Sweet Dreams Are Made Of This: Could REM Sleep Behaviour Disorder Be A Precursor To Dementia With Lewy Bodies?

Dementia, in its many forms, is an interesting disorder; it comes with quite a variety of impairments and abnormal functioning. Thus, it is not uncommon to find dementia patients suffering from sleep abnormalities. These can manifest as changes in sleep patterns or difficulties in sleeping. There is not a huge amount of knowledge on the reasons behind this, but it is assumed that dementia’s morphing of the brain has an impact on the regions that engage in sleep behaviours. This blog will be focusing specifically on Dementia with Lewy Bodies (DLB) and it’s association with REM Sleep Behaviour Disorder (RSBD).

Dementia with Lewy Bodies counts for approximately 5-10% of all dementia cases; however, it has been suggested that DLB is largely under-diagnosed or misdiagnosed, due to an overlap of features with Alzheimer’s Disease. It’s main symptoms are cognitive fluctuations, hallucinations, disturbed sleep patterns and parkinsonism features (due to its similarities in pathology with Parkinson’s Disease). It can be identified at autopsy by the large number of lewy bodies found in the limbic system, basal ganglia and cortex. Lewy bodies are abnormal aggregates of protein found inside neurons. For more information on DLB, please see: http://www.alzheimers.org.uk/site/scripts/documents_info.php?documentID=113.

REM Sleep Behaviour Disorder has been commonly associated with DLB and other disorders that occur with the presence of synucleinopathies. A review paper by Turner (2002) report that out of 93 cases of Parkinson’s Disease, Multiple Systems Atrophy and DLB, 86% of patients were found to suffer from RSBD. But what is RSBD? There are three stages of the wake-sleep cycle: wakefulness, REM sleep and non-REM sleep. REM sleep is the lightest stage of sleep, characterized by rapid eye movements, paralysis of muscles and dreaming. RSBD appears to reflect a dysfunction in this stage of sleep, with loss of muscle atonia and vivid dreams (Boeve , Silber & Ferman, 2004). It is characterized by abnormal vocalizations, such as yelling or swearing, and abnormal motor behaviour, which can be simple jerky movements or limb flailing, punching, etc.  Patients usually report dreams to involve insects or animals, and being chased or attacked. Bed partners’ comments or attempts to wake up the patient may become interwoven into the dream, and lead to harm of the patient or partner. The frequency and severity of the dream re-enactment usually wanes as the dementia progresses. Below, I have linked a video that provides a brief glimpse at how RSBD may manifest itself:

How can REM Sleep Behaviour Disorder help with the diagnosis of Dementia with Lewy Bodies?

It has been indicated that RBD is a supportive feature in the diagnosis of DLB as it occurs when there is a greater frequency of synucleinopathies than in other disorders, such as Alzheimers Disease or Fronto Temporal Dementia (Boeve, 2010). Synucleinopathies are abnormal aggregates of alpha-synuclein proteins in nerves, glial cells or nerve fibres, i.e. Lewy bodies. Boeve et al., 2004’s paper presented a good description of the pathology behind RBD and how it links to DLB. It suggests that the loss of neurons in the locus coeruleus and substantia nigra, and subsequent dysregulation of cholinergic neurons in the pedunculopontine nucleus in DLB might disrupt normal REM sleep, as the pedunculopontine nucleus is thought to project cholinergic mesopontine neurons to the medullary reticular neurons, which inhibit the spinal motor neurons (Boeve et al., 2004). This in turn leads to atonia in REM sleep. Thus if there is a disruption to the normal workings of the pedunculopontine nucleus, atonia during REM sleep will be lost, leading to excessive motor activity. This has been further supported by case studies, such as a DLB patient’s autopsy report as described by Turner (2002), in which an examination of the substantia nigra and locus coeruleus revealed a significant amount of depigmentation, neuronal loss and up to five lewy bodies per neuron. Studies such as these have provided excellent evidence that these two disorders are interlinked. This link suggests that RSBD could be predictive of DLB and other parkinsonism disorders.

But why is the connection between these two disorders important? It has been found that there is are huge issues with clinical accuracy for DLB diagnosis, with consensus being between 22-83% and specificity between 87%-100% (Turner, 2002). Under-diagnosis and misdiagnosis appeared to be large problems within this, with DLB often mistaken for Alzheimer’s Disease. This is understandable, as DLB often occurs with a memory impairment, while hallucinations may not be reported and cognitive fluctuations remain difficult to define. It is essential that this changes, as correct diagnosis is necessary to ensure the best treatments and support are being given to such vulnerable patients. While RSBD and DLB may share similar pathological hallmarks, there is an additional reason that RSBD may provide a fundamental diagnostic marker for DLB. It has been reported to occur many years prior to the onset of cognitive impairments in DLB, with Turner (2002) reporting a case study of a 73 patient who suffered from RSBD up to 13 years before his first cognitive symptom was noticed.

It has been noted that RSBD can be clinically diagnosed, with screen tools (such as questionnaires) that hold efficient validity (Munhoz & Teive, 2014). Additionally, RSBD can be diagnosed using a polysomnography – with specific features being rapid eye movement and an elevated EMG tone. Video evidence is also usually recorded for diagnostic purposes. This has been viewed as the “gold standard” for RSBD assessment (Munhoz & Teive, 2014). With its widely accepted diagnosis, there is a possibility that RSBD could act as an early diagnostic marker for DLB, and thus could enhance the sensitivity and accuracy of diagnosis.


Boeve, B. F. (2010). REM sleep behavior disorder. Annals of the New York Academy of Sciences, 1184(1), 15-54.
Boeve, B. F., Silber, M. H., & Ferman, T. J. (2004). REM sleep behavior disorder in Parkinson’s disease and dementia with Lewy bodies. Journal of geriatric psychiatry and neurology, 17(3), 146-157.
Munhoz, R. P., & Teive, H. A. (2014). REM sleep behaviour disorder: How useful is it for the differential diagnosis of parkinsonism?. Clinical neurology and neurosurgery, 127, 71-74.
Turner, R. S. (2002). Idiopathic rapid eye movement sleep behavior disorder is a harbinger of dementia with Lewy bodies. Journal of geriatric psychiatry and neurology, 15(4), 195-199.


C’mon Baby, Do The Locomotion: Gait Analysis as a a Diagnostic Tool for MCI and Dementia

Movement has long struck me as a funny thing. The general population regard it as a simple, automatic process and cast not another thought towards it; yet it is an incredibly complex synchronization of neuronal activity and muscular response. I will not ramble into the intricacies of this, but like many facets of the brain’s role in our daily life, we are still only scratching the surface of our understanding of such mechanisms. What I will bring to your attention is an exercise many of us engage in every day: walking.

It can easily be taken for granted that our locomotive abilities deplete with age: an elderly man’s stiff, heavy-footed shuffle shows only the thinnest ghost of a young boy’s playful, prancing step. This could be attributed to our muscular and general body function. We get old and we begin to feel all the aches and pains of living a long life. But we could imply that there is more to the change in our pace that the simple wear-and-tear the years have brought us. A variety of regions in the cerebral cortex influence our gait and the natural atrophy of our brain could change the manner and capacity of their function.

However, aging is not the only factor that changes our swagger. Neurological disorders, causing lesions to cerebral regions involved in gait, can become obvious through our walk. The most prominent example of this is the parkinsonism gait: small, shuffling steps and an overall slow pace. Indeed, in his book “Phantoms in the brain”, V.S. Ramachandran (2005) described an old professor of his instructing his medical class to diagnose Parkinson’s Disease with their eyes closed – simply by listening to the dragging sound of their feet as they walked. When we consider the cognitive components captured by locomotion, such an abnormality is not unfounded. Gait is directed by goals, thus is mediated by attentional circuits (Rochester, Galna, Lord & Burn, 2014). This involves frontal lobe activity, which is disrupted in Parkinson’s Disease due to the dysfunction of the basal ganglia. In the case of parkinsonism, velocity and stride length is predominately affected, but multiple sites within the cortico-basal ganglion-thalamic circuit can cause varying degrees of gait disturbances (Elble, 2007). As in Parkinson’s Disease, movement ability has been shown to decline years prior to the onset of cognitive impairments in the other common dementia subgroups (Montero-Odasso, Verghase, Beauchet & Hausdorff, 2012).

The Dynamic Relationship Between Gait and Cognition

That finding has opened a new area of research: the complementary relationship between gait and cognition. To discuss this, let us first examine the regions of the brain implicated in successful gait. We’ve already mentioned the frontal lobes’ role in attention, a fundamental component of locomotion. This area is also associated with executive function, which (depending on the paper) can describe a wide range of every day tasks: problem-solving, set-switching, working memory, reasoning, etc. These abilities are vital for engaging in our environments, allowing us to move through the world safely and efficiently. Without them, we are at risk of several locomotive problems, such as postural instability and falling (Montero-Odasso & Hachinski, 2014). This will be explained later in regards to the increasing demand accurate gait places on the cognitive resources of the diseased brain. The frontal subcortical networks controlling motor and cognitive abilities are located closely to one another, lending an explanation as to why white matter disease or frontal atrophy may simultaneously affect both gait and executive function. The temporal lobe also plays an important part in gait ability, due to its role in spatial navigation and memory (Annweiler, Beauchet, Bartha & Montero-Odasso, 2013). Unsteady and uncoordinated gait may result from lesions to the hippocampal area, as they would allow a deficit in the recall of the complex sequences of movement necessary for walking. Imaging studies have correlated medial temporal lobe atrophy with mild cognitive impairment (MCI; Annweiler et al., 2013). Lastly, it has been suggested that the parietal cortex’s integration of visuospatial, cognitive and motor information could have an impact on an individual’s gait.

Research into MCI’s relationship with gait has begun to spring up in the last number of years. MCI is described as a predementia state, with individuals developing either amnesic or other cognitive impairments  (Montero-Odasso, Oteng-Amoako, Speechley, Gopaul, Beauchet, Annweiler & Muir-Hunter, 2014). The current proposal behind the correlation in gait disturbances and cognitive failing is as follows: with age or disease, the automatic processes that the subcortical areas engage in to ensure smooth gait weaken, leading to a need for an increase in voluntary cortical mechanisms (Gillain, Warzee, Lekeu, Wojtasik, Maquet, Croisier… & Petermans, 2009). In essence, we begin to find it necessary to think about how we walk. Using this principle, our clever researchers have begun to develop a method in which to utilize gait analysis as a diagnostic tool for MCI. Lundin-Olsson’s (1997) seminal study “Stop walking when talking” introduced a new technique to predict falls: the dual task. This hypothesizes that walking while performing a secondary, cognitively engaging task will create competition between the brain’s resources, causing an interference effect. The modifications we must automatically make to our gait in order to navigate around our  environments are described as “costs” in relation to the diseased brain (Montero-Odasso & Hachinski, 2014). Hence, an individual who has yet to reveal cognitive deficits may reveal subtle gait impairments when asked to engage in a dual-task. These disturbances occur due to the cognitive stress placed on the neural networks mediating these tasks, and as such may be facilitated for the early prediction of MCI.

Gait Analysis and Dementia

These researchers are now beginning to apply these findings to the early prediction of dementia. This is a crucial area to develop, as dementia is becoming increasingly prevalent with our growing elderly population; approximately 8% of our over 65s are diagnosed with it, with as high as 35% of the over 85 age group reported to have it (Montero-Odasso et al., 2012). This not only takes a toll on the individuals suffering from dementia and their loved ones, it also places a rising monetary cost on society (Hurd, Martorell, Delavande, Mullen & Langa, 2013). Early diagnosis and treatment of dementia is currently the most feasible way forward to bring down both of these burdens. Gait analysis is a “cheap and cheerful” method in which to diagnose such diseases, as other techniques (such as neuroimaging) may not be suitable to individuals with limited resources (Verghese, Annweiler, Ayers, Barzilai, Beauchet, Bennett, … & Wang,2014). It is also quite applicable for early diagnosis, as gait disturbance has been observed up to 12 years prior to cognitive onset of dementia; this is certainly suitable for the most common sub-type, Alzheimer’s Disease, in which the neurodegeneration can begin as early as 20 years before obvious symptoms appear (Montero-Odasso et al., 2012). As it stands, the diagnostic measures are not overtly different from those from MCI; the employment of dual-task should sufficiently indicate an underlying cognitive disorder. What the literature is lacking is an accurate utilization of gait analysis in differentiating early signs of the dementia sub-groups. Some studies have shed light onto this matter by describing different failing gait characteristics for different dementias; a fine example is the growing body of evidence for motoric cognitive risk syndrome as a predictor of vascular dementia (Verghese et al., 2014). Another study has suggested that a deficit in gait rhythm could indicate underlying Alzheimer’s Disease pathology (Verghese, Wang,  Lipton, Holtzer,& Xue, X. 2007). Although this shows a start on the path forwards, we still have a long way to go before we find the answers we’re looking for.

The first steps into this treasure-trove of research are being made, and I, for one, am excited to see the kinds of hidden gems waiting to be discovered.


Annweiler, C., Beauchet, O., Bartha, R., & Montero-Odasso, M. (2013). Slow gait in MCI is associated with ventricular enlargement: results from the Gait and Brain Study. Journal of Neural Transmission, 120(7), 1083-1092.

Blakeslee, S. & Ramachandran, V.S. (2005). Phantoms in the Brain: Human nature and the architecture of the mind. London: Harper Perennial

Elble, R. J. (2007). Gait and dementia: moving beyond the notion of gait apraxia. Journal of neural transmission, 114(10), 1253-1258.

Gillain, S., Warzee, E., Lekeu, F., Wojtasik, V., Maquet, D., Croisier, J. L., … & Petermans, J. (2009). The value of instrumental gait analysis in elderly healthy, MCI or Alzheimer’s disease subjects and a comparison with other clinical tests used in single and dual-task conditions. Annals of physical and rehabilitation medicine, 52(6), 453-474.

Hurd, M. D., Martorell, P., Delavande, A., Mullen, K. J., & Langa, K. M. (2013). Monetary costs of dementia in the United States. New England Journal of Medicine, 368(14), 1326-1334.

Lundin-Olsson, L., Nyberg, L., & Gustafson, Y. (1997). “Stops walking when talking” as a predictor of falls in elderly people. The Lancet, 349(9052), 617.

Montero-Odasso, M., & Hachinski, V. (2014). Preludes to brain failure: executive dysfunction and gait disturbances. Neurological Sciences, 35(4), 601-604.

Montero-Odasso, M., Oteng-Amoako, A., Speechley, M., Gopaul, K., Beauchet, O., Annweiler, C., & Muir-Hunter, S. W. (2014). The motor signature of mild cognitive impairment: results from the Gait and Brain Study. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, glu155.

Montero‐Odasso, M., Verghese, J., Beauchet, O., & Hausdorff, J. M. (2012). Gait and cognition: a complementary approach to understanding brain function and the risk of falling.  Journal of the American Geriatrics Society, 60(11), 2127-2136.

Rochester, L., Galna, B., Lord, S., & Burn, D. (2014). The nature of dual-task interference during gait in incident Parkinson’s disease. Neuroscience, 265, 83-94.

Verghese, J., Annweiler, C., Ayers, E., Barzilai, N., Beauchet, O., Bennett, D. A., … & Wang, C. (2014). Motoric cognitive risk syndrome Multicountry prevalence and dementia risk. Neurology, 83(8), 718-726.

Verghese, J., Wang, C., Lipton, R. B., Holtzer, R., & Xue, X. (2007). Quantitative gait dysfunction and risk of cognitive decline and dementia.Journal of Neurology, Neurosurgery & Psychiatry, 78(9), 929-935.

Stroke Rehabilitation: Paving New Pathways To Improvement

I came across a very interesting article today with regards to stroke, and the impact cerebral plasticity has on rehabilitative techniques (see http://www.theguardian.com/science/2015/feb/08/robert-mccrum-lucky-survivor-stroke-treatment-revolution?CMP=twt_gu). It’s an area that I have read quite a bit on, and so this blog will aspire to give a brief overview of different forms of rehabilitation, and the reasoning behind them. The focus will be on motor function, rather than the cognitive impairments that can accompany a stroke.

Firstly, a stroke occurs when the blood flow to a particular brain area is disrupted (Murphy & Corbett, 2009). This allows cells to die off, which negatively affects the functioning of that cerebral region, i.e. an infarct to the hand knob of the motor cortex could lead to an impairment of hand movement. Strokes can be caused by a burst aneurysm or a blood clot blocking a blood vessel. This website (http://www.stroke.org/) will answer a wide range of questions regarding the causes and consequences of stroke. This blog will be discussing one of the most notable and debilitating effects of stroke: motor impairment.

Robert McCrum speaks of the difference in the rehabilitation environment between today and 30 years ago, when he first came into contact with it. He uses words like “dynamic” to describe the attitudes and approaches of stroke recovery nowadays. He attributes the growing knowledge surrounding cerebral plasticity to this new optimism. Cerebral plasticity refers to the structural change of the brain in order to accommodate changing demands (Lövdén, Wenger, Märtensson, Lindenberger & Bäckman, 2013). This is often depicted as the “rewiring” of neural connections, and appears to be fundamental for learning and re-learning, in the case of rehabilitation (Kleim & Jones, 2008). Although the concept can seem complex and daunting, it is actually a simple enough idea; the brain creates a compensatory pathway or method to carry out a task to the best of the individual’s (new) ability. It’s the same principle as finding an obstruction preventing you from taking the easy route on the highway to your destination, and choosing to drive down the smaller, less-taken roads to reach it.

Physical rehabilitation has been employed in cases of stroke for quite a long time. One might believe that this is simply to strengthen the muscles that have wasted away, and has nothing to do with the neural mechanisms of motor function. But why have the muscles diminished in the first place? In the majority of cases, lesions to the motor cortex destroy the motor neurons responsible for stimulating said muscles which leads to a gradual depletion of tone and strength. Physical rehabilitation attempts to stimulate the motor regions, in order to excite the motor areas responsible for the impairment in functioning (Liepert, Miltner, Bauder, Sommer, Dettmers, Taub & Weiller,1998). This will allow a reorganization of the (now) redundant anatomical circuits and allow neuronal populations to change their physiological relationships with other neuronal ensembles (Linazasoro, 2006). Physical rehabilitation for stroke is largely concerned with muscle strengthening and physical conditioning, with advancements in technology introducing us to an era of robot-assisted movement training (Teixeira-Salmela, Olney, Nadeau & Brouwer, 1999; Lum, Burgar, Shor, Majmunder & Van der Loos, 2002). Imaging studies have demonstrated plastic changes to the neural networks involved in movement, coinciding with marked motor improvement (Hodics, Cohen & Cramer, 2006).

While neural plasticity’s place in physical rehabilitation is interesting, even more fascinating is it’s role in rehabilitative interventions which employ mental/motor imagery to aid recovery. Mental imagery can be defined as a process in which individuals can actively relive sensations (visual, auditory, tactile, etc) without the need for external stimuli (Jackson, Lafleur, Malouin, Richards & Doyon, 2001). Motor imagery is described as the internal reproduction of the representation of a specific action, without the execution of movement (Jackson et al., 2001). A notable example of the reasoning behind the use of mental imagery in motor rehabilitation comes from Pascaul-Leone and colleagues (1995) study. This investigation incorporated three groups: (i). the physical group, which involved physically practicing playing a piano piece over a period of time, (ii). the mental group, which involved mentally imagining playing the same piano piece over the same period of time, and (iii). a control group. The results revealed that both the mental and physical group showed a marked improvement in their fine finger motor skills, when compared to controls. It also demonstrated that structural changes to the motor cortex pertaining to the fingers, in both the physical and mental group. This suggests that these neural networks were recruited for the learning of the motor task, and that mental practice can appropriately access and modulate those connections (Pascaul-Leone et al., 1995). This study recruited healthy individuals, but it lays a foundation for the use of mental/motor imagery in stroke rehabilitation.

Stroke research has used the evidence of mental/motor imagery recruiting the same cortical motor areas in order to function, as an argument for its place in rehabilitation. Researchers have suggested that imagery of movement can stimulate the redistribution of active connections between parallel motor regions, and thus, improve recovery of motor function (Dijkerman, Ietswaart, Johnson & MacWalter, 2004). This form of rehabilitation involves techniques such as mentally rehearsing an action over a set period of time, and mentally practicing an action just prior to actually engaging in said movement. However, these methods have been met with mixed results. It should be noted that these studies can be confounded by a number of factors, that could lead to results determining whether the rehabilitation is effective or not. These include patients’ inability to engage in mental imagery (as lesions may disrupt neural networks involved in these processes), small sample sizes, heterogeneity in participants’ characteristics and outcome measures (Sharma, Pomeroy & Baron, 2006). Within the number of studies that provide evidence for mental/motor imagery’s positive impact on motor recovery, there have been reports that improvement in motor function is specific to the mentally rehearsed tasks (Dijkerman et al., 2004). This is less than optimal, as treatment generalizability is exceedingly important within rehabilitative techniques. Nonetheless, mental/motor imagery as a form of rehabilitation is an area that researchers should strive to engage in; even to use it as a complimentary add-on to physical rehabilitation. This type of intervention is ideal, as it requires little supervision, is cost-effective and easily accessible (Braun, Kleynen, Schols, Beurskens & Wade, 2008).

Stroke is a highly prevalent and disabling event, and thus, it is no surprise that there is a variety of rehabilitation programmes being researched and developed to combat it’s harsh impact on motor performance. It is important to be aware of cerebral plasticity’s role in these rehabilitative interventions, as it is the reorganization of neural connections  that stroke researchers are targeting. It should also be noted that due to the nature of stroke, the research into stroke rehabilitation has wider implications for other neurological disorders; these often provide a basis for treatments for neurodegenerative disorders affecting the motor system, such as Parkinson’s Disease, or for motor impairments resulting from traumatic brain injuries. In addition to the research’s practical significance, neural plasticity is a fascinating concept; the ability of the brain to pave new pathways and build new bridges in order to engage in learning or re-learning processes. It’s certainly an area worth keeping an eye on, and hopefully, the coming years will find these rehabilitative techniques to make progress in leaps and bounds.


Braun, S., Kleynen, M., Schols, J., Schack, T., Beurskens, A., & Wade, D. (2008). Using mental practice in stroke rehabilitation: a framework. Clinical Rehabilitation22(7), 579-591.

Dijkerman, H. C., Ietswaart, M., Johnston, M., & MacWalter, R. S. (2004). Does   motor imagery training improve hand function in chronic stroke patients? A pilot study. Clinical rehabilitation18(5), 538-549.

Hodics, T., Cohen, L. G., & Cramer, S. C. (2006). Functional imaging of intervention effects in stroke motor rehabilitation. Archives of physical medicine and rehabilitation, 87(12), 36-42.

Jackson, P. L., Lafleur, M. F., Malouin, F., Richards, C., & Doyon, J. (2001). Potential role of mental practice using motor imagery in neurologic    rehabilitation. Archives of physical medicine and rehabilitation82(8), 1133-    1141.

Kleim, J. A., & Jones, T. A. (2008). Principles of experience-dependent neural plasticity: implications for rehabilitation after brain damage. Journal of Speech, Language, and Hearing Research, 51(1), S225-S239.

Liepert, J., Miltner, W. H. R., Bauder, H., Sommer, M., Dettmers, C., Taub, E., & Weiller, C. (1998). Motor cortex plasticity during constraint-induced movement therapy in stroke patients. Neuroscience letters, 250(1), 5-8.

Linazasoro, G. (2006). Plasticity in PD: from compensatory usefulness to negative aberrant             behaviours. Focus Parkinson Dis18, 5-9.

Lövdén, M., Wenger, E., Mårtensson, J., Lindenberger, U., & Bäckman, L. (2013).            Structural brain plasticity in adult learning and development. Neuroscience &          Biobehavioral Reviews37(9), 2296-2310.

Lum, P. S., Burgar, C. G., Shor, P. C., Majmundar, M., & Van der Loos, M. (2002). Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke.Archives of physical medicine and rehabilitation, 83(7), 952-959.

Murphy, T. H., & Corbett, D. (2009). Plasticity during stroke recovery: from synapse to behaviour. Nature Reviews Neuroscience, 10(12), 861-872.

Pascual-Leone, A., Dang, N., Cohen, L. G., Brasil-Neto, J. P., Cammarota, A., & Hallett, M. (1995). Modulation of muscle responses evoked by transcranial magnetic stimulation during the acquisition of new fine motor skills. Journal of neurophysiology74, 1037-1037.

Sharma, N., Pomeroy, V. M., & Baron, J. C. (2006). Motor imagery a backdoor to the motor system after stroke?. Stroke, 37(7), 1941-1952.

Teixeira-Salmela, L. F., Olney, S. J., Nadeau, S., & Brouwer, B. (1999). Muscle strengthening and physical conditioning to reduce impairment and disability in chronic stroke survivors. Archives of physical medicine and rehabilitation, 80(10), 1211-1218.

Beyond the Headlines: What to look out for when reading a scientific paper.

Yesterday, an interesting study appeared on my Twitter timeline: it explored the attitudes of male college students towards women when investigating whether they would identify an intent into forcing sexual intercourse on a woman, and whether they would classify this as rape or not (Edwards, Bradshaw & Hinsz, 2014; link will be provided in the reference section). The purpose of the study was to gather an understanding of the motivation behind rape, and perhaps provide a stepping stone into the development of a sexual assault prevention method. It was the first study of its kind and had a relatively small sample size; 73 participants in total. From this, 13 participants appeared to endorse the intention to use force, but did not describe this as rape, and 10 participants endorsed both intention to use force and rape itself. Although it is an understatement to say that I feel disgusted that there was any one such response, it should be remembered that this sample is hardly generalizable to the larger population.

Given that the study addresses issues that are being widely discussed on social network platforms (such as the concept of “rape-culture”), it is hardly surprising that popular online news websites generated an article on the subject quite promptly (http://www.buzzfeed.com/rossalynwarren/a-third-of-male-students-in-a-new-study-say-theyd-rape-a-wom). It was not long before this started circulating the social networks, sparking shock and horror at its outlandish, eye-catching headline “A Third of Male Students Say They’d Rape a Woman If There Were No Consequences, a Study Reveals”. You can hear the increasing thrum of outrage from the masses right now, if you listen closely enough. Don’t forget that this headline is designed to pull in as many readers as possible; this small study hardly speaks for all male students out there. This blog post is not going to be about Edwards et al., (2014) article, or even this particular Buzzfeed one. I’m not here to discuss how the media often misinterpret scientific research, thus twisting the findings (although Ben Goldacre has a very good chapter on this in his book, Bad Science). However, it will hopefully outline some components that you should look at in such studies before you take everything they tell you as truth.

Firstly, what is the rationale behind the study? Why have the researchers decided to undertake this work and how has previous work inspired their aims? This requires you to read more than the abstract of the paper. I’m not telling you to look into every single citation that the authors have referenced; although it can be beneficial to look into how relevant these are to determine that the investigators aren’t trying to increase their references in order to make the study look better. Do read the introduction section thoroughly and come to grips with the concepts that it explains. It is equally important to find out if the researchers are looking into this out of their own interests, or if they are working for a company that may bias their interpretation of the findings. For example, a study undertaken by scientists who work for a drug company is hardly going to say that the drug is useless and shouldn’t be touched by consumers.

Secondly, the participants section; who are they, how many is there and why did they partake? Generally, psychology studies recruit a WEIRD sample; that is they are western, educated, industrialized, rich and democratic (Heinrich, Heine & Norenzayan, 2010). In short, they are college students: an easy sample for researchers to get their hands on. It should be noted that this may not be the most representative population to conduct research on. They usually undergo the studies to gain either credit for their course or for a financial reimbursement. The amount of subjects is what really counts here: the larger the sample, the more applicable the results are to the general public. It’s important to be careful when looking into this as subjects can drop out or withdraw their data at any time. This means a study may say that it had 100 participants, but 40 could have dropped out due to a chronic stomach bug and this wouldn’t be mentioned until further down in the results section. Keep your eyes peeled for these differences; it happens with great regularity.

Now, look at the study’s methods. What tests were used? How appropriate were they to the investigation? What were the controls? It is important to understand how the tests work and what they are used to assess. You are hardly going to give credit to a study using the Doors and People test to investigate executive function in Parkinson’s Disease patients (although the murky definition of executive function is another rant entirely). Controls are equally important to pay attention to; you want to make sure the researchers attempted to eliminate as many confounding factors as they could. After all, you don’t want a study that states A equals C because of B, when it could actually be because of D or E, or any other letter of the alphabet.

Finally, we arrive at the results and discussion sections of the paper. How well do these to tie together? The discussion should reflect the results accurately. I’m not going to go too much into the important aspects of statistics, but look at what results came out as significant and reflect what that could mean. This is what the authors should have done to reach their conclusions in the discussion section. How well does the discussion tie their findings to previous research? Significant or not, results should always either support and possibly expand on previous studies, or contradict them. Do the authors address the limitations of the study? These are important, because they let us know what should be improved upon for future research and allow us to know how wary we should be of the findings.

This can be arduous, I’m aware. You might be reading a 90 page paper and would prefer to scan through it as quickly as possible just to get it over and done with. But paying attention and striving to understand the papers you are reading can save you the hours you can’t get back, chasing the wrong line of research. As the saying goes, “a stitch in time saves nine”.


Edwards, S. R., Bradshaw, K. A., & Hinsz, V. B. (2014). Denying Rape but Endorsing Forceful Intercourse: Exploring Differences Among Responders.Violence and Gender, 1(4), 188-193. (http://online.liebertpub.com/doi/abs/10.1089/vio.2014.0022)

Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world?. Behavioral and brain sciences, 33(2-3), 61-83.

Trapped Thoughts: Consciousness In A Vegetative State

In the final year of my undergraduate degree in psychology, I came across Owen et al’s (2006) article, “Detecting awareness in a vegetative state”. This research sparked my interest and had a hugely inspiring effect on my academic direction; it was certainly a contributing factor to my pursuit of a career in neuroscience.

This case study involves a 23-year-old woman who suffered from severe traumatic brain injury, who received the clinical diagnosis of a vegetative state. The researchers conducted a fMRI study to investigate the patient’s neural responses to spoken sentences. Activation was observed in the middle and superior temporal gyri. However, due to the nature of the experiment, these results could not decisively determine awareness in the patient, as studies have previously shown that such aspects of human cognition can occur even in an unconscious state.

A second fMRI study was conducted in order to assess consciousness in the patient. She was given spoken instructions for two mental imagery tasks: to imagine playing tennis and to imagine walking around her home. During the tennis task, her supplementary motor cortex showed significant activation while her parahippompal gyrus, the posterior parietal cortex and the lateral premotor cortex were activated during the spatial navigation task. These responses were concurrent with those of the control group. Not only did this study demonstrate that the patient understood the spoken instructions and could follow them, it also implied that she intended to engage in this activities. This was a compelling finding, as it holds implications for the criteria of clinical diagnosis of a vegetative state and the question of possible communication with vegetative and minimally conscious patients.

Research into the investigation of consciousness in vegetative states has continued, which can be seen from the results of Chennu et al.’s (2014) article just a few months ago. This study used EEG and a branch of mathematics called “graph theory” to investigate activity in the brain of 32 vegetative and minimally conscious patients in comparison to healthy controls. This research revealed that there are networks in the brain of healthy controls and some vegetative patients that support awareness. The patients that such networks were observed in had shown neural activity during neuroimaging tasks, such as imagining to play tennis. These results once again demonstrate the need to re-evaluate the method of diagnosis for vegetative state and provides a technique that is less expensive and more easily administered than fMRI.

I was reminded of these articles and the importance of research in this area today when this story appeared on my Twitter feed: http://www.npr.org/blogs/health/2015/01/09/376084137/trapped-in-his-body-for-12-years-a-man-breaks-free?utm_campaign=storyshare&utm_source=twitter.com&utm_medium=social. It is often forgotten that clinical subjects in science are people who have or who had lives, families, friends, hopes and ambitions. This heartrending piece presents a more human, less analytical reason for such research to be funded and conducted. We should be striving towards making cases such as Martin a myth, not reality.


Owen, A. M., Coleman, M. R., Boly, M., Davis, M. H., Laureys, S., & Pickard, J. D. (2006). Detecting awareness in the vegetative state. Science, 313(5792), 1402-1402.

Chennu, S., Finoia, P., Kamau, E., Allanson, J., Williams, G. B., Monti, M. M., … & Bekinschtein, T. A. (2014). Spectral signatures of reorganised brain networks in disorders of consciousness. PLoS computational biology, 10(10), e1003887.

The excuse of pathology: ethical considerations for the investigation of psychopathology and other disorders.

Neuroimaging techniques continue to become more advanced, and thus allow us to derive more information about the brain. This has permitted an opening into research on psychopathology, which has taken the media’s interest (http://www.bbc.co.uk/news/health-15386740). However, researchers have also been investigating possible underlying pathologies for pedophilia and psychiatric disorders (Schiffer, Peschel, Gizewski, Forsting, Leygraf, Schedlowski & Krueger, 2007; Andreason, 1988). Putting aside the scientific issues with such claims, this article will attempt to put forward two pressing ethical issues with the discovery of such pathologies, and how such questions might be answered. The two issues raised here will be confidentiality and responsibility.

First, the issue of confidentiality will be looked at from the hypothetical standpoint that such pathologies may have demonstrated both validity and scientific rigor. Given that approximately 10% of neuroimaging studies discover incidental findings (IFs) such as tumours, it is likely that IFs would increase in prevalence when associated with these kinds of pathologies (The Royal College of Radiologists, 2011). This issue then becomes two-fold: should researchers allow the individuals to know about their abnormalities, and should they inform authorities of the potential risk of such individuals? Informing individuals will be discussed in more detail below (Fuchs, 2006). Informing authorities breaches the confidentiality of the participant. This becomes a debate between the public’s right to safety and the individual’s right to freedom. Taking pedophilia as an example,the issue of confidentiality is minimal with convicted pedophiles, due to the various equivalents of Megan’s law (Canli & Amin, 2002). But should a non-criminal with this pathology be treated as those convicted; should they be forced to register or inform their employers? This issue needs to be addressed by the scientific community at large (Glannon, 2006). There should be a consensus determining the significance of such scans, and guidelines pertaining to each population at risk implemented.

In terms of the issue of responsibility, two problems may arise here: informing a participant of their pathology before they’ve exhibited at-risk behaviour, and the discovery of such pathologies after they committed a crime. Informing the participants may lead to self-fulfilling prophecies and diminished responsibilities, increasing the likelihood of such behaviour (Glannon, 2006). Hand-in-hand with this, the discovery of pathologies after a crime has been committed may take away the individual’s responsibility. We don’t blame Phineas Gage’s bad behaviour on himself, but rather on the injury caused to his brain, so how can we blame a person with a neurological disposition to such behaviour for acting as such (Farah, 2006)? A proposed answer for the former solution is directing such individuals towards treatments or therapies that can help them overcome such pre-dispositions. The latter could be dealt with by treatment in a high-security mental health facility rather than imprisonment. Although the underlying pathology may not be subject to change, the tendency towards such dangerous behaviours could be inhibited through treatment.

The ethical issues surrounding the discovery of these kinds of pathologies in the brain are complex, and no single answer appears to be the right fit. However, in the words of neuroscientist, Joseph LeDoux (2003): “It is testimony to the progress being made that these questions need to be asked” (p.221).


Andreasen, N. C. (1988). Brain imaging: applications in psychiatry. Science,239(4846), 1381-1388.

Canli, T., & Amin, Z. (2002). Neuroimaging of emotion and personality: Scientific evidence and ethical considerations. Brain and cognition50(3), 414-431.

Farah, M. J. (2005). Neuroethics: the practical and the philosophical. Trends in cognitive sciences, 9(1), 34-40.

Fuchs, T. (2006). Ethical issues in neuroscience. Current opinion in Psychiatry,19(6), 600- 607.

Glannon, W. (2006). Neuroethics. Bioethics20(1), 37-52.

LeDoux, J. E. (2003). Synaptic self: How our brains become who we are (p.221). Penguin.

Schiffer, B., Peschel, T., Paul, T., Gizewski, E., Forsting, M., Leygraf, N., Schedlowski, M., & Krueger, T. H. (2007). Structural brain abnormalities in the frontostriatal systemand cerebellum in pedophilia. Journal of psychiatric research41(9), 753-762.

The Royal College of Radiologists. (2011). Management of incidental findings detected during research imaging. London: The Royal College of Radiologists.