Seeking Inner Knowledge

doi:10.1017/9781009026949.012

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

Thomas T. Hills ,

Nancy B. Lundin ,

Mahi Luthra and

Peter M. Todd

Edited by

Irene Cogliati Dezza ,

Eric Schulz and

Charley M. Wu

Show author details

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

Book contents

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.

Keywords

Inner knowledge foraging memory Marginal Value Theorem exploitation exploration

Type: Chapter
Information: The Drive for Knowledge
The Science of Human Information Seeking
, pp. 237 - 258

DOI: https://doi.org/10.1017/9781009026949.012 [Opens in a new window]

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), 558–569.Google Scholar

Adamic, L. A. (1999). The small world web. International Conference on Theory and Practice of Digital Libraries, 1696, 443–452.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), 1063–1087.Google Scholar

Anderson, J. R., & Pirolli, P. L. (1984). Spread of activation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10(4), 791–798.Google Scholar

Anderson, J. R., & Schooler, L. J. (1991). Reflections of the environment in memory. Psychological Science, 2(6), 396–408.Google Scholar

Benhamou, S. (2007). How many animals really do the Lévy walk? Ecology, 88(8), 1962–1969.Google Scholar

Bhatia, S., Richie, R., & Zou, W. (2019). Distributed semantic representations for modeling human judgment. Current Opinion in Behavioral Sciences, 29, 31–36.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), 1099–1107.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), 646–655.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), 43–57.Google Scholar

Bokat, C. E., & Goldberg, T. E. (2003). Letter and category fluency in schizophrenic patients: A meta-analysis. Schizophrenia Research, 64(1), 73–78.CrossRef Google Scholar PubMed

Bousfield, W. A., & Sedgewick, C. H. W. (1944). An analysis of sequences of restricted associative responses. The Journal of General Psychology, 30(2), 149–165.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), 1656–1673.Google Scholar

Buzsáki, G., & Moser, E. I. (2013). Memory, navigation and theta rhythm in the hippocampal-entorhinal system. Nature Neuroscience, 16(2), 130–138.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), 544–547.Google Scholar

Charnov, E. L. (1976). Optimal foraging, the marginal value theorem. Theoretical Population Biology, 9(2), 129–136.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), 1464–1468.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), 799–810.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, 1560–1570.Google Scholar

Eichenbaum, H. (2004). Hippocampus: Cognitive processes and neural representations that underlie declarative memory. Neuron, 44(1), 109–120.Google Scholar

Ferrer i Cancho, R., & Solé, R. V. (2001). The small world of human language. Proceedings of The Royal Society B, 268, 2261–2265.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), 355–412.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), 164–176.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, 96–101.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), 1014–1025.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), 225–240.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), 1024–1038.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), 78–101.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), 1212–1222.Google Scholar

Heylighen, F. (2016). Stigmergy as a universal coordination mechanism II: Varieties and evolution. Cognitive Systems Research, 38, 50–59.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. 77–111). New York: CRC Press.Google Scholar

Hills, T. T. (2006). Animal foraging and the evolution of goal-directed cognition. Cognitive Science, 30(1), 3–41.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), 431–440.CrossRef Google Scholar PubMed

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.12570 Google 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), 46–54. 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), 2547–2557.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, 47–53.Google Scholar

Jones, H. E. (1923). The effects of examination on the performance of learning. Archives of Psychology, 10, 1–70.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), 570–574.Google Scholar

Jones, M. N., & Mewhort, D. J. (2007). Representing word meaning and order information in a composite holographic lexicon. Psychological Review, 114(1), 1–37.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), 39–49.Google Scholar

Kolling, N., Behrens, T. E., Mars, R. B., & Rushworth, M. F. (2012). Neural mechanisms of foraging. Science, 336(6077), 95–98.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), 1083–1094.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), 211–240.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), 1943–1967.CrossRef Google Scholar

Lloyd, M. (1967). Mean crowding. Journal of Animal Ecology, 36(1), 1–30.CrossRef Google 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. 450–458). MIT Press. https://direct.mit.edu/isal/proceedings/isal2020/450/98395 Google 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. 182–190). 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), 327–336.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), 13203–13208.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), 5336–5350.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), 1925–1939.Google Scholar

Montoya, J. M., & Solé, R. V. (2002). Small world patterns in food webs. Journal of Theoretical Biology, 214(3), 405–412.Google Scholar

Morais, A. S., Olsson, H., & Schooler, L. J. (2013). Mapping the structure of semantic memory. Cognitive Science, 37(1), 125–145.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, 161–168.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), 722–726.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), 11120–11124.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), 270–276.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, 647–657. 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), 437–447.Google Scholar

Ratcliff, R., & McKoon, G. (1988). A retrieval theory of priming in memory. Psychological Review, 95(3), 385–408.Google Scholar

Rhodes, T., & Turvey, M. T. (2007). Human memory retrieval as Lévy foraging. Physica A: Statistical Mechanics and its Applications, 385(1), 255–260.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), 1–20.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), 231–252.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 Scholar PubMed

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), 1127–1139.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), 1249–1254.CrossRef Google Scholar

Shima, K., & Tanji, J. (1998). Role for cingulate motor area cells in voluntary movement selection based on reward. Science, 282(5392), 1335–1338.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), 41–78.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), 655–669.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), 369–369.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), 309–315. https://doi.org/10.1177/0963721420915861 Google 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, 189–208.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, 810–819.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), 138–146.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), 499–504.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), 267–276.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), 911–914.Google Scholar

Wang, M. Z., & Hayden, B. Y. (2021). Latent learning, cognitive maps, and curiosity. Current Opinion in Behavioral Sciences, 38, 1–7.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), 240–245.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), 582–589.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. 125–156). MIT Press.Google Scholar

Book contents

Chapter 11 - Seeking Inner Knowledge

Summary

Keywords

Access options

References

Save book to Kindle

Save book to Dropbox

Save book to Google Drive