RESUMO
The brain-derived neurotrophic factor (BDNF) is an essential regulator of synaptic plasticity, a candidate neurobiological mechanism underlying learning and memory. A functional polymorphism in the BDNF gene, Val66Met (rs6265), has been linked to memory and cognition in healthy individuals and clinical populations. Sleep contributes to memory consolidation, yet information about the possible role of BDNF in this process is scarce. To address this question, we investigated the relationship between the BDNF Val66Met genotype and consolidation of episodic declarative and procedural (motor) non-declarative memories in healthy adults. The carriers of Met66 allele, as compared with Val66 homozygotes, showed stronger forgetting overnight (24 h after encoding), but not over shorter time (immediately or 20 min after word list presentation). There was no effect of Val66Met genotype on motor learning. These data suggest that BDNF plays a role in neuroplasticity underlying episodic memory consolidation during sleep.
Assuntos
Memória Episódica , Adulto , Humanos , Fator Neurotrófico Derivado do Encéfalo/genética , Genótipo , Polimorfismo de Nucleotídeo Único/genética , Sono/genéticaRESUMO
There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.
Assuntos
Inteligência Artificial , Conhecimento , Aprendizagem/fisiologia , Modelos Neurológicos , Robótica , Comunicação , Humanos , Resolução de Problemas/fisiologiaRESUMO
There is increasing evidence that sleep promotes off-line enhancement of a variety of explicitly learned motor tasks in young adults. However, whether sleep promotes off-line consolidation of implicitly learned motor tasks is still under question. Furthermore, the role of sleep in promoting transfer of learning remains unknown. This study examined the role of sleep in learning and transfer of learning of an implicit continuous motor task. Twenty-three neurologically intact individuals (mean age 26.4 years) were randomly assigned to either a sleep group or a no-sleep group. The sleep group practiced a continuous tracking task in the evening and underwent retention and transfer testing the following morning, while the no-sleep group practiced the tracking task in the morning and underwent retention and transfer testing in the evening. The results show that in both the sleep and no-sleep groups, performance improved off-line without further practice for both the general skill and the sequence-specific skill. The results also indicate that sleep and time promote transfer of learning of both sequence-specific and general skill learning to a spatial and temporal variation of the motor task. These findings demonstrate that sleep does not play a critical role in promoting off-line learning and transfer of learning of an implicit continuous motor task.
RESUMO
OBJECTIVE: To investigate the effects of night sleep on motor cortical excitability with TMS (transcranial magnetic stimulation) and finger tapping performance. METHOD: Eight volunteers were enrolled to investigate the effects of day wake or night sleep on motor learning and finger performance. Each subject underwent a finger tapping task over a 12 hour period, which was employed to evaluate the motor cortical excitability affected by motor learning. Starting at 9:00 am for the day wake cycle and restarting at 9:00 pm for the night sleep cycle. The finger tapping task was the index finger of the non-dominant hand with the Hangul word personal computer (PC) training program. The data was assessed by comparing the changes observed with the cortical excitability and finger tapping performance tests between the day wake and night sleep after equivalent amounts of training. RESULTS: The results showed that in paired-pulse techniques, there was a significant decrease of intracortical inhibition (ICI) in the morning following the night sleep cycle (p<0.05), but no significant change was seen in the ICI in the evening for the day wake cycle. In addition a significant decrease of the ICI was observed in comparison to the morning following the night sleep cycle and the evening following the day wake cycle (p<0.05). The 140% recruitment curve (RC) and accuracy of the finger tapping performance demonstrated a significant improvement for both cycles (p<0.05). CONCLUSION: Through this study, we observed that the Hangul typing practice requires both explicit and implicit skill learning. And also the off-line learning during a night of sleep may be affected by an inhibitory neurotransmitter related synaptic plasticity and by the time dependent learning with recruitments of remote or less excitable motor neurons in the primary motor cortex.