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Evidence for a subcircuit in medial entorhinal cortex representing elapsed time during immobility

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Abstract and Figures

The medial entorhinal cortex (MEC) is known to contain spatial encoding neurons that likely contribute to encoding spatial aspects of episodic memories. However, little is known about the role MEC plays in encoding temporal aspects of episodic memories, particularly during immobility. Here using a virtual ‘Door Stop’ task for mice, we show that MEC contains a representation of elapsed time during immobility, with individual time-encoding neurons activated at a specific moment during the immobile interval. This representation consisted of a sequential activation of time-encoding neurons and displayed variations in progression speed that correlated with variations in mouse timing behavior. Time- and space-encoding neurons were preferentially active during immobile and locomotion periods, respectively, were anatomically clustered with respect to each other, and preferentially encoded the same variable across tasks or environments. These results suggest the existence of largely non-overlapping subcircuits in MEC encoding time during immobility or space during locomotion.
Functionally and anatomically clustered populations of neurons in MEC encode space during locomotion and elapsed time during immobile intervals of the Door Stop task a, ΔF/F traces of significant transients (green traces; P < 0.01; see Methods) from individual example rest-selective cells (left) and run-selective cells (right) during running and resting periods (black traces) in Door Stop task. b, Histogram of RRI for all active cells across all FOVs in all mice during Door Stop task; transition periods and reward zone excluded. c, Top: mean ΔF/F vs. time across all correct trials of a single session for 6 individual neurons from the same FOV during the 6-s Door Stop wait interval. Purple dashed lines and arrows indicate transition period. Bottom: ΔF/F vs. time for each correct trial. Scale bars indicate 100% ΔF/F. d, Mean ΔF/F vs. time across all correct trials in a single session for all time-encoding cells (each row represents an individual neuron mean ΔF/F value) in a single FOV during the 6-s Door Stop wait interval. Mean ΔF/F is normalized to peak for each neuron (each row). e, Histogram of RRI for all time-encoding cells (red) and all space-encoding cells (blue) across all FOVs in all mice during Door Stop task; transition periods and reward zone excluded. f, MEC FOVs of GCaMP6f-labeled populations (top) colored red or blue to indicate cells encoding time or space, respectively (bottom). g, Mean pairwise distance (left) or fold-change (right) between neurons in various groups. All space- or time-encoding cells from all mice in Door Stop task. Black lines connect measures (dots) from same FOV; thick lines are means across all FOVs (n = 11 imaging fields from 7 mice; repeated-measures ANOVA, F = 11.8, P < 0.0001; between time-encoding cells vs. between all cells, P < 0.001 Tukey’s post hoc test with Bonferroni correction; between time-encoding cells vs. between time- and space-encoding cells, P < 0.01 Tukey’s post hoc test with Bonferroni correction.) Notably, spatial cells were not significantly clustered compared to all cells, although we previously found grid cells clustered compared to nongrid cells²³. This difference is likely due to the heterogeneous spatial cell population defined here, which likely includes grid, border, and spatially selective nongrid cells. ***P < 0.001, **P < 0.01; N.S., nonsignificant.
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Sequence progression across time-encoding MEC cells correlates with animal wait time a, Velocity leading into (time < 0 s), during (0 s < time < 6 s) and after 6-s Door Stop wait interval for all short wait (pink) and long wait (green) correct trials (dark line, mean; shading, s.e.m.). b, Examples of normalized ΔF/F sequence for (top) all time-encoding cells from an individual trial (same cell-ordering and same session in left and right; short wait = 6.1 s, long wait = 8.0 s), (middle) across all trials from an individual FOV (same cell-ordering and same session in left and right; mean short wait = 6.3 ± 0.3 s (mean ± s.d.), mean long wait = 8.3 ± 0.7 s (mean ± s.d.)) and (bottom) for all time-encoding cells across all FOVs (same cell ordering, includes multiple sessions in left and right; mean short wait = 6.5 ± 0.3 (mean ± s.d.), mean long wait = 8.0 ± 0.7 (mean ± s.d.)), short waits (6–7 s; left) and long waits (7–9.5 s; right). Cells were ordered according to each cell’s mean center of mass across all short wait trials (earliest mean center of mass at top, latest at bottom). Pink and green lines are linear fits of short (pink, left) and long (green, right) wait sequences. c, Plot of slopes (from linear fits of cell activations per second) as a function of animal wait time for all individual trials (each circle represents a single trial, as in top panel of b). Cells were ordered according to each cell’s mean center of mass across all correct (6–9.5 s) trials (earliest mean center of mass at top, latest at bottom; n = 73 wait trials from 4 imaging fields in 3 mice).
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The temporal representation formed by populations of time-encoding cells in MEC is present from the first moments of new experiences a, Views of linear tracks mice navigated in during environment-switch experiments. b, Bottom: ΔF/F vs. time for each voluntary rest period (wait trial) of a single session for 4 individual neurons from 2 different mice during the first session in the novel linear track (see a). Rest period 1 was the first time the mice stopped to rest in the novel track (orange trace). Top, mean ΔF/F (red) and velocity (black) vs. time across all rest periods; ΔF/F (orange) and locomotion velocity (gray) from first rest period. Note that negative deflection in mouse velocity trace reflects backwards movements on the treadmill. c, Pearson’s correlation between the calcium transients during each rest period and the mean timing field over all periods (y axis) as a function of the number of wait periods in novel environment (x axis). Gray, mean across all cells in a single FOV in a single session; black, mean ± s.e.m. across all cells in all sessions; n = 5 imaging fields across 3 mice. d, Cumulative distribution of the trial number on which a transient first occurred in the significant timing field (P < 0.05 from bootstrapping; see Methods) in the novel session across all time encoding cells. e, Mean fraction of trials with transients occurring within the significant timing field across all cells for the first half of wait trials in the session versus the second half of wait trials in the session (n = 5 imaging fields from 3 mice; P = 0.1875, two-sided paired Wilcoxon signed-rank test). Black circles indicate means for each session; red circles indicate means across all sessions.
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Articles
https://doi.org/10.1038/s41593-018-0252-8
Department of Neurobiology, Northwestern University, Evanston Illinois, Evanston, IL, USA. *e-mail: d-dombeck@northwestern.edu
Over the past 50 years, research from humans and animal
models have implicated the medial temporal lobe, which
includes the hippocampus and MEC, in the formation
of personal memories of events that occur at specific places and
involve specific time intervals1,2. While a vast amount of research
has uncovered cellular substrates in the hippocampus and MEC
that likely make up the spatial representation required for these epi-
sodic memories38, our understanding of the temporal representa-
tion is substantially less advanced and has focused mostly on the
hippocampus911. Time-related neurons were first demonstrated in
the hippocampus using studies in which rodents were moving to
some degree, either in a running wheel12, on a treadmill13, or in a
small box14. Notably, one study found hippocampal time-related
activity during immobility15. These so-called hippocampal ‘time
cells’ fire briefly and consistently at specific times during the task,
such that behavioral time periods are tiled by a sequence of brief
neuronal activations. Strikingly, specialized circuitry representing
spatial information during immobility has also been demonstrated
in the hippocampus16,17. This suggests that separate circuitry within
the medial temporal lobe might be used to encode behaviorally rel-
evant variables between mobile and immobile periods, though it is
unclear from these studies whether the representation of elapsed
time maps onto a particular circuit(s).
In MEC, one study18 found that MEC grid cells can provide timing-
related information during treadmill running, and a separate study
found MEC neurons that were more active at low running speeds
rather than high speeds during locomotion19. Inactivation of MEC
during such mobile periods was found to produce deficits in encod-
ing memories across trace periods20,21, produce deficits in a temporal
memory task, and cause instability in downstream hippocampal time
cells22. These studies suggest that a code for elapsed time may exist
in MEC during locomotion, but it is currently unknown whether the
neural circuitry in MEC forms a representation of elapsed time during
immobility, when sensory cues may not change in a temporally infor-
mative manner. Furthermore, if such a representation exists in MEC, it
is unknown how the neural circuitry might be organized to generate it.
Results
To explore these ideas, we used our previously developed functional
two-photon imaging methods23 to optically record from popula-
tions of layer II MEC neurons (Fig. 1a and Supplementary Fig. 1)
during mouse navigation in a novel virtual Door Stop task. The
Door Stop task combines both a locomotion-dependent virtual
navigation phase and an explicit instrumental timing phase that
was separated in time and location from reward delivery (Fig. 1b
and Supplementary Fig. 2a). Mice were trained to run down a lin-
ear track to a specific location where they encountered an invisible
door, which they could not run past, though they could still run
on the treadmill. At the door location, the mice were required to
stop and wait for at least 6 s (an auditory click signaled the start of
the 6-s interval once the treadmill velocity fell below a threshold;
see Methods); if the mice began running on the treadmill before
the expiration of the 6 s interval, the mice could not progress past
the closed door and the trial would start over (signaled by another
click). After the 6-s interval, the door would open and the mice
could run down the remaining length of the track to the reward
zone. After 6–8 weeks of training, mice ran to the invisible door and
stopped on their first attempt for the full 6-s wait period on 55.1%
of trials (Fig. 1c), referred to as ‘correct trials’. To easily compare
neural activity during immobile timing periods and neural activity
during locomotion periods, we excluded a transition zone between
these periods and excluded the reward zone when behavior was
more ambiguous (Fig. 1e, Supplementary Fig. 2a, and see Methods).
During the wait periods, mice mostly sat immobile with essentially
0 velocity with small jerky movements occurring during 12.9% of
the wait period to maintain balance on the treadmill (velocity over
wait periods = 0.33 ± 1.00 cm/s (mean ± s.d.); Fig. 1d,e). All of the
data presented in Figs. 24 using the (invisible door) Door Stop task
come only from these correct trials (see Supplementary Fig. 2b–f
for velocity on all trials). Since the mice could not see the invisible
door opening at the end of the 6-s interval, this Door Stop task
therefore required an internal temporal representation for efficient
completion.
Evidence for a subcircuit in medial entorhinal
cortex representing elapsed time during
immobility
JamesG.Heys and DanielA.Dombeck *
The medial entorhinal cortex (MEC) is known to contain spatial encoding neurons that likely contribute to encoding spatial
aspects of episodic memories. However, little is known about the role MEC plays in encoding temporal aspects of episodic
memories, particularly during immobility. Here using a virtual ‘Door Stop’ task for mice, we show that MEC contains a repre-
sentation of elapsed time during immobility, with individual time-encoding neurons activated at a specific moment during the
immobile interval. This representation consisted of a sequential activation of time-encoding neurons and displayed variations
in progression speed that correlated with variations in mouse timing behavior. Time- and space-encoding neurons were prefer-
entially active during immobile and locomotion periods, respectively, were anatomically clustered with respect to each other,
and preferentially encoded the same variable across tasks or environments. These results suggest the existence of largely non-
overlapping subcircuits in MEC encoding time during immobility or space during locomotion.
NATURE NEUROSCIENCE | VOL 21 | NOVEMBER 2018 | 1574–1582 | www.nature.com/natureneuroscience
1574
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... The hippocampus (HIPP) has been considered critical for memory of elapsed time (Meck et al., 1984Jacobs et al., 2013;Yin and Meck, 2014;Sabariego et al., 2019). Recent evidence shows that neural activity in the HIPP and its major input region, the medial entorhinal cortex (MEC), encodes elapsed time through the sequential firing of time-sensitive neurons, or time cells, at specific moments of delay periods (Gill et al., 2011;Kraus et al., 2013;MacDonald et al., 2013;Kraus et al., 2015;Salz et al., 2016;Heys and Dombeck, 2018;Umbach et al., 2020). This sequential organization of firing patterns in the HIPP is likely dependent on intact MEC inputs (Schlesiger et al., 2015;Robinson et al., 2017; but see Sabariego et al., 2019), which are critical to holding information across delays (Sauvage et al., 2010;Suh et al., 2011;Kitamura et al., 2014). ...
... At this stage, rats had no access to external cues guiding the waiting period and had to retrieve a previously memorized target time to successfully complete the task. Comparable to previous work with mice in a virtual reality head-fixed preparation (Heys and Dombeck, 2018), waiting behavior in the freely moving rat became highly stereotyped, consisting of a well defined period of immobility inside the ROI, followed by significant acceleration starting on completion of the target interval (Fig. 1C). This pattern suggested a similar strategy across distinct intervals, tuning to the target interval in the absence of external temporal cues, and showed that the interval was memorized. ...
... Using rats trained in an explicit goal-directed timing task, we show that MEC is necessary for accurate online estimation of time. Interestingly, MEC time cells were previously found to correlate with elapsed time during immobility when animals needed to report an interval by waiting (Heys and Dombeck, 2018). This earlier study showed that sequences of putatively excitatory MEC time cells progressed slower or faster when mice reported longer or shorter intervals, respectively. ...
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The hippocampal region has long been considered critical for memory of time, and recent evidence shows that network operations and single-unit activity in the hippocampus and medial entorhinal cortex (MEC) correlate with elapsed time. However, whether MEC activity is necessary for timing remains largely unknown. Here we expressed DREADDs (designer receptors exclusively activated by designer drugs) under the CaMKIIa promoter to preferentially target MEC excitatory neurons for chemogenetic silencing, while freely moving male rats reproduced a memorized time interval by waiting inside a region of interest. We found that such silencing impaired the reproduction of the memorized interval and led to an overestimation of elapsed time. Trial history analyses under this condition revealed a reduced influence of previous trials on current waiting times, suggesting an impairment in maintaining temporal memories across trials. Moreover, using GLM (logistic regression), we show that decoding behavioral performance from preceding waiting times was significantly compromised when MEC was silenced. In addition to revealing an important role of MEC excitatory neurons for timing behavior, our results raise the possibility that these neurons contribute to such behavior by holding temporal information across trials.
... For example, outside the NAc, synaptic eligibility traces have been found to have longer time scales of 5 s in the neocortex 30 and 10 min in the hippocampus 31 . In addition to synaptic eligibility traces, persistent activities that store eligible events in working memory can also associate temporally separated events 32 . ...
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... It is of some significance that the medial temporal lobe which encodes episodic memories also carries information about the temporal context of objects (Hsieh et al., 2014;MacDonald et al., 2011). A subcircut in the entorhinal cortex in that lobe has been shown to represent elapsed time in immobile animals (Heys & Dombeck, 2018) and correlated ramping activity in humans (Umbach et al., 2020). ...
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Our sense of time is far from constant. For instance, time flies when we are having fun, and it slows to a trickle when we are bored. Midbrain dopamine neurons have been implicated in variable time estimation. However, a direct link between signals carried by dopamine neurons and temporal judgments is lacking. We measured and manipulated the activity of dopamine neurons as mice judged the duration of time intervals. We found that pharmacogenetic suppression of dopamine neurons decreased behavioral sensitivity to time and that dopamine neurons encoded information about trial-to-trial variability in time estimates. Last, we found that transient activation or inhibition of dopamine neurons was sufficient to slow down or speed up time estimation, respectively. Dopamine neuron activity thus reflects and can directly control the judgment of time.