented stimulus set never hits. Because responses are so sparse, different neurons are active at different moments, which is what keeps their pairwise noise correlations weak. lifetime sparseness population sparseness reliability response class imaging depths mean response tuning metrics running state pupil position and area correlation Pearson correlation Kolmogorov-Smirnov test Kolmogorov-Smirnov (KS) test Bonferroni correction Bonferroni correction for the number of comparisons chi-squared test chi-square test Sidak multiple-comparisons correction Šidák multiple comparisons correction Gaussian mixture model clustering with Bayesian Information Criterion model selection Gaussian Mixture Model clustering ... average Bayesian Information Criterion K-nearest-neighbors classification (decoding) K Nearest-Neighbors classifiers cross-validation five-fold cross-validation ridge regression linear ridge regression models polynomial regression coefficient of variation interquartile range bootstrap bootstrapped samples permutation/shuffle test stimulus trials were shuffled to break trial-wise correlations calcium-imaging
Method, as described: two-photon-calcium-imaging

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second readingalternativesan independent re-reading of a facet, recorded whether or not it agrees
relation to other workclaim_relationshow this paper stands to another: agrees, contradicts, extends, qualifies
claim typeclaim_typethe shape of the claim: existence, mechanism, method, critique, prediction, null
concept edgeconcept_edgesan asserted relation between two concepts, with the sentence asserting it
conceptconceptsan idea the paper works with, quoted where the paper uses it
content tagcontent_tagsa finding, definition, quantity, statistic or variable named in the paper
contributioncontributionwhat the paper claims to add
controlcontrolsan experiment run to eliminate a rival explanation
limitationlimitationswhat the paper says its evidence cannot support
mechanismmechanismshow the reported effect is said to come about
methodmethodhow the paper produced its evidence
object of studyobject_of_studywhat the paper is about — the thing it investigates
phenomenonphenomenonthe effect or regularity under study
research questionresearch_questionthe question the paper sets itself
sensesensesa distinct use of a term, quoted where the paper fixes it
transfertransfersa method or concept carried in from another field

The paper

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Every tag on this page

alternatives 3 · claim_relations 7 · claim_type 1 · concept_edges 4 · concepts 1 · content_tags 64 · contribution 1 · controls 5 · limitations 8 · mechanisms 7 · method 1 · object_of_study 1 · phenomenon 1 · research_question 1 · senses 19 · transfers 1

Relations on this page carry a quotation for the claim. Where a relation was separately evidenced — and so tested against the vocabulary for its type — the row says so; none of 4 relations here carry that mark. The rest are the tagger’s reading of the sentence quoted beside them.

facettagfieldconf.whose words
object_of_studyhow stimulus representations ARE TRANSFORMED THROUGHOUT THE VISUAL CORTEX, surveyed rather than sampled
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object_of_studythe paper's words
research_questionwhether the standard account of visual cortex survives a survey that does not select its neurons by their responses - A KEY CHALLENGE RESULTS FROM THE FACT THAT THIS UNDERSTANDING IS BASED ON MANY SMALL STUDIES, RECORDING RESPONSES FROM DIFFERENT STAGES IN THE CIRCUIT, USING DIFFERENT STIMULI AND ANALYSES
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research_questionthe paper's words
contributionan open survey in which THE LARGEST CLASS IS NOT RELIABLY RESPONSIVE TO ANY OF THE STIMULI AND BECOMES PROGRESSIVELY LARGER IN HIGHER VISUAL AREAS
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contributionthe paper's words
claim_typeexistence
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claim_typethe paper's words
phenomenonfunctional organization of mouse visual cortex
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phenomenonthe paper's words
methodcalcium-imaging
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methodthe paper's words
mechanismsmechanisms
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
mechanisms[0]the tagger's words
mechanismsmechanisms
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
mechanisms[1]the tagger's words
mechanismsmechanisms
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
mechanisms[2]the tagger's words
mechanismsthe bias this survey is built against, described as a procedure: NEURONS WERE IDENTIFIED BY RESPONDING TO A TEST STIMULUS - THE STIMULUS WAS THEN HAND-TUNED TO ELICIT THE STRONGEST RELIABLE RESPONSE FROM THAT NEURON, AND THE EXPERIMENT PROCEEDED USING MANIPULATIONS AROUND THIS CONDITION
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mechanisms[3]1.0the tagger's words
mechanismsand what that procedure cannot see: THESE STUDIES MAY HAVE FAILED TO CAPTURE THE VARIABILITY OF RESPONSES, THE BREADTH OF FEATURES THAT WILL ELICIT A NEURAL RESPONSE, AND THE BREADTH OF FEATURES THAT DO NOT ELICIT A RESPONSE - THIS RESULTS IN SYSTEMATIC BIAS IN THE MEASUREMENT OF NEURONS AND A CONFIRMATION BIAS REGARDING MODEL ASSUMPTIONS
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
mechanisms[4]1.0the tagger's words
mechanismsthe one design decision that removes it: THIS PIPELINE REDUCED CRITICAL EXPERIMENTAL BIASES BY SEPARATING QUALITY CONTROL OF DATA COLLECTION FROM RESPONSE CHARACTERIZATION
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
mechanisms[5]1.0the tagger's words
mechanismsand the reason it matters for a whole literature: THIS UNDERSTANDING IS BASED ON MANY SMALL STUDIES, RECORDING RESPONSES FROM DIFFERENT STAGES IN THE CIRCUIT, USING DIFFERENT STIMULI AND ANALYSES - THE INHERENT EXPERIMENTAL SELECTION BIASES AND LACK OF STANDARDIZATION OF THIS APPROACH INTRODUCE ADDITIONAL OBSTACLES TO CREATING A COHESIVE UNDERSTANDING OF CORTICAL FUNCTION
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mechanisms[6]1.0the tagger's words
limitationsThe putative ventral higher visual areas could not be imaged, so the expected inverse (spatial-over-motion) organisation could not be tested.
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what this limits: the same scope as limitations[4] - the putative ventral higher visual areas could not be imaged, so the expected inverse organisation is missing for a reason about the window, not the brain
limitations[0]the tagger's words
limitationsNeurons classed as responding only to natural stimuli may be conventional cells tuned to spatial or temporal frequencies the stimulus set did not sample.
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
what this limits: the class of neurons responding only to natural stimuli: THESE NEURONS COULD BE 'CLASSICAL' NEURONS AS WELL BUT ARE TUNED FOR SPATIAL OR TEMPORAL FREQUENCIES THAT WERE NOT INCLUDED IN OUR STIMULUS SET
limitations[1]the tagger's words
limitationsThe wavelet models leave a large amount of visually responsive activity unexplained.
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what this limits: the explanatory reach of the wavelet models: THERE IS A GREAT DEAL OF VISUALLY RESPONSIVE ACTIVITY THAT IS NOT BEING CAPTURED BY THESE MODELS
limitations[2]the tagger's words
limitationsThe epileptiform-event screening used to exclude mice could not be applied to the inhibitory Cre lines.
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
what this limits: the epileptiform screening, and therefore the quality control on the inhibitory lines: INHIBITORY LINES WERE EXCLUDED FROM THIS ANALYSIS AS THE NEURONAL LABELLING WAS TOO SPARSE TO RELIABLY ASSESS THESE EVENTS
limitations[3]the tagger's words
limitationsone half of the expected organisation is missing for a reason that is about the window, not the brain - WE WERE UNABLE TO IMAGE THE PUTATIVE VENTRAL AREAS LI, POR, OR P WITHIN OUR CRANIAL WINDOW
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
what this limits: reading the absence of a ventral counterpart to the dorsal specialisation as a finding about the cortex
limitations[4]1.0the tagger's words
limitationsthe largest class may be an artefact of the stimulus set rather than a property of the cells - IT IS POSSIBLE THESE NEURONS ARE VISUALLY DRIVEN, BUT ARE RESPONSIVE TO HIGHLY SPARSE AND SPECIFIC NATURAL FEATURES, or THESE NEURONS COULD BE INVOLVED IN NON-VISUAL COMPUTATION
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what this limits: reading 'does not respond to visual stimuli' as 'is not visual'
limitations[5]1.0the tagger's words
limitationsand the stimulus parameters may have been set too low - AS OUR STIMULUS PARAMETERS WERE CHOSEN TO MATCH PREVIOUS MEASUREMENTS OF MOUSE ACUITY, THIS COULD SUGGEST THAT THE ACUITY OF MOUSE HAS BEEN UNDERESTIMATED
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what this limits: reading poor prediction for artificial stimuli as a property of the neurons rather than of the parameter range
limitations[6]1.0the tagger's words
limitationsthe models fail for most of the cortex - EVEN WITH THE INCLUSION OF RUNNING, OUR MODELS PREDICT RESPONSES IN A MINORITY OF NEURONS
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
what this limits: any claim that the standard models describe this cortex: EVEN WITH THE INCLUSION OF RUNNING, OUR MODELS PREDICT RESPONSES IN A MINORITY OF NEURONS
limitations[7]1.0the tagger's words
transfersthe pipeline itself - STANDARD OPERATING PROCEDURES WITH INTEGRATED ENGINEERING TOOLS, applied to make 243 mice comparable to each other
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transfers[0]0.8the tagger's words
controlsquality control of the recording separated from characterisation of the response
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
eliminates: the dataset selecting for cells that respond - STRICT QUALITY CONTROL MEASURES NOT DEPENDENT UPON STIMULUS-DRIVEN ACTIVITY · outcome (stated by the tagger, no quotation): held
controls[0]1.0the tagger's words
controlsthe functional classes validated against a model containing the standard machinery plus running speed
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eliminates: the classes being an artefact of the reliability clustering - the models contain MOST OF THE BASIC FEATURES FOUND IN VISUAL NEUROPHYSIOLOGICAL MODELING as well as THE RUNNING SPEED OF THE MOUSE · outcome (stated by the tagger, no quotation): partial
controls[1]0.8the tagger's words
controlsboth artificial and natural stimuli presented to the same neurons
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
eliminates: a conclusion that holds only for parameterised stimuli - RESPONSES TO NATURAL SCENES CANNOT BE WELL PREDICTED BY RESPONSES TO NOISE OR GRATING STIMULI · outcome (stated by the tagger, no quotation): held
controls[2]1.0the tagger's words
controlsrunning checked as an explanation for the unresponsive class
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
eliminates: locomotion accounting for the 'none' class - WE FOUND LITTLE EVIDENCE THAT THESE NEURONS WERE CORRELATED WITH THE MOUSE'S RUNNING · outcome (stated by the tagger, no quotation): held
controls[3]1.0the tagger's words
controlsa STANDARDISED survey - fixed operating procedures and stimuli applied identically across 59,610 neurons in 243 mice - in place of experiment-specific stimulus choices
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
eliminates: the experimenter's choice of stimulus as the determinant of what is found. The paper states the fault it is answering: earlier studies 'may have failed to capture…', producing 'a CONFIRMATION BIAS regarding…' · outcome (stated by the tagger, no quotation): held
controls[4]0.9the tagger's words
conceptsnone
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also in: none
concepts[0]0.85the paper's words
sensesTHE LARGEST CLASS OF NEURONS RESPONDS TO NOTHING: REMARKABLY, THE LARGEST CLASS OF NEURONS WAS THE “none” CLASS, CONSTITUTING THOSE NEURONS THAT DID NOT RESPOND RELIABLY TO ANY OF THE STIMULI (34% OF NEURONS) - THESE NEURONS ARE THE LEAST LIKELY TO BE DESCRIBED BY “classical receptive fields,” AS EVIDENCED BY THEIR POOR MODEL PERFORMANCE FOR ALL STIMULI
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
senses[0]1.0the tagger's words
sensesand in one area it is almost everything: AREA RL HAS THE LARGEST PROPORTION OF NEURONS IN THE “none” CLASS, OVER 85%, CONSISTENT WITH THE VERY LOW PERCENT OF RESPONSIVE NEURONS
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
senses[1]1.0the tagger's words
sensesTHE PAPER ASKS THE QUESTION ITSELF AND LEAVES IT OPEN: WHAT, THEN, DO THESE NEURONS DO? - and offers both readings, that they ARE RESPONSIVE TO HIGHLY SPARSE AND SPECIFIC NATURAL FEATURES or COULD BE INVOLVED IN NON-VISUAL COMPUTATION
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senses[2]1.0the tagger's words
sensesTHE CLASS THE STANDARD MODEL EXPLAINS IS A TENTH OF THE CORTEX: NEURONS IN THE “DG-SG-NS-NM” CLASS WERE WELL PREDICTED, WITH VALUES COMPARABLE TO THOSE FOUND IN PRIMATES - HOWEVER, THIS CLASS CONSTITUTES ONLY 10% OF THE MOUSE VISUAL CORTEX. And EVEN WITH THE INCLUSION OF RUNNING, OUR MODELS PREDICT RESPONSES IN A MINORITY OF NEURONS
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
senses[3]1.0the tagger's words
sensesTHE SELECTION BIAS OF A WHOLE LITERATURE, DESCRIBED AS A PROCEDURE: NEURONS WERE IDENTIFIED BY RESPONDING TO A TEST STIMULUS - THE STIMULUS WAS THEN HAND-TUNED TO ELICIT THE STRONGEST RELIABLE RESPONSE FROM THAT NEURON... THIS RESULTS IN SYSTEMATIC BIAS IN THE MEASUREMENT OF NEURONS AND A CONFIRMATION BIAS REGARDING MODEL ASSUMPTIONS
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
senses[4]1.0the tagger's words
sensesand the fix is one sentence of study design: THIS PIPELINE REDUCED CRITICAL EXPERIMENTAL BIASES BY SEPARATING QUALITY CONTROL OF DATA COLLECTION FROM RESPONSE CHARACTERIZATION - the decision to include a cell is made before anyone knows whether it responds
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
senses[5]1.0the tagger's words
sensesTHE PROBLEM STATED AS A PROBLEM OF SYNTHESIS: THIS UNDERSTANDING IS BASED ON MANY SMALL STUDIES, RECORDING RESPONSES FROM DIFFERENT STAGES IN THE CIRCUIT, USING DIFFERENT STIMULI AND ANALYSES - THE INHERENT EXPERIMENTAL SELECTION BIASES AND LACK OF STANDARDIZATION OF THIS APPROACH INTRODUCE ADDITIONAL OBSTACLES TO CREATING A COHESIVE UNDERSTANDING OF CORTICAL FUNCTION
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
senses[6]1.0the tagger's words
sensesand the field asked for exactly this: INFLUENTIAL REVIEWS HAVE QUESTIONED THE VALIDITY OF THIS STANDARD MODEL, AND HAVE ARGUED THAT “What would be most helpful is to accumulate a database of single unit or multi-unit data that would allow modelers to test their best theory under ecological conditions.”
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senses[7]1.0the tagger's words
sensesA MISSING HALF OF THE ANSWER, ATTRIBUTED TO THE WINDOW AND NOT THE BRAIN: THE LACK OF AN INVERSE RELATIONSHIP, WHEREIN SPATIAL INFORMATION IS OVERREPRESENTED RELATIVE TO MOTION IN A PUTATIVE “ventral” STREAM, LIKELY REFLECTS THE FACT THAT WE WERE UNABLE TO IMAGE THE PUTATIVE VENTRAL AREAS LI, POR, OR P WITHIN OUR CRANIAL WINDOW
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senses[8]1.0the tagger's words
sensesTWO INTERNEURON CLASSES, 94% AGAINST 9%, TO THE SAME STIMULUS: 94% OF Sst NEURONS IN V1 ARE RESPONSIVE TO DRIFTING GRATINGS, AND RESPOND QUITE RELIABLY ACROSS TRIALS, FAR MORE THAN THE OTHER CRE LINES - Vip NEURONS, ON THE OTHER HAND, ARE LARGELY UNRESPONSIVE, EVEN SUPPRESSED, BY DRIFTING GRATINGS, WITH ONLY 9% OF Vip NEURONS IN V1 LABELLED RESPONSIVE
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senses[9]1.0the tagger's words
sensesand the same cells are highly responsive to a different stimulus class: Vip NEURONS ARE VERY RESPONSIVE TO BOTH NATURAL SCENES AND NATURAL MOVIES, but SHOW LITTLE SELECTIVITY TO THESE STIMULI, AS THEIR MEDIAN LIFETIME SPARSENESS IS LOWER THAN BOTH THE Sst AND THE EXCITATORY NEURONS. `Vip cells are unresponsive` is true of one stimulus set and false of another
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senses[10]1.0the tagger's words
sensesA MEASUREMENT THAT REVERSES AN EARLIER ONE, WITH THE STIMULUS NAMED: RECEPTIVE FIELD MAPPING USING LOCALLY SPARSE NOISE REVEALED THAT Vip NEURONS IN V1 HAVE REMARKABLY LARGE RECEPTIVE FIELD AREAS, LARGER THAN BOTH Sst AND EXCITATORY NEURONS, IN CONTRAST TO THE SMALLER SUMMATION AREA FOR Vip NEURONS, PREVIOUSLY MEASURED USING WINDOWED DRIFTING GRATINGS
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senses[11]1.0the tagger's words
sensesTHE STIMULUS CLASS DECIDES THE ANSWER, AND THE PAPER SAYS SO BEFORE MEASURING: IT IS KNOWN THAT STIMULUS STATISTICS AFFECT VISUAL RESPONSES, SUCH THAT RESPONSES TO NATURAL SCENES CANNOT BE WELL PREDICTED BY RESPONSES TO NOISE OR GRATING STIMULI - WHILE ARTIFICIAL STIMULI CAN BE EASILY PARAMETERIZED AND INTERPRETED, NATURAL STIMULI ARE CLOSER TO WHAT IS ETHOLOGICALLY RELEVANT
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senses[12]1.0the tagger's words
sensesthe headline positive, with its complement: 77% OF NEURONS IN THE MOUSE VISUAL CORTEX RESPOND TO AT LEAST ONE OF THESE VISUAL STIMULI - and THE RESPONSES TO ALL STIMULI ARE HIGHLY SPARSE AND VARIABLE
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senses[13]1.0the tagger's words
sensesTHE DIFFERENCES ARE BETWEEN THE INHIBITORY LINES, NOT THE EXCITATORY ONES: WHILE SUBTLE DIFFERENCES DO EXIST BETWEEN THE EXCITATORY CRE LINES, THESE POPULATIONS ARE LARGELY SIMILAR; THE MORE MARKED DIFFERENCES ARE AMONG THE INHIBITORY INTERNEURONS
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senses[14]1.0the tagger's words
sensesand yet the excitatory lines are not interchangeable either: RORB, SCNN1A-TG3, AND NR5A1, WHICH LABEL DISTINCT LAYER 4 POPULATIONS IN V1, EXHIBIT DISTINCT SPATIAL AND TEMPORAL TUNING PROPERTIES, DIFFERENT DEGREES OF RUNNING CORRELATION, AND SUBTLE DIFFERENCES IN THEIR CLASS DISTRIBUTION - THESE DIFFERENCES SUGGEST THAT THERE ARE SEPARATE CHANNELS OF FEEDFORWARD INFORMATION
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
senses[15]1.0the tagger's words
sensesTHE CLASSES DO NOT RESPECT THE AREAS: Quotation withheld
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
senses[16]1.0the tagger's words
sensesand what organisation there is comes from proportions rather than presence: THE OVERREPRESENTATION OF CLASSES RESPONSIVE TO NATURAL MOVIES AND MOTION STIMULI IN AREAS AL, PM, AND AM RELATIVE TO THE OTHER CLASSES IS CONSISTENT WITH THE ASSIGNMENT OF THESE AREAS TO THE PUTATIVE “dorsal” OR “motion” STREAM
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senses[17]1.0the tagger's words
sensesTHE DATASET IS THE CONTRIBUTION AND IT IS ALREADY BEING REUSED: THESE DATA HAVE BEEN USED BY OTHER RESEARCHERS TO DEVELOP IMAGE PROCESSING METHODS, TO EXAMINE STIMULUS ENCODING AND DECODING, AND TO TEST MODELS OF CORTICAL COMPUTATIONS
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senses[18]1.0the tagger's words
alternativesclaim_type: existence
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a second reading reaching the same value. Recorded: existence — note: a second reading reaching the same value from a different sentence. Not applied - a person decides.
alternatives.claim_typethe tagger's words
alternativesmethod: run every animal through one standardised pipeline with QUALITY CONTROL MEASURES NOT DEPENDENT UPON STIMULUS-DRIVEN ACTIVITY, so that entry into the dataset is decided before any response is measured
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
a second reading DIFFERING from the recorded value. Recorded: calcium-imaging — note: a second reading, verbatim-verified, disagreeing with the value on the record. Not applied - a person decides.
alternatives.methodthe tagger's words
alternativesphenomenon: a population of cortical neurons that respond reliably to none of the stimuli a field has spent decades building
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
a second reading DIFFERING from the recorded value. Recorded: functional organization of mouse visual cortex — note: a second reading, verbatim-verified, disagreeing with the value on the record. Not applied - a person decides.
alternatives.phenomenonthe tagger's words
claim_relationsbuilds-on → Jewell et al. L0-penalized event detection method
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claim_relations[0]the tagger's words
claim_relationsbuilds-on → Vinje and Gallant definition of lifetime sparseness
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claim_relations[1]the tagger's words
claim_relationsbuilds-on → Schoppe et al. computation of CCmax
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claim_relations[2]the tagger's words
claim_relationscritiques → the standard model of visual cortex built from hand-tuned single-neuron recordings
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differs in: how the neurons enter the sample - NEURONS WERE IDENTIFIED BY RESPONDING TO A TEST STIMULUS and THE STIMULUS WAS THEN HAND-TUNED TO ELICIT THE STRONGEST RELIABLE RESPONSE
claim_relations[3]1.0the tagger's words
claim_relationscontradicts → the smaller summation area reported for Vip neurons
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differs in: the stimulus used to map it - LOCALLY SPARSE NOISE here, against WINDOWED DRIFTING GRATINGS previously
claim_relations[4]1.0the tagger's words
claim_relationsextends → previous work showing functional differences among cortical areas in layer 2/3, extended across layers and 12 transgenic lines
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claim_relations[5]0.7the tagger's words
claim_relationsqualifies → the assignment of AL, PM and AM to a dorsal stream
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differs in: that the complement was not testable - WE WERE UNABLE TO IMAGE THE PUTATIVE VENTRAL AREAS LI, POR, OR P WITHIN OUR CRANIAL WINDOW
claim_relations[6]1.0the tagger's words
concept_edgesnone —is-a→ class
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strength of the relation: 1 · note: THE LARGEST CLASS OF NEURONS WAS THE 'none' CLASS, CONSTITUTING THOSE NEURONS THAT DID NOT RESPOND RELIABLY TO ANY OF THE STIMULI (34% OF NEURONS)
also in: none · class
concept_edges[0]1.0the tagger's words
concept_edgesnone —part-of→ RL
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depends on: which area is measured - the same class is 34% of the survey as a whole · strength of the relation: 0.85 · note: AREA RL HAS THE LARGEST PROPORTION OF NEURONS IN THE 'none' CLASS, OVER 85% Audit 2026-09-28: DOUBTFUL - read against its span and kept, but RL has the largest share of non-responsive neurons; part-of is loose.
also in: none · RL
concept_edges[2]1.0the tagger's words
concept_edgesquality control —causes→ bias
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strength of the relation: 1 · note: THIS PIPELINE REDUCED CRITICAL EXPERIMENTAL BIASES BY SEPARATING QUALITY CONTROL OF DATA COLLECTION FROM RESPONSE CHARACTERIZATION Audit 2026-09-28: DOUBTFUL - read against its span and kept, but the pipeline reduced biases; the edge carries no direction.
also in: quality control · bias
concept_edges[4]1.0the tagger's words
concept_edgesnatural —contrasted-with→ gratings
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strength of the relation: 1 · note: RESPONSES TO NATURAL SCENES CANNOT BE WELL PREDICTED BY RESPONSES TO NOISE OR GRATING STIMULI Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but the source endpoint 'natural' is a bare adjective; the span writes 'natural (scenes and movies) stimuli'.
also in: natural · gratings
concept_edges[11]1.0the tagger's words
content_tagscorrelation
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also in: correlation
content_tags.statistics[0]the tagger's words
content_tagsKolmogorov-Smirnov test
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content_tags.statistics[1]the tagger's words
content_tagsBonferroni correction
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content_tags.statistics[2]the tagger's words
content_tagschi-squared test
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content_tags.statistics[3]the tagger's words
content_tagsSidak multiple-comparisons correction
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content_tags.statistics[4]the tagger's words
content_tagsGaussian mixture model clustering with Bayesian Information Criterion model selection
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content_tags.statistics[5]the tagger's words
content_tagsK-nearest-neighbors classification (decoding)
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content_tags.statistics[6]the tagger's words
content_tagscross-validation
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content_tags.statistics[7]the tagger's words
content_tagsridge regression
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content_tags.statistics[8]the tagger's words
content_tagspolynomial regression
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content_tags.statistics[9]the tagger's words
content_tagscoefficient of variation
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content_tags.statistics[10]the tagger's words
content_tagsinterquartile range
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content_tags.statistics[11]the tagger's words
content_tagsbootstrap
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also in: bootstrap
content_tags.statistics[12]the tagger's words
content_tagspermutation/shuffle test
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content_tags.statistics[13]the tagger's words
content_tagslifetime sparseness
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content_tags.statistics[14]1.0the tagger's words
content_tagsIN TOTAL, 77% OF NEURONS WERE RESPONSIVE TO AT LEAST ONE OF THE VISUAL STIMULI PRESENTED
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content_tags.findings[0]the tagger's words
content_tagsBY FAR THE LARGEST SINGLE CLASS REVEALED BY THIS ANALYSIS IS THAT OF NEURONS THAT ARE LARGELY UNRESPONSIVE TO ALL STIMULI, TERMED `none,` WHICH CONTAINS 34±2% OF THE NEURONS
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content_tags.findings[1]the tagger's words
content_tagsArea RL is the extreme case, with over 85% of its neurons falling into the unresponsive 'none' class.
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content_tags.findings[2]the tagger's words
content_tagsHow reliably a neuron responds to one stimulus type predicts almost nothing about how reliably it responds to another.
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content_tags.findings[3]the tagger's words
content_tagsA standard linear-plus-quadratic Gabor wavelet encoding model fits only about 2% of the population well, with median correlations near 0.2.
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content_tags.findings[4]the tagger's words
content_tagsAdding the mouse's running speed to the encoding model gave essentially no extra predictive power except for Vip neurons in V1.
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content_tags.findings[5]the tagger's words
content_tagsMost neurons do not respond on most individual trials, even to the stimulus condition that drives their largest average response.
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content_tags.findings[6]the tagger's words
content_tagsSst interneurons are the most reliably driven population, with 94% of Sst neurons in V1 responsive to drifting gratings.
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content_tags.findings[7]the tagger's words
content_tagsVip interneurons are the mirror image: only 9% of Vip neurons in V1 are responsive to drifting gratings, and many are suppressed by them.
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content_tags.findings[8]the tagger's words
content_tagsCOMPARISONS ACROSS AREAS AND LAYERS REVEALED THAT DIRECTION SELECTIVITY IS HIGHEST IN LAYER 4 OF V1
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content_tags.findings[9]the tagger's words
content_tagsExcitatory neurons had a median lifetime sparseness of 0.77 for natural scenes.
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content_tags.findings[10]the tagger's words
content_tagsTHIS DIVERGENCE IN REPRESENTATION OF THE MOTION CLASSES FROM THE NATURAL CLASSES IN AREAS AL, PM, AND AM IS CONSISTENT WITH THE PUTATIVE DORSAL AND VENTRAL STREAM SEGREGATION IN THE VISUAL CORTEX
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content_tags.findings[11]the tagger's words
content_tagsVip neurons in V1 have unusually large receptive fields mapped with sparse noise, larger than Sst or excitatory neurons and at odds with their small summation area measured with windowed gratings.
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content_tags.findings[12]the tagger's words
content_tagsREMARKABLY, THE LARGEST CLASS OF NEURONS WAS THE `none` CLASS, CONSTITUTING THOSE NEURONS THAT DID NOT RESPOND RELIABLY TO ANY OF THE STIMULI (34% OF NEURONS)
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content_tags.findings[13]1.0the tagger's words
content_tagsAREA RL HAS THE LARGEST PROPORTION OF NEURONS IN THE `none` CLASS, OVER 85%
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content_tags.findings[14]1.0the tagger's words
content_tagsthe well-predicted class CONSTITUTES ONLY 10% OF THE MOUSE VISUAL CORTEX, and EVEN WITH THE INCLUSION OF RUNNING, OUR MODELS PREDICT RESPONSES IN A MINORITY OF NEURONS
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content_tags.findings[15]1.0the tagger's words
content_tags77% OF NEURONS IN THE MOUSE VISUAL CORTEX RESPOND TO AT LEAST ONE OF THESE VISUAL STIMULI, and THE RESPONSES TO ALL STIMULI ARE HIGHLY SPARSE AND VARIABLE
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content_tags.findings[16]1.0the tagger's words
content_tags94% OF Sst NEURONS IN V1 ARE RESPONSIVE TO DRIFTING GRATINGS, while ONLY 9% OF Vip NEURONS IN V1 are LABELLED RESPONSIVE
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content_tags.findings[17]1.0the tagger's words
content_tagsVip NEURONS IN V1 HAVE REMARKABLY LARGE RECEPTIVE FIELD AREAS, LARGER THAN BOTH Sst AND EXCITATORY NEURONS, IN CONTRAST TO THE SMALLER SUMMATION AREA PREVIOUSLY MEASURED USING WINDOWED DRIFTING GRATINGS
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content_tags.findings[18]1.0the tagger's words
content_tagsQuotation withheld
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content_tags.findings[19]1.0the tagger's words
content_tagsWHILE SUBTLE DIFFERENCES DO EXIST BETWEEN THE EXCITATORY CRE LINES, THESE POPULATIONS ARE LARGELY SIMILAR; THE MORE MARKED DIFFERENCES ARE AMONG THE INHIBITORY INTERNEURONS
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content_tags.findings[20]1.0the tagger's words
content_tagslifetime sparseness
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content_tags.definitions[0]the tagger's words
content_tagspopulation sparseness
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content_tags.definitions[1]the tagger's words
content_tagsreliability
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also in: reliability
content_tags.definitions[3]the tagger's words
content_tagsresponse class
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content_tags.definitions[4]the tagger's words
content_tagsimaging depths
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content_tags.variables[1]the tagger's words
content_tagsmean response
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also in: mean response
content_tags.variables[2]the tagger's words
content_tagstuning metrics
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content_tags.variables[3]the tagger's words
content_tagsrunning state
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also in: running state
content_tags.variables[4]the tagger's words
content_tagspupil position and area
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content_tags.variables[5]the tagger's words
content_tagsrunning
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also in: running
content_tags.variables[7]1.0the tagger's words
content_tagsclass
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also in: class
content_tags.variables[8]1.0the tagger's words
content_tags59,610 — neurons imaged in the survey, drawn from 432 experiments
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content_tags.quantities[0]the tagger's words
content_tags77% — share of neurons responsive to at least one visual stimulus
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content_tags.quantities[1]the tagger's words
content_tags34±2% — share of clustered neurons in the 'none' class, unresponsive to every stimulus
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content_tags.quantities[2]the tagger's words
content_tags33% — share of neurons in area RL responding to any stimulus, the lowest of the six areas
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content_tags.quantities[3]the tagger's words
content_tagsmedian 0.36 — WHILE Sst NEURONS WERE COMPARABLE TO EXCITATORY NEURONS (MEDIAN 0.77), Vip NEURONS EXHIBITED LOW LIFETIME SPARSENESS (MEDIAN 0.36)
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content_tags.quantities[4]the tagger's words
content_tags13% — share of neurons whose evoked responses were significantly modulated by running
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content_tags.quantities[5]the tagger's words
content_tags1.9 fold — increase in the median evoked response when the mouse was running versus stationary
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content_tags.quantities[6]the tagger's words
content_tagsmedian 0.02 — noise correlation of excitatory populations, against 0.06 for Sst and 0.15 for Vip
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content_tags.quantities[7]the tagger's words
content_tags517451 — number of free parameters in the 3D Gabor wavelet encoding model
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content_tags.quantities[8]the tagger's words
content_tags33.6% — share of neurons successfully matched across all three imaging sessions
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content_tags.quantities[9]the tagger's words
content_tags21% — share of responsive neurons whose trial responses the average tuning curve predicts with r above 0.5 (11% of all neurons)
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content_tags.quantities[10]the tagger's words
content_tagsover 85% — share of area RL neurons in the unresponsive 'none' class
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content_tags.quantities[11]the tagger's words
content_tags34% — of neurons in the 'none' class - the largest single class in the survey
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depends on: the area - AREA RL HAS THE LARGEST PROPORTION OF NEURONS IN THE 'none' CLASS, OVER 85%
content_tags.quantities[12]1.0the tagger's words
content_tagsonly 10% — of the mouse visual cortex in the class the standard model predicts well
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content_tags.quantities[13]1.0the tagger's words
content_tags77% — of neurons responding to AT LEAST ONE of the stimuli - so 23% respond to none of them
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content_tags.quantities[14]1.0the tagger's words
content_tags94% — of Sst neurons in V1 responsive to drifting gratings
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depends on: the cell class - the matched Vip figure is 9%
content_tags.quantities[15]1.0the tagger's words
content_tagsover 85% — of neurons in area RL falling in the 'none' class
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content_tags.quantities[16]1.0the tagger's words

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