Functional Neuroimaging of Place Learning in a Computer-Generated Space

1. Functional Neuroimaging of Place Learning in a Computer-Generated Space Ming Hsu & W. Jake Jacobs

2. Introduction • Our experiment employed the use of a Computer-Generated (C-G) Arena in conjunction with fMRI to study the neural structures involved in human place learning. • The C-G Arena was originally designed after the Morris Water Maze (MWZ), an apparatus instrumental in the development of the cognitive mapping theory.

3. Introduction cont. • We have previously shown that the C-G Arena is a good representation of the human place learning in real space. • We have also shown that people can learn locations within C-G space by observation. • Thus, we took advantage of this close correspondence to mount an fMRI examination of observational place learning.

4. Introduction cont. • Following the predictions made by cognitive mapping theory, we expect to find activation in the human hippocampus during observational place learning.

5. Experiment Design • Subjects were shown a recording of a target being found from various locations in the C-G Arena. • Two experimental conditions were used: • 1. Searches in a room that contains a visible target. • 2. Searches in a room that contains an invisible target (i.e., visible only upon contact).

6. Invisible Kaleidoscope Visible Kaleidoscope 1 2 11 13 22 24 33 35 44 Invisible Kaleidoscope Visible Kaleidoscope 46 55 57 66 68 77 79 88 Invisible Kaleidoscope Visible Kaleidoscope 90 99 101 110 112 121 123 132 Invisible Kaleidoscope Visible Kaleidoscope 134 143 145 154 156 165 167 176 177 invisible visible kaleidoscope Experiment Design cont. All trials can be roughly divided into thirds. First 1/3 of the trial consists of panning towards the target, second 1/3 shows movement to the target, and the last 1/3 of the trial shows turning while on target.

7. Activation in Perceptual Model Perceptual Model (1) invisible trials - kaleidoscope (2) visible trials - kaleidoscope

8. Model Subjects MF & RD

9. Activation Highest RD: vis v. kal MF: inv. v. kal Low Neutral Low MF: vis. v. kal Deactivation Highest RD: inv v. kal Precentral Gyrus Activation

10. MF: invisible v. kaleidoscope • Because subject RD did not contain any significant clusters of activation, only activation curves from MF will be shown.

11. RD: vis v. kal Activation Highest RD: inv v. kal Low Neutral Low MF: inv v. kal MF: vis v. kal Deactivation Highest Intraparietal Sulcus

12. MF: invisible v. kaleidoscope Notice again the 2 “bumps” in the activation curves.

13. RD: inv v. kal RD: invisible v. kaleidoscope Therefore, the latter 1/3 of the trial appears to be crucial for subsequent performance in the CG-Arena

14. Activation Highest RD: vis v. kal Low Neutral Low MF: inv_kal Deactivation Highest MF: vis_kal RD: inv v. kal Cerebellum Activation

15. MF: inv_kal MF: invisible v. kaleidoscope • Again, only MF activation curves will be shown. Cerebellar activity seems to mirror, albeit roughly, the activity in the precentral and parietal areas.

16. Activation in Learning Model Learning Models (1) first 2 invisible trial - last 2 invisible trials (2) first 2 visible trials - last 2 visible trials

17. Activation Highest Low Neutral Low MF: invisible Deactivation Highest RD: invisible MF: visible RD: visible Prefrontal Cortex

18. Activation Highest Low Neutral Low MF: invisible MF: visible RD: invisible RD: visible Deactivation Highest Temporal Lobe: Anterior

19. Activation Highest Low Neutral Low MF: invisible MF: visible RD: visible RD: invisible Deactivation Highest Temporal Lobe: Posterior Activity in temporal lobe appears to be at least an indicator of learning.

20. MF: invisible MF: MT Activity

21. Recapitulation • Activity in the precentral cortex, and around the intraparietal sulcus during the last 1/3 of the invisible trials is associated with learning. • Activity in the prefrontal cortex and temporal cortex in the first 2 invisible trials is also associated with learning.

22. Conclusions & Hypotheses • “What & Where” System • Ungleider & Mishkin 1982. • Dorsal/Parietal = Where. • Therefore, the time when the relationships between the target and cues are established is the crucial period that determines spatial learning. • Ventral/Occipital = What. • Both streams end in inferotemporal cortex, called in monkeys polysensory cortex.

23. C&H cont. • Parieto-precentral Network: From vision to motion. • Evidence in monkey and imaging literature. • Unanswered questions within the model. • How visual information gets from parietal to precentral cortex, as motor cortex has only access to “blind” areas of parietal lobe.

24. C&H cont. • Role of temporal lobe • Temporal activity decreases with familiarity in monkey and imaging studies. • In this task, temporal lobe activity appears to be associated primarily with knowledge of spatial relationships among cues and target--difference between invisible and visible trials. • Possibility of cognitive mapping within MT.

25. C&H cont. • Role of cerebellum • Abundance of cerebellar activity in imaging studies. • Cognition, or fine motor control, or facilitation of cerebral functions? • Possibility of cerebellum as pathway between parietal and precentral areas.

26. Future directions/questions • How to get hippocampal activation that argues convincingly for (or against) cognitive mapping? • What exactly is the role of cerebellum in all this? • Further elucidation of the existence and function of these networks.

27. End of Presentation