mteb/BrightProPsychologyRetrieval huggingface dataset:
In the hippocampus, spatial maps are formed by place cells while contextual
memories are thought to be encoded as engrams  1  ,  2  ,  3  ,  4  ,  5  , 
6 .") . Engrams are typically
identified by expression of the immediate early gene _Fos_ , but little is
known about the neural activity patterns that drive, and are shaped by, Fos
expression in behaving animals  7  ,  8  ,  9  ,  10
.") . Thus,
it is unclear whether Fos-expressing hippocampal neurons also encode spatial
maps and whether Fos expression correlates with and affects specific features
of the place code   11 .") . Here we
measured the activity of CA1 neurons with calcium imaging while monitoring Fos
induction in mice performing a hippocampus-dependent spatial learning task in
virtual reality. We find that neurons with high Fos induction form ensembles
of cells with highly correlated activity, exhibit reliable place fields that
evenly tile the environment and have more stable tuning across days than
nearby non-Fos-induced cells. Comparing neighbouring cells with and without
Fos function using a sparse genetic loss-of-function approach, we find that
neurons with disrupted Fos function have less reliable activity, decreased
spatial selectivity and lower across-day stability. Our results demonstrate
that Fos-induced cells contribute to hippocampal place codes by encoding
accurate, stable and spatially uniform maps and that Fos itself has a causal
role in shaping these place codes. Fos ensembles may therefore link two key
aspects of hippocampal function: engrams for contextual memories and place
codes that underlie cognitive maps.
We used a custom headplate holder designed for reproducible day-to-day
mounting of the mouse on the ball. Before imaging, the cannula and window were
cleaned using rounds of filtered water and gentle vacuum suction to remove
fine dust and debris. The mouse was positioned under the objective, and the
field of view was manually aligned with a reference image taken on day 1 of
the experiment. To maintain a consistent axial plane during imaging, a subset
of recently acquired frames were registered online to a reference stack to
estimate displacements from the target plane. These results were plotted
throughout the experiment to guide periodic small manual adjustments
countering axial and lateral drift. Post hoc assessment of drift and image
quality was performed by manually examining sped-up and downsampled movies of
the entire experiment after motion correction   63
.") . Experiments with insufficiently stable imaging
quality or imaging plane were excluded before the start of in-depth analysis.
We examined the arrangement of cells that participated in these ensembles
(Fig.  4d  ). We reasoned that groups of
neurons with high activity correlations may make up an ensemble specific to a
particular location on the track. Instead, clusters of cells with high
correlations consisted of place cells with fields separated in space and that
notably spanned the length of the track. Therefore, the clusters of Fos-high
neurons form ensembles that are configured as place cell sequences and thus
could serve as a spatial map of the entire track.
###   Source Data Fig. 5
* Chia-Hsuan Wang
* Thomas J. McHugh
###   Source Data Extended Data Fig. 7
##  Supplementary information
##  Data availability
The following analyses were performed only on cells with significant place
fields. To identify groups of place cells that had correlated activity across
trials, independently of the positioning of their place fields in the track,
we quantified the level of activity of each cell within its place field(s) on
each eligible trial (see ‘Place field definition’) within the session: we
refer to this as the trial-wise place field activation. Within-group
correlation was quantified as the mean pairwise correlation of trial-wise
place field activation within each group. To visualize and quantify group
structure within the trial-to-trial variability in the population, we
clustered cells with affinity propagation   76
.") , using
as similarity their pairwise correlations in trial-wise place field activation
(preference parameter, −1; max iterations, 5,000). To analyse within-group
correlations across days, we examined pairs of sessions within the same animal
separated by the variable ∆sessions. We will refer to the earlier session as
the reference session and the subsequent session as the target session: for
example, comparing sessions 3 and 4 corresponds to a ∆+1 pair, where the
reference session is 3 and the target session is 4. Because we only considered
pairs with a positive ∆ value, each unique pair of sessions was considered at
most once in the analysis. For every pair of sessions with a positive ∆ value
where the reference session had Fos induction data, the cell groups (Fos-high
and Fos-low) were defined by induction quantile (top 20% and bottom 20%,
respectively) on the reference session. We then computed the within-group
correlation between these cells in the target session, as described above.
**a** , Task schematic. **b** , Example behaviour during learning (left) and
expert performance (right). Top, raster plot of licks (black), rewards (teal)
and reward consumption licks (grey). Middle, fraction of trials with a lick
(black) or consumption lick (grey) in each spatial bin. Bottom, average
running speed in each spatial bin. **c** , Average learning curve of licking
selectivity (  Methods  ). Data (left to
right) are shown as the mean ± s.e.m. for _n_ = 10, 10, 10, 12, 12, 12, 10, 8,
7, 6 and 5 mice. **d** , Example behaviour following saline (left) or muscimol
(right) injection. Similar to **b** . **e** , Licking selectivity for saline
and muscimol sessions. Connected dots correspond to individual mice ( _n_ = 4
mice). _P_ < 0.001, two-sided permutation test with 1,000 shuffles. **f** ,
Measurement of Fos induction, corresponding to the fold change in GFP
fluorescence from the start of the session to 2–4 h after the session. Scale
bar, 50 µm. **g** , Histogram of fold induction (GFP  after session  /GFP
baseline  ) at less than 1 h (black; _n_ = 34,359 cells) and 2–4 h (red; _n_ =
39,635 cells) from the start of the behaviour session. Of the 73,994 points,
267 beyond the _x_ -axis limits are not shown for improved visualization.
**h** , Fold induction as a function of time from the start of a behaviour
session (1-h time bins). Data are shown as the mean ± s.e.m.; _n_ for time
points (from left to right) = 37, 35, 2, 19 and 22 sessions. **i** ,
Representative imaging field of view (left) and calcium traces (right). **j**
– **n** , Calcium transient properties of Fos-high versus Fos-low cells. Top,
each circle indicates the mean across neurons for one session. Bottom,
session-wise difference histogram (grey) with kernel density estimation
(black). Two-sided paired-sample _t_ test: _P_ = 6 × 10  −6  ( **j** ), _P_ =
0.047 ( **k** ), _P_ = 0.00066 ( **l** ), _P_ = 0.14 ( **m** ), _P_ = 0.00097
( **n** ). _n_ = 27 sessions for 6 mice. NS, not significant; *, _P_ < 0.05;
***, _P_ < 0.001.
All experimental procedures were approved by the Harvard Medical School
Institutional Animal Care and Use Committee and were performed in compliance
with the Guide for Animal Care and Use of Laboratory Animals. For muscimol
inactivation experiments, data were collected from four adult wild-type
C57BL/6J male mice (Jackson Laboratory, stock no. 000664). For Fos staining
experiments, data were collected from four adult wild-type C57BL/6J male mice
(Jackson Laboratory, stock no. 000664) and four Npas4-FH   24
.") ,  54 .") mice
(Greenberg laboratory, Harvard Medical School), split evenly between the
control and exposed conditions. Npas4 staining was not analysed. For Fos-GFP
reporter imaging experiments, data were collected from four adult
Thy1-jRGECO1a   55 .") ×
B6.Cg-Tg(Fos-tTA,Fos-EGFP*)1Mmay/J double-transgenic male mice and seven
B6.Cg-Tg(Fos-tTA,Fos-EGFP*)1Mmay/J transgenic male mice (Jackson Laboratory,
stock no. 018306) injected with AAV (serotype 2/1) encoding a CAG-jRGECO1a
red-shifted calcium indicator   56 .") . As the _Fos_ \- _GFP_ transgene in
these mice is not under the control of doxycycline and the Tet transactivator
was not used, doxycycline was not administered in this study. GFP was
localized to the nucleus owing to a nuclear localization sequence (M. Mayford,
personal communication). For Fos-KO imaging experiments, data were collected
from six adult _Fos_ _fl_ / _fl_ ; _Fosb_ _fl_ / _fl_ ; _Junb_ _fl_ / _fl_
male mice   24 .") ,  57 .") . For
all behaviour and imaging experiments, mice were at least 12 weeks old before
the first data collection. For ex vivo experiments, data were collected from
six _Fos_ _fl_ / _fl_ ; _Fosb_ _fl_ / _fl_ ; _Junb_ _fl_ / _fl_ male and
female mice 4–6 weeks of age and six B6.Cg-Tg(Fos-tTA,Fos-EGFP*)1Mmay/J male
and female mice 4–6 weeks of age.
Cannula implantation for hippocampal imaging was performed on mice after water
schedules had started, at approximately 90% of initial body weight. The
hippocampal window and headplate implantation surgeries were carried out as
described previously   43 .") , [ 62
](/articles/s41586-022-05113-1#ref-CR62 "Ulivi, A. F. et al. Longitudinal two-
photon imaging of dorsal hippocampal CA1 in live mice. J. Vis. Exp.
###  Remapping experiments
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##  Extended data figures and tables
##  nature.com sitemap
The hippocampus contains engram cells that have a privileged role in the
encoding and retrieval of memories   4 .") ,  12
.") . Engram cells are typically identified by expression of the
activity-inducible transcription factor Fos   13
.") during the encoding of a memory   7
.") , and their synchronous
activation can trigger robust memory recall   8
.") ,  14 .") . There is growing evidence that neurons defined by
Fos expression carry information about context that can be used to form
lasting associations, for example, between a specific environment and an
aversive outcome. In addition, the hippocampus contains place cells that
encode spatial maps of an environment and are thought to support spatial
memories and navigation   2 .") ,  3 .") ,  15 .") ,  16
.") .
Given the higher fraction of cells with place fields and higher reliability in
activity for Fos-high cells, we reasoned that these cells may constitute a
subpopulation well suited for representing the mouse’s current location. We
trained a naive Bayes’ decoder to predict the mouse’s location on the basis of
the activity in a population of Fos-high or Fos-low neurons (Fig.  2i
 ). In all sessions, the accuracy of
decoding the mouse’s position using a population of Fos-high cells was greater
than with an equally sized population of Fos-low cells, observed as lower
decoding error in the Fos-high population (Fig.  2j,k
 ). This improvement in decoding with
higher Fos induction was present across all spatial positions of the track and
increased with the level of Fos induction (Fig.  2l,m
 ). To test whether the increased decoding
accuracy could be explained by higher calcium activity in the Fos-high
population, we subsampled Fos-high and Fos-low cells in each session to create
populations with similar integrated ∆ _F_ / _F_ (Extended Data Fig.  6c,d
 ). Even after matching activity levels,
Fos-high cells exhibited significantly lower decoding error, higher incidence
of place fields and greater spatial information than their Fos-low
counterparts (Extended Data Fig.  6e–h 
). Thus, Fos-high cells have a link to place coding that goes beyond their
higher calcium activity.
###   Extended Data Fig. 10 Fos-KO and Fos-WT place field distribution.
https://doi.org/10.1101/031658
###   Source Data Fig. 3
##  Source data
* Accepted  :  14 July 2022
To monitor changes in Fos expression potentially resulting from the task, we
used a _Fos_ -transgenic reporter mouse in which enhanced green fluorescent
protein (eGFP) with a short half-life is expressed under the control of the
_Fos_ promoter (hereafter referred to as Fos-GFP)   7
.") . We quantified Fos
induction by comparing the GFP fluorescence of cells before the start of a
behavioural session with the fluorescence intensity approximately 3 h later
(Fig.  1f–h  ). We chose this latter time
point from a time-course analysis, which showed that fluorescence changes
peaked around 3 h after the start of a behaviour session, in line with
previous studies using this reporter   29 .") ,  30
.") (Extended Data Fig.  2a–g
 ). In separate experiments using post hoc
staining, we observed an increase in Fos expression in the hippocampus of mice
exposed to the virtual environment used in our task when compared with
expression in mice that ran on a treadmill in darkness (Extended Data Fig. 
3a–c  ). These results indicate that,
within CA1, Fos expression may be triggered by navigation through a virtual
environment.
###   Source Data Extended Data Fig. 6
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**Table 1 Descriptive statistics of variables**
3. For detail, please refer to  http://ceps.ruc.edu.cn  . We are grateful to Professor Weidong Wang and his colleagues for data collection.
The first source is derived from FHR data, called UMETRICS, on all personnel
paid on sponsored research projects for 118 college campuses from 36
universities from 2001 to 2022 (the exact years covered vary by institution)
 36 .") . A full list of participating institutions, which are
primarily research-intensive, can be found at  https://iris.isr.umich.edu/
 .
Job titles for each employee, which are also referred to in the text as
positions, or roles, are constructed from the FHR records   42
.") . Some employees may hold different job
titles on the same or different teams; in those instances, the title is
equally weighted based on the number of days they were paid in each title
within each team.
where _i_ potential authorship observations are characterized by an employee
_e_ working on team _l_ in the year prior to a document with a publication or
application date _t_ (calendar year × months). The primary variable of
interest,  \\({{\rm{woman}}}_{i,e}\\)  , is an indicator of whether a
potential authorship was attributable to an employee who was a woman. Equation
(  1  ) is estimated on the sample of
17,929,271 potential authorships of journal articles, whereas the patent
results are estimated on the sample of 3,203,831 potential inventorship.
Research Topics __
##  Attribution and survey data
Thus, some of the well-documented ‘productivity gap’  1  ,  2  ,  3  ,  4  , 
5 .") may
not be a gap in the contribution of women to science at all, but rather a gap
in how much their contributions are recognized. The associated qualitative
work suggests that the standards determining scientific attribution are not
well-known or understood by all parties and are frequently disregarded. The
result appears to be that women are systematically disadvantaged. Although our
focus here is on gender, these gaps were also reported in our survey for other
marginalized groups.
###  Finance and human resources data
Article  Open access  04 October 2022
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####  Gender
###  Hypothesis 3a
The international comparison based on cross-sectional data also shows that
although men still have advantages in mathematics in general, this is not
always the case for specific countries/cultures/ethnicities. For example,
among the 78 countries/regions participating in the 2018 Program for
International Student Assessment (PISA),  Footnote  4  32 did not have
significant gender differences in average math scores (accounting for 41%),
while 32 were male leading (41%) and 14 were female leading (18%).  Footnote
5  Similar findings are found in other comparative studies of transnational or
cross-ethnic data. For junior high school students, male students are ahead of
female students in mathematics in general, but the difference varies greatly
among countries or ethnicities, and sometimes, the direction is reversed
(Penner  2008 : S138–S170.") ; Baker and Jones  1993
: 91–103.") ).
.  2009 Nov;135(6):859-884.
6. Julia I. Lane
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1. Matthew B. Ross
* Social Environment
American Psychological Association
In the study of the gender gap in mathematics learning, there are
controversies about how to measure the mathematics level. Some researchers
believe that different test methods will lead to variations in gender
differences, e.g., that girls are better at learning textbook knowledge.
Therefore, in course examinations with familiar examination forms and related
teaching content, girls’ performance is likely to be better than that of boys.
However, if the test contents are not closely related to textbook knowledge
and the test methods are novel, male students are likely to perform better
(Halpern et al.  2007 : 1–51.") ). In other
words, girls are better at mathematics knowledge derived from textbooks and
classroom teaching, and boys are better at mathematical capability outside the
classroom and textbooks. Since many studies focus on the math test results of
students in schools, the differences between boys and girls in mathematical
capability cannot be convincingly reflected even if the advantages of girls
are found.
Home  __  Research Topics
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Protestantism

__  Evangelicalism
Publications are drawn from the Web of Science database produced and
maintained by Clarivate Analytics, which contains publication and citation
information on approximately 69.3 million total articles from 1900 to 2018.
The analysis focuses on articles published from 2014–2016 and linked to
individuals observed in UMETRICS from 2013–2016, although we include some
additional robustness checks on other year ranges and other publication types
in the  Supplementary Information  .
*  Analysis of the perceptions, competencies, and educational needs for global health among Korean medical students.
Psychologists have verified the existence of stereotype threat in mathematics
learning with various experimental designs. It was found that the presence of
male participants or the presence of psychological implications before the
test (“men do better in math”) will weaken females’ performance in the
experiment and thus affect their attitude toward participating in math tests,
making them feel more burdened by the pressure of competition than men and
less willing to participate in the competition. The researchers further
reasoned that since females’ performance and willingness in the competition
are very vulnerable to the influence of their competitors' gender, the gender
ratio of competitors is likely to affect the gender gap in the competition
results (Spencer et al.  1999 :
4–28.") ; Niederle & Lise  2010 : 129–144.") ). Moreover, some studies have found that a higher
proportion of female students in schools has a positive relationship with
their math performance (Nollenberger et al.  2016
: 257–261.") ).
7. For more information, see  https://www.ndrc.gov.cn/fggz/fzzlgh/gjjzxgh/201707/W020191104624349042474.pdf  .
All the Stata code (version 17) and Python code (version 3.7.6) used is
available in the Virtual Data Enclave at the University of Michigan. Access
information is provided at  https://iris.isr.umich.edu/research-data/access/
 .
####  Linked administrative records
###  The gender stereotype of mathematics
The analytical linked dataset, which consists of observations on 128,859
individuals employed on 9,778 research teams from 2013 to 2016 linked to
39,426 subsequent articles and 7,675 patents, is constructed from three
sources: internal finance and human resources (FHR) administrative data from
20 universities and 57 colleges and campuses   36
.") , representing over 40% of total academic R&D spending in the United
States, journal articles from the Web of Science and patent data derived from
the universe of patents from the US Patent and Trademark Office.
In sum, and beyond the results presented here, this paper serves as the
introduction to a new and rich data infrastructure that is at least as rich as
the bibliometrics data infrastructure that has served as the evidence basis
for the study of the science of science   34
.") . The infrastructure,
which is currently being used by more than 200 researchers can be, and has
been, replicated in other countries   35 .") and provides new insights into the organization of science.
Raviv Murciano-Goroff
What the data says about abortion in the U.S.
The possibility that women receive less recognition for their scientific
contributions is not hypothetical: the canonical example is that of Rosalind
Franklin. Franklin’s pivotal contribution to the discovery of the structure of
DNA initially went unrecognized   6 .") , and it was not until long after she died that the
scientific community became aware that she was wrongfully denied authorship on
the original Crick and Watson paper. Indeed, her contribution was apparently
only recognized because Watson’s account of the discovery was so incorrect  
9 .") and stimulated a reconstruction of events by Franklin’s friends  
10 .") . More recently, Walter Isaacson recounts Jennifer
Doudna’s concern that she and Emmanuelle Charpentier were being relegated to
“minor players” in the history and commercial use of CRISPR-Cas9   7
.") . The open questions, of course, are how many women’s
contributions have been missed in similar but less high-profile circumstances,
and how many women have been discouraged from pursuing careers in science as a
result   11 .") .
*  How accurate are interest inventories? A quantitative review of career choice hit rates.
Asia & the Pacific   Europe & Russia   Latin America
  Middle East
& North Africa   North America   Sub-Saharan Africa
 
Multiple Regions / Worldwide
All publications and patents that acknowledge one of the team’s grants and/or
has an author/inventor from the team are linked to the team. This results in a
total of 47,101 scientific documents (39,426 articles and 7,675 patents)
published between 2014–2016 which were linked to employees and teams observed
in UMETRICS at any point in the previous year, that is, from 2013–2016.
Summary information about the individuals and the teams is provided in
Extended Data Table  1  . Additional
information about the differences between authors and non-authors in the
sample as well as some basic descriptive information surrounding grant funding
sources is provided in part 2 of the  Supplementary Information
 .
#####  Formats __
Funding: NSF grants 2100234, 1932689, 1761008, 1760544; NIA, OBSSR and NSF
SciSIP through P01 AG039347; R01 GM140281, UL1 TR002733, Alfred P. Sloan
Foundation, Ewing Marion Kauffman Foundation, Schmidt Futures, Patrick J.
McGovern Foundation; B.A.W. was supported on P01 AG039347 by the NBER directly
and on a subaward from NBER to Ohio State. Research reported in this
publication was developed using the Collaborative Archive and Data Research
Environment (CADRE) project (  https://doi.org/10.26313/rdy8-4w58
 ); the authors received some support
through CADRE’s funders. CADRE was developed with support from a National
Leadership Grant from the Institute of Museum and Library Services (IMLS;
grant number LG-70-18-0202-18), including cost-share from the Big Ten Academic
Alliance Library Initiatives (BTAA), Microsoft Research, the Web of Science
Group, and academic university libraries (Ohio State University, Michigan
State University, Purdue University, University of Michigan, University of
Minnesota, Penn State University, University of Iowa and Rutgers University).
Assistance was provided by F. Kreuter, E. Levitskaya, A. Myers, J. O. Smith,
N. Nicholls and J. Xiao.
##  Conclusion and discussion