Electroencephalography for Autism and Epileptic

Autism Management using EEG

Approximately 1% of children across the globe have autism. Nevertheless, the diagnosis of autism spectrum conditions is still in the dark times since it remains a perplexing and biased practice where physicians convey their judgment following observation of the behaviors of a child and evaluating past signs and symptoms. The symptoms of autism spectrum conditions fluctuate noticeably from one individual to another, varying from mild communication and social challenges to intense cognitive problems (Catarino et al. 2375-2380). Amid the difficulties in autism is that there is no simple and perfect method of categorizing patients into groups or what such groupings could constitute. However, researchers have established and are refining novel and objective methods of diagnosing autism, the electroencephalographic (EEG) methodologies. Determining through EEG methodologies how rapidly the mind reacts to sounds and sights could be the explanation for a perfect and clear-cut recognition of autism.

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The EEG methodologies are anchored in scientific understanding of the way human brains classify the received information (Catarino et al. 2375-2380). When a person listens to another, he/she collects input concerning what they are saying not just from perceiving their words but as well watching their facial expression. In the meantime, a given section of the brain is acting on the auditory message while another section is working on the visual information. To add up what has been stated, the two dissimilar brain sections have to communicate with one another. Via earlier studies, researchers have found that the communication involving the brain sections is in some way impaired, or merely less efficient, amid children with autism when judged against normally developing children. This was established while researchers were employing an electroencephalogram (EEG) to determine the brainwaves of a number of children. Evaluating the recordings of every child, they found out the way children with autism worked on the sensory message (touch, visual, and audio) less quickly when compared to their normally developing counterparts.

Many neuroimaging pieces of research have illustrated brain abnormalities in autistics when judged against healthy controls. The electroencephalogram has been crucial in the management of autism, for instance, attributable to its capacity to examine the neurobiology of autism. The identification of an elevated occurrence of electroencephalographic anomalies and seizure disorders in people with autism indicates a biological foundation for the disorder (Ingudomnukul et al. 597-604). Additionally, the electroencephalographic methodologies are premier instruments in the evaluation of neural dysfunctions associated with autism and seizures because of their noninvasive quality, accessibility, and usefulness in detailing such forms of problems. In the electroencephalographic methodologies, spikes could denote causal morphological brain anomalies or metabolic disorders thus ensuring that they are addressed in a timely manner.

Brainwave electroencephalographic recordings could possibly express the manner in which people with severe cases of autism are affected (Golan et al. 1096-1106). Furthermore, such recordings could assist in the early diagnosis of autism spectrum disorder. Early diagnosis enables opportune treatment, which plays a key role in ensuring the possibility of better results. Being novel and objective, EEG methodologies are vital for the identification of autism at an early stage thus leading to better treatment and ultimately offering great optimism of an industrious existence. Nevertheless, only less than fifteen percent of autistic children are currently diagnosed before attaining four years of age. There is a great need to adapt this technology extensively to enable early autism identification, therapy, and management of a higher proportion of children.

Overview of Autism Spectrum Conditions

There is a significant overlie amid the dissimilar kinds of autism. The broad scope of symptoms amongst autistic children, nevertheless, has created the concept of autism spectrum conditions. The word spectrum denotes the broad scope of symptoms, proficiencies, and rates of impact or disability that autistic children could demonstrate. Some autistic individuals show minor signs while others are critically affected. Though autism spectrum conditions seem to be highly increasing, it is not clear whether the rising number of diagnoses expresses an actual augment or emanates from enhanced recognition (Roelfsema et al. 734-739). Early identification of autism is crucial as it plays a vital role in assisting autistic children to make noteworthy gains in social and language proficiencies. At times, the growth of children is retarded from delivery. However, some children appear to grow typically prior to abruptly losing communication or social proficiencies. Other children express normal development till they have adequate language to illustrate abnormal interests and ideas.

Autism spectrum disorder (ASD), also referred to as autism, denotes an array of intricate neurodevelopment disorders typified by social problems, communication challenges, and constrained, recurring, and stereotyped forms of conduct (Ruta et al. 1154-1163). The autism spectrum depicts a scope of conditions categorized as neurodevelopmental disorders. Such conditions along the spectrum encompass a mild kind of Asperger disorder, pervasive developmental disorder-not otherwise specified (PDD-NOS), and pervasive developmental disorders encompassing Autism and childhood disintegrative disorder. There is a range of numerous illnesses that are similar to autistic disorder, for instance, epileptic attacks, mental retardation, sensory integration difficulties, and seizure disorders. On this note, comorbidity expresses the impact of other illnesses that a patient could suffer apart from the primary ailment of concern, which is autism in this case.

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Diagnosis Background of Autism Spectrum

The diagnosis of autism spectrum does not occur through a single test but normally entails a scope of examinations and evaluations, which often engages numerous professionals. Through tests and the involvement of specialists, a perfect diagnosis and suitable treatment arrangement for autism spectrum disorder are realized (Clare and Woodbury-Smith 109-134). Diagnosis is anchored in observing the manner in which children play and interrelate with others (present development), engaging parents in interviews, and analyzing the developmental account of the children (past development). Through the application of numerous tools, health professionals establish the position in the spectrum that the children fall. While diagnosing the autism spectrum, specialists such as psychologists and psychiatrists make reference to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). DSM-5 assists in grouping the signs and symptoms of autism spectrum disorder. Diagnosis assists in ascertaining the subdivision that fits the patient, for instance, autistic disorder, Asperger syndrome, and PDD-NOS. The diagnosis of autism spectrum establishes a severity ranking, level 1 to 3, depending on the intensity of support that the patient requires.

Currently, professionals diagnose ASD based on problems in two areas, and a child must have challenges in both to be diagnosed with the autism spectrum disorder (Golan, Baron-Cohen, and Golan 1534-1541). This method substitutes the preceding technique that was based on three areas: repetitious and limited conducts and concentrations, social interrelation, and language and communication. Communication and social difficulties have been combined into one area called deficits in social communication. Problems in this area seldom encompass making use of language to communicate with others, not talking by any means, not reacting when talked to, or not imitating the actions of others, for instance, clapping. The other area is the fixed concerns and repetitious conducts, for instance, arranging toys in a given manner repetitively or showing narrow and extreme involvements.

Neurocognitive Theories

The mind-blindness theory affirms that children with ASD have hindered the development of the theory of mind (ToM), the capacity to assume being in another individual’s shoes, and envisaging of deliberations and opinions. The mind-blindness theory implies that individuals that have an autistic disorder or Asperger disorder have hindered the advancement of their theory of mind, making them have a measure of mind-blindness. Consequently, they view the conduct of others as puzzling and impulsive, even dreadful (Auyeung et al. 1509-1521). Proof for this hails from the challenges they demonstrate at every position on the progress of the capability to mind construe. Autistic children and children with Asperger’s disorder demonstrate a decreased rate of joint interest in toddlerhood. For instance, the typical 2-year-old baby is involved in pretend play while utilizing their mind-construing proficiencies to comprehend that in the other individual’s mind, they are only feigning. On the contrary, autistic children and children with Asperger’s disorder express minimal pretend play or their make-believe is restricted to more rule-anchored plans.

While a typical 9-year-old can construe a different individual’s manifestations from their eyes, to discover what they could be considering or feeling, children that have Asperger disorder perceive such tryouts far more intricate and similarly when the adult assessment of interpreting the mind in the eyes is employed (Wakabayashi et al. 1823-1832). Autistic grownups and those with Asperger disorder score less than the typical ones on the assessment of enhanced mind construing. The mind-blindness theory has been proved triumphant in explaining the communication and social challenges that typify such circumstances but cannot clarify the non-social aspects (the narrow concerns, requirement for similarity, and concentration to detail). On the other hand, the empathizing-systemizing (E-S) theory affirms that two aspects are required to elucidate non-social and social facets of the autism spectrum conditions. The E-S theory is linked to other neurocognitive hypotheses, for instance, the weak central coherence theory (WCC) and male brain theory.

The E-S theory elucidates the communication and social challenges in people with Asperger disorder and autism by orientation to delays and deficits in empathy, while clarifying the points of strength by consultation to integral or even advanced proficiency in systemizing. Therefore, it is the difference between E and S that establishes whether an individual is probable of developing autism (Happé and Frith 5-25). Similar to the weak central coherence theory, the empathizing-systemizing theory concerns a cognitive approach and conceives superb attention to detail (in insight and remembrance), because when one systemizes he/she has to consider fine details.

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The weak central coherence theory anticipates that individuals with Asperger syndrome or autism will be everlastingly mislaid in the detail and by no means realize comprehension of the system in its entirety (because this would necessitate an international impression). In contrast, the E-S theory expects that, with time, the individual could attain a brilliant comprehension of the entire system, given the chance to examine and manage every variable in the structure. The empathizing-systemizing theory, being a two-aspect theory, seems better fitting to elucidate the entire set of the attributes typifying autism spectrum conditions (von dem Hagen et al. 53). The theory also appears more germane when judged against the executive dysfunction description or WCC theory, which has drawbacks in terms of descriptive or catholicity scale.

Neurophysiological Patterns in Autism Spectrum

Progress in neuropsychology, neurobiology, and brain imaging has enabled fresh perceptiveness into the likely brain foundation of autism (Falkmer et al. 1-23). Different sections of the brain that range from the medial lobe parts and cerebellum to the prefrontal cortex have been established as likely core segments of the anomaly in autism spectrum conditions. Moreover, it is established that dysfunction in a given section of the brain possibly influences the functioning and progress of associated sections of the brain. Indeed, autism spectrum disorders most certainly entail dysfunction of brain circuits that back the operations of different brain sections. Neurophysiological patterns demonstrate that lower-functioning autistic children are affected by a visual identification recall test exploiting medial temporal lobe structures.

Neurophysiological studies have a tendency of evaluating mechanisms as compared to etiology and have embarked on two general directions, one underscoring the interruptions of cognition and language and the second highlighting the disorders of sensory modulation and motion. The disorders of cognition and language imply subcortical dysfunction (Izawa et al. 124-136). Neurophysiological studies concerning cortical patterns are pertinent to the disorders of communication and language in autism. The neurophysiological studies that have centered on cortical mechanisms have encompassed electroencephalographic studies, event-associated potential studies, and radiological studies (encompassing numerous computerized tomography explorations). Though the proof of an unusual pattern of hemispheric lateralization is incoherent, and the basis of any likely abnormal or deficient irregularity might or might not be cortical, abnormal right or left cortical function in autism is a likely explanation of diverse facets of autistic conduct.

Prevalence Rates

From around 1960, there seems to have been a constant rise in the rate of autistic children, which is alleged to be an outcome of enhanced diagnostic techniques, broadening of diagnostic measures, less stigmatization of the conditions, and better enlightenment from medical professionals. The prevalence rates for autism spectrum conditions in the UK have demonstrated a constant increase in the course of the last 40 years (Baron-Cohen, et al. 500-509). The consensus approximation for the prevalence of autism was 4 in 10,000 people in 1978. The current prevalence rate for autism is one percent of the population. There is no record or accurate count, but the data regarding the likely prevalence rates in the UK is anchored in epidemiological investigations. The recent frequency studies of autism spectrum conditions signify that more than 695,000 (1%) individuals in the United Kingdom have autism spectrum conditions. If the family members are to be included, it means that autism affects close to three million individuals daily.

Autism spectrum conditions do not only affect children since they develop to be autistic grownups (Lai et al. 208-215). The prevalence rates are anchored in a couple of reasonably recent kinds of research, one of the autistic children, and the other grownups. The huge rise is probable of reflecting seven aspects, which encompass enhanced identification, modifications in study methodologies, an augment in existing diagnostic services, augmented awareness amid parents and medical specialists, rising acceptance that autism can coexist with a variety of other conditions, and a broadening of the diagnostic criteria. The yearly prevalence of autism was approximated at about 4 per 1,000 males and 1 per 1,000 females, which was steady from 2004 to 2010. There is convincing proof that a great increase in prevalence rates of autistic spectrum conditions cropped up around the 1990s but got to a plateau in the early 2000s and has been steady since then.

Autism is Different Stages of Life

Autism is normally believed to be a condition that occurs only in childhood as public concentration centers mainly on children and the significance of early identification (Bird, Press, and Richardson 1556-1564). Nevertheless, autism spectrum disorders are lifetime conditions, and the accessible, essential assistance, as well as treatment, vary as individuals on the spectrum progress through key stages of life. With the high prevalence rate, there is a need to accommodate the pressing requirements and programs for individuals on the spectrum across the natural life. Similar to everybody else, individuals with autism progress through considerable stages of development in life. Their value of existence relies not just on the aid offered in childhood, but as well on ongoing assistance that is in line with their learning, social, recreational, health, family, and job requirements. Autistic individuals and their family members are mainly supported through three crucial phases of life.

The first stage is the early identification and the start of successful treatments prior to three years of age (Tavassoli and Baron-Cohen 1419-1424). Autistic behaviors could turn evident as early as one and a half years of age, and parents ought to assess once they suspect autistic spectrum conditions or any other developmental problem. Timely recognition of autism disorder could lessen lifelong care outlays by up to 60% since it enables parents, health professionals, and other stakeholders to start treatment early enough. Learning greatly concerning autistic spectrum conditions is significant at this phase.

The second stage entails the creation of a strong foundation from childhood to adolescence (Cook and Bird 1045-1051). Different organizations work to assist parents and health professionals design educational and treatment programs to ensure that every autistic child and adolescent can realize their utmost potential. During this stage of life, it is vital to comprehend the manner in which the school system can assist (for instance, via a personalized learning plan) and the way to prepare for the development of life in adulthood. The school years generate countless difficulties for autistic children though they as well bear incredible opportunities for development. The parents are faced with the challenge of determining and leveraging resources with the purpose of enhancing the children’s possibilities of academic learning, social encounters, and physical well-being. The existence of a team of experts is vital all through this stage since receiving aid from the people that are aware that the system can lessen distress on the family and advance results for autistic children. Apart from numerous educational programs targeting dissimilar needs and capabilities, there are several treatment approaches for school-going autistic children that encompass Applied Behaviour analysis among others.

The third stage entails a life of happiness and dignity. Some autistic individuals mature devoid of their condition being identified, at times through preference (Stewart et al. 6-14). Irrespective of age, it is never overdue to be diagnosed with autism though it is sometimes challenging as some National Health Service authorities do not offer to finance for diagnosing the condition in grownups. With a suitable diagnosis, grownups with autism could have the ability to access available support services. Different organizations currently operate to make sure that all autistic grownups have access to services and assistance that ascertain independence and secure the maximum value of life.


Neurofeedback denotes a greatly promising and novel therapy for autistic spectrum conditions (Wright et al. 175-184). Neurofeedback presents a tool for the direct training of brain function and that has been found triumphant in handling a broad scope of mental medical interests. Similar to the occurrence with different forms of therapy, its use for autism disorders has been made difficult by the inherent complication of the condition. Nevertheless, researchers have reviewed the advancement of neurofeedback for autistic disorders and offered some direction to both parents and physicians in terms of the alternatives open to them. Whilst other behavior disorders for children, for instance, Attention Deficit Hyperactivity Disorder (ADHD), have gone through neurofeedback attention, it may seem that autism spectrum disorder will soon have its time in the sun.

The current studies are demonstrating that children with autism spectrum conditions are reacting in an excellent manner to both the haemoencephalographic (HEG) and electroencephalographic neurofeedback. In addition, recent studies indicate that neurofeedback could be a successful intervention for school-aged children with autistic disorders. Neurofeedback acts as an intervention meant to train people to control the biological operations in their brain effectively (Cook, Blakemore, and Press 2816-2824). This has generally engaged the self-regulation of electroencephalographic rhythmic activity, also known as electroencephalographic biofeedback, Neurotherapy, or neurofeedback. Nevertheless, in the present times, the perception of neurofeedback has expanded to encompass self-regulating of different neural substrates.

Theoretical Background of Neurofeedback

The identification of successful treatment is directly associated with the studies concerning the real reasons behind autism (Barnes and Baron-Cohen 1557-1565). Different studies are yet to establish every likely source fully. Nevertheless, many scientific research works ascertain that autism spectrum conditions mainly have genetic sources. Such genetic mutations could be high-risk aspects for an anomalous advancement of the brain, for instance, through inhibition of the development of significant neuronal linkages or generating insufficient brain wave actions. The abnormal patterns could result in severe shortfalls in neuropsychological operations and capacities, for example, executive operations, the theory of mind, central coherence, intelligence, language, and imitation proficiencies. Children normally begin copying facial expressions, gestures, or activities encompassing objects at an extremely young age. This denotes a considerable precondition for the advancement of the theory of mind, which acts as the capacity to be responsive to and understand internal deliberations and sentiments, as well as the ones of other people. In autistic children, these capacities frequently are developed in a limited manner.

People with autism normally express problems in designing and controlling their conduct or identifying intricate social conditions (Golan, Sinai-Gavrilov, and Baron-Cohen 22). It could be extremely difficult to establish and comprehend feelings, deliberations, or objectives. Several research studies assess the neuropsychological performance of autistic individuals and presented numerous professionals concur that a mirror neuron dysfunction network is amid the major sources of restricted neurocognitive capacities. The network checks identification and perception of fundamental motor activities but is apparently also engaged in more intricate cognitive practices and thus could result in a range of problems. In addition, researchers have identified that some brain sections of individuals with autism are differently aroused in the course of cognitive practice when judged against normally working brains. From time to time, completely dissimilar sections become stimulated for cognitive endeavors, for instance, functional memory or executive tasks. This implies the advancement of indemnified policies in the autistic mind. A different occurrence normally stated in many studies depicts that cerebral operations are not adequately incorporated and thus dissimilar psychological operations cannot be synchronized accurately. This leads to the frequently apparent discrepancies in incorporating, developing, or responding suitably to insights, feelings, or conducts.

It seems practical to study neurofeedback as a kind of intervention that is meant to modify the operations of the mind essentially (Luke et al. 612-621). Through obtaining immediate information regarding the neuronal patterns, people have the chance to learn to control the action of their brain waves anchored in influential training. With time, researchers have come up with numerous neurofeedback training plans that partially vary in their recording and likely guiding techniques. Contrary to numerous other treatment programs, neurofeedback training seeks to transform the person’s brain action essentially, rather than just addressing the signs and symptoms of a condition. Since neurofeedback is a non-invasive practice, the mind cannot become reliant on external influences such as electrical impulses and medicines. Attributable to such explanations, it is possible that neurofeedback can generate lasting impacts, which can stay unrelenting even following the end of the training.

Neurofeedback training programs are totally personalized anchored in the individual’s recorded mind action and the associated symptoms, which is a fundamental necessity particularly regarding treatment methods for autism spectrum conditions. Furthermore, neurofeedback training could be modified at any instance such as in the occurrence of the deterioration of symptoms or similar incidences (Wing, Gould, and Gillberg 768-773). Besides, so far no fallouts from neurofeedback training have been established. Another significant advantage is the option of merging neurofeedback training with different treatment techniques to possibly augment the therapy development.

Neuroplasticity and Neurofeedback

Neurofeedback, also referred to as electroencephalographic biofeedback, denotes an automated treatment technique for the neurobiological disorder that seeks to transform anomalous brain activities (Tavassoli et al. 1778-1780). Neuroplasticity denotes the capacity of the mind to rewire or restructure itself through creating or transforming neural links and varying the operations of dissimilar sections of the brain. On this note, neurofeedback training acts as the use of neuroplasticity by providing brain information regarding its latest conduct. Therefore, neurofeedback enables the brain to utilize its plastic quality to modify the way it operates with the purpose of acting more successfully and ably, even in cases of damage, for instance, brain injury and stroke. In twenty neurofeedback patterns that have response twice in a minute, a person gets 72,000 opportunities of learning. This entails much of performance and recurrence.

The study of the brain has indicated that recurrent exercise of its systems leads to alteration, which is termed neuroplasticity. To get to the bottom of the matter and restructure the brain, neurofeedback permits an individual to harness neuroplasticity. Neurofeedback training ensures the application of the mind’s remarkable capacity for change, its aptitude to reform the manner in which it operates, and assists people to tackle their challenges. Though everyone is born with hard-wiring systems of connecting fibers and neurons, the human brain are continuously being formed through experience. Frequent encounters lead to enhanced linkages amid neurons and in greater potency in the extant correlations (Eriksson et al. 23-33). Such small modifications, normally repeated, result in adaptations in the operations of the brain. Hence, it is possible to transform brain action models through response-directed learning.

Brief History of Neurofeedback

The management of autistic conditions with the help of neurofeedback dates back to about 25 years (Holtmann et al. 986-993). During such early times of its commencement, the utilization of neurofeedback was major to Attention-Deficit Hyperactivity Disorder, though such similar techniques were evidently also supportive for a range of other concerns. Therefore, it emerged naturally to a desire to attempt the techniques also with children having the autistic disorder. Such early endeavors were only as probable of making things poorer the same way they would make matters enhanced, thus researchers rapidly situated a virtual enclosure about autism and resolved that they did not identify much to embark there. Years afterward, a number of researchers in the field identified some excellent outcomes with novel approaches thus the barrier was once again removed to enable trying neurofeedback in the management of autistic conditions.

Neurofeedback approaches have proliferated in the form in the course of the years, and with an extensive set of medical devices, it is as well beneficial to be consistent with an expansive scope of medical difficulties in autistic disorders. The point was being realized where people could practically anticipate valuable progress with almost every child with autism. Simultaneously, scientific comprehension of the concerns was advancing to the point where the neurofeedback operation could presently be comprehended with respect to an established model. Prior to progressing into greater depth on the neurofeedback advance, it is useful to take that model into consideration. Therapies for autistic disorders could be mainly grouped into techniques that tackle biomedical matters that are in the causal chain and techniques that try to improve the behavioral effects (Hurt, Arnold, and Lofthouse 465-486).

Looking at a glance, neurofeedback suits the latter group, and certainly, neurofeedback practitioners have a tendency of belonging to the mental medical camp. Through tackling conduct at the phase of the brain, the novel ground that does not fit suitably either in the ideal biomedical model, the idyllic mental fitness, or behavioral representation is opened up. When observed from the view of brain conduct, the most obvious limitation in autistic spectrum conditions is at the level of integration of tasks. Furthermore, such shortfall is not consistent across functional domains but instead bothers particularly the psychological hub that enables people to operate in socially-associated habits (Hurt, Arnold, and Lofthouse 465-486).

At the position of the brain, even the psychological operation is systemized by neural systems. It is evident that there are developmental errors in the structural connectedness of such systems. Past, nevertheless, there are as well shortfalls in the operational linkages that function on the faulty style. By just studying the structural discrepancies in the white matter, researchers establish no explanation to believe that psychological systems ought to be selectively influenced. Neurofeedback occurs at the position of the operational linkage. Researchers have to fundamentally function in the restrictions of what is available with respect to structural connectedness, but the good thing is that psychological linkage in the children with autism lies mainly in the practical field and is hence medically reachable. Electroencephalographic neurofeedback enables this in an effective manner, and there is currently, fundamentally no other equivalent way of making it possible (Hurt, Arnold, and Lofthouse 465-486). There is no apparent final point to training in autism since the progressively proficient brain only keeps on developing fresh skills. Society requires ensuring that all children with autism have the chance to enlarge their mental perspectives with neurofeedback.

Epilepsy Prediction and Epileptic seizures

For numerous patients, anticonvulsant medicines could be offered at adequately higher dosages to hinder seizures though the patients normally experience fallouts (Engel et al. 922-930). For twenty to forty percent of epileptic patients, medicines are not successful, and even following the surgical elimination of epilepsy-causing tissue of the brain, numerous patients keep on encountering spontaneous ictuses. Regardless of the reality that seizures seldom happen, individuals with epilepsy experience constant anxiety because of the likelihood of their occurrence. Seizure prediction methods have the ability to assist people with epilepsy to have more typical lives.

There is a rising indication that the temporal kinetics of brain activity could be grouped into four classes that encompass Interictally (amid seizures), Ictal (seizure), Preictal (before seizure), and Post-ictal (following seizures). The prediction of epileptic seizures requires the capacity to determine a preictal situation that could be distinguished from the other three consistently. The major difficulty lies in distinguishing the preictal and interictal occurrences (Thomas et al. 124-129). The instances of epilepsy could be classified into different epilepsy syndromes by particular present aspects. Such aspects encompass the age that ictuses start, the kind of seizure, and electroencephalogram results to mention a few. Recognizing epilepsy syndromes is helpful in establishing the causes, in addition to the anti-seizure medicines that ought to be taken.

The capability to classify an instance of epilepsy into a given syndrome happens more frequently in children because the onset of ictuses is normally early. Predicting (diagnosing) epilepsy could be a difficult task. On this note, specialists and health professionals have to carry out many tests and collect much information from the patients and family members for a sure diagnosis (Hao et al. 30-32). Some tests that the professionals can arrange for the patients to have are electroencephalographic tests, computerized tomography (CT), and magnetic resonance imaging (MRI) scans. The prediction of epilepsy is complicated by the fact that no single test could give a certain diagnosis.

Epileptic seizures occur as succinct occurrences of signs and symptoms because of anomalous extreme or synchronic neuronal action in the brain (Vezzani et al. 31-40). The external impact could differ from unrestrained twitching movements to as slight as a short-lived loss of consciousness (absence seizure). The malady of the brain typified by a lasting inclination to produce epileptic seizures is termed epilepsy. Nevertheless, seizures could as well arise in individuals that do not have epilepsy. It might be exceedingly hard to diagnose seizures since the professionals and specialists are seldom able to witness them at the time of the clinic visit; it is thus crucial to have an accurate account of the events or occurrences. The initial occurrence of seizure normally does not necessitate treatment except when there is a particular impairment of brain imaging or EEG. Five to ten percent of individuals that live past eighty years have had at least a single epileptic seizure and the likelihood of having a second one is between forty and fifty percent. Approximately half of the patients with an evident first seizure have had other slight seizures; thus, their diagnosis could be epilepsy.

Epilepsy and Electroencephalography

The cells in the brain continually send information to one another and that could be collected as minute electrical pulsations on the scalp (Fisher et al. 475-482). The practice of gathering and recording the pulsations could be through electroencephalographic methodologies. A standard EEG record signifies that a person has a normal pattern of brainwave action while an atypical recording indicates that anomalous patterns of brain activeness are being generated and collected. For people with epilepsy, the brains at times do not function normally, which results in seizures, also referred to as epileptic fits. Individuals experiencing seizures could have normal brain activities (as indicated on EEG outcomes) or some minor anomalies in the middle of the attacks; hence, professionals and specialists are crucial during the observation and assessment of the EEG results. The EEG results will assist the health professional to determine the kind of epilepsy that an individual has and the factors that could be evoking the seizures, which will establish the most successful kind of medication for the prescription. In uncommon instances, treatment could necessitate brain operation (neurosurgery).

Electroencephalography denotes a fundamental section in the assessment of epilepsy (Heron et al. 152-160). The Electroencephalogram offers significant results concerning background recording and is vital for the diagnosis of some electroclinical syndromes. This form of diagnosis bears significant prognostic details, directs the choice of antiepileptic medicine, and proposes when to stop the medication. Neurologic evaluation in addition to imaging in the fundamental idiopathic, characteristically genetic, epilepsies is generally normal. After experiencing a seizure (that is, in the course of the postictal phase), the electroencephalographic background could be sluggish. Nevertheless, interictal background electroencephalographic frequencies that are greatly sluggish with respect to age denote symptomatic epilepsy. Typical electroencephalographic background implies primary epilepsy (that is, idiopathic or probably genetic epilepsy) (Berényi et al. 735-737). Therefore, the electroencephalographic background provides significant prognostic and categorization details, and epileptiform discharges assist medical professionals to distinguish generalized from central (that is, partial) seizures.

In the course of electroencephalographic tests, the electrical indications of the brain are registered (Morrell 1295-1304). The signals generated by the brain neurons are collected by the sensors and when sent to the instrument draw different graphs on a moving sheet traced in ink or on the monitor of a computer. While undertaking the EEG test, the patient lies on the examining bench and approximately twenty sensors are fixed on the scalp. He is then told to calm down and first lie with the eyes open and afterward closed. The patient could be told to breathe intensely and quickly or gaze at a blinking light, and both actions could generate modifications in the brainwave activities. When being assessed for a sleep disorder, the test could be carried out at night when the patient is sleeping. The recordings that entail analysis of body functions when the patient is asleep, for instance, pulse rate, are called polysomnography. A neurologist then analyses the recorded electroencephalographic patterns for anomalies in the brainwave activities that could reveal maladies of the nervous system.

Spatial-Temporal Dynamics in Epilepsy

The emergence of seizures is the major aspect across the scale of epileptic disorders. Epileptic seizures are amid the most common disturbances of the nervous system (Kellermann et al. 1-8). In epileptic individuals, a highly synchronized action of neural action is observed and could be recorded with the use of electroencephalographic methodologies. Through the use of analytical methods initiated for the evaluation of intricate nonlinear systems, it was possible to illustrate and measure specific variations in spatial-temporal dynamics in the electroencephalogram that start some minutes prior to and stop a few minutes following a seizure. Such variations seem to develop in a distinctive pattern, ending in a seizure. The developments show that in the near future it will be possible to achieve a signal handling technique with the ability to measure the EEG more precisely and in finer aspects as compared to the possibility in the course of medical assessment. This will not occur as a surprise since there will be an outstanding evaluation of dynamical patterns on a spatial-temporal course; that is, details that are not directly available through observing the electroencephalographic recordings.

In line with the theory of nonlinear dynamics, state scope denotes the usual domain for the measurement of the attributes of nonlinear dynamics (Hesdorffer et al. 184-191). It is evident that the incidence of epileptic seizures indicates a spatial-temporal state of transition involving extensive sections of the hippocampus, as well as the neocortex. Such a transition seems to arise over a greater time range as compared to what can be elucidated by existing theories of epileptogenesis. Anchored in multiple analyses of epileptic seizures from the recordings and neuron modeling, the condition could be divided into different spatial extents to demonstrate that the spatial degree of every patient expresses numerous time scope actions.

Detection and Prediction of Seizures on Scalp-EEG Data

EEG has acted as the most commonly employed tool for medical assessment of brain action hence making the categorization of epileptic seizures a possibility (Tomson et al. 609-617). EEG data denotes the amount of current that is produced in the course of synaptic fervors of the dendrites of numerous neurons in the cerebral mantle. They are measured by multiple sensor electroencephalographic instruments that could be placed either inside the brain, on the cerebral mantle beneath the skull, or some positions on the scalp and could be expressed in dissimilar styles. The majority of the traditional techniques for the evaluation of epilepsy, anchored in the electroencephalogram, are centered on the recognition and categorization of epileptic seizures. Amongst them, the most excellent technique of assessment is the visual examination of the electroencephalographic recordings by a professional. Nevertheless, with the initiation of novel data analyzing techniques founded on the mathematical hypothesis, there is an augmented concern in the study of the electroencephalogram for detecting and predicting epileptic seizures effectively.

Researchers have established five conditions (which encompass active alertness, quiet wakefulness, desynchronized electroencephalogram, phasic electroencephalogram, and sluggish electroencephalogram) for the detection of spike and devised a technique for automatic categorization of the condition. The researchers then created practices for the detection of nonepileptic episodes through the evaluation of different factors, for instance, sharpness and period of electroencephalographic waves. There has been an extensive application of artificial neural networks for the identification of seizures (Surges and Sander 201-207). The prediction of epilepsy identifies the period of development of the slow signal greater than a number of predetermined standards from scalp-EEG data.

Amid contemporary methods, time-frequency (TF) techniques successfully employ the reality that the origins of seizures are expressed by the TF field (Carvill et al. 1073-1076). Among the inclinations for effective prediction of seizures is the nonlinear approach. The brain is alleged to be a dynamical system, because epileptic neuronal systems are fundamentally intricate nonlinear formations and the nonlinear conduct of their dealings is, therefore, anticipated. On this note, the approaches have verified the assumption that measurement of the variations in the brain’s dynamics from the electroencephalogram may facilitate the prediction of epileptic seizures. On the contrary, traditional techniques of evaluation have not succeeded in the recognition of specific alterations before the occurrence of seizures.

Some of the nonlinear approaches that have been initiated include the dynamical similarity index, which quantifies the resemblance of electroencephalographic kinetics involving recordings carried out at different periods (Lutas and Yellen 32-40). Some techniques initiate factors of standard energy scalp-EEG data. Such techniques state that when seizures occur, there are ruptures of complex epileptiform action and subclinical seizure, in addition to progressive augments in energy in the epileptic center. The detection and prediction of seizures on scalp-EEG signals are mainly employed in health facilities. However, scalp-EEG data is more exposed to environmental noise and artifacts when judged against intracranial EEG, and the consequential waves are weakened and blended in their processing through bone and soft tissue.

Linear and Nonlinear Measures to Predicting of Seizures

Proof of a steady change was established around 1970 when researchers, utilizing linear data processing measures, found variations in EEG recordings starting a short while before the commencement of seizures (Lin, Mula, and Hermann 1180-1192). Several researchers established alterations in interictal signal or period before the start of seizures though others did not find constant alterations in the recorded patterns. These analyses were carried out through an evaluation of moderately brief electroencephalographic samples in a restricted number of epileptic individuals (Devinsky et al. 174-184). Even at the point of analysis, the researchers found that the occurrence of preictal modifications in the electroencephalogram increased the likelihood of predicting seizures. Linear measures, for instance, consistency, spectrogram, and energy necessitate the presumption of a linear wave.

Before the end of the 1980s, quicker computers with broader storage capacities ensured the possibility of methodically assessing longer fragments of electroencephalographic recordings before and after seizures from a huge number of epileptic individuals and using more advanced techniques of data processing. Stimulated by assumptions that seizures could emanate from spontaneous conditions in disorganized nonlinear coordination, numerous researchers started employing mathematical approaches initiated for the study of intricate nonlinear systems to evaluate EEGs for qualities unique to the changes prior to and following seizures. In this regard, there was the initiation of ways of reporting quantifiable alterations in the electroencephalographic dynamics (spatial-temporal and temporal) that occurred before seizures. Such alterations were measured with respect to signal arrangement, wave intricacy, time dependence, and resemblance, all predicted through the creation of multidimensional stage space (Russ, Larson, and Halfon 256-264). The actual significance of the measured signals was excellently comprehended when employed in computer-created yield from independent representations of deterministic self-directed intricate nonlinear measures. The restrictions of nonlinear measures have resulted in many researchers regenerating endeavors to predict seizures with linear techniques.

Seizures Control

The objective of treatment in people experiencing epileptic seizures is the realization of a seizure-free position devoid of unpleasant outcomes (Walker et al. 105). This objective is attained in over sixty percent of the people that desire treatment with anticonvulsants. The majority of epileptic individuals encounter negative impacts from the drugs, nevertheless, and several of them have seizures that are stubborn to medical treatment. Monotherapy is beneficial since it lessens the possibility of negative impacts and prevents the interaction of drugs. Furthermore, monotherapy could be cheaper when judged against polytherapy since most of the older drugs have hepatic enzyme-stimulating qualities that reduce the serum degree of associated medication hence augmenting the needed dosage of the drugs. Patients with seizures encounter psychosocial changes following their diagnosis; hence, social and occupational rehabilitation could be required. Some doctors underrate the impact that an epilepsy diagnosis could have on individuals. For instance, epileptic patients could live in dread of having the next seizure and might be incapable of driving or working at high heights. The epileptic individuals with stubborn spells ought to be referred to epileptologists or other health professionals for further treatment, encompassing video-EEG examination, to typify the etiology of the seizures with the purpose of controlling them. When the likelihood of surgical treatment is mulled over, a neurosurgical professional should be consulted (Heck et al. 432-441).

Taking medication has at all times been a fact for the majority of individuals that live with epilepsy (Kwan, Schachter, and Brodie 919-926). Before 1990, the selection of epilepsy medication was relatively simple because just a few types were on the market. In the course of the last fifteen years, epilepsy treatment meant for seizures control has had numerous developments. The number of epilepsy medications in the market has increased almost threefold thus enhancing treatment but, resulting in their selection being more intricate. The realization of the most effective medication to a patient involves a bit of presumption. Though it might not be guesswork, there is certainly an issue of testing and making a mistake. Health professionals take into consideration a good deal of information (such as kind of seizure, age, gender, and health conditions) concerning the patient prior to the recommendation of initial medication. Nevertheless, eventually, the choice of epilepsy medication turns out to be a learned leap of conviction. There are no dependable means of predicting whether an epileptic patient will react to a given drug negatively or the level of fallout that will be encountered.

The new assumption in the treatment of epilepsy is that every means of seizure control has its side effects (Lehnertz and Dickten 201-215). Though some health professionals might differ with the assumption, every medicine has its side effects that many individuals experience. However, shifting to an epilepsy medicine with lesser side effects could also be risky though worth it in terms of the quality of life; some of the risks for such drugs are tiredness, insomnia, and confusion. When it comes to selecting the most excellent medicine, the number of alternatives for controlling seizures could be overpowering even to physicians. Although inaccurate, the control of seizures is at times realized. 50% of individuals with a recent diagnosis of seizure are seizure-free after the initial attempt of epilepsy medication.

Slow Cortical Potentials (SCPs)

Slow cortical potentials denote the unconstructive or constructive polarizations of the magnetic field alterations in the magnetoencephalogram or electroencephalogram that occur for a short time (Breshears et al. 305). They emanated from the depolarizations of the dendrites in the cerebral cortex and are initiated by synchronous firing. Functionally, they form a standard regulation system for restricted excitatory adoption (unconstructive SCPs) or suppression (constructive SCPs) cortical systems. SCPs could appear as slow unconstructive direct current alterations quantifiable at the scalp. They fit in the group of event-associated potentials, varying from the spontaneous activity achieved from predictable electroencephalographic capacities.

The neurophysiological foundations of slow unconstructive direct current alterations are long-term excitatory postsynaptic thresholds at the dendrites. Slow cortical potentials are linked to intricate cognitive and emotional processing, revealing a broad scope of tasks encompassing intent, motor development, communication, item and occurrence handing, and psychological orientation; eventually, it entails all consciously propelled, attentional, and operating memory tasks. Human beings could discover the means of voluntarily regulating the potentials subsequent to operant training with the aid of immediate feedback and constructive reinforcement for spontaneous slow potential alterations. Following the discovered self-adjustment of unconstructive SCPs, cognitive, as well as the motor undertaking of diverse roles are reliant on the particular cortical position of the discerned response. Discovered lessening of cortical negativity augments the rate of seizures and facilitates medicine-resistant epileptic attacks (Peñagarikano et al. 235-246). In this regard, the discovered self-adjustment of SCPs is anchored in the redistribution of attentional resources and relies significantly on a prefrontal, in addition to thalamic attention organization.

Works Cited

Auyeung, Bonnie, Sally Wheelwright, Carrie Allison, Matthew Atkinson, Nelum Samarawickrema, and Simon Baron-Cohen. “The children’s empathy quotient and systemizing quotient: Sex differences in typical development and in autism spectrum conditions.” Journal of autism and developmental disorders 39.11 (2009): 1509-1521. Print.

Barnes, Jennifer, and Simon Baron-Cohen. “The big picture: Storytelling ability in adults with autism spectrum conditions.” Journal of autism and developmental disorders 42.8 (2012): 1557-1565. Print.

Baron-Cohen, Simon, Fiona Scott, Carrie Allison, Joanna Williams, Patrick Bolton, Fiona Matthews, and Carol Brayne. “Prevalence of autism-spectrum conditions: UK school-based population study.” The British Journal of Psychiatry 194.6 (2009): 500-509. Print.

Berényi, Antal, Mariano Belluscio, Dun Mao, and György Buzsáki. “Closed-loop control of epilepsy by transcranial electrical stimulation.” Science 337.6095 (2012): 735-737. Print.

Bird, Geoffrey, Clare Press, and Daniel Richardson. “The role of alexithymia in reduced eye-fixation in autism spectrum conditions.” Journal of autism and developmental disorders 41.11 (2011): 1556-1564. Print.

Breshears, Jonathan, Charles Gaona, Jarod Roland, Mohit Sharma, David Bundy, Joshua Shimony, Samiya Rashid, Lawrence Eisenman, Edward Hogan, Abraham Snyder, and Eric Leuthardt. “Mapping sensorimotor cortex using slow cortical potential resting-state networks while awake and under anesthesia.” Neurosurgery 71.2 (2012): 305. Print.

Carvill, Gemma, Brigid Regan, Simone Yendle, Brian O’Roak, Natalia Lozovaya, Nadine Bruneau, Nail Burnashev, Adiba Khan, Joseph Cook, Eileen Geraghty, Lynette Sadleir, Samantha Turner, Meng-Han Tsai, Richard Webster, Robert Ouvrier, John Damiano, Samuel Berkovic, Jay Shendure, Michael Hildebrand, Pierre Szepetowski, Ingrid Scheffer, and Heather Mefford. “GRIN2A mutations cause epilepsy-aphasia spectrum disorders.” Nature Genetics 45.9 (2013): 1073-1076. Print.

Catarino, Ana, Owen Churches, Simon Baron-Cohen, Alexandre Andrade, and Howard Ring. “Atypical EEG complexity in autism spectrum conditions: A multiscale entropy analysis.” Clinical Neurophysiology 122.12 (2011): 2375-2383. Print.

Clare, Isabel, and Marc Woodbury-Smith. “Autism spectrum conditions.” Forensic neuropsychology in practice 2.4 (2009): 109-134. Print.

Cook, Jennifer, and Geoffrey Bird. “Atypical social modulation of imitation in autism spectrum conditions.” Journal of autism and developmental disorders 42.6 (2012): 1045-1051. Print.

Cook, Jennifer, Sarah-Jayne Blakemore, and Clare Press. “Atypical basic movement kinematics in autism spectrum conditions.” Brain 136.9 (2013): 2816-2824. Print.

Devinsky, Orrin, Annamaria Vezzani, Souhel Najjar, Nihal De Lanerolle, and Michael Rogawski. “Glia and epilepsy: Excitability and inflammation.” Trends in neurosciences 36.3 (2013): 174-184. Print.

Engel, Jerome, Michael McDermott, Samuel Wiebe, John Langfitt, John Stern, Sandra Dewar, Michael Sperling, Irenita Gardiner, Giuseppe Erba, Itzhak Fried, Margaret Jacobs, Harry Vinters, Scott Mintzer, and Karl Kieburtz. “Early surgical therapy for drug-resistant temporal lobe epilepsy: A randomized trial.” Jama 307.9 (2012): 922-930. Print.

Eriksson, Mats Anders, Joakim Westerlund, Åsa Hedvall, Per Åmark, Christopher Gillberg, and Elisabeth Fernell. “Medical conditions affect the outcome of early intervention in preschool children with autism spectrum disorders.” European child & adolescent psychiatry 22.1 (2013): 23-33. Print.

Falkmer, Marita, Katie Anderson, Annette Joosten, and Torbjörn Falkmer. “Parents’ perspectives on inclusive schools for children with autism spectrum conditions.” International Journal of Disability, Development, and Education 62.1 (2015): 1-23. Print.

Fisher, Robert S., Carlos Acevedo, Alexis Arzimanoglou, Alicia Bogacz, J. Helen Cross, Christian E. Elger, Jerome Engel, Lars Forsgren, Jacqueline French, Mike Glynn, Dale Hesdorffer, Gary Mathern, Solomon Moshé, Emilio Perucca, Ingrid Scheffer, Torbjörn Tomson, Masako Watanabe, and Samuel Wiebe. “ILAE official report: A practical clinical definition of epilepsy.” Epilepsia 55.4 (2014): 475-482. Print.

Golan, Ofer, Simon Baron-Cohen, and Yael Golan. “The ‘reading the mind in films’ task [child version]: Complex emotion and mental state recognition in children with and without autism spectrum conditions.” Journal of autism and developmental disorders 38.8 (2008): 1534-1541. Print.

Golan, Ofer, Simon Baron-Cohen, Jacqueline Hill, and Mary Rutherford. “The ‘reading the mind in the voice’ test-revised: A study of complex emotion recognition in adults with and without autism spectrum conditions.” Journal of autism and developmental disorders 37.6 (2007): 1096-1106. Print.

Golan, Ofer, Yana Sinai-Gavrilov, and Simon Baron-Cohen. “The Cambridge mindreading face-voice battery for children (CAM-C): Complex emotion recognition in children with and without autism spectrum conditions.” Molecular Autism 6.1 (2015): 22. Print.

Hao, Yan, Xue-Hai Guan, Tao-Tao Liu, Zhi-Gang He, and Hong-Bing Xiang. “Hypothesis: The central medial amygdala may be implicated in sudden unexpected death in epilepsy by melanocortinergic–sympathetic signaling.” Epilepsy & Behavior 41 (2014): 30-32. Print.

Happé, Francesca, and Uta Frith. “The weak coherence account: Detail-focused cognitive style in autism spectrum disorders.” Journal of autism and developmental disorders 36.1 (2006): 5-25. Print.

Heck, Christianne, David King‐Stephens, Andrew Massey, Dileep Nair, Barbara Jobst, Gregory Barkley, and Vicenta Salanova. “Two‐year seizure reduction in adults with medically intractable partial onset epilepsy treated with responsive neurostimulation: final results of the RNS System Pivotal trial.” Epilepsia 55.3 (2014): 432-441. Print.

Heron, Sarah, Bronwyn Grinton, Sara Kivity, Zaid Afawi, Sameer Zuberi, James Hughes, and Clair Pridmore. “PRRT2 mutations cause benign familial infantile epilepsy and infantile convulsions with choreoathetosis syndrome.” The American Journal of Human Genetics 90.1 (2012): 152-160. Print.

Hesdorffer, Dale, Lianna Ishihara, Lakshmi Mynepalli, David Webb, John Weil, and Allen Hauser. “Epilepsy, suicidality, and psychiatric disorders: A bidirectional association.” Annals of Neurology 72.2 (2012): 184-191. Print.

Holtmann, Martin, Sabina Steiner, Sarah Hohmann, Luise Poustka, Tobias Banaschewski, and Sven Bölte. “Neurofeedback in autism spectrum disorders.” Developmental Medicine & Child Neurology 53.11 (2011): 986-993. Print.

Hurt, Elizabeth, Eugene Arnold, and Nicholas Lofthouse. “Quantitative EEG neurofeedback for the treatment of pediatric attention-deficit/hyperactivity disorder, autism spectrum disorders, learning disorders, and epilepsy.” Child and adolescent psychiatric clinics of North America 23.3 (2014): 465-486. Print.

Ingudomnukul, Erin, Simon Baron-Cohen, Sally Wheelwright, and Rebecca Knickmeyer. “Elevated rates of testosterone-related disorders in women with autism spectrum conditions.” Hormones and Behavior 51.5 (2007): 597-604. Print.

Izawa, Jun, Sarah Pekny, Mollie Marko, Courtney Haswell, Reza Shadmehr, and Stewart Mostofsky. “Motor learning relies on integrated sensory inputs in ADHD, but over‐selectively on proprioception in autism spectrum conditions.” Autism Research 5.2 (2012): 124-136. Print.

Kellermann, Tanja, Leonardo Bonilha, Jack Lin, and Bruce Hermann. “Mapping the landscape of cognitive development in children with epilepsy.” Cortex 66 (2015): 1-8. Print.

Kwan, Patrick, Steven Schachter, and Martin Brodie. “Drug-resistant epilepsy.” New England Journal of Medicine 365.10 (2011): 919-926. Print.

Lai, Meng-Chuan, Michael Lombardo, Greg Pasco, Sally Wheelwright, Susan Sadek, Bhismadev Chakrabarti, and Simon Baron-Cohen. “A behavioral comparison of male and female adults with high functioning autism spectrum conditions.” PloS one 6.6 (2011): 208-215. Print.

Lehnertz, Klaus, and Henning Dickten. “Assessing directionality and strength of coupling through symbolic analysis: An application to epilepsy patients.” Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences 373.2034 (2015): 201-215. Print.

Lin, Jack, Marco Mula, and Bruce Hermann. “Uncovering the neurobehavioural comorbidities of epilepsy over the lifespan.” The Lancet 380.9848 (2012): 1180-1192. Print.

Luke, Lydia, Isabel Clare, Howard Ring, Marcus Redley, and Peter Watson. “Decision-making difficulties experienced by adults with autism spectrum conditions.” Autism 16.6 (2012): 612-621. Print.

Lutas, Andrew, and Gary Yellen. “The ketogenic diet: metabolic influences on brain excitability and epilepsy.” Trends in neurosciences 36.1 (2013): 32-40. Print.

Morrell, Martha. “Responsive cortical stimulation for the treatment of medically intractable partial epilepsy.” Neurology 77.13 (2011): 1295-1304. Print.

Peñagarikano, Olga, Brett Abrahams, Edward Herman, Kellen Winden, Amos Gdalyahu, Hongmei Dong, and Lisa Sonnenblick. “Absence of CNTNAP2 leads to epilepsy, neuronal migration abnormalities, and core autism-related deficits.” Cell 147.1 (2011): 235-246. Print.

Roelfsema, Martine, Rosa Hoekstra, Carrie Allison, Sally Wheelwright, Carol Brayne, Fiona Matthews, and Simon Baron-Cohen. “Are autism spectrum conditions more prevalent in an information-technology region? A school-based study of three regions in the Netherlands.” Journal of autism and developmental disorders 42.5 (2012): 734-739. Print.

Russ, Shirley, Kandyce Larson, and Neal Halfon. “A national profile of childhood epilepsy and seizure disorder.” Pediatrics 129.2 (2012): 256-264. Print.

Ruta, Liliana, Erin Ingudomnukul, Kevin Taylor, Bhismadev Chakrabarti, and Simon Baron-Cohen. “Increased serum androstenedione in adults with autism spectrum conditions.” Psychoneuroendocrinology 36.8 (2011): 1154-1163. Print.

Stewart, Mary, Clair McAdam, Mitsuhiko Ota, Sue Peppé, and Joanne Cleland. “Emotional recognition in autism spectrum conditions from voices and faces.” Autism 17.1 (2013): 6-14. Print.

Surges, Rainer, and Josemir Sander. “Sudden unexpected death in epilepsy: mechanisms, prevalence, and prevention.” Current opinion in neurology 25.2 (2012): 201-207. Print.

Tavassoli, Teresa, and Simon Baron-Cohen. “Taste identification in adults with autism spectrum conditions.” Journal of autism and developmental disorders 42.7 (2012): 1419-1424. Print.

Tavassoli, Teresa, Keziah Latham, Michael Bach, Steven Dakin, and Simon Baron-Cohen. “Psychophysical measures of visual acuity in autism spectrum conditions.” Vision Research 51.15 (2011): 1778-1780. Print.

Thomas, Rhys, Jordana Walsh, Carla Church, Graeme Sills, Anthony Marson, Gus Baker, and Mark Rees. “A comprehensive neuropsychological description of cognition in drug-refractory juvenile myoclonic epilepsy.” Epilepsy & Behavior 36 (2014): 124-129. Print.

Tomson, Torbjörn, Dina Battino, Erminio Bonizzoni, John Craig, Dick Lindhout, Anne Sabers, Emilio Perucca, and Frank Vajda. “Dose-dependent risk of malformations with antiepileptic drugs: An analysis of data from the EURAP epilepsy and pregnancy registry.” The Lancet Neurology 10.7 (2011): 609-617. Print.

Vezzani, Annamaria, Jacqueline French, Tamas Bartfai, and Tallie Baram. “The role of inflammation in epilepsy.” Nature Reviews Neurology 7.1 (2011): 31-40. Print.

von dem Hagen, Elisabeth, Raliza Stoyanova, Simon Baron-Cohen, and Andrew Calder. “Reduced functional connectivity within and between ‘social’ resting-state networks in autism spectrum conditions.” Social cognitive and affective neuroscience 2.4 (2012): 53. Print.

Wakabayashi, Akio, Simon Baron-Cohen, Tokio Uchiyama, Yuko Yoshida, Miho Kuroda, and Sally Wheelwright. “Empathizing and systemizing in adults with and without autism spectrum conditions: Cross-cultural stability.” Journal of autism and developmental disorders 37.10 (2007): 1823-1832. Print.

Walker, Lauren, Karen Tse, Emanuele Ricci, Thimmasettappa Thippeswamy, Graeme Sills, Steve White, Daniel Antoine, Anthony Marson, and Munir Pirmohamed. “High mobility group box 1 in the inflammatory pathogenesis of epilepsy: Profiling circulating levels after experimental and clinical seizures.” The Lancet 383 (2014): 105. Print.

Wing, Lorna, Judith Gould, and Christopher Gillberg. “Autism spectrum disorders in the DSM-V: Better or worse than the DSM-IV?” Research in developmental disabilities 32.2 (2011): 768-773. Print.

Wright, Barry, David Sims, Siobhan Smart, Ahmed Alwazeer, Ben Alderson-Day, Victoria Allgar, and Clare Whitton. “Melatonin versus placebo in children with autism spectrum conditions and severe sleep problems not amenable to behavior management strategies: A randomized controlled crossover trial.” Journal of autism and developmental disorders 41.2 (2011): 175-184. Print.

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