We investigated whether the visual hMT+ cortex plays a role in supramodal representation of sensory flow, not mediated by visual mental imagery. We used functional magnetic resonance imaging to measure neural activity in sighted and congenitally blind individuals during passive perception of optic and tactile flows. Visual motion-responsive cortex, including hMT+, was identified in the lateral occipital and inferior temporal cortices of the sighted subjects by response to optic flow. Tactile flow perception in sighted subjects activated the more anterior part of these cortical regions but deactivated the more posterior part. By contrast, perception of tactile flow in blind subjects activated the full extent, including the more posterior part. These results demonstrate that activation of hMT+ and surrounding cortex by tactile flow is not mediated by visual mental imagery and that the functional organization of hMT+ can develop to subserve tactile flow perception in the absence of any visual experience. Moreover, visual experience leads to a segregation of the motion-responsive occipitotemporal cortex into an anterior subregion involved in the representation of both optic and tactile flows and a posterior subregion that processes optic flow only.

Observing and learning actions and behaviors from others, a mechanism crucial for survival and social interaction, engages the mirror neuron system. To determine whether vision is a necessary prerequisite for the human mirror system to develop and function, we used functional magnetic resonance imaging to compare brain activity in congenitally blind individuals during the auditory presentation of hand-executed actions or environmental sounds, and the motor pantomime of manipulation tasks, with that in sighted volunteers, who additionally performed a visual action recognition task. Congenitally blind individuals activated a premotor-temporoparietal cortical network in response to aurally presented actions that overlapped both with mirror system areas found in sighted subjects in response to visually and aurally presented stimuli, and with the brain response elicited by motor pantomime of the same actions. Furthermore, the mirror system cortex showed a significantly greater response to motor familiar than to unfamiliar action sounds in both sighted and blind individuals. Thus, the mirror system in humans can develop in the absence of sight. The results in blind individuals demonstrate that the sound of an action engages the mirror system for action schemas that have not been learned through the visual modality and that this activity is not mediated by visual imagery. These findings indicate that the mirror system is based on supramodal sensory representations of actions and, furthermore, that these abstract representations allow individuals with no visual experience to interact effectively with others.

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Federated Learning (FL) has emerged as a promising technique for edge devices to collaboratively learn a shared prediction model, while keeping their training data on the device, thereby decoupling the ability to do machine learning from the need to store the data in the cloud. However, FL is difficult to implement and deploy in practice, considering the heterogeneity in mobile devices, e.g., different programming languages, frameworks, and hardware accelerators. Although there are a few frameworks available to simulate FL algorithms (e.g., TensorFlow Federated), they do not support implementing FL workloads on mobile devices. Furthermore, these frameworks are designed to simulate FL in a server environment and hence do not allow experimentation in distributed mobile settings for a large number of clients. In this paper, we present Flower 1 , a FL framework which is both agnostic towards heterogeneous client environments and also scales to a large number of clients, including mobile and embedded devices. Flower's abstractions let developers port existing mobile workloads with little overhead, regardless of the programming language or ML framework used, while also allowing researchers flexibility to experiment with novel approaches to advance the state-of-the-art. We describe the design goals and implementation considerations of Flower and show our experiences in evaluating the performance of FL across clients with heterogeneous computational and communication capabilities. 1 https://flower.dev/ Preprint. Under review.

The present study was designed to investigate the brain functional architecture that subserves visuo-spatial and motor processing in highly skilled individuals. By using functional magnetic resonance imaging (fMRI), we measured brain activity while eleven Formula racing-car drivers and eleven ‘naïve’ volunteers performed a motor reaction and a visuo-spatial task. Tasks were set at a relatively low level of difficulty such to ensure a similar performance in the two groups and thus avoid any potential confounding effects on brain activity due to discrepancies in task execution. The brain functional organization was analyzed in terms of regional brain response, inter-regional interactions and blood oxygen level dependent (BOLD) signal variability. While performance levels were equal in the two groups, as compared to naïve drivers, professional drivers showed a smaller volume recruitment of task-related regions, stronger connections among task-related areas, and an increased information integration as reflected by a higher signal temporal variability. In conclusion, our results demonstrate that, as compared to naïve subjects, the brain functional architecture sustaining visuo-motor processing in professional racing-car drivers, trained to perform at the highest levels under extremely demanding conditions, undergoes both ‘quantitative’ and ‘qualitative’ modifications that are evident even when the brain is engaged in relatively simple, non-demanding tasks. These results provide novel evidence in favor of an increased ‘neural efficiency’ in the brain of highly skilled individuals.

Human middle temporal complex (hMT+) responds also to the perception of non-visual motion in both sighted and early blind individuals, indicating a supramodal organization. Visual experience, however, leads to a segregation of hMT+ into a more anterior subregion, involved in the supramodal representation of motion, and a posterior subregion that processes visual motion only. In contrast, in congenitally blind subjects tactile motion activates the full extent of hMT+. Here, we used fMRI to investigate brain areas functionally connected with the two hMT+ subregions (seeds) during visual and tactile motion in sighted and blind individuals. A common functional connectivity network for motion processing, including bilateral ventral and dorsal extrastriate, inferior frontal, middle and inferior temporal areas, correlated with the two hMT+ seeds both in sighted and blind individuals during either visual or tactile motion, independently from the sensory modality through which the information was acquired. Moreover, ventral premotor, somatosensory, and posterior parietal areas correlated only with the anterior but not with the posterior portion of hMT+ in sighted subjects, and with both hMT+ seeds in blind subjects. Furthermore, a correlation between middle temporal and occipital areas with primary somatosensory seeds was demonstrated across conditions in both sighted and blind individuals, suggesting a cortico-cortical pathway that conveys non-visual information from somatosensory cortex, through posterior parietal regions, to ventral extrastriate cortex. These findings expand our knowledge about the development of the functional organization within hMT+ by showing that distinct patterns of brain functional correlations originate from the anterior and posterior hMT+ subregions as a result of visual experience.

Breast lesion detection employing state of the art microwave systems provide a safe, non-ionizing technique that can differentiate healthy and non-healthy tissues by exploiting their dielectric properties. In this paper, a microwave apparatus for breast lesion detection is used to accumulate clinical data from subjects undergoing breast examinations at the Department of Diagnostic Imaging, Perugia Hospital, Perugia, Italy. This paper presents the first ever clinical demonstration and comparison of a microwave ultra-wideband (UWB) device augmented by machine learning with subjects who are simultaneously undergoing conventional breast examinations. Non-ionizing microwave signals are transmitted through the breast tissue and the scattering parameters (S-parameter) are received via a dedicated moving transmitting and receiving antenna set-up. The output of a parallel radiologist study for the same subjects, performed using conventional techniques, is taken to pre-process microwave data and create suitable data for the machine intelligence system. These data are used to train and investigate several suitable supervised machine learning algorithms nearest neighbour (NN), multi-layer perceptron (MLP) neural network, and support vector machine (SVM) to create an intelligent classification system towards supporting clinicians to recognise breasts with lesions. The results are rigorously analysed, validated through statistical measurements, and found the quadratic kernel of SVM can classify the breast data with 98% accuracy.

In life, everyone goes through hurtful events caused by significant others: a deceiving friend, a betraying partner, or an unjustly blaming parent. In response to painful emotions, individuals may react with anger, hostility, and the desire for revenge. As an alternative, they may decide to forgive the wrongdoer and relinquish resentment. In the present study, we examined the brain correlates of forgiveness using functional Magnetic Resonance Imaging (fMRI). Healthy participants were induced to imagine social scenarios that described emotionally hurtful events followed by the indication to either forgive the imagined offenders, or harbor a grudge toward them. Subjects rated their imaginative skills, levels of anger, frustration, and/or relief when imagining negative events as well as following forgiveness. Forgiveness was associated with positive emotional states as compared to unforgiveness. Granting forgiveness was associated with activations in a brain network involved in theory of mind, empathy, and the regulation of affect through cognition, which comprised the precuneus, right inferior parietal regions, and the dorsolateral prefrontal cortex. Our results uncovered the neuronal basis of reappraisal-driven forgiveness, and extend extant data on emotional regulation to the resolution of anger and resentment following negative interpersonal events.