## Today

::: incremental
-   Who am I? Who is everyone?
-   A quick overview of the module.
-   What to expect, assessment/coursework?
-   101 of functional MRI and experiment design.
:::

## Overview

::: r-fit-text
| Timetable week | Lecturer     | Lecture                                               |     |
|:-------------|:-------------|:-------------|:----------------------------|
| 02             | D Schluppeck | Overview, **fMRI & study design.**                    |     |
| 03             | M Schürmann  | **Basic neuroanatomy**                                |     |
| 04             | K Dyke       | **Brain stimulation & study design.**                 |     |
| 05             | W v Heuven   | **Language**                                          |     |
| 06             |  | **Reading week (!)**                            |     |
| 07             | D Schluppeck | **Vision + brain imaging**                            |     |
| 08             | D Schluppeck | **Q&A, experimental design, coursework**              |     |
| 09             | L Cragg      | **Developmental neuroimaging.**                       |     |
| 10             | J Derrfuss   | **Cognitive control, attention, and working memory.** |     |
| 11             | R Filik      | **Moral Cognition**                                   |     |
| 12             | D Schluppeck | **Perceptual Decision making**, Q&A for assignment    |     |
:::

## Assessment

-   Written assignment (max 3000 words) including a 250 word abstract.

-   Details on [moodle (2024/25)](https://moodle.nottingham.ac.uk/course/view.php?id=137637).

. . .

### What? How?

> How can fMRI and/or brain stimulation be used to study different neuroscience questions? Cover at least two topics and/or methods from the course.

## Today's lecture

::: incremental
-   A brief introduction to fMRI.

-   Scope and limitations of the fMRI method.

-   Principles of experimental design in psychology.

-   Experimental design for fMRI.
:::

## Learning objectives

::: columns
::: {.column .fragment width="60%"}
By the end of the lecture you should be able to:

-   Understand what fMRI measures.
-   Evaluate the strengths and weaknesses of fMRI.
-   Evaluate different experimental designs.
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::: {.column .fragment width="40%"}
![image of statistical maps on brains](images/blobs-on-brains.png)
:::
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## LO {background="images/20307dtp.jpg" data-background-opacity="1.0"}

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![person being positioned in an MRI scanner](images/20307dtp.jpg)
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::: {.r-fit-text style="color: white; -webkit-text-stroke: 2px; -webkit-text-fill-color: black;"}
fMRI basics
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## fMRI basics {background="images/20307dtp.jpg" data-background-opacity="0.3"}

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![person being positioned in an MRI scanner](images/20307dtp.jpg)
:::

::: incremental
-   MRI uses **static** and **oscillating** electromagnetic fields to detect different biological tissue properties.

-   **functional MRI** measures changes in blood oxygenation over time.

-   BOLD signal: [blood oxygen level dependent]{style="fontweight: bold; color: red;"}
:::

## Example research questions

::: columns
::: {.column .fragment width="45%"}
![](images/approach-finding-areas.png){width="100%"} **Where** are the areas more active in **Condition A** than in **Condition B**?
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:::

::: {.column .fragment width="45%"}
![](images/approach-using-rois.svg){width="100%"} How do pre-defined **regions of interest** respond in different experimental conditions?
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## Experimental "pipeline"

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**Prepare**

Theory ➡️ Research Question ➡️ Hypothesis
:::

::: {.r-fit-text .fade-in-then-semi-out .fragment}
**Plan & do**

Experimental Design ➡️ Piloting ➡️ Data collection
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::: {.r-fit-text .fade-in-then-semi-out .fragment}
**Analyse & report**

Preprocessing ➡️ Analysis ➡️ Interpretation
:::

::: notes
General overview of how imaging experiments often work / get designed.
:::

## Study {background="images/fMRI-Fig-08-01-0.jpg" data-background-opacity="1.0" background-size="contain"}

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![diagram from textbook showing study design ideas](images/fMRI-Fig-08-01-0.jpg)
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## General thoughts (BOLD)

What does the blood-oxygen-level-dependent (BOLD) signal measure?

::: fragment
-   neuronal activity?!
-   populations of neurons (excitatory, inhibitory)
-   spikes or (pre-)synaptic activity
:::

## General thoughts (Signal/Noise)

(fMRI) signals are weak + noisy.

::: fragment
-   How does that limit voxel size?
-   Short events, minimum durations?
-   Need for averaging?
-   Blocks versus "event-related" designs?
:::

## General thoughts (Variability)

Details of brain anatomy vary across individuals.

::: fragment
-   What does this mean for group studies?
-   Individual subjects results first?
-   Data in 3d or 2d (cortical surface?)
:::

## Example data / images

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![Anatomical image (T1w)](images/anatomical-image.png){fig-alt="anatomy" fig-align="left" width="80%"}
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![Functional image (T2\*, EPI)](images/functional-image.png){fig-alt="fMRI image" fig-align="left" width="80%"}
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## fMRI measures changes over time

![](images/timecourse.png)

## Example: visual cortex

![anatomical image with position of fMRI slice](images/dsBrain.png){height="400px"}

## Example: visual cortex (movie)

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![one slice over 160 repeated measurements (every 1.5s)](images/test-2.gif){height="400px"}
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::: {.content-visible when-format="pdf"}
![one slice over 160 repeated measurements (every 1.5s)](images/test-2.png){height="400px"}
:::

## fMRI measures changes over time

![](images/timecourse.png)

## "There is no free lunch"

::: incremental
-   both, *spatial resolution* and *temporal resolution*, are limited
-   often, experimenter has to trade off one against the other
-   so, different choices for different applications...
:::

## Why do we need high spatial resolution?

::: incremental
-   brain structures of interest are \~mm in size, sometimes separated by \~cm; need appropriate sampling

-   smaller voxels: less mixing of grey matter, white matter, CSF, veins, ... reduced partial voluming
:::

## Appropriate sampling

![Table of structures / sizes](images/table-structures.jpg)

## Volume → no. of cells

... if packing density in grey matter of cortex is \~50,000 cells / mm$^3$

::: fragment
| edge (mm) | volume (mm$^3$) | #cells in pure GM |
|-----------|-----------------|-------------------|
| 1         | 1               | 50k               |
| 3         | 27              | 1.35M             |
| 5         | 125             | 6.25M             |
:::

## PVE {background="images/spatial-resolution-images.png" background-size="contain"}

## Partial volume effects

![A typical 3mm voxel contains a mixture of tissues](images/partial-voluming.png)

## What limits (spatial) resolution

::: fragment
**hardware** (the scanner)
:::

::: fragment
**the subjects**

-   peripheral nerve stimulation PNS
-   specific absorption rate SAR limits
-   time in scanner ( \>1.5h is not fun)
:::

::: fragment
**signal-to-noise ratio** - smaller voxels = proportionally more noise head motion, physiology, ...
:::

## fMRI measures changes over time

![](images/timecourse.png)

## What limits (temporal) resolution

::: callout-important
## physiology

basis of the blood-oxygen-level-dependent (BOLD) signal
:::

-   BOLD is **haemodynamic**, an indirect measure of neural activity (+ still hotly debated)
-   BOLD signal is **delayed and blurred** in space, but also in time

## Haemodynamic response

the shape of the response to a brief event is called the haemodynamic response function (HRF)

![haemodynamic response](images/hrf-image.png){.r-stretch}

e.g. haemodynamic response to a 1s visual stimulus peaks several seconds later and is spread out

## Intermediate summary

-   Overview of the fMRI method.

-   How to interpret fMRI data.

-   Limiting factors of fMRI.

-   Trade-off between temporal and spatial resolution.

::: fragment
Thinking about **temporal resolution** particularly important when designing fMRI experiments
:::

## Some principles of experimental design

> Why do we need to worry about designing experiments?

::: notes
break
:::

## Terminology

Independent Variable:

:   variable which is intentionally manipulated (different manipulations are called conditions / levels)

Dependent Variable:

:   measured variable

Confound:

:   a property that co-varies with the IV

## eg. this experiment

![](images/fvh.jpg){height="100px"}

::: fragment
![](images/faces-color.png){width="700px"}

![](images/houses-bw.png){width="700px"}
:::

## Dealing with confounds

::: fragment
**Counterbalancing:** a process for removing confounds by ensuring they have equal influence at each level of the IV
:::

::: fragment
**Randomization:** removing confounds by making sure they vary randomly at each level of the IV
:::

## Within or between subjects? {.smaller}

::: fragment
**Within-subjects designs are stronger as they control for:**

-   Age Gender.
-   Experience.
-   Individual Difference.
-   Brain size / shape.
:::

::: fragment
**Between-subjects designs are sometime unavoidable**

-   Diagnostic comparisons
-   Gender effects

Match the design to the research question...
:::

## ... and for fMRI?

All the above, plus...

::: fragment
-   Selecting an appropriate IV
-   Selecting an appropriate control condition
-   Types of experimental design
-   Stimulus presentation timing
:::

## Many studies: cognitive subtraction

Compare two very similar conditions that are assumed to differ only in one property.

![](images/approach-finding-areas.png)

## Control conditions are important

![](images/control-condition.png){height="600px"}

## fMRI designs

-   Block Designs -- trials appear in alternating blocks (Task A, Task B)

-   Event Related Designs -- stimuli are presented one-at-a-time in a random order

-   Mixed Designs -- alternating blocks of tasks but with mixed trials

-   (resting state fMRI) - no task

## Block designs

![](images/timecourse.png){height="200px"}

-   Powerful for detecting signal changes if a good control is selected.

-   Not very good for estimating the shape of the HRF.

-   Sensitive to noise (scanner drift)

-   The block length is very important to consider

## Event-related designs

come in two "flavours"

-   Slow -- stimulus followed by long inter-trial intervals (eg 10-15s rest)

-   Fast/Rapid variable -- rapid stimulus presentation with variable, but short ISI (2s)

##  {#slide-events-id data-menu-title="Comparing different designs" background="images/F1.large.jpg" background-size="contain"}

<!--# Khalife et al (2022) eNeuro paper  !-->

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![figure showing timing of events in touch experiment](images/F1.large.jpg)
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##  {#slide-temp-precision-id data-menu-title="Temporal precision in fMRI" background="images/temporal-precision.png" background-size="contain"}

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![figure illustrating different aspects of temporal precision in fMRI experiments](images/temporal-precision.png)
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## Summary

Principles of experimental psychology apply to good fMRI study design also.

::: incremental
-   Consider how the hypotheses make predictions about space and time (and do they align with the scope of what fMRI can measure).

-   The experimental design should be appropriate for the research question.

-   Timing of stimulus presentation is key!
:::

## Thanks

::: r-fit-text
See you soon!
:::

## Colophon {.smaller}

-   This presentation was made with `quarto` and `revealjs`.

-   Uses a font called `Atkinson Hyerlegible`, which was designed to work better for people with low vision: available via [google fonts](https://fonts.google.com/specimen/Atkinson+Hyperlegible).
