TC_Chu's Point

Brain Structure and Its Origins

2023-67

一整個月都在看這本書

有點無趣 都只是在講 誰接到誰 在接到誰 @@

A Browsable Petascale Reconstruction of the Human Cortex

BMM Summer Course 2021

iBeacon as Name Tag & Bag Tag

We can use iBeacon as name tag , so when group leader need to call people gather together he can use iPad or iPhone to tell who is nearby.

When travel in group, the guide will have to count people and bags every time. If we put a iBeacon for every people and bags, then in no time we can know what is missing.

by the way,

iBeacon as Dog tag is not bad. Maybe Cat tag. Since cat like to wondering around.

Neural ensemble

The concept of neural ensemble dates back to the work of Charles Sherrington who described the functioning of the CNS as the system of reflex arcs, each composed of interconnected excitatory and inhibitoryneurons. In Sherrington's scheme, α-motoneurons are the final common path of a number of neural circuits of different complexity: motoneurons integrate a large number of inputs and send their final output to muscles.

Donald Hebb theoretically developed the concept of neural ensemble in his famous book "The Organization of Behavior" (1949). He defined "cell assembly" as "a diffuse structure comprising cells in the cortex and diencephalon, capable of acting briefly as a closed system, delivering facilitation to other such systems". Hebb suggested that, depending on functional requirements, individual brain cells could participate in different cell assemblies and be involved in multiple computations.

In the 1980s, Apostolos Georgopoulos and his colleagues Ron Kettner, Andrew Schwartz, and Kenneth Johnson formulated a population vector hypothesis to explain how populations of motor cortex neurons encode movement direction. This hypothesis was based on the observation that individual neurons tended to discharge more for movements in particular directions, the so-called preferred directions for individual neurons. In the population vector model, individual neurons 'vote' for their preferred directions using their firing rate. The final vote is calculated by vectorial summation of individual preferred directions weighted by neuronal rates. This model proved to be successful in description of motor-cortex encoding of reach direction, and it was also capable to predict new effects. For example, Georgopoulos' population vector accurately described mental rotations made by the monkeys that were trained to translate locations of visual stimuli into spatially shifted locations of reach targets.

via Wiki

Canadian Scientists Create Virtual Human Brain

A large scale model of a human brain has been created by a team of scientists at the Centre for Theoretical Neuroscience, University of Waterloo, Ontario. This is a virtual model, inside a computer, that involves 2,5 million virtual neurons structures in a pattern resembling the overall human brain’s anatomy, including cortical regions, motor control regions, etc. There are two components of the model: Visual processing including input and visual memory, and motor control sufficient to make a relatively simple, but 3D, arm move so it can draw things. The brain is called Semantic Pointer Architecture Unified Network, or, rather creepily, “Spaun.”

http://scienceblogs.com/gregladen/2012/12/05/canadian-scientists-create-virtual-human-brain/

Long Term Memory Encoding in the Brain

Researchers may finally have uncovered the brain mechanism for storage of long term memories. It's long been suspected that synaptic connections between neurons were part of the mechanism. But somehow our memories survive while individual neurons die and are replaced. There's a new paper on the subject by Travis J. A. Craddock, Jack A. Tuszynski, and Stuart Hameroff, titled "Cytoskeletal Signaling: Is Memory Encoded in Microtubule Lattices by CaMKII Phosphorylation?" 

http://robots.net/article/3343.html

IBM's New Chips Compute More Like We Do

Inside the brain, information is processed in parallel, and computation and memory are entwined. Each neuron is connected to many others, and the strength of these connections changes constantly as the brain learns. These dynamics are thought to be crucial to learning and memory, and they are what the researchers sought to mimic in silicon. Conventional chips, by contrast, process one bit after another and shunt information between a discrete processor and memory components. The bigger a problem is, the larger the number of bits that must be shuffled around.

The IBM researchers have built and tested two demonstration chips that store and process information in a way that mimics a natural nervous system. The company says these early chips could be the building blocks for something much more ambitious: a computer the size of a shoebox that has about half the complexity of a human brain and consumes just one kilowatt of power. This is being developed with $21 million in funding from the Defense Advanced Research Projects Agency, in collaboration with several universities.

via MIT Technology Review

離開半導體業約10年 就這個消息最令人覺得興奮 希望能有更多這顆IC的資料!

More information from Engadget

數學如何塑造人腦

大腦中有一個特定的區域能讓人們估計數量級，讓他們對數和量有一種直覺。每個人的這個系統在敏感性上具有差異，這就影響到他們的數學學習。

6加7等於幾

如果讓一名小朋友做“6＋7＝？”這 道數學題，他會如何做計算？小孩子通常用到的方法有四種：掰手指、口頭數數、檢索記憶和分解。在一名兒童的成長過程中，他做加法運算時最早使用的方法是費 時費力的數數，之後則更多地借助於基於記憶的方法。這被神經科學家認為是人腦認知發展和學習的重要過程。

這個過程通常發生在大約7到9歲的年齡階段。美國斯坦福大學醫學院的維諾德‧米儂(Vinod Menon)教授及合作者在最近發表的一項研究中掃描了不同階段的兒童的大腦。

他們把讀二年級和三年級的小學生分成兩組，一組是那些依賴數數來做加法的兒童，另一組是依靠記憶的。然後，他們讓這些小學生計算一些數學題，同時用功能 性核磁共振(fMRI)查看他們的腦部活動情況。“我們想要知道隨著兒童對數學更加熟練，有了更多知識，他們的腦部活動會產生怎樣的變化。”米儂說。

他們發現，檢索法和數數法會引起截然不同的大腦活動模式，這種不同並不是參與記憶和數學計算的腦區中的腦波信號在強弱上的差異，而是不同的活動模式所指引下的截然不同的行為方式。

在另一項研究中，米儂等人從不同的學校裏找來90名兒童，其中一半剛剛完成二年級的學業，另一半剛剛完成三年級的學業。“令人驚訝的是，你會看到一年之 內發生的顯著變化。”米儂說。他們認為，比較短時間內的大腦活動的變化特別重要，因為此前的一些研究比較的是兒童和成人之間的變化，這些研究中遺漏很多人 腦在成熟過程中的變化細節。

“拋開個體差異，平均來說，一年的學習對大腦的功能和技能產生重大的影響。”米儂說。

這些不同年級的小學生在做數學計算的時候，活動的腦區並沒有發生改變，變化的是這些腦區對數學任務的響應方式。

在測試中，這些孩子的任務分為三種：復雜加法、簡單加法和對照測試。所謂“復雜加法”，是計算兩個2到9之間的整數的和(比如7＋2＝9)。“簡單加法”則是兩個數中有一個為“1”(比如5＋1＝6)。對照測試是讓他們判斷一個加法計算的結果是否正確。

米儂等人發現，三年級孩子的大腦對復雜加法和簡單加法做出的響應具有較大的差異。這些差異出現在與加法計算有關的兩個腦區——背外側前額葉和頂內溝，前者在大腦中負責操縱記憶，後者的作用是估計數量。

這些研究只是米儂所做的一係列相關研究中的兩個。他們的最終目標是，研究能夠幫助人們發展出更好的數學教育方法。

vi http://diyiat.blogspot.com

Untangling the brain - by Nature Video

Fly Over the “Brainbow”

Using a clever trick of genetic engineering, in which genes for three or more different fluorescent proteins were combined like paints to generate different hues, researchers created a system to make each neuron glow one of 100 different colors. The result was that the dendrites and axons of individual neurons, previously almost impossible to pick apart from their neighbors, could be traced through the mouse brain according to their color.

via MIT Technology Review

GALLERY: The Art of Neuroscience vol. III

We’re delighted to have some exclusive images from Jason Snyder’s microscope.  He has a sharp eye for the compelling, unusual forms of brain tissue and uses a beautiful array of staining techniques to highlight young neurons and answer questions relating to neurophysiological results of neurogenesis.

via thebeautifulbrain

'Brain recycling' puts kids' writing in a twist

Dehaene suggests that at birth, the VWFA responds to all visual information in both the normal and the mirror orientation. But as we learn to read and write, it is "recycled" – it "unlearns" the mirror form of words and letters, so that by adulthood it no longer responds to them.

via newscientist

小孩子學寫字時常會寫成鏡像字('d' ''b') 這邊的說法是說出生時大腦對字或是圖片的鏡像和不是鏡像都會嘗試讀取(有反應) 但是學習寫字之後大腦將能夠辨識鏡像的功能關閉(Un-Learn)