Eric Hahn

Event-related potentials associated with Attention Network Test

Selective visual attention is thought to be comprised of distinct neuronal networks that serve different attentional functions. The Attention Network Test (ANT) has been introduced to allow for assessment of alerting, orienting, and response inhibition. Information on associated measures of neural processing during ANT is still scarce. We topographically analyzed top-down ANT effects on visual event-related potential morphology in 44 healthy participants. Significant reaction time effects were obtained for all attention networks. Posterior cue-locked target N1 amplitude was significantly increased during both alerting and orienting. P3 amplitude was significantly modulated at frontal and parietal leads as a function of inhibition. Our data suggests that attentional mechanisms of alerting and orienting are employed simultaneously at early stages of the visual processing stream to amplify perceptual discrimination and load onto the same ERP component. Fronto-parietal modulations of P3 amplitude seem to mirror both response inhibition and visual target detection and may be interesting markers for further studies.

Executive Attention in Schizophrenic Males and the Impact of COMT Val108/158Met Genotype on Performance on the Attention Network Test

BACKGROUND Executive control of attention in schizophrenia has recently been assessed by means of the Attention Network Test (ANT). In the past, for tasks assessing executive attention, findings in schizophrenia have been contradictory, among others suggesting a lack of increased stimulus interference effects. Attention and executive functioning are substantially influenced by candidate genes of schizophrenia, including the functional single-nucleotide polymorphism catechol-o-methyltransferase (COMT) Val108/158Met, with task-dependent, specific effects of Met allele load on cognitive function. Therefore, we aimed at investigating executive attention in schizophrenic patients (SZP) as compared with healthy controls (HC), and to assess the specific impact of COMT Val108/158Met on executive attention, using ANT. METHODS We applied ANT to 63 SZP and 40 HC. We calculated a general linear model to investigate the influence of affection status and the COMT Val108/158Met genotype on executive attention as assessed by the ANT. RESULTS Multivariate analysis of variance revealed a significant effect of group on executive attention. SZP exhibited smaller conflict effects in the ANT. Met allele load significantly modulated executive attention efficiency, with homozygous Met individuals showing low overall reaction time but increased effects conflicting stimulus information in executive attention. CONCLUSIONS Our data suggest a disease-related dissociation of executive attention with reduced conflict effects in SZP. Furthermore, they support the hypothesis of differential tonic-phasic dopamine activation and specific dopamine level effects in different cognitive tasks, which helps interpreting contradictory findings of Met allele load on cognitive performance. Disease status seems to modulate the impact of COMT Val108/158Met on cognitive performance.

Attention Network Test reveals alerting network dysfunction in multiple sclerosis

Attention is one of the cognitive domains typically affected in multiple sclerosis. The Attention Network Test was developed to measure the function of the three distinct attentional networks, alerting, orienting, and executive control. The Attention Network Test has been performed in various neuropsychiatric conditions, but not in multiple sclerosis. Our objective was to investigate functions of attentional networks in multiple sclerosis by means of the Attention Network Test. Patients with relapsing—remitting multiple sclerosis (n = 57) and healthy controls (n = 57) matched for age, sex, and education performed the Attention Network Test. Significant differences between patients and controls were detected in the alerting network (p = 0.003), in contrast to the orienting (p = 0.696) and the conflict (p = 0.114) network of visual attention. Mean reaction time in the Attention Network Test was significantly longer in multiple sclerosis patients than in controls (p = 0.032), Multiple sclerosis patients benefited less from alerting cues for conflict resolution compared with healthy controls. The Attention Network Test revealed specific alterations of the attention network in multiple sclerosis patients which were not explained by an overall cognitive slowing.

Single-subject classification of schizophrenia by event-related potentials during selective attention

BACKGROUND Executive dysfunction has repeatedly been proposed as a robust and promising substrate of analytical approaches in the research of neurocognitive markers of schizophrenia. Here, we present a mixed model- and data-driven classification approach by applying a task that targets executive dysfunction in schizophrenia and by investigating relevant event-related potential (ERP) features with machine learning classifiers. METHODS Forty schizophrenic patients and forty matched healthy controls completed the Attention Network Test while an electroencephalogram was recorded. Target-locked N1 and P3 ERP components were constructed and submitted to different classification analyses without a priori hypotheses. Standardized source localization was applied to estimate neural sources of N1 and P3 deficits in schizophrenia. RESULTS We obtained a classification accuracy of 79% using only very few ERP components. Central P3 components following compatible and incompatible trials and right parietal N1 latencies averaged across targets and were sufficient for classification. P3 deficits were associated with anterior cingulate cortex dysfunction, while right posterior current density deficits were observed in schizophrenia during the N1 time frame. CONCLUSIONS The data exemplarily show how automated inference may be applied to classify a pathological state in single subjects without prior knowledge of their diagnoses. While classification accuracy may be optimized by application of other executive paradigms, this approach illustrates the potential of machine learning algorithms for the identification of biomarkers that are independent of clinical assessments. Conversely, data suggest a pathophysiological mechanism that includes early visual and late executive deficits during response inhibition in schizophrenia.

Evidence of specificity of a visual P3 amplitude modulation deficit in schizophrenia

BACKGROUND In a previous study, we found a reduced amplitude modulation of the visual P3 component of the event-related potential (ERP) in schizophrenic patients compared with healthy controls during inhibition in the Attention Network Test (ANT). The objective of the present study was to replicate this finding and to explore whether this cortical processing deficit is specific to schizophrenia. METHODS Sixteen schizophrenic patients, sixteen depressive patients, and sixteen healthy controls matched for age, sex, and education were included. Participants were tested with the ANT, a test of selective attention that provides behavioral estimates for alerting, orienting, and inhibition. 32-Channel electroencephalogram was recorded and visual P3 amplitudes were topographically analyzed and compared between groups. RESULTS There were no significant behavioral between-group differences in terms of mean reaction time, accuracy, and ANT effects alerting, orienting, and inhibition. Absolute visual P3 amplitude was not reduced in schizophrenia or depression. P3 amplitude modulation was defined as P3 amplitude at Pz as a function of ANT flanker conditions. We found a parietal P3 amplitude modulation deficit in schizophrenic patients (-.015) that was absent in both healthy controls (-.705; p = .002) and depressive patients (-1.022; p = .001). CONCLUSION The results provide evidence that a deficit of visual P3 amplitude modulation distinguishes schizophrenia from healthy and disease controls and provides greater discriminative power than absolute visual P3 amplitude.

Test-retest reliability of Attention Network Test measures in schizophrenia.

BACKGROUND The Attention Network Test (ANT) is a well established behavioral measure in neuropsychological research to assess three different facets of selective attention, i.e., alerting, orienting, and conflict processing. Although the ANT has been applied in healthy individuals and various clinical populations, data on retest reliability are scarce in healthy samples and lacking for clinical populations. The objective of the present study was a longitudinal assessment of relevant ANT network measures in healthy controls and schizophrenic patients. METHODS Forty-five schizophrenic patients and 55 healthy controls were tested with ANT in a test-retest design with an average interval of 7.4 months between test sessions. Test-retest reliability was analyzed with Pearson and Intra-class correlations. RESULTS Healthy controls revealed moderate to high test-retest correlations for mean reaction time, mean accuracy, conflict effect, and conflict error rates. In schizophrenic patients, moderate test-retest correlations for mean reaction time, orienting effect, and conflict effect were found. The analysis of error rates in schizophrenic patients revealed very low test-retest correlations. CONCLUSIONS The current study provides converging statistical evidence that the conflict effect and mean reaction time of ANT yield acceptable test-retest reliabilities in healthy controls and, investigated longitudinally for the first time, also in schizophrenia. Obtained differences of alerting and orienting effects in schizophrenia case-control studies should be considered more carefully. The analysis of error rates revealed heterogeneous results and therefore is not recommended for case control studies in schizophrenia.

Dissection of early bottom-up and top-down deficits during visual attention in schizophrenia

OBJECTIVE To characterize the interplay of bottom-up and top-down processing deficits of the early visual ERP component N1 in schizophrenia. METHODS Thirty-three schizophrenic patients and 61 healthy controls underwent a visual selective attention paradigm while 32-channel electroencephalogram was recorded. Visual N1 responses were calculated and source localization was applied. RESULTS Significant reductions of the cue N1 as well as the target N1 components were found in schizophrenia patients. Linear regression slopes for the cue N1 and for the cue-locked target N1 indicated significantly reduced early bottom-up and top-down modulation in patients relative to controls. Source analyses indicated that bottom-up as well as top-down N1 deficits in schizophrenia are associated with partially overlapping current density deficits in posterior cortex areas. Differential functional deficits were observed in right parietal lobe during bottom-up processing and in anterior cingulate cortex during top-down attention. CONCLUSIONS The results provide evidence for both early visual bottom-up and top-down deficits in schizophrenia and illustrate how disturbances in these processing streams converge on the visual N1 amplitude. SIGNIFICANCE Visual top-down disturbances in schizophrenia appear to be confounded by visual bottom-up deficits.

Exploring the time course of N170 repetition suppression: a preliminary study.

Several studies employed the repetition suppression paradigm to investigate the face-specific N170 component of the event-related potential (ERP), but yielded highly inconsistent results. Varying inter-stimulus intervals (ISIs) may account for inconsistencies between studies. This study aimed at exploring the time course of repetition suppression by systematically investigating the association between ISI and ERP adaptation. Fourteen healthy subjects were investigated with a passive face recognition paradigm using paired stimuli. Stimuli were presented for 500ms and ISIs parametrically varied between 400 and 2000ms. N170 was constructed to investigate adaptation effects on the level of perceptual face processing. We found an evidence for an asymptotic decay of repetition suppression over time with significant N170 adaptation effects only after the shortest ISI. Our results robustly demonstrate that N170 adaptation in a paired stimulus protocol critically depends on short ISIs, thereby explaining the inconsistencies observed in the previous studies. For future social cognition studies using neuronal adaptation to face stimuli, the current results provide a well defined ISI associated with a large N170 adaptation effect.

Spatiotemporal mapping of sex differences during attentional processing.

Functional neuroimaging studies have increasingly aimed at approximating neural substrates of human cognitive sex differences elicited by visuospatial challenge. It has been suggested that females and males use different behaviorally relevant neurocognitive strategies. In females, greater right prefrontal cortex activation has been found in several studies. The spatiotemporal dynamics of neural events associated with these sex differences is still unclear. We studied 22 female and 22 male participants matched for age, education, and nicotine with 29‐channel‐electroencephalogram recorded under a visual selective attention paradigm, the Attention Network Test. Visual event‐related potentials (ERP) were topographically analyzed and neuroelectric sources were estimated. In absence of behavioral differences, ERP analysis revealed a novel frontal‐occipital second peak of visual N100 that was significantly increased in females relative to males. Further, in females exclusively, a corresponding central ERP component at around 220 ms was found; here, a strong correlation between stimulus salience and sex difference of the central ERP component amplitude was observed. Subsequent source analysis revealed increased cortical current densities in right rostral prefrontal (BA 10) and occipital cortex (BA 19) in female subjects. This is the first study to report on a tripartite association between sex differences in ERPs, visual stimulus salience, and right prefrontal cortex activation during attentional processing. Hum Brain Mapp 2009.

Neurocognitive Pattern Analysis Reveals Classificatory Hierarchy of Attention Deficits in Schizophrenia

Attention deficits, among other cognitive deficits, are frequently observed in schizophrenia. Although valid and reliable neurocognitive tasks have been established to assess attention deficits in schizophrenia, the hierarchical value of those tests as diagnostic discriminants on a single-subject level remains unclear. Thus, much research is devoted to attention deficits that are unlikely to be translated into clinical practice. On the other hand, a clear hierarchy of attention deficits in schizophrenia could considerably aid diagnostic decisions and may prove beneficial for longitudinal monitoring of therapeutic advances. To propose a diagnostic hierarchy of attention deficits in schizophrenia, we investigated several facets of attention in 86 schizophrenia patients and 86 healthy controls using a set of established attention tests. We applied state-of-the-art machine learning algorithms to determine attentive test variables that enable an automated differentiation between schizophrenia patients and healthy controls. After feature preranking, hypothesis building, and hypothesis validation, the polynomial support vector machine classifier achieved a classification accuracy of 90.70% ± 2.9% using psychomotor speed and 3 different attention parameters derived from sustained and divided attention tasks. Our study proposes, to the best of our knowledge, the first hierarchy of attention deficits in schizophrenia by identifying the most discriminative attention parameters among a variety of attention deficits found in schizophrenia patients. Our results offer a starting point for hierarchy building of schizophrenia-associated attention deficits and contribute to translating these concepts into diagnostic and therapeutic practice on a single-subject level.