Poor Behavioral Performance Research Articles

Investigating Working Memory Deficits in School-Age Children with Attention-Deficit/Hyperactivity Disorder: An Event-Related Potentials Study During Delayed-Match-to-Sample Task

Objective: To investigate the neural mechanisms underlying working memory (WM) deficits in children with ADHD. Method: WM was compared between thirty-four children with ADHD and thirty-four matched controls using neuropsychological tests, spatial and verbal versions of modified delayed matching-to-sample (DMTS) tasks, and the event-related potential technique. Results: Children with ADHD demonstrated poor behavioral performance, delayed P3 latencies in high-load spatial modified DMTS tasks during encoding, and delayed P2 and N2 latencies during retrieval in spatial modified DMTS tasks. In high-load verbal modified DMTS tasks during encoding, they showed a smaller P3 amplitude. Discussion: Pronounced deficits in the central executive system in children with ADHD were exhibited by neuropsychological tests and the modified DMTS task. Children with ADHD exhibited a slowing of processing speed during encoding. Under high-load conditions, they showed a reduced P3 amplitude during retrieval, suggesting reduced neural resource allocation was available when the central executive of the working memory was heavily loaded.

EEG Information Transfer Changes in Different Daily Fatigue Levels During Drowsy Driving.

A significant issue for traffic safety has been drowsy driving for decades. A number of studies have investigated the effects of acute fatigue on spectral power; and recent research has revealed that drowsy driving is associated with a variety of brain connections in a specific cortico-cortical pathway. In spite of this, it is still unclear how different brain regions are connected in drowsy driving at different levels of daily fatigue. This study identified the brain connectivity-behavior relationship among three different daily fatigue levels (low-, median- and high-fatigue) with the EEG data transfer entropy. According to the results, only low- and medium-fatigue groups demonstrated an inverted U-shaped change in connectivity from high performance to poor behavioral performance. In addition, from low- to high-fatigue groups, connectivity magnitude decreased in the frontal region and increased in the occipital region. These study results suggest that brain connectivity and driving behavior would be affected by different levels of daily fatigue.

Evaluation of the transverse aortic constriction model in ICR and C57BL/6J mice.

Transverse aortic constriction (TAC) is a frequently used model to investigate pressure overload-induced progressive heart failure (HF); however, there is considerable phenotypic variation among different mouse strains and even sub-strains. Moreover, less is known about the TAC model in ICR mice. Therefore, to determine the suitability of the ICR strain for TAC-induced HF research, we compared the effects of TAC on ICR and C57BL/6J mice at one, two and fourweeks post-TAC via echocardiography, organ index, morphology, and histology. At the end of the study, behavior and gene expression patterns were assessed, and overall survival was monitored. Compared to the sham-operated mice, ICR and C57BL/6J mice displayed hypertrophic phenotypes with a significant increase in ventricle wall thickness, heart weight and ratio, and cross-sectional area of cardiomyocytes after a 2-week TAC exposure. In addition, ICR mice developed reduced systolic function and severe lung congestion 4weeks post-TAC, whereas C57BL/6J did not. Besides, ICR mice demonstrated comparable survival, similar gene expression alteration but severer fibrotic remodeling and poor behavioral performance compared to the C57BL/6J mice. Our data demonstrated that ICR was quite sensitive to TAC-induced heart failure and can be an ideal research tool to investigate mechanisms and drug intervention for pressure overload-induced HF.

Electroacupuncture Alleviates Neuropathic Pain through Regulating miR-206-3p Targeting BDNF after CCI.

Background Electroacupuncture (EA) has benefits for neuropathic pain. However, the underlying mechanisms are still unknown. The current study explores the underlying mechanisms of EA in neuropathic pain of chronic constriction injury (CCI) rats. Material/Methods. Overall, 126 Sprague-Dawley (200-250 g) rats were divided into nine groups randomly: the sham-operated, CCI, CCI+EA, CCI+sham EA, CCI+NS, CCI+AAV-NC, CCI+AAV-miR-206-3p, CCI+EA+NS, and CCI+EA+AAV-miR-206-3p groups. The animals were sacrificed 14 days postsurgery. Mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWL) tests were used to determine differences in neurobehavioral manifestations. qPCR, western blotting, and immunofluorescence (IF) were carried out to detect the expression levels of miR-206-3p, BDNF, BAX/Bcl-2, TNF-α, and IL-6. Nissl staining was measured to observe morphological changes in neurons. Transmission electron microscopy (TEM) was employed to evaluate microscopic changes in dorsal horn synapses. Results Hyperalgesia was reduced markedly by EA in the CCI model. The expression level of miR-206-3p was elevated, whereas the expression levels of BDNF, BAX/Bcl-2, TNF-α, and IL-6 were decreased in EA-treated CCI rats. However, a miR-206-3p inhibitor partially abrogated the analgesic effect of EA and resulted in poor behavioral performance and the BDNF, BAX/Bcl-2, TNF-α, and IL-6 expression was elevated as well. Conclusions EA can relieve neuropathic pain by regulating the miR-206-3p/BDNF pathway, thus exerting anti-inflammatory and antiapoptotic effect.

Cortical low-frequency power correlates with behavioral impairment in animal model of focal limbic seizures.

Impairment in consciousness is a debilitating symptom during and after seizures; however, its mechanism remains unclear. Limbic seizures have been shown to spread to arousal circuitry to result in a "network inhibition" phenomenon. However, prior animal model studies did not relate physiological network changes to behavioral responses during or following seizures. Focal onset limbic seizures were induced while rats were performing an operant conditioned behavioral task requiring response to an auditory stimulus to quantify how and when impairment of behavioral response occurs. Correct responses were rewarded with sucrose. Cortical and hippocampal electrophysiology measured by local field potential recordings was analyzed for changes in low- and high-frequency power in relation to behavioral responsiveness during seizures. As seen in patients with seizures, ictal (p<.0001) and postictal (p=.0015) responsiveness was variably impaired. Analysis of cortical and hippocampal electrophysiology revealed that ictal (p=.002) and postictal (p=.009) frontal cortical low-frequency 3-6-Hz power was associated with poor behavioral performance. In contrast, the hippocampus showed increased power over a wide frequency range during seizures, and suppression postictally, neither of which were related to behavioral impairment. These findings support prior human studies of temporal lobe epilepsy as well as anesthetized animal models suggesting that focal limbic seizures depress consciousness through remote network effects on the cortex, rather than through local hippocampal involvement. By identifying the cortical physiological changes associated with impaired arousal and responsiveness in focal seizures, these results may help guide future therapies to restore ictal and postictal consciousness, improving quality of life for people with epilepsy.

Load-dependent relationships between frontal fNIRS activity and performance: A data-driven PLS approach

Neuroimaging research frequently demonstrates load-dependent activation in prefrontal and parietal cortex during working memory tasks such as the N-back. Most of this work has been conducted in fMRI, but functional near-infrared spectroscopy (fNIRS) is gaining traction as a less invasive and more flexible alternative to measuring cortical hemodynamics. Few fNIRS studies, however, have examined how working memory load-dependent changes in brain hemodynamics relate to performance. The current study employs a newly developed and robust statistical analysis of task-based fNIRS data in a large sample, and demonstrates the utility of data-driven, multivariate analyses to link brain activation and behavior in this modality. Seventy participants completed a standard N-back task with three N-back levels (N = 1, 2, 3) while fNIRS data were collected from frontal and parietal cortex. Overall, participants showed reliably greater fronto-parietal activation for the 2-back versus the 1-back task, suggesting fronto-parietal fNIRS measurements are sensitive to differences in cognitive load. The results for 3-back were much less consistent, potentially due to poor behavioral performance in the 3-back task. To address this, a multivariate analysis (behavioral partial least squares, PLS) was conducted to examine the interaction between fNIRS activation and performance at each N-back level. Results of the PLS analysis demonstrated differences in the relationship between accuracy and change in the deoxyhemoglobin fNIRS signal as a function of N-back level in eight mid-frontal channels. Specifically, greater reductions in deoxyhemoglobin (i.e., more activation) were positively related to performance on the 3-back task, unrelated to accuracy in the 2-back task, and negatively associated with accuracy in the 1-back task. This pattern of results suggests that the metabolic demands correlated with neural activity required for high levels of accuracy vary as a consequence of task difficulty/cognitive load, whereby more automaticity during the 1-back task (less mid-frontal activity) predicted superior performance on this relatively easy task, and successful engagement of this mid-frontal region was required for high accuracy on a more difficult and cognitively demanding 3-back task. In summary, we show that fNIRS activity can track working memory load and can uncover significant associations between brain activity and performance, thus opening the door for this modality to be used in more wide-spread applications.

Auditory attention tracking states in a cocktail party environment can be decoded by deep convolutional neural networks

Objective. A deep convolutional neural network (CNN) is a method for deep learning (DL). It has a powerful ability to automatically extract features and is widely used in classification tasks with scalp electroencephalogram (EEG) signals. However, the small number of samples and low signal-to-noise ratio involved in scalp EEG with low spatial resolution constitute a limitation that might restrict potential brain-computer interface (BCI) applications that are based on the CNN model. In the present study, a novel CNN model with source-spatial feature images (SSFIs) as the input is proposed to decode auditory attention tracking states in a cocktail party environment. Approach. We first extract SSFIs using rhythm entropy and weighted minimum norm estimation. Next, we develop a CNN model with three convolutional layers. Furthermore, we estimate the performance of the proposed model via generalized performance, alternative models that deleted or replaced a model’s component, and loss curves. Finally, we use a deep transfer model with fine-tuning for a low (poor) behavioral performance group (L-group). Main results. Based on cortical activity reconstructions from the scalp EEGs, the classification accuracy (CA) of the proposed model is 80.4% (chance level: 52.5%), which is superior to that achieved by scalp EEG. Additionally, the performance of the proposed model is more stable when compared to alternative models that delete or replace specific model components. The proposed model identifies the difference between two auditory attention tracking states (successful versus unsuccessful) at an early stage with a short time window (250 ms after target offset). Furthermore, we propose a deep transfer learning model to improve the classification for the L-group. With this model, the CA of the L-group significantly increase by 5.3%. Significance. Our proposed model improves the performance of a decoder for auditory attention tracking, which could be suitable for relieving the difficulty with the attentional modulation of individual’s neural responses. It provides a novel communication channel with auditory cognitive BCI for patients with attention and hearing impairment.

Relation between cortical auditory evoked potentials and behavioral auditory discrimination in cochlear implant children

Abstract Background Cochlear implants (CI) can partially or totally revert the effects of sensory deprivation; thus enabling the development of auditory abilities. However, there remains a large amount of variability in speech perception outcome among CI users. Such variability may be attributed to the children’s diverse capabilities in detecting amplitude, temporal and spectral changes in the incoming complex speech signals in quiet and in difficult listening situations. Objective To study whether the newly introduced Acoustic Change Complex (ACC) cortical potential using short duration can be used to document such variability. If used as a tool for cortical discrimination, it will aid in evaluating young children who cannot be tested using behavioral measures. Patients and Methods Cortical auditory evoked potentials were recorded in forty five unilaterally-implanted children ranging in age from 6 to 12 years. Stimuli used to elicit ACC were short duration (500 msec.) speech and tonal stimuli. Spectral change was done using /i/ to /u/ vowels, while temporal change was done using variable gaps-in-1000 Hz tone, ranging from 5 msec. to 200 msec. Auditory evoked responses were compared to behavioral tests which included speech perception test (PBKG) and psychophysical test for temporal resolution. Results ACC potentials were successfully recorded in most of the children evaluated. Generally, ACC were significantly highly detected in temporal changes than spectral change. Individual data showed that poor behavioral performance was associated with higher ACC detection thresholds to gap in tone and poorer % detection to vowel change. Conclusion: ACC potential using short duration stimuli can be recorded in young implanted children in an ordinary clinical setting. However, more research is needed to document the complex behavioral-objective relationship and its ultimate link to speech perception and language development in young CI recipients.

Cognitive Modeling Informs Interpretation of Go/No-Go Task-Related Neural Activations and Their Links to Externalizing Psychopathology

BackgroundIndividuals with attention-deficit/hyperactivity disorder and other externalizing psychopathologies tend to display poor behavioral performance on the go/no-go task, which is thought to reflect deficits in inhibitory control. However, clinical neuroimaging studies using this task have yielded conflicting results, raising basic questions about what the task measures and which aspects of the task relate to clinical outcomes. We used computational modeling to provide a clearer understanding of how neural activations from this task relate to the cognitive mechanisms that underlie performance and to probe the implications of these relationships for clinical research. MethodsA total of 143 young adults (8–21 years of age) performed the go/no-go task during functional magnetic resonance imaging scanning. We used the diffusion decision model (DDM), a cognitive modeling approach, to quantify distinct neurocognitive processes that underlie go/no-go performance. We then assessed correlations between DDM parameters and brain activation from standard go/no-go contrasts and assessed relationships of DDM parameters and associated neural measures with clinical ratings. ResultsRight-lateralized prefrontal activations on correct inhibition trials, which are generally assumed to isolate neural processes involved in inhibition, were unrelated to DDM parameters (and other performance indices). However, responses to failed inhibitions in brain regions associated with error monitoring were strongly related to more efficient task performance and correlated with externalizing behavior and attention-deficit/hyperactivity disorder symptoms. ConclusionsOur findings cast doubt on conventional interpretations of go/no-go task-related activations as reflecting the neural basis of inhibitory functioning. We instead found evidence that error-related contrasts provide clinically relevant information about neural systems involved in monitoring and optimizing the efficiency of cognitive performance.

THE CEREBELLUM MAY MITIGATE OBESITY-DRIVEN COGNITIVE IMPAIRMENT IN LATE LIFE

Mice that overexpress mutant human tau in forebrain neurons develop many features of Alzheimer’s disease (AD), including behavioral impairments and neurodegeneration by 5 months of age. While an appropriate model to study AD-like pathology, the transgene’s high neurotoxicity makes it difficult to investigate how aging impacts AD onset and progression. The removal of endogenous mouse tau decreases the transgene’s neurotoxicity in young mice, which has allowed us to age mice to 20 months of age and investigate behavior at a more AD-relevant stage of life. Interestingly, the tau transgenic mice show increased discrimination between familiar and unfamiliar objects than non-transgenic littermates (p = 0.02) suggesting tau transgenic mice have better memory. The transgenic mice also displayed increased physical activity in the Open Field Test than non-transgenic littermates (distance traveled, p = 0.0102, and gait speed, p = 0.0219). Their improved behavioral performance occurred despite significant forebrain atrophy (20% smaller, p=0.0003). Interestingly, the non-transgenic control mice lacking endogenous mouse tau developed insulin resistance and obesity, and had significantly smaller cerebellum than transgenic mice (10% smaller, p = 0.0007). These data suggest that insulin resistance and obesity contribute more profoundly to poor behavioral performance than forebrain neurodegeneration. Moreover our study suggests that the cerebellum, recognized primarily for its role in coordination and motor function, may be an important mediator of late life cognitive function, especially in the presence of insulin resistance and obesity.

Epigenetic Control of CDK5 Promoter Regulates Diabetes-Associated Development of Alzheimer's Disease.

Cyclin-dependent kinase-5 (CDK5) is activated by p35 and then binds to both p35 and its truncated form p25 to promote hyperphosphorylation of tau protein, thereby facilitating the pathological progression of Alzheimer's disease (AD). However, it is unknown whether a patient's diabetic status promotes the later onset of AD in a CDK5-dependent manner. Here, we induced pro-diabetic insulin resistance and glucose intolerance in rats using a combined high fat and high glucose diet. Compared to normal diet-fed rats, these pro-diabetic rats exhibited poorer behavioral performance in the Morris water maze test and the novel object recognition test. Increased phosphorylation of tau protein was detected in the hippocampal CA1 region of the rat brain, suggesting neurodegeneration. Moreover, CDK5 transcriptional activity was significantly increased in the HFGD-rat brain, likely resulting from an increase in acetylation and a decrease in methylation of the CDK5 promoter. Together, these data suggest that epigenetic control of the CDK5 promoter by acetylation and methylation may regulate the diabetes-associated development of AD.

Characterizing neurocognitive markers of familial risk for depression using multi-modal imaging, behavioral and self-report measures

BackgroundMajor depressive disorder (MDD) is associated with poorer behavioral performance in domains of working memory and associated cognitive systems for cognitive control and attention. Functional neuroimaging studies show altered functioning in MDD in frontal executive control circuits implicated in these cognitive processes. It is not yet known whether poor cognitive performance involving these circuits is part of the familial risk for MDD, and we addressed this issue using a multi-modal imaging, behavioral and self-report approach in unaffected first-degree relatives of parent probands with MDD. Methods72 unaffected adult first-degree relatives of probands with MDD (mean age 30.5 ± 13.4 years) with and 66 case-wise matched non-relative controls underwent functional magnetic resonance imaging during performance of ‘n-back’ working memory task, a Go/No-go task assessing cognitive control and an Auditory Oddball test of selective attention. Groups were compared on imaging data analyzed voxel wise with a focus on dorsolateral prefrontal cortex, anterior cingulate cortex and insula regions of interest, and on corresponding behavioral accuracy and reaction time data. Symptoms were assessed using self-report scales. ResultsRelatives were distinguished by comparatively decreased activation in the left dorsolateral prefrontal cortex (DLPFC) during updating of working memory. Behaviorally, relatives also showed more errors of omission during working memory updating. DLPFC hypo-activation was associated with greater depressive symptom severity. ConclusionsDeficits in cognitive processing may be part of the profile of familial risk for depression, preceding illness onset, specifically in the domain of working memory.

EEG Multiscale Complexity in Schizophrenia During Picture Naming.

Introduction: Patients with schizophrenia show cognitive deficits that are evident both behaviourally and with EEG recordings. Recent studies have suggested that non-linear analyses of EEG might more adequately reflect the complex, irregular, non-stationary behavior of neural processes than more traditional ERP measures. Non-linear analyses have been mainly applied to EEGs from patients at rest, whereas differences in complexity might be more evident during task performance.Objective: We aimed to investigate changes in non-linear brain dynamics of patients with schizophrenia during cognitive processing.Method: 18 patients and 17 matched healthy controls were asked to name pictures. EEG data were collected at rest and while they were performing a naming task. EEGs were analyzed with the classical Lempel-Ziv Complexity (LZC) and with the Multiscale LZC. Electrodes were grouped in seven regions of interest (ROI).Results: As expected, controls had fewer naming errors than patients. Regarding EEG complexity, the interaction between Group, Task and ROI indicated that patients showed higher complexity values in right frontal regions only at rest, where no differences in complexity between patients and controls were found during the naming task. EEG complexity increased from rest to task in controls in left temporal-parietal regions, while no changes from rest to task were observed in patients. Finally, differences in complexity between patients and controls depended on the frequency bands: higher values of complexity in patients at rest were only observed in fast bands, indicating greater heterogeneity in patients in local dynamics of neuronal assemblies.Conclusion: Consistent with previous studies, schizophrenic patients showed higher complexity than controls in frontal regions at rest. Interestingly, we found different modulations of brain complexity during a simple cognitive task between patients and controls. These data can be interpreted as indicating schizophrenia-related failures to adapt brain functioning to the task, which is reflected in poorer behavioral performance.Highlights: - We measured classical and multiscale Lempel-Ziv Complexity (LZCN and MLZC) of the EEG signal of patients with schizophrenia and controls at rest and while performing a cognitive task. - We found that patients and controls showed a different pattern of brain complexity depending on their cognitive state (at rest or under cognitive challenge). - Our results illustrate the value of the MLZC in the characterization of the pattern of brain complexity in schizophrenia on function of frequency bands. - Nonlinear methodologies of EEG analysis can help to characterize brain dysfunction in schizophrenia.

Sense, the single neuron, and multi-dimensional stimuli

Sensory processing disorders are characterized by poor behavioral performance in psychophysical tasks relative to the general population. To assess the etiology of those deficits, a tempting possibility is to look for abnormalities in the information available in responses of specific groups of neurons, which could then become the target of rehabilitation. I discuss here basic limitations in linking behavioral performance to neuronal responses. Our understanding of sensory neurons comes from measuring tuning curves, which describe how the response varies when a dimension of the stimulus is varied. In reality, however, neural responses are modulated by many stimulus features, e.g., in the auditory system: amplitude and spectrum of the stimulus, spatial position, temporal properties, etc. I illustrate the challenges that this tuning heterogeneity raises when trying to predict results of behavioral experiments from neuronal responses. I first exhibit effects in theory using Fisher Information, then analyze explicit optimal decoders trained to estimate spectral and spatial properties of an auditory stimulus from neural responses. I show how heterogeneity in tuning is a major contributor to the robustness of the encoding of multiple stimulus dimensions. Finally, I described how this changes the interpretation of neural constraints on behavioral acuity.

Association between subjective tinnitus and cognitive performance: protocol for systematic review and meta-analysis

IntroductionSubjective tinnitus is very common and has a number of comorbid associations including depression, sleep disturbance and concentration difficulties. Concentration difficulties may be observable in people with tinnitus through poorer...

Age-Related Changes in Global Motion Coherence: Conflicting Haemodynamic and Perceptual Responses

Our aim was to use both behavioural and neuroimaging data to identify indicators of perceptual decline in motion processing. We employed a global motion coherence task and functional Near Infrared Spectroscopy (fNIRS). Healthy adults (n = 72, 18–85) were recruited into the following groups: young (n = 28, mean age = 28), middle-aged (n = 22, mean age = 50), and older adults (n = 23, mean age = 70). Participants were assessed on their motion coherence thresholds at 3 different speeds using a psychophysical design. As expected, we report age group differences in motion processing as demonstrated by higher motion coherence thresholds in older adults. Crucially, we add correlational data showing that global motion perception declines linearly as a function of age. The associated fNIRS recordings provide a clear physiological correlate of global motion perception. The crux of this study lies in the robust linear correlation between age and haemodynamic response for both measures of oxygenation. We hypothesise that there is an increase in neural recruitment, necessitating an increase in metabolic need and blood flow, which presents as a higher oxygenated haemoglobin response. We report age-related changes in motion perception with poorer behavioural performance (high motion coherence thresholds) associated with an increased haemodynamic response.

Probabilistic Category Learning and Striatal Functional Activation in Psychosis Risk.

Psychosis risk is associated with striatal dysfunction, including a previous behavioral study that found that psychosis risk is associated with impaired performance on a probabilistic category learning task (PCLT; ie, the Weather Prediction Task), a task strongly associated with striatal activation. The current study examined whether psychosis risk based on symptom levels was associated with both poor behavioral performance and task-related physiological dysfunction in specific regions of the striatum while performing the PCLT. There were 2 groups of participants: psychosis risk (n = 21) who had both (a) extreme levels of self-reported psychotic-like beliefs and experiences and (b) interview-rated current attenuated psychotic symptoms (APS); and a comparison group (n = 20) who had average levels of self-reported psychotic-like beliefs and experiences. Participants completed the PCLT during fMRI scanning. The current research replicated previous work finding behavioral PCLT deficits at the end of the task in psychosis risk. Furthermore, as expected, the psychosis risk group exhibited decreased striatal activation on the task, especially in the associative striatum. The psychosis risk group also displayed decreased activation in a range of cortical regions connected to the associative striatum. In contrast, the psychosis risk group exhibited greater activation predominantly in cortical regions not connected to the associative striatum. Psychosis risk was associated with both behavioral and striatal dysfunction during performance on the PCLT, suggesting that behavioral and imaging measures using this task could be a marker for psychosis risk.

The Synergy of Aging and LPS Exposure in a Mouse Model of Parkinson’s Disease

Aging is an inevitable physiological challenge occurring in organisms over time, and is also the most important risk factor of neurodegenerative diseases. In this study, we observed cellular and molecular changes of different age mice and LPS-induced Parkinson disease (PD) model. The results showed that behavioral performance and dopaminergic (DA) neurons were declined, accompanied by increased expression of pro-inflammatory factors (TLR2, p-NF-kB-p65, IL-1β and TNF-α), as well as pro-oxidative stress factor gp91phox in aged mice compared with young mice. Aging exaggerated inflammatory M1 microglia, and destroyed the balance between oxidation and anti-oxidation. The intranasal LPS instillation induced PD model in both young and aged mice. The poor behavioral performance and the loss of DA neurons as well as TLR2, p-NF-kB-p65, IL-1β, TNF-α, iNOS and gp91phox were further aggravated in LPS-aged mice. Interestingly, the expression of Nrf2 and HO-1 was up-regulated by LPS only in young LPS-PD mice, but not in aged mice. The results indicate that the synergy of aging process and LPS exposure may prominently aggravate the DA neurons loss caused by more serious neuroinflammation and oxidative stress in the brain.

Electrophysiological and Behavioral Evidence of Reduced Binaural Temporal Processing in the Aging and Hearing Impaired Human Auditory System.

A person’s ability to process temporal fine structure information is indispensable for speech understanding. As speech understanding typically deteriorates throughout adult life, this study aimed to disentangle age and hearing impairment (HI)-related changes in binaural temporal processing. This was achieved by examining neural and behavioral processing of interaural phase differences (IPDs). Neural IPD processing was studied electrophysiologically through steady-state activity in the electroencephalogram evoked by periodic changes in IPDs over time, embedded in the temporal fine structure of acoustic stimulation. In addition, behavioral IPD discrimination thresholds were determined for the same stimuli. To disentangle potential effects of age from those of HI, both measures were applied to six participant groups: young, middle-aged, and older persons, with either normal hearing or sensorineural HI. All participants passed a cognitive screening, and stimulus audibility was controlled for in participants with HI. The results demonstrated that HI changes neural processing of binaural temporal information for all age-groups included in this study. These outcomes were revealed, superimposed on age-related changes that emerge between young adulthood and middle age. Poorer neural outcomes were also associated with poorer behavioral performance, even though the behavioral IPD discrimination thresholds were affected by age rather than by HI. The neural outcomes of this study are the first to evidence and disentangle the dual load of age and HI on binaural temporal processing. These results could be a valuable first step toward future research on rehabilitation.

P383 Multiscale lempel-ZIV complexity in schizophrenia at rest and while performing a naming task

Schizophrenic patients show cognitive deficits which are evident in EEG measures. Recent studies have suggested that non-linear EEG indexes might more adequately reflect the complex, irregular, nonstationary behavior of neural processes in schizophrenia than more traditional ERP measures (Fernandez et al., 2011). So far, non-linear analyses have mainly been performed to EEGs from patients at rest, whereas differences in complexity might be more evident during task performance. In addition, most studies have explored complexity at a single time scale. Objective We aimed to investigate changes in nonlinear multiscale brain dynamics in schizophrenic patients during cognitive processing. Method 18 patients and 17 matched healthy controls were asked to name pictures. EEG data were collected at rest and while they were performing the task. EEGs were analyzed with the classical and the multiscale Lempel-Ziv Complexity. Electrodes were grouped in seven regions of interest (ROI). Results Controls had fewer naming errors than patients. More importantly, we found greater complexity values for patients than for controls in right frontal regions, at rest. The interaction between Group, Task and ROI indicated that differences between patients and controls were more evident when performing the task, with increments in brain complexity in left temporal parietal regions, only in the control group. Conclusions We found different modulations of brain complexity during a simple cognitive task between patients and controls. These data can be interpreted as a failure of patients to adapt their brain functioning to the task, which reflect in poorer behavioral performance.