cortical columns

Cortical Columns

Ling 411 – 11

Perspective – What we know so far: ISources of information about the brain

Aphasiology• Research findings during a century-and-a-half

Brain imaging Neuroanatomy Other research in neuroscience

• E.g., Mountcastle, Perceptual Neuroscience (1998)

Perspective – What we know so far: IILarge-Scale Representation of Information

Subsystems and their locations• Known for some important ones:

Primary areas Phonological recognition Phonological production Etc.

Interconnections among subsystems E.g., arcuate fasciculus

The Wernicke Principle

What we know so far III: Connectionism

“Wernicke’s Principle” • Each local area does a small job• Large jobs are done by multiple small areas

working together, by means of interconnecting fiber bundles

The basic principle of connectionism• Connectivity Rules• Consequence: Distributed processing

Anatomical support for connectionism

The brain is a network Composed, ultimately, of neurons

• Neurons are interconnected Axons (with branches) Dendrites (with branches)

• Activity travels along neural pathways

Consequences of basic principle of connectionism

Everything represented in the brain has the form of a network• (the “human information system”)

Therefore a person’s linguistic and conceptual system is a network• (part of the information system)

It would appear to follow that every lexeme and every concept is a sub-network (next slide)

Example: The concept DOG

We know what a dog looks like• Visual information, in occipital lobe

We know what its bark sounds like• Auditory information, in temporal lobe

We know what its fur feels like• Somatosensory information, in parietal lobe

All of the above..• constitute perceptual information• are subwebs with many nodes each• have to be interconnected into a larger web• along with further web structure for

conceptual information

Connectionism and lexicon

The information pertaining to a single lexical item must be widely distributed

That is, every lexical item is represented by a large distributed network• With subnetworks for different kinds

of information Phonological (three subwebs) Multiple subwebs for different

facets of the meaning

What we know so far IV: Determinants of location of subsystems

Genetically determined primary areas• Motor – frontal lobe• Perceptual – posterior cortex

Somatic – parietal Visual – occipital Auditory – temporal

Hierarchy Plasticity

• Consequence: Higher-level areas not in genetically determined areas

Locations of Subsystems I

Phonology is separate from grammar and meaning Phonology has three components

• Recognition (Wernicke’s area)• Production (Broca’s area)• Monitoring (Somatosensory mouth area)

Writing likewise has three components Phonological-graphic correspondences

• Alternative pathways (cf. ‘phonics’ vs. ‘whole words’)• Angular gyrus

Meaning is all over the cortex• Different areas for different kinds of words• Different areas for the network of a single concept

Grammar depends heavily on frontal lobe• In or near Broca’s area

Locations of Subsystems II

Nouns and verbs are different• In some ways (what ways?)• How to explain?

Written forms are connected to conceptual information independently of phonological forms

Writing can be accessed from meaning even if speech is impaired

Conceptual information for nouns of different categories may be in different locations

Locations of Subsystems III:

Locations of various kinds of “information”• Primary

Visual Auditory Tactile Motor

• Phonological Recognition Production Monitoring

• Etc.

What we know so far V: Processing

Processing in the cortex is• Distributed • Parallel and serial • Bidirectional

Next on the agenda:

I. Small-scale representation Cortical Columns

II. Processing at the small scale Operation of cortical columns

Vernon W. Mountcastle

From Wikipedia: He discovered and characterized the columnar organization of the cerebral cortex in the 1950s. This discovery was a turning point in investigations of the cerebral cortex, as nearly all cortical studies of sensory function after Mountcastle's 1957 paper on the somatosensory cortex used columnar organization as their basis. Indeed, David Hubel in his Nobel Prize acceptance speech said Mountcastle's "discovery of columns in the somatosensory cortex was surely the single most important contribution to the understanding of cerebral cortex since Cajal".

Vernon Mountcastle

More from Wikipedia: Mountcastle's devotion to studies of single unit neural coding evolved through his leadership in the Bard Labs of Neurophysiology at the Johns Hopkins UniversitySchool of Medicine, which was for many years the only institute in the world devoted to this sub-field, and its work is continued today in the Krieger Mind/Brain Institute. He is University Professor Emeritus of Neuroscience Johns Hopkins University.

Professor Mountcastle was elected to the National Academy of Sciences in 1966.In 1978, he was awarded the Louisa Gross Horwitz Prize from Columbia University together with David Hubel and Torsten Wiesel, who both received the Nobel Prize in Physiology or Medicine in 1981. In 1983, he was awarded the Albert Lasker Award for Basic Medical Research. He also received the United States National Medal of Science in 1986.

Quote from Mountcastle

“[T]he effective unit of operation…is not the single neuron and its axon, but bundles or groups of cells and their axons with similar functional properties and anatomical connections.”

Vernon Mountcastle, Perceptual Neuroscience (1998), p. 192

Evidence for columns

Microelectrode penetrations If perpendicular to cortical surface

• Neurons all of same response properties If not perpendicular

• Neurons of different response properties

Microelectrode penetrations in the paw area of a cat’s cortex

Columns for orientation of lines (visual cortex)

Microelectrode penetrations

K. Obermayer & G.G. Blasdell, 1993

The (Mini)Column

Extends thru the six cortical layers• Hence three to six mm in length• The entire thickness of the cortex is

accounted for by the columns Roughly cylindrical in shape About 30–50 m in diameter If expanded by a factor of 100, the

dimensions would correspond to a tube with diameter of 1/8 inch and length of one foot

Three views of the gray matter

Different stains show different features

Layers of the cortex

I – dendritic tufts of pyramidal neurons• No cell bodies in this layer

II, III – pyramidal neurons of these layers project to other cortical areas

IV – spiny stellate cells, receive activation from thalamus and transmit it to other neurons of same column

V, VI – pyramidal neurons of these layers project to subcortical areas

Various kinds of inhibitory neurons are distributed among the layers

Layers of the Cortex

From top to bottom, about 3 mm

Cortical column structure

Minicolumn 30-50 microns diameter Recurrent axon collaterals of pyramidal neurons activate

other neurons in same column Inhibitory neurons inhibit neurons of neighboring columns

Columns and neurons

At the small scale..• Each column is a little network

At a larger scale..• Each column is a node of the cortical network

The cerebral cortex:• Grey matter — columns of neurons• White matter — inter-column connections

Minicolumns and Maxicolumns

Minicolumn 30-50 microns diameter Maxicolumn – a contiguous bundle of minicolumns

(typically around 100)• 300-500 microns diameter• Dimensions vary from one part of cortex to another• In some areas at least, they are roughly hexagonal

Cortical minicolumns: Quantities

Diameter of minicolumn: 30 microns Neurons per minicolumn: 70-110 (avg. 75-80) Minicolumns/mm2 of cortical surface: 1460 Minicolumns/cm2 of cortical surface: 146,000 Neurons under 1 sq mm of cortical surface: 110,000 Approximate number of minicolumns in Wernicke’s

area: 2,920,000 (at 20 sq cm for Wernicke’s area)

Cf. Mountcastle 1998: 96

Simplified model of minicolumn I:Activation of neurons in a column

Thalamus

Other corticallocations

Subcorticallocations

IIIII

IV

VVI

Connections to neighboring columns not shown

Cell Types

Pyramidal

Spiny Stellate

Inhibitory

Simplified model of minicolumn II:Inhibition of competitors

Thalamus

Other corticallocations

IIIII

IV

V

VI

Cells in neighboring columns

Cell Types

Pyramidal

Spiny Stellate

Inhibitory

Another Quotation

“Every cellular study of the auditory cortex in cat and monkey has provided direct evidence for its columnar organization.”

Vernon Mountcastle (1998:181)

Deductions from findings about cortical columns

Property I: Cortical topography Property II: Intra-column uniformity of function Property III: Nodal specificity Property IV: Adjacency Property V: Extension of II-IV to larger columns

Deductions from findings about cortical columns

Property I: Cortical topography Property II: Intra-column uniformity of function Property III: Nodal specificity Property IV: Adjacency Property V: Extension of II-IV to larger columns

Large-scale cortical anatomy

The cortex in each hemisphere • Appears to be a three-dimensional structure• But it is actually very thin and very broad

The grooves – sulci – are there because the cortex is “crumpled” so it will fit inside the skull

Topologically, the cortex of each hemisphere (not including white matter) is..

Like a thick napkin, with• Area of about 1300 square centimeters

200 sq. in. 2600 sq cm for whole cortex

• Thickness varying from 3 to 5 mm• Subdivided into six layers

Just looks 3-dimensional because it is “crumpled” so that it will fit inside the skull

The cortex as a network of columns

Each column represents a node The network is thus a large two-dimensional array of

nodes Nodes are connected to other nodes both nearby and

distant• Connections to nearby nodes are either excitatory

or inhibitory • Connections to distant nodes are excitatory

Via long (myelinated) axons of pyramidal neurons

Deductions from findings about cortical columns

Property I: Cortical topography Property II: Intra-column uniformity of function Property III: Nodal specificity Property IV: Adjacency Property V: Extension of II-IV to larger columns

Uniformity of function within the cortical column

All neurons of a column have the same response properties

It follows that: The nodes of the cortical information network are cortical columns

The properties of the cortical column are approximately those described by Vernon Mountcastle • Mountcastle, Perceptual Neuroscience, 1998

Topological essence of cortical structure

The cortex is an array of nodes• A two-dimensional structure of

interconnected nodes (columns) Third dimension for

• Internal structure of the nodes (columns)• Cortico-cortical connections (white matter)

Deductions from findings about cortical columns

Property I: Cortical topography Property II: Intra-column uniformity of function Property III: Nodal specificity Property IV: Adjacency Property V: Extension of II-IV to larger columns

Nodal specificity

Property III: Every column (hence every node) has a specific function

Known from the experiments for all areas that have been tested

Hypothesis: nodal specificity applies throughout the cortex• Including higher-level areas• The cortex is relatively uniform in structure• Therefore, specificity should apply

generally to cortical columns• This claim needs to be investigated (soon)

Microelectrode penetrations in the paw area of a cat’s cortex

Map of auditory areas in a cat’s cortex

AAF – Anterior auditory fieldA1 – Primary auditory field PAF – Posterior auditory fieldVPAF – Ventral posterior auditory field

A1

More quantities

Neurons per minicolumn: average 75-80 Number of neurons in cortex: 27.4 billion Number of minicolumns: ca. 350 million

(27,400,000,000 / (75-80)) Neurons beneath 1 mm2 of surface: 113,000 Columns beneath 1 mm2 of surface:

14,000 – 15,000 (113,000 / (75-80))

Mountcastle 96

Features of the cortical (mini)column

75 to 110 neurons 70% of the neurons are pyramidal The rest include

• Other excitatory neurons• Several different kinds of inhibitory neurons

Findings summarized by Vernon Mountcastle, Perceptual Neuroscience (1998)

Findings relating to columns(Mountcastle, Perceptual Neuroscience, 1998)

The column is the fundamental module of perceptual systems • probably also of motor systems

Perceptual functions are very highly localized• Each column has a very specific local function

This columnar structure is found in all mammals that have been investigated

The theory is confirmed by detailed studies of visual, auditory, and somatosensory perception in living cat and monkey brains

Deductions from findings about cortical columns

Property I: Cortical topography Property II: Intra-column uniformity of function Property III: Nodal specificity Property IV: Adjacency Property V: Extension of II-IV to larger columns

Nodal Adjacency

Property IV: Nodes that are anatomically adjacent have closely related functions

This property extends beyond immediate neighbors• Adjacent nodes are functionally very similar• Nodes that are nearby but not adjacent have similar

function• Degrees of topographic closeness correspond to

degrees of functional similarity Consequence: A cortical area forms a functional map

Deductions from findings about cortical columns

Property I: Cortical topography Property II: Intra-column uniformity of function Property III: Nodal specificity Property IV: Adjacency Property V: Extension of properties II-IV to larger columns

Columns of different sizes

Minicolumn• Basic anatomically described unit• 70-110 neurons (avg 75-80)• Diameter barely more than that of pyramidal cell body (30-50 μ)

Maxicolumn (term used by Mountcastle)• Diameter 300-500 μ• Bundle of about 100 continuous minicolumns

Hypercolumn – up to 1 mm diameter• Can be long and narrow rather than cylindrical

Functional column• Intermediate between minicolumn and maxicolumn• A contiguous group of minicolumns

Functional Columns

Intermediate in size between minicolumn and maxicolumn

Hypothesized functional unit whose size is determined by experience/learning

A maxicolumn consists of multiple functional columns A functional column consists of multiple minicolumns Functional column may be further subdivided with

learning of finer distinctions

Columns of different sizes In order according to size

Minicolumn• The smallest unit• 70-110 neurons

Functional column• Variable size – depends on experience• Intermediate between minicolumn and maxicolumn

Maxicolumn (a.k.a. column)• 100 to a few hundred minicolumns

Hypercolumn• Several contiguous maxicolumns

Hypercolums: Modules of maxicolumns

A visual area in temporal lobe of a macaque monkey

Functional columns

The minicolumns within a maxicolumn respond to a common set of features

Functional columns are intermediate in size between minicolumns and maxicolumns

Different functional columns within a maxicolumn are distinct because of non-shared additional features • Shared within the functional column• Not shared with the rest of the maxicolumn

Mountcastle: “The neurons of a [maxi]column have certain sets of static and dynamic properties in common, upon which others that may differ are superimposed.”

Similarly..

Neurons of a hypercolumn may have similar response features, upon which others that differ may be superimposed

Result is maxicolumns in the hypercolumn sharing certain basic features while differing with respect to others

Such maxicolumns may be further subdivided into functional columns on the basis of additional features

That is, columnar structure directly maps categories and subcategories

Hypercolums: Modules of maxicolumns

A visual area in the temporal lobe of a macaque monkey

Category (hypercolumn)

Subcategory(can be further subdivided)

The Proximity Principle

Closely related cortical functions tend to be in adjacent areas• Broca’s area and primary motor cortex• Wernicke’s area and primary auditory area• Angular gyrus and Wernicke’s area• Brodmann area 37 and Wernicke’s area

A function that is intermediate between two other functions tends to be in an intermediate location• Wernicke’s area – between primary auditory

area and Angular gyrus

Deductions from findings about cortical columns

Property I: Cortical topography Property II: Intra-column uniformity of function Property III: Nodal specificity Property IV: Adjacency Property V: Extension of II-IV to larger columns Property VI: Competition

Nodal interconnections (known facts from neuroanatomy)

Nodes (columns) are connected to• Nearby nodes• Distant nodes

Connections to nearby nodes are either excitatory or inhibitory • Via horizontal axons (through gray matter)

Connections to distant nodes are excitatory only• Via long (myelinated) axons of pyramidal neurons

Local and distal connections

excitatory

inhibitory

Lateral inhibition

Inhibitory connections Extend horizontally to other columns in the vicinity

• These columns are natural competitors Enhances contrast

Inhibitory connections Based on Mountcastle (1998)

Columnar specificity is maintained by pericolumnar inhibition (190)

• Activity in one column can suppress that in its immediate neighbors (191)

Inhibitory cells can also inhibit other inhibitory cells (193)

Inhibitory cells can connect to axons of other cells (“axoaxonal connections”)

Large basket cells send myelinated projections as far as 1-2 mm horizontally (193)

end