What the Solitaire illusion tells us about perception of numerosity.

In four experiments we investigated the Solitaire illusion. In this illusion, most observers see as more numerous a set of dots that forms a single central group, compared to dots on the outside of that group. We confirmed and extended the effect to configurations with much higher numerosity than the original and of various colours. Contrary to prediction, separating the two groups, so that they are presented side by side, reduced but did not abolish or reverse the illusion. In this illusion, therefore, neither total size of the region (area), not average distance of the elements has the expected effect. In Experiments 3 and 4 we eliminated the regularity of the pattern, by sampling 50% (Exp 3) or only a 10% (Exp 4) of the elements. These produces quasi-random configurations. For these configurations the bias for the inner groups was still present, and it was only eliminated when the groups were shown as separate. However, the effect never reversed (no bias for the outer group, despite its larger area). We conclude that the Solitaire illusion is evidence of a strong bias in favour of centrally located elements, a bias that can overcome other factors.

Altered Microcirculation in Alzheimer's Disease Assessed by Machine Learning Applied to Functional Thermal Imaging Data.

Alzheimer's disease (AD) is characterized by progressive memory failures accompanied by microcirculation alterations. Particularly, impaired endothelial microvascular responsiveness and altered flow motion patterns have been observed in AD patients. Of note, the endothelium influences the vascular tone and also the small superficial blood vessels, which can be evaluated through infrared thermography (IRT). The advantage of IRT with respect to other techniques relies on its contactless features and its capability to preserve spatial information of the peripheral microcirculation. The aim of the study is to investigate peripheral microcirculation impairments in AD patients with respect to age-matched healthy controls (HCs) at resting state, through IRT and machine learning (ML) approaches. Particularly, several classifiers were tested, employing as regressors the power of the nose tip temperature time course in different physiological frequency bands. Among the ML classifiers tested, the Decision Tree Classifier (DTC) delivered the best cross-validated accuracy (accuracy = 82%) when discriminating between AD and HCs. The results further demonstrate the alteration of microvascular patterns in AD in the early stages of the pathology, and the capability of IRT to assess vascular impairments. These findings could be exploited in clinical practice, fostering the employment of IRT as a support for the early diagnosis of AD.

On the usefulness of graph-theoretic properties in the study of perceived numerosity.

Observers can quickly estimate the quantity of sets of visual elements. Many aspects of this ability have been studied and the underlying system has been called the Approximate Number Sense (Dehaene, 2011). Specific visual properties, such as size and clustering of the elements, can bias an estimate. For intermediate numerical quantities at low density (above five, but before texturization), human performance is predicted by a model based on the region of influence of elements (occupancy model: Allïk & Tuulmets, 1991). For random 2D configurations we computed ten indices based on graph theory, and we compared them with the occupancy model: independence number, domination, connected components, local clustering coefficient, global clustering coefficient, random walk, eigenvector centrality, maximum clique, total degree of connectivity, and total edge length. We made comparisons across a range of parameters, and we varied the size of the region of influence around each element. The analysis of the pattern of correlations suggests two main groups of graph-based measures. The first group is sensitive to the presence of local clustering of elements, the second seems more sensitive to density and the way information spreads in graphs. Empirical work on perception of numerosity may benefit from comparing, or controlling for, these properties.

Evidence of Neurovascular Un-Coupling in Mild Alzheimer's Disease through Multimodal EEG-fNIRS and Multivariate Analysis of Resting-State Data.

Alzheimer's disease (AD) is associated with modifications in cerebral blood perfusion and autoregulation. Hence, neurovascular coupling (NC) alteration could become a biomarker of the disease. NC might be assessed in clinical settings through multimodal electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Multimodal EEG-fNIRS was recorded at rest in an ambulatory setting to assess NC and to evaluate the sensitivity and specificity of the methodology to AD. Global NC was evaluated with a general linear model (GLM) framework by regressing whole-head EEG power envelopes in three frequency bands (theta, alpha and beta) with average fNIRS oxy- and deoxy-hemoglobin concentration changes in the frontal and prefrontal cortices. NC was lower in AD compared to healthy controls (HC) with significant differences in the linkage of theta and alpha bands with oxy- and deoxy-hemoglobin, respectively (p = 0.028 and p = 0.020). Importantly, standalone EEG and fNIRS metrics did not highlight differences between AD and HC. Furthermore, a multivariate data-driven analysis of NC between the three frequency bands and the two hemoglobin species delivered a cross-validated classification performance of AD and HC with an Area Under the Curve, AUC = 0.905 (p = 2.17 × 10-5). The findings demonstrate that EEG-fNIRS may indeed represent a powerful ecological tool for clinical evaluation of NC and early identification of AD.

Working Memory Decline in Alzheimer's Disease Is Detected by Complexity Analysis of Multimodal EEG-fNIRS.

Alzheimer's disease (AD) is characterized by working memory (WM) failures that can be assessed at early stages through administering clinical tests. Ecological neuroimaging, such as Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS), may be employed during these tests to support AD early diagnosis within clinical settings. Multimodal EEG-fNIRS could measure brain activity along with neurovascular coupling (NC) and detect their modifications associated with AD. Data analysis procedures based on signal complexity are suitable to estimate electrical and hemodynamic brain activity or their mutual information (NC) during non-structured experimental paradigms. In this study, sample entropy of whole-head EEG and frontal/prefrontal cortex fNIRS was evaluated to assess brain activity in early AD and healthy controls (HC) during WM tasks (i.e., Rey-Osterrieth complex figure and Raven's progressive matrices). Moreover, conditional entropy between EEG and fNIRS was evaluated as indicative of NC. The findings demonstrated the capability of complexity analysis of multimodal EEG-fNIRS to detect WM decline in AD. Furthermore, a multivariate data-driven analysis, performed on these entropy metrics and based on the General Linear Model, allowed classifying AD and HC with an AUC up to 0.88. EEG-fNIRS may represent a powerful tool for the clinical evaluation of WM decline in early AD.

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.

Complexity of Frontal Cortex fNIRS Can Support Alzheimer Disease Diagnosis in Memory and Visuo-Spatial Tests.

Decline in visuo-spatial skills and memory failures are considered symptoms of Alzheimer's Disease (AD) and they can be assessed at early stages employing clinical tests. However, performance in a single test is generally not indicative of AD. Functional neuroimaging, such as functional Near Infrared Spectroscopy (fNIRS), may be employed during these tests in an ecological setting to support diagnosis. Indeed, neuroimaging should not alter clinical practice allowing free doctor-patient interaction. However, block-designed paradigms, necessary for standard functional neuroimaging analysis, require tests adaptation. Novel signal analysis procedures (e.g., signal complexity evaluation) may be useful to establish brain signals differences without altering experimental conditions. In this study, we estimated fNIRS complexity (through Sample Entropy metric) in frontal cortex of early AD and controls during three tests that assess visuo-spatial and short-term-memory abilities (Clock Drawing Test, Digit Span Test, Corsi Block Tapping Test). A channel-based analysis of fNIRS complexity during the tests revealed AD-induced changes. Importantly, a multivariate analysis of fNIRS complexity provided good specificity and sensitivity to AD. This outcome was compared to cognitive tests performances that were predictive of AD in only one test. Our results demonstrated the capabilities of fNIRS and complexity metric to support early AD diagnosis.

Assessment of the Autonomic Response in Alzheimer's Patients During the Execution of Memory Tasks: A Functional Thermal Imaging Study.

BACKGROUND: Alzheimer's disease (AD) is a form of dementia characterized by failure of memory that becomes more severe with the progression of the disease. The Free and Cued Selective Reminding Test (FCSRT) is a clinical test used to evaluate such a deficit. However, since the cognitive performances could depend also on the psychophysiological state of the individual, it is important to monitor that state through the peripheral autonomic activity during the execution of the test. Thermal infrared imaging has been used for this kind of assessment in order to preserve the free and unbiased interaction between doctor and patient, thanks to the contactless features of the technique. OBJECTIVE: To investigate whether the variation of facial temperature parameters during the FCSRT is indicative of different autonomic states in the early AD with respect to healthy controls (HC). RESULTS: At a group level, a greater sympathetic activity for the HC with respect to AD during the execution of the test was found, indicative of a suppression of anxiety associated with the performances of the FCSRT in AD patients. CONCLUSION: These results indicate that AD and HC may present different autonomic activity associated with the execution of a cognitive task, thus suggesting a different modulation of high-cognition and emotion network.

Study of memory deficit in Alzheimer's disease by means of complexity analysis of fNIRS signal.

Working memory deficit is a signature of Alzheimer's disease (AD). The free and cued selective reminding test (FCSRT) is a clinical test that quantifies memory deficit for AD diagnosis. However, the diagnostic accuracy of FCSRT may be increased by accompanying it with neuroimaging. Since the test requires doctor-patient interaction, brain monitoring is challenging. Functional near-infrared spectroscopy (fNIRS) could be suited for such a purpose because of the fNIRS flexibility. We investigated whether the complexity, based on sample entropy and multiscale entropy metrics, of the fNIRS signal during FCSRT was correlated with memory deficit in early AD. fNIRS signals were recorded over the prefrontal cortex of healthy and early AD participants. Group differences were tested through Wilcoxon-Mann-Whitney test ([Formula: see text]). At group level, we found significant differences for Brodmann areas 9 and 46. The results, although preliminary, demonstrate the feasibility of performing ecological studies on early AD with fNIRS. This approach may provide a potential neuroimaging-based method for diagnosis of early AD, viable at the doctor's office level, improving test-based diagnosis. The increased entropy of the fNIRS signal in early AD suggests the opportunity for further research on the neurophysiological status in AD and its relevance for clinical symptoms.

Spatial clustering and its effect on perceived clustering, numerosity, and dispersion.

Human observers are able to estimate the numerosity of large sets of visual elements. The occupancy model of perceived numerosity in intermediate numerical ranges is based on overlapping regions of influence. The key idea is that items within a certain range count for less than their actual numerical value and more so the closer they are to their neighbours. Therefore occupancy is sensitive to the grouping of elements, but there are other spatial properties of  configurations that could also influence perceived numerosity, such as: area of convex hull, occupancy area, total degree of connectivity, and local clustering For all indices apart from convex hull, we varied the radius of the area that defined neighbours. We tested perceived numerosity using a fixed number of elements placed at random within a circular region. Observers compared two patterns (presented in two intervals) and chose the one that appeared more numerous. The same observers performed two other separate tasks in which they judged which pattern appeared more dispersed or more clustered. In each pair of images, the number was always the same (22, 28, 34, or 40 items), because we were interested in which "appeared" more numerous on the basis of spatial configuration. The results suggest that estimates of numerosity, dispersion, and clustering are based on different spatial information, that there are alternative approaches to quantifying clustering, and that in all cases clustering is linked to a decrease in perceived numerosity. The alternative measures have different properties and different practical and computational advantages.

Prognostic relevance of masked hypertension in subjects with prehypertension.

BACKGROUND: The prognostic impact of masked hypertension is not yet completely clear. The aim of this study was to evaluate the prognostic relevance of masked hypertension in subjects with prehypertension. METHODS: The occurrence of fatal and nonfatal cardiovascular events was evaluated in 591 subjects with prehypertension defined as clinic blood pressure (BP) in the range of 120-139 mm Hg for systolic BP and 80-89 mm Hg for diastolic BP. Among them, 471 were classified as having true prehypertension (clinic BP <140/90 mm Hg and daytime BP <135/85 mm Hg) and 120 as having masked hypertension (clinic BP <140/90 mm Hg and daytime BP > or =135 or 85 mm Hg). RESULTS: During the follow-up (6.6 +/- 4.3 years, range 0.5-15.5 years), 29 cardiovascular events occurred. In subjects with true prehypertension and masked hypertension the event-rates per 100 patient-years were 0.57 and 1.51, respectively. Event-free survival was significantly different between the groups (P < 0.005). After adjustment for other covariates, including clinic BP (forced into the model), Cox regression analysis showed that cardiovascular risk was significantly higher in masked hypertension than in true prehypertension (masked vs. true prehypertension, relative risk 2.65, 95% confidence interval 1.18-5.98, P = 0.018). CONCLUSIONS: Among subjects with prehypertension, those with masked hypertension are at higher cardiovascular risk than those with true prehypertension. Out-of-office BP should be known in individuals with prehypertension, preferably by ambulatory BP monitoring or alternatively by home BP measurement, to obtain a better prognostic stratification.

Ambulatory blood pressure monitoring in obese children: role of insulin resistance.

OBJECTIVES: To investigate the relationship between ambulatory blood pressure (ABPM) parameters and insulin resistance in obese children. METHODS: A population of 56 obese prepubertal children was recruited for the study. They underwent ABPM, an oral glucose tolerance test and complete physical examination, including adiposity indexes such as body mass index (BMI), skinfolds, waist-to-hip ratio (WHR) and fat mass. RESULTS: The standard deviation score for BMI was significantly correlated with 24-h systolic blood pressure (SBP) (r = 0.30; P = 0.02) and diastolic blood pressure (DBP) (r = 0.29; P = 0.03), daytime SBP and DBP (r = 0.28; P = 0.04 and r = 0.32; P = 0.02), night-time SBP and DBP (r = 0.32; P = 0.01 and r = 0.27; P = 0.04). Fat mass was correlated with 24-h SBP (r = 0.46; P = 0.005), daytime SBP (r = 0.40; P = 0.01) and night-time SBP (r = 0.49; P = 0.03). No correlations were found between ABPM parameters and WHR. Furthermore, significant correlations were found between insulin resistance indexes, such as the homeostasis model assessment of insulin resistance and quantitative insulin-sensitivity check index, and 24-h DBP (r = 0.34; P = 0.01 and r = -0.29; P = 0.03), daytime DBP (r = 0.35; P = 0.009 and r = -0.34; P = 0.01) and daytime SBP (r = 0.32; P = 0.02 and r = -0.27; P = 0.04). Only 24-h and daytime DBP remained correlated with insulin resistance after adjustment for obesity. The analysis of the circadian rhythm of blood pressure revealed that 24 out the 56 children were non-dippers. CONCLUSIONS: The results of the present study indicate that adiposity and insulin resistance have an important role in influencing blood pressure in obese children, and also show a high prevalence of non-dipping phenomenon. This is of particular relevance because blood pressure tracks from childhood into adulthood and an already early-life high blood pressure is associated with an increased cardiovascular risk.