Sense of agency in the human brain

In adult life, people normally know what they are doing. This experience of controlling one's own actions and, through them, the course of events in the outside world is called 'sense of agency'. It forms a central feature of human experience; however, the brain mechanisms that produce the sense of agency have only recently begun to be investigated systematically. This recent progress has been driven by the development of better measures of the experience of agency, improved design of cognitive and behavioural experiments, and a growing understanding of the brain circuits that generate this distinctive but elusive experience. The sense of agency is a mental and neural state of cardinal importance in human civilization, because it is frequently altered in psychopathology and because it underpins the concept of responsibility in human societies

Putting brain training to the test

‘Brain training’, or the quest for improved cognitive function through the regular use of computerised tests, is a multimillion pound industry1, yet scientific evidence to support its efficacy is lacking. Modest effects have been reported in some studies of older individuals2,3 and preschool children4, and video gamers out perform non-gamers on some tests of visual attention5. However, the widely held belief that commercially available computerised brain trainers improve general cognitive function in the wider population lacks empirical support. The central question is not whether performance on cognitive tests can be improved by training, but rather, whether those benefits transfer to other untrained tasks or lead to any general improvement in the level of cognitive functioning. Here we report the results of a six-week online study in which 11,430 participants trained several times each week on cognitive tasks designed to improve reasoning, memory, planning, visuospatial skills and attention. Although improvements were observed in every one of the cognitive tasks that were trained, no evidence was found for transfer effects to untrained tasks, even when those tasks were cognitively closely related

Feature-reduction and semi-simulated data in functional connectivity-based cortical parcellation

Recently, resting-state functional magnetic resonance imaging has been used to parcellate the brain into functionally distinct regions based on the information available in functional connectivity maps. However, brain voxels are not independent units and adjacent voxels are always highly correlated, so functional connectivity maps contain redundant information, which not only impairs the computational efficiency during clustering, but also reduces the accuracy of clustering results. The aim of this study was to propose feature-reduction approaches to reduce the redundancy and to develop semi-simulated data with defined ground truth to evaluate these approaches. We proposed a feature-reduction approach based on the Affinity Propagation Algorithm (APA) and compared it with the classic featurereduction approach based on Principal Component Analysis (PCA). We tested the two approaches to the parcellation of both semi-simulated and real seed regions using the K-means algorithm and designed two experiments to evaluate their noiseresistance. We found that all functional connectivity maps (with/without feature reduction) provided correct information for the parcellation of the semisimulated seed region and the computational efficiency was greatly improved by both featurereduction approaches. Meanwhile, the APA-based feature-reduction approach outperformed the PCAbased approach in noise-resistance. The results suggested that functional connectivity maps can provide correct information for cortical parcellation, and feature-reduction does not significantly change the information. Considering the improvement in computational efficiency and the noise-resistance, feature-reduction of functional connectivity maps before cortical parcellation is both feasible and necessary

A natural history of the human mind: tracing evolutionary changes in brain and cognition

Since the last common ancestor shared by modern humans, chimpanzees and bonobos, the lineage leading to Homo sapiens has undergone a substantial change in brain size and organization. As a result, modern humans display striking differences from the living apes in the realm of cognition and linguistic expression. In this article, we review the evolutionary changes that occurred in the descent of Homo sapiens by reconstructing the neural and cognitive traits that would have characterized the last common ancestor and comparing these with the modern human condition. The last common ancestor can be reconstructed to have had a brain of approximately 300–400 g that displayed several unique phylogenetic specializations of development, anatomical organization, and biochemical function. These neuroanatomical substrates contributed to the enhancement of behavioral flexibility and social cognition. With this evolutionary history as precursor, the modern human mind may be conceived as a mosaic of traits inherited from a common ancestry with our close relatives, along with the addition of evolutionary specializations within particular domains. These modern human-specific cognitive and linguistic adaptations appear to be correlated with enlargement of the neocortex and related structures. Accompanying this general neocortical expansion, certain higher-order unimodal and multimodal cortical areas have grown disproportionately relative to primary cortical areas. Anatomical and molecular changes have also been identified that might relate to the greater metabolic demand and enhanced synaptic plasticity of modern human brain's. Finally, the unique brain growth trajectory of modern humans has made a significant contribution to our species’ cognitive and linguistic abilities