fMRI Investigation of Cortical and Subcortical Networks in the Learning of Abstract and Effector-Specific Representations of Motor Sequences

A visuomotor sequence can be learned as a series of visuo-spatial cues or as a sequence of effector movements. Earlier imaging studies have revealed that a network of brain areas is activated in the course of motor sequence learning. However these studies do not address the question of the type of representation being established at various stages of visuomotor sequence learning. In an earlier behavioral study, we demonstrated that acquisition of visuo-spatial sequence representation enables rapid learning in the early stage and progressive establishment of somato-motor representation helps speedier execution by the late stage. We conducted functional magnetic resonance imaging (fMRI) experiments wherein subjects learned and practiced the same sequence alternately in normal and rotated settings. In one rotated setting (visual), subjects learned a new motor sequence in response to an identical sequence of visual cues as in normal. In another rotated setting (motor), the display sequence was altered as compared to normal, but the same sequence of effector movements were used to perform the sequence. Comparison of different rotated settings revealed analogous transitions both in the cortical and subcortical sites during visuomotor sequence learning  a transition of activity from parietal to parietal-premotor and then to premotor cortex and a concomitant shift was observed from anterior putamen to a combined activity in both anterior and posterior putamen and finally to posterior putamen. These results suggest a putative role for engagement of different cortical and subcortical networks at various stages of learning in supporting distinct sequence representations

Inhibition of left anterior intraparietal sulcus shows that mutual adjustment marks dyadic joint-actions in humans

Creating real-life dynamic contexts to study interactive behaviors is a fundamental challenge for the social neuroscience of interpersonal relations. Real synchronic interpersonal motor interactions involve online, inter-individual mutual adaptation (the ability to adapt one's movements to those of another in order to achieve a shared goal). In order to study the contribution of the left anterior Intra Parietal Sulcus (aIPS) (i.e. a region supporting motor functions) to mutual adaptation, here, we combined a behavioral grasping task where pairs of participants synchronized their actions when performing mutually adaptive imitative and complementary movements, with the inhibition of activity of aIPS via non-invasive brain stimulation. This approach allowed us to investigate whether aIPS supports online complementary and imitative interactions. Behavioral results showed that inhibition of aIPS selectively impairs pair performance during complementary compared to imitative interactions. Notably, this effect depended on pairs' mutual adaptation skills and was higher for pairs composed of participants who were less capable of adapting to each other. Thus, we provide the first causative evidence for a role of the left aIPS in supporting mutually adaptive interactions and show that the inhibition of the neural resources of one individual of a pair is compensated at the dyadic level

Decoding visual object categories in early somatosensory cortex

Neurons, even in the earliest sensory areas of cortex, are subject to a great deal of contextual influence from both within and across modality connections. In the present work, we investigated whether the earliest regions of somatosensory cortex (S1 and S2) would contain content-specific information about visual object categories. We reasoned that this might be possible due to the associations formed through experience that link different sensory aspects of a given object. Participants were presented with visual images of different object categories in 2 fMRI experiments. Multivariate pattern analysis revealed reliable decoding of familiar visual object category in bilateral S1 (i.e., postcentral gyri) and right S2. We further show that this decoding is observed for familiar but not unfamiliar visual objects in S1. In addition, whole-brain searchlight decoding analyses revealed several areas in the parietal lobe that could mediate the observed context effects between vision and somatosensation. These results demonstrate that even the first cortical stages of somatosensory processing carry information about the category of visually presented familiar objects

How skill expertise shapes the brain functional architecture: an fMRI study of visuo-spatial and motor processing in professional racing-car and naïve drivers

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

Does extensive motor learning trigger local sleep?

After prolonged learning we all have experienced a reduction of alertness, resulting in errors that we would normally not make. Despite this being a common situation in everyday life, the reasons for this phenomenon are unclear. A possible explanation is that the regions of the brain which are involved in the learning, go off-line trying to partially recover. This event is defined as local sleep and it has been detected in animals and sleep-deprived humans performing learning tasks. Local sleep is a sleep-like electrophysiological activity occurring locally, while the rest of the brain is fully awake, and producing performance deterioration. However, since all the studies included both lack of sleep and learning, it is uncertain whether such phenomenon is related to sleep deprivation or if it is the consequence of prolonged learning. Further, local sleep has not been related to electrophysiological changes occurring during the task. This thesis aimed to assess, for the first time in well rested subjects, whether local sleep and performance decline occur because of prolonged learning. Specifically, the goal was to discriminate between sustained practice and learning, as to determine whether learning is required to cause local sleep. Also, a 90-minute nap was evaluated to establish whether sleep is necessary to counterbalance neuronal fatigue and performance decrease. The starting hypothesis was that local sleep is a plasticity-related phenomenon affecting performance and requiring learning to be triggered. Consequently, sleep would be a prerequisite to counterbalance performance and electrophysiological changes. High-Density EEG and behavioral data of 78 healthy young subjects were collected during and after two learning tasks performed for three hours: a visual sequence learning task, and a visuo-motor rotation task, randomly selected. Afterward, subjects were divided in two groups: those who slept for one hour and a half and those who remained awake and quietly rested for the same amount of time before being tested for electrophysiological and behavioral changes. Moreover, to discriminate between the effects of prolonged learning and practice, 11 additional subjects performed a control condition consisting in planar upper limb reaching movements instead of the above-mentioned learning tasks. In detail, the power spectrum of the EEG activity during the task and at rest with eyes opened was divided into five ranges to determine frequency changes of the EEG activity: delta 1 to 4 Hz; theta 4 to 8 Hz; alpha 8 to 13 Hz, beta 13 to 25 Hz, gamma 25 to 55 Hz. Additionally, movement-related beta activity of 35 young subjects was analyzed to find a relationship between task related oscillations and performance indices, as the modulatory activity during practice may reflect plasticity-related phenomena that can describe the occurrence of local sleep. Finally, 13 young subjects were compared to a dataset of 13 older participants who performed planar upper limb reaching movements to determine whether beta oscillations were affected by age. Specifically, beta activity was assessed during reaching movements in different brain regions, in terms of topography, magnitude, and peak frequency. Results demonstrated that sustained learning produced electrophysiological changes both at rest and during the task. In fact, resting state was characterized by a progressive slowing of the EEG activity over areas overlapping with those engaged during the task. Precisely, we detected task-related activity mainly in the high-frequency ranges (gamma and beta right temporo-parietal activity for the visual sequence learning task; alpha and beta activity over a fontal and left parietal areas for the visuo-motor rotation); the same areas were characterized by a progressive increase of the low frequency EEG activity at rest ranging from alpha, beta after one hour of practice, to theta after three one-hour blocks. The control task did not trigger such EEG slowing, as reaching movements without learning did only left an alpha, beta trace in the resting state over a cluster reflecting the motor area contralateral to the movement. Further, continuous learning triggered performance deteriorations only in tests sharing the same neural substrate of the previously performed task. In other words, the visuo-motor learning task only affected performance in a motor test consisting in random reaching movements; conversely, visual sequence learning altered performance on a visual working memory test, but did not influence reaching movements. Also, the control condition did not affect performance in any of the two exercises. Performance decline, learning ability and local sleep were partially renormalized by a 90-minute nap but not by an equivalent period of wake. As such, the global EEG activity, computed as the mean power of all the electrodes, was not affected by either 90 minutes of sleep or quiet wake. However, the regions characterized by low frequency at rest benefited from the sleep period, as the low frequencies content partially decreased after the nap but not after quiet wake. Task related beta activity during motor practice presented similar magnitude and timing patterns in different brain areas, with a progressive increase with practice, in both young and older subjects, despite the older subjects performing slower, less accurate movements. Intriguingly, the motor areas showed a post movement beta synchronization having a peak between 15 and 18 Hz, as opposed to a frontal area that has it between 23 and 29 Hz. Finally, results did not reveal any direct relationship between EEG beta oscillations and performance indices. Altogether, these results indicate that local sleep and performance decrease can be triggered by prolonged learning in well rested subjects; furthermore, some amount of sleep can partially renormalize learning ability, EEG activity and performance. Also, differences in the brainnoscillations during motor activity can express separate processes underlying motor planning, execution and skills acquisition. The present study adds some important knowledge in the field of local sleep; in fact, it suggests that such phenomenon is triggered by sustained learning rather than sleep deprivation, thus being a plasticity-related phenomenon. Finally, the role of sleep on counterbalancing local sleep has been proved, despite additional studies are required to establish whether a full night of sleep rather than a specific amount of time is needed to fully restore learning ability and electrophysiological activity. In conclusion, the present findings are of importance in all the fields where sustained learning is required, such as rehabilitative programs, sport and military trainings, and must be taken into account when plasticity plays a fundamental role in the acquisition of new skills

It’s not all in your car: functional and structural correlates of exceptional driving skills in professional racers

Driving is a complex behavior that requires the integration of multiple cognitive functions. While many studies have investigated brain activity related to driving simulation under distinct conditions, little is known about the brain morphological and functional architecture in professional competitive driving, which requires exceptional motor and navigational skills. Here, 11 professional racing-car drivers and 11 “naïve” volunteers underwent both structural and functional brain magnetic resonance imaging (MRI) scans. Subjects were presented with short movies depicting a Formula One car racing in four different official circuits. Brain activity was assessed in terms of regional response, using an Inter-Subject Correlation (ISC) approach, and regional interactions by mean of functional connectivity. In addition, voxel-based morphometry (VBM) was used to identify specific structural differences between the two groups and potential interactions with functional differences detected by the ISC analysis. Relative to non-experienced drivers, professional drivers showed a more consistent recruitment of motor control and spatial navigation devoted areas, including premotor/motor cortex, striatum, anterior, and posterior cingulate cortex and retrosplenial cortex, precuneus, middle temporal cortex, and parahippocampus. Moreover, some of these brain regions, including the retrosplenial cortex, also had an increased gray matter density in professional car drivers. Furthermore, the retrosplenial cortex, which has been previously associated with the storage of observer-independent spatial maps, revealed a specific correlation with the individual driver's success in official competitions. These findings indicate that the brain functional and structural organization in highly trained racing-car drivers differs from that of subjects with an ordinary driving experience, suggesting that specific anatomo-functional changes may subtend the attainment of exceptional driving performance