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Is it possible to control the game straight from human nerves?

This is from a creative essay I wrote for a Neuroscience Seminar 6 years ago. It talks broadly about the possibility of mind control technologies. The short answer is theoretically, yes. But the technology is not good enough at this stage.The final frontiers in neuroscience – technologies of the mindNeuroscientists have always been fascinated by how our brains function so intricately to give rise to the experience of the world we take for granted. As understanding of these processes deepen, further questions arise as to how our knowledge of the mind can be applied to serve our everyday needs. This review will introduce medical and other technologies under development based on neuroscientific advances, such as mind controlled-wheelchair and prosthetic limbs, biofeedback as a therapeutic strategy to treat epilepsy or ADHD, as well as possible mind reading or manipulation devices.Disabling disabilityDisabilities relating to loss of control of movement of limbs commonly results from spinal cord injury, motor neuron disease or muscle wasting diseases, like Duchenne’s muscular dystrophy. These conditions usually involve some degree of immobility, and in more severe cases, complete paralysis of both upper and lower limbs. This loss of motor control drastically affects the ability of the patient to be self-sufficient, and they often require long-term, fulltime carer guidance and support. The ultimate goal for neuroscientists is attempting to restore some self-sufficiency to these patients, and this involves improvements to current technologies designed to assist with transporting the patient, enabling the patient to communicate more effectively with the external world, and further down the track to introduce prosthetic limbs that are able to be controlled by thought alone.In spinal cord injury, lower motor neurons are affected at segments pertaining the origin of injury, giving rise to flaccid paralysis, but upper motor neurons from the descending corticospinal tracts are also commonly affected, leading to spastic paralysis below the level of the lesion (McDonald and Sakowsky, 2002). Presently, the prognosis for complete spinal cord injury is quite poor, based on the extent of damage and the low intrinsic ability of central neurons to undergo repair or regenerate after acute damage, rendering both paraplegics and quadriplegics largely confined to wheelchairs for mobility. Electric powered wheelchairs have been developed in an attempt to allow efficient transport, both indoors and outdoors, of patients who lack sufficient upper limb control to operate an arm-controlled wheelchair (as with quadriplegics), or of patients who are less mobile, such as the elderly. These wheelchairs are fitted with controls which require minimal limb movements to operate, such as through joysticks, ball-mouse, keyboard, voice sensors or head tilting. A large majority of electric powered wheelchair users testify increased autonomy, social interaction as well as reduced dependency on carers (Frank et al., 2000). Thus there is an overall increase in quality of life which extends beyond health benefits (Davies et al., 2003). However, many users also complain that it is difficult to manoeuvre the chair indoors, due to the sheer bulkiness of the chair in relation to the confined indoor space, and that outdoor conditions may not be ideal for navigating a wheelchair, such as movement over bumpy or cracked pavements and roads. In addition, there are various safety concerns with collisions of the wheelchair with objects or people, as well as occasional mishaps, such as the chair tipping over (Evans et al., 2007). This has led to the design of sensors that can be installed on the chairs, which are able to detect incoming collisions using infrared, ultraviolet or laser detection strategies (Ishida and Miyamoto, 2013). Furthermore, these chairs are able to respond by slowing down in close proximity to surrounding objects with high accuracy (LoPresti et al., 2011).Although electric powered wheelchairs demonstrate the capacity to enhance mobility of patients who have paralysis or loss of motor function, these devices still require some motor function to operate, such as movement of a joystick, or turning of the head. Therefore, patients with severe motor impairment are likely to encounter difficulties operating the chair using its basic controls. For neuroscientists, the answer is a no brainer – bypass motor neurons! The basic principle behind all of our neurological functions is that neurons are able to receive information about environmental stimuli, transmit that information to other neurons, process that information and deliver an appropriate response via efferents that innervate target organs, or skeletal muscle in the case of voluntary movement. The idea is to use the same efferents involved in motor responses, but redirect these towards the control of wheelchair function in place of limbs, which may later extend to use in prosthetics. Technologies that enable communication to the external world via non-muscular routes are collectively termed brain-computer interfaces (BCIs). The primary function of any BCI is to convert brain derived electrophysiological signals into a desirable output that bypasses nerves and muscles (Wolpaw et al., 2002). These signals are best received through high temporal resolution monitoring of neural activity such as through electroencephalogram (EEG). The EEG may involve laying multiple electrodes on the scalp, which constitutes a non-invasive measure, or sometimes intracortically. Although intracortical methods produce less noise and provide substantially higher resolution compared to EEG obtained using surface electrodes, it is a highly invasive procedure and generally reserved as a last resort. The EEG conveys mass electrical activity of the brain to via an amplifier to an external device, which translates this activity into a desirable output, delivering feedback to allow self-regulation of the EEG signal through training (Schwartz et al., 2006). For instance, feedback such as the presentation of a visual stimulus moving towards, or away from a target can be used to allow the user to modulate their EEG output as required. This allows a binary ‘yes’/’no’ response, in which the user can select a target on computer screen to indicate a choice (McFarland et al., 2003).More precise selection can be granted with a P300 system based on event related potentials (ERPs) which are generated in response to highly salient or infrequent visual, auditory or somatosensory stimuli against non-salient, or common background cues. In this paradigm, the user is presented with a 6 x 6 matrix with letters on a screen and is required to focus on the number of times a particular letter flashes on a screen, which leads to the generation of a P300 ERP linked to the targeted stimulus (Donchin et al., 2000; Kubler and Neumann, 2005).One of the more obvious uses of this technology would be to enable written communication for patients with locked in syndrome, where motor and verbal responses are both impaired, leaving them largely unable to communicate with the outside world, although they are fully conscious. This system can be used reliably to spell words through letter selection with a minimal accuracy of 60%, although the selection rate is very slow, enabling selection of roughly five letters per minute. The selection rate can be increased, although this tends to correlate with an increased rate of errors. Further studies should aim to increase selection rate with a reasonable control of error rate. One of the advantages of using P300 BCI is that it does not require training since the ERP is naturally evoked to the desired choice (Wolpaw et al., 2002). Although there were initial concerns that the P300 may change over time, results were shown to be consistent across a period of several months (Nijboer et al., 2008), providing hope that this technology may enable patients with locked in syndrome to effectively communicate with the external world.In one study, Cincotti et al. (2008) demonstrated the feasibility of controlling an electronically driven assistive device using BCI. The trial involved both healthy able-bodied subjects and patients with severe neuromuscular impairment, such as Duchenne’s muscular dystrophy. After training, users were able to modulate their brain activity to control a cursor on a screen, and later a prototype robotic device. Patients indicated that they felt the device enabled them to act independently of a caregiver. This would be highly useful in both a clinical setting (hospital or a rehabilitation centre) as well as at home, where the user can operate various devices, such as light switches, television, adjustable beds and electronically activated doors on their own.For patients with degeneration of motor neurons but minimal muscular atrophy, there is the possibility that normal function of limbs could be restored by circumventing the usual pathway taken by motor neurons, allowing artificial control of limbs that are independent motor neurons. At present no experiments have sought to directly connect motor cortices with peripheral muscles, since this is a highly invasive procedure, and safety and efficacy has not been established. However, studies have started to use BCIs to control prosthetic limbs and this may serve a strong starting platform for research into this area.Hochberg et al. (2006) successfully demonstrated the feasibility of BCI for a quadriplegic patient to operate a cursor on a computer screen, and then open and close a prosthetic limb via a microelectrode array implant into the motor cortex. Importantly, they discovered that intended motor signals generated were intact in the motor cortex even three years post-injury, and therefore could be harnessed through a non-muscular route. Further studies into neural controlled prosthetics showed that monkeys are able to modulate motor cortical activity to operate a prosthetic limb for self feeding, with multiple degrees of freedom involved compared to the simpler one dimensional movement of cursors (Velliste et al., 2008). The results of the study have led to testing in humans, and have demonstrated positive results. Subjects had little direct training but were able to successfully perform reaching and grasping movements, with one subject able to drink out of a coffee mug (Hochberg et al., 2012). There are obvious limitations in using prosthetics, such as lack of fine control and accuracy, as well as the slowness, fragmentation and rigidity of movements, compared to healthy able bodied subjects. Nevertheless these technologies provide tetraplegics and patients with insufficient upper limb control otherwise inaccessible interactions with the outside world using only their thoughts.Biofeedback, ADHD and video gamesBiofeedback refers to a tuneable, conscious adjustment of internal physiological activity, such as heart rate, respiration rate and blood pressure. Similar to the training regimen employed using BCI, biofeedback involves transmitting real time physiological information to the user, allowing them to alter their physiological activity, often through relaxation techniques. The clinical applications of biofeedback are numerous. Studies have shown the effectiveness of biofeedback in controlling sympathetic output, a key component in chronic stress, as well as various diseases relating to the cardiovascular system, such as chronic heart failure (McKee and Moravec, 2010). Biofeedback can be used here to reduce sympathetic activation, while boosting parasympathetic activity, which leads to improved clinical outcomes and possibly reduced morbidity and mortality. However, there appear to be limitations to biofeedback in controlling certain physiological conditions. While many studies have focused on the control of hypertension via biofeedback, meta-analyses consistently find little to no significant improvements blood pressure regulation in biofeedback subjects (Greenhalgh et al., 2010; Nakao et al., 2003). This indicates that amidst much hype about simple non-pharmacological treatment strategies, biofeedback must be carefully investigated and compared against pharmacological measures in terms of efficacy.One of the more successful applications of biofeedback has been in the control of epileptic seizures, on the basis that learned behavioural inhibition correlates strongly with a 12 -15 Hz EEG pattern in the sensorimotor cortex (Sterman, 2010), and has been appropriately labelled as the ‘sensorimotor rhythm’ (SMR). Conversely, a slower EEG rhythm of 8-12 Hz is correlated with an increased frequency of seizure activity. Upregulation of the SMR and downregulation of the slower rhythm could have clinical benefits for epileptics, especially for those who do not respond well to anti-epileptics. The general protocol for EEG training involves an operational conditioning paradigm, which would reward subjects for successfully controlling their EEG rhythms conducive to seizure reduction. This could be contingent or non-contingent, in which the subject would see a false EEG reading not correlative with their actual EEG. A meta-analysis which examined 10 studies on EEG biofeedback on seizure events found a significant effect of biofeedback on attenuating duration and frequency of seizure events not accounted for by medication or placebo (non-contingent) controls (Tan et al., 2009). Thus, biofeedback could be an effective treatment especially for epileptics who do not respond well to medication.Biofeedback can also be a useful tool to train attention deficit hyperactivity disorder (ADHD) patients to control their own brain wave activity, and hence control their attention. Patients with ADHD generally show symptoms of hyperactivity, impulsivity and inattention. This can have major disruptive consequences in their relationships with others, aptitude for learning, motivation to complete tasks. Pharmacological treatments involving psychostimulants such as methylphenidate or amphetamine (Antshel et al., 2011) have been considered of choice and have demonstrated efficacy in treating ADHD, although they are not without adverse effects, which can lead to anxiety, suppression of appetite and sleep disturbances (Sonuga-Barke et al., 2009). A meta-analysis (Arns et al., 2009) comparing across 15 different studies on the effect of neurofeedback on ADHD found the treatment to demonstrate strong efficacy and specificity, with a large effect size for measures of inattention and impulsivity, and a medium effect size for hyperactivity. The results establish the clinical significance of using biofeedback to manage ADHD, although there are still recommendations against ceasing medication.A step forward from biofeedback is the introducing of BCI to video gaming. Many ADHD patients turn to video games, and unsurprisingly, this would have certain benefits based on the level of attention required to interact with the game. BCI video gaming adds an extra dimension of personalised control to the game by adapting based on the user’s mental states (Nijholt et al., 2009). For instance, the game may involve the control of a racing car, where speed, ease of control or manoeuvrability is determined by the generation of brain waves linked to arousal and alertness. A lack of concentration leads to poorer performance in the game. Thus performance is predicated by the user’s modulation of brain waves to produce a specific outcome. Some companies like Playstation and Nintendo have taken this on board, with certain types of games, especially mobile role playing platform games, racing or sporting games, fitted with EEG based feedback devices that link with the joypad or controller. Others are investigating joypad independent (non-motor) systems where EEG activity is directly linked to an outcome on a screen (Lecuyer et al., 2008). The applications of such technologies are endless, and span beyond medical uses. For instance, it can be used to update standard hazard training and simulation for pilots, soldiers and surgeons to provide feedback about alertness and situational awareness. Studies show similar virtual reality training can be used as a means of exposure therapy for common phobias like arachnophobia (Hoffman et al., 2003), social phobia (Parsons and Rizzo, 2007) or PTSD (Goncalves et al., 2012), in which BCI could complement the user’s experience and control of the virtual scenario encountered. It could also be applied to research into how attention and consciousness works. But of course, it could be the realisation of quasi-3D virtual reality video gaming systems, marking a new era of video gaming.A Brave New World1. Do you see what I see?The concept of mind reading has been around for a long time, and it is not simply a trick of the trade that magicians employ. The most primitive measures attempted to shake the truth out with polygraph lie detectors, which is considered too unreliable to be admissible in court (Iacono and Lykken, 1997). Our latest advances in mind reading come in the form of fMRI – functioning magnetic resonance imaging, an imaging technology that highlights specific areas correlating to brain activity in close to real time. fMRI has confirmed consciousness of patients with locked-in syndrome (Owen et al., 2006) and may offer a crude means of communication similar to the ‘Yes’/’No’ paradigm discussed earlier. Neuroscientists are taking fMRI to the next level in an attempt to deconstruct a person’s thoughts.Kay et al. (2008) have attempted to decode cortical representations of visual images and use these as prototypes for classifying other images of a similar category. For example, an image of a particular shoe would evoke certain voxel activity, which could then be used as a reference for identifying other shoes. This was taken further to identify with over 85% accuracy certain mental states involved in everyday tasks, such as mental arithmetic, singing a tune silently, recalling recent events or relaxing (Shirer et al., 2012). The fear of having your mind read from a non-divine entity can be allayed for now given the crude, low resolution readings obtained and the difficulty of abstracting information from sources beyond those referenced. However, authors have suggested that it could be a useful tool for diagnostics or study into Alzheimer’s disease or schizophrenia.2. Mind controlIf mind reading sounded scary, then they might alleviate you of your fear by changing the way you think. The popular PC Command and Conquer series, Red Alert featured some Russian psionic commanders who were able to control an American crew member operating a nuclear silo to detonate the bomb in base. In the original Star Wars, Obi-wan Kenobi uses a ‘jedi mind trick’ to bypass a storm trooper interrogation. Avid Doctor Who fans tremble when the word ‘Cyberman’ is brought up – where a simple ear piece can force you to live against your own will. Believe it or not, there exists such technology even in its simplest stages of development – transcranial magnetic stimulation (TMS). TMS involves the generation of magnetic fields that can excite or inhibit certain cortical neurons depending on the area stimulated, which has been shown to alter perception (Taylor et al., 2010) and evoke limb movements (Barker et al., 1985). A recent report (BBC News, 2013) commented on experimental ‘telepathy’ conducted by two psychologists, Rajesh Rao and Andrea Stocco, based in Washington University, where it was possible for one of them to move the finger of the other subject using a combined EEG input-TMS output interface. On the subject of mind control, the research assistant, Prat reassures, “There's no possible way the technology that we have could be used on a person unknowingly or without their willing participation.” That’s believable. It has been reported that leaked documents from DARPA confirm investigation into mind control technologies with TMS to disrupt or even change certain thought patterns, political ideologies or behaviours, and in the fullest extent to coerce people into acting against their will with minimal resistance (Activist Post, 2013)!ConclusionRene Descartes once said, ‘Cogito ergo sum’ i.e. ‘I think, therefore I am’, a statement of our identity linked so strongly with our capacity to think. It is an amazing feat for anyone to comprehend their own thoughts. Whoever imagined the mind should be given due credit. We do have marvellous and complex minds to think, reason and interact with the world. Neuroscientists are only just skimming the surface of how our minds work and the technologies using mind power to control wheelchairs, prosthetic limbs, and therapeutic video games will revolutionise medicine. At the same time, the future is a brave new world, one full of uncertainty as to how these technologies could be used to benefit many, or perhaps abused in the wrong hands.ReferencesActivist Post (2013). Secret DARPA mind control project revealed: leaked document. Available at DARPA Mind Control Secret Program Leaked (accessed 26 October 2013).Antshel KM, Hargrave TM, Simonescu M, Kaul P, Hendricks K, Faraone SV (2011). Advances in understanding and treating ADHD. BMC Med 9: 72.Arns M, de Ridder S, Strehl U, Breteler M, Coenen A (2009). Efficacy of neurofeedback treatment in ADHD: the effects on inattention, impulsivity and hyperactivity: a meta-analysis. Clin EEG Neurosci 40(3): 180-189.Barker AT, Jalinous R, Freeston IL (1985). Non-invasive magnetic stimulation of human motor cortex. Lancet 1(8437): 1106-1107.Cincotti F, Mattia D, Aloise F, Bufalari S, Schalk G, Oriolo G, et al. (2008). Non-invasive brain-computer interface system: towards its application as assistive technology. Brain Res Bull 75(6): 796-803.Davies A, De Souza LH, Frank AO (2003). Changes in the quality of life in severely disabled people following provision of powered indoor/outdoor chairs. Disabil Rehabil 25(6): 286-290.Donchin E, Spencer KM, Wijesinghe R (2000). The mental prosthesis: assessing the speed of a P300-based brain-computer interface. IEEE Trans Rehabil Eng 8(2): 174-179.Evans S, Frank AO, Neophytou C, de Souza L (2007). Older adults' use of, and satisfaction with, electric powered indoor/outdoor wheelchairs. Age Ageing 36(4): 431-435.Frank AO, Ward J, Orwell NJ, McCullagh C, Belcher M (2000). Introduction of a new NHS electric-powered indoor/outdoor chair (EPIOC) service: benefits, risks and implications for prescribers. Clin Rehabil 14(6): 665-673.Goncalves R, Pedrozo AL, Coutinho ES, Figueira I, Ventura P (2012). Efficacy of virtual reality exposure therapy in the treatment of PTSD: a systematic review. PLoS One 7(12): e48469.Greenhalgh J, Dickson R, Dundar Y (2010). Biofeedback for hypertension: a systematic review. J Hypertens 28(4): 644-652.Hochberg LR, Bacher D, Jarosiewicz B, Masse NY, Simeral JD, Vogel J, et al. (2012). Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature 485(7398): 372-375.Hochberg LR, Serruya MD, Friehs GM, Mukand JA, Saleh M, Caplan AH, et al. (2006). Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 442(7099): 164-171.Hoffman HG, Garcia-Palacios A, Carlin A, Furness Iii TA, Botella-Arbona C (2003). Interfaces that heal: coupling real and virtual objects to treat spider phobia. International Journal of Human-Computer Interaction 16(2): 283-300.Iacono WG, Lykken DT (1997). The validity of the lie detector: Two surveys of scientific opinion. Journal of Applied Psychology 82(3): 426.Ishida S, Miyamoto H (2013). Collision-Detecting Device for Omnidirectional Electric Wheelchair. ISRN Robotics 2013: 8.Kay KN, Naselaris T, Prenger RJ, Gallant JL (2008). Identifying natural images from human brain activity. Nature 452(7185): 352-355.Kubler A, Neumann N (2005). Brain-computer interfaces--the key for the conscious brain locked into a paralyzed body. Prog Brain Res 150: 513-525.Lécuyer A, Lotte F, Reilly RB, Leeb R, Hirose M, Slater M (2008). Brain-computer interfaces, virtual reality, and videogames. Computer 41(10): 66-72.Lopresti EF, Sharma V, Simpson RC, Mostowy LC (2011). Performance testing of collision-avoidance system for power wheelchairs. J Rehabil Res Dev 48(5): 529-544.McDonald JW, Sadowsky C (2002). Spinal-cord injury. Lancet 359(9304): 417-425.McFarland DJ, Sarnacki WA, Wolpaw JR (2003). Brain-computer interface (BCI) operation: optimizing information transfer rates. Biol Psychol 63(3): 237-251.McKee MG, Moravec CS (2010). Biofeedback in the treatment of heart failure. Cleve Clin J Med 77 Suppl 3: S56-59.Nakao M, Yano E, Nomura S, Kuboki T (2003). Blood pressure-lowering effects of biofeedback treatment in hypertension: a meta-analysis of randomized controlled trials. Hypertens Res 26(1): 37-46.Nijboer F, Sellers EW, Mellinger J, Jordan MA, Matuz T, Furdea A, et al. (2008). A P300-based brain-computer interface for people with amyotrophic lateral sclerosis. Clin Neurophysiol 119(8): 1909-1916.Nijholt A, Reuderink B, Oude Bos D (2009). Turning Shortcomings into Challenges: Brain-Computer Interfaces for Games. In: Nijholt A, Reidsma D, Hondorp H (ed)^(eds). Intelligent Technologies for Interactive Entertainment, edn, Vol. 9: Springer Berlin Heidelberg. p^pp 153-168.Owen AM, Coleman MR, Boly M, Davis MH, Laureys S, Pickard JD (2006). Detecting awareness in the vegetative state. Science 313(5792): 1402.Parsons TD, Rizzo AA (2008). Affective outcomes of virtual reality exposure therapy for anxiety and specific phobias: a meta-analysis. J Behav Ther Exp Psychiatry 39(3): 250-261.Schwartz AB, Cui XT, Weber DJ, Moran DW (2006). Brain-controlled interfaces: movement restoration with neural prosthetics. Neuron 52(1): 205-220.Shirer WR, Ryali S, Rykhlevskaia E, Menon V, Greicius MD (2012). Decoding subject-driven cognitive states with whole-brain connectivity patterns. Cereb Cortex 22(1): 158-165.Sonuga-Barke EJ, Coghill D, Wigal T, DeBacker M, Swanson J (2009). Adverse reactions to methylphenidate treatment for attention-deficit/hyperactivity disorder: structure and associations with clinical characteristics and symptom control. J Child Adolesc Psychopharmacol 19(6): 683-690.Sterman MB (2010). Biofeedback in the treatment of epilepsy. Cleve Clin J Med 77 Suppl 3: S60-67.Tan G, Thornby J, Hammond DC, Strehl U, Canady B, Arnemann K, et al. (2009). Meta-analysis of EEG biofeedback in treating epilepsy. Clin EEG Neurosci 40(3): 173-179.Taylor PC, Walsh V, Eimer M (2010). The neural signature of phosphene perception. Hum Brain Mapp 31(9): 1408-1417.Velliste M, Perel S, Spalding MC, Whitford AS, Schwartz AB (2008). Cortical control of a prosthetic arm for self-feeding. Nature 453(7198): 1098-1101.Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan TM (2002). Brain-computer interfaces for communication and control. Clin Neurophysiol 113(6): 767-791.

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