A Neural Network Model of Subliminal Priming

1. A Neural Network Model of Subliminal Priming Howard Bowman Computing Laboratory, University of Kent at Canterbury Collaborators: Friederike Schlaghecken (Psychology, Univ Warwick) Adam Aron (Psychiatry, University of Cambridge) Prof. Martin Eimer (Psychology, Birkbeck College) Prof. Phil Barnard (Cognition and Brain Sciences Unit)

2. Contents • Connectionism Now • Subliminal Priming • Eimer and Schlaghecken Pattern Masked Priming • Lateral Inhibition and Opponent Processes • The Model • Predictions and Future Directions

3. Connectionism - The Claim • Connectionism claims to offer a bridge between cognition and the brain. • How complex behaviour emerges from the interaction of a multitude of computationally unsophisticated (one might even say dumb) units.

4. Is this claim justified? • Arguments against Connectionism • Neural networks are not actually biologically plausible, e.g. problems with backpropagation • How are computational implementations related to psychological theories? Does the model work because of the theory it realises or because of hidden implementation assumptions? • Models can do anything, e.g. backpropagation can learn any computable function!

5. Connectionism Now • Biological plausibility • all models are abstractions • connectionist abstractions are becoming more grounded, e.g. spiking neurons and biologically plausible learning • re-circulation algorithms instead of backpropagation • Hebbian learning, sparse representations and sparsification techniques

6. Reducing the degrees of freedom • work closely within context of existing cognitive theory; • apply biological constraints; • systematic and transparent parameter setting (e.g. do statistics on model); • make clear the key mechanisms involved; • testable predictions from the models (especially counter-intuitive ones).

7. Theoretical Background • Two central theoretical issues • the role of conscious control in visuomotor performance • the “cognitive levels” at which inhibition functions

8. Issue 1: Consciousness and Visuomotor Performance • Tight coupling of vision and action • actions planned on basis of visual information • action execution guided by vision • The debate, • “To what extent is conscious experience a prerequisite for the control of visuomotor performance?” • “Is there a direct, below conscious, link from vision to action?” Direct Parameter Specification Hypothesis [Neumann & Klotz,94]

9. Tentative Support for Direct Parameter Specification (1) • Blindsight [Weiskrantz et al,74] • above chance visual guided action in absence of visual awareness • Visual Illusions [Carey,01] • movements (e.g. grasp apertures) resist visual illusions • Visual Form Agnosia [Milner et al,91] • profound deficits in object recognition, but intact visuomotor performance Note: dissociation dorsal (where) stream ventral (what) stream but subcortical routes also significant

10. Support for Direct Parameter Specifiction (2) • More direct evidence provided by masking experiments. Two varieties, • Metacontrast masked priming • Pattern masked priming

11. Metacontrast Masked Priming • Fehrer & Raab (1962), Neumann & Klotz (1994), Vorberg (2002) • For example, [Neumann & Klotz,94] • subjects not told of presence of prime • subjects either respond to diamonds or squares • respond left or right depending upon target position • target stimulus metacontrast masks the prime • strict criteria for perception of prime - signal detection

12. Neumann and Klotz Metacontrast Priming Paradigm [Neumann & Klotz,94]

13. Results • Positive compatibility results, • compatible trials yield behavioural benefits (both errors and reaction times) • incompatible trials yield behavioural costs

14. Signal Detection Blocks • Signal detection blocks follow reaction time blocks (rules out learning) • subjects asked to state whether prime present on 5 point scale, e.g. “I am pretty sure that prime was present” • signal detection gives d-prime statistically equivalent to zero, i.e. no phenomenological experience of prime

15. Implications • “.. a stimulus can have access to the motor system and activate or even start an intended, planned response without being represented in consciousness.” [Neumann & Klotz,94] • Note further, this preconscious processing requires integration of form (diamonds vs squares) and position (left vs right) information. More than just a presence / absence judgement. what - where dissociation??

16. Issue 2 - Levels of Inhibition • Inhibitory mechanisms certainly ubiquitous in brain, e.g. GABAergic interneurons throughout cortex and subcortical regions. • Typically, psychological theories situate inhibitory mechanisms at level of attentional (executive) function, e.g. • (working memory) Baddeley’s central executive • Shallice’s Supervisory Attentional System Inhibition as a (pre)frontal lobe function?

17. Inhibition and task / set shifting • Neuropsychological example - frontal lobe damage yields perseveration errors (e.g. Wisconsin Card Sorting task) and increased distractibility. • Psychological example - negative priming (conscious inhibition of distractors) • Inhibition argued to be central to conscious attentional control • QUESTION: could inhibition arise at level of direct parameter specification?

18. Eimer and Schlaghecken’s Pattern Masked Priming Task A subliminal priming paradigm • response buttons under left and right index fingers; • basic stimuli - • neutral stimuli - <> and ><; and • mask - superimposition of >> and << >> (right response) and << (left response); (other masks explored, e.g. classic pattern masks)

19. 16 ms NOTE: Prime is subliminal (verified by forced choice blocks, which follow RT-blocks.) >> 100 ms PRIME >> >> 100 ms MASK >> Time TARGET

20. Conditions

21. Eimer 99 - Results

22. Implications • negative compatibility; • behavioural costs on compatible trials and benefits on incompatible trials; • candidate explanation: inhibitory processes at work; • suppression of response activation (even before response fires); • supporting evidence from EEG study.

23. Eimer 99 - LRPs

24. Further Implications • LRP shows it is more than just sensory priming, i.e. residual perceptual activation. Prime induced activation propagated right through to response systems.

25. Candidate Explanation • low-level inhibitory mechanism • “emergency brake” - suppress response once visual evidence for that response removed • possibly part of a larger “clearing-up” mechanism - suppress activation traces of completed responses in order to enable sequences of co-ordinated actions.

26. Data to reproduce • short mask-target SOAs (0-32ms) yield positive compatibility (target and mask presented together) • longer mask-target SOAs (64ms - 150ms (ish)) yield negative compatibility • low strength primes yield positive compatibility. Reduce strength by, • presenting prime in periphery, or, • presenting prime centrally, but overlaid with random-dot degradation

27. Further Data to Reproduce • forced choice - at chance • forced choice blocks both with and without target • forced choice blocks follow reaction time response blocks (thus, learning to detect prime not an explanation) • QUESTION?? - how can priming affect target response speeds but not forced choice judgements? NOTE: Signal-detection theory not used.

28. Further LRP Data Schlaghecken and Eimer data

29. Mechanism (1) - competition and masking • masked and masking stimuli compete for shared neural resources, see [Keysers & Perrett,02] • neural trace of prime rapidly suppressed when mask presented • implementation possibilities, • lateral inhibition • gating mechanism

30. Mechanism (2) - response competition • responses compete in a winner take all fashion. • only one response can be executed. • sustains (in fact, accentuates) response separation, c.f. M00 condition. • implemented through lateral inhibition between response nodes. excitatory inhibitory response 2 response 1

31. Mechanism (3) - Opponent Processes • previously investigated in a number of models, e.g. • negative priming and inhibition of return [Houghton & Tipper,94] • serial order in working memory and in motor action sequencing [Houghton,90]

32. An Opponent Circuit Excitatory Link Response Node (Opponent) OFF Node Inhibitory feedback can be threshold gated Inhibitory Link OFF node just an inhibitory interneuron

33. Mechanism (4) - S-R Binding • nodes in relevant stimulus-response pathways pre-activated and hence foregrounded from the set of possible S-R bindings • called response-set delineation in [Bowman et al,02] • implemented by giving backgrounded nodes a strongly negative bias

34. Excitatory Gating Links: Links: Inhibitory Links: Perceptual Pathways: apply time averaging to perceptual input The Network Response Selection: difference between response node activation Mask/ Neutral Example (left compatible): 1 cycle of <<; 6 cycles of the mask; 6 cycles of <<. 1 << LEFT ON 5 7 OFF 14 2 >> 8 6 OFF 15 3 RIGHT ON Perception Layer Perceptual Pathways Response Selection Layer

35. Formal Parameters Time averaging activation function: input to node on cycle i regulates time averaging activation on cycle i+1 Sigmoidal, (squashes activation into range 0 to +1) t set to 0.3

36. Basic Results • difference between response nodes gives separation; • similar pattern to LRP.

37. Response Time Comparison (mean response times) Assuming: (i) one cycle corresponds to 16.6666 ms; (ii) selection criteria - separation magnitude (absolute value) - 0.4; (iii) latency of 200 ms compared to Eimer data. NOTE: RTs currently very approximate!

38. Reduced Strength Prime • Prime induced response activation does not cross opponent circuit threshold; • reproduces basic switch to positive compatibility

39. Observations (i) • model RTs in right general ball park (parameter optimizations would improve these); • RT difference between conditions is good; • time course of separation close to LRP profile.

40. Observations (ii) • explanation of forced choice results, • selection criteria is the model’s analogue of super / subliminality threshold (simplification since just located at action end). • while selection criteria not satisfied, no evidence available for decision process, i.e. at chance • residual activation from prime only affects outcome if it is built upon (since it influences speed with which threshold (selection criteria) is crossed) • one reason for selection criteria is to ensure background fluctuations do not yield overt responses

41. Relationship to Houghton and Tipper Model • inhibition modulated by high level attentional processes in HT94; • selection of target from distractor in negative priming; • orienting system in inhibition of return; • our model - a direct (low level) link from perception to action - inhibition is a “dumb” mechanism (not directed by high-level attention).

42. Further Work • Biological plausibility - fMRI studies suggest basal ganglia as locus of inhibition • broaden scope of model - locate pattern and metacontrast masked priming in same modelling framework • modelling error rates

43. Conclusions • Masked priming data fits with a theory of consciousness in which, • “when we apperceive the stimulus, we have usually already started responding to it; our motor apparatus does not wait for consciousness, but does restlessly its duty, and our consciousness watches it and is not entitled to order it about.” [Munsterberg,1889] • Two largely independent effects of a stimulus, • determines a motor response • has later effect in consciousness Also see Libet’s work and implicit memory literature

44. Further Conclusions • Effects not restricted to specific stimulus-response connections [Neumann & Klotz,94] • rapidly modified through instruction cues • cannot be explained through automaticity

45. Discussion Points • Why this model? • Clearly (even at psychological level) there are many models which could satisfy the data (even infinitely many); • In favour of model, + Simple and canonical; + Opponent networks used to model a number of inhibitory phenomena; + Increasing body of empirical data explained.