Fiberless, Multi-Channel fNIRS-EEG System Based on Silicon Photomultipliers: Towards Sensitive and Ecological Mapping of Brain Activity and Neurovascular Coupling

Portable neuroimaging technologies can be employed for long-term monitoring of neurophysiological and neuropathological states. Functional Near-Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) are highly suited for such a purpose. Their multimodal integration allows the evaluation of hemodynamic and electrical brain activity together with neurovascular coupling. An innovative fNIRS-EEG system is here presented. The system integrated a novel continuous-wave fNIRS component and a modified commercial EEG device. fNIRS probing relied on fiberless technology based on light emitting diodes and silicon photomultipliers (SiPMs). SiPMs are sensitive semiconductor detectors, whose large detection area maximizes photon harvesting from the scalp and overcomes limitations of fiberless technology. To optimize the signal-to-noise ratio and avoid fNIRS-EEG interference, a digital lock-in was implemented for fNIRS signal acquisition. A benchtop characterization of the fNIRS component showed its high performances with a noise equivalent power below 1 pW. Moreover, the fNIRS-EEG device was tested in vivo during tasks stimulating visual, motor and pre-frontal cortices. Finally, the capabilities to perform ecological recordings were assessed in clinical settings on one Alzheimer's Disease patient during long-lasting cognitive tests. The system can pave the way to portable technologies for accurate evaluation of multimodal brain activity, allowing their extensive employment in ecological environments and clinical practice.

Parsing the Flanker task to reveal behavioral and oscillatory correlates of unattended conflict interference

Stimulus-Response conflict is generated by an overlap between stimulus and response dimensions, but the intrinsic nature of this interaction is not yet deeply clarified. In this study, using a modified Eriksen flanker task, we have investigated how flankers have to be incongruent to target in order to produce an interference and whether and how this interference interacts with the one produced by Stimulus features overlap. To these aims, an Eriksen-like task employing oriented hands\arrows has been designed to distinguish between two types of Stimulus-Response (S-R) interferences: one derived by a short-term association and one based on automatic processes. Stimulus-Stimulus (S-S) conflict has been also included in the same factorial design. Behavioral, Event Related Potential (ERP) and oscillatory activity data have been measured. Results revealed distinct S-S and automatic S-R effects on behavioral performance. ERP and Theta band power modulation results suggested an early frontal S-S conflict processing followed by a posterior simultaneous S-S and automatic S-R conflict processing. These findings provide evidence that, in presence of different conflicts, the sequence of stimulus identification and response selection could not move forward in a linear serial direction, but it may involve further effort, mirrored in posterior late components and response time prolongation.

Hilbert spectral analysis of EEG data reveals spectral dynamics associated with microstates

BACKGROUND

This study addresses an ongoing debate, i.e. whether microstates have a relation to specific oscillations or frequency bands. The previous literature on this has been inconclusive. Due to stochastic calculation of microstates it is important to address this issue because instead of providing further insights, it might lead us to ambiguous interpretations.

NEW METHOD

Here we propose a new method that allows to remove the time-frequency trade-off, which hampered previous works, using Empirical Mode Decomposition (EMD) and the AM-FM model. The method is applied to two resting-state EEG datasets.

RESULTS

First, our analysis confirmed that, indeed, when overlooking time-dependence in frequency domain, the results are inconclusive and consequently, highlighted the importance of preserving time-information in the spectral domain. Second, it is confirmed using synthetic data that the local peaks in global field potential (GFP) waveform are influenced by spectral powers present in composite signals. Based on synthetic results, it is inferred that in our dataset, an average frequency range of 10-15 Hz dominates the formation and the temporal dynamics of microstates. Third, it is shown that multiple overlapping patterns of synchronized activities described by a single meta-process in full band microstate studies can be identified using the proposed frequency-band subdivision. The results are consistent across both datasets.

CONCLUSION

This study opens several new ventures to be explored in the future: e.g. analysis of temporally overlapping patterns described so far by single topographic patterns, which we show to be spectrally differentiable via band-wise topographic segmentation proposed in the present study.

Autonomic impairment in Alzheimer's disease is revealed by complexity analysis of functional thermal imaging signals during cognitive tasks

OBJECTIVE

Alzheimer's disease (AD) is characterized by progressive memory failures and visuospatial impairment. Moreover, AD can be accompanied by autonomic system alterations, which, among other impacts, affect thermoregulatory activity. We here investigate differences in autonomic activity between AD patients and healthy controls (HC), employing a complexity analysis of functional infrared imaging (fIRI) data acquired at rest and during the execution of clinical cognitive and mnemonic tests.

APPROACH

fIRI allows for contactless monitoring of autonomic activity and its thermoregulatory expression without interfering with the psychophysiological state of the subject, preserving free interaction with the doctor. The signal complexity analysis, based on the sample entropy, was compared to a standard frequency-based analysis of autonomic-related signals.

MAIN RESULTS

AD patients exhibited lower complexity of fIRI signals during the tests, which could be indicative of a stronger sympathetic activity with respect to HC. No significant effects were found at rest. No differences were found on employing frequency-based analysis.

SIGNIFICANCE

This study confirms that AD patients may exhibit peculiar autonomic responses associated with the execution of cognitive tasks that can be measured through fIRI. Moreover, these responses could be highlighted by a nonlinear metric of signal predictability such as the sample entropy establishing autonomic impairment of AD patients.

EEG microstates distinguish between cognitive components of fluid reasoning

Fluid reasoning is considered central to general intelligence. How its psychometric structure relates to brain function remains poorly understood. For instance, what is the dynamic composition of ability-specific processes underlying fluid reasoning? We investigated whether distinct fluid reasoning abilities could be differentiated by electroencephalography (EEG) microstate profiles. EEG microstates specifically capture rapidly altering activity of distributed cortical networks with a high temporal resolution as scalp potential topographies that dynamically vary over time in an organized manner. EEG was recorded simultaneously with functional magnetic resonance imaging (fMRI) in twenty healthy adult participants during cognitively distinct fluid reasoning tasks: induction, spatial relationships and visualization. Microstate parameters successfully discriminated between fluid reasoning and visuomotor control tasks as well as between the fluid reasoning tasks. Mainly, microstate B coverage was significantly higher during spatial relationships and visualization, compared to induction, while microstate C coverage was significantly decreased during spatial relationships and visualization, compared to induction. Additionally, microstate D coverage was highest during spatial relationships and microstate A coverage was most strongly reduced during the same condition. Consistently, multivariate analysis with a leave-one-out cross-validation procedure accurately classified the fluid reasoning tasks based on the coverage parameter. These EEG data and their correlation with fMRI data suggest that especially the tasks most strongly relying on visuospatial processing modulated visual and default mode network activity. We propose that EEG microstates can provide valuable information about neural activity patterns with a dynamic and complex temporal structure during fluid reasoning, suggesting cognitive ability-specific interplays between multiple brain networks.

Deep Convolutional Neural Networks for Feature-Less Automatic Classification of Independent Components in Multi-Channel Electrophysiological Brain Recordings

OBJECTIVE

Interpretation of the electroencephalographic (EEG) and magnetoencephalographic (MEG) signals requires off-line artifacts removal. Since artifacts share frequencies with brain activity, filtering is insufficient. Blind source separation, mainly through independent component analysis (ICA), is the gold-standard procedure for the identification of artifacts in multi-dimensional recordings. However, a classification of brain and artifactual independent components (ICs) is still required. Since ICs exhibit recognizable patterns, classification is usually performed by experts' visual inspection. This procedure is time consuming and prone to errors. Automatic ICs classification has been explored, often through complex ICs features extraction prior to classification. Relying on deep-learning ability of self-extracting the features of interest, we investigated the capabilities of convolutional neural networks (CNNs) for off-line, automatic artifact identification through ICs without feature selection.

METHODS

A CNN was applied to spectrum and topography of a large dataset of few thousand samples of ICs obtained from multi-channel EEG and MEG recordings acquired during heterogeneous experimental settings and on different subjects. CNN performances, when applied to EEG, MEG, and combined EEG and MEG ICs, were explored and compared with state-of-the-art feature-based automatic classification.

RESULTS

Beyond state-of-the-art automatic classification accuracies were demonstrated through cross validation (92.4% EEG, 95.4% MEG, 95.6% EEG+MEG).

CONCLUSION

High CNN classification performances were achieved through heuristical selection of machinery hyperparameters and through the CNN self-selection of the features of interest.

SIGNIFICANCE

Considering the large data availability of multi-channel EEG and MEG recordings, CNNs may be suited for classification of ICs of multi-channel brain electrophysiological recordings.

Circadian Rhythms in Fractal Features of EEG Signals

Time-of-day modulations affect both performance on a wide range of cognitive tasks and electrical activity of the brain, as recorded by electroencephalography (EEG). The aim of this work was to identify fluctuations of fractal properties of EEG time series due to circadian rhythms. In twenty-one healthy volunteers (all males, age between 20 and 30 years, chronotype: neutral type) high density EEG recordings at rest in open and closed eyes conditions were acquired in 4 times of the day (8.00 a.m., 11.30 a.m., 2.30 p.m., 7.00 p.m.). A vigilance task (Psychomotor Vigilance Test, PVT) was also performed. Detrended fluctuation Analysis (DFA) of envelope of alpha, beta and theta rhythms was performed, as well as Highuchi fractal dimension (HFD) of the whole band EEG. Our results evidenced circadian fluctuations of fractal features of EEG at rest in both eyes closed and eyes open conditions. Lower values of DFA exponent were found in the time T1 in closed eyes condition, likely effect of the sleep inertia. An alpha DFA exponent reduction was found also in central sensory-motor areas at time T3, the day time in which the sleepiness can be present. In eyes open condition, HFD lowered during the day. In eyes closed condition, an HFD increase was observed in central and frontal regions at time T2, the time in which alertness reaches its maximum and homeostatic sleep pressure is low. Complexity and the persistence of temporal correlations of brain rhythms change during daytime, parallel to changes in alertness and performance.

Exploiting neurovascular coupling: a Bayesian sequential Monte Carlo approach applied to simulated EEG fNIRS data

OBJECTIVE

Electrical and hemodynamic brain activity are linked through the neurovascular coupling process and they can be simultaneously measured through integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Thanks to the lack of electro-optical interference, the two procedures can be easily combined and, whereas EEG provides electrophysiological information, fNIRS can provide measurements of two hemodynamic variables, such as oxygenated and deoxygenated hemoglobin. A Bayesian sequential Monte Carlo approach (particle filter, PF) was applied to simulated recordings of electrical and neurovascular mediated hemodynamic activity, and the advantages of a unified framework were shown.

APPROACH

Multiple neural activities and hemodynamic responses were simulated in the primary motor cortex of a subject brain. EEG and fNIRS recordings were obtained by means of forward models of volume conduction and light propagation through the head. A state space model of combined EEG and fNIRS data was built and its dynamic evolution was estimated through a Bayesian sequential Monte Carlo approach (PF).

MAIN RESULTS

We showed the feasibility of the procedure and the improvements in both electrical and hemodynamic brain activity reconstruction when using the PF on combined EEG and fNIRS measurements.

SIGNIFICANCE

The investigated procedure allows one to combine the information provided by the two methodologies, and, by taking advantage of a physical model of the coupling between electrical and hemodynamic response, to obtain a better estimate of brain activity evolution. Despite the high computational demand, application of such an approach to in vivo recordings could fully exploit the advantages of this combined brain imaging technology.

Deep learning for hybrid EEG-fNIRS brain-computer interface: application to motor imagery classification

OBJECTIVE

Brain-computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG with other neuroimaging technologies, such as functional near infrared spectroscopy (fNIRS). A crucial step of BCI is brain state classification from recorded signal features. Deep artificial neural networks (DNNs) recently reached unprecedented complex classification outcomes. These performances were achieved through increased computational power, efficient learning algorithms, valuable activation functions, and restricted or back-fed neurons connections. By expecting significant overall BCI performances, we investigated the capabilities of combining EEG and fNIRS recordings with state-of-the-art deep learning procedures.

APPROACH

We performed a guided left and right hand motor imagery task on 15 subjects with a fixed classification response time of 1 s and overall experiment length of 10 min. Left versus right classification accuracy of a DNN in the multi-modal recording modality was estimated and it was compared to standalone EEG and fNIRS and other classifiers.

MAIN RESULTS

At a group level we obtained significant increase in performance when considering multi-modal recordings and DNN classifier with synergistic effect.

SIGNIFICANCE

BCI performances can be significantly improved by employing multi-modal recordings that provide electrical and hemodynamic brain activity information, in combination with advanced non-linear deep learning classification procedures.

Offline stimulation of human parietal cortex differently affects resting EEG microstates

The interference effects of transcranial magnetic stimulation (TMS) on several electroencephalographic (EEG) measures in both temporal and frequency domains have been reported. We tested the hypothesis whether the offline external inhibitory interference, although focal, could result in a global reorganization of the functional brain state, as assessed by EEG microstates. In 16 healthy subjects, we inhibited five parietal areas and used a pseudo stimulation (Sham) at rest. The EEG microstates were extracted before and after each stimulation. The canonical A, B, C and D templates were found before and after all stimulation conditions. The Sham, as well as the stimulation of a ventral site did not modify any resting EEG microstates’ topography. On the contrary, interfering with parietal key-nodes of both dorsal attention (DAN) and default mode networks (DMN), we observed that the microstate C clearly changes, whereas the other three topographies are not affected. These results provide the first causal evidence of a microstates modification following magnetic interference. Since the microstate C has been associated to the activity in regions belonging to the cingulo-opercular network (CON), the regional specificity of such inhibition seems to support the theory of a link between CON and both DAN and DMN at rest.

Prognostic Value of EEG Microstates in Acute Stroke

Given the importance of neuronal plasticity in recovery from a stroke and the huge variability of recovery abilities in patients, we investigated neuronal activity in the acute phase to enhance information about the prognosis of recovery in the stabilized phase. We investigated the microstates in 47 patients who suffered a first-ever mono-lesional ischemic stroke in the middle cerebral artery territory and in 20 healthy control volunteers. Electroencephalographic (EEG) activity at rest with eyes closed was acquired between 2 and 10 days (T0) after ischemic attack. Objective criteria allowed for the selection of an optimal number of microstates. Clinical condition was quantified by the National Institute of Health Stroke Scale (NIHSS) both in acute (T0) and stabilized (T1, 5.4 ± 1.7 months) phases and Effective Recovery (ER) was calculated as (NIHSS(T1)-NIHSS(T0))/NIHSS(T0). The microstates A, B, C and D emerged as the most stable. In patients with a left lesion inducing a language impairment, microstate C topography differed from controls. Microstate D topography was different in patients with a right lesion inducing neglect symptoms. In patients, the C vs D microstate duration differed after both a left and a right lesion with respect to controls (C lower than D in left and D lower than C in right lesion). A preserved microstate B in acute phase correlated with a better effective recovery. A regression model indicated that the microstate B duration explained the 11% of ER variance. This first ever study of EEG microstates in acute stroke opens an interesting path to identify neuronal impairments with prognostic relevance, to develop enriched compensatory treatments to drive a better individual recovery.

EEG-fMRI Bayesian framework for neural activity estimation: a simulation study

OBJECTIVE

Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework.

APPROACH

We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF).

MAIN RESULTS

First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements.

SIGNIFICANCE

The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.

Conventional fascial technique versus mesh repair for advanced pelvic organ prolapse: Analysis of recurrences in treated and untreated compartments

117 women with severe pelvic organ prolapse (POP; stage > 2) were enrolled to elucidate a 24-month outcome of POP surgery, using conventional or mesh repair with 3 techniques. 59 patients underwent conventional repair and 58 underwent mesh repair. Two types of mesh were used: a trocar-guided transobturator polypropylene (Avaulta, Bard Inc.) and a porcine dermis mesh (Pelvisoft, Bard Inc.). Women with recurrences, who underwent previous unsuccessful conventional repair, were randomised. Primary outcome was the evaluation of anatomic failures (prolapse stage > 1) in treated and untreated compartments. Anatomic failure was observed in 11 of 58 patients (19%; CI 8.9-29) in the mesh group and in 16 of 59 patients (27.1%; p value = 0.3) in the conventional group. 9 of 11 failures in the mesh group (15.5%; CI 6.2-24.8) were observed in the untreated compartment (de novo recurrences), 14.3% in Pelvisoft and 16.7% in Avaulta arm, while only 1 recurrence in the untreated compartment (1.7%) was observed in the conventional group (odds ratio 10.6, p = 0.03).

[Cesarean section, techniques and skin suture materials]

AIM

The aim of the study was to compare the outcome, complications and costs of three skin suture techniques after Caesarean section.

METHODS

The study sample was 310 women who underwent caesarean section between 2003 and 2007. The sample was divided into three groups: an intradermal suture with non-reabsorbable thread was applied in 98; metallic clips were placed in 90; 2-octyl-cyanoacrylate (2-OCA) glue was used for wound closure in 112. The sutures were checked at 4 days and 2 months after the operation to determine cosmetic outcome, patient compliance, strength of incision closure, allergic reactions, suture infection, and total cost of each technique.

RESULTS

No substantial differences in strength of incision closure or cosmetic outcome between the techniques were found. Compliance was better in the group that received 2-OCA, while the total cost of suture alone was lower in the group that received the non-reabsorbable intradermal suture.

CONCLUSION

The results suggests that following Caesarean section according to Stark, skin suture with 2-OCA glue has the advantage of greater patient compliance, while intradermal thread suture is less costly with a cosmetic outcome comparable to that of the other two techniques.

[Ultrasonographic evaluation of timing in emergency cervical cerclage]

The aim of the present paper is to utilise endovaginal ultrasonography as an instrument for establishing the most appropriate moment for carrying out cervical cerclage after interrupting uterine contractions in a situation of near miscarriage. A patient at 20 weeks and 4 days of gestation, with contractions, integral membranes and complete dilatation, was laid in the Trendelemburg position, keeping the bladder moderately full, and given tocolytic therapy. After 14 days cerclage was carried out on a reconstituted neck. At 37 weeks and 1 day, the patient delivered a female newborn weighing 3.100 g. The Trendelemburg position, the moderately full bladder and tocolytic therapy with endovaginal ultrasonographic monitoring can move the timing of surgery forward so as to render it safer and more useful for prognostic purposes.

Gastric carcinoma detected by cervical cytology

This paper is a report on a case of gastric carcinoma of diffuse type in a young female patient aged 38. The patient was still asymptomatic at hospital admission, her only pathological sign being the finding of malignant cells of indeterminate origin at a routine Pap-test examination. Subsequent investigations showed the presence of a poorly differentiated gastric carcinoma, with metastatic diffusion to uterus, ovaries and peritoneum. Only a few cases of gastric carcinomas without cervical localization, detected by Pap-test, are reported in literature. A few other cases with cervical localization have been described. The aim of this work is to point out that a Pap-test smear may reveal the presence of extragenital tumors still unappreciated.

[Endometriosis of the ileum and colon complicated by intestinal obstruction. Report of two cases]

The authors report two cases of intestinal occlusion, one ileal and the other colic, caused by endometriosis. Both patients underwent surgery. Following a review of data in the literature regarding the frequency, pathogenesis, diagnosis and management, the authors conclude that pre- and intraoperative diagnosis is often impossible in these cases and must be postponed to histological analysis. Full remission was achieved after surgery.

[Cloacal exstrophy, ultrasonic diagnosis]

This study aims to underline the importance of transvaginal ultrasonography in the first three months of pregnancy. The authors report a case which was referred to their attention for preliminary tests performed prior to amniocentesis, recommended by the general physician because of the mother's age. The primapara woman and father of the fetus were healthy and the family history excluded hereditary diseases or congenital pathologies. Transvaginal ultrasonography permitted the diagnosis at the start of the fourth month of pregnancy of a polymalformed fetus with cloacal exstrophy, sacral myelomeningocele, clubfoot, single umbilical artery. In this case, the mother decided to undergo eugenic abortion in view of the severity of the pathology.

[Selective episiotomy. Comparison of two suture technics]

AIMS

The study aimed to highlight any differences between the sequelae of episiorrhaphy performed using the Blair-Donatti and Guilmen-Pontonnier techniques.

METHODS

A total of 202 pregnant women were recruited in the Obstetrics Ward of Codogno Civic Hospital in 1994 and 1995. Subjects were randomly divided into two groups matched for socioeconomic status, age and parity (group A: Guilmen-Pontonnier suture, group B: Blair-Donatti suture). The following parameters were evaluated: pain twenty-four hours, sixty-six hours and one, two and three months after labour, pain during sexual relations, the onset of infection, hematoma, dehiscence of the wound, and lastly the cosmetic results.

RESULTS

No significant differences were found between the parameters examined in both groups, barring the improved cosmetic result in group A.

[A clinical study of the use of a combination of glucomannan with lactulose in the constipation of pregnancy]

RATIONALE

Constipation is a problem frequently encountered during pregnancy as is excessive weight gain. Treatments of common use to control constipation are endowed with some drawbacks and they are not active in controlling weight increase. A preparation of lactulose and glucomannan in previous studies proved very effective and well tolerated in patients affected by stypsis and evidentiated also activity both in controlling excessive food intake and in correcting some metabolic imbalances regarding lipids and urea.

MATERIAL AND METHODS

50 pregnant females affected by constipation were treated with sachets containing a preparation of glucomannan (1.45 g) and lactulose (4.2 g) in a posology of 2 (1-4) sachets a day for 1-3 months.

RESULTS

Treatment induced a return to normal frequency of weekly number of evacuations (4.9-5.8/week) and a parallel control of weight gain (within 20% of initial body weight). The latter finding seems to be related to hunger control induced by glucomannan at the gastric level which prevents an excessive food intake.