Shedding light into the brain: Methodological innovations in optical neuroimaging

Functional near-infrared spectroscopy (fNIRS) and diffuse optical tomography (DOT) are non-invasive techniques used to infer stimulus-locked variations in human cortical activity from optical variations of near-infrared light injected and subsequently detected at specified scalp locations. Relative to functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), these optical techniques are more portable, less invasive and less sensitive to motion artifacts, making them ideal to explore brain activity in a variety of cognitive situations, and in a range of populations, including newborns and children. FNIRS and DOT measure stimulus-locked hemodynamic response in the form of changes in oxy- (HbO) and deoxy- (HbR) hemoglobin concentration taking place in specific areas. This signal is however structurally intertwined with physiological noise owing to cardiac pulsations, respiratory oscillations and vasopressure wave. Furthermore, the absolute magnitude of hemodynamic responses is substantially smaller than these non-informative components of the measured optical signal, and has a frequency which largely overlaps with that of the vasopressure wave. Thus, recovering the hemodynamic response is a challenging task. Several methods have been proposed in the literature to try to reduce physiological noise oscillations and recover the hemodynamic response, but none of them has become a common standard in the optical signal processing pipeline. In this thesis, a novel algorithm, devised to overcome a large subset of drawbacks associated with the use of these literature techniques, is presented and validated. Reduced sensitivity to motion artifacts notwithstanding, the optical signal must always be assumed as contaminated by some form of mechanical instability, most prominently during signal acquisitions from pathological (e.g., stroke patients) or difficult (e.g., newborns) populations. Several techniques have been proposed to correct for motion artifacts with the specific aim of preserving contaminated measures as opposed to rejecting them. However, none of them has become the gold standard in the optical signal processing pipeline, and there are currently no objective approaches to choose the most appropriate filtering technique based on objective parameters. In fact, due to the extreme variability in shape, frequency content and amplitude of the motion artifacts, it is likely that the best technique to apply is data-dependent and, in this vein, it is essential to provide users with objective tools able to select the best motion correction technique for the data set under examination. In this thesis, a novel objective approach to perform this selection is proposed and validated on a data-set containing a very challenging type of motion artifacts. While fNIRS allows only spectroscopic measurements of hemoglobin concentration changes, DOT allows to obtain 3D reconstructed images of HbO and HbR concentration changes. To increase the accuracy and interpretability of DOT reconstructed images, valuable anatomical information should be provided. While several adult head models have been proposed and validated in this context, only few single-ages head models have been presented for the neonatal population. However, due to the rapid growth and maturation of the infant's brain, single-age models fail to capture precise information about the correct anatomy of every infant's head under examination. In this thesis, a novel 4D head model, ranging from the preterm to the term age, is proposed, allowing developmental neuroscientists to make finer-grained choices about the age-matched head model and perform image reconstruction with an anatomy as similar as possible to the real one. The outline of the thesis will be as follows. In the first two chapters of this thesis, the state of the art of optical techniques will be reviewed. Particularly, in chapter 1, a brief introduction on the physical principles of optical techniques and a comparison with other more common neuroimaging techniques will be presented. In chapter 2, the components of the measured optical signal will be described and a brief review of state of the art of the algorithms that perform physiological noise removal will be presented. The theory on which optical image reconstruction is based will be reviewed afterwards. In the final part of the chapter, some of the studies and achievements of optical techniques in the adult and infants populations will be reviewed and the open issues and aims of the thesis will be presented. In chapters 3, 4 and 5, new methodologies and tools for signal processing and image reconstruction will be presented. Particularly, in chapter 3, a novel algorithm to reduce physiological noise contamination and recover the hemodynamic response will be introduced. The proposed methodology will be validated against two literature methods and results and consequent discussion will be reported. In chapter 4, instead, a novel objective approach for the selection of the best motion correction technique will be proposed. The main literature algorithms for motion correction will be reviewed and the proposed approach will be validated using these motion correction techniques on real cognitive data. In chapter 5, instead, a novel 4D neonatal optical head model will be presented. All the steps performed for its creation will be explained and discussed and a demonstration of the head model in use will also be exhibited. The last part of the thesis (chapters 6, 7 and 8) will be dedicated to illustrate three distinct examples of application of the proposed methodologies and tools on neural empirical data. In chapter 6, the physiological noise removal algorithm proposed in chapter 3 will be applied to recover subtle temporal differences between hemodynamic responses measured in two different areas of the motor cortex in short- vs. long- duration tapping. In chapter 7, the same algorithm will be applied to reduce physiological noise and recover hemodynamic responses measured during a visual short-term memory paradigm. In both chapters, cognitive results and a brief discussion will be reported. In chapter 8, instead, the neonatal optical head model proposed in chapter 5 will be applied to perform image reconstruction with data acquired on a healthy full term baby. In the same chapter, the importance of motion artifact correction will be highlighted, reconstructing HbO concentration changes images before and after the correction took place

Measuring Cerebral Activation From fNIRS Signals: An Approach Based on Compressive Sensing and Taylor-Fourier Model

Functional near-infrared spectroscopy (fNIRS) is a noninvasive and portable neuroimaging technique that uses NIR light to monitor cerebral activity by the so-called haemodynamic responses (HRs). The measurement is challenging because of the presence of severe physiological noise, such as respiratory and vasomotor waves. In this paper, a novel technique for fNIRS signal denoising and HR estimation is described. The method relies on a joint application of compressed sensing theory principles and Taylor-Fourier modeling of nonstationary spectral components. It operates in the frequency domain and models physiological noise as a linear combination of sinusoidal tones, characterized in terms of frequency, amplitude, and initial phase. Algorithm performance is assessed over both synthetic and experimental data sets, and compared with that of two reference techniques from fNIRS literature

Long-term continuous monitoring of the preterm brain with diffuse optical tomography and electroencephalography: A technical note on cap manufacturing

open12noDiffuse optical tomography (DOT) has recently proved useful for detecting whole-brain oxygenation changes in preterm and term newborns' brains. The data recording phase in prior explorations was limited up to a maximum of a couple of hours, a time dictated by the need to minimize skin damage caused by the protracted contact with optode holders and interference with concomitant clinical/nursing procedures. In an attempt to extend the data recording phase, we developed a new custom-made cap for multimodal DOT and electroencephalography acquisitions for the neonatal population. The cap was tested on a preterm neonate (28 weeks gestation) for a 7-day continuous monitoring period. The cap was well tolerated by the neonate, who did not suffer any evident discomfort and/or skin damage. Montage and data acquisition using our cap was operated by an attending nurse with no difficulty. DOT data quality was remarkable, with an average of 92% of reliable channels, characterized by the clear presence of the heartbeat in most of them.openopenAlfonso Galderisi; Sabrina Brigadoi; Simone Cutini; Sara Basso Moro; Elisabetta Lolli; Federica Meconi; Silvia Benavides-Varela; Eugenio Baraldi; Piero Amodio; Claudio Cobelli; Daniele Trevisanuto; Roberto Dell'AcquaGalderisi, Alfonso; Brigadoi, Sabrina; Cutini, Simone; BASSO MORO, Sara; Lolli, Elisabetta; Meconi, Federica; Silvia, Benavides-Varela; Baraldi, Eugenio; Amodio, Piero; Cobelli, Claudio; Trevisanuto, Daniele; Dell'Acqua, Robert

Using multi-modal neuroimaging to characterise social brain specialisation in infants

The specialised regional functionality of the mature human cortex partly emerges through experience-dependent specialisation during early development. Our existing understanding of functional specialisation in the infant brain is based on evidence from unitary imaging modalities and has thus focused on isolated estimates of spatial or temporal selectivity of neural or haemodynamic activation, giving an incomplete picture. We speculate that functional specialisation will be underpinned by better coordinated haemodynamic and metabolic changes in a broadly orchestrated physiological response. To enable researchers to track this process through development, we develop new tools that allow the simultaneous measurement of coordinated neural activity (EEG), metabolic rate, and oxygenated blood supply (broadband near-infrared spectroscopy) in the awake infant. In 4- to 7-month-old infants, we use these new tools to show that social processing is accompanied by spatially and temporally specific increases in coupled activation in the temporal-parietal junction, a core hub region of the adult social brain. During non-social processing, coupled activation decreased in the same region, indicating specificity to social processing. Coupling was strongest with high-frequency brain activity (beta and gamma), consistent with the greater energetic requirements and more localised action of high-frequency brain activity. The development of simultaneous multimodal neural measures will enable future researchers to open new vistas in understanding functional specialisation of the brain

A wide field-of-view, modular, high-density diffuse optical tomography system for minimally constrained three-dimensional functional neuroimaging

The ability to produce high-quality images of human brain function in any environment and during unconstrained movement of the subject has long been a goal of neuroimaging research. Diffuse optical tomography, which uses the intensity of back-scattered near-infrared light from multiple source-detector pairs to image changes in haemoglobin concentrations in the brain, is uniquely placed to achieve this goal. Here, we describe a new generation of modular, fibre-less, high-density diffuse optical tomography technology that provides exceptional sensitivity, a large dynamic range, a field-of-view sufficient to cover approximately one-third of the adult scalp, and also incorporates dedicated motion sensing into each module. Using in-vivo measures, we demonstrate a noise-equivalent power of 318 fW, and an effective dynamic range of 142 dB. We describe the application of this system to a novel somatomotor neuroimaging paradigm that involves subjects walking and texting on a smartphone. Our results demonstrate that wearable high-density diffuse optical tomography permits three-dimensional imaging of the human brain function during overt movement of the subject; images of somatomotor cortical activation can be obtained while subjects move in a relatively unconstrained manner, and these images are in good agreement with those obtained while the subjects remain stationary. The scalable nature of the technology we described here paves the way for the routine acquisition of high-quality, three-dimensional, whole-cortex diffuse optical tomography images of cerebral haemodynamics, both inside and outside of the laboratory environment, which has profound implications for neuroscience

Mapping cortical haemodynamics during neonatal seizures using diffuse optical tomography: A case study

AbstractSeizures in the newborn brain represent a major challenge to neonatal medicine. Neonatal seizures are poorly classified, under-diagnosed, difficult to treat and are associated with poor neurodevelopmental outcome. Video-EEG is the current gold-standard approach for seizure detection and monitoring. Interpreting neonatal EEG requires expertise and the impact of seizures on the developing brain remains poorly understood. In this case study we present the first ever images of the haemodynamic impact of seizures on the human infant brain, obtained using simultaneous diffuse optical tomography (DOT) and video-EEG with whole-scalp coverage. Seven discrete periods of ictal electrographic activity were observed during a 60 minute recording of an infant with hypoxic–ischaemic encephalopathy. The resulting DOT images show a remarkably consistent, high-amplitude, biphasic pattern of changes in cortical blood volume and oxygenation in response to each electrographic event. While there is spatial variation across the cortex, the dominant haemodynamic response to seizure activity consists of an initial increase in cortical blood volume prior to a large and extended decrease typically lasting several minutes. This case study demonstrates the wealth of physiologically and clinically relevant information that DOT–EEG techniques can yield. The consistency and scale of the haemodynamic responses observed here also suggest that DOT–EEG has the potential to provide improved detection of neonatal seizures

Recommendations for motion correction of infant fNIRS data applicable to data sets acquired with a variety of experimental designs and acquisition systems

Despite motion artifacts are a major source of noise in fNIRS infant data, how to approach motion correction in this population has only recently started to be investigated. Homer2 offers a wide range of motion correction methods and previous work on simulated and adult data suggested the use of Spline interpolation and Wavelet filtering as optimal methods for the recovery of trials affected by motion. However, motion artifacts in infant data differ from those in adults' both in amplitude and frequency of occurrence. Therefore, artifact correction recommendations derived from adult data might not be the optimal for infant data. We hypothesized that the combined use of Spline and Wavelet would outperform their individual use on data with complex profiles of motion artifacts. To demonstrate this, we first compared, on infant semi-simulated data, the performance of several motion correction techniques on their own and of the novel combined approach; then, we investigated the performance of Spline and Wavelet alone and in combination on real cognitive data from three datasets collected with infants of different ages (5, 7 and 10 months), with different tasks (auditory/visual and tactile) and with different NIRS systems. To quantitatively estimate and compare the efficacy of these techniques, we adopted four metrics: hemodynamic response recovery error, within-subject standard deviation, between-subjects standard deviation and number of trials that survived each correction method. Our results demonstrated that (i) it is always better correcting for motion artifacts than rejecting the corrupted trials; (ii) Wavelet filtering on its own and in combination with Spline interpolation seems to be the most effective approach in reducing the between- and the within-subject standard deviations. Importantly, the combination of Spline and Wavelet was the approach providing the best performance in semi-simulation both at low and high levels of noise, also recovering most of the trials affected by motion artifacts across all datasets, a crucial result when working with infant data. [Abstract copyright: Copyright © 2019. Published by Elsevier Inc.

Optical imaging and spectroscopy for the study of the human brain: status report.

This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions

Shedding light into the brain: Methodological innovations in optical neuroimaging

Functional near-infrared spectroscopy (fNIRS) and diffuse optical tomography (DOT) are non-invasive techniques used to infer stimulus-locked variations in human cortical activity from optical variations of near-infrared light injected and subsequently detected at specified scalp locations. Relative to functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), these optical techniques are more portable, less invasive and less sensitive to motion artifacts, making them ideal to explore brain activity in a variety of cognitive situations, and in a range of populations, including newborns and children. FNIRS and DOT measure stimulus-locked hemodynamic response in the form of changes in oxy- (HbO) and deoxy- (HbR) hemoglobin concentration taking place in specific areas. This signal is however structurally intertwined with physiological noise owing to cardiac pulsations, respiratory oscillations and vasopressure wave. Furthermore, the absolute magnitude of hemodynamic responses is substantially smaller than these non-informative components of the measured optical signal, and has a frequency which largely overlaps with that of the vasopressure wave. Thus, recovering the hemodynamic response is a challenging task. Several methods have been proposed in the literature to try to reduce physiological noise oscillations and recover the hemodynamic response, but none of them has become a common standard in the optical signal processing pipeline. In this thesis, a novel algorithm, devised to overcome a large subset of drawbacks associated with the use of these literature techniques, is presented and validated. Reduced sensitivity to motion artifacts notwithstanding, the optical signal must always be assumed as contaminated by some form of mechanical instability, most prominently during signal acquisitions from pathological (e.g., stroke patients) or difficult (e.g., newborns) populations. Several techniques have been proposed to correct for motion artifacts with the specific aim of preserving contaminated measures as opposed to rejecting them. However, none of them has become the gold standard in the optical signal processing pipeline, and there are currently no objective approaches to choose the most appropriate filtering technique based on objective parameters. In fact, due to the extreme variability in shape, frequency content and amplitude of the motion artifacts, it is likely that the best technique to apply is data-dependent and, in this vein, it is essential to provide users with objective tools able to select the best motion correction technique for the data set under examination. In this thesis, a novel objective approach to perform this selection is proposed and validated on a data-set containing a very challenging type of motion artifacts. While fNIRS allows only spectroscopic measurements of hemoglobin concentration changes, DOT allows to obtain 3D reconstructed images of HbO and HbR concentration changes. To increase the accuracy and interpretability of DOT reconstructed images, valuable anatomical information should be provided. While several adult head models have been proposed and validated in this context, only few single-ages head models have been presented for the neonatal population. However, due to the rapid growth and maturation of the infant's brain, single-age models fail to capture precise information about the correct anatomy of every infant's head under examination. In this thesis, a novel 4D head model, ranging from the preterm to the term age, is proposed, allowing developmental neuroscientists to make finer-grained choices about the age-matched head model and perform image reconstruction with an anatomy as similar as possible to the real one. The outline of the thesis will be as follows. In the first two chapters of this thesis, the state of the art of optical techniques will be reviewed. Particularly, in chapter 1, a brief introduction on the physical principles of optical techniques and a comparison with other more common neuroimaging techniques will be presented. In chapter 2, the components of the measured optical signal will be described and a brief review of state of the art of the algorithms that perform physiological noise removal will be presented. The theory on which optical image reconstruction is based will be reviewed afterwards. In the final part of the chapter, some of the studies and achievements of optical techniques in the adult and infants populations will be reviewed and the open issues and aims of the thesis will be presented. In chapters 3, 4 and 5, new methodologies and tools for signal processing and image reconstruction will be presented. Particularly, in chapter 3, a novel algorithm to reduce physiological noise contamination and recover the hemodynamic response will be introduced. The proposed methodology will be validated against two literature methods and results and consequent discussion will be reported. In chapter 4, instead, a novel objective approach for the selection of the best motion correction technique will be proposed. The main literature algorithms for motion correction will be reviewed and the proposed approach will be validated using these motion correction techniques on real cognitive data. In chapter 5, instead, a novel 4D neonatal optical head model will be presented. All the steps performed for its creation will be explained and discussed and a demonstration of the head model in use will also be exhibited. The last part of the thesis (chapters 6, 7 and 8) will be dedicated to illustrate three distinct examples of application of the proposed methodologies and tools on neural empirical data. In chapter 6, the physiological noise removal algorithm proposed in chapter 3 will be applied to recover subtle temporal differences between hemodynamic responses measured in two different areas of the motor cortex in short- vs. long- duration tapping. In chapter 7, the same algorithm will be applied to reduce physiological noise and recover hemodynamic responses measured during a visual short-term memory paradigm. In both chapters, cognitive results and a brief discussion will be reported. In chapter 8, instead, the neonatal optical head model proposed in chapter 5 will be applied to perform image reconstruction with data acquired on a healthy full term baby. In the same chapter, the importance of motion artifact correction will be highlighted, reconstructing HbO concentration changes images before and after the correction took place.La spettroscopia funzionale nel vicino infrarosso (fNIRS) e la tomografia ottica diffusa (DOT) sono tecniche non invasive che, sfruttando le proprietà della luce nel vicino infrarosso, permettono di misurare l'attività cerebrale. Sorgente e detettore sono posti a contatto con il cuoio capelluto ad una distanza prestabilita. Dall'attenuazione subita dalla luce nel passaggio attraverso i tessuti cerebrali, è possibile ricavare le variazioni nell'attività corticale, che avvengono in seguito alla presentazione di uno stimolo. Rispetto alla risonanza magnetica funzionale (fMRI) ed all'elettroencefalografia (EEG), le tecniche ottiche sono più portatili, meno invasive e meno sensibili agli artefatti da movimento; sono pertanto tecniche ideali per esplorare l'attività cerebrale in numerosi ambiti cognitivi e in un gran numero di popolazioni, come neonati e bambini. FNIRS e DOT misurano la risposta emodinamica in seguito alla presentazione di uno stimolo nella forma di variazioni nella concentrazione di emoglobina ossigenata (HbO) e deossigenata (HbR) che avvengono in specifiche aree della corteccia. Tuttavia, il segnale misurato non contiene solo la risposta emodinamica d'interesse, ma anche rumore fisiologico, dovuto per esempio alla pulsazione cardiaca, alle oscillazioni dovute alla respirazione e all'onda vasomotrice. Inoltre, la risposta emodinamica d'interesse si presenta di solito con un'ampiezza ridotta rispetto alle componenti non informative del rumore fisiologico e con una frequenza molto simile a quella dell'onda vasomotrice. Da ciò si deduce come stimare la risposta emodinamica sia un compito molto difficile. Molti metodi sono stati proposti in letteratura per cercare di ridurre il rumore fisiologico e stimare la risposta emodinamica. Tuttavia, ad oggi, non esiste un metodo standard per l'analisi del segnale ottico. In questa tesi, quindi, è stato proposto e validato un nuovo algoritmo, messo a punto per far fronte agli svantaggi associati ai metodi presenti in letteratura. Nonostante la ridotta sensibilità agli artefatti da movimento, il segnale ottico ne risulta comunque contaminato, soprattutto durante acquisizioni di popolazioni patologiche (per esempio pazienti diagnosticati con ictus) o difficili (come per esempio i neonati). Sono state proposte numerose tecniche per correggere gli artefatti da movimento, invece di eliminare la parte di segnale da essi contaminata. Tuttavia, nessuna di queste tecniche, per il momento, è riuscita a emergere come la più adatta per l'analisi del segnale ottico. In aggiunta a questo, non esistono criteri oggettivi con cui sia possibile selezionare la tecnica migliore da applicare, dato un segnale misurato. Si suppone, infatti, che, data l'estrema variabilità presente negli artefatti da movimento in termini di forma, contenuto in frequenza e ampiezza, la tecnica da applicare sia dipendente dal segnale misurato nello specifico caso. Da ciò emerge la necessità di fornire agli sperimentatori dei criteri oggettivi, che permettano loro di selezionare la tecnica di correzione più adatta ad ogni segnale misurato. In questa tesi, quindi, è stato proposto un innovativo ed oggettivo approccio per la selezione della tecnica di correzione da utilizzare. La validazione è stata eseguita su dei segnali contenenti una tipologia di artefatto da movimento molto difficile da identificare e correggere. FNIRS permette di ottenere solo misure spettroscopiche delle variazioni di concentrazione di emoglobina; DOT invece è in grado di ricostruire immagini tridimensionali delle variazioni di concentrazione di HbO e HbR. Per aumentare l'accuratezza e l'interpretabilità delle immagini ricostruite con DOT, è necessario fornire accurate informazioni anatomiche di supporto. Numerosi modelli di teste per tecniche ottiche sono stati proposti e validati nella popolazione adulta. Al contrario, in quella neonatale, i modelli analoghi creati finora sono molto pochi e tutti riferiti ad una sola età neonatale. Tuttavia, nei neonati, il cervello è soggetto ad una crescita ed una maturazione molto rapida. Per questo motivo, modelli riferiti ad una singola età neonatale falliscono nel fornire informazioni anatomiche corrette per ogni neonato sotto esame. In questa tesi si è proposto un innovativo modello 4D di teste per tecniche ottiche, contenente informazioni anatomiche per neonati pretermine e a termine. Questo modello può fornire ai neuroscienziati che lavorano in ambito evolutivo la possibilità di selezionare il modello corrispondente all'età del neonato in esame e ricostruire quindi le immagini di variazione di concentrazione di emoglobina usando un'anatomia il più possibile vicina a quella reale. L'organizzazione della tesi è la seguente. Nei primi capitoli verrà analizzato lo stato dell'arte delle tecniche ottiche. In particolare nel capitolo 1 verrà presentata una breve introduzione dei principi fisici alla base di queste tecniche alla quale seguirà un confronto con le tecniche di neuroimmagini più diffuse. Il capitolo 2 descriverà le componenti del segnale ottico misurato e verrà illustrato lo stato dell'arte relativo ad algoritmi di rimozione del rumore fisiologico. Successivamente sarà esposta la teoria che sta alla base del processo di ricostruzione delle immagini. Nella parte finale del capitolo, invece, verranno presentati alcuni studi che hanno utilizzato tecniche ottiche sia nella popolazione adulta che in età evolutiva. Infine saranno presentati gli scopi di questa tesi. I capitoli 3, 4 e 5 saranno dedicati alla presentazione di nuovi strumenti e metodologie per l'analisi del segnale ottico e per la ricostruzione di immagini ottiche. In particolare nel capitolo 3 verrà introdotto un nuovo algoritmo per la rimozione del rumore fisiologico e la stima della risposta emodinamica. La metodologia proposta verrà validata tramite il confronto con due algoritmi preesistenti. Il capitolo 4 tratterà il problema degli artefatti da movimento e proporrà un innovativo e oggettivo approccio per la selezione della tecnica di correzione da utilizzare. Le principali tecniche di correzione verranno illustrate e il nuovo approccio verrà validato utilizzando dati cognitivi reali. Nel capitolo 5 verrà presentato un nuovo atlante 4D neonatale di modelli di teste per tecniche ottiche. Verranno descritti tutti i passaggi che hanno portato allo sviluppo di questo atlante e ne sarà riportato un esempio applicativo. La parte finale di questa tesi (capitoli 6, 7 e 8) presenterà tre distinti esempi applicativi, su dati neurali empirici, delle metodologie e strumenti proposti. L'algoritmo per la rimozione del rumore fisiologico proposto nel capitolo 3 sarà utilizzato nel capitolo 6 per stimare differenze temporali poco evidenti tra risposte emodinamiche, misurate in due diverse aree della corteccia durante compiti di movimento manuale di diversa durata. Nel capitolo 7 lo stesso algoritmo verrà applicato a dati acquisiti durante un paradigma di memoria visiva a breve termine. Infine nel capitolo 8 verranno ricostruite immagini di variazioni di concentrazione di emoglobina, utilizzando il modello di teste per tecniche ottiche presentato nel capitolo 5. I dati sono stati acquisiti da un neonato a termine e il modello di testa utilizzato nella ricostruzione è quello relativo all'età corrispondente. Nello stesso capitolo verranno ricostruite immagini di concentrazione sia in presenza che in assenza di tecniche di correzione di artefatti da movimento, evidenziandone così l'importanza