2019-11-17 09:30:49

Prelude

Announcements

Today’s topics

  • Wrap-up on structural methods
  • Functional methods

Magnetic Resonance Imaging (MRI)

  • Magnetic resonance a property of some isotopes and complex molecules
  • Hydrogen (\(H\)), common in water & fat, is one
  • In magnetic field, \(H\) atoms absorb and release radio frequency (RF) energy
  • \(H\) atoms align with strong magnetic field

  • Applying RF pulse perturbs alignment
  • Rate/timing of realignment varies by tissue
  • Realignment gives off radio frequency (RF) signals
  • Strength of RF ~ density of \(H\) (or other target)
  • K-space (frequency/phase) -> anatomical space

MRI

Structural MRI

  • Tissue density/type differences
  • Gray matter (nerve cells & dendrites) vs. white matter (axon fibers)
  • Spectroscopy (specific metabolites)
  • Region sizes/volumes

Aside about Fourier analysis/synthesis

  • Fourier analysis (complex signal -> frequencies in that signal)
  • Fourier synthesis (frequencies in signal -> composite of those frequencies)

  • In MRI, \(K\) space is frequency of magnetic resonance; image space is what we see

Voxel-based morphometry (VBM)

Volume differences in schizophrenic patients vs. controls

(Pomarol-Clotet et al., 2010)

What is the wiring diagram (“connectome”)?

Retrograde (output -> input) vs. anterograde (input -> output) tracers

Diffusion Tensor Imaging (DTI)

  • Structural MRI technique
  • Diffusion tensor: measurement of spatial pattern of \(H_2O\) diffusion in small volume
  • Uniform (“isotropic”) vs. non-uniform (“anisotropic”)
  • Strong anisotropy suggests large # of axons with similar orientations (fiber tracts)

Connectome as matrix

Functional methods

  • Recording from the brain
  • Interfering with the brain
  • Stimulating the brain
  • Simulating the brain

Recording from the brain

  • Single/multi unit recording
  • Microelectrodes
  • Small numbers of nerve cells

Single/multi-unit Recording

Single/multi-unit recording

  • What does neuron X respond to?
  • Great temporal (ms), spatial resolution (um)
  • Invasive
  • Rarely suitable for humans, but…

Electrocorticography (ECoG)

Single-cell studies ask…

  • How does firing frequency, timing vary with behavior?

Combinations of micro and meso-scale methods

Positron Emission Tomography (PET)

Positron Emission Tomography (PET)

  • Radioactive tracers (glucose, oxygen)
  • Positron decay activates paired detectors
  • Tomographic techniques reconstruct 3D geometry
  • Experimental condition - control
  • Average across individuals

More on PET

  • Temporal (~ s) and spatial (mm-cm) resolution worse than fMRI
  • Radioactive exposures + mildly invasive
  • Dose < airline crew exposure in 1 yr

Functional Magnetic Resonance Imaging (fMRI)

  • Neural activity -> local \(O_2\) consumption increase
  • Blood Oxygen Level Dependent (BOLD) response
  • Oxygenated vs. deoxygenated hemoglobin ≠ magnetic susceptibility

  • How do regional blood \(O_2\) levels (& flow & volume) vary with behavior X?
  • MRI “signals” relate to the speed (1/T) of “relaxation” of the perturbed nuclei to their state of alignment with the main (\(B_0\)) magnetic field.
  • Imaging protocols emphasize different time constants of this relaxation (\(T1\), \(T2\), \(T2^*\)); \(T^2*\) for BOLD imaging

Evaluating fMRI

  • Non-invasive, but expensive
  • Moderate but improving (mm) spatial, temporal (~sec) resolution
  • Spatial limits due to
    • field strength (@ 3T \(~3mm^3\) voxel)
    • Physiology of hemodynamic response

  • Temporal limits due to
    • Hemodynamic Response Function (HRF): ~ 1s delay plus 3-6 s ramp-up
    • Speed of image acquisition
  • Indirect measure of neural activity

Hemodynamic Response Function (HRF)

Generate “predicted” BOLD response to event; compare to actual

Higher field strengths (3 Tesla vs. 7 Tesla)

Multi-modal whole brain methods

I want some power…

(Szucs & Ioannides, 2017)

“Assuming a realistic range of prior probabilities for null hypotheses, false report probability is likely to exceed 50% for the whole literature.”

(Szucs & Ioannides, 2017)

Functional Near-infrared Spectroscopy (fNIRS)

  • Near infrared light penetrates scalp and skull, refracted by brain tissue
  • Returned signal altered by blood \(O_2\) levels
  • Time course (temporal resolution) ~ BOLD fMRI; spatial resolution low

Electroencephalography (EEG)

  • How does it work?
  • Electrodes on scalp or brain surface
  • What do we measure?
    • Voltage differences between source and reference electrode
  • Combined activity of huge # of neurons

How does EEG arise?

  • Current/voltage gradients between apical (near surface) dendrites and basal (deeper) dendrites and cell body/soma

Collecting EEG

EEG

  • High temporal, poor spatial resolution
  • Analyze activity in different ‘bands’ of frequencies
    • LOW: deep sleep (delta or \(\delta\) band)
    • MIDDLE: Quiet, alert state (alpha \(\alpha\) band)
    • HIGHER: Sensorimotor activity reflecting observed actions? (mu or \(\mu\) band), (Hobson & Bishop, 2017)
    • HIGHER STILL: “Binding” information across senses or plasticity? (gamma or \(\gamma\) band), (Amo et al., 2017)

Event-related potentials (ERPs)

Brain Computer Interface (BCI)

Magneto-encephalography (MEG)

  • Like EEG, but measuring magnetic fields
  • High temporal resolution
  • Magnetic fields propagate w/o distortion
    • But are orthogonal to electric field
  • Requires shielded chamber (to keep out strong magnetic fields)
  • ++ cost vs. EEG

MEG

New device minimizes problems with motion
[[@Hill2019-ik]](https://doi.org/10.1038/s41467-019-12486-x)

(Hill et al., 2019)

Figure 1. A paediatric MEG system: a Experimental setup for three participants age 2- (left), 5- (centre) and 24-years (right). OPMs, housed in a modified bike helmet, measured the MEG signal. b Time-frequency spectra from a single (synthesised gradiometer) channel. Changes in neural oscillations are shown; blue indicates a reduction in oscillatory amplitude relative to baseline; yellow indicates an increase. Note reduction in beta (13–30 Hz) and mu (8–13 Hz) amplitude. c The spatial signature of beta modulation during the period of tactile stimulation (0 s < t < 2 s) (blue overlay)

How do EEG/MEG and fMRI relate?

How do EEG/MEG and fMRI relate?

Manipulating the brain

  • Interfering with it
  • Stimulating it

Interfering with the brain

  • Nature’s“experiments”
  • Stroke, head injury, tumor
  • Neuropsychology

Phineas Gage

Evaluating neuropsychological methods

  • Logic: IF damage to area X impairs performance, THEN region critical for behavior Y
  • Double dissociation: Damage to area Z leaves behavior Y intact
  • Weak spatial/temporal resolution

Stimulating the brain

  • Electrical (Direct Current Stimulation - DCS)
  • Pharmacological
  • Magnetic (Transcranial magnetic stimulation - TMS)

Stimulating the brain

  • Spatial/temporal resolution?
  • Assume stimulation mimics natural activity?

Deep brain stimulation as therapy

  • Depression
  • Epilepsy
  • Parkinson’s Disease

Optogenetics

  • Gene splicing techniques insert light-sensitive molecules into neuronal membranes
  • Application of light at specific wavelengths alters neuronal function
  • Cell-type specific and temporally precise control
  • Mimics brain activity

Simulating the brain

  • Computer/mathematical models of brain function
  • Example: neural networks
  • Cheap, noninvasive, can be stimulated or “lesioned”

Main points

  • Multiple structural, functional methods
  • Different levels of spatial & temporal analysis
  • Functional tools have different strengths & weaknesses

References

Amo, C., De Santiago, L., Zarza Luciáñez, D., León Alonso-Cortés, J. M., Alonso-Alonso, M., Barea, R., & Boquete, L. (2017). Induced gamma band activity from EEG as a possible index of training-related brain plasticity in motor tasks. PloS One, 12(10), e0186008. https://doi.org/10.1371/journal.pone.0186008

Barson, D., Hamodi, A. S., Shen, X., Lur, G., Constable, R. T., Cardin, J. A., … Higley, M. J. (2019). Simultaneous mesoscopic and two-photon imaging of neuronal activity in cortical circuits. Nature Methods. https://doi.org/10.1038/s41592-019-0625-2

Fultz, N. E., Bonmassar, G., Setsompop, K., Stickgold, R. A., Rosen, B. R., Polimeni, J. R., & Lewis, L. D. (2019). Coupled electrophysiological, hemodynamic, and cerebrospinal fluid oscillations in human sleep. Science, 366(6465), 628–631. https://doi.org/10.1126/science.aax5440

Hill, R. M., Boto, E., Holmes, N., Hartley, C., Seedat, Z. A., Leggett, J., … Brookes, M. J. (2019). A tool for functional brain imaging with lifespan compliance. Nature Communications, 10(1), 4785. https://doi.org/10.1038/s41467-019-12486-x

Hobson, H. M., & Bishop, D. V. M. (2017). The interpretation of mu suppression as an index of mirror neuron activity: Past, present and future. Royal Society Open Science, 4(3), 160662. https://doi.org/10.1098/rsos.160662

Logothetis, N. K., Pauls, J., Augath, M., Trinath, T., & Oeltermann, A. (2001). Neurophysiological investigation of the basis of the fMRI signal. Nature, 412(6843), 150–157. https://doi.org/10.1038/35084005

Logothetis, N. K., & Wandell, B. A. (2004). Interpreting the BOLD signal. Annu. Rev. Physiol., 66(1), 735–769. https://doi.org/10.1146/annurev.physiol.66.082602.092845

Pomarol-Clotet, E., Canales-Rodrı'guez, E. J., Salvador, R., Sarró, S., Gomar, J. J., Vila, F., … McKenna, P. J. (2010). Medial prefrontal cortex pathology in schizophrenia as revealed by convergent findings from multimodal imaging. Mol. Psychiatry, 15(8), 823–830. https://doi.org/10.1038/mp.2009.146

Sladky, R., Baldinger, P., Kranz, G. S., Tröstl, J., Höflich, A., Lanzenberger, R., … Windischberger, C. (2013). High-resolution functional MRI of the human amygdala at 7 T. European Journal of Radiology, 82(5), 728–733. https://doi.org/10.1016/j.ejrad.2011.09.025