Hippocampal "time cells": time versus path integration — TEI-tagged view

Kraus, Robinson, White, Eichenbaum, Hasselmo · 2013 · neuroscience · doi:10.1016/j.neuron.2013.04.015 · full text at the source · TEI xml · tagged edition · index · concepts · authors
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. Claim type coded as 'existence' because the headline result is the demonstrated existence of two dissociable cell populations (time-preferring and distance-preferring); the paper's argument against pure path-integration accounts is captured as a claim_relation rather than as a 'critique' claim_type. The paper is simultaneously a partial replication of Pastalkova et al. (2008) on one point and a contradiction of it on another — both are recorded. Replication status is 'untested' because the paper's own novel time-vs-distance dissociation is not reported as having been independently retested. 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.
Other fields define these differently the same word, defined another way in another discipline
model 4 fields · time 4 fields · behavior 4 fields · episodic memory 3 fields · GLM 3 fields · standard deviation 3 fields · and 4 more →
Tags on this paper every tag the record carries, whether or not the words occur in the text below — a number is how many papers in the corpus carry that tag; a tag with no number is unique to this paper
time4 distance5 location5 hippocampal6 neuron13 treadmill3 speed2 firing4 place cell6 path integration2 time cell2 GLM5 model22 tuning curve4 deviance2 covariate spatial4 episodic memory15 theta15 interneuron24 clamp behavior19 task13 direction3 assumption2 field width self-motion network dynamics ANOVA114 electrophysiology110

Our tag layer for this paper

Cross-disciplinary analysis
content-tags & facets: phenomenon · claim-type · cross-domain-transfer · mechanism · claim-relation · replication-status · limitation — grounded in the full text
phenomenonhippocampal time cells— “Recent studies have reported the existence of hippocampal “time cells,” neurons that fire at particular moments during periods when behavior and location are relatively constant.”
claim-typeexistence— “These results demonstrate the existence of both hippocampal cells that more accurately encode the time the rat has spent on the treadmill and hippocampal cells that more accurately encode the distance the rat has run on the treadmill.”
method — evidence— “Here, we distinguished influences of location, time, and distance by recording from multiple hippocampal neurons as rats ran continuously in place at different speeds on a treadmill placed in the stem of a figure-eight maze ( Figure 1 ).”
object of study — evidence— “In experiments where time cells have been observed, the animals either run continuously in place (in a running wheel) ( Pastalkova et al., 2008 ) or can move on a small platform ( Gill et al., 2011 ) or in a chamber ( MacDonald et al., 2011 ), allowing movement to play a substantial role in accounting for variations in firing rate ( Hasselmo…
research question — evidence— “Indeed, several theoretical conceptions have proposed that path integration is the primary function of hippocampal networks ( Etienne and Jeffery, 2004 ; McNaughton et al., 1991 , 1996 , 2006 ; O’Keefe and Burgess, 2005 ; Samsonovich and McNaughton, 1997 ). To fully understand the extent to which time and distance, as well as location, govern…
contribution — evidence— “Our strategy in distinguishing behavior, location, time, and distance was to “clamp” the behavior and location of the animal on the maze, and vary the treadmill speed to decouple the distance the rat traveled from the time spent on the treadmill. Multiple analyses showed that the activity of most hippocampal neurons that were active when the…
transferfrom spatial navigation research: Muller's random-foraging strategy of clamping behavior and randomising an irrelevant variable, reused with speed in place of direction— “In 1987, Muller and colleagues introduced the “random foraging” task, in which rats search continuously in all directions and locations to find food scattered throughout their environment ( Muller et al., 1987 ). Their aim was to “clamp” behavior (as foraging) and vary direction randomly to determine whether a spatial signal would emerge in…transfers[0]
transferfrom statistical modelling: nested-model deviance testing, used to ask what each covariate class adds rather than whether a fit is good— “To simultaneously and quantitatively examine the extent to which each neuron was influenced by location, time, and distance, we fit the spiking of each neuron to a generalized linear model (GLM) that included treadmill time, treadmill distance, spatial position (x and y room coordinates), treadmill speed, and spike history as covariates (see…transfers[1]
transferfrom memory theory: the requirement that episodic memory be temporally organised, which is what makes a time-based template worth looking for— “However, other neurons, and many of the same neurons that were active on the treadmill, had place fields elsewhere on the maze (see Movie S1 and Figure S3 ), indicating that during other components of the task, where locations on the maze were important to task success, space was a strong influence over firing patterns of even the same…transfers[2]
transferfrom exercise physiology apparatus: a commercial treadmill, set into a maze specifically to hold place constant while motion continues— “During treadmill running, the rats’ heads were consistently facing forward, and 75% of the time spent on the treadmill could be accounted for by an area with a radius of approximately 3.3 cm (average area: 35 cm 2 ; standard deviation: 15.9 cm 2 ; range: 12 to 59 cm 2 ). This indicates that the location of the rats’ heads were generally…transfers[3]
mechanismRepeating sequences of transiently active hippocampal cells act as a time-based template onto which episodic memories are written and from which they are later read out, disambiguating memories that share a location— “This sequential firing could underlie the ability of the hippocampus to encode temporal aspects of episodic memory, by serving as a time-based template upon which new memories are stored and later recalled.”mechanisms[0]
mechanismDistance-coding cells must be reading self-motion (idiothetic) cues generated by the moving belt, so their firing is driven by sensed movement rather than purely by internal network dynamics— “Also, the presence of cells that signal distance indicates that these neurons are not driven entirely by network dynamics without the influence of either idiothetic or allothetic cues, as suggested by Pastalkova et al. (2008) (see also Itskov et al., 2011 ), as the neurons must be responding to the treadmill speed, or self-motion cues…mechanisms[1]
mechanismthe spiking of each neuron is fit to a generalized linear model including treadmill time, treadmill distance, spatial position, treadmill speed and spike history as covariates, and each nested model removes one or more categories of covariates— “To simultaneously and quantitatively examine the extent to which each neuron was influenced by location, time, and distance, we fit the spiking of each neuron to a generalized linear model (GLM) that included treadmill time, treadmill distance, spatial position (x and y room coordinates), treadmill speed, and spike history as covariates (see…mechanisms[2]
mechanismand the distance cells must be reading treadmill speed or the self-motion cues it produces, which is what rules out pure internal network dynamics— “Also, the presence of cells that signal distance indicates that these neurons are not driven entirely by network dynamics without the influence of either idiothetic or allothetic cues, as suggested by Pastalkova et al. (2008) (see also Itskov et al., 2011 ), as the neurons must be responding to the treadmill speed, or self-motion cues…mechanisms[3]
mechanismwhile the existence of time-only cells rules out pure path integration, so the hippocampus is holding both dimensions at once— “In addition, the observation of cells whose activity was significantly influenced by only time indicates that these neurons are also not exclusively driven by path integration ( Etienne and Jeffery, 2004 ; McNaughton et al., 1996 , 2006 ). Rather, in the present study where both of these dimensions are prominent, our results show that the…mechanisms[4]
mechanismwith distance encoded even though there are no visual cues of movement to read it from— “The observation of distance coding in this task indicates that hippocampal neurons can integrate the length of a path even in the absence of visual cues usually associated with movement through space.”mechanisms[5]
replicates Pastalkova et al. (2008)— “These results are similar to those found by Pastalkova et al. (2008) and show that significantly more neurons were active on the treadmill than would be expected if they were simply hippocampal place cells with place fields on the treadmill.”claim_relations[0]
contradicts Pastalkova et al. (2008) — the proposal that treadmill-period firing is driven purely by internal network dynamics without idiothetic or allothetic cues— “Also, the presence of cells that signal distance indicates that these neurons are not driven entirely by network dynamics without the influence of either idiothetic or allothetic cues, as suggested by Pastalkova et al. (2008) (see also Itskov et al., 2011 ), as the neurons must be responding to the treadmill speed, or self-motion cues…claim_relations[1]
contradicts path-integration accounts of hippocampal function (Etienne and Jeffery, 2004; McNaughton et al., 1996, 2006)— “In addition, the observation of cells whose activity was significantly influenced by only time indicates that these neurons are also not exclusively driven by path integration ( Etienne and Jeffery, 2004 ; McNaughton et al., 1996 , 2006 ).”claim_relations[2]
contradicts the reading of hippocampal time cells as pure path integration over distance travelled— “In addition, the observation of cells whose activity was significantly influenced by only time indicates that these neurons are also not exclusively driven by path integration ( Etienne and Jeffery, 2004 ; McNaughton et al., 1996 , 2006 ). Rather, in the present study where both of these dimensions are prominent, our results show that the…claim_relations[3]
contradicts the account that delay-period sequences are driven entirely by internal network dynamics without idiothetic or allothetic cues— “Also, the presence of cells that signal distance indicates that these neurons…claim_relations[4]
critiques earlier time-cell studies, in which elapsed time was confounded with distance travelled
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claim_relations[5]
supports the view that hippocampal firing reflects whichever regularities the task makes relevant, rather than a fixed variable
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claim_relations[6]
reconciles time coding and distance coding, by showing both in the same theta cycles rather than as alternating regimes
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claim_relations[7]
predicts that the mixed-selectivity majority encode time and distance conjunctively at all times
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claim_relations[8]
senseTWO VARIABLES CONFOUNDED IN EVERY EARLIER STUDY OF THE PHENOMENON: when animals stayed in a constant location, ELAPSED TIME WAS CONFOUNDED WITH THE DISTANCE TRAVELLED - the number of steps taken - so the whole time-cell result was open to a path-integration reading
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senses[0]
sensewith the design answer stated as a verb - CLAMP behavior and location, and vary the treadmill speed so that time and distance come apart
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senses[1]
senseAND THE DECOUPLING IS DECLARED INCOMPLETE: it is IMPOSSIBLE to completely separate time and distance as long as the rat is still running - the effect of speed grows as the run proceeds
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senses[2]
senseWITH THE CONSEQUENCE FOR THE FIGURES ADMITTED: the most visually distinct examples typically fire AT THE END of the treadmill run, because that is where the method has power - the examples shown are selected by where the design can see
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senses[3]
senseand the residual correlation is carried into the conclusion - the paper CANNOT SAY WITH CERTAINTY whether mixed cells encode both dimensions or switch between them
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senses[4]
senseTHE CLAMP IS REPORTED AS PARTIAL, NOT AS ACHIEVED: clamping was LARGELY SUCCESSFUL, although minor variations persisted and were taken into account in the analyses
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senses[5]
senseA FIRING-RATE THRESHOLD DEFINES A CELL CLASS: units averaging more than 8 Hz over the session were considered putative interneurons and EXCLUDED - the category is a number, applied before any analysis
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senses[6]
senseTWO METHODS WITH DIFFERENT ASSUMPTIONS, MADE TO AGREE ON PURPOSE: a nonparametric spatial look-up table and a five-parameter GLM, correlating at r = 0.49 - so the conclusion DOES NOT DEPEND UPON THE ASSUMPTIONS MADE BY EITHER MODEL
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senses[7]
senseand the location account is tested by construction rather than asserted - if position sufficed, the predicted and observed temporal tuning curves would match; if the rat were stationary the prediction would be FLAT
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senses[8]
sensewith the outcome that nearly all neurons DID show spatial tuning, and location was still NOT SUFFICIENT to explain the firing
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senses[9]
senseTHE POPULATION SPLITS AT BOTH EXTREMES: 42 neurons informative for distance but not time, 30 for time but not distance, 284 for both and 44 for neither
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senses[10]
senseand the two extremes fire IN THE SAME THETA CYCLE, which is what argues for simultaneous representation rather than switching between them
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senses[11]
senseTHE CATEGORY IS RELATIVE TO THE TASK, NOT INTRINSIC TO THE CELL: neurons identified as time cells or distance cells on the treadmill OFTEN EXPRESSED STANDARD PLACE FIELDS elsewhere on the maze
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senses[12]
senseAND THE FIELD ALREADY KNEW THIS ABOUT DIRECTION: where direction was irrelevant to the task, firing was NOT influenced by direction; where it becomes meaningful, it is - hippocampal activity reflects the regularities THAT CHARACTERIZE THE TASK AT HAND
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senses[13]
sensewith the precedent named - Muller's 1987 random foraging task used the same move, CLAMPING behavior and randomising direction to see what signal would emerge
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senses[14]
senseTWO RIVAL ACCOUNTS ELIMINATED BY TWO SUBPOPULATIONS: distance cells rule out firing driven ENTIRELY by internal network dynamics, and time-only cells rule out pure path integration
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senses[15]
senseand the same neurons carry place fields elsewhere, so space dominates when the task makes location matter - the representation follows what the experiment makes relevant
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senses[16]
controla generalised linear model using ONLY spatial covariates, fitted to firing during treadmill running where distance and time are dissociated — held — rules out that time-cell firing on the treadmill is really place coding - that the apparent timing signal is explained by where the animal is
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controls[0]
controlresidual variation in location during treadmill running was checked against the transient firing — held — rules out that the transient firing at specific moments is driven by small residual differences in the animal's position rather than by elapsed time
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controls[1]
differs inPastalkova et al. (2008) — the proposal that treadmill-period firing is driven purely by internal network dynamics without idiothetic or allothetic cues — whether anything outside the network drives the firing: THE NEURONS MUST BE RESPONDING TO THE TREADMILL SPEED, OR SELF-MOTION CUES INFLUENCED BY THE TREADMILL SPEED, IN ORDER TO ENCODE DISTANCE - against being DRIVEN ENTIRELY BY NETWORK DYNAMICS WITHOUT THE INFLUENCE OF EITHER IDIOTHETIC OR ALLOTHETIC CUES
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claim_relations[1]
differs inpath-integration accounts of hippocampal function (Etienne and Jeffery, 2004; McNaughton et al., 1996, 2006) — which variable drives the cell: CELLS WHOSE ACTIVITY WAS SIGNIFICANTLY INFLUENCED BY ONLY TIME INDICATES THAT THESE NEURONS ARE ALSO NOT EXCLUSIVELY DRIVEN BY PATH INTEGRATION
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claim_relations[2]
differs inthe reading of hippocampal time cells as pure path integration over distance travelled — whether it is one variable or both: OUR RESULTS SHOW THAT THE HIPPOCAMPUS REPRESENTS BOTH THE DISTANCE TRAVELED AND TIME, where path integration predicts distance alone
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claim_relations[3]
differs inthe account that delay-period sequences are driven entirely by internal network dynamics without idiothetic or allothetic cues — the same parameter as item 1 - the presence of self-motion cues: THE NEURONS MUST BE RESPONDING TO THE TREADMILL SPEED, OR SELF-MOTION CUES INFLUENCED BY THE TREADMILL SPEED, IN ORDER TO ENCODE DISTANCE
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claim_relations[4]
differs inearlier time-cell studies, in which elapsed time was confounded with distance travelled — whether time and distance were separable at all in the earlier designs: THE ANIMALS EITHER RUN CONTINUOUSLY IN PLACE (IN A RUNNING WHEEL) OR CAN MOVE ON A SMALL PLATFORM OR IN A CHAMBER, ALLOWING MOVEMENT TO PLAY A SUBSTANTIAL ROLE IN ACCOUNTING FOR VARIATIONS IN FIRING RATE
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claim_relations[5]
differs intime coding and distance coding, by showing both in the same theta cycles rather than as alternating regimes — concurrent against switching representations: WHETHER TIME AND DISTANCE WERE BEING REPRESENTED CONCURRENTLY OR WHETHER THE HIPPOCAMPUS WAS SWITCHING BETWEEN SEPARATE REPRESENTATIONS OF TIME AND DISTANCE - decided by whether the extreme neurons were ACTIVE TOGETHER WITHIN THE SAME THETA CYCLES
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claim_relations[7]
audittime cell —operationalised-as→ firing — Audit 2026-09-28: DOUBTFUL - read against its span and kept, but the span defines time cells by when they fire; operationalised-as is loose.
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concept_edges[0]
notetime cell —operationalised-as→ firing — neurons that fire at particular moments during periods when BEHAVIOR AND LOCATION ARE RELATIVELY CONSTANT
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concept_edges[0]
edgeGLM —contrasted-with→ tuning curve
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concept_edges[21]
auditnetwork dynamics —distinct-from→ self-motion — Audit 2026-09-28: DOUBTFUL - read against its span and kept, but the span says neurons are not driven entirely by network dynamics without cues; distinct-from is loose.
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concept_edges[38]
notenetwork dynamics —distinct-from→ self-motion — TWO RIVALS ELIMINATED BY TWO SUBPOPULATIONS - distance cells must be reading treadmill speed or the self-motion cues it produces, so the firing is NOT driven entirely by network dynamics
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concept_edges[38]
auditpath integration —distinct-from→ time — Audit 2026-09-28: DOUBTFUL - read against its span and kept, but the span says time-only cells are not exclusively driven by path integration; distinct-from is loose.
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concept_edges[40]
notepath integration —distinct-from→ time — and the time-only cells rule out pure path integration, so the hippocampus represents BOTH dimensions simultaneously
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concept_edges[40]
outcome (stated by the tagger, no quotation)control — heldcontrols[0]
outcome (stated by the tagger, no quotation)control — heldcontrols[1]
for which uselimitation — the mixed cells specifically: WE CANNOT SAY WITH CERTAINTY WHETHER THOSE NEURONS ... WERE ENCODING BOTH TIME AND DISTANCE SIMULTANEOUSLY OR WHETHER THE HIPPOCAMPUS WAS SHIFTING BETWEEN TYPES OF REPRESENTATIONS
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limitations[0]
for which uselimitation — the time-versus-distance dissociation the paper is built on: IT IS IMPOSSIBLE TO COMPLETELY SEPARATE TIME AND DISTANCE AS LONG AS THE RAT IS STILL RUNNING ON THE TREADMILL
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limitations[1]
for which uselimitation — every claim that location and behaviour were held constant: the clamping WAS LARGELY SUCCESSFUL, ALTHOUGH MINOR VARIATIONS PERSISTED, AND WERE TAKEN INTO ACCOUNT IN SUBSEQUENT ANALYSES
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limitations[2]
for which uselimitation — the same scope as limitations[1], with the consequence for the figures: THE EFFECTS OF VARYING SPEED BECOMES MORE PRONOUNCED AS TIME ELAPSES, so the alignment is easier to see at the end of the run than the beginning
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limitations[3]
for which uselimitation — the same scope as limitations[0] - simultaneous coding and switching cannot be told apart here
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limitations[4]
for which uselimitation — the same scope as limitations[2], with the numbers: 75% OF THE TIME SPENT ON THE TREADMILL COULD BE ACCOUNTED FOR BY AN AREA WITH A RADIUS OF APPROXIMATELY 3.3 cm
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limitations[5]
for which uselimitation — the cell-class labels, which belong to the task segment and not to the cell: NEURONS IDENTIFIED AS RESPONDING MORE ACCURATELY TO TIME OR ... DISTANCE ... OFTEN EXPRESSED STANDARD PLACE FIELDS IN OTHER REGIONS OF THE MAZE WHEN THE TREADMILL WAS OFF
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limitations[6]
duplicate ofmechanism — mechanisms[3]
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mechanisms[1]
replicationuntested
no type for thiselapsed time → distance — THE TWO CANNOT BE SEPARATED IN THIS STUDY - the DESIGN form of the negative relation / No edge type can express it: all eight assert that a relation HOLDS. Recorded here because a confounding statement BOUNDS WHAT THE PAPER'S OWN RESULTS CAN MEAN, and it lives in a methods paragraph where nothing downstream will find it. The confound is between the two things the paper's own title sets against each other, and it is the paper that ANSWERS Eichenbaum2014's question - so a reader joining the two needs this sentence and would never see it.
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unhoused_relations[0]
limitationdue to the residual correlation between time elapsed and distance traveled, the paper cannot say with certainty whether neurons influenced by both were encoding both simultaneously or whether the hippocampus was shifting between types of representations
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limitations[0]
limitationThe experimental design cannot fully dissociate time from distance during ongoing treadmill running.
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limitations[1]
limitationthe clamping of behavior and location was largely successful, although minor variations persisted, and were taken into account in subsequent analyses
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limitations[2]
limitationtime and distance cannot be fully separated while the animal is still running, so the decoupling is partial by construction
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limitations[3]
limitationand the residual correlation means the paper cannot say whether the mixed cells encode both at once or switch between representations - the theta result is what makes the first reading likely
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limitations[4]
limitationthe clamping of behaviour and location was only largely successful; minor variations persisted and had to be modeled rather than removed
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limitations[5]
limitationand the cell classes are relative to this task - the same neurons carry ordinary place fields elsewhere on the maze
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limitations[6]
Content tags
content-observations: finding · quantity · variable · definition · key-term — grounded in the full text
findingFiring of hippocampal neurons during treadmill running was driven by elapsed time and distance run, and could not be explained by the small residual variation in the rat's head position.
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content_tags.findings[0]
finding42 neurons (11%) showed distance but not time as informative, and 30 neurons (8%) showed time but not distance as informative
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content_tags.findings[1]
findingneurons only responding significantly to time fired within the same theta cycle as neurons only responding significantly to distance, suggesting that the hippocampus is representing both time and distance simultaneously
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content_tags.findings[2]
findingActive neurons fired in a repeating sequence that tiled the whole treadmill run, so some subset of cells was firing at every moment.
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content_tags.findings[3]
findingDistance coding on a treadmill shows the hippocampus can integrate path length using self-motion alone, without the visual flow that normally accompanies travel.
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content_tags.findings[4]
findingFiring fields that peaked later in the run were also wider, so temporal precision degraded as the run progressed.
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content_tags.findings[5]
findingneurons identified as responding more accurately to time or more accurately to distance during treadmill running often expressed standard place fields in other regions of the maze when the treadmill was off
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content_tags.findings[6]
findingTWO VARIABLES CONFOUNDED IN EVERY EARLIER STUDY: elapsed time was confounded with the distance travelled, THE NUMBER OF STEPS TAKEN, leaving the time-cell result open to a path-integration reading
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content_tags.findings[7]
findingand path integration has been proposed as the PRIMARY FUNCTION of hippocampal networks, which is why the parameters had to be disentangled
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content_tags.findings[8]
findingthe design stated as a verb - CLAMP behavior and location, and vary the treadmill speed to decouple distance from time
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content_tags.findings[9]
findingneurons fire at particular moments during periods when behavior and location are relatively constant, with the speed varied to distinguish time from distance
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content_tags.findings[10]
findingmost neurons were strongly influenced by both time and distance, and some significantly by only one
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content_tags.findings[11]
findingAND THE DECOUPLING IS DECLARED INCOMPLETE: it is IMPOSSIBLE to completely separate time and distance while the rat is still running
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content_tags.findings[12]
findingwith the consequence for the figures admitted - the most visually distinct examples typically fire AT THE END of the run, because that is where the effect of speed has grown
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content_tags.findings[13]
findingand the residual correlation is carried into the conclusion - the paper CANNOT SAY WITH CERTAINTY whether mixed cells encode both dimensions or switch between them
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content_tags.findings[14]
findingTHE CLAMP IS REPORTED AS PARTIAL: largely successful, with minor variations persisting and taken into account rather than removed
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content_tags.findings[15]
findingthe rats spent 74% of treadmill time inside an area visited in every time bin, and that area contained 82% of the tighter one
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content_tags.findings[16]
findingA FIRING-RATE THRESHOLD DEFINES A CELL CLASS: units averaging more than 8 Hz were considered putative interneurons and excluded before any analysis
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content_tags.findings[17]
findingsignificantly more neurons were active on the treadmill than expected if they were simply place cells with fields there
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content_tags.findings[18]
findingthe location account is tested BY CONSTRUCTION - if position sufficed the predicted and observed curves would match, and a stationary rat would give a FLAT prediction
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content_tags.findings[19]
findingand nearly all neurons DID show spatial tuning, with location still NOT SUFFICIENT to explain the firing
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content_tags.findings[20]
finding92% of treadmill-active neurons significantly changed firing rate across time bins
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content_tags.findings[21]
findingTWO METHODS WITH DIFFERENT ASSUMPTIONS MADE TO AGREE ON PURPOSE: the finding DOES NOT DEPEND UPON THE ASSUMPTIONS MADE BY EITHER MODEL
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content_tags.findings[22]
findingsix nested models, each removing one or more CATEGORIES of covariate, so each deviance measures what that category was worth
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content_tags.findings[23]
findingTHE POPULATION SPLITS AT BOTH EXTREMES: 42 neurons (11%) distance-but-not-time and 30 (8%) time-but-not-distance, with 284 (70%) informative for both
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content_tags.findings[24]
findingat the extremes some neurons EXCLUSIVELY signalled time and others EXCLUSIVELY distance
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content_tags.findings[25]
finding62% were more tuned to time and 38% more tuned to distance, with 63% more influenced by time than by space
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content_tags.findings[26]
findingand the two extremes fire IN THE SAME THETA CYCLE, arguing for simultaneous representation rather than switching
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content_tags.findings[27]
findingNOT A PROPERTY OF THE CELL: neurons identified as responding more accurately to time or more accurately to distance during treadmill running OFTEN EXPRESSED STANDARD PLACE FIELDS in other regions of the maze when the treadmill was off
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content_tags.findings[28]
findingAND THE FIELD ALREADY KNEW THIS ABOUT DIRECTION: where direction was irrelevant firing ignored it, where it became meaningful it did not - activity reflects the regularities THAT CHARACTERIZE THE TASK AT HAND
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content_tags.findings[29]
findingwith the precedent named - Muller 1987 clamped behaviour as foraging and randomized direction to see what signal would emerge
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content_tags.findings[30]
findingTWO RIVALS ELIMINATED BY TWO SUBPOPULATIONS: distance cells rule out firing driven ENTIRELY by network dynamics, since they must read treadmill speed or self-motion cues
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content_tags.findings[31]
findingand time-only cells rule out pure path integration, so both dimensions are represented at once
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content_tags.findings[32]
findingwith distance integrated EVEN IN THE ABSENCE of the visual cues usually associated with movement through space
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content_tags.findings[33]
findingfields peaking later in the run were wider (r = 0.50)
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content_tags.findings[34]
findingwhere maze locations mattered to task success, space strongly influenced the firing of even the same neurons
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content_tags.findings[35]
quantity927 — putative pyramidal cells recorded, drawn from 18 sessions in 6 rats
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content_tags.quantities[0]
quantity92% (366/400) — share of treadmill-active neurons whose firing rate changed significantly across time bins in the two-factor ANOVA
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content_tags.quantities[1]
quantity380/400 — neurons for which adding time plus distance covariates significantly improved the GLM fit over space alone
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.quantities[2]
quantity314/400 (79%) and 326/400 (82%) — neurons for which distance, in addition to time and space, was informative, and neurons for which time, in addition to distance and space, was informative
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content_tags.quantities[3]
quantity220/356 (62%) — neurons more strongly tuned to time than distance, the remaining 38% being more tuned to distance
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content_tags.quantities[4]
quantity0.50 — Pearson correlation between a neuron's normalized peak firing time and its normalized firing field width
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.quantities[5]
quantity35 to 49 cm/s — the range from which treadmill speed was randomly drawn on each trial
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content_tags.quantities[6]
quantity3.3 cm — radius of the area containing 75% of the rat's head positions during treadmill running, the measure of how well location was clamped
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content_tags.quantities[7]
quantity42 neurons (11%) ... 30 neurons (8%) — cells informative for distance but not time, and for time but not distance - the two small groups that eliminate one rival account each
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content_tags.quantities[8]
quantity8 Hz — the session-average firing rate above which a unit was reclassified as an interneuron and dropped - a cell class defined by a threshold rather than by a property of the cell
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content_tags.quantities[9]
quantity92% — of treadmill-active neurons significantly changing firing rate across time bins - the coarse result the rest of the paper has to survive
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content_tags.quantities[10]
quantity0.49 — agreement between a nonparametric and a parametric estimate of the same thing, reported so that the conclusion cannot be attributed to either model's assumptions
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content_tags.quantities[11]
quantity74% — of treadmill time spent inside the area visited in every time bin - the number that makes 'location was held constant' checkable rather than asserted
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content_tags.quantities[12]
variabletreadmill speed (independent)
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content_tags.variables[0]
variableneuronal firing pattern (dependent)
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content_tags.variables[2]
variabledistance traveled (control)
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content_tags.variables[3]
variabletime
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content_tags.variables[5]
variabledistance
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content_tags.variables[6]
variablespeed
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content_tags.variables[7]
variablefield width
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content_tags.variables[8]
definitiontime cells
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content_tags.definitions[0]
definitionpath integration
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content_tags.definitions[1]
definitiondifference score
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content_tags.definitions[2]
definitionclamp
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content_tags.definitions[5]
definitioninterneuron
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content_tags.definitions[6]
definitiondeviance
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content_tags.definitions[7]
definitionfield width
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content_tags.definitions[8]
key-termstime, distance, location, hippocampal, neuron, treadmill, speed, firing, place cell, path integration, time cell, confound, GLM, model, tuning curve, deviance, covariate, spatial, episodic memory, theta, interneuron, clamp, behavior, task, direction, assumption, field width, self-motion, network dynamics, ANOVA
Statistics — cross-field join keys
field-invariant statistical terms, used in their statistical sense (gated on a number / symbol / test). A p-value or a standard deviation means the SAME thing in physics, biology, psychology and sociology — so these are the strongest cross-field join keys. Grounded verbatim.
ANOVA as written: two-factor ANOVA with spatial bin and “temporal” bin as two factors
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content_tags.statistics[0]
correlation as written: Pearson’s linear correlation coefficient
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content_tags.statistics[1]
bootstrap N as written: bootstrap samples by randomly sampling (with replacement)
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content_tags.statistics[2]
confidence interval as written: 95% confidence bounds
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content_tags.statistics[3]
generalized linear model λ as written: generalized linear model (GLM)
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content_tags.statistics[4]
likelihood ratio test Γ as written: likelihood ratio tests to compare each nested model to the full model
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content_tags.statistics[5]
chi-squared χ2 as written: χ 2 10 > 18.3
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content_tags.statistics[6]
maximum likelihood estimation as written: iterative Newton-Raphson method to maximize the likelihood function
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content_tags.statistics[7]
Poisson regression λ as written: inhomogeneous Poisson process
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content_tags.statistics[8]
standard deviation
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content_tags.statistics[9]
p-value p as written: p ≤ 0.05
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content_tags.statistics[10]
two-factor ANOVA
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content_tags.statistics[11]
Pearson’s linear correlation coefficient
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content_tags.statistics[12]
deviance
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content_tags.statistics[13]
Second readings
a facet read a second time, independently, from its own sentence — and whether the two readings agree
claim typeexistence — a second reading reaching the same value; recorded: existence
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alternatives.claim_type
methodthe same firing fit twice under different assumptions - a nonparametric spatial look-up table and a parametric nested-model GLM - so the conclusion does not rest on either — a second reading DIFFERING from the recorded value; recorded: electrophysiology
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alternatives.method
phenomenonsequences of transient hippocampal firing during a delay in which behaviour and place are held constant — a second reading DIFFERING from the recorded value; recorded: hippocampal time cells
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alternatives.phenomenon

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.

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