Inverted central auditory hierarchies for encoding local intervals and global temporal patterns

Asokan, Williamson, Hancock, Polley · Current Biology · 2021 · neuroscience · 10.1016/j.cub.2021.01.076 · record Asokan2021-inverted-central-auditory-hierarchies-for-en
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. Citations are numeric throughout, so claim relations targets are described by content rather than author name; each recorded relation rests on an explicit positioning sentence, not a bare citation. The 'extends' relation to the SSA literature is the paper's own four-point contrast (no high/low probability stimuli, longer integration window, absent subcortically, and carried by spike timing rather than rate) - see also 'The context sensitivity we report here is completely absent in our sample of IC units and is weakly expressed in MGB neurons.' claim type is 'existence' (an emergent cortical sensitivity to global rhythm exists), though the finding that regularity is carried by spike arrangement rather than rate ('Shifts in stimulus regularity were not represented by changes in A1 spike rates, but rather in how the spikes were arranged in time.') is mechanism-shaped. Replication status 'untested' applies to the novel cortical-regularity claim; the paper does internally reproduce the long-known temporal-fidelity gradient, which is recorded as a 'replicates' relation instead. 2026-08-13 schema-0.3 pass: 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.
1 quotation on this page contains 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
principal component analysis 5 fields · cross-validation 3 fields · support vector machine 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 37 concept tags on this paper, none is 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.
neural timescale decay time constant decay constant shorter decay constants mean firing rate SSA spike rate adaptation contrast gain control context sensitivity IC MGB A1 IC-MGB-A1 hierarchy ascending auditory pathway regular spiking fast spiking putative parvalbumin-expressing interneuron trough to peak interval threshold of interval decoding neural timescale asymmetry index first spike latency stimulus regularity inter-burst intervals repeated across cycles rhythmic patterns predictable rhythm slow neural timescales interfere with precise temporal coding cortical advantage temporal fidelity forward suppression tonotopic gradient best frequency gradient template matching support vector machine ensemble spiking current source density predictive sensory processing Dendrite-targeting cortical GABAergic interneurons dampen pyramidal-neuron spike decay when stimulus timing becomes predictable Corticothalamic feedback recruits thalamic reticular nucleus inhibition, which dampens feedforward thalamocortical drive during rhythms Cortex switches from a recurrent deliberative mode to a pass-through mode once incoming sound matches internal predictive models temporal integration spike timing rhythm decoder accuracy threshold spike waveform classification hierarchical stage cycle size decoder threshold random-random stimulus stimulus context spike decay time constant sound-evoked firing rate Kruskal-Wallis test Kruskal-Wallis ANOVA Mixed design ANOVA Two-way repeated measures ANOVAs t-test paired t-test effect size Effect sizes were estimated with Cohen’s d normality test Lilliefors test multiple-comparison correction Bonferroni correction principal component analysis support vector machine classification a SVM with a linear kernel cross-validation Cliff's delta one-sample t-test Cohen's d two-way repeated measures ANOVA principal components analysis electrophysiology

Legend

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
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

The full text is not reproduced here. This article is not cleared for redistribution, so the page carries the tag layer only. Its evidence sentences are withheld; the grounding status remains with each tag, and the article itself is at https://doi.org/10.1016/j.cub.2021.01.076. The reading view exists for the papers whose licence permits it.

Every tag on this page

alternatives 3 · claim_relations 10 · claim_type 1 · concept_edges 16 · content_tags 65 · contribution 1 · controls 2 · limitations 7 · mechanisms 9 · method 1 · object_of_study 1 · phenomenon 1 · research_question 1 · senses 6 · transfers 4

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

facettagfieldconf.whose words
object_of_studyhow the timescale of neural activity changes from midbrain to cortex, and what each stage can therefore encode
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object_of_studythe paper's words
research_questionwhether the slow timescales that cost the cortex temporal precision are what let it encode global patterns that subcortical stations cannot
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research_questionthe paper's words
contributionshows the auditory hierarchy is inverted between two encoding jobs - fidelity for local intervals falls from IC to A1 while sensitivity to global rhythm appears only in A1 - and that the cortical signal is carried by spike timing with no change in firing rate
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contributionthe paper's words
claim_typeexistence
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claim_typethe paper's words
phenomenonhierarchical temporal coding in the central auditory pathway
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phenomenonthe paper's words
methodelectrophysiology
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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.
status: the paper's own words: may reflect
mechanisms[2]the tagger's words
mechanismsthe cortex reads regularity by compressing its own spike decay constant, not by changing how much it fires
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mechanisms[3]1.0the tagger's words
mechanismsthe timescale that changes is about 40x faster than the stimulus feature driving it, so the sensitivity must be inherited from other circuits rather than computed by the unit itself
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mechanisms[4]0.8the tagger's words
mechanismscandidate source: dendrite-targeting somatostatin or NDNF interneurons that dampen recurrent excitation and track slow state variables
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mechanisms[5]0.5the tagger's words
mechanismsalternative source: corticothalamic feedback damping thalamocortical input through the thalamic reticular nucleus, suggested by the weaker MGB effect
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mechanisms[6]0.5the tagger's words
mechanismsstimulus-specific adaptation, the nearest neighbouring phenomenon, works instead by synaptic fatigue for standard inputs while deviant inputs stay unadapted
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mechanisms[7]0.9the tagger's words
mechanismsperipheral speed is a design constraint: the morphologies and synapses that give the early stages sub-millisecond precision are what make them unsuited to slow structure
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mechanisms[8]0.8the tagger's words
limitationsCortical sensitivity to regularity did not extend to longer or more complex cycles, so the integration window demonstrated is bounded at roughly 0.8-1.6 s.
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what this limits: the regularity result, with its ceiling measured: SINGLE UNIT SENSITIVITY TO REGULARITY IS LIMITED TO STIMULUS TIMESCALES ON THE ORDER OF 4-8 REPEATING ELEMENTS OR 0.8-1.6s
limitations[0]the tagger's words
limitationsOnly A1 in passively listening mice was studied; higher-order fields and behaviourally engaged listening remain to be tested.
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what this limits: the generality beyond A1 and beyond passive listening: it would be important to test the CANDIDATE HIGHER-ORDER AREAS ... PARTICULARLY WHEN MICE ARE BEHAVIORALLY ENGAGED
limitations[1]the tagger's words
limitationsThe circuit that actually confers sensitivity to the ~800 ms regularity is not identified; candidate local and long-range mechanisms are only conjectured.
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what this limits: any mechanistic reading: the timescale dynamics ARE LIKELY THE PRODUCT OF OTHER LOCAL OR LONG-RANGE CIRCUITS THAT RESPOND MORE DIRECTLY TO THE CHANGE IN PREDICTABILITY - the circuit that confers the sensitivity is not identified
limitations[2]the tagger's words
limitationsthe cortical sensitivity has a measured ceiling - it holds for cycles of four to eight intervals and is gone at twelve
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what this limits: the same scope as limitations[0] - the effect holds for cycles of four to eight and is gone beyond
limitations[3]1.0the tagger's words
limitationspassive listening only; whether engagement in a task extends the integration window is untested
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duplicate of: limitations[1] · what this limits: the same scope as limitations[1], for engagement specifically - only passive listening was tested
limitations[4]0.9the tagger's words
limitationsonly A1 was recorded, so the higher-order fields where longer regularities might be encoded were not sampled
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what this limits: the same scope as limitations[1], for anatomy specifically - only A1 was recorded, so the higher-order fields where longer regularities might be encoded were not sampled
limitations[5]0.9the tagger's words
limitationscell class is inferred from spike waveform width, not from a molecular marker
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what this limits: every result reported by cell class: REGULAR and FAST SPIKING are assigned by THE TROUGH TO PEAK INTERVAL ... EXCEEDING 0.6ms, a waveform proxy rather than a molecular identification
limitations[6]1.0the tagger's words
transfersthe neural-timescale metric (decay constant of an exponential fit to the spike-count autocorrelation), developed for hierarchies of visual cortical areas and here applied to the auditory pathway
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transfers[0]the tagger's words
transfersthe autocorrelation-decay measure of neural timescale, and the expectation that it lengthens up a hierarchy
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transfers[1]1.0the tagger's words
transfersthe paradigm of contrasting repeating with random acoustic patterns
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transfers[2]0.9the tagger's words
transfersthe binary support vector machine, used here as a readout of ensemble state
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transfers[3]0.9the tagger's words
controlsa random-random stimulus, keeping the stimulus random for all 50 post-baseline cycles instead of switching from rhythmic to random (Figure S4 - three sentences describe this one control, recorded once)
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eliminates: the ordinal arrangement of random-following-rhythmic, rather than the change in regularity, as the cause of the spike-patterning differences · outcome (stated by the tagger, no quotation): held
controls[0]0.95the tagger's words
controlsrepeating the whole analysis on cycle-order-shuffled data, for every recording in all three brain regions - the exclusion is carried by the word shuffling rather than spelled out, hence the lower weight
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eliminates: structure that would appear in the analysis regardless of the true ordering of cycles · outcome (stated by the tagger, no quotation): held
controls[1]0.75the tagger's words
sensesneural timescale = the decay constant of a single unit's spike-count autocorrelation, about 20ms in A1 - NOT the window over which the unit integrates, which is 800ms; the paper states the 40x gap itself
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senses[0]1.0the tagger's words
sensesregular, sense 1 = a property of the stimulus sequence (intervals repeating in a fixed order), the paper's independent variable
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senses[1]1.0the tagger's words
sensesregular, sense 2 = a waveform class of neuron (trough-to-peak > 0.6ms, putative pyramidal); same word, unrelated referent, both used throughout
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senses[2]1.0the tagger's words
sensescontext = the global statistics of the stimulus sequence (random vs rhythmic), not behavioural or task context
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senses[3]0.9the tagger's words
sensestonotopy here is an instrument, not an object: the frequency gradient and its reversal are used to certify that the probe is in A1
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senses[4]1.0the tagger's words
senseshierarchy = the ascending anatomical pathway IC to MGB to A1, ordered by synaptic distance from the cochlea
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senses[5]0.9the 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: simultaneous three-probe extracellular single-unit recording from IC, MGB and A1 of awake head-fixed mice, with template-matching interval decoding and an SVM on principal components of ensemble spiking
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a second reading DIFFERING from the recorded value. Recorded: electrophysiology — note: a second reading, verbatim-verified, disagreeing with the value on the record. Not applied - a person decides.
alternatives.methodthe tagger's words
alternativesphenomenon: emergent cortical sensitivity to the regularity of a sequence of intervals, expressed as compression of the spike decay constant
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a second reading DIFFERING from the recorded value. Recorded: hierarchical temporal coding in the central auditory pathway — note: a second reading, verbatim-verified, disagreeing with the value on the record. Not applied - a person decides.
alternatives.phenomenonthe tagger's words
claim_relationsreplicates → previously documented progressive loss of temporal fidelity along the ascending auditory pathway (reviews cited as refs 1, 2, 4)
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claim_relations[0]the tagger's words
claim_relationsextends → prior animal work on stimulus-specific adaptation (SSA) and contrast gain control (refs 17, 20-26)
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claim_relations[1]the tagger's words
claim_relationsbuilds-on → the neural-timescale measure (autocorrelation decay constant) established across visual cortical hierarchies (refs 6, 7)
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claim_relations[2]the tagger's words
claim_relationsbuilds-on → human work on cortical activity and perceptual awareness of complex repeating acoustic patterns (refs 15, 16)
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claim_relations[3]the tagger's words
claim_relationsdistinguishes-from → stimulus-specific adaptation and contrast gain control
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claim_relations[4]1.0the tagger's words
claim_relationsdistinguishes-from → SSA and contrast gain control, on anatomical distribution
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differs in: THE AXIS IS ANATOMICAL DISTRIBUTION. 'while SSA, contrast gain control or other neural signatures of stimulus context changes are robustly expressed in the A1, Quotation withheld.' The known adaptation phenomena appear at every level; this one does not - so a cortical result that resembles them is distinguished by WHERE ELSE IT CAN BE FOUND rather than by what it looks like.
claim_relations[5]1.0the tagger's words
claim_relationsdistinguishes-from → rate-based accounts of context-dependent adaptation
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differs in: THE AXIS IS WHAT CARRIES THE SIGNAL - RATE OR TEMPORAL PATTERN. 'Quotation withheld.' The existing accounts are not denied their data; they are denied coverage of a signal their measure cannot see.
claim_relations[6]1.0the tagger's words
claim_relationsextends → human work on cortical responses to repeating acoustic patterns
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claim_relations[7]0.9the tagger's words
claim_relationsbuilds-on → visual-cortex measurements of neural timescale by autocorrelation decay
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claim_relations[8]1.0the tagger's words
claim_relationsconfirms → prior reports of declining temporal fidelity along the ascending auditory pathway
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claim_relations[9]1.0the tagger's words
concept_edgesneural timescale —operationalised-as→ decay time constant
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strength of the relation: 1 · note: imported from visual-cortex hierarchy work; the quote names the source field as well as the measure
concept_edges[0]1.0the tagger's words
concept_edgesstimulus regularity —operationalised-as→ inter-burst intervals repeated across cycles
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strength of the relation: 1 Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but the span writes 'regular contexts' / intervals that 'repeated across cycles', not 'stimulus regularity'.
concept_edges[1]1.0the tagger's words
concept_edgesA1 —operationalised-as→ best frequency gradient
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strength of the relation: 0.9 · note: tonotopy as the criterion for having reached A1 - the same word is the object of study elsewhere in this corpus
concept_edges[2]1.0the tagger's words
concept_edgesregular spiking —operationalised-as→ trough to peak interval
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strength of the relation: 1 · note: cut at 0.6ms; fast spiking is the same measure on the other side of it
concept_edges[3]1.0the tagger's words
concept_edgesfast spiking —same-as→ putative parvalbumin-expressing interneuron
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strength of the relation: 0.6 — the record marks this weak · note: an identity asserted by apposition and hedged by 'putative'; the evidence for it is waveform width, not a marker
concept_edges[4]0.7the tagger's words
concept_edgescontext sensitivity —distinct-from→ SSA
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strength of the relation: 1 · note: discriminated by anatomical distribution: SSA is expressed in IC and MGB too, this is absent in IC
concept_edges[5]1.0the tagger's words
concept_edgescontext sensitivity —distinct-from→ contrast gain control
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strength of the relation: 1 · note: same demarcation paragraph; its fourth point, rate versus timing, is carried in claim relations
concept_edges[6]1.0the tagger's words
concept_edgesSSA —is-a→ spike rate adaptation
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strength of the relation: 1
concept_edges[7]1.0the tagger's words
concept_edgesdecay constant —distinct-from→ mean firing rate
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strength of the relation: 1 · note: dissociated empirically in the same units and the same 100ms window, not merely conceptually
concept_edges[8]1.0the tagger's words
concept_edgesA1 —contrasted-with→ IC
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strength of the relation: 1 · note: on rhythm classification the cortex succeeds and the midbrain fails - the reverse of the interval-decoding ordering
also in: A1 · IC
concept_edges[9]1.0the tagger's words
concept_edgesA1 —contrasted-with→ MGB
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strength of the relation: 1
also in: A1 · MGB
concept_edges[10]1.0the tagger's words
concept_edgesslow neural timescales —causes→ interfere with precise temporal coding
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strength of the relation: 0.9 · note: the cost. Same property and same sentence as the edge below, opposite valence - the sign lives in the target, not in a note Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but slow timescales 'MAY interfere' with precise temporal coding; causes is hedged.
concept_edges[11]0.9the tagger's words
concept_edgesslow neural timescales —causes→ cortical advantage
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strength of the relation: 0.9 · note: the capability: an advantage over subcortical stations for encoding slowly evolving features Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but the sluggish processing 'COULD SUGGEST' a cortical advantage; causes is hedged.
concept_edges[12]0.9the tagger's words
concept_edgesrhythmic patterns —causes→ shorter decay constants
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strength of the relation: 1 · note: the headline effect, stated in the same sentence that rules out any change in mean firing rate
concept_edges[13]1.0the tagger's words
concept_edgesA1 —part-of→ IC-MGB-A1 hierarchy
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strength of the relation: 1
concept_edges[14]0.9the tagger's words
concept_edgesIC —part-of→ ascending auditory pathway
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strength of the relation: 1
concept_edges[15]0.9the tagger's words
content_tagsKruskal-Wallis test
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content_tags.statistics[0]the tagger's words
content_tagsANOVA
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also in: ANOVA
content_tags.statistics[1]the tagger's words
content_tagsANOVA
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also in: ANOVA
content_tags.statistics[2]the tagger's words
content_tagst-test
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also in: t-test
content_tags.statistics[3]the tagger's words
content_tagst-test
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also in: t-test
content_tags.statistics[4]the tagger's words
content_tagseffect size
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also in: effect size
content_tags.statistics[5]the tagger's words
content_tagsnormality test
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content_tags.statistics[6]the tagger's words
content_tagsmultiple-comparison correction
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content_tags.statistics[7]the tagger's words
content_tagsprincipal component analysis
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content_tags.statistics[8]the tagger's words
content_tagssupport vector machine classification
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content_tags.statistics[9]the tagger's words
content_tagscross-validation
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content_tags.statistics[10]the tagger's words
content_tagsKruskal-Wallis
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content_tags.statistics[11]1.0the tagger's words
content_tagsCliff's delta
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also in: Cliff's delta
content_tags.statistics[12]1.0the tagger's words
content_tagsBonferroni correction
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content_tags.statistics[13]1.0the tagger's words
content_tagsone-sample t-test
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content_tags.statistics[14]1.0the tagger's words
content_tagsCohen's d
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also in: Cohen's d
content_tags.statistics[15]1.0the tagger's words
content_tagstwo-way repeated measures ANOVA
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content_tags.statistics[16]1.0the tagger's words
content_tagsprincipal components analysis
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content_tags.statistics[17]1.0the tagger's words
content_tagssupport vector machine
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content_tags.statistics[18]1.0the tagger's words
content_tagsNeural timescales, measured as the autocorrelation decay constant, roughly double from auditory midbrain to cortex.
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content_tags.findings[0]the tagger's words
content_tagsAccuracy of decoding the interval between two noise bursts falls progressively from midbrain to thalamus to cortex.
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content_tags.findings[1]the tagger's words
content_tagsOnly cortical ensemble activity, not thalamic or midbrain activity, allowed a classifier to tell rhythmic from random interval sequences.
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content_tags.findings[2]the tagger's words
content_tagsRhythmic context shortened neural timescales strongly and reliably in A1, weakly in MGB, and not at all in IC.
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content_tags.findings[3]the tagger's words
content_tagsRegularity was encoded by the arrangement of spikes in time rather than by any change in mean firing rate.
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content_tags.findings[4]the tagger's words
content_tagsCortical sensitivity to regularity was bounded, disappearing for rhythmic cycles longer than roughly 4 to 8 repeating intervals.
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content_tags.findings[5]the tagger's words
content_tagsThe timescale compression occurred in putative pyramidal (regular-spiking) neurons across layers but not in putative parvalbumin interneurons.
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content_tags.findings[6]the tagger's words
content_tagsA random-random control sequence produced chance-level classification and no timescale change, ruling out simple stimulus-order effects.
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content_tags.findings[7]the tagger's words
content_tagsneural timescales roughly double from midbrain to cortex
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content_tags.findings[8]1.0the tagger's words
content_tagsthe median interval-decoding threshold rises from 1.4ms in IC to 16ms in MGB to 64ms in A1
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content_tags.findings[9]1.0the tagger's words
content_tagsensemble spiking distinguishes rhythmic from random sequences in A1 but not in MGB or IC
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content_tags.findings[10]1.0the tagger's words
content_tagsthe discriminating signal is spike arrangement in time; mean firing rate does not change
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content_tags.findings[11]1.0the tagger's words
content_tagsin A1, decay constants were slightly reduced for rhythms of eight repeating intervals and did not differ between random and rhythmic epochs with twelve
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content_tags.findings[12]1.0the tagger's words
content_tagsthe timescale compression appears in regular-spiking units across all A1 layers and not at all in fast-spiking units
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content_tags.findings[13]1.0the tagger's words
content_tagsunder regular input the cortex comes to resemble the thalamus on the two timing measures
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content_tags.findings[14]0.9the tagger's words
content_tagsa random-to-random control produced near-chance classification, ruling out the ordinal position of the epoch
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content_tags.findings[15]1.0the tagger's words
content_tagsdecoder accuracy threshold
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content_tags.definitions[1]the tagger's words
content_tagsneural timescale asymmetry index
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content_tags.definitions[2]the tagger's words
content_tagsspike waveform classification
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content_tags.definitions[3]the tagger's words
content_tagsSSA
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also in: SSA
content_tags.definitions[4]1.0the tagger's words
content_tagsneural timescale
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content_tags.definitions[5]1.0the tagger's words
content_tagsneural timescale asymmetry index
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content_tags.definitions[6]0.85the tagger's words
content_tagstemplate matching
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content_tags.definitions[7]1.0the tagger's words
content_tagsregular spiking
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content_tags.definitions[8]1.0the tagger's words
content_tagshierarchical stage
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content_tags.variables[0]the tagger's words
content_tagscycle size
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also in: cycle size
content_tags.variables[2]the tagger's words
content_tagsneural timescale
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content_tags.variables[3]the tagger's words
content_tagsdecoder threshold
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content_tags.variables[4]the tagger's words
content_tagsmean firing rate
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content_tags.variables[5]the tagger's words
content_tagsrandom-random stimulus
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content_tags.variables[7]the tagger's words
content_tagsstimulus context
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content_tags.variables[8]1.0the tagger's words
content_tagsspike decay time constant
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content_tags.variables[11]1.0the tagger's words
content_tagssound-evoked firing rate
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content_tags.variables[12]1.0the tagger's words
content_tags1.4ms, 16ms, 64ms — median interval-decoding threshold in inferior colliculus, medial geniculate body and primary auditory cortex respectively
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content_tags.quantities[0]the tagger's words
content_tags0.8s — duration of one complete stimulus cycle, the minimum integration window needed to detect regularity
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content_tags.quantities[1]the tagger's words
content_tags40x — how much slower the stimulus feature (800ms rhythm) is than the cortical spiking timescale (20ms) it modulates
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content_tags.quantities[2]the tagger's words
content_tagsF = 20.95, p = 6x10 −9 — main effect of brain structure on interval classification accuracy in the mixed-design ANOVA
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content_tags.quantities[3]the tagger's words
content_tags5/164 — number of mice and single units contributing A1 timescale measurements in the random versus rhythmic comparison
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content_tags.quantities[4]the tagger's words
content_tags1.4ms, 16ms, 64ms — median interval-decoding threshold in IC, MGB and A1
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content_tags.quantities[5]1.0the tagger's words
content_tags0.8 - 1.6s — the span of stimulus regularity A1 single units are sensitive to
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content_tags.quantities[6]1.0the tagger's words
content_tagsapproximately 40x — how much slower the driving stimulus feature is than the timescale that reports it (800ms vs 20ms)
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content_tags.quantities[7]1.0the tagger's words
content_tags0.6ms — trough-to-peak cut between regular- and fast-spiking units
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content_tags.quantities[8]1.0the tagger's words
content_tags200ms — mean inter-burst interval, with no interval below 100ms so that forward suppression cannot contribute
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content_tags.quantities[9]1.0the tagger's words
content_tags20 ms, 70 dB SPL, 1-64 kHz — duration, level and bandwidth of the frozen noise burst used throughout
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content_tags.quantities[10]1.0the tagger's words
content_tagsless than 5% — permitted refractory-period violations for a cluster to count as a single unit
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content_tags.quantities[11]1.0the tagger's words
content_tags6-8 weeks — age of the C57BL6 mice at recording
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content_tags.quantities[12]1.0the tagger's words

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