Marco Tettamanti

Reconciling the anatomical observation that the human brain comprises two asymmetrical halves with the phenomenal unity of the mind is a puzzle that has challenged neuroscientists since the dawn of research in the field. White-matter commissural fibres of the corpus callosum constitute a critical anatomical substrate for the functional resolution of this anatomical duality. However, the extent of the functional involvement of the callosum in different domains of cognition represents, to this day, a mostly uncharted territory. Here we present a probabilistic characterization of callosal involvement in a set of cognitive functions. In particular, we estimated structural callosal connections by means of the Disconnectome approach applied to a reference sample of healthy participants while using the macro-anatomical cortical areas contained in the Harvard-Oxford template as seeds. By multiplying structural connectivity by the involvement of each cortical area in a set of cognitive functions (as derived from Neurosynth meta-analyses), we produced a voxel-wise characterization of the corpus callosum in different functional domains. We were able to highlight greater involvement of posterior callosal regions in vision and episodic memory, greater involvement of more anterior callosal regions in decision making and working memory, with somatosensory and motor functions more related to the central dorsal portion of the callosum.

The experience of making sense of novel words is ubiquitous in human communication. Still, novel words have traditionally been considered as meaningless by cognitive research. Here we combined behavioral, univariate and multivariate fMRI techniques, and computational modelling to explore whether and how novel words activate the neurocognitive hallmarks of semantic processing triggered by existing words, and whether this process is influenced by the presence of familiar functional linguistic elements, i.e., morphemes. We observed that semantic activation for novel words is comparable to that of existing words, provided that novel words contain a concatenation of identifiable morphemes. In addition, representational similarity analysis highlighted that existing words and novel words containing morphemes (but not novel words not containing morphemes) can activate fine-grained semantic representations. These results suggest that the difference in the neurocognitive underpinnings of semantic processing for existing and novel words might be quantitative rather than qualitative and based on how reliably linguistic form points to meaning.

Social interaction relies on neurocognitive processes that support mutual prediction and coordination. Traditional neuroimaging investigates brain activity at the individual level, limiting insight into the reciprocal nature of social exchange. Hyperscanning overcomes this by simultaneously recording brain activity from interacting individuals. We conducted a systematic review of 28 functional magnetic resonance imaging (fMRI) hyperscanning studies examining inter-brain coupling during interactive tasks. We assessed study features and examined whether paradigms included four key properties that make the use of hyperscanning particularly valuable over single-brain designs: real-time reciprocity, mutual information flow, unpredictability, and irreproducibility. Substantial methodological heterogeneity was observed, and only a few studies incorporated all four theoretically relevant features. To identify consistent spatial neural patterns of inter-brain coupling, we performed coordinate-based hierarchical clustering on residual (task-independent) and task-evoked coupling data. The latter was further analysed in relation to the complexity of the interaction. Residual coupling consistently involved the right posterior superior temporal gyrus, overlapping with the anterior temporo-parietal junction (TPJ), suggesting a role in spontaneous alignment. Task-evoked coupling differed by interactional complexity, with posterior temporal regions involved in low-complexity tasks, and medial frontal, mid-cingulate, and insular areas in high-complexity ones. These findings support the relevance of fMRI hyperscanning for studying inter-brain dynamics and inform future methodological development.

Dyslexia is a neurobiological disorder characterized by reading difficulties, yet its causes remain unclear. Neuroimaging and behavioral studies found anomalous responses in tasks requiring phonological processing, motion perception, and implicit learning, and showed gray and white matter abnormalities in dyslexics compared to controls, indicating that dyslexia is highly heterogeneous and promoting a multifactorial approach. To evaluate whether combining behavioral and multimodal MRI improves sensitivity in identifying dyslexia neurocognitive traits compared to monocomponential approaches, 19 dyslexic and 19 control subjects underwent cognitive assessments, multiple (phonological, visual motion, rhythmic) mismatch-response functional MRI tasks, structural diffusion-weighted imaging (DWI) and T1-weighted imaging. Between group differences in the neurocognitive measures were tested with univariate and multivariate approaches. Results showed that dyslexics performed worse than controls in phonological tasks and presented reduced cerebellar responses to mismatching rhythmic stimuli, as well as structural disorganization in white matter tracts and cortical regions. Most importantly, a machine learning model trained with features from all three MRI modalities discriminated between dyslexics and controls with greater accuracy than single-modality models. The individual classification scores in the multimodal machine learning model correlated with behavioral reading accuracy. These results characterize dyslexia as a composite condition with multiple distinctive cognitive and brain traits.

The maturation of the auditory-language brain network begins before birth, driven by gene-environment interactions. We investigated the association between familial and environmental factors and the foetal development of this network, as well as the predictive value of this association for postnatal language outcomes. Using prenatal resting-state fMRI, we examined 25 foetuses to identify functional connectivity within the auditory-language network. Postnatal language was assessed longitudinally between 1 and 3 years using the Bayley-III scale. Familial risk for language disorders and prenatal speech exposure were quantified using a newly developed questionnaire. First, hierarchical clustering on foetal functional connectivity confirmed that an auditory-language network can be identified in the foetal brain. In this network, foetuses with higher speech exposure exhibited increased connectivity between left-hemisphere regions and decreased connectivity between homologous right-hemisphere regions. Higher familial risk was linked to reduced connectivity within the left language network. Regression analyses revealed that prenatal functional connectivity between insula, caudate nucleus, and rolandic operculum significantly predicted postnatal language. These findings underscore the critical role of genetic and environmental influences in functionally shaping the foetal auditory-language network, with lasting impacts on early language development. By integrating prenatal brain connectivity, familial risk, and speech exposure, this study provides new insights into prenatal language neurodevelopment, highlighting its importance for future language capabilities.

The recognition of manipulable objects results from the encoding of sensory input in combination with predictive decoding of experience-derived visuomotor information stored in conceptual-semantic representations. This grounded interpretative processing was previously found to subsist even under unaware perception of manipulable object pictures. In this fMRI study, we first aimed to extend this finding by testing whether experientially grounded visuomotor representations are unawarely recruited when manipulable objects are not visually depicted, but only referred to by words presented subliminally through continuous flash suppression. Second, we assessed the generalizability of decoding experience-derived conceptual information to other semantic categories, by extending our investigation to subliminally presented emotion words and testing for unaware recruitment of grounded emotion representations in the limbic system. Univariate analysis of data sampled from 21 human participants (14 females) showed that manipulable object words selectively activated a left-lateralized visuomotor network, both when words were presented below perceptual threshold and when participants subjectively reported lack of stimulus awareness. Emotion words selectively engaged the bilateral limbic network, although univariate analysis did not provide evidence for its recruitment under subliminal perceptual conditions. In turn, multivariate pattern analysis showed that neural codes associated with both manipulable object and emotion words could be decoded even in the absence of perceptual awareness. These findings suggest that the brain automatically engages in conceptual-semantic decoding of experience-derived information not only when circumstances require to interact with manipulable objects and emotions, but also when these referents are dislocated in time and space and only referred to by words.

In the field of developmental neuropsychology, interesting patterns of association between functional brain development at birth and neurodevelopmental outcomes during early childhood have been recently highlighted. In this work, we investigated a population of preterm neonates ( n = 32) and (1) derived perinatal functional connectivity (p-FC) markers of prematurity, through direct comparison with a group of at-term borns and (2) tested the role of these markers as predictors of cognitive (COG), language (LANG), and socioemotional (SE) outcomes measured at 6, 12, 24, and 36 months. We did this by means of regression models in which functional markers were tested as predictors, after accounting for variability captured by metrics derived from current clinical practice and which were previously reported to be associated with a higher risk for adverse neurodevelopmental outcomes (i.e., pregnancy, perinatal weight and physiological conditions, and structural brain development variability). Our results revealed that (1) p-FC between the bilateral cerebellar hemispheres predicted SE outcomes at 6 months; (2) p-FC between the bilateral visual cortices predicted COG outcomes at 12 months; (3) p-FC between cortices related to language and emotional control predicted SE outcomes at 12 months; (4 and 5) p-FC between somatosensory motor and higher-order control cortices predicted LANG outcomes at 24 months and COG outcomes at 36 months; and (6 and 7) p-FC between language-related cortices predicted SE and COG outcomes at 36 months. Linear mixed model analyses with pattern mixture modeling, performed to comprehensively explore the longitudinal impact of significant perinatal functional predictors, demonstrated the importance of specific perinatal functional predictors of global neurodevelopment over time. We discuss our results by suggesting that perinatal functional imaging of the brain at rest could represent a very valuable and unique addition to current preterm clinical care routines, to improve pediatric clinical practices of the near future.

Dyslexia is a neurobiological disorder characterised by reading difficulties, yet its underlying causes remain unclear. Neuroimaging and behavioural studies found anomalous responses in tasks requiring phonological processing, motion perception, and implicit learning, and showed gray and white matter abnormalities in several brain regions of dyslexics compared to controls, indicating that dyslexia is a heterogeneous condition and promoting a multifactorial approach. In order to evaluate whether the combination of behavioural and multimodal MRI can have greater sensitivity in identifying neurocognitive traits of dyslexia compared to monocomponential approaches, in 19 dyslexic and 19 control subjects we acquired behavioural cognitive assessments, multiple (phonological, visual motion, rhythmic) mismatch-response functional MRI tasks, structural diffusion-weighted and T1-weighted images. To examine between-group differences in the multimodal neurocognitive measures, we applied univariate and multivariate approaches. Results showed that dyslexics performed worse than controls in behavioural phonological tasks. Neuroimaging analyses revealed that individuals with dyslexia present reduced cerebellar responses to mismatching rhythmic stimuli, as well as structural disorganization in several white matter tracts and cortical regions previously implicated in dyslexia. Most importantly, in line with the view of dyslexia as a multifactorial phenomenon, a machine learning model trained with features from all three MRI modalities (functional, diffusion, and T1-weighted) discriminated between dyslexics and controls with greater accuracy than models including just one modality. The individual classification scores in the multimodal machine learning model correlated with behavioural reading accuracy. These results confirm that dyslexia should be approached as a composite condition characterised by multiple distinctive cognitive and brain features.