Semantic Memory Flashcards

1
Q

What is semantic memory?

A

SEMANTIC MEMORY represents our conceptual knowledge of the world – the meaning of words and objects, factual knowledge (e.g. Paris is the capital of France). Has a central role in human cognition in that it lies at the interface of language, memory and perception.

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2
Q

Irish and Piguet (2013) found that mean recall of autobiographical details from remote time periods is impaired in patients with semantic dementia. Explain this results.

A

Semanticisation of remote episodic memories. Semantic and episodic memory do show a double dissociation, yet: strong interdependence.

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3
Q

Explain the concepts of cognitive economy and inheritance in the context of Collins and Quillian’s (1969) hierarchical network model of semantic memory.

A

Hierarchical organization models: there are specific concepts and properties of concepts [at the nodes for each concept]. Additional properties can be determined by moving up the network, along the lines connecting the concepts. For example, moving from “canary” up to “bird” indicates that canaries have feathers and wings and can fly.
Cognitive economy: shared properties are only stored at higher‐level nodes.
Inheritance: Lower‐level items share properties of higher‐level items.

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4
Q

Point out some criticisms of Collins and Quillian (1969) hierarchical network model of semantic memory.

A

 Cannot explain typicality effects “a robin is a bird” vs “a penguin is a bird”.
 Problematic sentence‐verification results: “a pig is a mammal” is a slower responce than “a pig is an animal” even though the distance between the latter concepts is bigger
 “hierarchical distance” confounded with familiarity: “a canary is yellow” you probably have heard before, “a canary has skin” probably not.
Conrad (1972) controlling for familiarity found no support for a hierarchical network.

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5
Q

What is spreading activation?

A

SPREADING ACTIVATION (activation = arousal level of a node): when a node is activated, activity spreads out along all connected links. Concepts that receive activation are primed and more easily accessed from memory.

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6
Q

How did Collins and Loftus (1975) modify the original hierarchical model in order to account for tipicality / familiarity effects?

A

 Shorter links to connect closely related concepts;
 Longer linkers for less closely related concepts;
 No hierarchical structure; based on person’s experience.

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7
Q

What are the differences between an organization of the concept based on similarity (common features) and a “special categories” account?

A
  1. Categorization based on similarity: Some categories (e.g. animals) are represented differently in the brain because they tend to possess certain features (e.g. movement) that are not possessed by other categories (e.g. inanimate objects). Thus, categorization emerges because of similarities at the level of subordinate knowledge.
  2. Special categories: Some categories (e.g. animals) are represented differently by the brain because they are a special category (e.g. innate endowment of neural resources). In this example, category membership is explicitly encoded rather than inferred from similarity – i.e. categorization at a superordinate level.
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8
Q

Explained the evidence on animate–inanimate categories distinction using the sensory–functional account.

A

Evidence:
– Warrington and McCarthy (1983): patient with good knowledge of animals, foods, flowers, relative to inanimate objects.
– Warrington and Shallice (1984): four patients with the opposite profile.
Explanation: animate–inanimate categories emerge because of feature similarity rather than actual category membership. Categorization is determined by whether objects are defined more perceptually or more functionally.
 Animals and fruit = defined more by sensory knowledge (color, shape, four legs, etc.)
 Inanimate objects (e.g. tools) = defined more by their functions

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9
Q

What are some further examples of category specificity?

A

Other Types of Category Specificity:
 FOOD: Samson and Pillon (2003): Some patients have impaired semantic knowledge of food.
 BODY PARTS: autotopagnosia = inability to localize body parts on self or others. Errors are conceptual (e.g. knee-elbow, eye-ear). Can point to location of ties and gloves, but not chest and hand. Can say mouth used for eating, and name body parts.

Specificity: Alternative Theories
• Allport (1985): sharing of features is important but does not divide neatly into two different kinds.
• Caramazza & Shelton: animals have a distinct representation because they are an innate category (nothing to do with the features they have).

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10
Q

POBRIC ET AL. (2010) - CATEGORY-SPECIFIC VS. CATEGORY-GENERAL EFFECTS
THE HUB‐AND‐SPOKE MODEL Integrates classical view of abstract representation and more recent models of representation of perceptual and motor features. Describe its two main components.

A

1) A modality independent unified conceptual representation: ATL act as an amodal hub.
2) Modality‐specific (perceptual, motor, language-related) representations modality-specific association areas support sensory, verbal, and motor sources (the spokes)

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11
Q

POBRIC ET AL. (2010) - CATEGORY-SPECIFIC VS. CATEGORY-GENERAL EFFECTS
Describe the design and results: what were the effects of TMS applied on different brain regions, on the retrieval of different categories of objects?

A

Subjects named living & non-living, manipulable and non‐manipulable things (+ number reading task).
TMS over ATL (hub) impaired naming of all categories (no impact on number naming), but TMS over IPL (a spoke involved in object‐directed actions) only impaired naming of manipulable things. TMS on occipital lobe for control.

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12
Q

POBRIC ET AL. (2010) - CATEGORY-SPECIFIC VS. CATEGORY-GENERAL EFFECTS
So what is the role of ATL in semantic memory? and the one of modality specific regions?

A

Modality specific regions provide the basic sensory, motor, and verbal ingredients, while the ATL hub supports an additional amodal representation which codes the pan-modal, deep statistical structure and thus generates a high-dimensional, modality independent similarity matrix = ‘hub’ and ‘spokes’ provide important contributions to conceptualisation

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13
Q

At what level do we usually name objects? What is the effect of expertise on this general tendency?

A

Strong preference for naming at the basic level (car, elephant, chisle, sofa): best balance between distinctiveness and informativeness & requires similar means of interaction with object. Compared to subordinate (Toyota, Asian elephant, love seat, Humphrey Bogart) or superordinate (vehicle, animal, tool, furniture) levels.

Expertise is associated with naming at subordinate level. There are also cultural differences. However, familiar faces are named at the subordinate level.

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14
Q

What did Barlett from his Native American Stories experiments?

A

We use schemas of existing knowledge to process and remember the story. American students transform the story to conform to their own experience: e.g. “something black came out of his mouth” became “he foamed at the mouth”, “canoes” became “boats”.

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15
Q

What is the effect of schema-consistency on memory?

A

Stevyers and Hemmer (2012): recall was highest for objects in the most schema‐consistent category Schema-consistency aids memory. However, schema inconsistency can actually help: effect of distinctiveness.

Tricky one ehehe

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16
Q

What is some recent evidence that suggests specificity coding in semantic networks?

A

Quiroga et al, 2005 Evidence for “single cell” concepts in the brain: Single cell recording during brain surgery in humans.
FFA (faces) and PPA (places) do suggest a form of specificity coding… but there aren’t specific regions for each possible category.

17
Q

How do connectionist models (developed in the ’80s) compel single cell concepts with distributed coding evidence?

A

Various layers of units (“neurons”) with mutual connections: Input units, hidden units, output units; Connections can have different strengths (weights). Leads to parallel distributed processing
Representation = in essence an arbitrary pattern of activation and weights, but unique for each concept
Advantages:
 Realistic: resembles the brain: neurons & synapses, distributed representations;
 Robust against damage (graceful degradation);
 Can learn;
 Can generalize (similar concepts will lead to similar activation patterns);
 High capacity.
High activity in a unit does not mean specificity, low activity can be as important as high activity. Neural markers of specificity coding could be caused by anatomically local population codes.