Social familiarity and reinforcement value: a behavioral-economic analysis of demand for social interaction with cagemate and non-cagemate female rats

Abstract

Rats were studied in social reinforcement procedures in which lever presses opened a door separating two adjacent spaces, permitting access to social interaction with a partner rat. The number of lever presses required for social interaction was systematically increased across blocks of sessions according to fixed-ratio schedules, generating demand functions at three different social reinforcement durations: 10 s, 30 s, and 60 s. The social partner rats were cagemates in one phase, and non-cagemates in a second phase. The rate at which social interactions were produced declined with the fixed-ratio price, and was well described by an exponential model that has been successfully employed with a range of social and non-social reinforcers. None of the main parameters of the model varied systematically with social interaction duration or with the social familiarity of the partner rat. On the whole, the results provide further evidence of the reinforcing value of social interaction, and its functional parallels with non-social reinforcers.

Full text

Frontiers in Psychology 01 frontiersin.org
Social familiarity and
reinforcement value: a
behavioral-economic analysis of
demand for social interaction with
cagemate and non-cagemate
female rats
RachelSchulingkamp
1, HaoranWan
1,2 and
TimothyD.Hackenberg
1
*
1 Department of Psychology, Reed College, Portland, OR, United States, 2 Department of Psychological
and Brain Sciences, Washington University in St. Louis, St. Louis, MO, United States
Rats were studied in social reinforcement procedures in which lever presses
opened a door separating two adjacent spaces, permitting access to social
interaction with a partner rat. The number of lever presses required for social
interaction was systematically increased across blocks of sessions according
to fixed-ratio schedules, generating demand functions at three dierent
social reinforcement durations: 10 s, 30 s, and 60 s. The social partner rats were
cagemates in one phase, and non-cagemates in a second phase. The rate at
which social interactions were produced declined with the fixed-ratio price, and
was well described by an exponential model that has been successfully employed
with a range of social and non-social reinforcers. None of the main parameters of
the model varied systematically with social interaction duration or with the social
familiarity of the partner rat. On the whole, the results provide further evidence
of the reinforcing value of social interaction, and its functional parallels with non-
social reinforcers.
KEYWORDS
social reinforcement, operant methods, demand analysis, rats, social familiarity
Introduction
For mammals and other social animals, social interaction serves key adaptive functions at
various stages of development, including parental care, social play, and reproductive behavior
(Trezza et al., 2011). Indeed, this tendency to seek out social interaction is a dening
characteristic of a social species. It is therefore unsurprising that social reinforcement (here
dened as contingent access to social interaction) has been observed in a variety of species,
including chimpanzees (Mason etal., 1962), capuchin monkeys (Dettmer and Fragaszy, 2000),
horses (Søndergaard etal., 2011), foxes (Hovland etal., 2011), calves (Holm etal., 2002), sows
(Kirkden and Pajor, 2006), mice (Martin et al., 2014), voles (Beery et al., 2021), hamsters
(Borland etal., 2017), and rats (Wilsoncro, 1968; Evans etal., 1994).
A variety of methods have been used to study social reinforcement (see review by Trezza
etal., 2011), including operant procedures in which behavior produces opportunities for social
OPEN ACCESS
EDITED BY
Sarah Till Boysen,
Independent researcher,
Sunbury, OH, UnitedStates
REVIEWED BY
Justin Strickland,
Johns Hopkins University, UnitedStates
Alan Silberberg,
American University, UnitedStates
Kennon Lattal,
West Virginia University, UnitedStates
Annaliese K. Beery,
University of California,
Berkeley, UnitedStates
*CORRESPONDENCE
Timothy D. Hackenberg
hack@reed.edu
RECEIVED 03 February 2023
ACCEPTED 21 April 2023
PUBLISHED 12 May 2023
CITATION
Schulingkamp R, Wan H and
Hackenberg TD (2023) Social familiarity and
reinforcement value: a behavioral-economic
analysis of demand for social interaction with
cagemate and non-cagemate female rats.
Front. Psychol. 14:1158365.
doi: 10.3389/fpsyg.2023.1158365
COPYRIGHT
© 2023 Schulingkamp, Wan and Hackenberg.
This is an open-access article distributed under
the terms of the Creative Commons Attribution
License (CC BY). The use, distribution or
reproduction in other forums is permitted,
provided the original author(s) and the
copyright owner(s) are credited and that the
original publication in this journal is cited, in
accordance with accepted academic practice.
No use, distribution or reproduction is
permitted which does not comply with these
terms.
TYPE Original Research
PUBLISHED 12 May 2023
DOI 10.3389/fpsyg.2023.1158365

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Frontiers in Psychology 02 frontiersin.org
interaction with a conspecic (Evans etal., 1994; Borland etal., 2017;
Hiura et al., 2018; Vanderhoo et al., 2019; Beery et al., 2021;
Hackenberg etal., 2021; Chow etal., 2022; Kirkman etal., 2022; Smith
etal., 2023). Chief among the advantages of such operant methods is
their analytic precision. Measuring how much work an animal will
devote to obtaining social interaction, or how much it prefers one type
of social interaction to another, provide quantitative assessments of
relative reinforcement value. Moreover, such methods have
longstanding success in the quantitative analysis of non-social
reinforcers, and these can readily be brought to bear on social
reinforcement eects. For example, Hiura etal. (2018) showed that
social interaction with a social partner increased behavior on which it
was contingent, showing a reinforcement eect; the behavior
decreased when it no longer produced opportunities for social
interaction, showing an extinction eect. us, when studied with
methods with proven success in analyzing non-social reinforcement,
social interaction displays characteristics of reinforcers in general.
Subsequent research with operant demand-based methods has
been used to better quantify the value of social reinforcers, in much
the same way such methods have been used with non-social
reinforcers. In studies by Vanderhoo etal. (2019) and Chow etal.
(2022), for example, rats were given repeated opportunities to produce
social interaction as the xed ratio (FR) price (number of responses
to produce social interaction) increased systematically across blocks
of sessions. In both studies, the frequency of social interactions varied
inversely with its price, displaying the characteristic downward-
sloping demand functions seen with other reinforcers (Hursh and
Roma, 2016). Chow etal. (2022) also compared demand for social
interaction with demand for food reinforcers, and found that while
demand for both reinforcers declined with price, demand for social
interaction was more sensitive to FR price changes than demand for
food. Similar results were shown by Kirkman et al. (2022) using
demand-based choice procedures to assess reinforcer interactions.
Rats were given repeated choices between food and social interaction,
with the FR prices of the two reinforcers varied, separately and
together, across conditions. When the FR price of food increased
while the price of social interaction was held constant, more social
reinforcers were produced, suggesting that social interaction partially
substituted for the higher-priced food reinforcers. Both eects were
well described by an exponential model developed to quantify
reinforcer value (Hursh and Silberberg, 2008), but revised to include
zero levels of reinforcer production (Gilroy etal., 2021).
Prior research has also included an assessment of social
reinforcement magnitude, arranged as variations in social interaction
access time. Vanderhoo etal. (2019) found that in a majority of rats,
the shortest (10 s) social access time produced higher levels of
responding than the longest (60 s) access time. Similarly, Chow etal.
(2022) found that shorter durations of social access (in the range of
15–30 s) yielded higher levels of responding, on average, than both
shorter and longer durations. Complicating the interpretation of social
access duration, however, are the results of a subsequent choice test,
in which rats were indierent between a shorter (3.75 s) and much
longer (240 s) social access duration, suggesting that the eects of
social access time may beprocedure-dependent. Given such mixed
results of a key reinforcement variable, additional research on social
reinforcer magnitude eects is warranted.
Following Vanderhoo etal. (2019) and Chow at el. (2022), the
present experiment examined demand for social interaction as a
function of its duration, varied across conditions. Following Kirkman
etal. (2022), weused the Gilroy etal. (2021) Zero-Bounded Exponential
(ZBEn) model to improve the ts by handling data from sessions with
zero levels of social interaction.
IHSQ IHSQ e
AIHSQ QP
A
()
=
()
×
−
()
00
0
()
α
(1)
where
QA
is the consumption of commodity A, IHS is a log-like
scale
(log .. ))(IHSQQ=+
×+
10
00
2
05 02
51
,
Q0
represents the level of
demand at zero price, and α the rate of decline in relative consumption
with increases in (FR) price,
PA
, of commodity A.
P
ma
x
is dened as
the price at which the slope of the demand equaled −1 (i.e., where
demand changes from inelastic to elastic), and O
max
, the predicted
consumption at P
max
. Together, these parameters comprise quantitative
properties of reinforcer value, and are especially useful in comparisons
between dierent reinforcer dimensions, such as reinforcer magnitude,
and other variables that may inuence the value of social interaction.
Another such variable is social familiarity – whether the rats are
familiar with each other. Using similar operant methods, Hackenberg
etal. (2021) gave rats repeated choices between interacting with a
cagemate or a non-cagemate social partner. In a three-chamber
apparatus, lever presses on either of two levers by a rat in the middle
chamber opened an adjacent door, behind which either their cagemate
or non-cagemate rat was located. Across a series of conditions and side
reversals, consistent preference for the non-cagemate rat was observed
(17 of 18 conditions). is type of preference for less familiar over
more familiar social partners parallels ndings from social preference
tests in mice (Moy etal., 2004) and rats (Smith etal., 2015), although
procedural dierences limit more direct comparisons. In social
preference tests, the social partner rats are novel each trial and thus
truly unfamiliar, whereas in the operant choice procedures used by
Hackenberg etal. (2021) the social partner rats serve repeatedly in that
role across trials and sessions, and thus become increasingly familiar
over time. Moreover, in social preference tests, animals are typically
studied for only 10 min each and have only indirect contact (from
behind a mesh barrier), whereas in the operant procedures used by
Hackenberg etal. (2021), animals were studied for hundreds of trials over
dozens of sessions, and had direct contact with one another. Notably,
when social preference tests are extended to 180-min assessments, and
direct contact is permitted, the novelty preference typically seen with
mice and rats dissipates (Beery and Shambaugh, 2021), suggesting
perhaps that brief tests with indirect contact and longer tests with direct
contact are measuring dierent aspects of social preference. In light of
these dierent procedures and conicting ndings, it is necessary to
examine social novelty eects across dierent procedures.
e present study examined demand for social interaction
separately for cagemate and non-cagemate rats over extended time
periods – roughly 25 sessions each per social partner – and with
procedures permitting direct contact between rats. While these
procedures closely parallel those used by Hackenberg etal. (2021), it
is not a foregone conclusion that social preferences for the
non-cagemate rat will also bereected in the present demand-based
methods. In research with food and water-based reinforcers, demand-
based indices of reinforcement value are not always in alignment with
preference tests (Madden etal., 2007; Tan and Hackenberg, 2015).
Similarly, in research on social reinforcement, Beery et al. (2021)

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showed that social preference did not always predict social motivation:
Male prairie voles preferred familiar animals when given free access,
but did not work harder to produce access to a familiar animal in an
operant FR procedure, suggesting perhaps that choosing social
interaction (i.e., social preference) and working to produce social
interaction (i.e., social motivation) may bedierent aspects of socially-
reinforced behavior.
Given these potential disparities across procedures, it is useful to
compare behavior with social preference procedures, as in Hackenberg
etal. (2021), to behavior with social motivation procedures, like those
used eectively by Vanderhoo etal. (2019), Chow etal. (2022), and
Kirkman etal. (2022). Based on the consistent preference for the less
familiar rats reported by Hackenberg etal. (2021), one might predict
that demand curves for non-cagemate rats would beless elastic (less
sensitive to price) than those for more cagemate rats. If, on the other
hand, the two procedures are tapping into dierent aspects of
reinforcement value, there may beless alignment across procedures.
Either way, most useful at this stage of the research is detailed
parametric analyses. To that end, in the present study, wesystematically
explored demand and response output at three dierent social
interaction durations (10 s, 30 s, and 60 s) for cagemate and
non-cagemate rats on a within-subject basis, generating a total of 24
demand functions. is permits a quantitative behavioral-economic
analysis of social reinforcement value, and how it is aected by price,
social familiarity, and social reinforcement magnitude.
Method
Subjects
Twelve experimentally naïve female Sprague–Dawley rats (Rattus
norvegicus) served as subjects in the present study. Rats were pair-
housed in Ancare® transparent polycarbonate rodent cages (measuring
26.5 cm × 48.2 cm × 20.3 cm) in a temperature-controlled colony room,
with a 12-h light/dark cycle. Rats had free access to water, but food was
restricted 18–20 h prior to each session. Four rats from dierent cages
were arbitrarily assigned as focal rats (the rats with respect to which
the contingencies were arranged) and the other eight rats as social
target rats (the rats in the side chamber to which access was provided).
e social target rats were either housed with the focal rats outside of
the sessions (deemed cagemate rats) or with other rats not in the
experiment (non-cagemate rats). All procedures were in accord with
the Reed College Animal Care and Use Committee.
Apparatus
e apparatus consisted of two adjoined chambers
(31 cm × 25 cm × 22 cm) with Plexiglas barriers (see Figure 1). A
circular opening (7.5 cm in diameter) was cut into the Plexiglas
barriers between the le and center chambers. In its resting position,
the opening was blocked by a metal door hinged at the back of the
chamber; when operated, it opened upwards at a 90-degree angle. e
opening was further obstructed by a ap door, designed to permit
one-way access from the center to the le side chamber (but not vice
versa). e center chamber contained two levers
(5 cm × 1.5 cm × 1.5 cm, mounted 6 cm above the oor), and two
stimulus lamps (2 cm diameter, mounted 10.5 cm above the oor), but
only the le lever and stimulus lamp were used in the present
experiment. Positioned 3.5 cm below and equidistant between the two
levers was a food receptacle, into which 45-mg Bio-Serv® banana-
avored sucrose pellets were delivered from a MED Associates® pellet
dispenser located behind the center wall. Experimental events were
controlled and data recorded on a Windows®-based computer with
MED-PC® soware. Chamber surfaces were sprayed and wiped with
a sanitizer solution between sessions to reduce residual odors.
Preliminary training
Because the rats were experimentally naïve, some preliminary
training was needed prior to the experiment proper. In the initial
phase (four sessions), focal rats were placed into the center chamber
and the door between chambers was opened every 30 s, irrespective of
responding. If the rat entered the side chamber, the door was closed.
e rat was permitted 30 s to explore the side chamber, aer which it
was returned to the center chamber and the 30-s timer was reset. If the
rat did not enter the chamber within 10 s, the door was closed and the
timer reset. Initially, the ap on the door was taped open, permitting
free transit to the side chamber. Once the rats were entering the side
chamber consistently, wetrained them to enter through the ap door
by gradually lowering it across successive sessions. When the ap was
at least half closed, the cagemate of the focal rat was introduced into
the side chamber as a social target rat. e door continued to
beopened every 30 s, and once the side chamber was entered, the rats
had 30 s of social interaction time before the focal rat was returned to
the center chamber. e ap continued to belowered across successive
sessions, until the focal rat entered the side chamber reliably when the
ap was fully closed.
At this time, lever-press training commenced for three sessions,
in which presses on the le lever (closest to the door) were reinforced
by door openings, permitting social interaction with the social partner
in the side chamber. is lever pressing contingency was signaled by
a cue light about the le lever. e light was o during reinforcement
periods, during which responses produced no scheduled
consequences. is dierential contingency was arranged so that the
light would come to function as a discriminative stimulus (S+),
signaling when lever presses would open the door, and the absence of
light as an extinction stimulus (S−), signaling when lever presses were
ineective in door opening. Shaping methods were used, whereby
successive approximations to lever pressing were reinforced by door
opening. Such methods proved unsuccessful, however, as the social
partner rats in the side chamber learned to open the ap and enter the
center chamber. In an attempt to keep the rats in the side chamber,
wethen tried to restrain them in a harness (a method used eectively
with other rats in our laboratory, Hackenberg etal., 2021), but this also
failed to achieve the desired result in a timely manner, and
was abandoned.
We then trained lever pressing with food rather than social
access, using shaping methods described above. Establishing the food
as an eective reinforcer required restricting food access outside the
training sessions, and because the rats were pair housed, food was
restricted for both rats for 18–20 h prior to each session. When lever
pressing occurred consistently (3 sessions), the social target rat was
reintroduced in the side chamber, and the consequence of lever
pressing shied from food to social interaction. Each lever press
opened the door, permitting 30-s social interaction. Because the

Schulingkamp et al. 10.3389/fpsyg.2023.1158365
Frontiers in Psychology 04 frontiersin.org
social target rats were not restrained, the social interaction period
could occur in either chamber, depending on which rat initiated it.
us, while in theory either rat could initiate the social interaction,
in most cases it was initiated by the focal rat and occurred in the side
chamber. When both rats were together in either chamber, the door
was closed and the 30-s timer began, at the end of which the rats were
returned to their respective chambers for the next trial. If neither rat
initiated social interaction within 10 s, the door closed and the next
trial began. Because the rats were more active and more responsive
to training under food deprivation conditions, the food-restriction
methods remained in place for the remainder of the experiment. is
training phase was in place until responding was occurring reliably;
this required nine sessions for Rats 2, 3, and 4, and 13 sessions
for Rat 1.
Experimental procedures
e main experiment involved systematic manipulations of FR
price and duration of social interaction across six experimental
phases. More specically, demand functions were generated by
increasing the FR price across conditions at each of three dierent
social interaction durations (10 s, 30 s, and 60 s), rst (Part 1) with
cagemate rats and then (Part 2) with non-cagemate rats as social
targets. us, FR price was manipulated across blocks of sessions
(conditions), social interaction was manipulated across three dierent
phases (blocks of conditions) and social familiarity was manipulated
across two parts (blocks of phases). e demand functions in each of
the six phases began with several sessions at FR 1, and thereaer
increased across successive sessions until no social interactions were
produced in a session. is was followed by a return to FR 1 (baseline
sessions) in the subsequent phase (with a dierent social interaction
duration). Because responding could not bemaintained consistently
for Rat 1in Part 1 with the cagemate rat as social target, this rat
received a single session of food reinforcement on FR 1 (with no social
partner present) on the day prior to the baseline sessions in the three
phases of Part 1; these food-only sessions were not needed to maintain
responding in Part 2 conditions with the unfamiliar (non-cagemate)
rat, and so were discontinued.
Sessions lasted 30 min, and were conducted 5 days per week at
approximately the same time each day. Baseline (FR 1) conditions
remained in eect until responding was deemed stable via visual
inspection of daily response rates. e number of baseline sessions
and FR prices could thus vary across rats, depending on how long
responding took to achieve baseline stability and the FR price at which
responding failed to produce social interactions. Table1 shows the
range and sequence of conditions and the number of sessions
conducted at each. Due to a programming error, some of the data
from the initial 30-s reinforcement duration for Rats 2, 3, and 4 were
unavailable, and so this condition was replicated following the 60-s
duration condition for these 3 rats.
Analysis
e number of social interaction episodes was recorded each
session. Wealso recorded door openings, and while these measures
could potentially dier (i.e., door openings without either rat initiating
an interaction within 10 s), nearly all openings resulted in social
interaction. us, while only social interactions (i.e., obtained
reinforcers) were included in the analysis, the results would besimilar
had door openings (i.e., programmed reinforcers) been substituted for
interactions. To account for dierences in response opportunity across
the dierent social reinforcement durations, rate of social interaction
served as the main dependent variable, with active session time as the
denominator. Active session time was dened as time during which a
response was possible (i.e., any time the door was closed and the lever
cue light on). Because active session time data were unavailable for
Rats 2, 3, and 4 from the initial 30-s social reinforcement phase, only
data from the replicated conditions were included in the analysis.
Social interaction rate was modeled using the ZBEn model (Eq.1)
implemented with R Version 4.2.1 (R Core Team, 2022), generating
six separate curves per rat: three for social interaction duration (10,
30, and 60 s) under each of two familiarity conditions (cagemate or
non-cagemate). Four parameters obtained from the demand curve
model were analyzed: 𝑄0, the predicted consumption at zero price; 𝛼,
the rate of decline in relative consumption with increases in price, 𝑃
𝐴
;
𝑃𝑚𝑎𝑥, the predicted price at which the slope of the demand equals −1;
FIGURE1
Experimental apparatus, with components presented to scale. See text for additional details.

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and Omax, the predicted consumption at Pmax. e values of 𝑃𝑚𝑎𝑥 and
O
max
were obtained by numeric approximation using the tted
model parameters.
Results
Figure2 shows the demand functions (social interaction rate) as
a function of FR price for each rat (columns) and across the 3 social
interaction durations (rows) (e response and reinforcement rates
from which the demand functions were derived can befound in the
Supplementary material). e demand functions obtained with
cagemate and non-cagemate rats are shown as separate curves within
each panel. e rate of social interaction rate declined systematically
with price across all conditions for all rats, and was well described by
Eq.1, with mean R
2
= 0.91 (see Table2). Data from both parts of the
experiment were equally well described by Eq. 1: mean R
2
= 0.89
(range = 0.85–0.94) in Part 1 with cagemate rats and mean R2 = 0.93
(range = 0.91–0.95) in Part 2 with non-cagemate rats.
Table2 also shows parameter estimates for
Q0
, α,
P and O
ma
xm
ax
,,
as dened above. None of the main parameters of the model varied
systematically with either social familiarity or social interaction
duration. ese non-systematic eects are depicted graphically in
Figure3, which shows two sets of demand curves, one comparing Part
1 (cagemate rats) and Part 2 (non-cagemate rats), collapsed across the
three social interaction durations (top panels), and one comparing the
three social interaction durations, collapsed across both parts (bottom
panels) (ese are the same data shown in Figure2, but aggregated
dierently to focus on each variable separately). Neither variable
exerted consistent eects on demand for social interaction. ese
results were veried with linear contrast tests, averaged across the four
rats. First, with respect to social familiarity (top panels), there were no
signicant dierences in demand intensity (Q
0
) or demand elasticity
(α) between Part 1, with cagemate rats, and Part 2, with non-cagemate
rats, averaged across the three social interaction durations (
Q0
:
p = 0.471; α: p = 0.710). ere were some exceptions for Rats 3 and 4,
in that Q0 was higher with non-cagemate rats (see Table2, top panels
of Figure3), but the dierences were not seen for the other two rats.
Similarly, with respect to social interaction duration (see Table 2,
bottom panels of Figure3), there were also no signicant dierences
in the main parameters of the model across the three durations,
averaged across social familiarity (
Q0
: p = 0.805; α: p = 0.226).
Figure4 shows response output (responses per min) as a function
of FR price for each rat (columns) and across the three social
interaction durations (rows), with curve tting derived from Eq.1.
e functions for Part 1 (cagemates) and Part 2 (non-cagemates) are
shown as separate curves within each plot. e functions were
typically bitonic in form, increasing at moderate prices before
declining at the higher prices, corresponding to the inelastic portions
of the demand curves shown in Figure2, before declining at the higher
TABLE1 Sequence of conditions and number of experimental sessions per condition for each subject.
Rat Phase FR1 FR2 FR5 FR10 FR20 FR40 FR80
1
Cagemate,
10 s
4 1 1 1 – – –
2 8 1 1 1 1 – –
3 3 1 1 1 1 – –
4 6 1 1 1 1 1 –
1
Cagemate,
60 s
5 1 1 1 – – –
2 4 1 1 1 1 1 –
3 4 1 1 1 1 1 –
4 4 1 1 1 1 1 1
1
Cagemate,
30 s
4 1 1 1 1 – –
2 3 1 1 1 – – –
3 3 1 1 1 – – –
4 4 1 1 1 1 1 1
1
Non-cagemate,
30 s
4 1 1 – – – –
2 4 1 1 1 1 – –
3 3 1 1 1 1 1 –
4 4 1 1 1 1 1 –
1
Non-cagemate,
10 s
7 1 1 1 1 1 –
2 3 1 1 1 1 1 –
3 6 1 1 1 1 1 1
4 4 1 1 1 1 1 1
1
Non-cagemate,
60 s
4 1 1 1 1 – –
2 3 1 1 1 1 1 –
3 3 1 1 1 1 1 –
4 3 1 1 1 1 1 –

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prices. e functions from both parts of the experiment were well
described by Eq.1, but did not vary systematically with either social
familiarity or social interaction duration.
Figure5 shows the same data replotted with respect to social
familiarity (top panels), collapsed across the three social interaction
durations, and with respect to interaction duration (bottom panels),
collapsed across social familiarity. As with the demand functions
(Figure3), the response rate functions and maximum response output
(Omax) were consistently higher for Rats 3 and 4 with non-cagemate
rats than with cagemate rats, but these dierences were not observed
in the other two rats (see Table 2). Similarly, O
max
did not vary
systematically with social interaction duration, at either the individual
or group level (Figure5 bottom, Table2).
Discussion
e rate at which social interaction was produced declined
systematically with price, consistent with the law of demand, and with
a growing body of research aimed at quantifying social reinforcement
eects (Vanderhoo etal., 2019; Chow etal., 2022; Kirkman etal.,
2022; Smith etal., 2023). Both the individual and aggregate data were
well described by Eq.1 (Gilroy etal., 2021), an extension of Hursh and
Silberberg’s (2008) essential value model. Along with two other recent
studies of social demand (Vanderhoo etal., 2019; Kirkman etal.,
2022), the model accounts for over 90% of the variance describing 65
demand curves of 14 rats, across the three studies. More important
than the ts per se is the broad consistency of the results with those of
other operant-based demand methods applied to other species and
other reinforcers (Hursh and Roma, 2016; Strickland and Lacy, 2020).
is suggests that social reinforcement shares functional properties
with other reinforcers, and demonstrates the utility of behavioral
economic methods in characterizing them.
Despite the strong sensitivity to social interaction price, wedid
not nd systematic eects of social familiarity: demand and response
output for cagemate rats did not dier appreciably from demand and
response output for non-cagemate rats. Some between-subject
variability was evident, with hints of higher demand intensity (higher
Q
0
values) and response output (higher O
max
values) for some rats
responding for non-cagemates. Between-subject variability, however,
was such that strong claims cannot bemade. Moreover, because the
demand curves for non-cagemate rats were always generated aer the
demand curves for cagemate rats, any eects attributable to social
familiarity were confounded by order eects. Future research should
include reversal conditions and between-subject counterbalancing the
order of exposure to conditions, to disentangle order eects from
eects of social familiarity. It would also bebenecial to replicate with
a larger sample to determine whether the hints of sensitivity to social
familiarity seen with some rats are reliable.
e lack of a systematic eect of social familiarity stands
somewhat in contrast with prior research, in both directions – that is,
both with research showing higher value of cagemate over
non-cagemate (Chow etal., 2022, Experiment 2), as well as the
opposite (Hackenberg etal., 2021). In the Chow etal. (2022) stu dy,
response rates were higher for cagemate than for non-cagemate rats,
but only for rats housed alone outside the sessions. ere were no such
dierences for pair-housed rats, suggesting that social motivation may
have been higher for these socially isolated rats. In support of this
interpretation, prior research has shown social restriction enhances
social reinforcement eects (Varlinskaya and Spear, 2008; Hiura etal.,
FIGURE2
Social interaction rate (number of social interactions produced per min) as a function of FR price for each rat at all three social interaction durations,
along with the fits from Eq.1. The curves for familiar (cagemate) rats from Part 1 and for unfamiliar (non-cagemate) rats from Part 2 are indicated with
dierent symbols.

Schulingkamp et al. 10.3389/fpsyg.2023.1158365
Frontiers in Psychology 07 frontiersin.org
2018; Templer et al., 2018; Hackenberg etal., 2021). Such social
motivation eects would presumably beless pronounced for the pair-
housed rats in the present study, and may help explain the relative
insensitivity to social familiarity. Future research should further
explore the impact of social motivational eects on sensitivity to
social familiarity.
e lack of a systematic eect of social familiarity also diers from
what might bepredicted on the basis of choice procedures, where
consistent preference for non-cagemate over cagemate rats has been
found (Hackenberg etal., 2021). Perhaps single-alternative response-
output procedures used in the present study and concurrent-
alternative choice procedures used in prior research tap into dierent
aspects of social reinforcement value, as previous work with non-social
reinforcers has shown (Madden et al., 2007; Tan and Hackenberg,
2015). Our initial plan was to include a concurrent-choice phase
following the completion of the demand curves, permitting direct
within-subject comparisons. Although time constraints precluded this
part of the study, a direct comparison of demand and choice
procedures within the same study should be a major priority for
future research.
Especially promising in this regard would be concurrent
procedures used to assess cross-price demand elasticity, which have
proven useful in assessing interactions between qualitatively dierent
reinforcers, such as social interaction and cocaine (Smith etal., 2023)
and social interaction and food (Kirkman et al., 2022). In some
conditions in the Kirkman etal. (2022) study, for example, the price
of food reinforcement increased while the price of social interaction
was held constant at FR 1. As the price of food increased, demand for
food declined (own-price elasticity), while demand for social
interaction increased (cross-price elasticity). at is, as food became
more expensive and demand more elastic, social interaction served as
a partial substitute (Green and Freed, 1993) for the more expensive
food reinforcers. Such procedures would beespecially useful in a
quantitative assessment of own-price and cross-price elasticity with
cagemate and non-cagemate rats. In the prior research showing
preference for non-cagemate rats (Hackenberg etal., 2021), the costs
of social access were small (i.e., essentially only the rst part of a
demand curve) and preferences were non-exclusive (suggesting
perhaps some degree of substitution). Exploring the full demand
curves with cagemate and non-cagemate rats would permit a more
precise analysis of the degree to which each type of social interaction
comes to substitute for the other as their price and availability changes.
In the present study, and in most prior research, social familiarity
has been dened in terms of homecage housing conditions: cagemates
(more familiar) or non-cagemates (less familiar). It may be more
useful, however, to view social familiarity on a continuum, ranging
from an unfamiliar stranger at one end to a familiar live-in partner at
the other. In short-term procedures like the 10-min social preference
(Smith etal., 2015), the unfamiliar rat is truly novel. In long-term
procedures like the present, however, the non-cagemate rats are
unfamiliar only at the beginning of the experiment; over time and
experience with the procedures, they become increasingly more
familiar. Our focal rats, for instance, accumulated dozens of
interactions with the non-cagemate rat across Part 2 of the experiment
(25 sessions, on average, per rat). Clearly the non-cagemate rats
became quite familiar to the focal rats, even if somewhat less so than
the cagemate rats with whom they lived outside the sessions. Perhaps
the dierences between a familiar cagemate and a somewhat less
TABLE2 Model fits and parameter values for Eq.1.
Rat αQ0 Pmax Omax R2
Cagemate Non-
cagemate
Cagemate Non-
cagemate
Cagemate Non-
cagemate
Cagemate Non-
cagemate
Cagemate Non-
cagemate
1
10 Sec 1.17E-02 2.82E-03 47.96 46.34 1.11 4.78 15.99 66.34 0.98 0.85
30 Sec 4.72E-03 1.51E-02 55.10 53.98 2.36 1.00 39.42 12.02 0.97 0.90
60 Sec 6.15E-03 5.90E-03 57.83 35.18 1.72 3.12 30.17 32.19 0.87 0.98
Mean 7.52E-03 7.94E-03 53.63 45.17 1.73 2.97 28.53 36.85 0.94 0.91
2
10 Sec 2.34E-03 1.91E-03 68.03 75.03 3.77 4.15 78.81 96.17 0.87 0.97
30 Sec 3.27E-03 2.84E-03 94.05 65.05 1.89 3.26 55.66 65.02 0.73 0.88
60 Sec 1.86E-03 1.86E-03 82.28 79.15 3.85 4.00 98.41 98.27 0.98 0.99
Mean 2.49E-03 2.20E-03 81.45 73.08 3.17 3.80 77.63 86.48 0.86 0.95
3
10 Sec 3.05E-03 7.61E-04 51.31 93.27 3.95 8.21 61.18 239.53 0.82 0.98
30 Sec 2.53E-03 1.43E-03 126.63 47.53 1.77 9.20 71.31 131.11 0.75 0.87
60 Sec 3.17E-03 1.01E-03 28.95 144.51 7.25 3.87 60.43 178.57 0.98 0.98
Mean 2.92E-03 1.06E-03 68.96 95.10 4.32 7.09 64.31 183.07 0.85 0.94
4
10 Sec 1.31E-03 6.09E-04 39.09 73.80 12.50 13.25 144.38 301.94 0.97 0.94
30 Sec 1.13E-03 1.58E-03 25.02 58.54 24.00 6.59 170.81 117.46 0.83 0.91
60 Sec 2.31E-03 1.23E-03 18.01 63.73 17.07 7.69 85.28 149.99 0.89 0.90
Mean 1.58E-03 1.14E-03 27.37 65.36 17.85 9.18 133.49 189.79 0.90 0.92

Schulingkamp et al. 10.3389/fpsyg.2023.1158365
Frontiers in Psychology 08 frontiersin.org
familiar non-cagemate in the present study were simply too small to
produce an eect. Future research should further explore a wider
range of points along the social familiarity continuum between the
extremes of full-time cagemate and non-cagemate.
We also found no consistent eect of social interaction duration
(see bottom panels of Figures 3, 5). e reasons for the lack of
sensitivity to duration are unclear. One possibility is that the present
procedures were simply not suciently sensitive to detecting eects
of social reinforcement magnitude. With food reinforcers,
reinforcement magnitude eects are complex and somewhat
procedure dependent (Bonem and Crossman, 1988), in some cases
increasing and decreasing response rates within the same study (Reed,
1991). On the other hand, using procedures similar to those used here,
Vanderhoo etal. (2019) reported higher
Q0
and
P
max
values for 10-s
FIGURE3
Social interaction rate (number of social interactions produced per min) as a function of FR price for each rat, collapsed across the three social
interaction durations (top panels) and across social familiarity (bottom panels). The fits are from Eq.1. See text for additional details.
FIGURE4
Response output (number of responses per min) as a function of FR price for each rat at all three social interaction durations, along with the fits from
Eq.1. The curves for familiar (cagemate) rats from Part 1 and for unfamiliar (non-cagemate) rats from Part 2 are indicated with dierent symbols.

Schulingkamp et al. 10.3389/fpsyg.2023.1158365
Frontiers in Psychology 09 frontiersin.org
over 60-s social access durations in a majority of rats. Chow etal.
(2022) similarly found relatively shorter social access times yield
higher levels of responding than longer times, suggesting some
sensitivity to access duration. In subsequent choice tests, however,
Chow etal.’s rats were indierent between a short (3.75 s) and much
longer (240 s) social access times. at preferences were unaected by
such vast dierences in social access time suggests perhaps that much
of the reinforcing eect of social access occurs in the early portions of
the reinforcer period, and thereaer additional time contributes little
to social reinforcer value. Given the mixed patterns of results, future
research should continue to explore social interaction across a wider
range of durations using procedures better suited to detecting
duration eects.
Another possibility is that there is more to the magnitude of social
reinforcement than merely the duration of the interaction episode. In
addition to the quantity of social interaction, more attention should
bepaid to the quality of the social interaction episode (e.g., the types
of behavior it enables). A distinction has been made in prior research
between appetitive (social motivation and approach toward the social
stimulus) and consummatory (social contact and engagement with the
social stimulus) aspects of social interaction. e present analysis
focused exclusively on the former (i.e., the conditions responsible for
producing the social interaction), but a detailed analysis of the latter
(i.e., the behavior within the social interaction episode) would shed
meaningful light on the quality of the social interaction. Both are
necessary components in a comprehensive account of
social reinforcement.
In behavioral-economic demand analyses, the costs and benets
are typically operationalized in terms of eort (e.g., FR price) and
reinforcers consumed, respectively. Price changes also yield
concomitant changes in the delay to the reinforcer, however, so it is
possible to view the costs in terms of the time between reinforcers (i.e.,
the interreinforcement interval) in addition to the eort per reinforcer
(Schwartz and Hursh, 2022). Indeed, orderly demand functions have
been reported with time rather than eort as a constraint on
consumption (Bauman, 1991; Tsunematsu, 2001), and there is good
reason to suspect that the time between successive social reinforcers
would also yield orderly social demand functions. is could
be studied by future work by substituting interval for the ratio
schedules used in the present study.
It is also worth noting that when the amount of a reinforcer varies
across conditions, as in the present study, costs can becomputed as a
unit price (i.e., FR price divided by the reinforcer magnitude), yielding
a composite cost metric. is type of analysis has proven especially
useful in understanding drug eects on demand, where reinforcer
magnitude is dened in terms of drug dose (Strickland and Lacy,
2020), but can equally well beapplied to reinforcer duration. Wealso
analyzed the present data therefore with respect to unit price (i.e., FR
per social access time) in addition to the simple FR price. Because
there was no magnitude eect, however, the unit price analysis did not
alter the main results, and so wedid not pursue this further.
In the present study, weused only female rats, as wehave found
in our prior work with similar procedures that female rats are
somewhat more responsive than male rats to social reinforcement
eects (Vanderhoo et al., 2019). Prior research with males rats,
however, shows that social reinforcement eects are not limited to
females (Hiura etal., 2018; Heslin and Brown, 2021; Smith etal.,
2023). Indeed, Chow etal. (2022) compared male and female rats in
the same experiment, and found no dierences in response rate or
preference measures. Similarly, strain dierences do not seem to
matter, as both Long Evans and Sprague–Dawley strains (the two most
common rat strains studied in laboratory experiments) have been
used successfully in social reinforcement research. Nonetheless, future
research should continue to explore the conditions under which sex
and strain dierences may beseen.
Some previous research showing social reinforcement eects has
used a social-release procedure, in which the social target rat is
restrained in a tube and then released for a period of social interaction
FIGURE5
Response output (number of responses per min) as a function of FR price for each rat, collapsed across the three social interaction durations (top
panels) and across social familiarity (bottom panels). The fits are from Eq.1. See text for additional details.

Schulingkamp et al. 10.3389/fpsyg.2023.1158365
Frontiers in Psychology 10 frontiersin.org
(Silberberg etal., 2014; Hiura etal., 2018; Vanderhoo etal., 2019;
Wan etal., 2021; Kirkman etal., 2022). e use of the tube restraint
grew out of earlier research claiming that social release was due not to
social reinforcement, but rather, to an empathic concern for the
restrained rat (Ben-Ami Bartal etal., 2011). e weight of evidence
now clearly favors a social reinforcement view, not only on social-
release procedures (Hachiga etal., 2018; Blystad, 2019; Heslin and
Brown, 2021; Blystad and Hansen, 2022), but also on social-approach
procedures like those used in the present study and by Hackenberg
et al. (2021). Indeed, it is not even clear what an empathy-based
account would have to say about social approach, in which the animals
are unrestrained and not in any obvious state of distress that is
required by an empathy-based account. A social reinforcement
account, on the other hand, readily accommodates data from social-
approach procedures, and indeed, from any procedures that involve
contingent access to social stimuli, including mazes and place
preference tasks (Trezza etal., 2011).
e social-approach methods used here also better approximate
naturalistic conditions in which rats encounter one another outside
the laboratory. e procedures thus have greater ecological realism
than social-release procedures, in which each social access period
begins with the social stimulus rat inside a tube restraint, or social-
preference tests, in which the social stimulus rat is behind a mesh
partition. A potential concern with the social-approach methods used
here was that, because they do not specify the location or behavior of
the social stimulus rat at the start of the social access period, social
contact may bedelayed and therefore less reinforcing than in social-
release methods, in which the social interaction is initiated in the same
way every trial. A related concern was that because the social stimulus
rats learned to operate the ap door and thus could initiate the social
contact with the focal rat, that the results may somehow dier from
prior results in which the social contact was unidirectional. ese
concerns were unfounded, however, as the reinforcing eects of social
interaction were comparable in the present study with other recent
ndings with social-release methods (Vanderhoo et al., 2019;
Kirkman etal., 2022). e enhanced ecological realism that comes
from social approach methods thus fortunately does not come at the
expense of quantitative rigor.
In sum, wefound that opportunities for social interaction served
as eective reinforcers for rats, adding to an expanding literature on
social reinforcement eects in rodents (Borland et al., 2017;
Vanderhoo etal., 2019; Beery etal., 2021; Wan etal., 2021; Kirkman
etal., 2022; Vahaba etal., 2022; Smith etal., 2023). Future research
should include a wider range of species, including but not limited to
rodents. Even amongst rodents, there are notable inter-species
dierences in social relationships related to dierences in social
ecology (Beery and Shambaugh, 2021), and a broader comparative
approach that includes non-traditional species (i.e., those not typically
studied in laboratory environments) is essential to a comprehensive
understanding of social behavior in all its diversity (Taborsky etal.,
2015). At the same time, the use of more traditional laboratory species,
such as rats, can play a signicant role as well, elucidating proximal
mechanisms, as both the behavior and neurobiology of rats are well
studied. And when combined with a functional approach regarding
the evolution and social ecology of the species (Schweinfurth, 2020),
the laboratory analysis of a traditional model organism like the rat can
make meaningful contributions to a comparative approach.
Standardized methods for analyzing and quantifying social
motivation, like those used in the present study, should prove
especially valuable tools in building the types of predictive testable
models needed for an integrated cross-species approach to social
behavior (Taborsky etal., 2015).
Data availability statement
e original contributions presented in the study are included in
the article/Supplementary material. Further inquiries can bedirected
to the corresponding author.
Ethics statement
e animal study was reviewed and approved by Reed College
Animal Care and Use Committee.
Author contributions
RS and TH collaborated in the design and conduct of the
experiment. RS, TH, and HW collaborated on the analyses and
contributed to the writeup. All authors contributed to the article and
approved the submitted version.
Funding
e research was part of a Senior esis by RS, and was supported
in part by a Research Initiative Grant from Reed College. e authors
are indebted to Greg Wilkinson for his expert technical assistance, and
to Jon Rork for comments on an earlier version of the paper. All
procedures were in accord with the Reed College Institutional Animal
Care and Use Committee.
Conflict of interest
e authors declare that the research was conducted in the
absence of any commercial or nancial relationships that could
beconstrued as a potential conict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their aliated organizations,
or those of the publisher, the editors and the reviewers. Any product
that may be evaluated in this article, or claim that may be made by its
manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
e Supplementary material for this article can befound online
at: https://www.frontiersin.org/articles/10.3389/fpsyg.2023.1158365/
full#supplementary-material

Schulingkamp et al. 10.3389/fpsyg.2023.1158365
Frontiers in Psychology 11 frontiersin.org
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