Skip to main content Accessibility help
×
Hostname: page-component-586b7cd67f-vdxz6 Total loading time: 0 Render date: 2024-11-28T15:59:42.604Z Has data issue: false hasContentIssue false

Chapter 11 - Seeking Inner Knowledge

Foraging in Semantic Space

from Part III - Which Machinery Supports the Drive for Knowledge?

Published online by Cambridge University Press:  19 May 2022

Irene Cogliati Dezza
Affiliation:
University College London
Eric Schulz
Affiliation:
Max-Planck-Institut für biologische Kybernetik, Tübingen
Charley M. Wu
Affiliation:
Eberhard-Karls-Universität Tübingen, Germany
Get access

Summary

Information-seeking is usually conceived of as gathering information to make better decisions by observing and sampling from the external world. But for humans and many other intelligent agents, much of that information, once gathered, is also stored to guide future decisions, necessitating mechanisms for seeking information in some form of inner space. Here we survey various types of evidence suggesting that strategies adapted for search in external spatial environments are also used to seek information internally from memory. These include foraging strategies such as area-restricted search, which adaptively balances exploitation of locally clustered resources with exploration for resources more widely dispersed. We also describe how internal search satisfies the predictions of external foraging theory via the Marginal Value Theorem and show how these predictions can be used to investigate individual differences in memory search such as those caused by aging and cognitive impairment. Finally, we consider evidence that the structure of inner space may be a result of the very processes we use to search it.

Type
Chapter
Information
The Drive for Knowledge
The Science of Human Information Seeking
, pp. 237 - 258
Publisher: Cambridge University Press
Print publication year: 2022

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abbott, J. T., Austerweil, J. L., & Griffiths, T. L. (2015). Random walks on semantic networks can resemble optimal foraging. Psychological Review, 122(3), 558569.Google Scholar
Adamic, L. A. (1999). The small world web. International Conference on Theory and Practice of Digital Libraries, 1696, 443452.Google Scholar
Anderson, M. C., Bjork, R. A., & Bjork, E. (1994). Remembering can cause forgetting: Retrieval dynamics in long-term memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20(5), 10631087.Google Scholar
Anderson, J. R., & Pirolli, P. L. (1984). Spread of activation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10(4), 791798.Google Scholar
Anderson, J. R., & Schooler, L. J. (1991). Reflections of the environment in memory. Psychological Science, 2(6), 396408.Google Scholar
Benhamou, S. (2007). How many animals really do the Lévy walk? Ecology, 88(8), 19621969.Google Scholar
Bhatia, S., Richie, R., & Zou, W. (2019). Distributed semantic representations for modeling human judgment. Current Opinion in Behavioral Sciences, 29, 3136.Google Scholar
Birn, R. M., Kenworthy, L., Case, L., Caravella, R., Jones, T. B., Bandettini, P. A., & Martin, A. (2010). Neural systems supporting lexical search guided by letter and semantic category cues: A self-paced overt response fMRI study of verbal fluency. Neuroimage, 49(1), 10991107.Google Scholar
Blanchard, T. C., & Hayden, B. Y. (2014). Neurons in dorsal anterior cingulate cortex signal postdecisional variables in a foraging task. Journal of Neuroscience, 34(2), 646655.Google Scholar
Boettcher, S. E., Drew, T., & Wolfe, J. M. (2018). Lost in the supermarket: Quantifying the cost of partitioning memory sets in hybrid search. Memory & Cognition, 46(1), 4357.Google Scholar
Bokat, C. E., & Goldberg, T. E. (2003). Letter and category fluency in schizophrenic patients: A meta-analysis. Schizophrenia Research, 64(1), 7378.CrossRefGoogle ScholarPubMed
Bousfield, W. A., & Sedgewick, C. H. W. (1944). An analysis of sequences of restricted associative responses. The Journal of General Psychology, 30(2), 149165.Google Scholar
Brown, J. W., & Alexander, W. H. (2017). Foraging value, risk avoidance, and multiple control signals: How the anterior cingulate cortex controls value-based decision-making. Journal of Cognitive Neuroscience, 29(10), 16561673.Google Scholar
Buzsáki, G., & Moser, E. I. (2013). Memory, navigation and theta rhythm in the hippocampal-entorhinal system. Nature Neuroscience, 16(2), 130138.Google Scholar
Chadwick, M. J., Hassabis, D., Weiskopf, N., & Maguire, E. A. (2010). Decoding individual episodic memory traces in the human hippocampus. Current Biology, 20(6), 544547.Google Scholar
Charnov, E. L. (1976). Optimal foraging, the marginal value theorem. Theoretical Population Biology, 9(2), 129136.Google Scholar
Constantinescu, A. O., O’Reilly, J. X., & Behrens, T. E. (2016). Organizing conceptual knowledge in humans with a gridlike code. Science, 352(6292), 14641468.Google Scholar
Costafreda, S. G., Fu, C. H., Lee, L., Everitt, B., Brammer, M. J., & David, A. S. (2006). A systematic review and quantitative appraisal of fMRI studies of verbal fluency: Role of the left inferior frontal gyrus. Human Brain Mapping, 27(10), 799810.Google Scholar
Davidsen, J., Ebel, H., & Bornholdt, S. (2002). Emergence of a small world from local interactions: Modeling acquaintance networks. Physical Review Letters, 88(12), 128701.Google Scholar
Dick, P. K. (1959). Time out of joint. J. B. Lippencott & Co.Google Scholar
Dubossarsky, H., De Deyne, S., & Hills, T. (2017). Quantifying the structure of free association networks across the lifespan. Developmental Psychology, 53, 15601570.Google Scholar
Eichenbaum, H. (2004). Hippocampus: Cognitive processes and neural representations that underlie declarative memory. Neuron, 44(1), 109120.Google Scholar
Ferrer i Cancho, R., & Solé, R. V. (2001). The small world of human language. Proceedings of The Royal Society B, 268, 22612265.Google Scholar
Fu, W. T., & Pirolli, P. (2007). SNIF-ACT: A cognitive model of user navigation on the World Wide Web. Human–Computer Interaction, 22(4), 355412.Google Scholar
Gates, A. I. (1917). Recitation as a factor in memorizing. Archives of Psychology, 6, 40.Google Scholar
Gauthier, C. T., Duyme, M., Zanca, M., & Capron, C. (2009). Sex and performance level effects on brain activation during a verbal fluency task: A functional magnetic resonance imaging study. Cortex, 45(2), 164176.Google Scholar
Gelbard-Sagiv, H., Mukamel, R., Harel, M., Malach, R., & Fried, I. (2008). Supporting online material internally generated reactivation of single neurons in human hippocampus during free recall. Science Reports, 322, 96101.Google Scholar
Gruber, M. J., & Ranganath, C. (2019). How curiosity enhances hippocampus-dependent memory: The prediction, appraisal, curiosity, and exploration (PACE) framework. Trends in Cognitive Sciences, 23(12), 10141025.Google Scholar
Gruenewald, P. J., & Lockhead, G. R. (1980). The free recall of category examples. Journal of Experimental Psychology: Human Learning and Memory, 6(3), 225240.Google Scholar
Gurd, J. M., Amunts, K., Weiss, P. H., Zafiris, O., Zilles, K., Marshall, J. C., & Fink, G. R. (2002). Posterior parietal cortex is implicated in continuous switching between verbal fluency tasks: An fMRI study with clinical implications. Brain, 125(5), 10241038.Google Scholar
Henry, J. D., & Crawford, J. R. (2005). A meta-analytic review of verbal fluency deficits in depression. Journal of Clinical and Experimental Neuropsychology, 27(1), 78101.Google Scholar
Henry, J. D., Crawford, J. R., & Phillips, L. H. (2004). Verbal fluency performance in dementia of the Alzheimer’s type: A meta-analysis. Neuropsychologia, 42(9), 12121222.Google Scholar
Heylighen, F. (2016). Stigmergy as a universal coordination mechanism II: Varieties and evolution. Cognitive Systems Research, 38, 5059.Google Scholar
Hills, T. (2003). Towards a unified theory of animal event timing. In H. Meck, W (Ed.), Functional and neural mechanisms of interval timing (pp. 77111). New York: CRC Press.Google Scholar
Hills, T. T. (2006). Animal foraging and the evolution of goal-directed cognition. Cognitive Science, 30(1), 341.Google Scholar
Hills, T. T. (2019). Neurocognitive free will. Proceedings of the Royal Society B, 286(1908), 20190510.Google Scholar
Hills, T. T., Jones, M. N., & Todd, P. M. (2012). Optimal foraging in semantic memory. Psychological Review, 119(2), 431440.CrossRefGoogle ScholarPubMed
Hills, T. T., Kalff, C., & Wiener, J. M. (2013). Adaptive Lévy processes and area-restricted search in human foraging. PLoS One, 8(4), e60488.Google Scholar
Hills, T. T., & Kenett, Y. (2021). Is the mind a network? Maps, vehicles, and skyhooks in cognitive network science. Topics in Cognitive Science. https://onlinelibrary.wiley.com/doi/abs/10.1111/tops.12570Google Scholar
Hills, T. T., Mata, R., Wilke, A., & Samanez-Larkin, G. R. (2013). Mechanisms of age-related decline in memory search across the adult life span. Developmental Psychology, 49(12), 2396.Google Scholar
Hills, T. T., & Pachur, T. (2012). Dynamic search and working memory in social recall. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38(1), 218.Google Scholar
Hills, T. T., Todd, P. M., Lazer, D., Redish, A. D., Couzin, I. D., & Cognitive Search Research Group (2015). Exploration versus exploitation in space, mind, and society. Trends in Cognitive Science, 19(1), 4654. doi:10.1016/j.tics.2014.10.004Google Scholar
Hirshorn, E. A., & Thompson-Schill, S. L. (2006). Role of the left inferior frontal gyrus in covert word retrieval: Neural correlates of switching during verbal fluency. Neuropsychologia, 44(12), 25472557.Google Scholar
Hupbach, A., Gomez, R., Hardt, O., & Nadel, L. (2007). Reconsolidation of episodic memories: A subtle reminder triggers integration of new information. Learning & Memory, 14, 4753.Google Scholar
Jones, H. E. (1923). The effects of examination on the performance of learning. Archives of Psychology, 10, 170.Google Scholar
Jones, M. N., Hills, T. T., & Todd, P. M. (2015). Hidden processes in structural representations: A reply to Abbott, Austerweil, and Griffiths (2015). Psychological Review, 122(3), 570574.Google Scholar
Jones, M. N., & Mewhort, D. J. (2007). Representing word meaning and order information in a composite holographic lexicon. Psychological Review, 114(1), 137.Google Scholar
Joyce, E. M., Collinson, S. L., & Crichton, P. (1996). Verbal fluency in schizophrenia: Relationship with executive function, semantic memory and clinical alogia. Psychological Medicine, 26(1), 3949.Google Scholar
Kolling, N., Behrens, T. E., Mars, R. B., & Rushworth, M. F. (2012). Neural mechanisms of foraging. Science, 336(6077), 9598.Google Scholar
Laisney, M., Matuszewski, V., Mézenge, F., Belliard, S., de la Sayette, V., Eustache, F., & Desgranges, B. (2009). The underlying mechanisms of verbal fluency deficit in frontotemporal dementia and semantic dementia. Journal of Neurology, 256(7), 10831094.Google Scholar
Landauer, T. K., & Dumais, S. T. (1997). A solution to Plato’s problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychological Review, 104(2), 211240.Google Scholar
Latora, V., & Marchiori, M. (2001). Efficient behavior of small-world networks. Physical Review Letters, 87(19), 198701.Google Scholar
Levin, S. A. (1992). The problem of pattern and scale in ecology. Ecology, 73(6), 19431967.CrossRefGoogle Scholar
Lloyd, M. (1967). Mean crowding. Journal of Animal Ecology, 36(1), 130.CrossRefGoogle Scholar
Lundin, N. B. (2022). Disorganized speech in psychosis: Computational and neural markers of semantic foraging and discourse cohesion. Unpublished doctoral dissertation. Indiana University Bloomington.Google Scholar
Lundin, N. B., Todd, P. M., Jones, M. N., Avery, J. E., O’Donnell, B. F., & Hetrick, W. P. (2020). Semantic search in psychosis: Modeling local exploitation and global exploration. Schizophrenia Bulletin Open, 1(1), sgaa011.Google Scholar
Luthra, M., Izquierdo, E. J., & Todd, P. M. (2020). Cognition evolves with the emergence of environmental patchiness. In Bongard, J, Lovato, J, Herbert-Dufresne, L, Dasari, R, & Soros, L (Eds.), Proceedings of the Artificial Life Conference 2020 (pp. 450458). MIT Press. https://direct.mit.edu/isal/proceedings/isal2020/450/98395Google Scholar
Luthra, M. & Todd, P. M. (2021). Social search evolves with the emergence of clustered environments. In Čejková, J, Holler, S, Soros, L, & Witkowski, O (Eds.), Proceedings of the Artificial Life Conference 2021 (pp. 182190). MIT Press.Google Scholar
Lydon-Staley, D. M., Zhou, D., Blevins, A. S., Zurn, P., & Bassett, D. S. (2021). Hunters, busybodies and the knowledge network building associated with deprivation curiosity. Nature Human Behaviour, 5(3), 327336.Google Scholar
O’Keefe, J., & Nadel, L. (1978). The hippocampus as a cognitive map. Oxford University Press.Google Scholar
Mack, M. L., Love, B. C., & Preston, A. R. (2016). Dynamic updating of hippocampal object representations reflects new conceptual knowledge. Proceedings of the National Academy of Sciences, 113(46), 1320313208.Google Scholar
Mehta, P. S., Tu, J. C., LoConte, G. A., Pesce, M. C., & Hayden, B. Y. (2019). Ventromedial prefrontal cortex tracks multiple environmental variables during search. Journal of Neuroscience, 39(27), 53365350.Google Scholar
Meyer, D. E., & Schvaneveldt, R. W. (1971). Facilitation in recognizing pairs of words: Evidence of a dependence between retrieval operations. Journal of Experimental Psychology, 90(2), 227.Google Scholar
Montez, P., Thompson, G., & Kello, C. T. (2015). The role of semantic clustering in optimal memory foraging. Cognitive Science, 39(8), 19251939.Google Scholar
Montoya, J. M., & Solé, R. V. (2002). Small world patterns in food webs. Journal of Theoretical Biology, 214(3), 405412.Google Scholar
Morais, A. S., Olsson, H., & Schooler, L. J. (2013). Mapping the structure of semantic memory. Cognitive Science, 37(1), 125145.Google Scholar
Morton, N. W., Sherrill, K. R., & Preston, A. R. (2017). Memory integration constructs maps of space, time, and concepts. Current Opinion in Behavioral Sciences, 17, 161168.Google Scholar
Nader, K., Schafe, G. E., & Le Doux, J. E. (2000). Fear memories require protein synthesis in the amygdala for reconsolidation after retrieval. Nature, 406(6797), 722726.Google Scholar
Nyberg, L., Habib, R., Mcintosh, A. R., & Tulving, E. (2000). Reactivation of encoding-related brain activity during memory retrieval. Proceedings of the National Academy of Sciences, 97(20), 1112011124.Google Scholar
Olesen, J. M., Bascompte, J., Dupont, Y. L., & Jordano, P. (2006). The smallest of all worlds: Pollination networks. Journal of Theoretical Biology, 240(2), 270276.Google Scholar
Pezzulo, G., van der Meer, M.A., Lansink, C.S., & Pennartz, C.M. (2014). Internally generated sequences in learning and executing goal-directed behavior. Trends in Cognitive Sciences, 18, 647657. doi:10.1016/j.tics. 2014.06.011Google Scholar
Pyc, M. A., & Rawson, K. A. (2009). Testing the retrieval effort hypothesis: Does greater difficulty correctly recalling information lead to higher levels of memory? Journal of Memory and Language, 60(4), 437447.Google Scholar
Ratcliff, R., & McKoon, G. (1988). A retrieval theory of priming in memory. Psychological Review, 95(3), 385408.Google Scholar
Rhodes, T., & Turvey, M. T. (2007). Human memory retrieval as Lévy foraging. Physica A: Statistical Mechanics and its Applications, 385(1), 255260.Google Scholar
Rips, L. J., Shoben, E. J., & Smith, E. E. (1973). Semantic distance and the verification of semantic relations. Journal of Verbal Learning and Verbal Behavior, 12(1), 120.Google Scholar
Sandoval, T. C., Gollan, T. H., Ferreira, V. S., & Salmon, D. P. (2017). What causes the bilingual disadvantage in verbal fluency? The dual-task analogy. Bilingualism: Language and Cognition, 13(2), 231252.Google Scholar
Sen, P., Dasgupta, S., Chatterjee, A., Sreeram, P. A., Mukherjee, G., & Manna, S. S. (2003). Small-world properties of the Indian railway network. Physical Review, 67, 036106.Google ScholarPubMed
Shenhav, A., Straccia, M. A., Botvinick, M. M., & Cohen, J. D. (2016). Dorsal anterior cingulate and ventromedial prefrontal cortex have inverse roles in both foraging and economic choice. Cognitive, Affective, & Behavioral Neuroscience, 16(6), 11271139.Google Scholar
Shenhav, A., Straccia, M. A., Cohen, J. D., & Botvinick, M. M. (2014). Anterior cingulate engagement in a foraging context reflects choice difficulty, not foraging value. Nature Neuroscience, 17(9), 12491254.CrossRefGoogle Scholar
Shima, K., & Tanji, J. (1998). Role for cingulate motor area cells in voluntary movement selection based on reward. Science, 282(5392), 13351338.Google Scholar
Steyvers, M., & Tenenbaum, J. B. (2005). The large-scale structure of semantic networks: Statistical analyses and a model of semantic growth. Cognitive Science, 29(1), 4178.Google Scholar
Strange, B. A., Witter, M. P., Lein, E. S., & Moser, E. I. (2014). Functional organization of the hippocampal longitudinal axis. Nature Reviews Neuroscience, 15(10), 655669.Google Scholar
Taler, V., Johns, B., Sheppard, C., & Jones, M. (2015, December). Determining the linguistic information sources underlying verbal fluency performance across aging and cognitive impairment. Canadian Journal of Experimental Psychology-Revue Canadienne De Psychologie Experimentale, 69(4), 369369.Google Scholar
Thompson, G. W., & Kello, C. (2014). Walking across Wikipedia: A scale-free network model of semantic memory retrieval. Frontiers in Psychology, 5, 86.Google Scholar
Todd, P. M., & Hills, T.T. (2020). Foraging in mind. Current Directions in Psychological Science, 20(3), 309315. https://doi.org/10.1177/0963721420915861Google Scholar
Todd, P. M., Hills, T. T., & Robbins, T. W. (Eds.). (2012). Cognitive search: Evolution, algorithms, and the brain. MIT Press.Google Scholar
Tolman, E. C. (1948). Cognitive maps in rats and men. Psychological Review, 55, 189208.Google Scholar
Tolman, E. C., & Gleitman, H. (1949). Studies in learning and motivation: I. Equal reinforcements in both end-boxes, followed by shock in one end-box. Journal of Experimental Psychology, 39, 810819.Google Scholar
Troyer, A. K., Moscovitch, M., & Winocur, G. (1997). Clustering and switching as two components of verbal fluency: Evidence from younger and older healthy adults. Neuropsychology, 11(1), 138146.Google Scholar
Troyer, A. K., Moscovitch, M., Winocur, G., Alexander, M. P., & Stuss, D. O. N. (1998). Clustering and switching on verbal fluency: The effects of focal frontal- and temporal-lobe lesions. Neuropsychologia, 36(6), 499504.Google Scholar
van Beilen, M., Pijnenborg, M., van Zomeren, E. H., van den Bosch, R. J., Withaar, F. K., & Bouma, A. (2004). What is measured by verbal fluency tests in schizophrenia? Schizophrenia Research, 69(2–3), 267276.Google Scholar
Viswanathan, G. M., Buldyrev, S. V., Havlin, S., Da Luz, M. G. E., Raposo, E. P., & Stanley, H. E. (1999). Optimizing the success of random searches. Nature, 401(6756), 911914.Google Scholar
Wang, M. Z., & Hayden, B. Y. (2021). Latent learning, cognitive maps, and curiosity. Current Opinion in Behavioral Sciences, 38, 17.Google Scholar
Wang, X., & Pleimling, M. (2017). Foraging patterns in online searches. Physical Review E, 95(3), 032145.Google Scholar
Wheeler, M. A., & Roediger, H. L. (1992). Disparate effects of repeated testing: Reconciling Ballard’s (1913) and Bartlett’s (1932) results. Psychological Science, 3(4), 240245.Google Scholar
Williams, S. C. (2019). Neural correlates of adaptive behavior: Structure, dynamics, and information processing (Publication No. 27543239) [Doctoral dissertation, Indiana University Bloomington]. ProQuest Dissertations Publishing.Google Scholar
Wimber, M., Alink, A., Charest, I., Kriegeskorte, N., & Anderson, M. C. (2015). Retrieval induces adaptive forgetting of competing memories via cortical pattern suppression. Nature Neuroscience, 18(4), 582589.Google Scholar
Winstanley, C. A., Robbins, T. W., Balleine, B. W., Brown, J. W., Büchel, C., Cools, R., … & Seamans, J. K. (2012). Search, goals, and the brain. In Todd, P. M., Hills, T. T., & Robbins, T. W. (Eds.), Cognitive search: Evolution, algorithms, and the brain. Strüngmann Forum reports (pp. 125156). MIT Press.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×