Innovations in Clinical Neuropsychology - Extensive Lecture Notes

Innovations in Clinical Neuropsychology Lectures
Lecture 1: Introduction
Nowadays technology
Nowadays, a lot of companies on the market claim their brain training platforms improve cognitive
control/performance or reduce impairment from health conditions. However, research has shown that
even though they claim this, they cannot provide any scientific evidence of their protective nature that
they claim to have. Researchers have come together and found little evidence that training enhances
performance on distantly related tasks or that training improves everyday cognitive performance.
In other words: near transfer works (playing more Stroop tasks makes you better at a Stroop task),
but far transfer does not work (playing more Stroop tasks does not make you better at playing chess).

Technological development is becoming more and more interactive. You’re not only connecting to
your computer, but also to everyone out there. There is technology everywhere: in navigation (old
cards vs. google maps), in education (studying through VR goggles), and in sports (golfing in real life
vs. golfing on a screen). During the lecture, a video was shown of a gym that had a VR-machine in
which you could do a workout in a VR-world. This is a solution, but is there actually a problem…?

Technology in Neuropsychology
Unfortunately, there is little technological advancement in neuropsychology. Only 6% of the tools is
computerized, with mostly obsolete technologies (= no new ideas). There are some companies
working on it, e.g. metrisquare. This company is working on making neuropsychological tests digital,
e.g. the trail making test.

Why should we innovate?
But why should we even work on this and innovate? There are several reasons for this.
1. The technical development is available, so why not use it?
2. It could give us more insights into cognitive functions. We could benefit from this from a
scientific perspective (= the scientific motivation)
3. New tools might have less limitations compared to existing materials. They could bring us
more data and be less susceptible to issues.

Let’s discuss how we can innovate or how we’re already doing it within clinical neuropsychology.

Innovations in Diagnostic Tools
Computer-based assessment of cognition is mostly utilized in military and sports, as it is mainly
needed here. It’s also so advanced here because they have the money for it, and innovation is not
cheap. It’s not much seen in clinical settings, because of several reasons. The costs of it are high, and
there still is some concerns among clinical neuropsychologist regarding utility and validity. There is
only little normative data about digital versions of existing standardized material. So, are we really
still measuring the same thing?

There was a big review for computerized neurocognitive assessment tools for military mTBI (mild
traumatic brain injury). Because evidence and applicability vary across tools and populations, they
had some recommendations for using the computerized NCATS. Firstly, they stressed cautious use
(not use it as a standalone diagnostic). Furthermore, they recommended choosing tools based on
purpose and target population, whatever feels best to fit the targeted population. These results should
then be interpreted in light of age/education and remain aware of forthcoming recommendations.
Furthermore, in order to be classified as a good tool it should be evaluated using Randolph criteria:
test-retest reliability, sensitivity, validity, reliable change scores, and clinical utility.

,There are several advantages of computerized neuropsychological assessments:
- More detailed measurements
o Time (e.g. initiation, inspection, per item). E.g. for a TMT you can easily check
performance afterwards as you can track everything (when did the pen touch the
screen, when did it move to the next letter, etc.).
o Drawing and writing (e.g. start, cluster and neglect). On the lecture slides, a picture is
replicated in which colours are used. However, the patient did not use colours in real
life, but the program colour coded the colours in terms of time stamps. This gives you
insight in the process: e.g. where did they start? You can use that to enrichen the
diagnostics and improve it.
- Tailor to specific needs
- It is easier to use (once you know how it works).
- It reduces human errors (e.g. stopping the stopwatch too late by the psychologist, this in turn leads
time errors and wrong measurements, which eventually will be ‘put down’ on the patient).
- Mimicking everyday situations: computerized tasks can be mimicked for everyday situations, and
therefore also measure everyday function.
- Remote and portable testing: you don’t need to get everyone to the medical centre. You can do it
at home or even send it to them so the patient can do it on their iPad/laptop.

However, there are also several disadvantages of computerized neuropsychological assessments:
- Norm data are not directly transferrable, as validity and reliability still need to be proven.
- There are technical requirements, e.g. you need a tablet to use the digital tool or need internet data
to transfer the data.
- It needs training of clinicians, as it is not always self-explanatory.
- Cognitive processes are possibility different for a digital environment compared to a paper, e.g. a
laptop is way more luminous, or contrasts are way sharper compared to a piece of paper.
- Cybersickness: you can get sick because of VR.
- Novelty costs, as you need to transfer things from one to the other. Therefore, adjustment time is
needed.
- Privacy issues: data storage, where do you store the data privately? Often it has to be uploaded in
the cloud.

One example from their own research of van der Ham et al. (2015) is where they measured the
ecological validity of VR diagnostics. They had 4 different conditions. In the real condition
participants walked through the hallways at Utrecht University. On certain locations on that route
landmarks were put. In the hybrid condition participants still walked, but they walked on a basketball
field but saw the hallway on a tablet. The last condition was completely virtual where they passively
were being navigated through the hallway. They found these conditions affected performance
selectively. Landmark and route knowledge were unaffected, while locomotion benefited survey
knowledge (making a cognitive map in your head, = allocentric). In a completely virtual condition
where they added a compass, it made participants worse. Somehow it was so distracting from the task
it made performance worse.

Innovations in Treatment Tools
Treatment tools are in general less developed than diagnostics, however they are rapidly increasing.
These tools mostly focus on physical therapy. In a study by Pelosin they had Parkinson patients going
on a treadmill with VR glasses. The training was for motor function and cognitive training. It showed
the training on the treadmill decreased the risk and fear of falling in patients and there were cognitive
benefits. However, all the effects were only short term. Important take away is that it does work to a
certain degree, and it can offer increased ecological validity.

Something you need to consider for treatment is whether you train compensation or restoration.
Compensation is the use of other function. Thus, another function reduces the impairment (e.g.
changing your cognitive strategy). For this, situations can be presented in which alternative strategy is
stimulated. On the other hand, there is restoration, which is the case if you improve lost/reduced

,function, e.g. memory training. For this, relevant situations can be presented that stimulate function
use. However, there are some ethical considerations to take into account. If you can also do it real,
why would you then choose to do it virtual? Should we do social interactions in those tools? What is
the level of understanding of patients – do they feel safe? Also, there is a bigger possibility of falling
in VR.

eHealth
eHealth is an emerging field in the intersection of medical informatics, public health and the business
referring to health services and information delivered or enhanced through the Internet and related
technologies. So its basically about health services being provided online. Also see last lecture.
There are 4 big domains of eHealth:
- Records: making online files and records. So we don’t have a basement anymore that is full of
archives, but it is all online. This makes communication easier between clinicians and to the
patient. However, there are privacy issues to consider.
- Communication: you don’t necessarily need to go somewhere in person, but you can do it in
other form. This makes communication easier. E.g. you can have a phone call, make appointments
online or find additional information through online portals.
- Tracking and monitoring: with new technology you can get information on physiological
processes, and this can be used as additional information, such as data analysis, assessing the
success of a treatment, or the progression of a certain disorder. E.g. if you take a specific
medication; you can see a biological marker going down. Don’t confuse this domain with the
next… (self-management)
- Self-management: an addition to regular care, e.g. wearables or a smart watch. Self-management
are if-then situations, e.g. if your blood level is low, then you inject insulin.
The goal of eHealth eventually is to improve access to health care resources. It should empower
patients to become active and have power and agency over the disorder in their life. It should also
improve the understanding of disease and its progression. It should educate and support patients.

Non-technological innovations
So far, we have talked about technological innovations in the field. However, there also are
noteworthy non-technological innovations.
For example, the innovation to stop thinking in terms of disorder, but start to think in terms of health.
The standard ICD-10 classifies everything in different groups of casues of death or disorder. However,
there is a complementary approach now, called the ICF model (international classification of
functioning, disability and health). Underlying it we have a biopsychosocial model, and 4 core
principles. which emphasizes on 4 things and therefore the whole individual instead of just the disease
1. Universality: classify all people. Not just healthy/disorders, but everyone.
2. Parity: there is no distinction between where the condition comes from (mental/physical).
3. Neutrality: emphasize both positive and negative aspect of function and ability.
4. Environmental factors: every health disorder is embedded into the environment and a function
of the context.

,Another framework is the RDoC framework (Research Domain
Criteria), that focuses on underlying functioning rather than only
on symptoms. A key term associated with this is
transdiagnostic, an overarching diagnostic approach that also
accounts for the environment/cultural/social determinants of
health. It is a multi-level approach, integrating information from
different sources, such as behaviour, neural activity, and
physiology. The RDoC matrix helps to organize and implement
these principles. For example, researchers may examine
physiological measures such as heart rate or cortisol levels
alongside behavioural and neural data.

One example of an RDoC-related construct is performance monitoring, which is the ability to
monitor and adjust ongoing performance. One common behavioural effect is for post-error slowing:
people often respond more slowly after committing an error. Researchers have identified 3 core ERP
components related to performance monitoring after a response is given. For example, in the Stroop
task, a large negativity pattern when participants perform an error. We know that in healthy
individuals there is a clear difference between brain responses to correct versus incorrect trials.
However, in certain populations (ADHD, Alzheimer’s, Parkinson’s), the difference between error and
correct in this specific ERP component is bigger or smaller. This is not only true for
neuropsychological populations, but also for anxiety. We could use this information as a
transdiagnostic marker for underlying problems.

,Lecture 2 Visuospatial Cognition – VR and serious gaming

Spatial Cognition
Spatial cognition is understanding where you are and the objects around you are and being able to
interact with them. Sometimes, spatial cognition is difficult, such as in difficult traffic situations.
Some tools help us for spatial cognition, such as an air tag (where did I leave my keys?). However,
simple things – such as holding an object, is spatial cognition too. You need to understand how big the
object is and what you should do to pick it up (how far it is etc.).

This is also reflected when you look at our brains. A lot of brain regions are related to spatial
processing, such as the hippocampus, the visual cortex, the temporal cortex, the posterior parietal
cortex and the frontal cortex. You can better ask; which brain region is not involved in spatial
processing? See the picture below for more details about which brain region is involved in which
specific part of spatial cognition.




An important aspect of spatial cognition is knowing that we can look at it from a small versus large
scale space.
Small scale space: you do not need to move your body to interact with it. It is just a small simple
object that can fit on a A4 piece of paper. E.g. mental rotation test.
Large scale space: you do need to move your body to interact with it. E.g. water maze with rodents.
How do these 2 relate to each other? There is a partial overlap. Some cognitive abilities are specific
for large scale space, and some for small scale space. There also is an overlapping part.




When we talk about spatial cognition, we talk about everything, so small and large scale. However,
because of logistical restraints of just performing tasks on a task, neuropsychology often only
focusses on small scale spatial ability. However, we are trying to change that and also focus on large
scale space.

, What is navigation?
Navigation is our interaction with large scale space. You can list this in three different forms of
spatial behaviour that occur in all animals (very fundamental):
- Route following
o Ants secrete pheromones. The more pheromones pile up, the better the trace will be.
Over time, the most efficient route will be stabilized in the environment. By doing
that they find a food source.
o We as human also do this too. When you go skiing/walking, you often follow a trail
(e.g. a red pole or a number).
- Piloting
o Morris water maze; mice are put in water they cannot see true. As they do not like
swimming, they will try to find a platform to sit on. In a few trials the mice learn
where the platform is because they understand discrepancies between the water/the
wall because of the differences in lighting contrast.
o We as human do that too, we use markers and landmarks for it.
- Dead reckoning: your vestibular system and parietal cortex register your movements. So even if
you are blindfolded and you move, you still kind of know where you came from.
This is what we see in all animals. But it is not that simple, because we as humans we have created a
much more difficult world for ourselves. This can be categorized in all types of spatial navigation
(you don’t need to remember this, just an impression:
- Spatial cues: environmental & self-motion
- Computational mechanisms: spatial computations & executive processes
- Spatial representations: online representations & offline representations.

Problem identification
But what is the problem? Ineke did really fundamental research on spatial cognition. For her, it was
interesting, but she was also doubting the relevance of it. What she mainly learned from that, is that
there is a lot of individual variation. Some people are good at spatial cognition, and some people are
not. Where do these differences come from? Some factors are identified:
- Gender: a strategic preference is seen.
o Females: often rely on landmarks
o Males: often rely on cardinal directions (N/S/E/W); more abstract
- Age
o Children: use of perspective strategies; so they look at it from their own perspective
until the age of 12.
o Eldery: navigation ability decreases from the age of 50. This leads to implications for
mobility: is it wise to change the location from an elderly person to somewhere that is
unfamiliar for someone.

The lecture explained the situations of 2 interesting patients. Their biggest complaint: they got lost.
They did every test they could do; but none of them could identify getting lost.
Patient AC had a minor lesion. Patient WJ had brain surgery because of a tumor. The lesions were on
the right parietal side of the brain for both patients.
Patient AC was in her 30’s, well-educated with three kids. Out of nowhere she would get lost; she
would be driving and out of a sudden she would get lost. On the highway she got anxious, got lost,
and did not know where to go. At first, it was thought she had an anxiety disorder, but they couldn’t
find anything. Eventually, she was sent to a neurologist and a minor brain lesion was found. There
was no other deficit, just that she would get lost. All the other tests that were done, the woman was
very good at.
Patient WJ also got lost, but had some other problems going on too, as her executive functions were
a bit worse too. But she too, had fear navigating.

However, no one in the world did any research in getting lost. So, they did questionnaires in patients
with mild impairments, and they found it was very common, as around 30% in stroke patients