Functional Neuroimaging of Place Learning in a Computer-Generated Space

Post on 07-Feb-2016

28 views 0 download

description

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

Transcript of Functional Neuroimaging of Place Learning in a Computer-Generated Space

Ming Hsu & W. Jake Jacobs

Functional Neuroimaging of Place Learning in a Computer-Generated Space

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.

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.

Introduction cont.

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

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).

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.

Experiment Design cont.

Invisible Kaleidoscope Visible

Invisible Kaleidoscope Visible Kaleidoscope

Kaleidoscope

Invisible Kaleidoscope Visible Kaleidoscope

Invisible Kaleidoscope Visible Kaleidoscope

1 2 11 13 22 24 33 35 44

46 55 57 66 68 77 79 88

90 99 101 110 112 121 123 132

134 143 145 154 156 165 167 176 177

invisiblevisible kaleidoscope

Activation in Perceptual ModelPerceptual Model

(1) invisible trials - kaleidoscope(2) visible trials - kaleidoscope

Model Subjects MF & RD

Precentral Gyrus Activation

MF: vis. v. kalActivation

Deactivation

Neutral

Highest

LowLow

Highest

MF: inv. v. kalRD: vis v. kal RD: inv v. kal

MF: invisible v. kaleidoscope

Because subject RD did not contain any significant clusters of activation, only activation curves from MF will be shown.

Intraparietal Sulcus

Activation

Deactivation

Neutral

Highest

LowLow

Highest

MF: inv v. kal MF: vis v. kalRD: inv v. kalRD: vis v. kal

MF: invisible v. kaleidoscope

Notice again the 2 “bumps” in the activation curves.

RD: invisible v. kaleidoscope

RD: inv v. kal

Therefore, the latter 1/3 of thetrial appears to be crucial for subsequent performance in the CG-Arena

Cerebellum Activation

MF: vis_kalRD: inv v. kalMF: inv_kal Activation

Deactivation

Neutral

Highest

LowLow

Highest

RD: vis v. kal

MF: invisible v. kaleidoscope

MF: inv_kal

Again, only MF activation curves will be shown.

Cerebellar activity seems to mirror, albeit roughly, the activity in the precentral and parietal areas.

Activation in Learning Model

Learning Models

(1) first 2 invisible trial - last 2 invisible trials(2) first 2 visible trials - last 2 visible trials

Prefrontal Cortex

Activation

Deactivation

Neutral

Highest

LowLow

Highest

MF: invisible MF: visibleRD: invisibleRD: visible

Temporal Lobe: Anterior

Activation

Deactivation

Neutral

Highest

LowLow

Highest

MF: invisible MF: visibleRD: invisibleRD: visible

Temporal Lobe: Posterior

MF: invisible Activation

Deactivation

Neutral

Highest

LowLow

Highest

MF: visibleRD: invisibleRD: visibleActivity in temporal lobe appears to be at leastan indicator of learning.

MF: MT Activity

MF: invisible

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.

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.

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.

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.

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.

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.

End of Presentation