• Users Online: 28
  • Home
  • Print this page
  • Email this page
Home Current issue Archives Ahead of print Search Subscribe Instructions Submit article About us Editorial board Contacts Login 

 Table of Contents  
ORIGINAL ARTICLE
Year : 2021  |  Volume : 42  |  Issue : 3  |  Page : 139-147

Electrophysiological and psychophysical testing in children with attention-deficit hyperactivity disorder


1 Department of Neuropsychiatry, Otolaryngology, Faculty of Medicine, Tanta University, Tanta, Egypt
2 Audiovestibular Medicine, Department of Audiology Otolaryngology, Faculty of Medicine, Tanta University, Tanta, Egypt

Date of Submission23-Jan-2021
Date of Decision20-Feb-2021
Date of Acceptance09-Apr-2021
Date of Web Publication28-Sep-2021

Correspondence Address:
MD Shereen D. Abo Hammer
Department of Neuropsychiatry, Faculty of Medicine, Tanta University, Tanta, 31527
Egypt
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ejpsy.ejpsy_12_21

Rights and Permissions
  Abstract 


Background Multiple techniques are used for understanding, determining the real pathophysiological process, and treating attention-deficit hyperactivity disorder (ADHD). The aim of this study was to assess cortical auditory evoked potentials (CAEP) as well as P300 in children with ADHD, and its correlation with neurocognitive tests [Wisconsin card sorting test (WCST), digit span (DS), and Stroop test (ST)].
Patients and methods A prospective cross-sectional study was performed on 103 children, who were divided into two groups: 53 children newly diagnosed with ADHD (according to Diagnostic and statistical manual of mental disorders, 5th ed.), who were drug naïve, and 50 normal control matched for age, sex, educational and social level, and intelligence quotient. All participants had detailed psychiatric history, intelligence quotient Wechsler intelligence scale for children (WICS), Conners’ parent/teacher rating scale abbreviated form for ADHD, neuropsychological tests (WCST and Stroop), pure tone audiometry, speech audiometry using GSI 61 audiometer, immittance test using interacoustic, and sustained attention test using auditory continuous performance test (ACPT) P300.
Results Children with ADHD had more perseverative responses, more preservative errors, and more failure to maintain set (FMS) than controls in WCST, with a significant difference among study groups. ADHD group was impaired in digit span backward and ST than control group. P300 amplitude and latency were significantly different between the study groups. In comparison with the control group, statistical delayed latencies of significance were observed in ADHD between all CAEP components. A significant difference for P1-N1 amplitude was observed among different components of CAEP, and no significance was observed regarding P2-N2 amplitude. ACPT showed a significant difference between both groups, with higher percentage in control group. Positive correlations were observed between P300 amplitude and WCST (perseverative error), P300 amplitude and ST results, and N2 latency and DS backward.
Conclusion Assessment of CAEPs and P300 in children with ADHD, as well as their correlation with neurocognitive tests (WCST, DS, and ST), is crucial in diagnosis and management.

Keywords: ACPT, attention-deficit hyperactivity disorder, P300, Stroop, Wisconsin card sorting test


How to cite this article:
Hammer SA, Lasheen RM, Kotait MA, Amer RA. Electrophysiological and psychophysical testing in children with attention-deficit hyperactivity disorder. Egypt J Psychiatr 2021;42:139-47

How to cite this URL:
Hammer SA, Lasheen RM, Kotait MA, Amer RA. Electrophysiological and psychophysical testing in children with attention-deficit hyperactivity disorder. Egypt J Psychiatr [serial online] 2021 [cited 2021 Dec 8];42:139-47. Available from: http://new.ejpsy.eg.net/text.asp?2021/42/3/139/326847




  Introduction Top


Attention-deficit hyperactivity disorder (ADHD) is the commonest neurological and developmental childhood disorder manifested by characteristic symptoms of degrees of decreased attention, increased activity, and impulsivity. With an ∼3–7% prevalence and 30–40% adulthood persistence rate, it became an important medical challenge because of its effect on children’s socioeducational life (Polanczyk et al., 2015).

The disease is manifested by characteristic age-unrelated symptoms of decreased attention, motor restlessness, and impulsive behavior. Major financial costs were placed on many services like education, social, and clinical ones owing to ADHD, and lifetime impairment has occurred in some of them (Sergeant et al., 2002).

The use of new tools for diagnosis, with neurological and psychological evaluation directed toward school-age children, is essential. This is mainly true for executive function (EF) measure tools. The Auditory Continuous Performance Test and cortical auditory evoked potentials (CAEPs) are computerized tests developed to measure selected EF skills in children (Marquardt et al., 2018).

Throughout the previous 20 years, the psychotic diseases’ biological substrates were investigated using electrophysiology. The advantage of electrophysiological procedures is the ability to scan mental processes in real time without invasion. Moreover, fast neural actions and oscillations with high frequency are captured by their extremely high time resolution, and this makes scanning of functional brain possible through source analysis of maps of high density (Blakey et al., 2018).

In the few years, the processing of information and neurological states assessment will be performed mainly using electrophysiological methods, which are promising methods for assessment of causes and predictors of response to clinical treatment (Kamarajan and Porjesz, 2015).

In ADHD cases, changed event-related potential (ERP) has been noted, which reflects neurocognitive dysfunction related to attention domains, inhibitory control, and processing of reward and data. As a result of ERP findings, different stages of sensory and cognitive functions have been shown to be processed in a different manner in children experiencing ADHD. In addition, a different form of component of ERP was observed between subtypes of ADHD. ERP component was used as a predictor for treatment response (Marquardt et al., 2018).

Auditory P300 is a positive ERP component happening nearly 300 ms following target stimuli. It is a selective attention neurological and physiological correlate, working memory, and novelty detection. The P300 is a late ERP component that has been suggested to assess functions of execution and attention, including the function of the memory of working, classifying of event, attentional resource allocation, and attentional reorientation (Polich, 2007).

The P300 amplitude identifies the attention allocation effort and correlates with the gray matter volume contribution to wave, amplitude of P300 could be utilized to discern ADHD subtypes, and it was believed to be a neurophysiological indicator of alerting deficits (Heinrich et al., 2014).

Sangal and Sangal (2006), demonstrated that the topography of P300 could anticipate stimulant efficacy, and that P300 amplitude is related to response to atomoxetine, whereas the P300 latency reflects the processing speed of stimulus discrimination.

This work aims to assess CAEPs as well as P300 in children with ADHD, and its correlation with neurocognitive tests [Wisconsin card sorting test (WCST), digit span (DS), Stroop test (ST)].


  Patients and methods Top


This cross-sectional prospective study was conducted on 103 children, who were divided into two groups: first group was 53 children with ADHD (18 females and 35 males) newly diagnosed with ADHD, who were drug-naïve children, aged between 8 and 14 years. The ADHD diagnosis was according to the Diagnostic and statistical manual of mental disorders, 5th ed.. They were matched with 50 normal controls (29 female and 21 male) with normal hearing, with no history of attention deficit or hyperactivity, with normal school performance and matched with patients for age, sex, educational and social level, and intelligence quotient (IQ).

All attendants of the outpatient child and adolescent psychiatry clinic in a Psychiatry and Neurology Center were recruited. The study was conducted in the Department of Neuropsychiatry and Department of Audiovestibular Medicine Units, Tanta University Hospitals.

The idea of the research was explained in detail to the participants. Patients who agreed to participate signed an informed consent. The participation was voluntary, and the patients could refuse to continue the study at any time without penalty or loss of advantages. Every patient had a code number. Results of this research were used only for scientific purpose. The duration of the study ranged from 6 months, in the period from March 2018 to September 2018. The trial has an approval from the medical ethical committees of Faculty of Medicine, Tanta University. An informed consent was taken from the caregivers of all participants.

Inclusion criteria

The following were the inclusion criteria:
  1. Children aged 8–14 years old.
  2. IQ above 80.
  3. Normal hearing sensitivity with no history of hearing loss, ear discharge, or ear disease.
  4. Normal middle ear function.
  5. Children ADHD who were drug naive.


Exclusion criteria

The following were the exclusion criteria:
  1. Children with mental retardation.
  2. Children with hearing loss or ear disease that affects the hearing function.
  3. Children with serious neurological, psychiatric, or metabolic disorders that affect cognitive and EFs.


All the participants were subjected to the following:
  1. Detailed psychiatric history from parents or caregiver.
  2. Assessment of IQ: Wechsler intelligence scale for children (WICS) to measure IQ.
  3. A semi-structured interview in the form of Kiddie Schedule of affective disorders and schizophrenia-present and life time version to confirm the diagnosis of ADHD.
  4. Conners’ parent/teacher rating scale abbreviated form for ADHD symptoms.
  5. Neuropsychological tests measuring EFs (WCST and Stroop).
  6. Basic audiological assessment, including audiometry of pure tone and audiometry of speech using a GSI 61 audiometer.
  7. Immittance test using interacoustic.
  8. Sustained attention test using auditory continuous performance test (ACPT).
  9. Electrophysiological test both CAEPs using tone and speech stimuli and P300 testing using oddball paradigm.


The participants of the study were recruited from child and adolescent psychiatric outpatient by the first and last investigators. Detailed psychiatric history was taken from the parents or the caregiver of children, with clinical evaluation of ADHD according to Diagnostic and statistical manual of mental disorders, 5th ed., and then Kiddie Schedule of affective disorders and schizophrenia-present and life time version was applied to ensure diagnosis and exclude any psychiatric comorbidity. IQ was evaluated by a trained psychologist, and Conners’ parent rating scale was completed, and then the children who fulfilled the inclusion criteria of the research were referred to Audiovestibular Medicine Unit to be assessed the second and third investigator, for P300 and CAEPs.

Then the cases and control were referred back to neuropsychiatry department for further assessment of their EF in a separate session. The computerized version of WCST was applied for all participants by the first instigator, whereas computerized ST was applied by the last investigator, and DS was already a subset of IQ assessment, which was previously assessed.

P300 and CAEPs were recorded from both control and study groups by Smart EPs of intelligent hearing system. Regarding P300, it was recorded in the oddball paradigm using two kinds of stimuli (speech and tone) that were presented in two paradigms. In the first paradigm, 1000 Hz and 2000 Hz were utilized as the standard and deviant stimuli simultaneously, whereas in the second paradigm, /ga/ stimuli were used as a standard stimulus and /da/ stimuli were utilized as the deviant stimulus using Smart EPs of Intelligent hearing system.

The two stimuli types were presented at one second rate of repetition, 15% deviant probability, and at 50 dBSL (re PTA average at 500, 1000, 2000, and 4000 Hz) monaurally to each ear in the two groups via an insert-phone. Four electrodes were used to record P300, which placed at Fz (‏ve electrode), Fpz (ground electrode), and M1 and M2 (mastoids) as reference electrodes according to side of stimulation. The child was asked to count the deviant one /da/. P300 was identified as the most robust positive wave around 300 ms following N1-P2 complex, and both absolute latency and amplitude were measured.

CAEPs components were recorded using Speech stimuli CV syllable /da/ using the same electrode montage for P300. The settings of filter (recording bandwidth) were 1–30 Hz (low pass 30 Hz and high pass 1 Hz). Stimuli have been monaurally presented to both ears via an ER3A insert phone beginning with ear of right side. The stimulus was presented at 90 dBnHL. All patients and their parents were informed of the test procedure.

During acquisition of the test, each patient was informed to be calm and lie down on a comfortable coach. They were advised at the same time not to focus on the presented stimuli. For identification of the response, the response consisted of a positive wave at about 50 ms (P1), a large negative wave at about 80–100 ms (N1), and a subsequent positive wave at about 180–200 ms (P2). Classically, the N2 is a negativity following the P2. Calculation of the latency and amplitude (peak to peak or baseline to peak) of each wave was done as follows: the P1-N1-P2 latency, which was the time from stimulus onset to the first positivity (P1), first negativity (N1), a subsequent positive wave at about 180–200 ms (P2), and a second negativity (N2). The P1-N1-P2 amplitude that was usually measured from the trace’s zero voltage to the most positive or negative trough in that trace.

Statistical analysis

Statistical analysis was done by SPSS v25 (IBM, Chicago, Illinois, USA). Quantitative parametric data were presented as mean and SD and were analyzed by unpaired Student t test. Quantitative nonparametric data were presented as median and interquartile range and were analyzed by Mann–Whitney test. Qualitative data were presented as number and percent and were compared by χ2. Pearson correlation was done between two variables. A two-tailed P value less than 0.05 was considered statistically significant.


  Results Top


The mean age of patients with ADHD was 10.9 years and for control was 11.1 years, with no significant difference between the two groups regarding age. Males were more than female in ADHD group 66% (n=35), whereas females were 42% (n=21) ([Table 1]).
Table 1 Demographic characteristics of the studied group

Click here to view


The mean IQ of ADHD group was 97.5, whereas it was 99.2 for controls, with no significant difference. Regarding Conners’ parent rating scale, a significant relation was observed among ADHD group and control (P<0.001).

In WCST, perseverative responses could differentiate between control and ADHD children, as children with ADHD had made more perseverative responses than controls, with a significant relation among the two groups (P<0.05). Regarding perseverative errors, they could differentiate control group and ADHD group and the performance of ADHD group differed significantly from controls (P<0.05). In failure to maintain set parameter, children with ADHD also failed to maintain set in comparison with normal control, with a statistically significant difference (P<0.05) ([Table 2]).
Table 2 Cognitive functions assessment among studied group

Click here to view


DS backward, which reflects working memory, was significantly different among clinical group and control group. ADHD group could repeat fewer digits backward than the control group (P<0.05) ([Table 2]).

ST, the time needed to name the color of the word, was significantly different among children with ADHD compared with the normal control, as children with ADHD needed more time to read the name of the color (P<0.05) ([Table 2]).

P300 in response to speech stimuli using oddball paradigm was recorded for both groups; both P300 absolute latency and amplitude were measured. P300 absolute latency showed delay in ADHD in comparison with the control group. This delay was statistically significant, as shown in [Table 3]. Regarding P300 amplitude, statistically significant differences were found between the two groups ([Table 3]).
Table 3 Results of P300 and cortical auditory evoked potential latency and amplitude using both speech and tone stimuli as well as ACPT among study and control groups

Click here to view


CAEP components were recorded using da stimuli. Regarding wave detectability, all CAEP waves (P1N1P2N2) were 100% detectable for both groups. Regarding wave latency, all CAEP components presented delayed latencies of significance in ADHD in comparison with the control group. Different amplitude components of CAEP were measured in the two groups, with difference of statistical significance for P1-N1 amplitude. On the contrary, a nonsignificant relation was found among both study groups regarding P2-N2 amplitude ([Table 3]).

Auditory continuous performance test was recorded for both groups, and there was a significant difference between both groups, with higher percentage in the control group ([Table 3]).

A correlation test was done between electrophysiological tests results and the tests of cognitive functions for ADHD group. A positive correlation was present between P300 amplitude and WCST (perseverative errors) (P=0.03). Moreover, a positive correlation was present among P300 amplitude and ST results (P=0.01)

There was also a positive correlation between N2 latency and DS backward (P=0.03). A positive correlation was present among N1 amplitude results and Conners’ parent rating scale results (P=0.04) ([Table 4]).
Table 4 Correlation of P300, cortical auditory evoked potential latency and amplitude as well as ACPT with cognitive functions in the studied patients (N=53)

Click here to view



  Discussion Top


This study was conducted on 103 children, comprising 53 children with ADHD aged from 8 to 14 years, who were matched with 50 normal control, matched for age, sex, educational and social level, and IQ, with no significant difference.

Conners’ parent rating scale for ADHD symptoms was used in this study. A score higher than 15 reflects presence of ADHD, and higher score reflects severity of ADHD. There was a significant statistical difference between ADHD group and control group.

WCST was used as an indicator of set shifting, cognitive flexibility, solving of problem, feedback using, the ability to alter wrong strategies, and to prevent arrogant responses.

Perseverative responses (replies in the new group that were classified per the previous classification principle), perseverative errors (wrongly classified cards, classified per the previous classification principle), and failure to maintain set parameters of WCST were used as variables in our study. We selected these parameters especially, as most of the studies on WCST had used same parameters in the test assessment, especially preservative responses, which is considered a sensitive parameter in test assessment.

WCST can differentiate children with ADHD from normal control. When the child had higher scores than control, this reflects impairment of set shifting and cognitive flexibility components of EFs (Heaton and Staff, 1993).

In this study, a relation of significance was present among ADHD group and control group, as ADHD group had higher scores in the tested parameters of WCST (preservative responses, perseverative faults, and inability to preserve set), as this group tended to do more perseverative responses and errors than normal controls, with more times to fail to maintain set.

When we try to connect results in our work with the pathophysiology of ADHD, there is a relation between set shifting component of EFs and the impairment in the left dorsolateral prefrontal cortex, so this test (WCST) may have a role in evaluation the underlying impairment in ADHD.

In this study, our results were in concordance with Sergeant et al. (2002), who stated that many WCST trials could differentiate ADHD from normal cases, but these conclusions depend on which parameters have been used. In most of the studies, perseverative response (which is considered a sensitive parameter in WCST), perseverative faults, and inability to preserve set were used to differentiate between ADHD and normal controls.

Our study is in concordance with other many studies that found set shifting impairment in patients with ADHD in comparison with normal control, for example, the studies of Barkley et al. (1992), Carter et al. (1995), Houghton et al. (1999), Seidman et al. (2000), Weyandt and Willis (1994), and Zakzanis et al. (2005).

In this study, a positive correlation was present among P300 amplitude and WCST (perseverative errors), which is a very important physiological correlate.

Scheres et al. (2003) results were not in concordance with our results, as they found that perseverative errors and failure to maintain set did a poor job in discriminating between ADHD and normal control.

ST was used in our study to detect the executive inhibition. Our ADHD sample was significantly impaired relative to control group in the test.

Moreover, a positive correlation was present among P300 amplitude and ST results. It is a neurological and physiological correlate of selective attention, working memory, and novelty detection. The P300 is a late ERP component and was suggested to identify executive and attentional functions, including the function of the working memory, categorizations of events, attentional resource allocation, and attentional reorientation (Polich, 2007).

Poor inhibition is manifested in many situations in children with ADHD who are impulsive as these children find difficulty in waiting turn, interrupt and intrude others, and often blurt out responses before the completion of questions. Inhibitory control of the deficit can encroach into capacity of working memory. This leads to working memory disruptions and interferes with planning and organized behavioral patterns.

Our results were in concordance with the study carried out by MacLeod (1991), who implied that an inhibitory control deficit is a key deficit in ADHD, which is important in situations required withholding or sudden interruption of an ongoing action. Our work was also in concordance with Harris et al. (1995).

This test was used for assessment of working memory. It was found that children with ADHD could recall fewer digits than the control, so there was a significant difference from control, which denotes working memory impairment in our sample of ADHD.

Working memory impairment in children with ADHD can be manifested in many occasions, as these children can find great difficulty in remembering where they just put something, what someone just said to them, what they have just read, or what they are about to say. There was also a positive correlation between N2 latency and DS backward.

A study of Barnett et al. (2001) agreed with the current results. They found working memory deficit in patients with ADHD in comparison with normal controls. Our trial was also in concordance with many other studies such as that of Willcutt et al. (2005) and that of Martinussen et al. (2005) and Finke et al. (2006).

In our study, we measured the P300 absolute latency and amplitude in response to speech stimuli using oddball paradigm in both groups. P300 absolute latency showed statistically significant delay in ADHD in comparison with the control group. Regarding the P300 amplitude, a reduction of statistically significance was present in children with ADHD.

Our results agreed with Borja and Ponde (2009), Tsai et al. (2012), and Yamamuro et al. (2016). who reported P300 latency time increased, and in individuals with ADHD, the amplitude decreased (Borja and Ponde, 2009; Yamamuro et al., 2016).

In the ADHD, it is noted that the P300 amplitude decrease represents deficits in the task-relevant processing or salient data, selective attention, and context updating, whereas the delayed P300 latency was explained by slower processing in ADHD cases (Mercugliano, 1999).

On the contrary, some trials did not agree with our results. Romero et al. (2013) made a comparison between the performance in children with and without ADHD. In comparison with the control group, normal values of P300 latency and amplitude in the ADHD group were noted (Romero et al., 2013).

They explained these nonsignificant differences in their study that the sample was small and recommend a higher number of cases to better auditory pathway analysis. One other possible reason for them was that children with ADHD have modifications in their processes of preattention and discrimination; nevertheless, through the interaction of brain plasticity and reconfiguration of nerve cells, these children may process the data via other structures of the central nervous system.

CAEP waves include P1, N1, P2, and N2; they provide information about perception of sound by the auditory cortex. P1 is a positive wave at 50–100 ms after stimulus and N1 is a negative peak that occurs at ∼80–120 ms following the stimulus initiation. Latencies of P1 and N1 are a helpful screening tool of central auditory development. P2 is a second positive peak at ∼100–160 ms following stimulus and N2 latency was about 200–280 ms (Durante et al., 2014; Sharma et al., 2015).

CAEP components obtained from speech stimuli provide information referring to detection of speech stimuli and processing in the auditory cortex (Souza and Tremblay, 2006).

In our study, CAEP was recorded using da stimuli. Regarding wave detectability, all CAEP waves (P1, N1, P2, and N2) were 100% detectable for both groups. Children with ADHD had delay in latencies by all CAEP components which was significant in comparison with controls. The amplitudes of different C components were evaluated in the two groups, with a statistically significant decrease in the amplitudes of P1, N1, and P2.

In ADHD, processes of response inhibition are affected by concurrent data owing to high distractibility, and this is reflected in the reduction in the amplitude of both P1 and N1. This might be represented in processes of perceptual gating and bottom-up attentional selection (P1 and N1) and at the resource allocation level (P2) (Herrmann and Knight, 2001).

Auditory P1 and N1 is used to assess automatic attention, and it reflects the sensory stimuli processing. The N1 decreased in ADHD suggested decreased automatic attention to salient sound stimuli, which might be owing to decreased activity of the pathways of brain-stem arousal (Sable et al., 2013).

Wang et al. (2008) stated that the frontal cortex could be an integrated component of an inhibitory circuit that inhibits the response to irrelevant, unattended stimuli by feeding back on sensory areas (in a normally functioning brain). This sensory filtering is reflected in reduced N1 amplitudes, indicating reduced attention to those sounds. Low-amplitude N1 may reflect reduced activity in the hindbrain norepinephrine system, including the locus coeruleus (Halperin and Schulz, 2006).

The N2 has been associated with cognitive control and response inhibition. Sable et al. (2013) studied automatic attention in young adults with ADHD. Their results showed reduced N1 amplitude and increased N2 in patients with ADHD, and they suggested that those patients may have developed certain compensatory top–down attentional mechanisms. This may explain the nonsignificance in the N2 amplitude between the both groups in our study. However, some studies showed reduced N2 peak in ADHD compared with the control group, and they suggested that this may indicate an atypical frontal inhibition process in ADHD (Barry et al., 2003).

The P2 component was suggested to reflect automatic stimulus discrimination and the inhibition of further processing of competing (Oades, 1998).

Romero et al. (2013) stated that N2 latency was delayed in ADHD, and they explained it by the decrease in the responses efficiency involving processes of preattention and discrimination.

Auditory continuous performance test was used in cases with ADHD to study sustained attention in those patients. The performance of children and adults with ADHD was found to be worse compared with the control group in many studies (Doehnert et al., 2013). In our study, there was a statistically significant difference between ADHD and the control group, with higher percentage in the controls. Distractibility, hyperactivity, and impulsivity are the main hallmarks in ADHD (Vahia, 2013). The efficiency of information processing and the ability to stay focused on a monotonous task are deficient in patients with ADHD, and they have poor performance on sustained attention (Mazor-Karsenty et al., 2019).


  Conclusion Top


Assessment of CAEPs and P300 in children with ADHD and their correlation with neurocognitivetests (WCST, DS, and ST) are crucial in diagnosis and management of children with ADHD.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.







[39]



 
  References Top

1.
Barkley RA, Grodzinsky G, DuPaul GJ (1992). Frontal lobe functions in attention deficit disorder with and without hyperactivity: a review and research report. J Abnorm Child Psychol 20: 163–188.  Back to cited text no. 1
    
2.
Barnett R, Maruff P, Vance A, Luk ES, Costin J, Wood C et al. (2001). Abnormal executive function in attention deficit hyperactivity disorder: the effect of stimulant medication and age on spatial working memory. Psychol Med 31:1107–1115.  Back to cited text no. 2
    
3.
Barry RJ, Johnstone SJ, Clarke AR (2003). A review of electrophysiology in attention-deficit/hyperactivity disorder: II. Event-related potentials. Clin Neurophysiol 114:184–198.  Back to cited text no. 3
    
4.
Blakey R, Ranlund S, Zartaloudi E, Cahn W, Calafato S, Colizzi M et al. (2018). Associations between psychosis endophenotypes across brain functional, structural, and cognitive domains. Psychol Med 48:1325–1340.  Back to cited text no. 4
    
5.
Borja A, Ponde M (2009). Assessment of cognitive evoked potential, p300 in children with and without ADHD. Rev Ciênc Méd Biol 8:198–205.  Back to cited text no. 5
    
6.
Carter CS, Krener P, Chaderjian M, Northcutt C, Wolfe V (1995). Asymmetrical visual-spatial attentional performance in ADHD: evidence for a right hemispheric deficit. Biol Psychiatry 37:789–797.  Back to cited text no. 6
    
7.
Doehnert M, Brandeis D, Schneider G, Drechsler R, Steinhausen HC (2013). A neurophysiological marker of impaired preparation in an 11-year follow-up study of attention-deficit/hyperactivity disorder (ADHD). J Child Psychol Psychiatry 54:260–270.  Back to cited text no. 7
    
8.
Durante AS, Wieselberg MB, Carvalho S, Costa N, Pucci B, Gudayol N et al. (2014). Cortical auditory evoked potential: evaluation of speech detection in adult hearing aid users. Codas 26:367–373.  Back to cited text no. 8
    
9.
Finke K, Bublak P, Zihl J (2006). Visual spatial and visual pattern working memory: neuropsychological evidence for a differential role of left and right dorsal visual brain. Neuropsychologia 44:649–661.  Back to cited text no. 9
    
10.
Halperin JM, Schulz KP (2006). Revisiting the role of the prefrontal cortex in the pathophysiology of attention-deficit/hyperactivity disorder. Psychol Bull 132:560–581.  Back to cited text no. 10
    
11.
Harris EL, Schuerholz LJ, Singer HS, Reader MJ, Brown JE, Cox C et al. (1995). Executive function in children with Tourette syndrome and/or attention deficit hyperactivity disorder. J Int Neuropsychol Soc 1:511–516.  Back to cited text no. 11
    
12.
Heaton RK, Staff P (1993). Wisconsin card sorting test: computer version 2. Odessa: Psychological Assessment Resources; 4:1–4.  Back to cited text no. 12
    
13.
Heinrich H, Busch K, Studer P, Erbe K, Moll GH, Kratz O (2014). Refining the picture of reduced alerting responses in ADHD − a single-trial analysis of event-related potentials. Neurosci Lett 582:49–53.  Back to cited text no. 13
    
14.
Herrmann CS, Knight RT (2001). Mechanisms of human attention: event-related potentials and oscillations. Neurosci Biobehav Rev 25:465–476.  Back to cited text no. 14
    
15.
Houghton S, Douglas G, West J, Whiting K, Wall M, Langsford S et al. (1999). Differential patterns of executive function in children with attention-deficit hyperactivity disorder according to gender and subtype. J Child Neurol 14:801–805.  Back to cited text no. 15
    
16.
Kamarajan C, Porjesz B (2015). Advances in electrophysiological research. Alcohol Res 37:53–87.  Back to cited text no. 16
    
17.
MacLeod CM (1991). Half a century of research on the Stroop effect: an integrative review. Psychol Bull 109:163.  Back to cited text no. 17
    
18.
Marquardt L, Eichele H, Lundervold AJ, Haavik J, Eichele T (2018). Event-related-potential (ERP) correlates of performance monitoring in adults with attention-deficit hyperactivity disorder (ADHD). Front Psychol 9:485.  Back to cited text no. 18
    
19.
Martinussen R, Hayden J, Hogg-Johnson S, Tannock R (2005). A meta-analysis of working memory impairments in children with attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry 44:377–384.  Back to cited text no. 19
    
20.
Mazor-Karsenty T, Parush S, Shalev L (2019). Sustained attention in sensory modulation disorder and attention deficit/hyperactivity disorder. Res Dev Disabil 88:22–29.  Back to cited text no. 20
    
21.
Mercugliano M (1999). What is attention-deficit/hyperactivity disorder?. Pediat Clin North Am 46:831–843.  Back to cited text no. 21
    
22.
Oades RD (1998). Frontal, temporal and lateralized brain function in children with attention-deficit hyperactivity disorder: a psychophysiological and neuropsychological viewpoint on development. Behav Brain Res 94:83–95.  Back to cited text no. 22
    
23.
Polanczyk GV, Salum GA, Sugaya LS, Caye A, Rohde LA (2015). Annual research review: a meta-analysis of the worldwide prevalence of mental disorders in children and adolescents. J Child Psychol Psychiatry 56:345–365.  Back to cited text no. 23
    
24.
Polich J (2007). Updating P300: an integrative theory of P3a and P3b. Clin Neurophysiol 118:2128–2148.  Back to cited text no. 24
    
25.
Romero AC, Capellini SA, Frizzo AC (2013). Cognitive potential of children with attention deficit and hyperactivity disorder. Braz J Otorhinolaryngol 79:609–615.  Back to cited text no. 25
    
26.
Sable JJ, Knopf KL, Kyle MR, Schully LT, Brooks MM, Parry KH et al. (2013). Attention‐deficit hyperactivity disorder reduces automatic attention in young adults. Psychophysiology 50:308–313.  Back to cited text no. 26
    
27.
Sangal RB, Sangal JM (2006). Attention-deficit/hyperactivity disorder: using P300 topography to choose optimal treatment. Expert Rev Neurother 6: 1429–1437.  Back to cited text no. 27
    
28.
Scheres A, Oosterlaan J, Swanson J, Morein-Zamir S, Meiran N, Schut H et al. (2003). The effect of methylphenidate on three forms of response inhibition in boys with AD/HD. J Abnorm Child Psychol 31:105–120.  Back to cited text no. 28
    
29.
Seidman LJ, Biederman J, Monuteaux MC, Weber W, Faraone SV (2000). Neuropsychological functioning in nonreferred siblings of children with attention deficit/hyperactivity disorder. J Abnorm Psychol 109:252–265.  Back to cited text no. 29
    
30.
Sergeant JA, Geurts H, Oosterlaan J (2002). How specific is a deficit of executive functioning for attention-deficit/hyperactivity disorder? Behav Brain Res 130:3–28.  Back to cited text no. 30
    
31.
Sharma A, Campbell J, Cardon G (2015). Developmental and cross-modal plasticity in deafness: evidence from the P1 and N1 event related potentials in cochlear implanted children. Int J Psychophysiol 95:135–144.  Back to cited text no. 31
    
32.
Souza PE, Tremblay KL (2006). New perspectives on assessing amplification effects. Trends Amplif 10:119–143.  Back to cited text no. 32
    
33.
Tsai ML, Hung KL, Lu HH (2012). Auditory event-related potentials in children with attention deficit hyperactivity disorder. Pediatr Neonatol 53:118–124.  Back to cited text no. 33
    
34.
Vahia VN (2013). Diagnostic and statistical manual of mental disorders 5: a quick glance. Indian J Psychol Med 55:220.  Back to cited text no. 34
    
35.
Wang AL, Mouraux A, Liang M, Iannetti GD (2008). The enhancement of the N1 wave elicited by sensory stimuli presented at very short inter-stimulus intervals is a general feature across sensory systems. PLoS ONE 3:e3929.  Back to cited text no. 35
    
36.
Weyandt LL, Willis WG (1994). Executive functions in school‐aged children: potential efficacy of tasks in discriminating clinical groups. Dev Neuropsychol 10:27–38.  Back to cited text no. 36
    
37.
Willcutt EG, Pennington BF, Olson RK, Chhabildas N, Hulslander J (2005). Neuropsychological analyses of comorbidity between reading disability and attention deficit hyperactivity disorder: in search of the common deficit. Dev Neuropsychol 27:35–78.  Back to cited text no. 37
    
38.
Yamamuro K, Ota T, Iida J, Nakanishi Y, Suehiro Y, Matsuura H et al. (2016). Event-related potentials correlate with the severity of child and adolescent patients with attention deficit/hyperactivity disorder. Neuropsychobiology 73:131–138.  Back to cited text no. 38
    
39.
Zakzanis KK, Mraz R, Graham SJ (2005). An fMRI study of the trail making test. Neuropsychologia 43:1878–1886.  Back to cited text no. 39
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Patients and methods
Results
Discussion
Conclusion
References
Article Tables

 Article Access Statistics
    Viewed124    
    Printed0    
    Emailed0    
    PDF Downloaded17    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]