Midterm 1

Midterm 1

Oct. 6 in class

Review Session after class on Monday

Read this article for Friday Oct 8th!

Mental Representations

• Mental representations can start with sensory input and progress to more abstract forms

– Local features such as colors, line orientation, brightness, motion are represented at low levels

How might a neuron “represent” the presence of this line?


• Mental representations can start with sensory input and progress to more abstract forms

– Local features such as colors, line orientation, brightness, motion are represented at low levels

A “labeled line”- Activity on this unit “means” that

a line is present- Does the line actually have to

be present?


• Mental representations can be “embellished”

- Kaniza Triangle is represented in a way that is quite different from the actual stimulus

-the representation is embellished and extended

First Principles

• What are some ways that information might be represented by neurons?

First Principles

• What are some ways that information might be represented by neurons?

– Magnitude might be represented by firing rate (e.g. brightness)

– Presence or absence of a feature or piece of information might be represented by whether certain neurons are active or not – the “labeled line” (e.g. color, orientation, pitch)

– Conjunctions of features might be represented by coordinated activity between two such labeled lines

– Binding of component features might be represented by synchronization of units in a network

V I S I O N S C I E N C E

Visual Pathways

• Themes to notice:

– Contralateral nature of visual system

– Information is organized:• According to spatial location

• According to features and kinds of information

Visual Pathways

• Image is focused on the retina

• Fovea is the centre of visual field– highest acuity

• Peripheral retina receives periphery of visual field– lower acuity– sensitive under low light

Visual Pathways

• Retina has distinct layers

Visual Pathways


• Photoreceptors– Rods and cones respond to

different wavelengths

Visual Pathways


• Amacrine and bipolar cells perform “early” processing

– converging / diverging input from receptors

– lateral inhibition leads to centre/surround receptive fields - first step in shaping “tuning properties” of higher-level neurons

Visual Pathways


– signals converge onto ganglion cells which send action potentials to the Lateral Geniculate Nucleus (LGN)

– two kinds of ganglion cells: Magnocellular and Parvocellular

• visual information is already being shunted through functionally distinct pathways as it is sent by ganglion cells

Visual Pathways

• visual hemifields project contralaterally– exception: bilateral

representation of fovea!

• Optic nerve splits at optic chiasm

• about 90 % of fibers project to cortex via LGN

• about 10 % project through superior colliculus and pulvinar– but that’s still a lot of fibers!

Note: this will be important when we talk about visuospatial attention

Visual Pathways

• Lateral Geniculate Nucleus maintains segregation:

– of M and P cells (mango and parvo)

– of left and right eyes

P cells project to layers 3 - 6

M cells project to layers 1 and 2

Visual Pathways

• Primary visual cortex receives input from LGN

– also known as “striate” because it appears striped when labeled with some dyes

– also known as V1

– also known as Brodmann Area 17

Visual Pathways

W. W. Norton

• Primary cortex maintains distinct pathways – functional segregation

• M and P pathways synapse in different layers

The Role of “Extrastriate” Areas

• Different visual cortex regions contain cells with different tuning properties


• Consider two plausible models:

1. System is hierarchical:– each area performs some elaboration on the input it is given

and then passes on that elaboration as input to the next “higher” area

2. System is analytic and parallel:– different areas elaborate on different features of the input


• Functional imaging (PET) investigations of motion and colour selective visual cortical areas

• Zeki et al.

• Subtractive Logic– stimulus alternates between two scenes that differ only in

the feature of interest (i.e. colour, motion, etc.)


• Identifying colour sensitive regions

Subtract Voxel intensities during these scans… …from voxel

intensities during these scans

…etc.Time ->


• result– voxels are identified that are preferentially selective for

colour– these tend to cluster in anterior/inferior occipital lobe


• similar logic was used to find motion-selective areas

Subtract Voxel intensities during these scans… …from voxel

intensities during these scans

…etc.Time ->

MOVING STATIONARY MOVING STATIONARY


• result– voxels are identified that are preferentially selective for

motion

– these tend to cluster in superior/dorsal occipital lobe near TemporoParietal Junction

– Akin to Human V5


• Thus PET studies doubly-dissociate colour and motion sensitive regions

• Electrical response (EEG) to direction reversals of moving dots generated in (or near) V5

• This activity is absent when dots are isoluminant with background



• V4 and V5 are doubly-dissociated in lesion literature:



– achromatopsia (color blindness): • there are many forms of color blindness• cortical achromatopsia arises from lesions in the area of V4• singly dissociable from motion perception deficit - patients with

V4 lesions have other visual problems, but motion perception is substantially spared



– akinetopsia (motion blindness): • bilateral lesions to area V5 (extremely rare)• severe impairment in judging direction and velocity of

motion - especially with fast-moving stimuli• visual world appeared to progress in still frames• similar effects occur when M-cell layers in LGN are

lesioned in monkeys

How does the visual system represent visual information?

How does the visual system represent features of scenes?

• Vision is analytical - the system breaks down the scene into distinct kinds of features and represents them in functionally segregated pathways

• but…

• the spike timing matters too!

Visual Neuron Responses

• Unit recordings in LGN reveal a centre/surround receptive field

• many arrangements exist, but the “classical” RF has an excitatory centre and an inhibitory surround

• these receptive fields tend to be circular - they are not orientation specific

How could the outputs of such cells be transformed into a cell with orientation specificity?


• LGN cells converge on “simple” cells in V1 imparting orientation (and location) specificity


• LGN cells converge on simple cells in V1 imparting orientation specificity

• Thus we begin to see how a simple representation - the orientation of a line in the visual scene - can be maintained in the visual system– increase in spike rate of specific neurons indicates presence of a line

with a specific orientation at a specific location on the retina

– Why should this matter?


• Edges are important because they are the boundaries between objects and the background or objects and other objects


• This conceptualization of the visual system was “static” - it did not take into account the possibility that visual cells might change their response selectivity over time

– Logic went like this: if the cell is firing, its preferred line/edge must be present and…

– if the preferred line/edge is present, the cell must be firing

• We will encounter examples in which these don’t apply!

• Representing boundaries must be more complicated than simple edge detection!


• Boundaries between objects can be defined by color rather than brightness


• Boundaries between objects can be defined by texture


• Boundaries between objects can be defined by motion and depth cues

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Midterm 1

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