Influence of Corticospinal Tracts from Higher Order Motor Cortices on Recruitment Curve Properties in Stroke

No fucking clue what this is trying to say. Ask your doctor what this will change in your stroke protocols. I'm feeling aggrieved and tired from beating my head against a stone wall for 6 years with nothing to show for it.
http://journal.frontiersin.org/article/10.3389/fnins.2016.00079/full?

Kelsey A. Potter-Baker¹, Nicole M. Varnerin¹, David A. Cunningham^1,2, Sarah M. Roelle¹, Vishwanath Sankarasubramanian¹, Corin E. Bonnett¹, Andre G. Machado³, Adriana B. Conforto^4,5, Ken Sakaie⁶ and Ela B. Plow^1,3,7*

• ¹Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
• ²School of Biomedical Sciences, Department of Neuroscience, Kent State University, Kent, OH, USA
• ³Center for Neurological Restoration, Neurosurgery, Neurological Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
• ⁴Neurology Clinical Division, Neurology Department, Clinics Hospital, São Paulo University, São Paulo, Brazil
• ⁵Hospital Israelita Albert Einstein, São Paulo, Brazil
• ⁶Department of Diagnostic Radiology, Imaging Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
• ⁷Department of Physical Medicine and Rehabilitation, Neurological Institute, Cleveland Clinic Foundation, Cleveland, OH, USA

Background: Recruitment curves (RCs) acquired using transcranial magnetic stimulation are commonly used in stroke to study physiologic functioning of corticospinal tracts (CST) from M1. However, it is unclear whether CSTs from higher motor cortices contribute as well.

Objective: To explore whether integrity of CST from higher motor areas, besides M1, relates to CST functioning captured using RCs.

Methods: RCs were acquired for a paretic hand muscle in patients with chronic stroke. Metrics describing gain and overall output of CST were collected. CST integrity was defined by diffusion tensor imaging. For CST emerging from M1 and higher motor areas, integrity (fractional anisotropy) was evaluated in the region of the posterior limb of the internal capsule, the length of CST and in the region of the stroke lesion.

Results: We found that output and gain of RC was related to integrity along the length of CST emerging from higher motor cortices but not the M1.

Conclusions: Our results suggest that RC parameters in chronic stroke infer function primarily of CST descending from the higher motor areas but not M1. RCs may thus serve as a simple, in-expensive means to assess re-mapping of alternate areas that is generally studied with resource-intensive neuroimaging in stroke.

Introduction

Transcranial magnetic stimulation (TMS) is a popular non-invasive technique to assess physiology of corticospinal tracts (CST; Di Lazzaro, 2004). TMS is able to gauge such physiology based on the principle of electromagnetic induction. Specifically, rapidly alternating currents form the basis for TMS. These are created by discharging a large capacitor into an insulated coiled wire. The produced currents then generate magnetic fields over the scalp and skull. Electrical currents are induced, which pass unimpeded to excite superficial areas like the primary motor cortices (M1). In M1, induced currents trigger volleys along descending CST pathways that produce motor evoked potentials (MEP) in contralateral muscles (Di Lazzaro, 2004). The resultant MEP amplitude is believed to reflect output of the CST pathways. With increasing TMS intensities, MEP amplitudes typically increase. By applying a range of increasing intensities, one can study incremental gains in MEPs that are plotted commonly as a stimulus-response or a recruitment curve. The slope of the curve and sum of MEP amplitudes signify gain and output of the descending CST (Devanne et al., 1997; Ridding and Rothwell, 1997; Boroojerdi et al., 2001; Monti et al., 2001; Ward et al., 2006).

TMS techniques are particularly relevant in stroke. This is because TMS can index function and recovery of the paretic upper limb by evaluating CST damage that is typical of stroke affecting the territory of the middle cerebral artery (Bogousslavsky and Regli, 1990; Johansen-Berg et al., 2002; Buffon et al., 2005). For example, several groups have established that the mere presence or absence of MEPs in paretic muscles can inform about clinical function (Ward et al., 2006; Stinear et al., 2007, 2012; Ward, 2011; Levy et al., 2016). Beyond the binary outcome, recruitment curves offer several additional advantages. By definition, recruitment curves assay MEPs at a range of increasing TMS intensities, and as such, illustrate a graded profile of CST function (Thickbroom et al., 2002). As a result, increases or decreases in slope or gain of the recruitment curve can signify recovery more closely than binary outcomes signaling the presence or absence of MEPs. For example, numerous studies have shown that decreases in recruitment curve parameters are indicative of more substantial CST damage, functional impairment, or poor recovery potential in patients with stroke (Devanne et al., 1997; Carroll et al., 2001; Liepert et al., 2005; Talelli et al., 2006; Ward et al., 2006; Lindberg et al., 2007; Lotze et al., 2012; Cunningham et al., 2014). In fact, graded increases in the slope of the recruitment curve have been associated with graded functional gains in recovery (Hummel et al., 2005) suggesting that metrics that are not binary, but rather based on an interval scale may serve as an effective monitor for rehabilitation-related recovery.

Recruitment curves are especially popular in stroke because they are believed to reflect CST gain and output from the region most linked to motor function, despite inherent damage, the primary motor cortex (M1; Devanne et al., 1997). However, given that other secondary motor cortices contribute to paretic hand function and recovery in stroke, it is possible that recruitment curves may also represent functioning of CST from higher motor areas beyond M1. For example, higher motor areas like the supplementary motor area (SMA) and premotor cortex (PMC) can support paretic hand function and recovery via re-mapping and plasticity changes proportional to the level of damage to CST from M1 (Weiller et al., 1992; Fries et al., 1993; Seitz et al., 1998; Liu and Rouiller, 1999; Fridman et al., 2004; Dancause et al., 2005; Ward et al., 2006, 2007; Bhatt et al., 2007; Takeuchi et al., 2007; Calautti et al., 2010; Zeiler et al., 2013; Plow et al., 2014). Indeed, SMA and PMC can offer alternate CST to the paretic upper limb, contributing in the range of 20–40% of entire CST (Dum and Strick, 1991; Schulz et al., 2012).

Understanding if there is a role of CST from secondary motor areas on recruitment curve properties is critical. TMS is already relevant for neurorehabilitation since it is simple and in-expensive. Therefore, by gaining this understanding, we could realize if using TMS generated recruitment curves could accurately and in-expensively interpret which areas re-map and contribute to overall CST function during recovery. For this reason, here we explored whether integrity of CST from PMC and SMA, besides M1, related to CST function as captured by recruitment curves in patients with chronic stroke. CST integrity was measured using diffusion tensor imaging (DTI) [fractional anisotropy (FA)] due to its long-standing use in neurology and generally accepted accuracy (Chenevert et al., 1990; Alexander et al., 2007; Soares et al., 2013). We argued that if recruitment curve properties were to reflect integrity of CST from higher motor cortices, then any increase in gain/output of the recruitment curve would signify their remapping in recovery. As such, our finding would create an opportunity to target PMC/SMA with techniques like cortical stimulation that are believed to boost recovery by boosting functioning of CST recovery (Fregni and Pascual-Leone, 2007). In addition, our results could help show that recruitment curves may serve as a simple, in-expensive means to assess function from areas generally studied with more resource-intensive structural and functional imaging in patients with stroke.

To our knowledge, only a pilot study by Lindberg et al. has directly investigated the relationship between CST integrity captured using DTI and recruitment curves in stroke. Within their study, Lindberg and colleagues found that a greater loss of integrity at the level of the cerebral peduncle was correlated with a reduced recruitment curve slope (Lindberg et al., 2007). However, because recent research has suggested that DTI indices describing CST integrity vary with extent and location of the lesion, it is critical to capture integrity not just in a single region but across several regions, and along the length of CST (Liepert et al., 2005; Zhu et al., 2010; Lindenberg et al., 2012; Schulz et al., 2012). Therefore, here, we chose to assess CST integrity at different regions along the path of CST. We captured FA at the most commonly used regions for analysis—the posterior limb of internal capsule (PLIC) and mean along the length of CST (Stinear et al., 2007; Allendorfer et al., 2012; Lindenberg et al., 2012). We also captured CST integrity in the region of the stroke lesion. We aimed to learn whether CST integrity at a specific region- PLIC, lesion or the length of CST pathways- closely related to neurophysiologic measurement of CST function described using the recruitment curve. We postulated that by identifying, which regions of CST most contribute to CST function, it would become possible to use recruitment curves as means to understand lesion characteristics, lesion load, and accordingly derive prognosis.(Who gives a shit about prognosis?, derive some solutions you lazy idiots.)