The Relationship Between Brain Synchronization, Cooperation and Group Creativity

What's the science?

When people cooperate instead of compete, they are more likely to build on each other’s ideas and explore new ideas. Creativity in a group setting is important to produce original work, but how cooperation and competition can enhance or hinder group creativity is still unclear. The neural processes involved in a group’s creative performance also remain unclear. This week in Cerebral Cortex, Lu, Xue, and colleagues scanned the brains of two people simultaneously while they completed tasks in competitive or cooperative modes, and measured creative performance. Their goal was to understand which mode fosters group creativity and what brain regions are involved in this process (including how synchronous brain activity is between individuals in the group).

How did they do it?

The study included 104 young adults (64 women), and participants worked in pairs with other participants they did not know. Pairs of participants were randomly assigned to complete one of two tasks (the Alternative Uses task or the Object Characteristic task), and each pair completed their tasks in both cooperation and competition mode. In the Alternative Uses task, which measures divergent thinking, participants generate alternate uses for everyday objects. In the cooperation mode, participants were asked to cooperate with each other for better group performance, while in the competition mode, participants were told the other participant was their opponent and that the winner would be determined by comparing performance between the two participants. In the Object Characteristic task, participants thought of characteristics of everyday objects (testing their memory, but not divergent thinking). In this task, participants were similarly asked to perform the task in cooperation or competition mode. In both tasks, participants took turns stating their answers. Performance on the Alternative Uses task was quantified with the number and originality of the ideas generated, and performance on the Object Characteristic task was quantified based on the number of characteristics generated. The extent to which participants combined their ideas or thought of ideas in the same topic/category was also quantified as an index of cooperation. To measure brain activity during these tasks (while participants faced one another), the authors used functional near-infrared spectroscopy (fNIRS) – a technique in which sensors are placed on the scalp to detect changes in blood oxygenation in the brain. Probes that contained several measurement channels were placed over the prefrontal cortex and right temporoparietal junction (rTPJ), brain areas known to be involved in group creativity. Interpersonal brain synchronization was calculated as coherence between a given pair of measurement channels between two individuals. A frequency band of interest (0.042-0.045 Hz) was chosen as interpersonal brain synchronization increased during the Alternative Use task (compared to while at rest) in both the prefrontal cortex and rTPJ in this band.

What did they find?

Across tasks, the number of idea/characteristics generated by participants was greater in cooperation mode versus competition mode. Originality of ideas in the Alternative Uses task and a behavioural index of cooperation (both participants having ideas in the same category) were higher in cooperation mode. In the prefrontal cortex (right dorsolateral prefrontal cortex region), interpersonal brain synchronization was higher compared to baseline/rest in the Alternate Use task during the cooperation mode, but not in any other task or mode. Higher interpersonal brain synchronization predicted greater cooperation. In the rTPJ, interpersonal brain synchronization was greater during the Alternative Use task versus the Object Characteristic Task, particularly during cooperation mode. Finally, interpersonal brain synchronization between the prefrontal cortex and rTPJ was also higher in the Alternative Uses task in the cooperation mode versus in the competition mode.

What's the impact?

This study found that group creativity was greater when individuals cooperate to complete a task, and that brain synchronization between individuals predicts the level of cooperation on the task. These results have implications for understanding how creativity is cultivated in a group setting. Greater brain synchrony between people was associated with greater cooperation, suggesting that greater synchrony is indicative of better interpersonal interaction.

Lu et al., Cooperation Makes a Group be More Creative. Cerebral Cortex (2018). Access the original scientific publication here.

The ‘Rosehip Cell’: A GABAergic Neuron

What's the science?

A critical goal of neuroscience is to understand the types of cells that make up the brain. Typically, novel cell types have been identified by studying the expression of molecular markers in different cells, and then confirming that the cell appears to have a distinct pattern of morphology of its axon and dendrites (the main processes attached to the cell body of a neuron). Essentially, researchers try to determine the relationship between genotype and phenotype. Some cell types are conserved across species, so a large portion of this type of research is done in rats and also applies to humans. However, not every cell type is conserved across species, so doing research in humans is important too. This week in Nature Neuroscience, Boldog and colleagues study molecular expression of different brain cells and characterize neuron morphology in humans.

How did they do it?

The authors first used single nucleus transcriptomics or RNA sequencing in two healthy post-mortem human brains. This method involves dissecting regions of interest from the cortex, isolating cell nuclei using tissue homogenization, and staining to identify neuronal (NeuN+) and non-neuronal (NeuN-) cells. The region of interest within the cortex was layer 1 of the middle temporal gyrus, which contains mostly inhibitory neurons. The resulting nuclei were then grouped using a clustering method according to the similarity of their transcriptional profiles.

To establish cell morphology, the authors identified interneurons in layer 1 in brain slices prepared from the parietal, temporal, and frontal cortices of 42 patients. Whole-cell recording and light microscopy of the cells was performed. Finally, they authors performed immunohistochemistry on the cells for which morphology was examined to test whether these cells were positive for gene markers indicative of different identified clusters (of gene markers).

What did they find?

Using single nucleus transcriptomics, on average 9937 genes were detected in neurons and 6287 genes were detected in glia (non-neuronal cells). When cells with similar transcriptional profiles were grouped together, different cell types (e.g. oligodendrocytes, microglia, astrocytes, excitatory neurons) were clustered with other cells of the same type as expected. Surprisingly, 11 different clusters of GABAergic or inhibitory neurons were identified within layer 1 of the middle temporal gyrus (however, this doesn’t mean that neurons belonging to these clusters wouldn’t also appear in other layers of the cortex). Different cell types could be identified by different marker genes – for example, GABAergic neurons were identified by the expression of glutamic acid decarboxylase 1 (GAD1). 

Using light microscopy of layer 1 interneurons, the authors identified subsets of cells that had been previously described, as well as a novel type of interneuron, newly named the ‘rosehip cell’ for its rosehip-shaped axonal boutons (terminals of an axon). The shape of the dendrites of these neurons were relatively short and bushy. These neurons tended to have the same number of dendrites as basket cells but fewer than neurogliaform cells (two other brain cell types). Dendrites were, however, smaller and less frequent in rosehip cells compared to basket cells. The rosehip cell dendrites were also found to branch more frequently than other cell types, with large boutons. When immunohistochemistry was performed, it was found that the rosehip neurons matched a previously identified cluster of inhibitory neurons with unique transcriptional features. Notably, this cluster was associated with genes involved in axon growth and structure of the synapse, indicating these genes could have contributed to its unique shape. When the electrophysiology of these neurons was examined, they were found to be tuned to beta and gamma frequencies with variable interspike intervals (active and silent periods). The authors also noted which cells partnered with the rosehip cells. Rosehip cells predominantly formed synapses with layer 3 pyramidal cells. Calcium signalling was suppressed upon rosehip cell input to pyramidal cells in some cases, indicating that these cells may be involved in calcium signalling of human pyramidal cells.

What's the impact?

This is the first study to identify transcriptional and morphological characteristics of a unique group of interneuron cells in layer 1 of the human cortex. These new cells are called ‘rosehip cells’ for the shape of their axonal boutons. The identification of this new type of inhibitory cell is groundbreaking because it could lead to significant advances in our understanding of the brain’s circuitry.

Boldog et al., Transcriptomic and morphophysiological evidence for a specialized human cortical GABAergic cell type. Nature Neuroscience (2018). Access the original scientific publication here.

Mapping Subjective Feelings

What's the science?

Subjective feelings are central to everyday human life from forgetfulness to feeling ill or having a good day with a friend. Subjective feeling is the current subjective phenomenological state of an individual. We currently do not have a clear understanding of the organization of inner feelings and where they can be mapped in the body or brain, despite how subjective feelings underlie most aspects of everyday life. Recently in PNAS, Nummenmaa and colleagues generate a map of different subjective feelings using subjective reports of feelings, bodily sensations and neuroimaging data associated with these feelings.

How did they do it?

1026 participants were interviewed and rated 100 subjective “feeling states” ranging from physiological sensations like hunger, to emotional and cognitive feelings like a pleasurable experience or the feeling of trying to remember something. They rated the intensity of these feelings in 4 dimensions 1) the mental experience 2) the bodily sensations associated with these feelings 3) the emotional contribution and 4) the level of control they had associated with these feelings. Participants were shown tokens associated with feelings as a list on a screen and were asked to arrange these feeling states in a box based on their similarity to one another. They were then asked to color on an image of the body where they felt a particular feeling state. They authors assessed how similar these feelings were to one another, how they map out topographically and onto the body, and lastly whether they were associated with patterns of brain activity using neuroimaging data (NeuroSynth: a database of brain activity studies and their associated topics). They performed a “representational similarity analysis” to determine how similar these feeling, body and brain maps were to one another.

What did they find?

The intensity of the mental experiences and bodily sensations associated with subjective feeling states were highly correlated. Almost all subjective feelings were associated with emotion. Less control was felt for unpleasant feelings than for pleasant feelings and for bodily states than cognitive/ mental states. Based on the rating of similarity between feelings, the authors created topographical map of the mental feeling space. Used density-based clustering they found 5 distinct clusters which included positive emotion, negative emotion, cognitive states, somatic states/illnesses and homeostatic states. They then used t-distributed stochastic neighbor embedding to determine how these clusters differed in the 4 dimensions of feeling. Mental involvement and positive vs. negative valence of a feeling were the most important dimensions. Negative and positive emotions were both mapped highly on the vertical scale of mental intensity, demonstrating that the more intense the emotion, the more strongly it is experienced in the mind. On the horizontal scale of emotional intensity, positive and negative emotions mapped on opposite ends of the spectrum. Homeostatic states (like eating), illnesses and cognitive states (like reasoning) were lower on the scale of mental intensity, demonstrating that they are experienced to a weaker degree in the mind. Cognitive processes were mapped towards the positive end of the spectrum of emotion, while illnesses are experienced as negative. Greater control (agency) was felt over positive feelings and cognitive processes, while less control was felt over negative feelings and illnesses.

All feeling states were associated with distinct bodily sensation maps, even for cognitive processes like remembering or reasoning. This mapping of feeling state onto body regions also clustered in a similar way demonstrating a similar organization of feeling states in the body. Lastly, they found that the organization of bodily feeling was associated with the mapping of subjective feelings based on brain activation. This neural organization of feeling states was also associated with the semantic similarity (from words associated with brain activity recorded in the NeuroSynth database). This suggests that there are neural signatures of subjectively felt bodily states associated with feelings. The subjective experience of mental states, however, was not associated with patterns of brain activation.

What's the impact?

This is the first study to map subjective feelings in terms of their subjective experience, their bodily sensations and their location in the brain. We now know that subjective feelings cluster into different types of feelings and that these correspond to distinct maps on the body. These patterns of bodily sensation also map onto brain activity associated with particular feelings. Understanding how we feel things is important for everyday life and for understanding the human experience.

Nummenmaa et al., Maps of subjective feelings. PNAS (2018). Access the original scientific publication here.