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Boechorststraat Marcus der by Van Edited Universiteit, Vrije Sciences, Movement and Behavioural of Faculty Psychology, a brain human Knapen Tomas the throughout processing retinotopic task-dependent reveals connectivity Topographic HP Tdtsto 7 ujcsi hc aawr col- were data which in subjects PNAS 174 of dataset 7T com- (HCP) to used and experiments be for across can states. estimated processing cognitive RC be visual–spatial explained can Thus, detailed the RC are pare paradigm. into activations, responses V1 experimental ongoing brain of of any since retinotopy function Finally, In a the brain. as coordinates. project the space to of visual us the rest into allows throughout because back patterns RC Second, RC translated effect, robust is world. space, be is visual frame outside can of the reference RC brain map not its First, a and because harbors V1. brain V1 movements, of the eye in surface of pat- fixed spatial the face the the on of in activation terms responses in of which explained processing There in tern are 1A). visual (RC), brain connectivity (Fig the assessing retinotopic throughout cortex to of cerebral advantages means the by distinct of several region are visual (4–6), first V1 with the connectivity specific topographically on based fied experiments. mapping retinotopic not the traditional outside of are falls scope function inputs visual likely high-level visual especially therefore charting is life that It eye demands. everyday continuous cognitive dynamic by in and characterized movements is Yet, vision maps 3). naturalistic and retinotopic (2, sparse, delineate brain and the space elicited in visual the to relate to responses researchers brain locations field. allowing stimu- visual fixation, neighboring visual during the sparse is, lation in leverage That locations experiments (1). mapping neighboring Retinotopic represent retina brain the the of in according layout organized the retinotopic: to is processing vision, modality, O field pnz etefrNuomgn,RylNtelnsAaeyo cecs ebrdef7,10 KAsedm h ehrad;and Netherlands; The Amsterdam, BK 1105 75, Meibergdreef Sciences, of Academy Netherlands Royal , for Centre Spinoza efre Caayi nteHmnCnetm Project Human the on analysis RC performed I identi- be can brain the throughout processing Retinotopic | in riigtruhtesne.I u oiatsensory impres- dominant on our In based senses. ultimately the is through world arriving sions the of experience ur 01Vl 1 o e2017032118 2 No. 118 Vol. 2021 auaitcvision naturalistic | hippocampus a,b,1 | onciefield connective | ouainreceptive population doi:10.1073/pnas.2017032118/-/DCSupplemental ulse eebr2,2020. 28, December Published at online information supporting contains article This 1 under distributed BY).y is (CC article access open This Submission.y Direct PNAS a is article This interest.y new competing no contributed declares author paper. research, y The the wrote performed and data, research, analyzed tools, designed reagents/analytic T.K. contributions: Author stimulation, task, experimental state. in cognitive and variations strength against participants and This robust across stable structure and location. both the are same connectivity cortex retinotopic the this visual of in low-level borders in their that means with similar, V2, are acquisi- in tions resting-state maps and field movie-watching, 1 visual retinotopic-mapping, (Fig. feature visual of beyond into or structure and parameters the V3, contrast, reveals CF overall locations best-fitting field arousal, the null corrects by Translating This 1D), energy. driven (Fig. model. course responses null time for average nontopographic V1’s performance a prediction, prediction model with model correlation (CV) for connectivity, cross-validated the topographic correct that specific ensure I fits spatially To only 1C). One captures (Fig. response (5). brain model to the (BOLD) (CF) throughout predictions dependent courses field time-course level time sur- model connective oxygenation that the comparing blood its on by ongoing posits 1B), model patch CF (Fig. RC Gaussian the V1 localized for of a face model from arise computational responses parsimonious A on depend Results representations visual how Moreover, state. visual. reveal cognitive considered analyses traditionally represented—even not these is regions space brain visual brain, how in of the quantification throughout previ- the processing and of visual–spatial movie- identification unknown the and ously allowed This resting-state, experiments. retinotopic-mapping, watching during lected mi:[email protected]. y Email: estosadmmr neeya iinadmna life. of mental operation and vision joint everyday the in memory to and speaks sensations hippocampus default-mode in and thought organization network traditionally visual out- regions This memory. brain This regions to in cortex. devoted in system, visual visual also primary the processing of side organized surface visually the on revealed explaining terms pattern by in the experiments activations several of during retinotopic signals surround- discover BOLD complex brain-wide I our from Here, meaning ings. derive and movements to eye use interaction, stim- we sparse vision everyday and in Conversely, fixation uli. strict retinotopically require retinotopic is experiments traditional because the unknown, of much remains How organized retina. the of reference frame the to retinotopically—according organized is Vision Significance https://doi.org/10.1073/pnas.2017032118 .Rtntpcmp eutn from resulting maps Retinotopic E–G). raieCmosAtiuinLcne4.0 License Attribution Commons Creative . y https://www.pnas.org/lookup/suppl/ b Cognitive | f6 of 1

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Fig. 1. (A) Visual processing in higher-order brain regions reveals itself through spatially specific retinotopic connectivity with V1. V1’s map of visual space allows us to translate retinotopic connectivity to representations of visual space. (B) Retinotopic connectivity is quantified by modeling responses throughout the brain as emanating from Gaussian connective fields on the surface of V1. Example Gaussian CF model profiles with different size (σ) and location (v0) parameters are shown on the inflated surface. (C) Predictions are generated by weighting the ongoing BOLD signals in V1 with these CF kernels. Estimating CF parameters for all locations throughout the brain captures significant variance also outside the nominal (non-V1 time courses). (D) Cross-validation procedure. CV prediction performance of the CF model is assessed on a left-out, test dataset and is corrected for the performance of a nontopographic null model, the average V1 time course. (E–G) CF modeling results can be used to reconstruct the retinotopic structure of . Polar angle preferences outside the black outline are reconstructed solely based on their topographic connectivity with V1, within the black outline. CF modeling was performed on data from retinotopic-mapping, resting-state, and movie-watching experiments separately. Visual field preferences are stable across cognitive states, as evidenced by the robust locations of polar angle reversals at the borders between V2 and V3 field maps. Additional retinotopic structure visualizations are in SI Appendix, Figs. S1 and S2.

Does this RC extend beyond the lower levels of the visual sys- retinotopy (9, 11) (Fig. 2C). The detailed differences in spatial tem, and, if so, how does it depend on the different cognitive representations between conditions, however, show the flexibil- states evoked in different experiments? Indeed, Fig. 2A shows ity of LO’s retinotopy: A very foveal bias during retinotopic that significant portions of movie-watching BOLD fluctuations mapping (11) gives way to broader coverage of the visual field throughout the cerebral cortex are explained as resulting from during resting state and movie watching. The across-condition RC. That is, more than half of the cerebral cortex, including large robustness of ANG eccentricity (Fig. 2F) is greater than that swaths of the temporal and frontal lobes, shows significant topo- of LO (all linear correlations ρ > 0.75, all P < 10−40). How- graphically specific connectivity with V1. Interestingly, the local ever, ANG shows an opposite pattern of retinotopic flexibility, strength of RC depends heavily on the experiment (Fig 2B). Dur- with visual field preferences being more foveal specifically dur- ing movie watching, mainly ventral visual and temporal brain ing the resting state. These foveopetal and foveofugal changes regions exhibit RC. This retinotopic connectivity likely reflects of eccentricity in both LO and ANG mimic the effects of top– object identity-related processing and audiovisual integration down attention (12, 13) and imagination (14) on visual field (7). Conversely, during resting-state scans the default-mode net- representations. This pattern is also similar to what happens to work (DMN) shows stronger RC, which may reflect endogenous visual items of interest as they are foveated through eye move- mental imagery during mind wandering (8). ments (15) and follows the topographic distribution of feedback If retinotopic visual processing is a stable organizational prop- related to visual object information (16) in the absence of eye erty, visual field preferences derived from one experiment should movements. predict RC from another. The detailed inspection of CF param- V1 represents contralateral visual field locations, allowing us eters can provide insights into the visual–spatial processing to use the hemisphere of the best-fitting CF as a proxy for visual embodied by RC, but also allows us to understand its modula- field representation laterality. In LO, visual representations are tion by cognition. We can compare two regions, lateral–occipital strongly contralateral and strongly correlated between experi- (LO) and (ANG), as exemplars of high-level visual mental conditions (t test between hemispheres: all T (> 123) > and DMN areas, respectively. In both regions, spatial sampling 10, P < 10−19). In the ANG region of the DMN, there is a extent, as quantified by CF size, is stable (9) and precise (5, 10) significant contralateral bias of visual field representations dur- during both retinotopy and resting state and becomes larger and ing retinotopic mapping and movie watching (all T (199) > 6, more variable during movie watching (Fig 2 C and D). Sampling P < 10−9), but, presumably due to the strong foveal bias of visual extent is strongly correlated between conditions (all linear cor- field representations, not during resting state (T (199) = 0.14, relations ρ > 0.36, all P < 10−13 (LO), ρ > 0.75, all P < 10−37 P = 0.9). These findings confirm previous reports that the DMN (ANG)—full statistics in SI Appendix, Table S1). This points to represents visual space similarly to high-level visual brain regions stable sampling of retinotopic space in both high-level visual and in situations of visual stimulation (17). DMN regions. Although it is not generally implicated in traditional vision In LO, the preferred eccentricity of cortical locations (Fig. 2E) science experiments, tracer-based connectivity studies place the is strongly correlated between experimental conditions (linear hippocampal formation at the top of the visual-processing hier- correlations ρ > 0.48, all P < 10−19), confirming its well-known archy (18). Hippocampus is thought to implement the interaction

2 of 6 | PNAS Knapen https://doi.org/10.1073/pnas.2017032118 Topographic connectivity reveals task-dependent retinotopic processing throughout the Downloaded by guest on September 30, 2021 Downloaded by guest on September 30, 2021 oorpi onciiyrvasts-eedn eiooi rcsigtruhu h ua brain human the throughout processing retinotopic task-dependent reveals connectivity Topographic Knapen 3 (Fig. subfields hippocampal across strongly Ammonis its Cornu stimulation. subserve visual the should during hippocampus in that cortex visual the is findings with of connectivity (27) earlier uncus and humans on region and based (CA) (22) prediction mice strong the hippocam- both A allow per images RC subfield. HCP state-dependent pal anatomical cognitive resolu- and of spatial functional quantification and both quality, of power, tion high connectivity The functional (24–26). and gradients microstructural detail anterior/posterior in found corresponds long, previously gradient RC to the This hippocampus. and the preference of medial/lateral RC axes the resting-state vs. both movie-watching along of hippocampus gradient experi- the a all in feature is in striking RC most The hippocampal–V1 conditions. mental significant reveals 3A) (Fig. S4). Fig. retinotopic Appendix, during (SI preference (23) mapping field dis- should visual recently understanding its contralateral thought above narrative and covered generated over hippocampus, both in internally RC that strong and evoke reason inputs naturalistic to of me leading (19– large imagery the 22), or of processing sensory result visual and a LO, memory-related as between In likely (G) disappears, (17). tendency regions this visual state high-level surface. resting V1 to During the (E similarly preference. of space conditions. sampling field (H its visual visual left/right). between in represents (L/R: contralateral bias correlations conditions DMN a foveal experimental high the maintains between ANG retinotopic-mapping stimulation, with similar and experiments, visual highly stable, movie-watching watching During and is for contralateral LO. preference size strongly in field are CF positions Like visual representations spatial (D) by in conditions. CF biases quantified between of foveal integration size (F marked shifts state. CF see spatial resting in we to of correlation and relative degree strong conditions, experiments experimental a across the across showing strongly averaged DMN watching correlates values movie the eccentricity correlation during in null-model–corrected variation to LO, size relates CF in linearly with opacity experiments, Marker Vertical retinotopic-mapping plots. and 0.9. and scatter experiment to retinotopy the the 0.1 resting as from from (C range during values ranges parameter conditions. same strongest represents and the in color is Methods) on Marker respectively. engaged V1 and defined results, (Materials is were and resting-state ratio and regions participants movie-watching correlation represent network whether normalized more axes are default-mode represents vertical on ( integration represents watching between depends audiovisual correlations. axis movie connectivity for V1 scale cross-validated vs. responsible Topographic state color to and best-fitting watching. identity resting connectivity significant movie object for to topographic have Colormap during sensitive state. of black V1 regions visual strength to not lateral local connected are and Ventral strongly The that thought. state. endogenous V1 or cognitive outside watching movie by locations modulated vertex is all connectivity locations; center CF possible 2. Fig. A B Medial M LateralLa h teghadcgiiesaedpnec fR varies RC of dependence cognitive-state and strength The courses time BOLD hippocampus to modeling CF Applying e Resting t dia e State r al aal eiooi onciiydrn oi acigepan infiataonso ainetruhu h ri.Tega eincnan all contains region gray The brain. the throughout variance of amounts significant explains watching movie during connectivity Retinotopic (A) 10 10 ntehg-ee iulsse,C iecreae togybtencniin.Seicly Fsz sfie n iia uigresting-state during similar and fixed is size CF Specifically, conditions. between strongly correlates size CF system, visual high-level the In ) -20 -3 Watching Movie Left Left Hemisphere P

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Fig. 3. RC is pervasive throughout the hippocampal formation. (A) Like the cerebral cortex, the hippocampus also displays a gradient of endoge- nous/exogenous processing, with stronger topographic connectivity in rostral/medial/inferior regions during movie watching, and in caudal/lateral/superior regions during resting state. Colormap for resting state vs. movie watching represents normalized correlation ratio ranges from 0.35 to 0.65: a narrower range than that used for cortex in Fig. 2. Full lightbox visualization of RC connectivity gradient and visual field parameters are in SI Appendix, Fig. S4. We see RC in both the anterior and posterior portions of the hippocampus in both experiments, rendering it unlikely that signal-to-noise-ratio (SNR) differences between anterior and posterior hippocampus (23) impact these specific findings. (B) Strength and stability of RC for different cognitive states, for separate hippocampal subfields. Inset shows a sagittal section of a hippocampal subfield segmentation for a single subject. (GC-DG, granule cell layer of the dentate gyrus; HC, hippocampus.) Full statistics are given in SI Appendix, Tables S2–S4.(C and D) Eccentricity (C) and size (D) of hippocampal CFs are stable between different cognitive states, with strong correlations between all three conditions (linear CF eccentricity and size correlations >0.55, P < 10−26). (E) Hippocam- pal visual field representations are significantly biased to represent the contralateral visual hemifield in movie watching, resting state, and retinotopy (t test between hemispheres, T = −4.3, P<2 · 10−5, df = 173, T = −3.4, P<10−3, df = 173, and T = −10.3, P<10−20, df = 173, respectively). These small yet significant contralateral biases are similar in scale to the contralaterality of visual field representations in the DMN. Detailed visualization of visual field representations in hippocampal and thalamic subregions is in SI Appendix, Fig. S5.

challenges. Could these patterns of retinotopic connectivity be tivity gradients found previously in the resting state. Specifically, due to the complex spatiotemporal correlations that characterize resting-state–movie-watching preferences behave as a combina- the naturalistic visual inputs of, and engagement with, the movie- tion of the primary sensory-transmodal and the multiple-demand watching experiment? Indeed, based on just the movie-watching gradients (24)—both in cortex and within the hippocampus (26). results, we cannot definitively assert that topographic connectiv- These large-scale gradients result from the push–pull between ity is evidence for visual–spatial processing. But in the resting sensory and attentional brain systems on the one hand and the state, topographic connectivity arises from the brain’s internal DMN on the other (28). Such countervailing activations and organization. Finding similar RC patterns in resting state and deactivations are thought to mediate a dynamic balance between movie watching thus hints strongly at a consistent visual–spatial outward-oriented, stimulus-driven processing on the one hand structure that the brain has internalized and that is used in and memory-related, endogenously generated processing on the ongoing thought. Moreover, many of these spatiotemporal cor- other (29, 30). Importantly, the present work identifies a con- relations in visual input and behavior that characterize movie sistent mode of organization across both memory-related and watching are explicitly avoided by the retinotopic-mapping stim- stimulus-directed processing: In both cognitive states, connec- ulus material and paradigm (for example, the fact that usually, tivity is retinotopically organized. Furthermore, these results human heads occur on top of bodies). I construe the similar pat- demonstrate that the push–pull between DMN and sensory terns of RC between movie-watching and retinotopy experiments regions in terms of signal amplitude (28) also involves a trade-off as evidence for a joint visual frame of reference used throughout in foveally biased processing between regions, possibly related the brain. to recent findings of retinotopic traveling waves in visual cor- This also suggests that the degree of similarity in RC patterns tex during resting state (31, 32). On the basis of these findings, I between all three experiments can be seen as a gauge for how propose that the detailed structure of concurrent retinotopically “visual” a brain region is. The gradient of RC similarity across organized activations in visual system, DMN, and hippocam- experiments in both cortex and hippocampus (Figs. 2 and 3) pus gives rise to interactions between attentional and mnemonic aligns surprisingly well with a combination of functional connec- processing (33).

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PSYCHOLOGICAL AND NEUROSCIENCE COGNITIVE SCIENCES ACKNOWLEDGMENTS. I thank Ed Silson, Chris Baker, Peter Zeidman, Nicholas 17683). Data were provided by the , Washington Hedger, and Eli Merriam for providing comments on an earlier version of University - Minnesota Consortium (Principal Investigators D. Van Essen and the manuscript and Kendrick Kay, Alex Huth, and Ben Hutchison for fruit- K. Ugurbil;ˇ 1U54MH091657) funded by the 16 NIH Institutes and Centers that ful discussions. T.K. was supported by a high-performance computing grant support the NIH Blueprint for Neuroscience Research, and by the McDonnell (Nederlandse Organisatie voor Wetenschappelijk Onderzoek [NWO] ENW- Center for Systems Neuroscience at Washington University in St. Louis.

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