Toward an integrated classification of neuronal cell types: morphoelectric and transcriptomic characterization of individual GABAergic cortical neurons

Gouwens, Sorensen, Baftizadeh, Budzillo, Lee, Jarsky, Alfiler, Arkhipov · bioRxiv · 2020 · neuroscience · 10.1101/2020.02.03.932244 · record Gouwens2020-toward-an-integrated-classification-of-neuro
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Where this record's text came from. faceted 2026-08 by reading the locally held text (pdftext); every evidence string verified as an exact substring of that text before merging. The method is Patch-seq, i.e. whole-cell recording combined with single-cell RNA-sequencing and biocytin morphological reconstruction; the controlled method vocabulary has no combined term, so 'electrophysiology' records the core measurement and the transcriptomic and morphological arms are not captured by that facet. Claim type is 'existence' because the headline claim is that at least 20 cross-modal met-types are present; the paper simultaneously reports a partial null (t-types are not reliably predictable from morpho-electric features, classifier accuracy 57%), which the single claim type field cannot hold. This is a bioRxiv preprint that had not been certified by peer review at the time of posting. 2026-08-14, 2026-08-16 and 2026-08-25 schema-0.3 passes: every quote verified as an exact substring of the staged text and anchored at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.
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Other fields define these differently the same word, defined another way in another discipline
principal component analysis 5 fields · cross-validation 3 fields · bootstrap 2 fields · statistical-significance 2 fields · morphological features 2 fields

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 7 concept tags on this paper, all 7 are grounded in a quoted sentence.
t-types me-types Martinotti cell met-types co-clusters consensus number t-type classifier the noisy modality is not clustered on its own but MAPPED onto a reference taxonomy built from the clean one, and the stated purpose is to minimise the contribution of contamination from non-neuronal cells and nearby excitatory neurons the mapping is bootstrapped rather than computed once - a hundred iterations, each using only seventy per cent of the available genes and of the reference cells - so that a cell's assigned type carries a confidence instead of being a bare label AMBIGUITY THAT BELONGS TO THE TAXONOMY IS SEPARATED FROM AMBIGUITY THAT BELONGS TO THE MEASUREMENT: a reference matrix records how often each type is confused with each other type in the clean data, and a cell's observed confusion is scored against that expectation rather than against zero two numerical cut-offs then decide which cells are set aside - a divergence above two, and, among the survivors, a correlation below one half between the cell's expression and the average expression of the types the per-type analyses are then run only on the subset with the highest-confidence mapping, and the stated reason is to limit the effect of mapping ambiguities due to technical issues the mapping is checked four separate ways rather than asserted: against a method that does not use the tree's hierarchy at all, against cells from transgenic lines labelling known types, against marker-gene expression levels, and against the layer distribution the dissociated cells show whether two named types are electrophysiologically distinct is made TESTABLE rather than assumed: a two-component model, one component per type, is fitted against a single-component model of the two merged, and how much better the split describes the data is then measured as a log-likelihood ratio between the two models correspondence between the two classifications is found by spectral co-clustering of the two type sets, with agreement given a stated threshold - at least two thirds of a type's cells falling inside its co-cluster THE FINAL TYPES ARE EDITED CO-CLUSTERS, NOT CO-CLUSTERS: the poorly-agreeing types are removed first, and the remaining co-clusters are split further wherever the transcriptomic differences inside one are large - so the twenty met-types are the output of a procedure with two further editing steps applied AFTER the clustering, not of the clustering itself met-type t-type “inconsistent” cells Patch-seq recording technique transcriptomic type intrinsic electrophysiological features morphological features soma location sparse principal component analysis principal component analysis principal components analysis (PCA) likelihood ratio test log-likelihood ratio (LLR) bootstrap parametric boostrap statistical-significance random forest classifier cross-validation cross-validated discriminant analysis discriminability index (effect size) d′ statistic correlation the correlation between an individual cell’s axon histogram and the t-type average Kullback-Leibler divergence Kullback-Leibler (KL) divergence Jensen-Shannon divergence Jensen-Shannon (JS) divergence standard error of the mean mean (lines) ± SEM resampling / subsampling for cluster stability electrophysiology

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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
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
phenomenonphenomenonthe effect or regularity under study
sensesensesa distinct use of a term, quoted where the paper fixes it

The paper

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Every tag on this page

claim_relations 2 · claim_type 1 · concept_edges 2 · concepts 7 · content_tags 38 · controls 1 · limitations 8 · mechanisms 9 · method 1 · phenomenon 1 · senses 3

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 2 relations here carry that mark. The rest are the tagger’s reading of the sentence quoted beside them.

facettagfieldconf.whose words
claim_typeexistence
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claim_typethe paper's words
phenomenoncortical GABAergic interneuron cell types
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phenomenonthe paper's words
methodelectrophysiology
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methodthe paper's words
mechanismsmechanisms
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mechanisms[0]0.85the tagger's words
mechanismsmechanisms
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mechanisms[1]0.95the tagger's words
mechanismsmechanisms
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mechanisms[2]0.95the tagger's words
mechanismsmechanisms
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mechanisms[3]0.95the tagger's words
mechanismsmechanisms
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mechanisms[4]0.85the tagger's words
mechanismsmechanisms
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mechanisms[5]0.95the tagger's words
mechanismsmechanisms
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mechanisms[6]0.85the tagger's words
mechanismsmechanisms
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mechanisms[7]0.95the tagger's words
mechanismsmechanisms
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mechanisms[8]0.85the tagger's words
limitationsToo few morphological reconstructions exist for the Vip, Lamp5 and Sncg subclasses, so the number of met-types may change.
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what this limits: the met-type count for three named subclasses: WE DO NOT YET HAVE A SUFFICIENTLY LARGE NUMBER OF MORPHOLOGY RECONSTRUCTIONS FOR THE Vip, Lamp5 AND Sncg SUBCLASSES
limitations[0]the tagger's words
limitationsBrain-slice preparation artifacts cannot be ruled out as a source of the observed morphological differences.
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what this limits: the morphological differences the classification rests on: WE CANNOT RULE OUT THE POSSIBILITY THAT ARTIFACTS OF THE BRAIN SLICE PREPARATION CONTRIBUTE TO OR EXPLAIN OBSERVED MORPHOLOGICAL DIFFERENCES
limitations[1]the tagger's words
limitationsRestricting analysis to highly consistent mappings may impose discrete types on what is really continuous variation.
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what this limits: the discreteness of the types themselves: SOME OF THE AMBIGUITY IN TYPES COULD BE BIOLOGICAL RATHER THAN TECHNICAL, SUCH THAT FOCUSING OUR ANALYSIS THIS WAY MAY OVERLY-DISCRETIZE A LANDSCAPE WITH MORE CONTINUOUS VARIATION BETWEEN CELLS AND CELL TYPES
limitations[2]the tagger's words
limitationsThe field is stated to have no consensus number, or even definition, of neuronal cell types.
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what this limits: any count of neuronal cell types taken as settled: the authors state the field has not readily converged on a consensus number, or even definition, of neuronal cell types, and that efforts to determine one have been limited by well-documented challenges
limitations[3]1.0the tagger's words
limitationsTwo modalities counting the same area's interneuron types differ by more than a factor of two.
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what this limits: any number of GABAergic cell types quoted for mouse VISp: the transcriptomic estimate is 60 t-types and the morpho-electric estimate 26 me-types, and the authors state such discrepancies are not unique to VISp
limitations[4]1.0the tagger's words
limitationsA classical cell-type name has no absolute definition, and by the loose reading every met-type would qualify.
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what this limits: any classification of a neuron as a Martinotti cell: the authors state they are not aware of an absolute definition in terms of total amount of axon in L1, that it is generally described as significant, and that all the Sst met-types contain at least one cell that could be considered one
limitations[5]1.0the tagger's words
limitationsThe combined classifier's stated improvement is over the morphology arm, not the electrophysiology arm.
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what this limits: any claim that combining modalities improved t-type prediction here: electrophysiology alone gave 57%, morphology alone 41%, and the combination 57%
limitations[6]1.0the tagger's words
limitationsType frequencies differ between the two preparations despite the same transgenic driver lines.
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what this limits: any comparison of t-type proportions between Patch-seq and dissociated-cell data: the difference persisted despite using the same, relatively specific transgenic driver lines, and the authors state it may reflect gene expression differences in slice versus dissociated cell preparations
limitations[7]1.0the tagger's words
controlsthe reference cells split into an 80 per cent training set and a 20 per cent test set before the classifier was fitted
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eliminates: a cell-type accuracy earned on the cells the classifier was fitted to - the held-out fifth is the only part of the data that can report performance · outcome (stated by the tagger, no quotation): held
controls[0]0.85the tagger's words
conceptst-types
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also in: t-types
concepts[0]the paper's words
conceptsme-types
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also in: me-types
concepts[1]the paper's words
conceptsMartinotti cell
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concepts[2]the paper's words
conceptsmet-types
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also in: met-types
concepts[3]the paper's words
conceptsco-clusters
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also in: co-clusters
concepts[4]the paper's words
conceptsconsensus number
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concepts[5]the paper's words
conceptst-type classifier
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concepts[6]the paper's words
sensesa Martinotti cell - A NAMED TYPE WHOSE DEFINING QUANTITY HAS NO THRESHOLD: the quantity is total amount of axon in L1, the criterion on it is the word significant, the authors state they are not aware of an absolute definition, and all the Sst met-types contain at least one cell that could therefore be considered one
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senses[0]1.0the tagger's words
sensesa met-type - A CO-CLUSTER THAT WAS THEN EDITED: spectral co-clusters of t-types and me-types were the starting point, t-types with poorer agreement were removed, and co-clusters were split further where transcriptomic differences were large, so the twenty is the output of a procedure with two judgement steps rather than a count of found groups
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senses[1]1.0the tagger's words
sensesthe counted number of GABAergic cell types - MODALITY-RELATIVE: for one cortical area of one species it is 60 by transcriptomics and 26 by morpho-electric features, a difference of more than a factor of two, and the authors state other areas have likewise arrived at varying numbers
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senses[2]1.0the tagger's words
claim_relationsextends → Tasic et al. (2018/2016) transcriptomic taxonomy and Gouwens et al. (2019) morpho-electric types
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claim_relations[0]the tagger's words
claim_relationsbuilds-on → Tasic et al. (2018) dissociated-cell transcriptomic reference dataset
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claim_relations[1]the tagger's words
concept_edgest-types —contrasted-with→ me-types
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differs in: how many kinds each yields for one cortical area of one species: 60 against 26 · strength of the relation: 1
also in: t-types · me-types
concept_edges[0]the tagger's words
concept_edgesmet-types —operationalised-as→ co-clusters
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holds when: after t-types with poorer agreement were removed and co-clusters were split further where transcriptomic differences were large · strength of the relation: 1
concept_edges[1]the tagger's words
content_tagssparse principal component analysis
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content_tags.statistics[0]the tagger's words
content_tagsprincipal component analysis
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content_tags.statistics[1]the tagger's words
content_tagslikelihood ratio test
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content_tags.statistics[2]the tagger's words
content_tagsbootstrap
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also in: bootstrap
content_tags.statistics[3]the tagger's words
content_tagsstatistical-significance
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content_tags.statistics[4]the tagger's words
content_tagsrandom forest classifier
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content_tags.statistics[5]the tagger's words
content_tagscross-validation
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content_tags.statistics[6]the tagger's words
content_tagsdiscriminability index (effect size)
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about this quote: DAMAGED GLYPHS IN THIS QUOTE: (cid:48). These are raw PDF font glyph indices that leaked out in place of the characters they stand for - usually a mathematical operator. The quote is verbatim to the staged text and its anchor is sound; the STAGED TEXT is what is damaged. NOT repaired: the cid-to-character mapping is defined by the font embedded in that particular PDF, so guessing it would produce a clean and unverifiable quote. Repair needs the source PDF and is a re-staging job.
content_tags.statistics[7]the tagger's words
content_tagscorrelation
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also in: correlation
content_tags.statistics[8]the tagger's words
content_tagsKullback-Leibler divergence
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content_tags.statistics[9]the tagger's words
content_tagsJensen-Shannon divergence
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content_tags.statistics[10]the tagger's words
content_tagsstandard error of the mean
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content_tags.statistics[11]the tagger's words
content_tagsresampling / subsampling for cluster stability
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content_tags.statistics[12]the tagger's words
content_tagsThe combined data support at least twenty GABAergic interneuron met-types whose transcriptomic, electrophysiological and morphological properties agree.
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content_tags.findings[0]the tagger's words
content_tagsNine met-types were resolved within the Sst subclass.
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content_tags.findings[1]the tagger's words
content_tagsSst neurons respect laminar boundaries, and their dominant laminar target may distinguish them more reliably than the presence of axon in layer 1.
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content_tags.findings[2]the tagger's words
content_tagsMost transcriptomic types differ systematically from one another in their electrophysiological properties.
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content_tags.findings[3]the tagger's words
content_tagsAdding morphological to electrophysiological features raised t-type classifier accuracy to 57%.
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content_tags.findings[4]the tagger's words
content_tagsA neuron's specific t-type is frequently hard to predict from its morphological and/or physiological features.
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content_tags.findings[5]the tagger's words
content_tagsSomata of many GABAergic t-types occupy specific laminar or sublaminar positions, giving an anatomical correlate to purely transcriptomic groupings.
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content_tags.findings[6]the tagger's words
content_tagsIndividual cells' axon depth histograms correlate positively with their t-type average, indicating consistent innervation patterns within a type.
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content_tags.findings[7]the tagger's words
content_tagsmet-type
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also in: met-type
content_tags.definitions[0]the tagger's words
content_tagst-type
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also in: t-type
content_tags.definitions[1]the tagger's words
content_tags“inconsistent” cells
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content_tags.definitions[2]the tagger's words
content_tagsPatch-seq recording technique
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content_tags.definitions[3]the tagger's words
content_tagstranscriptomic type
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content_tags.variables[0]the tagger's words
content_tagsintrinsic electrophysiological features
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content_tags.variables[1]the tagger's words
content_tagsmorphological features
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content_tags.variables[2]the tagger's words
content_tagssoma location
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also in: soma location
content_tags.variables[3]the tagger's words
content_tags3,708 — cortical GABAergic interneurons whose transcriptomic and electrophysiological data passed quality control; 350 of them were morphologically reconstructed
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content_tags.quantities[0]the tagger's words
content_tags3,417 of the 3,708 — cells mapped to one or more reference transcriptomic types with better than 70% confidence
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content_tags.quantities[1]the tagger's words
content_tags>90% — accuracy of the random forest classifier predicting transcriptomic subclass from electrophysiological features
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content_tags.quantities[2]the tagger's words
content_tags57% — accuracy of the classifier predicting individual t-type from electrophysiological features
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content_tags.quantities[3]the tagger's words
content_tags41% — accuracy of the classifier predicting t-type from morphological features alone
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content_tags.quantities[4]the tagger's words
content_tags57% — accuracy of the classifier when electrophysiological and morphological features were combined - no better than electrophysiology alone
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content_tags.quantities[5]the tagger's words
content_tags83% — share of the authors' Patch-seq recordings made in primary visual cortex, the remainder in surrounding higher visual areas
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content_tags.quantities[6]the tagger's words
content_tags(60) and (26) — previously estimated numbers of VISp GABAergic transcriptomic types versus morpho-electric types, the discrepancy this study set out to resolve
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content_tags.quantities[7]the tagger's words
content_tagstwenty — met-types produced by the co-clustering plus transcriptomic-splitting procedure
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content_tags.quantities[8]the tagger's words

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