Summary: A new study goes beyond the conventional focus on specific brain regions like the cerebral cortex to examine how connections across the entire brain affect the development of human intelligence. Using imaging data from over 800 individuals, researchers analyzed contact between brain regions to identify smooth, crystallized, and public intelligence scores.
Results demonstrate that distributed brain-wide connections surpass traditional models that highlight localized regions in terms of importance. This study emphasizes that knowledge is a universal characteristic of the head, providing new insights into how to understand mental processes.
Important Information:
- World Mental House: Intelligence is influenced by connections distributed across the whole mind, not only specific regions.
- Forecast Intelligence Types: General knowledge was predicted best, followed by formed and smooth knowledge.
- Enhanced Models: Adding comparable connections to existing beliefs improved estimates, showing unknown aspects of intelligence.
Origin: University of Wurzburg
The mortal mind serves as our body’s central control unit. It processes visual details and enables us, among other things, to form ideas, make choices and keep understanding. It seems almost contradictory how much we are aware of how many our brains are capable of.
Jonas Thiele and Dr. Kirsten Hilger, head of the” Networks of Behavior and Cognition” research group at the Department of Psychology I at Julius-Maximilians-Universität Würzburg ( JMU), are among those who are on the trail of the most complex and complicated organ.
Their latest investigation was recently published in the medical journal , PNAS Nexus.
Predicting Intelligence from Brain Connections
The Human Connectome Project, a large-scale information sharing project based in the US, was the subject of the researchers ‘ use of data set. Over 800 people were examined using the aid of brain, an imaging technique that measures changes in brain action. both while they sat still and while carrying out different tasks.
The Würzburg-led team analyzed different connections to determine the level of communication between various brain regions and derived conclusions about specific intelligence scores based on these findings.
” Some studies have been published in recent years that have aimed to predict intelligence from mental contacts,” says Kirsten Hilger. The researchers have a deeper understanding, though, because the predictions are never as reliable as the knowledge test results.
So, we wanted to break away from the realm of purely mathematical intelligence predictions and concentrate on gaining a better understanding of the brain’s essential processes. We hope that this will help us understand how different individuals ‘ intelligences differ neurally.
Kirsten Hilger aspires that others will follow her example and that more research will be created in the future with an emphasis on accuracy in order to advance the conceptual understanding of human thinking.
Three Types of Intelligence
The team identified three different kinds of intelligence in their hypotheses: Smooth intelligence refers to the capacity to identify patterns and process new information independently of previously acquired knowledge or learned abilities.
The knowledge and skills that a man acquires over the course of their existence are referred to as formed knowledge. This includes basic expertise, experience and understanding of vocabulary and concepts. It arises through education and experience.
Collectively, these two types make up public knowledge. The best predicted performance was achieved with common knowledge, followed by formed and smooth intelligence.
Brain-wide Connections Best Identify Intelligence
Which several connections in the brain were examined according to a number of philosophical factors. In addition, arbitrarily selected links were likewise tested. One important finding: more important than the precise brain areas in which the individual links were located, the supply of contacts across the entire head as well as the true number of connections were most important for predicted performance.
The interoperability of the selected connections suggests that the entire head has a global intelligence profile. According to Hilger,” we were able to identify cleverness not just from a particular set of brain connections but also from various combinations of connections spread throughout the brain.”
Findings Outperform Established Theories
The results of the study support the idea that connections between further head regions are crucial for intelligence, contrary to popular theories of intelligence that frequently focus on particular areas of the brain, such as the cerebral cortex.
The most well-known cognitive models of intelligence’s suggested connections of mental regions produced better outcomes than arbitrarily selected connections. But, the results were even better when complement relationships were added”, reports Kirsten Hilger.
Nevertheless, this suggests that there are even more facets of knowledge that were previously believed that need to be understood in the near future.
About this information about science and intelligence
Author: Esther Knemeyer Pereira
Source: University of Wurzburg
Contact: Esther Knemeyer Pereira – University of Wurzburg
Image: The image is credited to Neuroscience News
Original Research: Start entry.
” Choosing argument over performance: Insight from appliance learning-based forecast of human knowledge from mental connectivity” by Kirsten Hilger et al. PNAS Nexus
Abstract
Choosing argument over efficiency: Insights from appliance learning-based prediction of human brains from brain connectivity
A growing body of research based on brain characteristics, including practical brain connectivity, to predict individual mental ability levels.
The majority of this study manages to perform statistically significant predictions, but it only provides a glimpse into the physiological mechanisms that underlie the concepts.
The inappropriate identification of predicted brain characteristics may be a significant factor that may be a significant contributor to this constraint.
In this context, we advise that forecast model studies be designed with an emphasis on accuracy in order to improve our philosophical understanding of human cognition.
As an example, we investigated in a preregistered study which functional brain connections successfully predict general, crystallized, and fluid intelligence in a sample of 806 healthy adults ( replication:  , N , = 322 ).
For a better understanding of knowledge at the neural level, the choice of the predicted cleverness component as well as the job during which connection was measured proved important.
Additionally, knowledge had been predicted not only from one particular set of brain connections, but from different combinations of connections with system-wide locations.
For half useless, brain-wide functional connection characteristics complement intelligence-relevant connectivity of brain regions proposed by recognized intelligence theories.
In summary, our study highlights how future prediction studies on human cognition can enhance explanatory value by placing a focus on a thorough analysis of predictive brain characteristics before maximizing prediction performance.
