Research reportNeural foundations of emerging route knowledge in complex spatial environments
Introduction
Human spatial navigation is the expression of a complex ensemble of cognitive processes based on distinct spatial representations. Survey representations refer to an enduring, goal-independent representation of the environment. These representations—also termed cognitive maps or configurational knowledge—allow the individual to infer spatial relations between any two places irrespective of his own position. In contrast, route knowledge conveys information about a goal-directed, temporo-spatial sequence of environmental features. Salient objects (i.e. landmarks) in the environment are linked by their temporal occurrence during navigation and by spatial relations that determine movement decisions necessary to get from one landmark to the next (i.e. turn right). These spatial relations are encoded predominantly between neighboring objects [21], [42], presumably with respect to a place-dependent local reference system [40]. In addition, the connections between landmarks appear to be coded only in the direction experienced during navigation [45].
Even though different representations can be the result of experiencing an environment from different perspectives [46], [47], ground-level navigation by itself not only entails route knowledge [21], [34], [53], but can also result in survey representations [43], [51]. Hierarchical models have therefore conceptualized navigational learning as a succession of landmark, route and survey knowledge, the latter depending on a qualitative shift in the knowledge representation [48], [51]. However, the importance of both the applied learning strategy and general spatial abilities for the resultant representation has been emphasized repeatedly, arguing for the possibility to develop route or survey knowledge from the very beginning of a learning experience [4], [28].
Whereas many neuroimaging and lesion studies on spatial navigation have successfully investigated the retrieval of previously learned environments [1], [24], [26], [31], [32], [35], the neural foundations of learning complex spatial layouts have received less attention [3], [7], [33], [46]. Even though these studies have identified a network of areas including frontal, posterior parietal, retrosplenial and medial temporal regions the precise role of these structures remains controversial, particularly with respect to parietal function. For example, whereas Barrash et al. [7] did not find a systematic relationship between parietal lesions and route learning impairment, Shelton and Gabrieli [46] observed greater inferior parietal activity in an fMRI study for route as compared to survey encoding. One reason might be the lack of a behavioral measure allowing for a clear identification of the type of knowledge that was acquired, since many spatial memory tasks can be performed based on either route or survey representations [16]. In nonhuman primates, the importance of the posterior parietal cortex for route learning and retrieval has been demonstrated repeatedly [8], [52], arguing for its involvement in processing the spatial relationship between local environmental cues instead of representing the allocentric position of a goal or a fixed sequence of movements. In addition, subdivisions of the posterior parietal cortex have consistently been associated with general spatial abilities like mental rotation [6], [23], [25] or perspective taking [54] in humans, presumably reflecting the occurrence of mental spatial transformations. However, it remains unclear to what extent these areas are implicated in route learning as well.
In the present study, we aimed to characterize the neural system involved in one type of navigational learning, the acquisition of pure route knowledge. Route knowledge was conceptualized as an association between landmarks encountered in immediate temporal succession and the spatial relations connecting them. A complex virtual environment was designed enabling us to link behavioral performance directly to the gradual emergence of route knowledge. Reaction times and performance measures were obtained from judgments of spatial relations between pairs of buildings from adjacent intersections. With regard to the expected brain activation patterns, we formulated the following hypotheses: One important prerequisite for route learning consists of storing the temporal sequence of landmarks. This may entail involvement of medial frontal areas, given that they repeatedly have been associated with memory for temporal order and context [27], [50]. More importantly, the spatial relations between neighboring landmarks constitute the crucial links that can effectively guide navigational behavior. These relations presumably are encoded with respect to multiple local reference systems [40] that are imposed on distinct places within the environment. Considering the egocentric nature of these reference systems, we predicted a prominent involvement of the posterior parietal cortex in coding the spatial relations; an assumption based on its well-established role in the processing of spatial positions of external objects in various egocentric reference frames [5], [19], [20], [22].
Section snippets
Participants
Fourteen healthy male volunteers (mean age: 29.3 years, S.D.: 5.4, range: 23–35) with normal or corrected-to-normal vision gave written informed consent to participate in this study. The study was approved by the local ethics committee. All subjects understood the instructions without difficulty and none were aware of the hypotheses at the time of testing.
Experimental stimuli
In order to localize brain regions representing the emergence of route knowledge, a desktop virtual environment (Fig. 1) was constructed
Behavioral data
Participants were classified as route learners based on behavioral performance; in addition, we checked the maps drawn after fMRI scanning for global and/or local inconsistencies. According to our hypotheses, acquisition of route knowledge should manifest itself in performance improvements only for direct pairs. This behavioral pattern was observed in 11 out of 14 participants as reflected by response times and accuracy measures during retrieval (see Fig. 2). Whereas performance for both close
Discussion
In the present study, our aim was to determine the neural structures involved in route learning defined as temporo-spatial associations between consecutive landmarks. Therefore, we developed a behavioral paradigm that provided an objective distinction between route knowledge and survey representations. Eleven out of 14 participants showed evidence of pure route learning, reflected by increasing accuracy and decreasing response times during retrieval. Importantly, in these subjects, no
Acknowledgements
We thank the Physics and Methods group at NeuroImage Nord in Hamburg, Ron Paludan (www.railwaystation.com) for providing several 3D-models, and D. Waller, K.F. Richter, F. Binkofski, E. Schoell, A. McNamara and D. Gonzalo for suggestions on an earlier draft of this paper. This work was supported by the Volkswagenstiftung and the Bundesministerium für Bildung und Forschung (BMBF).
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