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Lecture Overview Regier System: Limitations Image Schemas: Recap Force Dynamic Schemas: Recap Sensory-Motor Schemas Evidence in Primates Evidence in Humans Do motor schemas play a role in language? A Computational Model of Motor Schemas Learning Hand Action terms (Bailey) Cultural Schemas and frames

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Lecture Overview. Regier System: Limitations Image Schemas: Recap Force Dynamic Schemas: Recap Sensory-Motor Schemas Evidence in Primates Evidence in Humans Do motor schemas play a role in language? A Computational Model of Motor Schemas Learning Hand Action terms (Bailey) - PowerPoint PPT Presentation

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Page 1: Lecture Overview

Lecture Overview

• Regier System: Limitations• Image Schemas: Recap• Force Dynamic Schemas: Recap• Sensory-Motor Schemas

– Evidence in Primates– Evidence in Humans

• Do motor schemas play a role in language?• A Computational Model of Motor Schemas• Learning Hand Action terms (Bailey)• Cultural Schemas and frames

Page 2: Lecture Overview

Limitations

• Scale

• Uniqueness/Plausibility

• Grammar

• Abstract Concepts

• Inference

• Representation

Page 3: Lecture Overview

Force Dynamics, modals and causatives

• A gust of wind made the pages of my book turn.

• The appearance of the headmaster made the pupils calm down.

• The breaking of the dam let the water flow from the storage lake.

• The abating of the wind let the sailboat slow down.

Page 4: Lecture Overview

Schematic Representation(Talmy)

Page 5: Lecture Overview

FD Patterns

• A gust of wind made the pages of my book turn.

• The appearance of the headmaster made the pupils calm down.

• The breaking of the dam let the water flow from the storage lake.

• The abating of the wind let the sailboat slow down.

Page 6: Lecture Overview

Semantic field Force-dynamics representation

Physical The ball kept rolling along the green

Physical/psychological 

John can't go out of the house

Intra-psychological He refrained from closing the door

Intra-psychological (lexicalized)

She's civil to him 

Socio-psychological  She gets to go to the park

Page 7: Lecture Overview

Closed Class vs. Open Class terms

• Image Schematic and Force Dynamic Patterns are expressed by closed class terms in language– Prepositions (in, on, into, out)

– Modals and causatives (make, let, might, prevent)

• How about open class terms?– Verbs and Event descriptions –

• Motor Schemas - Embodied

– Is there evidence for motor schemas and if so are they used in language?

• Frames – Composed from Image and motor schemas -Cultural

Page 8: Lecture Overview

Coordination

• PATTERN GENERATORS, separate neural networks that control each limb, can interact in different ways to produce various gaits.

– In ambling (top) the animal must move the fore and hind leg of one flank in parallel.

– Trotting (middle) requires movement of diagonal limbs (front right and back left, or front left and back right) in unison.

– Galloping (bottom) involves the forelegs, and then the hind legs, acting together

Page 9: Lecture Overview

Sensory-Motor Schemas

•A sensory (perceptual) schema determines whether a given situation is present in the environment. – Object Detection– Spatial relation recognition

• Execution of current plans is made up of motor schemas which are akin to control systems but distinguished by the fact that they can be combined to form coordinated control programs

• Sensory and Motor Schemas are closely coupled circuits sensory-motor schemas.

Page 10: Lecture Overview

The neural theory

Human concepts are embodied. Many concepts make direct use of the sensory-motor capacities of our body-brain system.

• Many of these capacities are also present in non-human primates.

• Let us look at concepts that make use of our sensory-motor capacities, ex. Grasp.

Page 11: Lecture Overview

Area F5

General Purpose Neurons:General Grasping

General Holding

General Manipulating

Page 12: Lecture Overview

AA Grasping with the mouth

BB Grasping with the cl. hand

CC Grasping with the ipsil. hand

General Purpose Neurons in Area F5General Purpose Neurons in Area F5

(Rizzolatti et al. 1988)

Page 13: Lecture Overview

General Purpose Neurons Achieve

Partial Universality: Their firing correlates with a goal-oriented action of a general type, regardless ofeffector or manner.

Page 14: Lecture Overview

Area F5cArea F5c

Convexity region of F5:

Mirror neurons

Page 15: Lecture Overview

F5c-PFF5c-PF

Rizzolatti et al. 1998

Page 16: Lecture Overview

(Rizzolatti et al. Cog Brain Res 1996)

Observed Action

Executed Action

Executed Action

Strictly congruent mirror neurons (~30%)

Page 17: Lecture Overview

Category Loosening in Mirror Neurons (~60%)(Gallese et al. Brain 1996)

A [C] is Observe (Execute) Precision Grip (Prototype) B [D] is Observe (Execute) Whole Hand Pre-hension

Page 18: Lecture Overview

The F5c-PF circuit

Links premotor area F5c and parietal area PF (or 7b).

Contains mirror neurons.

Mirror neurons discharge when:

Subject (a monkey) performs various types of goal-related hand actions

and when:

Subject observes another individual performing similar kinds of actions

Page 19: Lecture Overview

Phases

Area F5 contains clusters of neurons that control distinctphases of grasping: opening fingers, closing fingers.

Jeannerod, et al., 1995; Rizzolatti, et al., 2001.

Page 20: Lecture Overview

Mirror Neurons Achieve

Partial Universality, since they code an action regardless of agent, patient,modality (action/observation/hearing),manner, location.

Partial Role Structure, since they codean agent role and a purpose role.

The Agent Role: In acting, the Subject is an agent of that action.In observing, the Subject identifies the agent ofthe action as having the same role as he haswhen he is acting – namely, the agent role.

The Purpose Role: Mirror neurons fire only forpurposeful actions.

Page 21: Lecture Overview

Mirror Neurons Achieve

Category tightening and loosening

Page 22: Lecture Overview

The F4-VIP circuit

Page 23: Lecture Overview

The F4-VIP Circuit

Links premotor area F4 and parietal area VIP.

Transforms the spatial position of objects in peri-personal space

into motor programs for interacting with those objects.

Examples:

Reaching for the objects, or moving away from them

with various parts of your body such as the arm or head.

Page 24: Lecture Overview

Area F4Area F4

Arm reaching

Head turning

Page 25: Lecture Overview

Somato-Centered Bimodal RFs in area F4Somato-Centered Bimodal RFs in area F4

(Fogassi et al. 1996)

Page 26: Lecture Overview

Somato-Centered Bimodal RFs in area VIPSomato-Centered Bimodal RFs in area VIP

(Colby and Goldberg 1999)

Page 27: Lecture Overview

AIP and F5 (Grasping) in Monkey

F5 - grasp commands inpremotor cortexGiacomo Rizzolatti

AIP - grasp affordancesin parietal cortexHideo Sakata

Page 28: Lecture Overview

Size Specificity in a Single AIP Cell

•This cell is selective toward small objects, somewhat independent of object type ( Hideo Sakata)

•Note: Some cells show size specificity; others do not.

Page 29: Lecture Overview

Summary of Fronto-Parietal Circuits

Motor-Premotor/Parietal Circuits PMv (F5ab) – AIP Circuit

“grasp” neurons – fire in relation to movements of hand prehension necessary to grasp object

F4 (PMC) (behind arcuate) – VIP Circuit transforming peri-personal space coordinates so can move toward objects

PMv (F5c) – PF Circuit F5c different mirror circuits for grasping, placing or manipulating object

Together suggest cognitive representation of the grasp, active in action imitation and action recognition

Page 30: Lecture Overview

MULTI-MODAL INTEGRATION

The premotor and parietal areas, rather than havingseparate and independent functions, are neurally integratednot only to control action, but also to serve the function ofconstructing an integrated representation of:

(a) Actions, together with (b) objects acted on, and (c) locations toward which actions are directed.

In these circuits sensory inputs are transformed in order toaccomplish not only motor but also cognitive tasks, such asspace perception and action understanding.

Page 31: Lecture Overview

Modeling Motor Schemas

• Relevant requirements (Stromberg, Latash, Kandel, Arbib, Jeannerod, Rizzolatti)

– Should model coordinated, distributed, parameterized control programs required for motor action and perception.

– Should be an active structure.

– Should be able to model concurrent actions and interrupts.

– Should model hierarchical control (higher level motor centers to muscle extensor/flexors.

• Computational model called x-schemas (http://www.icsi.berkeley.edu/NTL)