An altered balance of integrated and segregated brain activity is a marker of cognitive deficits following sleep deprivation.

Sleep deprivation (SD) leads to impairments in cognitive function. Here, we tested the hypothesis that cognitive changes in the sleep-deprived brain can be explained by information processing within and between large-scale cortical networks. We acquired functional magnetic resonance imaging (fMRI) scans of 20 healthy volunteers during attention and executive tasks following a regular night of sleep, a night of SD, and a recovery nap containing nonrapid eye movement (NREM) sleep. Overall, SD was associated with increased cortex-wide functional integration, driven by a rise of integration within cortical networks. The ratio of within versus between network integration in the cortex increased further in the recovery nap, suggesting that prolonged wakefulness drives the cortex towards a state resembling sleep. This balance of integration and segregation in the sleep-deprived state was tightly associated with deficits in cognitive performance. This was a distinct and better marker of cognitive impairment than conventional indicators of homeostatic sleep pressure, as well as the pronounced thalamocortical connectivity changes that occurs towards falling asleep. Importantly, restoration of the balance between segregation and integration of cortical activity was also related to performance recovery after the nap, demonstrating a bidirectional effect. These results demonstrate that intra- and interindividual differences in cortical network integration and segregation during task performance may play a critical role in vulnerability to cognitive impairment in the sleep-deprived state.

Cortical gradients of functional connectivity are robust to state-dependent changes following sleep deprivation.

Sleep deprivation leads to significant impairments in cognitive performance and changes to the interactions between large scale cortical networks, yet the hierarchical organization of cortical activity across states is still being explored. We used functional magnetic resonance imaging to assess activations and connectivity during cognitive tasks in 20 healthy young adults, during three states: (i) following a normal night of sleep, (ii) following 24hr of total sleep deprivation, and (iii) after a morning recovery nap. Situating cortical activity during cognitive tasks along hierarchical organizing gradients based upon similarity of functional connectivity patterns, we found that regional variations in task-activations were captured by an axis differentiating areas involved in executive control from default mode regions and paralimbic cortex. After global signal regression, the range of functional differentiation along this axis at baseline was significantly related to decline in working memory performance (2-back task) following sleep deprivation, as well as the extent of recovery in performance following a nap. The relative positions of cortical regions within gradients did not significantly change across states, except for a lesser differentiation of the visual system and increased coupling of the posterior cingulate cortex with executive control areas after sleep deprivation. This was despite a widespread increase in the magnitude of functional connectivity across the cortex following sleep deprivation. Cortical gradients of functional differentiation thus appear relatively insensitive to state-dependent changes following sleep deprivation and recovery, suggesting that there are no large-scale changes in cortical functional organization across vigilance states. Certain features of particular gradient axes may be informative for the extent of decline in performance on more complex tasks following sleep deprivation, and could be beneficial over traditional voxel- or parcel-based approaches in identifying realtionships between state-dependent brain activity and behavior.

Evaluation of a personalized functional near infra-red optical tomography workflow using maximum entropy on the mean.

In the present study, we proposed and evaluated a workflow of personalized near infra-red optical tomography (NIROT) using functional near-infrared spectroscopy (fNIRS) for spatiotemporal imaging of cortical hemodynamic fluctuations. The proposed workflow from fNIRS data acquisition to local 3D reconstruction consists of: (a) the personalized optimal montage maximizing fNIRS channel sensitivity to a predefined targeted brain region; (b) the optimized fNIRS data acquisition involving installation of optodes and digitalization of their positions using a neuronavigation system; and (c) the 3D local reconstruction using maximum entropy on the mean (MEM) to accurately estimate the location and spatial extent of fNIRS hemodynamic fluctuations along the cortical surface. The workflow was evaluated on finger-tapping fNIRS data acquired from 10 healthy subjects for whom we estimated the reconstructed NIROT spatiotemporal images and compared with functional magnetic resonance imaging (fMRI) results from the same individuals. Using the fMRI activation maps as our reference, we quantitatively compared the performance of two NIROT approaches, the MEM framework and the conventional minimum norm estimation (MNE) method. Quantitative comparisons were performed at both single subject and group-level. Overall, our results suggested that MEM provided better spatial accuracy than MNE, while both methods offered similar temporal accuracy when reconstructing oxygenated (HbO) and deoxygenated hemoglobin (HbR) concentration changes evoked by finger-tapping. Our proposed complete workflow was made available in the brainstorm fNIRS processing plugin-NIRSTORM, thus providing the opportunity for other researchers to further apply it to other tasks and on larger populations.

Data-driven beamforming technique to attenuate ballistocardiogram artefacts in electroencephalography-functional magnetic resonance imaging without detecting cardiac pulses in electrocardiography recordings.

Simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is a very promising non-invasive neuroimaging technique. However, EEG data obtained from the simultaneous EEG-fMRI are strongly influenced by MRI-related artefacts, namely gradient artefacts (GA) and ballistocardiogram (BCG) artefacts. When compared to the GA correction, the BCG correction is more challenging to remove due to its inherent variabilities and dynamic changes over time. The standard BCG correction (i.e., average artefact subtraction [AAS]), require detecting cardiac pulses from simultaneous electrocardiography (ECG) recording. However, ECG signals are also distorted and will become problematic for detecting reliable cardiac peaks. In this study, we focused on a beamforming spatial filtering technique to attenuate all unwanted source activities outside of the brain. Specifically, we applied the beamforming technique to attenuate the BCG artefact in EEG-fMRI, and also to recover meaningful task-based neural signals during an attentional network task (ANT) which required participants to identify visual cues and respond accurately. We analysed EEG-fMRI data in 20 healthy participants during the ANT, and compared four different BCG corrections (non-BCG corrected, AAS BCG corrected, beamforming + AAS BCG corrected, beamforming BCG corrected). We demonstrated that the beamforming approach did not only significantly reduce the BCG artefacts, but also significantly recovered the expected task-based brain activity when compared to the standard AAS correction. This data-driven beamforming technique appears promising especially for longer data acquisition of sleep and resting EEG-fMRI. Our findings extend previous work regarding the recovery of meaningful EEG signals by an optimized suppression of MRI-related artefacts.

Inter-Subject Variability of Skull Conductivity and Thickness in Calibrated Realistic Head Models.

Skull conductivity has a substantial influence on EEG and combined EEG and MEG source analysis as well as on optimized transcranial electric stimulation. To overcome the use of standard literature values, we propose a non-invasive two-level calibration procedure to estimate skull conductivity individually in a group study with twenty healthy adults. Our procedure requires only an additional run of combined somatosensory evoked potential and field data, which can be easily integrated in EEG/MEG experiments. The calibration procedure uses the P20/N20 topographies and subject-specific realistic head models from MRI. We investigate the inter-subject variability of skull conductivity and relate it to skull thickness, age and gender of the subjects, to the individual scalp P20/N20 surface distance between the P20 potential peak and the N20 potential trough as well as to the individual source depth of the P20/N20 source. We found a considerable inter-subject variability for (calibrated) skull conductivity (8.44 ± 4.84 mS/m) and skull thickness (5.97 ± 1.19 mm) with a statistically significant correlation between them (rho = 0.52). Age showed a statistically significant negative correlation with skull conductivity (rho = -0.5). Furthermore, P20/N20 surface distance and source depth showed large inter-subject variability of 12.08 ± 3.21 cm and 15.45 ± 4.54 mm, respectively, but there was no significant correlation between them. We also found no significant differences among gender subgroups for the investigated measures. It is thus important to take the inter-subject variability of skull conductivity and thickness into account by means of using subject-specific calibrated realistic head modeling.

Accuracy and spatial properties of distributed magnetic source imaging techniques in the investigation of focal epilepsy patients.

Source localization of interictal epileptiform discharges (IEDs) is clinically useful in the presurgical workup of epilepsy patients. We aimed to compare the performance of four different distributed magnetic source imaging (dMSI) approaches: Minimum norm estimate (MNE), dynamic statistical parametric mapping (dSPM), standardized low-resolution electromagnetic tomography (sLORETA), and coherent maximum entropy on the mean (cMEM). We also evaluated whether a simple average of maps obtained from multiple inverse solutions (Ave) can improve localization accuracy. We analyzed dMSI of 206 IEDs derived from magnetoencephalography recordings in 28 focal epilepsy patients who had a well-defined focus determined through intracranial EEG (iEEG), epileptogenic MRI lesions or surgical resection. dMSI accuracy and spatial properties were quantitatively estimated as: (a) distance from the epilepsy focus, (b) reproducibility, (c) spatial dispersion (SD), (d) map extension, and (e) effect of thresholding on map properties. Clinical performance was excellent for all methods (median distance from the focus MNE = 2.4 mm; sLORETA = 3.5 mm; cMEM = 3.5 mm; dSPM = 6.8 mm, Ave = 0 mm). Ave showed the lowest distance between the map maximum and epilepsy focus (Dmin lower than cMEM, MNE, and dSPM, p = .021, p = .008, p < .001, respectively). cMEM showed the best spatial features, with lowest SD outside the focus (SD lower than all other methods, p < .001 consistently) and high contrast between the generator and surrounding regions. The average map Ave provided the best localization accuracy, whereas cMEM exhibited the lowest amount of spurious distant activity. dMSI techniques have the potential to significantly improve identification of iEEG targets and to guide surgical planning, especially when multiple methods are combined.

Determining the Thyroid Gland Volume Causing Tracheal Compression: A Semiautomated 3D CT Volumetry Study.

Background and objectives: Increased thyroid gland volume (TV) may bring about tracheal compression, which is one of the causes of respiratory distress. The aim of this study was to investigate the relationship between TV and the severity of tracheal compression independent of patients' symptoms using semiautomated three-dimensional (3D) volumetry (S3DV) reconstructed from computed tomography (CT) scans. Cut-off TVs leading to different levels of tracheal narrowing were evaluated. Materials and Methods: One hundred sixty-three contrast-enhanced head and neck CT examinations were retrospectively assessed. TVs were measured by S3DV. The degree of tracheal compression was measured at the point where the greatest percent reduction in the cross-sectional area of the trachea adjacent to the thyroid gland was observed. To determine the severity of compression, the tracheal compression ratio (TCR) was defined (TCR = A1 (the narrowest cross-sectional area of trachea)/A2 (the largest cross-sectional area of trachea)). Results: The mean tracheal narrowing was 15% (TCR = 0.85 ± 0.15) in the study population. Patients with more than 15% tracheal compression had significantly higher TV values than those with less than 15% tracheal compression (p < 0.001). In addition, a significant correlation was found between TV and tracheal compression (p < 0.001). Moreover, the receiver operating characteristic (ROC) curve analysis revealed that the cut-off levels for TV that predict a tracheal narrowing of 10%, 20%, 30%, and 40% were 19.75 mL, 21.56 mL, 24.54 mL, and 30.29 mL, respectively (p < 0.05). Conclusions: This study objectively demonstrated that larger thyroid glands cause more severe compression on the trachea. The results may be helpful during the decision-making process for thyroidectomies to be performed due to compression symptoms.

Reproducibility of EEG-MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy.

Fusion of electroencephalography (EEG) and magnetoencephalography (MEG) data using maximum entropy on the mean method (MEM-fusion) takes advantage of the complementarities between EEG and MEG to improve localization accuracy. Simulation studies demonstrated MEM-fusion to be robust especially in noisy conditions such as single spike source localizations (SSSL). Our objective was to assess the reliability of SSSL using MEM-fusion on clinical data. We proposed to cluster SSSL results to find the most reliable and consistent source map from the reconstructed sources, the so-called consensus map. Thirty-four types of interictal epileptic discharges (IEDs) were analyzed from 26 patients with well-defined epileptogenic focus. SSSLs were performed on EEG, MEG, and fusion data and consensus maps were estimated using hierarchical clustering. Qualitative (spike-to-spike reproducibility rate, SSR) and quantitative (localization error and spatial dispersion) assessments were performed using the epileptogenic focus as clinical reference. Fusion SSSL provided significantly better results than EEG or MEG alone. Fusion found at least one cluster concordant with the clinical reference in all cases. This concordant cluster was always the one involving the highest number of spikes. Fusion yielded highest reproducibility (SSR EEG = 55%, MEG = 71%, fusion = 90%) and lowest localization error. Also, using only few channels from either modality (21EEG + 272MEG or 54EEG + 25MEG) was sufficient to reach accurate fusion. MEM-fusion with consensus map approach provides an objective way of finding the most reliable and concordant generators of IEDs. We, therefore, suggest the pertinence of SSSL using MEM-fusion as a valuable clinical tool for presurgical evaluation of epilepsy.

Another cause of difficult airway in an elderly patient: Tongue-base abscess.

OBJECTIVE: An abscess of the tongue base is rare, but it can be a potentially life-threatening situation in elderly patients. CASE REPORT: A 72-year-old male patient presented with mid-anterior neck swelling, odynophagia, poor oral hygiene and severe dyspnoea. After a difficult intubation, the muscles were dissected via a submental suprahyoid approach and the abscess was drained. CONCLUSION: Poor oral hygiene may predispose elderly patients to tongue-base abscesses. An early decision should be made for surgical drainage due to the risk of airway obstruction.

Chronic sialadenitis due to the stone inside the accessory duct of submandibular gland.

PURPOSE: Sialolithiasis is the most common cause of chronic sialadenitis. In this case report, intraoperative finding of an accessory submandibular duct, obstructed with stone, originating from the same gland nearby the main Warthon's duct, is presented. CASE REPORT: A 22-year-old male patient, suffering from eating-related pain and swelling in his left submandibular region, was diagnosed with left sublandibular gland sialadenitis with radiologically manifested sialolithiasis, and gland excision was advised. Surgery was performed under general anesthesia. When the full anatomical scenery was delineated before excision of the gland, we surprisingly encountered two submandibular ducts originating from ipsilateral gland, one of them was obstructed with stone. After two ducts were ligated, the gland with sialolith was excised. According to histopathologic examination, the duct obstructed with stone was identified as the accessory duct and the other one was the main Wharton's duct. Postoperative days were uneventful; no neurologic complication was observed. CONCLUSIONS: Otolaryngologists should be aware of anatomic variations of the submandibular duct(s) to avoid possible complications, especially intraoperatively, because rutine preoperative radiologic preparation does not include investigation of possible accessory ducts.

Solitary Supraclavicular Fossa Masses.

OBJECTIVE: The aim of this study is to present the diagnostic spectrum of solitary supraclavicular fossa (SCF) masses in a Turkish context. The demographic data of the patients and the effectivity of the diagnostic tools are also discussed to improve current diagnostic strategies. PATIENTS AND METHODS: The charts of patients who underwent surgical intervention for solitary SCF mass of an unknown etiology between January 2005 and January 2015 were reviewed. Patients presenting evidences of synchronous cancers and patients with a history of previous cancers were excluded. The data encompassing the demographics of the patients, the discriminative specifications, the histopathological diagnosis of the masses, and the diagnostic tools used in the workup period were noted. The descriptive data are presented and statistical analyses were performed using the Mann-Whitney test, Fisher exact test, and Chi-squared tests. RESULTS: In total, 44 male (76%) and 14 (24%) female patients were enrolled in the study. Thirty-five masses (60%) were located in the left SCF and 23 masses (40%) in the right. The masses were categorized as neoplastic (n = 31, 53%), inflammatory (n = 18, 31%), and congenital (n = 9, 16%). The 44 (76%) masses in our series were lymph nodes (LNs), and 25 (57%) of them were malign, whereas 19 (43%) were either inflammatory or benign. Male sex (P = 0.027) and the size of the mass (P = 0.017) were significantly related to malign LNs. The patients' ages and sides of the masses were not significantly different between the malign and benign LN groups. CONCLUSIONS: Lymph nodes constitute the majority of solitary SCF masses. Although imaging techniques and fine needle aspirations are routinely applied, excisional biopsies are necessary in most cases to reach an exact diagnosis and to plan a definitive treatment regime in this presented series.

Minor salivary gland neoplasms.

OBJECTIVE: This study aimed to investigate the clinical presentation, histopathologic and epidemiological aspects, as well as the treatment modalities and outcomes of patients with minor salivary gland tumors (MSGTs). SUBJECTS AND METHODS: A series of 23 patients with MSGTs were reviewed retrospectively. RESULTS: This study included 11 (48%) benign and 12 (52%) malignant tumors of minor salivary glands. Minor salivary gland tumors were more common in men (70%) than in women (30%). The mean age was 31.3 years for benign tumors and 46.3 years for malignant tumors. Pleomorphic adenoma was the most common benign tumor, followed by myoepithelioma. Mucoepidermoid carcinoma and adenoid cystic carcinoma were the most common malignant tumors. The most common symptom was a painless mass of the palate. Surgical treatment was performed in all patients. Adjuvant radiotherapy was used in 3 malignant tumors. Twenty-three patients were followed-up for a median of 5 years. Two patients with malignant tumors underwent a second surgery for postoperative local recurrence. They were successfully treated with the second surgery. CONCLUSIONS: Minor salivary gland tumors are relatively uncommon neoplasms of the head and neck region. There is limited literature on MSGTs. This study provides a versatile approach for MSGTs from demographic data and clinical presentations to treatment modalities and treatment outcomes.

NREM sleep brain networks modulate cognitive recovery from sleep deprivation.

Decrease in cognitive performance after sleep deprivation followed by recovery after sleep suggests its key role, and especially non-rapid eye movement (NREM) sleep, in the maintenance of cognition. It remains unknown whether brain network reorganization in NREM sleep stages N2 and N3 can uniquely be mapped onto individual differences in cognitive performance after a recovery nap following sleep deprivation. Using resting state functional magnetic resonance imaging (fMRI), we quantified the integration and segregation of brain networks during NREM sleep stages N2 and N3 while participants took a 1-hour nap following 24-hour sleep deprivation, compared to well-rested wakefulness. Here, we advance a new analytic framework called the hierarchical segregation index (HSI) to quantify network segregation across spatial scales, from whole-brain to the voxel level, by identifying spatio-temporally overlapping large-scale networks and the corresponding voxel-to-region hierarchy. Our results show that network segregation increased in the default mode, dorsal attention and somatomotor networks during NREM sleep compared to wakefulness. Segregation within the visual, limbic, and executive control networks exhibited N2 versus N3 sleep-specific voxel-level patterns. More segregation during N3 was associated with worse recovery of working memory, executive attention, and psychomotor vigilance after the nap. The level of spatial resolution of network segregation varied among brain regions and was associated with the recovery of performance in distinct cognitive tasks. We demonstrated the sensitivity and reliability of voxel-level HSI to provide key insights into within-region variation, suggesting a mechanistic understanding of how NREM sleep replenishes cognition after sleep deprivation.

[An evaluation of histopathological changes in ethmoid sinus mucosa after endoscopic sinus surgery]. / Endoskopik sinüs cerrahisi sonrasi etmoid sinüs mukozasindaki histopatolojik degisikliklerin degerlendirilmesi.

OBJECTIVES: This study aims to evaluate postoperative histopathological changes in ethmoid sinus mucosa in patients undergoing limited or extensive endoscopic sinus surgery (ESS) due to chronic rhinosinusitis. PATIENTS AND METHODS: A total of 120 patients (74 males, 46 females; mean age 33 years; range 18 to 56 years) with chronic rhinosinusitis who underwent limited ESS (n=40), extensive ESS (n=40) and septoplasty or septorhinoplasty (n=40) in our clinic between May 2009 and October 2010 were enrolled. The control group consisted of patients who underwent septoplasty and septorhinoplasty alone. We took samples from the anterior ethmoid sinus mucosa at postoperative sixth months for the patients who underwent ESS and intraoperatively for the control patients. Tissue slices of mucosa samples were investigated under light microscope in terms of epithelial erosion, squamous metaplasia, submucosal fibrosis, basal membrane thickening, submucosal edema and submucosal inflammation. Histopathological findings of limited and extensive ESS groups were compared to each other and the control group. RESULTS: The incidence of squamous metaplasia and submucosal fibrosis was significantly higher in extensive ESS group, compared to limited ESS group (p=0.003 and p<0.001, respectively). Both of ESS groups had significantly higher incidences of epithelial erosion, submucosal fibrosis, basal membrane thickening, submucosal edema, submucosal inflammation, compared to the control group (p<0.001). CONCLUSION: Our study results show that ethmoid sinus mucosa may be still abnormal at the postoperative sixth month following ESS, regardless of the extension of ethmoidectomy. These patients should be followed closely, as they may have recurrent rhinosinusitis in the postoperative period due to impaired mucociliary activity.

Face processing in young adults with autism and ADHD: An event related potentials study.

Background: Atypicalities in perception and interpretation of faces and emotional facial expressions have been reported in both autism and attention-deficit/hyperactivity disorder (ADHD) during childhood and adulthood. Investigation of face processing during young adulthood (18 to 25 years), a transition period to full-fledged adulthood, could provide important information on the adult outcomes of autism and ADHD. Methods: In this study, we investigated event-related potentials (ERPs) related to visual face processing in autism, ADHD, and co-occurring autism and ADHD in a large sample of young adults (N = 566). The groups were based on the Diagnostic Interview for ADHD in Adults 2.0 (DIVA-2) and the Autism Diagnostic Observation Schedule-2 (ADOS-2). We analyzed ERPs from two passive viewing tasks previously used in childhood investigations: (1) upright and inverted faces with direct or averted gaze; (2) faces expressing different emotions. Results: Across both tasks, we consistently found lower amplitude and longer latency of N170 in participants with autism compared to those without. Longer P1 latencies and smaller P3 amplitudes in response to emotional expressions and longer P3 latencies for upright faces were also characteristic to the autistic group. Those with ADHD had longer N170 latencies, specific to the face-gaze task. Individuals with both autism and ADHD showed additional alterations in gaze modulation and a lack of the face inversion effect indexed by a delayed N170. Conclusion: Alterations in N170 for autistic young adults is largely consistent with studies on autistic adults, and some studies in autistic children. These findings suggest that there are identifiable and measurable socio-functional atypicalities in young adults with autism.

Genetic Overlap Between Midfrontal Theta Signals and Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder in a Longitudinal Twin Cohort.

BACKGROUND: Cognitive control has been strongly linked to midfrontal theta (4-8 Hz) brain activity. Such control processes are known to be impaired in individuals with psychiatric conditions and neurodevelopmental diagnoses, including attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Temporal variability in theta, in particular, has been associated with ADHD, with shared genetic variance underlying the relationship. Here, we investigated the phenotypic and genetic relationships between theta phase variability, theta-related signals (the N2, error-related negativity, and error positivity), reaction time, and ADHD and ASD longitudinally in a large twin study of young adults to investigate the stability of the genetic relationships between these measures over time. METHODS: Genetic multivariate liability threshold models were run on a longitudinal sample of 566 participants (283 twin pairs). Characteristics of ADHD and ASD were measured in childhood and young adulthood, while an electroencephalogram was recorded in young adulthood during an arrow flanker task. RESULTS: Cross-trial theta phase variability in adulthood showed large positive phenotypic and genetic relationships with reaction time variability and both childhood and adult ADHD characteristics. Error positivity amplitude was negatively related phenotypically and genetically to ADHD and ASD at both time points. CONCLUSIONS: We showed significant genetic associations between variability in theta signaling and ADHD. A novel finding from the current study is that these relationships were stable across time, indicating a core dysregulation of the temporal coordination of control processes in ADHD that persists in individuals with childhood symptoms. Error processing, indexed by the error positivity, was altered in both ADHD and ASD, with a strong genetic contribution.

Is quality of life related to high autistic traits, high ADHD traits and their Interaction? Evidence from a Young-Adult Community-Based twin sample.

This study explored whether high autistic traits, high attention deficit hyperactivity disorder (ADHD) traits and their interaction were associated with quality of life (QoL) in a sample of 556 of young-adult twins (Mean age 22 years 5 months, 52% Female). Four participant groups were created: high autistic traits, high ADHD traits, high autistic/ADHD traits, and low ADHD/autistic traits. High autistic traits were associated with lower QoL across domains (physical, psychological, social, and environmental). High ADHD traits associated with lower physical, psychological, and environmental QoL. The interaction of autistic and ADHD traits was not significant in any domain. While mental health difficulties were associated with lower QoL, after accounting for mental health, most relationships between autistic traits, ADHD traits and QoL remained.

What Has Been Learned from Using EEG Methods in Research of ADHD?

Electrophysiological recording methods, including electroencephalography (EEG) and magnetoencephalography (MEG), have an unparalleled capacity to provide insights into the timing and frequency (spectral) composition of rapidly changing neural activity associated with various cognitive processes. The current chapter provides an overview of EEG studies examining alterations in brain activity in ADHD, measured both at rest and during cognitive tasks. While EEG resting state studies of ADHD indicate no universal alterations in the disorder, event-related studies reveal consistent deficits in attentional and inhibitory control and consequently inform the proposed cognitive models of ADHD. Similar to other neuroimaging measures, EEG research indicates alterations in multiple neural circuits and cognitive functions. EEG methods - supported by the constant refinement of analytic strategies - have the potential to contribute to improved diagnostics and interventions for ADHD, underlining their clinical utility.

Diffuse optical reconstructions of functional near infrared spectroscopy data using maximum entropy on the mean.

Functional near-infrared spectroscopy (fNIRS) measures the hemoglobin concentration changes associated with neuronal activity. Diffuse optical tomography (DOT) consists of reconstructing the optical density changes measured from scalp channels to the oxy-/deoxy-hemoglobin concentration changes within the cortical regions. In the present study, we adapted a nonlinear source localization method developed and validated in the context of Electro- and Magneto-Encephalography (EEG/MEG): the Maximum Entropy on the Mean (MEM), to solve the inverse problem of DOT reconstruction. We first introduced depth weighting strategy within the MEM framework for DOT reconstruction to avoid biasing the reconstruction results of DOT towards superficial regions. We also proposed a new initialization of the MEM model improving the temporal accuracy of the original MEM framework. To evaluate MEM performance and compare with widely used depth weighted Minimum Norm Estimate (MNE) inverse solution, we applied a realistic simulation scheme which contained 4000 simulations generated by 250 different seeds at different locations and 4 spatial extents ranging from 3 to 40[Formula: see text] along the cortical surface. Our results showed that overall MEM provided more accurate DOT reconstructions than MNE. Moreover, we found that MEM was remained particularly robust in low signal-to-noise ratio (SNR) conditions. The proposed method was further illustrated by comparing to functional Magnetic Resonance Imaging (fMRI) activation maps, on real data involving finger tapping tasks with two different montages. The results showed that MEM provided more accurate HbO and HbR reconstructions in spatial agreement with the main fMRI cluster, when compared to MNE.