RESUMEN
Learning new skills by watching others is important for social and motor development throughout the lifespan. Prior research has suggested that observational learning shares common substrates with physical practice at both cognitive and brain levels. In addition, neuroimaging studies have used multivariate analysis techniques to understand neural representations in a variety of domains, including vision, audition, memory, and action, but few studies have investigated neural plasticity in representational space. Therefore, although movement sequences can be learned by observing other people's actions, a largely unanswered question in neuroscience is how experience shapes the representational space of neural systems. Here, across a sample of male and female participants, we combined pretraining and posttraining fMRI sessions with 6 d of observational practice to determine whether the observation of action sequences elicits sequence-specific representations in human frontoparietal brain regions and the extent to which these representations become more distinct with observational practice. Our results showed that observed action sequences are modeled by distinct patterns of activity in frontoparietal cortex and that such representations largely generalize to very similar, but untrained, sequences. These findings advance our understanding of what is modeled during observational learning (sequence-specific information), as well as how it is modeled (reorganization of frontoparietal cortex is similar to that previously shown following physical practice). Therefore, on a more fine-grained neural level than demonstrated previously, our findings reveal how the representational structure of frontoparietal cortex maps visual information onto motor circuits in order to enhance motor performance.SIGNIFICANCE STATEMENT Learning by watching others is a cornerstone in the development of expertise and skilled behavior. However, it remains unclear how visual signals are mapped onto motor circuits for such learning to occur. Here, we show that observed action sequences are modeled by distinct patterns of activity in frontoparietal cortex and that such representations largely generalize to very similar, but untrained, sequences. These findings advance our understanding of what is modeled during observational learning (sequence-specific information), as well as how it is modeled (reorganization of frontoparietal cortex is similar to that previously shown following physical practice). More generally, these findings demonstrate how motor circuit involvement in the perception of action sequences shows high fidelity to prior work, which focused on physical performance of action sequences.
Asunto(s)
Lóbulo Frontal/fisiología , Aprendizaje/fisiología , Imagen por Resonancia Magnética/métodos , Lóbulo Parietal/fisiología , Estimulación Luminosa/métodos , Desempeño Psicomotor/fisiología , Adulto , Femenino , Lóbulo Frontal/diagnóstico por imagen , Humanos , Masculino , Movimiento/fisiología , Lóbulo Parietal/diagnóstico por imagen , Adulto JovenRESUMEN
When learning a new motor skill, we benefit from watching others. It has been suggested that observation of others' actions can build a motor representation in the observer, and as such, physical and observational learning might share a similar neural basis. If physical and observational learning share a similar neural basis, then motor cortex stimulation during observational practice should similarly enhance learning by observation as it does through physical practice. Here, we used transcranial direct-current stimulation (tDCS) to address whether anodal stimulation to M1 during observational training facilitates skill acquisition. Participants learned keypress sequences across four consecutive days of observational practice while receiving active or sham stimulation over M1. The results demonstrated that active stimulation provided no advantage to skill learning over sham stimulation. Further, Bayesian analyses revealed evidence in favour of the null hypothesis across our dependent measures. Our findings therefore provide no support for the hypothesis that excitatory M1 stimulation can enhance observational learning in a similar manner to physical learning. More generally, the results add to a growing literature that suggests that the effects of tDCS tend to be small, inconsistent, and hard to replicate. Future tDCS research should consider these factors when designing experimental procedures.
Asunto(s)
Conducta Imitativa/fisiología , Aprendizaje/fisiología , Corteza Motora/fisiología , Destreza Motora/fisiología , Desempeño Psicomotor/fisiología , Estimulación Transcraneal de Corriente Directa/métodos , Adolescente , Adulto , Técnicas de Observación Conductual/métodos , Femenino , Humanos , Masculino , Estimulación Luminosa/métodos , Adulto JovenRESUMEN
Proton MR spectroscopy ((1)H-MRS) complements other brain research methods by providing measures of neurometabolites noninvasively in a localized brain area. Improvements in MR scanner technologies, and data acquisition and analysis methods should allow functional (1)H-MRS (fMRS) to measure neurometabolite concentration changes during task-induced brain activation. The aim of the current study was to further develop event-related fMRS at 3T to investigate glutamate dynamics in response to repetition suppression. A secondary aim was to investigate the relationship between blood-oxygen-level-dependent (BOLD) responses and glutamate dynamics in the same paradigm at the same time. A novel approach of interleaved water-suppressed (metabolite) and unsuppressed (water) fMRS was used to simultaneously detect the event-related dynamics of glutamate and BOLD signal to repetition suppression in the lateral occipital cortex of thirteen (N=13) volunteers. On average, (1)H-MRS-visible glutamate increased after novel visual stimuli presentations by 12% and decreased by 11-13% on repeated compared to novel presentations. The BOLD signal, as measured by water peak amplitude changes, showed significant difference between Task and Rest trials, and, on a GLM based analysis of the time series, demonstrated a significant difference between the novel and repeated trials, however appeared to be decoupled from the glutamate response as no correlation was found between the two. These results are the first demonstration that reductions in neuronal activity typical of repetition suppression effects are reflected by reduced glutamatergic and BOLD measures, that glutamate and BOLD responses may not be coupled as previously thought, and that these changes and relationships can be measured simultaneously using event-related fMRS at 3T.
Asunto(s)
Adaptación Fisiológica , Mapeo Encefálico/métodos , Ácido Glutámico/metabolismo , Espectroscopía de Protones por Resonancia Magnética/métodos , Corteza Visual/metabolismo , Percepción Visual/fisiología , Adulto , Encéfalo/metabolismo , Potenciales Evocados Visuales , Femenino , Humanos , Masculino , Adulto JovenRESUMEN
Over the last two decades, inhibitory control has featured prominently in accounts of how humans and other organisms regulate their behaviour and thought. Previous work on how the brain stops actions and thoughts, however, has emphasised distinct prefrontal regions supporting these functions, suggesting domain-specific mechanisms. Here we show that stopping actions and thoughts recruits common regions in the right dorsolateral and ventrolateral prefrontal cortex to suppress diverse content, via dynamic targeting. Within each region, classifiers trained to distinguish action-stopping from action-execution also identify when people are suppressing their thoughts (and vice versa). Effective connectivity analysis reveals that both prefrontal regions contribute to action and thought stopping by targeting the motor cortex or the hippocampus, depending on the goal, to suppress their task-specific activity. These findings support the existence of a domain-general system that underlies inhibitory control and establish Dynamic Targeting as a mechanism enabling this ability.
Asunto(s)
Memoria/fisiología , Corteza Prefrontal/fisiología , Adulto , Femenino , Hipocampo , Humanos , Imagen por Resonancia Magnética , Masculino , Corteza Motora , Desempeño Psicomotor/fisiología , Adulto JovenRESUMEN
Humans have a remarkable ability to learn by watching others, whether learning to tie an elaborate knot or play the piano. However, the mechanisms that translate visual input into motor skill execution remain unclear. It has been proposed that common cognitive and neural mechanisms underpin learning motor skills by physical and observational practice. Here we provide a novel test of the common mechanism hypothesis by testing the extent to which certain individual differences predict observational as well as physical learning. Participants (Nâ¯=â¯92 per group) either physically practiced a five-element key-press sequence or watched videos of similar sequences before physically performing trained and untrained sequences in a test phase. We also measured cognitive abilities across participants that have previously been associated with rates of learning, including working memory and fluid intelligence. Our findings show that individual differences in working memory and fluid intelligence predict improvements in dissociable aspects of motor learning following physical practice, but not observational practice. Working memory predicts general learning gains from pre- to post-test that generalise to untrained sequences, whereas fluid intelligence predicts sequence-specific gains that are tied to trained sequences. However, neither working memory nor fluid intelligence predict training gains following observational learning. Therefore, these results suggest limits to the shared mechanism hypothesis of physical and observational learning. Indeed, models of observational learning need updating to reflect the extent to which such learning is based on shared as well as distinct processes compared to physical learning. We suggest that such differences could reflect the more intentional nature of learning during physical compared to observational practice, which relies to a greater extent on higher-order cognitive resources such as working memory and fluid intelligence.