A quick introduction to connectionist cognitive architecture

•Simply a toolbox for creating psychological theories

•Better than the old “info processing” model - allows easy feedback & parallelism

A quick introduction to connectionist cognitive architecture

•Simply a toolbox for creating psychological theories

•Better than the old “info processing” model - allows easy feedback & parallelism

Assumptions Used

•The mind: a series of highly interconnected nodes, each encoding a hypothesis

A quick introduction to connectionist cognitive architecture

•Simply a toolbox for creating psychological theories

•Better than the old “info processing” model - allows easy feedback & parallelism

Assumptions Used

•The mind: a series of highly interconnected nodes, each encoding a hypothesis

•nodes are organized hierarchically in layers, increasing in abstractness

A quick introduction to connectionist cognitive architecture

•Simply a toolbox for creating psychological theories

•Better than the old “info processing” model - allows easy feedback & parallelism

Assumptions Used

•The mind: a series of highly interconnected nodes, each encoding a hypothesis

•nodes are organized hierarchically in layers, increasing in abstractness

•nodes have a state and trigger point, above which they influence other nodes

A quick introduction to connectionist cognitive architecture

•Simply a toolbox for creating psychological theories

•Better than the old “info processing” model - allows easy feedback & parallelism

Assumptions Used

•The mind: a series of highly interconnected nodes, each encoding a hypothesis

•nodes are organized hierarchically in layers, increasing in abstractness

•nodes have a state and trigger point, above which they influence other nodes

•nodes tend to excite those in other layers, and inhibit those in the same layer

A quick introduction to connectionist cognitive architecture

•Simply a toolbox for creating psychological theories

•Better than the old “info processing” model - allows easy feedback & parallelism

Assumptions Used

•The mind: a series of highly interconnected nodes, each encoding a hypothesis

•nodes are organized hierarchically in layers, increasing in abstractness

•nodes have a state and trigger point, above which they influence other nodes

•nodes tend to excite those in other layers, and inhibit those in the same layer

•on a stimulus, activation spreads through the network until it “settles” into a new state

A quick introduction to connectionist cognitive architecture

•Simply a toolbox for creating psychological theories

•Better than the old “info processing” model - allows easy feedback & parallelism

Assumptions Used

•The mind: a series of highly interconnected nodes, each encoding a hypothesis

•nodes are organized hierarchically in layers, increasing in abstractness

•nodes have a state and trigger point, above which they influence other nodes

•nodes tend to excite those in other layers, and inhibit those in the same layer

•on a stimulus, activation spreads through the network until it “settles” into a new state

•there is a fixed amount of activation available to excite nodes (attention)

“It has wings”

State = 0.4

An example of a node

An example of a network

Highly useful psychological modeling tools:

•Explain attention findings (divided vs. focussed attention)

•Explain differences between STM and LTM

•Explain forgetting

•Explain learning & application of concepts

•Explain priming effects in cognition generally

•Explain recognition of recall failure

Return to presence - the problem at hand

Current approach to understanding presence:identifying variables via empirical manipulation

For this to work, need to test as many variables in the same experiment as possible

This blind approach gives awesome practical problems!

Imagine: want to test the effects of these variables:

•Stereopsis (yes/no)

•Avatar animation (yes/no)

•Field of view (16°/ 32°/ 64°)

•Display type (MHD/Fishtank/Desktop)

•Perspective (1st person/3rd person)

This requires 2x2x3x3x2 = 72 conditions

At a minimum of 12 subjects per condition, 864 subjects!!

Apart from this, current research suffers from:

•Lack of statistical power (small effects, few subjects)

•Little methodological sophistication (still use 2 group experiments)

•Conclusions which go beyond data found

•Lack of understanding of psychological processes of perception

Solution to the problem: Follow standard natural science methods:

•Begin with a model

•Generate specific hypothesis implied by the model

•Test these hypotheses to evaluate the validity of the model

Advantage of this approach - there is always a defined research goaland avoids many null results

Current model of presence

Nothing explicitly or formally defined

Model seems to be:

“Being there” is a consequence of having sensory stimulation approaching that found in natural perception.

Problems with this model:

•No account of higher-level processes (“willing suspension of disbelief”)

•Gives a technology-centered view of a psychological process

•It is difficult to understand the implications of such a model

•Current evidence contradicts it

Towards a new model: considerations

Things we know about presence, supported by current model:

Positive correlations:

•Realism

•Attention on the VE

•Storyline

Negative correlations:

•Bad interface

•Attention on the RE (BIPs)

•Poor immersion

Most trustworthy results are relational (biggest effects)No information on causality with relational studies

From those findings, several things become clear:

•Direction of attention is important

•Quality of stimulus is important

•Interference with the process is possible

•Top-down processes are important

The current presence model does not take many of these points into account:

•cannot explain why BIPs occur, or why interference should happen

•does not give any space for top-down processing (such as storyline)

Connectionist networks are a possible candidate for modeling:

•they model attentional processes well

•they can account for interference

•they can explain selection between competing stimuli

•they can account for top-down effects, bottom-up effects as well as their interactions

Presence as a form of environmental perception & reaction

In my model, presence is a natural process, a part of perception

can occur in any setting, not just computer created VEs (theme parks, books, films, etc)

Rather than thinking of presence as a “feeling of being there”, look at it from a behaviorist view:

During the presence state, subjects are more likely to think and act in a way coherent with the demands of the virtual world rather those of the real world. The dominance of virtually-aligned cognition represents the level of presence.

This idea agrees with the classical “being there” idea of presence, but is more operationalized - bridges “presence” and “behavioral presence”

My idea of a connectionist model for environmental perception:

Perceptual layers

Detectors for “real” stimuli

Detectors for “image” stimuli

Conceptual layers

Detectors for other stimuli

The center layer (layers) represent them mechanisms which determine presence

Detectors for “real” stimuli

These nodes become activated when the subject is stimulated

by something which is perceived as real (eg. animation,

stereo, etc)

Detectors for “image” stimuli

These nodes are activated when the subject is stimulated by something which is perceived as an image (eg. glint of a photograph, jaggies, etc)

As usual, there is vertical excitation and lateral inhibition

Detectors for other stimuli

These nodes are activated when the subject is stimulated by other stimuli (not emanating from the VE)

Perceptual layers

Detectors for “real” stimuli

Detectors for “image” stimuli

Conceptual layers

Detectors for other stimuli

The high presence situation: Stable state with “Real” cluster most activated

Perceptual layers

Detectors for “real” stimuli

Detectors for “image” stimuli

Conceptual layers

Example: looking at a photograph (low presence)

AFlatness, glossiness, etc.

A“I am holding a photo”, etc.

Detectors for other stimuli

Result: action/thoughts are in terms of an image rather than an object

I I

A photo is a simple case - the Image perceptions outweigh the Real perceptions

In a VE, the Real, Image and Other clusters are competing far more strongly

However, in order for a stimulus to affect our actions and thoughts (presence), only one of those middle clusters can remain activated enough to affect the upper layers

Consider a “good” VE: high immersion (HMD, earphones), real walking to move

Perceptual layers

Detectors for “real” stimuli

Detectors for “image” stimuli

Conceptual layers

Example: High immersion VR (high presence): Initial conditions

Jaggies, low FOV, etc.

“I am in a VE”

Detectors for other stimuli

Perceptual layers

Detectors for “real” stimuli

Detectors for “image” stimuli

Conceptual layers

Example: High immersion VR (high presence): Stable state

Detectors for other stimuli

Result: action/thoughts are in terms of the VE rather than the RE

This is still a more simple case - what about presence with very poor immersion equipment? (Counter Strike presence)

In these cases, top-down processing becomes far more important - the storyline finding comes into effect

Consider a “bad” VE: low immersion (desktop), but player keen “to be a terrorist” (willing suspension of disbelief)

Perceptual layers

Detectors for “real” stimuli

Detectors for “image” stimuli

Conceptual layers

Example: Low immersion VR (high presence): Initial conditions

Jaggies, flatness, etc.

“I am in playing a game”

Detectors for other stimuli

“I am a terrorist”

disctractions

Perceptual layers

Detectors for “real” stimuli

Detectors for “image” stimuli

Conceptual layers

Example: Low immersion VR (high presence): Stable state

Detectors for other stimuli

Result: action/thoughts are in terms of the VE rather than the RE (moderate amount)

Evaluation of the new model - explaining acquisition of the presence state

Strengths:

•Can explain high presence levels in low immersion situations

•Can explain low presence in high immersion situations

•Agrees with the “holodeck” idea (lucid dreaming)

•Supersedes and expands the previous model

Weaknesses:

•Vague about the processes in the conceptual layers (key to presence)

•Division of middle layer into three clusters seems abitrary

•The “other” cluster is a bit of a kludge to explain distractions

Further explanations allowed by this model - failures of presence

Failure due to interference - distractions

High levels of activation of the “other” cluster will inhibit activation in the “Real” cluster

These distraction can come from below (extraneous sounds etc.) or from above (dual tasks eg. BIP detections)

Distractions can block presence, or merely reduce it

This explains the lower “presence power” of low immersion systems

Failure due to poor stimulus quality

The VE stimuli are always occurs in the presence of other stimuli

For the “Real” node to become dominant , the “Real” stimuli must be high enough to overcome “Image” and “Other”

if the stimuli is too poor, “Image” will inhibit “Real” too much

Poor stimuli do not ensure zero presence, but certainly lower levels

Failure due to non-compliant subject

This is a more complex situation - involves 2 simultaneous failures

The first is interference - a non-compliant subject will be attending to personal thoughts, activating the “Other” cluster from above

The second is a lack of top-down activation of the “Real” node. This will make it harder to make it dominant

Predictions from the connectionist model

Many predictions can be directly made from this model, such as:

•A low immersion, poor quality system can still create high levels of presence -

prime the subject, reduce distractions

•Task performance in VR will be increased in high presence situations only if the

task requires thought in terms of the VE (spacial or thematic)

Conversely, these translate into recommendations which we can make to VR authors:

•Give more importance to the subject’s mental set (priming materials)

•Ensure that immersion is increased, even if stimulus quality is low

•Tap into user’s previous experiences where possible (increase top-down

activation)

Empirically testing the model

Key statement of the theory:

Presence levels are determined by stimulus quality, priming, distractions all singly as well as in interaction

This should be directly tested, as it is the foundation of the theory

One possibility - use a 3-way factorial design (allows checking main effects and interactions)

Set up a 3x2x3 design (about 50 subjects if we use repeated measures - not ideal)

Variable 1: stimulus quality - 3 levelsStereo, textured, radiosityMono, texturedMono, flat shading

Variable 2: priming - 3 levelspreparatory video/booklet/briefingno preparation

Variable 3: distraction - 3 levelsno distraction, visual or auditoryinfrequent, slight distractionsfrequent intense distractions

Should find:

•Each variable makes a difference to presence levels individually

•Interactions between variables (eg. high presence when priming was

high but only if distractions were low as well)