Lecture 2 - Neuronal Structure and Basics of Synaptic Transmission

Neuronal structure and basics of synaptic

transmission Tansu Celikel

!Office hours: Anytime with prior arrangement

(t.celikel@donders.ru.nl)

NWI-BB034B NEUROBIOLOGYMay 16, 2014

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Meta-analysis on the video-access statistics (over 63 videos):87 access scored 9.6 3 access scored 2.1

73% of the students earned a passing score

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dpneuro What will we learn in this lecture?

Classification of neurons by morphological, biochemical and electrical characteristics

Canonical neuron under electron microscope

Electrical vs chemical neurotransmission

Synaptic events from neurotransmitter to postsynaptic activation

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dpneuro Not every neuron is the same: Different classes of neurons have different functions

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L1

L2

L3

L4

L5

L6

Each nuclei/layer consists of different sets of neurons

How to classify neuronsby morphological features by biochemical markers

by electrical characteristics

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dpneuro How to classify neurons : Inhibitory vs excitatory

= 1

Dale’s Law

Version 1: A neuron is either excitatory or inhibitory in its influence on other neurons.

!Version 2:

A neuron secretes a single (traditional) neurotransmitter at its synapses.

Inhibitory neurons secrete neurotransmitters that cause membrane hyperpolarization in the postsynaptic neurons

Excitatory neurons secrete neurotransmitters that cause membrane depolarization in the postsynaptic neurons

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dpneuro How to classify neurons

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Most neurons contain three major compartmentsSoma Contacted only by few (inhibitory) synapses

Dendrites Main receptive surface of the cell

Compartments for spatial and temporal integration of incoming informationSeveral primary dendrites

In pyramidal cells: 1 apical dendrite + 2 or more basal primary dendrites

Axon Efferent part of the cell, reveals projection domains

Initial segment targeted by specific inhibitory synapses

All features have important computational significance

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dpneuro Study of single neuron morphology

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Intracellular injection of tracers (e.g. biocytin)

Sparse expression of fluorescent proteins

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Two intracellularly filled neurons with biocytin

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apical dendrite

basal dendrite

axon

boutons

spines

Study of single neuron morphology

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dpneuro Form follows function

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Gray’s anatomy - Figure 627

(after Ramón y Cajal)

Gray’s anatomy - Figure 628

collateral axon

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dpneuro How to classify neurons: Somatodendritic features

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Ascoli et al, 2008

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dpneuro How to classify neurons: Somatodendritic features

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Excitatory neuron examples from the primary somatosensory cortex

L1

L2

L3

L4

L5

L6

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dpneuro How to classify neurons: Somatodendritic features

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multipolarbitufted

bipolar

Kawaguchi et al, 1995

Inhibitory neurons

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How to classify neurons: Axonal projection patterns

Bouton distribution reveals whether region is traversed or innerved

I II !III !IV !!Va !!Vb !!!VI !!!wm

Neurons can establish 1000s of boutons (synapses) in a layer specific distribution

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How to classify neurons: Axonal projection patterns

Quantitative analysis of axonal projections

I II !III !IV !!Va !!Vb !!!VI !!!wm

• Total axonal length [µm]

• Number of branching points [n]

• Number of endings [n]

• Branching pattern (Sholl analyis)

!• Total No. of boutons [n] • Bouton density [n / 100 µm] • Layer specific bouton distribution

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dpneuro Excitatory neurons display cell type-specific axonal projections

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Superimposing several reconstructions reveals cell type-specific projection domains

I II !III !IV !!Va !!Vb !!!VI !!!wm

All excitatory neurons, except for spiny stellate neurons, are projection neurons

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dpneuro Inhibitory neurons display unique axonal features

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Inhibitory neurons lack long-range projections

Chandelier cell

Larriva-Sahd 2010

Jones 1975

Cajal 1911

Wang 2002

Basket cell

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dpneuro Inhibitory neurons display unique axonal features

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Markram et al, 2004

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dpneuro Not every neuron is the same: Different classes of neurons have different functions

1

L1

L2

L3

L4

L5

L6How to classify neuronsby morphological features by biochemical markers

by electrical characteristics

Each nuclei/layer consists of different sets of neurons

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How to classify neurons: Biochemical markers

Calcium binding proteins

Neuropeptides

• Somatostatine (SOM)

• Vasoactive intestinal peptide (VIP)

• Cholecystokinin (CCK)

• Neuropeptide Y (NPY)

• Parvalbumin (PV)

• Calbindin (CB)

• Calretinin (CR)

Not commonly used – but applicable

• Ionchannel types

• Receptor subunits (GABA, Glu)

Typically used for classification of inhibitory interneurons onlyExcitatory neurons typically express layer (i.e. laminae) specific proteins

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How to classify neurons: Morphological and/or Biochemical markers ?

The problem: Poor correlation between morphological and biochemical markers

Markram et al, 200420

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How many different classes of neurons are there in the cerebral cortex ?

Excitatory neurons

Inhibitory neurons

By morphology: at least 3 main classes: spiny stellate, star pyramidal & pyramidal cells;

number of subclasses depends on cortical area.

By biochemical markers: Each layer possesses at least one unique subclass (up to 3) – depends on cortical area

Primary somatosensory cortex: believed to be 11+ subclasses

Even coarse classification still controversial

By morphology: most reliable code, at least 8 main morphological classes

By biochemical markers: at least 7 main biochemical classes

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dpneuro Not every neuron is the same: Different classes of neurons have different functions

1

L1

L2

L3

L4

L5

L6How to classify neuronsby morphological features by biochemical markers

by electrical characteristics

Each nuclei/layer consists of different sets of neurons

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dpneuro Intrinsic electrical characteristics of neurons

Active and passive !electrophysiological properties

Membrane properties

Excitability measures

Temporal pattern of spiking

Threshold to induce action!potential

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dpneuro Experimental approaches to monitor single neuron activity

Invasive intracellular methods (active and passive*)Sharp electrode recording

Whole-cell patch-clamp recordings

Invasive extracellular methods (passive methods)Juxtacellular recording

Extracellular single unit (i.e. neuron) recording

Imaging methods (passive methods)Ion (most commonly calcium) imaging

Voltage sensitive dye imaging

* Passive methods require an external stimulusAll methods can be used in vivo or in vitro

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dpneuro Electrical characterization of neurons

Passive intrinsic properties

•  Membrane(resistance:(Rm(

Rm(=(((Voltage(change((((Current(injec8on((

•  Res8ng(membrane(poten8al:(Vrmp(

Indicates,+how+sensi/ve+a+neuron+might+be+to+excita/on+

•  Membrane()me(constant:(τ"τ!=!Time!needed!to!reach!63!%!of!

voltage!change!

Indicates,+how+fast+a+neuron+might+react+on+excita5on+

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dpneuro Electrical characterization of neurons

Additional parameters:

ADP$

fAHP$sAHP$

•  Firing$threshold,$amplitudes$AHPs$

•  Inter$spike$intervals,$frequency$•  Adap>on$rate$during$ongoing$current$injec>on$

Quan>ta>ve$analysis:$

•  Ac>onpoten>al$amplitudes$(1st,$2nd),$halfwidth$

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dpneuro Electrical characterization of excitatory neurons

regular'spiking'neuron'

intrinsic'burst'spiking'neurons'

20#mV#200#ms#

'70#mV#

'63#mV#

150#pA#

150#pA#

50#ms#

Excitatory'neurons'display'two'main'firing'pa8erns'

•  RS#cells:#regular#trains#of#single#APs#

•  IB#cells:#strong#ADP#iniCates#high#frequency#burst#of#APs#

•  Found#in#corCcal#layers#II'VI#

•  Found#in#layers#IV#'#VI#

•  Most#powerful#IB#cells:#large#pyramidal#cells#in#main#output#layer#V#

•  E'code#correlates#not#with#M'code#

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dpneuro Electrical characterization of excitatory neuronsregular'spiking'neuron'

intrinsic'burst'spiking'neurons'

20#mV#200#ms#

'70#mV#

'63#mV#

150#pA#

150#pA#

50#ms#

Excitatory'neurons'display'two'main'firing'pa8erns'

•  RS#cells:#regular#trains#of#single#APs#

•  IB#cells:#strong#ADP#iniCates#high#frequency#burst#of#APs#

•  Found#in#corCcal#layers#II'VI#

•  Found#in#layers#IV#'#VI#

•  Most#powerful#IB#cells:#large#pyramidal#cells#in#main#output#layer#V#

•  E'code#correlates#not#with#M'code#

Bursts are more reliable than single spikes in "evoking postsynaptic neuronal responses."!Bursts overcome synaptic transmission failure. "!Bursts facilitate transmitter in the short-term release whereas "single spikes do not (i.e. short-term facilitation)."!Bursts evoke  long-term potentiation and hence affect synaptic plasticity much greater, or differently than single spikes."!Bursts have higher signal-to-noise ratio than single spikes. "!!

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dpneuro Electrical characterization of inhibitory neurons

Late%spiking%

Stu$ering*

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Fast spiking neurons respond rapidly once reaching threshold!! -- Rapid truncation of excitatory network activity !

!Late spiking need strong and lasting excitatory drive !

! -- Modulation of ongoing network activity!

Electrical characterization of inhibitory neurons

Fast%spiking% Late%spiking%

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dpneuro Coming back to combinatorial approach for neuronal classification

Markram&et&al.,&NatNeuroscRev&2004&

inflation of subclasses of inhibitory neurons

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dpneuro Anatomy of a neuron

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dpneuro Canonical neuron under electron microscope

Despite their many faces, "all neurons however share basic structural features

Dendrites: The principal input layer of neurons; "has the largest density of synapses

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dpneuro Despite their many faces, all neurons however share basic structural features

Harris KM, Stevens JK (1989)

Each dendrite might have inhibitory and excitatory inputs;But each synapse is either inhibitory or excitatory

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dpneuro Despite their many faces, all neurons however share basic structural features

Astrocytes closely interact with dendritic processes

Dendrite

Astrocytic"process

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dpneuro Despite their many faces, all neurons however share basic structural features

Astrocytes closely interact with dendritic processes,"and often co-localize with boutons

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dpneuro Despite their many faces, all neurons however share basic structural features

vesicules

microtubule

synapse

synapse

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dpneuro Synapses are enriched with mitochondria

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dpneuro Post-synaptic densities show where excitatory neurons make synapse

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dpneuro Asymmetrical vs symmetrical synapse correspond to excitatory vs inhibitory connections

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dpneuro A single bouton can make multiple synapses with a single dendritic spine

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dpneuro Not all synapses communicate with neurotransmitters: Chemical vs electrical synapses

chemical

electrical

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dpneuro Types of dendritic spines: Stubby

Stubby

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dpneuro Types of dendritic spines: Thin

Thin

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dpneuro Types of dendritic spines: Mushroom shaped

Mushroom

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dpneuro Electrical and Chemical Synapses

This and all subsequent figures are adapted from Purves et al (2007), unless stated otherwise

Pre- and postsynaptic neurons electrically communicate by ionic exchange

Gap-junction diameter is larger than voltage-gated ion channels, therefore allow exchange of non-ionic materials (i.e. second messengers, ATP, metabolites)

The electrical transmission in most gap-junctions is bidirectional

Passive current flow across the gap-junction is fast, virtually instantaneouswhich results in !synchronized electrical activity among neural populations.

Commonly observed in the brain stem, as central pattern generators, in thalamus, cortex, and cerebellum.

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dpneuro Electrical and Chemical Synapses

electrical synapses physically touch each other !47

electrical communication is efficient but does not allow advanced information processing

dpneuro Electrical and Chemical Synapses

minimal delay !(~0.1 ms)

Beierlein et al (2010)

Furshpan and Potter (1959)

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dpneuro Electrical potentials in a neuron

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dpneuro The rate and timing of spikes depend on resting membrane potential

-80 mV -70 mV -60 mV

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dpneuro Synaptic events from neurotransmitter to postsynaptic activation

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dpneuro What we learned today:

Classification of neurons by morphological, biochemical and electrical characteristics

Canonical neuron under electron microscope

Electrical vs chemical neurotransmission

Synaptic events from neurotransmitter to postsynaptic activation

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