Commit a42c951a authored by Julius Welzel's avatar Julius Welzel

Replace 1_introduction

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\begin{document}
In recent years, there has been a growing interest in age related studies on the brain.
With the aging of the worlds population arises a major challenge for the health care system. The number of people older than 60 and above is expected to more than double by 2050, increasing from 962 million in 2017 to 2.1 billion in 2050, with tendency to rise. This is only partly due to the growth in the world population, yet also to increasing life expectancy \citep{UN:2017}. Understanding the healthy aging brain is a central to the development of meaningful healthcare \citep{deak2015recent}.
Previous research has established that the healthy aging brain does differ from the healthy young brain in different domains like memory, perception and sensorimotor functioning \citep{cabeza2002hemispheric,hedden2004insights}.
Understanding the decline in sensorimotor functioning with age, can help with one of the many increasing neurological diseases, which will affect the motor system.. The cause of movement disorders are multi-factorial with the central nervous playing a key role \citep{seidler2010motor}. As it is often difficult to separate the effects of normal ageing from those of pathological processes, this study tries to contribute to the understanding of the normal aging brain in a movement related task using advanced neuroimaging techniques.
\subsection{Age differences in the Motor System}
Previous research comparing young and old adults suggests a decline in motor tasks performance with age \citep{Enoka2003MechanismsTC,seidler2010motor}.
Neuroimaging studies helped to understand these losses in performance to a greater extend. For simple movements tasks, previous fMRI research observed an additional recruitment of brain regions \citep{ward2003age,heuninckx2008systems}. Electrophysiological research found a age effect in slowing of motor responses in older adults while performing a motor execution (ME) task \citep{falkenstein2006effects,bardouille2019evidence}. A possible explanation for the overall age effect in motor tasks is the reduction of neural differentiation in older adults throughout the motor control network \citep{carp2011age}. However, age differences do not only occur in ME, but can also be found in several motor imagery (MI) studies. Why MI is of great interest, what it reflects and how ME and MI relate will be further introduced in the following sections.
\subsection{Motor Imagery}
\subsection{Neuronal Age Differences}
Age is important
\subsection{Stroke \& Motor Imagery}
The motor system of humans is extremely flexible. There are hardly any constraints to the spatial range or the timing of a movement. To execute a specific task, like grasping an object, or just out of pure joy, one can imagine all kinds of movements. It is even possible to imagine movement which are not physically possible. This ability leads one to suppose, that the motor system seems to be somewhat different from rigid hierarchically organised system with only top down processes \citep{mulder2007motor}. In this system the mental representation of a particular movement act without any motor output is defined as MI \citep{jeannerod2001neural,mulder2005observation}. MI is successfully used in sports, music practice and for rehabilitative purposes \citep{driskell1994does,kranczioch2014mobile,langhorne2009motor}. However, \citet{stinear2006kinesthetic} showed that kinesthetic but not visual imagery of a movement influenced corticomotor excitability. The underlying idea is, that brain areas engaged in the actual performance of movements are also active during motor imagery. %Many studies showed the involvement of movement related brain regions is active during MI. %%%LIT%%%%%%%%%%%%
This can be used as a backdoor for rehabilitaition of motor impairments, e.g. following a stroke. % MI STROKE LITERATURE
Cortical areas and motor networks in the brain are activated by imagining movements in order to avoid maladaptive developments of the brain and to promote a better recovery process \citep{sharma2006motor}.
% For instance
% kinaesthetic MI, but not visual MI, results in detectable activity changes in sensorimotor areas
% (Neuper et al., 2005; Stinear et al., 2006). Additionally, a direct comparison of implicit MI
% (Johnson et al., 2002; Parsons, 1987; Sekiyama, 1982) and explicit MI (Gerardin et al., 2000; Hanakawa et al., 2003) in patients with conversion disorder exhibiting paralysis of one arm
% revealed a larger activation in the ventromedial prefrontal and superior temporal cortex during implicit MI of the affected hand compared to explicit MI (de Lange, Roelofs, & Toni, 2008).
Therefore, extensive kinesthetic MI can positively influence motor learning and help the recovery of the motor system. But why is the neuronal pattern of MI in healthy older adults of interest in this study? This question is hopefully answered in the next section.
\subsection{BCI in rehabilitation} \label{chap:BCI}
\subsubsection{$\mu$-band}
SMA
SMR
Attention-modulation
\subsubsection{$\beta$-band}
$\beta$-rebound
Sensori-motor-integration
CSPs
\begin{hyp} \label{hyp:area} Older show greater cortical recruitment for ERD in complex visuo-motor task MI. \end{hyp}
\subsection{Hypothesis}
Cortex area involved \\
Compensatory process for bad MI \\
\end{document}
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