腦科學研究常證明，人腦結構決定人的性格、才智等。這次牛津大學教授研究再指出，腦功能連結度緊密者，是一般認為比較聰明者、事業有成、生活令人稱羨，如字彙能力強、記憶力異於常人、對生活滿意度高、收入及教育程度佳等。這是常見的研究，記錄一個。
人生而不平等，在智力上也不平等，這是事實。宗教對這些不平等與天生不幸的事情先是亂解釋，然後再不負責任地推到無可驗證的死後公平解決。譬如基督宗教徒對於上帝給人自由，非常興奮地解釋並感謝上帝。但是對於上帝使人生而不平等與某些人生而不幸的事，又說與上帝無關。其實這類事實明顯指出，進化論最可能是人類起源的正確理論。教徒就是沒有獨立思考能力的人。
下為一則研究新聞，在英文原文下方還附有兩分多鐘的卡通片說明：
【 英國研究來了 易發怒者「大腦連結度弱」】
〔 蘋果日報 2015年09月30日04:52 〕
個人成就高低與腦部構造有關？英國科學家昨公布研究指，人的腦部網絡與其行為有驚人關聯，超強記憶力或體力等較優秀者，腦功能連結度強，具易發怒等負面特質的人則連結度弱。國內醫師昨肯定該研究證明神經學上的認知，但也指它忽略後天環境因素。
以牛津大學為首的英科學家，用「功能性核磁共振」掃描 461 名自願參與研究者的大腦，再分析其「腦功能連結圖譜」（神經元間的連結），與 280 項個人成就與行為特質的關聯。此研究昨發表在《自然神經科學》期刊。研究指出，腦功能連結度緊密者，是一般認為比較聰明者、事業有成、生活令人稱羨，如字彙能力強、記憶力異於常人、對生活滿意度高、收入及教育程度佳等；而連結度較鬆散者，多有負面特質，如行為衝動、易犯法、嗜嗑藥、抽菸或家族成員有酗酒歷史。
主導研究的牛津大學教授史密斯（Stephen Smith）稱，功能性核磁共振可看出腦細胞如何在大腦的
200 個功能區傳導訊息，特別是主管語言或學習等高層次認知功能的部位，這種「前所未見」的影像資料有助了解智能的本質。（石秀娟╱綜合外電報導）
下為牛津大學發佈的原文：
“Particular brain connections linked to
positive human traits
There is a strong correspondence between a particular set of connections in the
brain and positive lifestyle and behaviour traits, according to a new study
by Oxford University researchers.
A team of scientists led by the
University’s Centre for Functional MRI of the Brain has investigated the
connections in the brains of 461 people and compared them with 280 different
behavioural and demographic measures that were recorded for the same
participants. They found that variation in brain connectivity and an
individual’s traits lay on a single axis — where those with classically
positive lifestyles and behaviours had different connections to those with
classically negative ones. The findings are published in Nature Neuroscience.
The team used data from the Human
Connectome Project (HCP), a $30m brain imaging study funded by the US National
Institutes of Health and led by Washington, Minnesota and Oxford Universities.
The HCP is pairing up functional MRI scans of 1,200 healthy participants with
in-depth data gained from tests and questionnaires. “The quality of the imaging
data is really unprecedented,” explains Professor Stephen Smith, who was the
lead author of the paper. “Not only is the number of subjects we get to study
large, but the spatial and temporal resolution of the fMRI data is way ahead of
previous large datasets.” So far, data for 500 subjects have been released to
researchers for analysis.
The Oxford team took the data from 461 of
the scans and used it to create an averaged map of the brain’s processes across
the participants. “You can think of it as a population-average map of 200
regions across the brain that are functionally distinct from each other,”
explains Professor Smith. “Then, we looked at how much all of those regions
communicated with each other, in every participant.”
The result is a connectome for every
subject: a detailed description of how much those 200 separate brain regions
communicate with each other, which can be thought of as a map of the brain’s
strongest connections. The team then added the 280 different behavioural and
demographic measures for each subject and performed a ‘canonical correlation
analysis’ between the two data sets — a mathematical process that can unearth
relationships between the two large sets of complex variables.
They found one strong correlation that
relates specific variations in a subject’s connectome with their behavioural
and demographic measures. Interestingly, the correlation shows that those with
a connectome at one end of scale score highly on measures typically deemed to
be positive, such as vocabulary, memory, life satisfaction, income and years of
education. Meanwhile, those at the other end of the scale were found to exhibit
high scores for traits typically considered negative, such as anger,
rule-breaking, substance use and poor sleep quality.
The researchers point out that their
results resemble what psychologists refer to as the ‘general intelligence
g-factor’: a variable first proposed in 1904 that’s sometimes used to summarise
a person’s abilities at different cognitive tasks. While the new results
include many real-life measures not included in the g-factor — such as income
and life satisfaction, for instance — those such as memory, pattern recognition
and reading ability are strongly mirrored.
Proponents of the g-factor point out that
many intelligence-related measures are inter-related — suggesting that if
you’re good at one thing, you’re likely to be good at the others, too. However,
in the past, the g-factor has also received some criticism, partly because it
is not necessarily clear if these correlations between different cognitive
abilities are truly reflecting correlations between distinct underlying brain circuits.
The new results, however, may provide an opportunity to understand if that’s
correct, or if the processes in the brain tell a more complex story.
“It may be that with hundreds of different
brain circuits, the tests that are used to measure cognitive ability actually
make use of different sets of overlapping circuits,” explains Professor Smith.
“We hope that by looking at brain imaging data we’ll be able to relate
connections in the brain to the specific measures, and work out what these
kinds of test actually require the brain to do.”
The team will continue to pursue this
investigation as the set of Human Connectome Project data sets made available
to researchers increases.
A report of the research, entitled ‘A
positive-negative mode of population covariation links brain connectivity,
demographics and behavior ’ is published in Nature
Neuroscience. doi:10.1038/nn.4125
The work was supported by the US
National Institutes of Health and the Wellcome Trust.
You can learn more about the work of
MFRIB in this animation:
牛津大學校方發佈的新聞稿：
牛津大學功能性核磁共振中心
Oxford Centre for Functional MRI of the Brain 的網址：
美國國家衛生研究院網址：
“Nature” 學刊網址：
