Introduction to Neuroscience: Systems Neuroscience – Concepts
NEUROSCIENCE Spatial representations of self and other in ... · NEUROSCIENCE Spatial...
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NEUROSCIENCE Spatial representations of self and other in the hippocampus Teruko Danjo, 1 Taro Toyoizumi, 2 Shigeyoshi Fujisawa 1 * An animal’ s awareness of its location in space depends on the activity of place cells in the hippocampus. How the brain encodes the spatial position of others has not yet been identified. We investigated neuronal representations of other animals’ locations in the dorsal CA1 region of the hippocampus with an observational T-maze task in which one rat was required to observe another rat’ s trajectory to successfully retrieve a reward. Information reflecting the spatial location of both the self and the other was jointly and discretely encoded by CA1 pyramidal cells in the observer rat. A subset of CA1 pyramidal cells exhibited spatial receptive fields that were identical for the self and the other.These findings demonstrate that hippocampal spatial representations include dimensions for both self and nonself. S patial navigation requires the hippocampus (1, 2). The cognitive map theory states that spatial recognition in the hippocampus is allocentric (3–5). Place cells in the hippo- campus are the physiological correlate of this representation because they are highly sensi- tive to changes in landmarks and contexts (6–13). The characterization of additional types of navi- gational representations, including head-direction cells and grid cells, has promoted our understand- ing of the neural mechanisms of allocentric spatial representations in the hippocampal-entorhinal cortex network (14–19). The studies of these neural maps have focused on the animal’ s own position in space. It still remains unclear whether and how spatial information of nonself, such as the position of conspecifics, landmarks, and moving objects, is represented in the hippocampus. We designed an observational T-maze task using a pair of rats (hereafter termed “self” and “other”) and investigated how the other’ s position is represented in the self’s hippocampus. The self was required to make a left/right choice to re- trieve a reward based on the location of the other. We used two versions of the task, an “opposite- side rule” version in which the self rat had to choose the side opposite to the other’s location (Fig. 1A, fig. S1, and movie S1) and a “same-side rule” in which the self rat had to choose the same side as the other rat (fig. S1 and movie S2). During the T-maze task, neuronal activity in the self’s hippocampus (dorsal CA1) was recorded extra- cellularly (n = 3 pairs of rats; 88 ± 8.1% and 84 ± 11% correct performance with opposite-side and same-side rules, respectively). All analyses were performed on single units with pyramidal cell features and place fields in the task area (n = 1298 and 1205 units with opposite-side and same- side rules, respectively) (fig. S2) [see the supple- mentary materials (SM)]. We first examined how the location of the other rat was represented in the opposite-side rule observational task. Firing-rate maps of the self’s positions (“self’s rate map”) and the other’s positions (“other’ s rate map, ” which were obtained by replacing the self’s positional data with the other’s) revealed that in addition to the expected coding of the observer’s own position in space, the majority of units also displayed obvious place fields for the other (Fig. 1, C to F, top). To under- stand the positional relationship of the rat pair at the time of firing, we constructed joint rate maps by linearizing the rats’ trajectories and entering them into two-dimensional x-y axes (fig. S3). Here, the self’s and other’s place fields composed from identical spikes were combined into a sin- gle joint place field (Fig. 1, C to F, bottom, and fig. S4). We then examined whether these joint place fields were truly modulated by the other’s positions and not a mere consequence of the constraints in the positional relationships of the two rats. The null hypothesis was that the firing only depended on the self’s position and was independent of the other’s. By computing the surrogate firing rates that followed this null hypothesis (see the SM) (20), we identified areas with significantly higher firing rates for the other (P < 0.05) (Fig. 1, C to F, third from top, and fig. S5). A significant firing dependency on the other’s positions was detected for 85% of units (Fig. 1, G to I), indicating that the other’s spatial information was generally encoded by the place cells in this T-maze task. Importantly, the sig- nificant areas were not dependent on the self’s specific behavior or the other’s positions (Fig. 1, C to I). Moreover, the firing activities of most units were not dependent on the time periods in the trial (fig. S6). Similar results were also observed when we analyzed the same-side rule version of the task (fig. S7). In the hippocampus, spatial information is en- coded not only by the average firing rates of the neurons but also by the timing of the spikes with respect to the phase of the underlying theta os- cillations (7 to 11 Hz) (21–24). We next examined this temporal coding in the other’s spatial repre- sentations. To control for confounds of the mo- tion of the observer, we focused on units whose rate peaks were located in the self’s starting po- sitions in the opposite-side rule and analyzed the relationship between the other’s positions and the theta phases of the spikes (n = 78 units). Although the self was not running during the time course of this analysis, the local field po- tential was dominated by theta oscillations (fig. S8 and SM). In contrast to the lack of theta- phase precession relative to the self’s location, 75% of the units displayed significant theta- phase precession as a function of the other’s location (P < 0.01) (Fig. 1, J to M). The observed theta-phase precession to the other’s location was consistent with that to the self’s location, as reported previously (21–24), demonstrating that the other’s spatial information was also temporally encoded in the hippocampal pyram- idal cells. We next sought to dissociate two types of units—those preferentially modulated by the other’s position (“other-preferred cells”) and those preferentially modulated by the self’s goal [“goal-preferred cells,” also previously described as “prospective cells” (25, 26)]. We took advan- tage of the two versions of our observational T-maze task (Fig. 2A). Other-preferred cells fire when the other is located on the same side of the side arms (left or right), irrespective of the rule during a given trial and, as a result, these neurons fire when the self’ s goal is on a different side across the two conditions (Fig. 2B). This should further support the allocentric representation of the other’s place. In contrast, goal-preferred cells increase their firing rate only according to the future choice of the observer. By statistically comparing the other’s rate maps between the two versions, we defined other-preferred cells and goal-preferred cells based on these criteria (see the SM). We identified 58 other-preferred cells (Fig. 2, C to G, and fig. S9) and 252 goal-preferred cells (Fig. 2, H and I). Although the number of other-preferred cells was smaller than that of goal-preferred cells, it represented 13% of the place-responsive units examined in this analysis (Fig. 2F and SM), and the firing-rate peaks of both unit groups distributed all along the side arms in the other’ s rate maps, constituting a full spatial map based on the position of the other rat (Fig. 2, G and I). Furthermore, the analysis of comparing the correct and the error trials in the opposite- side rule resulted in similar percentages of other- preferred and goal-preferred cells (fig. S10). We next looked for another type of spatial representation, “a common place field” for the self and other, for which a unit fires when either the other or the self is in a specific spatial loca- tion. We found 45 units that had common place fields in both the other’s and the self’s rate maps under the opposite-side rule (Fig. 3, A to E, and SM). We further tested the trajectory specificity of common place fields by separating left- and right-side targeting trials. Notably, we identified 51 of 1244 units in the opposite-side rule task RESEARCH Danjo et al., Science 359, 213–218 (2018) 12 January 2018 1 of 6 1 Laboratory for Systems Neurophysiology, RIKEN Brain Science Institute, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan. 2 Laboratory for Neural Computation and Adaptation, RIKEN Brain Science Institute, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan. *Corresponding author. Email: [email protected] on May 21, 2020 http://science.sciencemag.org/ Downloaded from
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NEUROSCIENCE
Spatial representations of self andother in the hippocampusTeruko Danjo,1 Taro Toyoizumi,2 Shigeyoshi Fujisawa1*
An animal’s awareness of its location in space depends on the activity of place cells inthe hippocampus. How the brain encodes the spatial position of others has not yet beenidentified. We investigated neuronal representations of other animals’ locations in thedorsal CA1 region of the hippocampus with an observational T-maze task in which onerat was required to observe another rat’s trajectory to successfully retrieve a reward.Information reflecting the spatial location of both the self and the other was jointly anddiscretely encoded by CA1 pyramidal cells in the observer rat. A subset of CA1 pyramidalcells exhibited spatial receptive fields that were identical for the self and the other. Thesefindings demonstrate that hippocampal spatial representations include dimensions forboth self and nonself.
Spatial navigation requires the hippocampus(1, 2). The cognitivemap theory states thatspatial recognition in the hippocampus isallocentric (3–5). Place cells in the hippo-campus are the physiological correlate of
this representation because they are highly sensi-tive to changes in landmarks and contexts (6–13).The characterization of additional types of navi-gational representations, includinghead-directioncells and grid cells, has promoted our understand-ing of the neuralmechanisms of allocentric spatialrepresentations in the hippocampal-entorhinalcortex network (14–19). The studies of these neuralmaps have focused on the animal’s own positionin space. It still remains unclear whether andhow spatial information of nonself, such as theposition of conspecifics, landmarks, and movingobjects, is represented in the hippocampus.We designed an observational T-maze task
using a pair of rats (hereafter termed “self” and“other”) and investigated how the other’s positionis represented in the self’s hippocampus. The selfwas required to make a left/right choice to re-trieve a reward based on the location of the other.We used two versions of the task, an “opposite-side rule” version in which the self rat had tochoose the side opposite to the other’s location(Fig. 1A, fig. S1, and movie S1) and a “same-siderule” in which the self rat had to choose the sameside as the other rat (fig. S1 andmovie S2). Duringthe T-maze task, neuronal activity in the self’shippocampus (dorsal CA1) was recorded extra-cellularly (n = 3 pairs of rats; 88 ± 8.1% and 84 ±11% correct performance with opposite-side andsame-side rules, respectively). All analyses wereperformed on single units with pyramidal cellfeatures and place fields in the task area (n =1298 and 1205 unitswith opposite-side and same-
side rules, respectively) (fig. S2) [see the supple-mentary materials (SM)].We first examined how the location of the
other rat was represented in the opposite-siderule observational task. Firing-rate maps of theself’s positions (“self’s ratemap”) and the other’spositions (“other’s ratemap,”whichwere obtainedby replacing the self’s positional data with theother’s) revealed that in addition to the expectedcoding of the observer’s own position in space,themajority of units also displayed obvious placefields for the other (Fig. 1, C to F, top). To under-stand the positional relationship of the rat pair atthe time of firing, we constructed joint rate mapsby linearizing the rats’ trajectories and enteringthem into two-dimensional x-y axes (fig. S3).Here, the self’s and other’s place fields composedfrom identical spikes were combined into a sin-gle joint place field (Fig. 1, C to F, bottom, andfig. S4). We then examined whether these jointplace fields were truly modulated by the other’spositions and not a mere consequence of theconstraints in the positional relationships ofthe two rats. The null hypothesis was that thefiring only depended on the self’s position andwas independent of the other’s. By computingthe surrogate firing rates that followed this nullhypothesis (see the SM) (20), we identified areaswith significantly higher firing rates for theother (P < 0.05) (Fig. 1, C to F, third from top, andfig. S5). A significant firing dependency on theother’s positions was detected for 85% of units(Fig. 1, G to I), indicating that the other’s spatialinformationwas generally encoded by the placecells in this T-maze task. Importantly, the sig-nificant areas were not dependent on the self’sspecific behavior or the other’s positions (Fig. 1,C to I). Moreover, the firing activities of mostunits were not dependent on the time periodsin the trial (fig. S6). Similar results were alsoobserved when we analyzed the same-side ruleversion of the task (fig. S7).In the hippocampus, spatial information is en-
coded not only by the average firing rates of theneurons but also by the timing of the spikes withrespect to the phase of the underlying theta os-
cillations (7 to 11 Hz) (21–24). We next examinedthis temporal coding in the other’s spatial repre-sentations. To control for confounds of the mo-tion of the observer, we focused on units whoserate peaks were located in the self’s starting po-sitions in the opposite-side rule and analyzedthe relationship between the other’s positionsand the theta phases of the spikes (n = 78 units).Although the self was not running during thetime course of this analysis, the local field po-tential was dominated by theta oscillations (fig.S8 and SM). In contrast to the lack of theta-phase precession relative to the self’s location,75% of the units displayed significant theta-phase precession as a function of the other’slocation (P < 0.01) (Fig. 1, J to M). The observedtheta-phase precession to the other’s locationwas consistent with that to the self’s location,as reported previously (21–24), demonstratingthat the other’s spatial information was alsotemporally encoded in the hippocampal pyram-idal cells.We next sought to dissociate two types of
units—those preferentially modulated by theother’s position (“other-preferred cells”) andthose preferentiallymodulated by the self’s goal[“goal-preferred cells,” also previously describedas “prospective cells” (25, 26)]. We took advan-tage of the two versions of our observationalT-maze task (Fig. 2A). Other-preferred cells firewhen the other is located on the same side ofthe side arms (left or right), irrespective of therule during a given trial and, as a result, theseneurons fire when the self’s goal is on a differentside across the two conditions (Fig. 2B). This shouldfurther support the allocentric representationof the other’s place. In contrast, goal-preferredcells increase their firing rate only according tothe future choice of the observer. By statisticallycomparing the other’s rate maps between thetwo versions, we defined other-preferred cells andgoal-preferred cells based on these criteria (seethe SM). We identified 58 other-preferred cells(Fig. 2, C to G, and fig. S9) and 252 goal-preferredcells (Fig. 2, H and I). Although the number ofother-preferred cells was smaller than that ofgoal-preferred cells, it represented 13% of theplace-responsive units examined in this analysis(Fig. 2F and SM), and the firing-rate peaks of bothunit groups distributed all along the side arms inthe other’s rate maps, constituting a full spatialmap based on the position of the other rat (Fig. 2,G and I). Furthermore, the analysis of comparingthe correct and the error trials in the opposite-side rule resulted in similar percentages of other-preferred and goal-preferred cells (fig. S10).We next looked for another type of spatial
representation, “a common place field” for theself and other, for which a unit fires when eitherthe other or the self is in a specific spatial loca-tion. We found 45 units that had common placefields in both the other’s and the self’s ratemapsunder the opposite-side rule (Fig. 3, A to E, andSM). We further tested the trajectory specificityof common place fields by separating left- andright-side targeting trials. Notably, we identified51 of 1244 units in the opposite-side rule task
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Danjo et al., Science 359, 213–218 (2018) 12 January 2018 1 of 6
1Laboratory for Systems Neurophysiology, RIKEN BrainScience Institute, 2-1 Hirosawa, Wako, Saitama, 351-0198,Japan. 2Laboratory for Neural Computation and Adaptation,RIKEN Brain Science Institute, 2-1 Hirosawa, Wako, Saitama,351-0198, Japan.*Corresponding author. Email: [email protected]
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Danjo et al., Science 359, 213–218 (2018) 12 January 2018 2 of 6
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Fig. 1. Joint spatial representations of self and other in theobservational task. (A) Schematic of the opposite-side rule. Seefig. S1A. (B) Schematic of linearizing the trajectories on the T-maze.See figs. S3 and S4. (C to F) Units whose firing rates significantlydepended on the other’s position. (Top) Other’s (left) and self’s (right)rate maps. (Second from top) Trajectory plots of other (left) andself (right). Gray lines, rats’ trajectories; red dots, spike positions.(Third from top) Linearized rate plots on other’s position (black lines).Red lines indicate statistically significant bands (P < 0.05) (see fig. S5).Blue thick line indicates the significant area. (Bottom) Joint ratemaps. Other’s and self’s linearized positions are coordinated in
horizontal and vertical axes, respectively. The maximum firing rate isindicated at the top of each map. (G to I) Linearized and normalized ratemaps based on the other’s position (G), the self’s position (H), and thesignificant area on the other’s position (I), sorted by maximum ratepositions on the other’s map (n = 1298 units). (J to L) Units withtheta-phase precession based on the other’s position. (Top) Self’s ratemaps (left), linearized rate plots, and theta phases of the spikes as afunction of self’s position (right). (Bottom) Other’s rate maps (left),linearized rate plots, and theta phases of the spikes as a function of other’sposition (right). (M) Correlation between theta phase and the other’sposition. Color bars indicate significant correlation (P < 0.01; n = 59 units).
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that had trajectory-specific common place fields(Fig. 3, F and G; fig. S11; and SM), which wassignificantly higher than the number expectedby chance (P < 0.05) (see SM).Because the allocentric representation of self’s
place was also demonstrated by reliable recon-struction of self’s positions only from the spikesof place-cell ensembles (27, 28), we further testedwhether the spikes of joint-place-cell ensemblescould also reconstruct the other’s positions. First,we performed Bayesian decoding analysis witha leave-one-out strategy in each rule (SM). The
reconstructed other’s trajectories revealed thatthe spikes of joint-place-cell ensembles containedsufficient information regarding the other’s po-sitions (Fig. 4A and fig. S12A). Although the er-ror distances between the actual and decodedpositions were larger for the other’s decodingthan those for the self, the differences in theerror distances were as small as 5 cm per timewindow (200 ms) in both rules (other’s versusself’s error distances, 20.3 versus 16.1 cm in theopposite-side rule, 20.1 versus 15.1 cm in the same-side rule) (Fig. 4B). We then examined whether
these spikes contained more information aboutthe other’s place than that obtained by distribu-tions of time spent in the positional relationshipsof the self and the other. We computed a controlestimation of the other’s positions by reconstruct-ing the self’s positions and then accordinglyreferring to the probability distributions of thepositional relationships (fig. S12B and SM). Forthe Bayesian reconstructions in this analysis,the prior templates were computed from trialsincluding both rules, and results were examinedbased on error distances in a block-wisemanner
Danjo et al., Science 359, 213–218 (2018) 12 January 2018 3 of 6
Fig. 2. Spatial representa-tions of other-preferredand goal-preferred cells.(A) Schematic of the relation-ship of the other’s positionand the self’s goal in opposite-side and same-side rules.(B) Schematic explainingother-preferred cells (left)and goal-preferred cells(right). Other-preferredcells fire preferentially whenthe other is on the same side,regardless of the rule. Simi-larly, goal-preferredcells fire when the self’sgoal is on the same side.(C to E) Rate maps ofother-preferred cells.(Top) Other’s rate mapsin the opposite-side rule(left) and same-side rule(right). (Bottom) Self’s ratemaps in the opposite-siderule (left) and the same-siderule (right). See fig. S9for statistical methods.(F) Summary of other-preferred cells and goal-preferred cells (n = total434 units). (G) Linearizedand normalized ratemaps of other-referredcells, sorted by peak ratepositions. (H) Other’s (top)and self’s (bottom) rate mapsof goal-preferred cells in theopposite-side rule (left)and the same-side rule(right). (I) Linearized andnormalized other’s ratemaps of goal-preferred cellsin the opposite-side task(left) and same-side task(right), sorted by themaximum rate positions.
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(Fig. 4, C and D, and SM). Reconstructing trajec-torieswithout rule information apparentlymadethe error distances of the other’s decoded posi-tions larger, but they were significantly smallerthan the control estimate of the other’s positions(Fig. 4D). The overall averages of the error dis-tances of the other’s decoding were less than40 cm and also were significantly smaller thanthose of the control estimation in both rules(Fig. 4E).
We propose an extended model of hippocam-pal spatial representations that can include di-mensions for both self and other (fig. S13). Ourmodel, encompassing various types of spatialrepresentations, can categorize spatial represen-tations into four types: own place fields, jointplace fields, other’s place fields, and commonplace fields (fig. S13, A to D). In particular, thecommon place field could be hypothesized to beamirror representation of place (29, 30). Combi-
natorial representations of spatial informationof self and nonself would open the door to exam-ining whether this allocentric spatial represen-tation extendsmore generally to other nonlivingmoving objects (31–33) and how it is generatedin the hippocampal-entorhinal cortex network.Our data indicate that the place cells in the hip-pocampus encode sufficient spatial informationfor organizing the recognition of other animals,which is essential for social behavior (34, 35).
Danjo et al., Science 359, 213–218 (2018) 12 January 2018 4 of 6
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Fig. 3. Common place fields in self’s and other’s rate maps. (A to C)Common place fields of representative units in the other’s (left) andthe self’s (middle) rate maps. (Right) The products (element-wisemultiplications) of normalized other’s and self’s firing rates in each pixel.(D) Linearized other’s (left) and self’s (middle) firing rates and theirproducts (right). The products are the element-wise multiplications of thenormalized firing rates of the self and the other at each position, of theunits shown in (A) to (C). This value was used to identify units withcommon place fields. (E) Linearized and normalized rate maps of units
with common place fields aligned by the position with the maximumvalue of the products (n = 45 of 908 units). (F and G) Trajectory-specificcommon place fields of two representative units. (Left) Other’s (top) andself’s (bottom) rate maps of whole trials. (Middle) Rate maps with the left andright trials separated. (Right) The products of normalized other’s and self’sfiring rates of right (top) and left (bottom) targeting trials in each pixel.Arrows indicate the centers of common place fields. The maximum colorvalue of the product map was set as 0.5, and the values in the product mapindicate the maximum of the product.
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Fig. 4. Decoding other’s and self’s positions from spikes of hippocampalcells. (A) Reconstructed other’s and self’s positions in the opposite-siderule. Red and blue lines, reconstructed other’s and self’s positions,respectively. Black lines, actual trajectories of the other or self. (B) Meanerror distances between actual and decoded positions (31 and 28 sessionsfrom the opposite-side and same-side rules, respectively). (C to E) Thereconstructions of other’s positions by using prior templates calculated fromtrials including both rules. (C) Schematic of the division of other’s trajectories
into six blocks. (D) Error distances of reconstructed other’s positions in eachblock. Red bars, distance between the actual and decoded other’s positions.Gray bars, distance between the actual and estimated other’s positions(n = 22 sessions) (two-way repeated measures analysis of variance: P < 0.001,F5 = 83.95 for the opposite-side rule; P < 0.001, F5 = 72.6 for the same-siderule). (E) Averaged error distances per block (two-tailed paired t test: P <0.001, t21 = –10.70 for the opposite-side rule; P < 0.001, t21 = –10.95 for thesame-side rule). Data are mean ± SEM.
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ACKNOWLEDGMENTS
We thank A. Amarasingham for helpful suggestions on dataanalysis and T. J. McHugh and C. Yokoyama for comments on themanuscript. This work was supported by Japan Society for thePromotion of Science Grants-in-Aid for Scientific Research(KAKENHI) nos. 16K14561 and 16H01290 to T.D. and 15H05876 and
16H01519 to S.F. All data necessary to support the paper’sconclusions are present in the paper and the supplementary materials.
SUPPLEMENTARY MATERIALS
www.sciencemag.org/content/359/6372/213/suppl/DC1Materials and MethodsFigs. S1 to S13Movies S1 and S2References (36–41)
14 July 2017; accepted 7 December 201710.1126/science.aao3898
Danjo et al., Science 359, 213–218 (2018) 12 January 2018 6 of 6
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Spatial representations of self and other in the hippocampusTeruko Danjo, Taro Toyoizumi and Shigeyoshi Fujisawa
DOI: 10.1126/science.aao3898 (6372), 213-218.359Science
, this issue p. 213, p. 218Scienceconspecifics in rat and bat brains, respectively.
now report the discovery of a subgroup of neurons in hippocampal area CA1 that encodes the presence ofet al.Omer andet al.Surprisingly, very little is known about how the position of other animals is represented in the brain. Danjo
need to know the position of other individuals for social interactions, observational learning, and group navigation. Different sets of neurons encode the spatial position and orientation of an organism. However, social animals
The representation of others in space
ARTICLE TOOLS http://science.sciencemag.org/content/359/6372/213
MATERIALSSUPPLEMENTARY http://science.sciencemag.org/content/suppl/2018/01/11/359.6372.213.DC1
CONTENTRELATED http://science.sciencemag.org/content/sci/359/6372/218.full
REFERENCES
http://science.sciencemag.org/content/359/6372/213#BIBLThis article cites 40 articles, 9 of which you can access for free
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