Neural Correlates of Integral and Separable Processing During Category Learning Catherine Hanson    Stephen José Hanson    Tara Schweighardt Rutgers University, Newark, NJ  Introduction Categorization  is  a  fundamental  cognitive  function  imposing  order  on  stimuli;  whether  objects  or  actions,  sights  or  sounds.  Crucial  to  the  ability  to  categorize  is  the  ability  to  selectively  attend  to  the  relevant  attributes  of  the  to­be­categorized  input.    Garner  (1974)  used  the  term  perceptual  structure  to  describe  the  way  dimensions  of  a  stimulus  combine  perceptually.    Factors  such  as  sensory  constraints,  development,  or  learning  can  affect  whether  attributes  are  integrally  related,  i.e.,    correlated,  or  separably  related,  i.e.,  seen  as  distinct  dimensions. Attributes that are integrally related form a single percept.   Separable attributes remain distinct and the percept is of a collection of  attributes.    Developmentally,  integral  processing  has  been  shown  to  proceed the onset of separable processing (Smith, 1989) and adults can  be  biased  smoothly  towards  either  type  of  processing  depending  on  category  structure.    In  addition  to  the  properties  of  the  input,  it  is  important to consider factors that may influence how the observer uses  those  properties  during  category  learning.  This  study  has  two  goals.  First,  to  explore  how  strategy  or  attentional  set  interacts  with  stimulus  dimensions of face stimuli during categorization. Second, to examine the  neural correlates associated with processing categories that mediate the  seamless switching between these two types of attentional processing. 

Method Scanning was done on a Siemens Allegra 3T system.  Stimuli were rear  projected onto a mirror in the head cage.  Responses were recorded with  an MRI compatible button box.  Subjects were normal, healthy adults.

that  covaried (integral task).  Subjects categorized the entire set of  faces three times; i.e., there were three categorization blocks. 0

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Filtration Task (separablel)

Condensation Task (integral)

Results Behavioral Data Forty  subjects  performed  the  judgement  and  categorization  tasks  outside  of  the  magnet.    An  analysis  of  the  correct  response  times  during  categorizataion  yielded  a  significant  main  effect  for    Categorization Task, F(1, 68) = 7.43, p <.01, and a significant inter­ action between Judgement Task and Categorization Task, F(1,68) =  4.33, p <.05.  An analysis on the mean accuracy of responses dur­ ing the categorization task yielded a similar pattern of results, i.e., a  main  effect  for  Categorization  Task,  F(1,68)  =  46.24,  p  <.001.  and  an interaction between Judgement Task and Categorization Task, F (1,68) = 3.77, p <.06.

Judgement Tasks 100

Condensation Filtration

Mean % Correct Categorization

1000

Mean Correct RT (msec)

Subjects  first  made  similarity  judgments about  pairs  of schematic  faces.  One  group based their judgements  on the similarity of features  (eyes or  mouth; separable priming) wheras the other group judged the similarity of  the emotion expressed by the faces (integral priming).  

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Condensation Filtration

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Feature

Judgement Task

fMRI Analysis The  fMRI  scans  were  analyzed  with  the  FSL    software  (Image  Analysis Grouup, FMRIB, Oxford, UK). Each block of categorization  trials  was  contrasted  with  a  block  of  rest.    The  results  of  this  analysis  was  used  in  a  second­level,  between­subjects  analysis.  This  analysis  found  a  trend  in  the  data  similar  to  that  found  in  the  behavioral data.  Specifically, a significant main effect was found for  Categorization  Task  and  for  the  interaction  between  Judgement  Task and Categorization Task. Task  Effect:   The  between­groups  analysis  of  the  fMRI  data  mirrored  that  of  the  behavioral  data  in  showing  a  significant  task  effect;  i.e., the filtration task was easier than the condensation task.   Areas  demonstrating  super­threshold  activation  were:    anterior  cingulate, caudate, cingulate gyrus, and medial frontal gyrus.  Shown  below are the tmaps for the third categorization block.  

Anterior Cigulate (14, 24, 24) Caudate (­12, 0, 20) Cingulate Gyrus ( ­18, ­2, 40) Medial Frontal Gyrus (­18, ­2, 40)             Corrected cluster level,                   F = 4.12, p < .05

Interaction  Effect:    In  addition  to  the  task  effect,  the    between­ groups  analysis  revealed  a  significant  interaction  between  the  judgement  task  (Emotion,  Feature)  and  categorization  task  (Condensation, Filtration) reflecting those areas most active when the  categorization task was incompatible with the judgement task.  

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Feature

Following    the  judgement  task,  subjects  were  asked  to  categorize  a  set  of  new  faces  into  two  categories.    All  subjects  categorized  the  same set of faces; however, for one group, the faces were categorized  on  the  basis  of  a  single  feature  (separable  task),  and  for  another  group, the same faces were categorized on the basis of two features

Cingulate Gyrus

Parahippicampal Gyrus

Block 1

Block 2

Block 3

Our finding that anterior cingulate, caudate, cingulate gyrus, and  medial frontal gyrus are involved in category processing replicates  other work that has examined the neural correlates of category  processing.  What we believe to be unique is our finding that  parahippocampal gyrus and posterior cingulate appear to moderate the  way stimulus features are processed.  These areas were most active  when the attentional set (emotion or feature) conflicted with the the  type of category structure being learned (integral or separable).  In  addition, the principal components analysis indicates that category  learning is reflected in  the location and orientation of patterns of  activation specific to the level of knowledge attained.

References

Judgement Task

Feature Task

Categorization Tasks

PCA  Analysis:   Supra­threshold  voxels  were  eroded  using  a  connectivity  measure  to  eliminate  sparsely  connected  voxels.    The  remaining  voxels  were  analyzed  using  the  following  principle  components analysis:  the voxel cooridinates of the of the remaining  voxels  were  placed  in  an  N  X  3  matrix,  M,  and  then  an  eigen­ decomposition was then performed on the covariance matrix  Mt M.

Discussion

80

50

0

Emotion Task

judgements were better on the Filtration task than on the Conden­ sation  task.    Those  subjects  who  had  performed  the  emotion  judgements  were  equally  good  on  both    types  of  categorization  tasks.

Garner,  W.R.    (1974).    The  Processing  of  Information  and  Structure.  Lawrence  Erlbaum,  Potomac,  Maryland, 1974.

Performance  on  the  categorization  task  was  also  analyzed  for  sub­ jects who were scanned.  The pattern of results was similar to that  obtained  for  subjects  who  had  not  been  scanned.    The  data  were  analyzed separately for the three categorization blocks.  All subjects  found the Filtration (separable) task to be simpler than the Conden­ sation (integral) task no matter what judgement task they had origi­ nally performed.  In addition, those subjects who had made feature

Smith,  L.B.  (1989).    From  global  similarity  to  kinds  of  similarity:  The  construction  of  dimensions  in  development.    In  S.  Vosniadou  and  A.  Ortony  (Eds.),  Similarity  and  analogical  reasoning  (pp.  146 ­178).  Cambridge: Cambridge  University Press. Parahippocampal Gyrus (11 ­46 4) Posteriior Cingulate (12 ­44 8)          corrected cluster level,                F=3.98, p <.05

Acknowledgements We  would  like  to  thank  the  James  S.  McDonnell  Foundation  and  NSF  (EIA­0205178)  for  their  generous  support.    Thanks  also  to  Donovan  Rebbechi for his help with the principal components analysis.

Neural Correlates of Integral and Separable Processing ...

the emotion expressed by the faces (integral priming). Neural Correlates of Integral and Separable Processing During Category Learning. Catherine Hanson Stephen José Hanson Tara Schweighardt. Rutgers University, Newark, NJ. Categorization Tasks. Following the judgement task, subjects were asked to categorize a.

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