A Modality-Independent Network Underlies the Retrieval of Large-Scale Spatial Environments in the Human Brain

In humans, the extent to which body-based cues, such as vestibular, somatosensory, and motoric cues, are necessary for normal expression of spatial representations remains unclear. Recent breakthroughs in immersive virtual reality technology allowed us to test how body-based cues influence spatial representations of large-scale environments in humans. Specifically, we manipulated the availability of body-based cues during navigation using an omnidirectional treadmill and a head-mounted display, investigating brain differences in levels of activation (i.e., univariate analysis), patterns of activity (i.e., multivariate pattern analysis), and putative network interactions between spatial retrieval tasks using fMRI. Our behavioral and neuroimaging results support the idea that there is a core, modality-independent network supporting spatial memory retrieval in the human brain. Thus, for well-learned spatial environments, at least in humans, primarily visual input may be sufficient for expression of complex representations of spatial environments. VIDEO ABSTRACT.

[1]  Sibylle D. Steck,et al.  Inertial cues do not enhance knowledge of environmental layout , 2003, Psychonomic bulletin & review.

[2]  Troy A. Smith,et al.  Human hippocampus represents space and time during retrieval of real-world memories , 2015, Proceedings of the National Academy of Sciences.

[3]  M. D. Ernst Permutation Methods: A Basis for Exact Inference , 2004 .

[4]  Roberta L Klatzky,et al.  Functional equivalence of spatial representations derived from vision and language: evidence from allocentric judgments. , 2004, Journal of experimental psychology. Learning, memory, and cognition.

[5]  Arno Klein,et al.  A reproducible evaluation of ANTs similarity metric performance in brain image registration , 2011, NeuroImage.

[6]  Jack M. Loomis,et al.  Locomotion Mode Affects the Updating of Objects Encountered During Travel: The Contribution of Vestibular and Proprioceptive Inputs to Path Integration , 1998, Presence.

[7]  Arne D Ekstrom,et al.  Learning-Dependent Evolution of Spatial Representations in Large-Scale Virtual Environments , 2019, Journal of experimental psychology. Learning, memory, and cognition.

[8]  Russell A. Poldrack,et al.  Spatiotemporal activity estimation for multivoxel pattern analysis with rapid event-related designs , 2012, NeuroImage.

[9]  Sean M. Polyn,et al.  Beyond mind-reading: multi-voxel pattern analysis of fMRI data , 2006, Trends in Cognitive Sciences.

[10]  D. Bassett,et al.  Dynamic reconfiguration of frontal brain networks during executive cognition in humans , 2015, Proceedings of the National Academy of Sciences.

[11]  Jeffrey S. Taube,et al.  Is Navigation in Virtual Reality with fMRI Really Navigation? , 2013, Journal of Cognitive Neuroscience.

[12]  Jessica R. Cohen,et al.  The Segregation and Integration of Distinct Brain Networks and Their Relationship to Cognition , 2016, The Journal of Neuroscience.

[13]  S. Bouallègue,et al.  A New Method , 2021, Black Power and the American Myth.

[14]  J. Bassett,et al.  Passive transport disrupts directional path integration by rat head direction cells. , 2003, Journal of neurophysiology.

[15]  Larry F. Lacey,et al.  Long-term effects of on , 1987 .

[16]  C. A. Castro,et al.  Spatial selectivity of rat hippocampal neurons: dependence on preparedness for movement. , 1989, Science.

[17]  Thomas Wolbers,et al.  Challenges for identifying the neural mechanisms that support spatial navigation: the impact of spatial scale , 2014, Front. Hum. Neurosci..

[18]  Marvin M Chun,et al.  Category-selective background connectivity in ventral visual cortex. , 2012, Cerebral cortex.

[19]  Endel Tulving,et al.  Encoding specificity and retrieval processes in episodic memory. , 1973 .

[20]  Daniel R. Montello,et al.  Scale and Multiple Psychologies of Space , 1993, COSIT.

[21]  Derek J. Huffman,et al.  The influence of low-level stimulus features on the representation of contexts, items, and their mnemonic associations , 2017, NeuroImage.

[22]  Derek J. Huffman,et al.  Multivariate pattern analysis of the human medial temporal lobe revealed representationally categorical cortex and representationally agnostic hippocampus , 2014, Hippocampus.

[23]  R. Klatzky,et al.  Nonvisual navigation by blind and sighted: assessment of path integration ability. , 1993, Journal of experimental psychology. General.

[24]  T. McNamara Memory's view of space , 1991 .

[25]  By Enrique Vargas,et al.  Dynamic Reconfiguration , 2003, Series in Computer Science.

[26]  T. Brandt,et al.  Vestibular loss causes hippocampal atrophy and impaired spatial memory in humans. , 2005, Brain : a journal of neurology.

[27]  David K Bilkey,et al.  Bilateral peripheral vestibular lesions produce long-term changes in spatial learning in the rat. , 2003, Journal of vestibular research : equilibrium & orientation.

[28]  Jonathan W. Kelly,et al.  Sensorimotor alignment effects in the learning environment and in novel environments. , 2007, Journal of experimental psychology. Learning, memory, and cognition.

[29]  J. Taube,et al.  Firing Properties of Head Direction Cells in the Rat Anterior Thalamic Nucleus: Dependence on Vestibular Input , 1997, The Journal of Neuroscience.

[30]  Nikolaus Kriegeskorte,et al.  Analyzing for information, not activation, to exploit high-resolution fMRI , 2007, NeuroImage.

[31]  D. Bates,et al.  Balancing Type I Error and Power in Linear Mixed Models , 2015, 1511.01864.

[32]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[33]  Abraham Z. Snyder,et al.  Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion , 2012, NeuroImage.

[34]  Sarah S. Chance,et al.  Spatial Updating of Self-Position and Orientation During Real, Imagined, and Virtual Locomotion , 1998 .

[35]  Ehren L. Newman,et al.  Learning your way around town: How virtual taxicab drivers learn to use both layout and landmark information , 2007, Cognition.

[36]  Jeffrey N. Rouder,et al.  Default Bayes factors for ANOVA designs , 2012 .

[37]  Jeremy R. Manning,et al.  MAGELLAN: a cognitive map-based model of human wayfinding. , 2014, Journal of experimental psychology. General.

[38]  H. Bülthoff,et al.  Qualitative differences in memory for vista and environmental spaces are caused by opaque borders, not movement or successive presentation , 2016, Cognition.

[39]  B T Thomas Yeo,et al.  Reconfigurable task-dependent functional coupling modes cluster around a core functional architecture , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.

[40]  Roberta L Klatzky,et al.  Spatial updating of locations specified by 3-d sound and spatial language. , 2002, Journal of experimental psychology. Learning, memory, and cognition.

[41]  John A. King,et al.  How vision and movement combine in the hippocampal place code , 2012, Proceedings of the National Academy of Sciences.

[42]  T. McNamara,et al.  Egocentric and geocentric frames of reference in memory of large-scale space , 2003, Psychonomic bulletin & review.

[43]  J. Rouder,et al.  Default Bayes Factors for Model Selection in Regression , 2012, Multivariate behavioral research.

[44]  Elizabeth R. Chrastil,et al.  Active and passive contributions to spatial learning , 2011, Psychonomic Bulletin & Review.

[45]  Sally Andrews,et al.  To transform or not to transform: using generalized linear mixed models to analyse reaction time data , 2015, Front. Psychol..

[46]  D. Bates,et al.  Fitting Linear Mixed-Effects Models Using lme4 , 2014, 1406.5823.

[47]  Magdalena G. Wutte,et al.  Modality-Independent Coding of Spatial Layout in the Human Brain , 2011, Current Biology.

[48]  H. Johansen-Berg,et al.  Distinct and overlapping functional zones in the cerebellum defined by resting state functional connectivity. , 2010, Cerebral cortex.

[49]  Elizabeth R. Chrastil,et al.  From Cognitive Maps to Cognitive Graphs , 2014, PloS one.

[50]  G. Committeri,et al.  Distributed cognitive maps reflecting real distances between places and views in the human brain , 2014, Front. Hum. Neurosci..

[51]  Arne D Ekstrom,et al.  Which way is the bookstore? A closer look at the judgments of relative directions task , 2019, Spatial Cogn. Comput..

[52]  Arne D. Ekstrom,et al.  Interacting networks of brain regions underlie human spatial navigation: a review and novel synthesis of the literature. , 2017, Journal of neurophysiology.

[53]  Jonathan D. Ericson,et al.  Wormholes in virtual space: From cognitive maps to cognitive graphs , 2017, Cognition.

[54]  David Waller,et al.  The role of body-based sensory information in the acquisition of enduring spatial representations , 2007, Psychological research.

[55]  Yaroslav O. Halchenko,et al.  Open is Not Enough. Let's Take the Next Step: An Integrated, Community-Driven Computing Platform for Neuroscience , 2012, Front. Neuroinform..

[56]  Anthony G. Montello Daniel R. Cohn,et al.  Spatial Cognition and Computation. An Interdisciplinary Journal. , 2003 .

[57]  Noah A. Russell,et al.  Long-Term Effects of Permanent Vestibular Lesions on Hippocampal Spatial Firing , 2003, The Journal of Neuroscience.

[58]  H. Eichenbaum The role of the hippocampus in navigation is memory. , 2017, Journal of neurophysiology.

[59]  Heinrich H. Bülthoff,et al.  Walking improves your cognitive map in environments that are large-scale and large in extent , 2011, TCHI.

[60]  Elizabeth R. Chrastil,et al.  Active and passive spatial learning in human navigation: acquisition of survey knowledge. , 2013, Journal of experimental psychology. Learning, memory, and cognition.

[61]  Aiden E. G. F. Arnold,et al.  A critical review of the allocentric spatial representation and its neural underpinnings: toward a network-based perspective , 2014, Front. Hum. Neurosci..

[62]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[63]  Timothy O. Laumann,et al.  Functional Network Organization of the Human Brain , 2011, Neuron.

[64]  Russell A. Epstein,et al.  The cognitive map in humans: spatial navigation and beyond , 2017, Nature Neuroscience.

[65]  Ekaterina P. Volkova,et al.  The effect of landmark and body-based sensory information on route knowledge , 2011, Memory & cognition.

[66]  Martin Wiesmann,et al.  Imagined locomotion in the blind: An fMRI study , 2009, NeuroImage.

[67]  Dmitriy Aronov,et al.  Engagement of Neural Circuits Underlying 2D Spatial Navigation in a Rodent Virtual Reality System , 2014, Neuron.

[68]  B. Tversky,et al.  Spatial mental models derived from survey and route descriptions , 1992 .

[69]  J. Loomis,et al.  Body-based senses enhance knowledge of directions in large-scale environments , 2004, Psychonomic bulletin & review.

[70]  Arne D. Ekstrom,et al.  Dissociation of frontal-midline delta-theta and posterior alpha oscillations: A mobile EEG study. , 2018, Psychophysiology.

[71]  Craig E. L. Stark,et al.  When zero is not zero: The problem of ambiguous baseline conditions in fMRI , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[72]  Timothy P. McNamara,et al.  Systems of Spatial Reference in Human Memory , 2001, Cognitive Psychology.

[73]  Ranxiao Frances Wang,et al.  Spatial updating and common misinterpretations of spatial reference frames , 2017, Spatial Cogn. Comput..

[74]  M. Greicius,et al.  Decoding subject-driven cognitive states with whole-brain connectivity patterns. , 2012, Cerebral cortex.

[75]  T. McNamara,et al.  Layout geometry in the selection of intrinsic frames of reference from multiple viewpoints. , 2007, Journal of experimental psychology. Learning, memory, and cognition.

[76]  Russell A. Epstein Parahippocampal and retrosplenial contributions to human spatial navigation , 2008, Trends in Cognitive Sciences.

[77]  Roberta L. Klatzky,et al.  Functional Equivalence of Spatial Images Produced by Perception and Spatial Language , 2007 .

[78]  Arne D. Ekstrom,et al.  Author response: Successful retrieval of competing spatial environments in humans involves hippocampal pattern separation mechanisms , 2015 .

[79]  Robert S. Kennedy,et al.  Simulator Sickness Questionnaire: An enhanced method for quantifying simulator sickness. , 1993 .

[80]  Russell A. Epstein,et al.  Outside Looking In: Landmark Generalization in the Human Navigational System , 2015, The Journal of Neuroscience.

[81]  Andrew P. Duchon,et al.  Do Humans Integrate Routes Into a Cognitive Map? Map- Versus Landmark-Based Navigation of Novel Shortcuts , 2005 .

[82]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[83]  Stefan Pollmann,et al.  PyMVPA: a Python Toolbox for Multivariate Pattern Analysis of fMRI Data , 2009, Neuroinformatics.

[84]  Viviana Betti,et al.  Dynamic reorganization of human resting-state networks during visuospatial attention , 2015, Proceedings of the National Academy of Sciences.

[85]  Larry R Squire,et al.  Contrasting effects on path integration after hippocampal damage in humans and rats , 2013, Proceedings of the National Academy of Sciences.

[86]  B. McNaughton,et al.  Self-Motion and the Hippocampal Spatial Metric , 2005, The Journal of Neuroscience.

[87]  Russell A. Poldrack,et al.  Deconvolving BOLD activation in event-related designs for multivoxel pattern classification analyses , 2012, NeuroImage.

[88]  Simon Lessels,et al.  For Efficient Navigational Search, Humans Require Full Physical Movement, but Not a Rich Visual Scene , 2006, Psychological science.

[89]  Nicholas A Giudice,et al.  Journal of Experimental Psychology : Learning , Memory , and Cognition Functional Equivalence of Spatial Images From Touch and Vision : Evidence From Spatial Updating in Blind and Sighted Individuals , 2011 .

[90]  Arne D Ekstrom,et al.  Successful retrieval of competing spatial environments in humans involves hippocampal pattern separation mechanisms , 2015, eLife.

[91]  David J. Bryant,et al.  Representing Space in Language and Perception , 1997 .

[92]  Michael S. Beauchamp,et al.  A new method for improving functional-to-structural MRI alignment using local Pearson correlation , 2009, NeuroImage.

[93]  Russell A. Epstein,et al.  Common Neural Representations for Visually Guided Reorientation and Spatial Imagery , 2016, Cerebral cortex.

[94]  Volker Schmid,et al.  Working with the DICOM and NIfTI Data Standards in R , 2011 .

[95]  Jonathan D. Power,et al.  Intrinsic and Task-Evoked Network Architectures of the Human Brain , 2014, Neuron.

[96]  R W Cox,et al.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.