Neuroscience methods

Evaluating methods

What are we measuring?

  • Structure
  • Activity
    • Why not function?

What is the question?

  • Structure X -> Structure Y
  • Structure X -> Function Y

Evaluating methods

Strengths & Weaknesses

  • Cost
  • Invasiveness
  • Spatial/temporal resolution

…and temporal resolution

Types of methods

  • Structural
    • Anatomy
    • Connectivity/connectome
  • Functional
    • What does it do?
    • Physiology/Activity

Structural methods

Mapping microstructure

  • Cell/axon stains
  • Cellular distribution, concentration, microanatomy

Golgi stain

  • whole cells, but small %


Nissl stain

  • Only cell bodies
  • Cell density ~ color intensity

Evaluating micro/cellular techniques

  • Invasive (in humans post-mortem only)
  • High spatial resolution, but poor/coarse temporal

Mapping macro-structures

Computed axial tomography (CAT), CT

  • X-ray based

Magnetic Resonance Imaging (MRI)

What it measures/how it works

  • 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

Structural MRI

  • Tissue density/type differences
  • Gray matter (nerve cells & dendrites) vs. white matter (axon fibers)

MR Spectroscopy (specific metabolites)

  • Region sizes/volumes

Voxel-based morphometry (VBM)

  • MRI technique for measuring brain sizes/volumes
  • Volume differences in schizophrenics vs. controls
  • Colored portions are statistical maps placed on top of a base structural map. - Maps provide information about the comparison in brain volumes between patients and controls in those areas

Mapping the wiring diagram (“connectome”)


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

http://openi.nlm.nih.gov/imgs/512/348/3176268/3176268_1471-2105-12-351-2.png


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)


Visualizing the connectome

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 + amplification
  • Small numbers of nerve cells
  • What does neuron X respond to?
  • How does firing frequency, timing vary with behavior?
  • Great temporal (ms), spatial resolution (um)
  • Invasive
  • Rarely suitable for humans, but…

Electrocorticography (ECoG)

Grid electrodes: (A) Craniotomy performed for electrocorticography (ECoG) grid electrode placement in epilepsy surgery candidate at Comprehensive Epilepsy Program, Florida Hospital for Children, Orlando, Florida, United States. (B) ECoG electrode grids placed directly on the brain surface. They will be used during presurgical monitoring for localizing seizure onset zone. The same electrodes are stimulated during electrical cortical stimulation mapping for identification of eloquent cortex. The ECoG signal recorded from these grids is separated in a different stream and used for real-time functional mapping (RTFM). (C) 3D reconstruction of the brain with overlaid grid electrodes. This reconstruction is used for creating RTFM montage.


Story about child who underwent ECoG surgery.

Positron Emission Tomography (PET)

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

but fMRI underpowered


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
  • More suitable for pediatric populations (less susceptible to movement artefact)


Electroencephalography (EEG)

  • How does it work?
  • Electrodes on scalp or brain surface

What does EEG measure?

  • Voltage differences between source and reference electrode
  • Combined activity of huge # of neurons
  • Current/voltage gradients between apical (near surface) dendrites and basal (deeper) dendrites and cell body/soma

Evaluating 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)

Brain Computer Interface (BCI)

  • Based on EEG/ERPs

Magneto-encephalography (MEG)

  • Like EEG, but measuring magnetic fields
  • Electrical and magnetic fields orthogonal
  • 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
New device minimizes problems with motion

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?

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

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

https://youtu.be/FlGbznBmx8M

Simulating the brain

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

Blue Brain project

Markram, 2006


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

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

Lichtman, J. W., Livet, J., & Sanes, J. R. (2008). A technicolour approach to the connectome. Nature Reviews Neuroscience, 9(6), 417–422. https://doi.org/10.1038/nrn2391

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-Rodrı́guez, 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

Sejnowski, T. J., Churchland, P. S., & Movshon, J. A. (2014). Putting big data to good use in neuroscience. Nat. Neurosci., 17(11), 1440–1441. https://doi.org/10.1038/nn.3839

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