Basis of the BOLD Signal Christoph Korn Andrea Dantas

Outline fMRI Physics BOLD Signal fMRI - Magnetic fields & spins fMRI - Radio pulse & relaxation times fMRI - Tissue contrasts fMRI - BOLD & T2* BOLD Signal Brain Metabolism Neural Basis of BOLD signal Technique & Protocols Advantages & Disadvantages Areas for future research

What do we want to understand? Singer et al., 2006

Which magnetic fields do we know? 1 Tesla = 20,000x Earth’s magnetic field

Where is the magnetic field in the scanner? B0 = constant magnetic field Along z-axis For fMRI 1.5T or 3T Z

Where are our compass needles? Protons have a spin and therefore a magnetic dipole moment MDM They can align to external magnetic fields in two ways: parallel or anti-parallel

What happens in the scanner? Outside scanner

What happens in the scanner? Inside scanner (B0) The protons of the H2O molecules in our body align along B0

Are there more up-spins than down-spins? Yes and the excess spins create a new magnetic field M which we can measure [T]

Do the spinning tops tumble? Precession and Larmor frequency ω = γ · B0 ω Larmor frequency γ gyromagnetic constant B0 static magnetic field e.g. 1.5 T  ω = 64 MHz z-axis

How do we measure spins? We have to disturb them How? With a radiofrequency pulse with Larmor frequency

What happens if spins fall down? z axis x-y plane

What happens if spins fall down? 90° High frequency pulse before after z axis x-y plane z axis x-y plane

What is the T1 relaxation? Recovery in z-axis = longitudinal relaxation = spin-lattice relaxation Supplied energy lost Spins re-align with B0 T1

What is the T2 relaxation? Dephasing in x-y plane = horizontal relaxation = spin-spin relaxation 90° pulse T2 relaxation

Why does this happen and what is T2*? Two reasons for dephasing in x-y plane Spin-spin interaction  T2 Local magnetic field inhomogeneities  T2* Magnetic field inhomogeneities T2(*) time constant

And? How can we use this for imaging? Different tissues have different relaxation times Let’s look at T1 Fat White matter Grey matter CSF

And T2? Different tissues have different relaxation times CSF Grey matter White matter Fat

How do the T1 & T2 contrasts look like? Fat White matter Grey matter CSF

How do we get these contrasts? How do we get a 3D-image? Too much to explain here Different times between high frequency pulses Different gradients along magnetic field

Finally, what is BOLD? Blood Oxygen Level Dependent signal O2 is transported by haemoglobin (Hb)

What is the difference between deoxyHb and oxyHb? Remember T2* and field inhomogeneities? DeoxyHb paramagnetic strong field inhomogeneities Fast dephasing Fast T2* OxyHb diamagnetic weak field inhomogeneities Slower dephasing slower T2*

Better? Singer et al., 2006

Outline fMRI Physics BOLD Signal fMRI - Magnetic fields & spins fMRI - Radio pulse & relaxation times fMRI - Tissue contrasts fMRI - BOLD & T2* BOLD Signal Brain Metabolism Neural Basis of BOLD signal Technique & Protocols Advantages & Disadvantages Areas for future research

Brain Metabolism Review Basic Facts 54ml of blood / 100g of brain tissue Brain: 2-3% of body weight 20% of O2 consumption For imaging purposes, the main vasculature concerned are the capillaries networks – where glucose and O2 exchanges happen

Principles of BOLD BOLD contrast depends on the balance between O2 supply and consumption by the neural tissues DeoxyHb is paramagnetic – as its proportion decreases, the MR signal increases and generates what is referred to as the BOLD signal

Neural Basis of BOLD – Energy Consumption Theory Initial thoughts were that increase of blood flow was due to the increase in energy requirements of the active tissue Most of the energy is spent maintaining action potentials and in post-synaptic signalling Inhibitory synapses use less energy than excitatory ones – controversy around whether these generate a BOLD signal at all!! Attwell, D. , Iadecola, C. 2002. “The neural basis of functional brain imaging signals”. Trends in Neuroscience. 25 (12) 621-625

Neural Basis of BOLD – Blood Flow Increase Energy use does not directly increase blood flow…so how does the brain cope with the increase in glucose and O2 demands? Glutamate-generated Calcium influx at post-synaptic level releases potent vasodilators: Nitric Oxide Adenosine Arachidonic Acid metabolites Blood flow is increased over an area larger than the one with neuronal activity Global blood flow changes also associated with dopamine, noradrenaline and serotonin Not related with regional energy utilisation at all!! Energy utilisation and increase in blood flow are processes that occur in parallel and are not causally related Attwell, D. , Iadecola, C. 2002. “The neural basis of functional brain imaging signals”. Trends in Neuroscience. 25 (12) 621-625

How can we (can we?) predict neural activity from fMRI signals? 90.000 to 100.000 neurons per 1mm3 of brain tissue 109 synapses, depending on cortical thickness

What is in a Voxel? Volume of 55mm3 Using a 9-16 mm2 plane resolution and slice thickness of 5-7 mm Only 3% of vessels and the rest are….(be prepared!!) 5.5 million neurons 2.2-5.5 x 1010 synapses 22km of dendrites 220km of axons

What are we actually measuring? Inputs or Outputs? BOLD responses correspond to intra-cortical processing and inputs, not outputs Aligned with previous findings related to high activity and energy expenditure in processing and modulation Excitation or inhibition circuits? Excitation increases blood flow, but inhibition might too – ambiguous data Neuronal deactivation is associated with vasoconstriction and reduction in blood flow (hence reduction in BOLD signal) And what about the awake, but resting brain? Challenges in interpreting BOLD signal Presence of the signal without neuronal spiking Logothetis, N. K. 2008, "What we can and cannot do with fMRI", Nature, vol. 453, pp. 869-877

fMRI Study Designs Main types of study design: Block design Consecutive tasks in pre-defined time intervals (also referred to as “epochs”) Event-related Stimuli (events or trials) are presented Higher image acquisition rates (1/sec) 5 minutes of scanning can result in over 80 MB of data!

Example of fMRI Protocol Delay between the stimulus and the vascular changes – might take up to 6 secs Initial “Dip” – decrease in BOLD signal due to O2 consumption

fMRI Image Processing Stages Images are re-aligned Spatial normalisation of images to a standard brain space Smooth and normalise the data Combine statistical maps with anatomical information Result is a superposition of a statistical map on a raw image

Sample fMRI Images

Advantages of BOLD Advantages over other methods: EEG / MEG – Poor spatial localisation, high number of electrodes needed PET – Invasive and need to use potentially toxic contrast Non-invasive Increasing availability High spatial and temporal resolution Enables demonstration of entire network brain areas engaged in specific activities Logothetis, N. K. 2008, "What we can and cannot do with fMRI", Nature, vol. 453, pp. 869-877

Disadvantages of BOLD Surrogate signal of haemodynamic activity – which has physical and biological constraints Neuronal mass activity and not activity of specific neuronal units Circuitry and functional organisation of the brain not fully understood Difficult to differentiate between excitation/inhibition and neuromodulation Signal intensity does not accurately differentiate between: Different brain regions Different tasks within the same region Logothetis, N. K. 2008, "What we can and cannot do with fMRI", Nature, vol. 453, pp. 869-877

Future Development Areas Multimodal approach is the way forward!!! Coupling of electrophysiological studies with BOLD Further improvements to fMRI technology Expansion of human and animal experimentation, enhancing the comprehension of the neural basis of haemodynamic responses New smart contrast agents that do not rely on haemoglobin

References Logothetis, N. K. 2008, "What we can and cannot do with fMRI", Nature, vol. 453, pp. 869-877 Attwell, D. , Iadecola, C. 2002. “The neural basis of functional brain imaging signals” Trends in Neuroscience. 25 (12) 621-625 Huettel, S. C., A. W. Song, and G. McCarthy. Functional Magnetic Resonance Imaging. 2nd ed. Sinauer Associates Inc., 2004 McRobbie, D.W., Moore, E.A., Graves, M.J., and Prince, M.R. MRI – From Picture to Proton. 2nd ed. Cambridge University Press, 2007 SIEMENS. Magnets, Spins and Resonance. 2003. 25-10-2008. Ref Type: Report