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Recently, The Journal of Neuroscience published a research paper titled "Working Memory in Spatial Sequences: Developmental and Evolutionary Factors Coding Sequence and Relational Structures" as a cover article online
.
The research was completed by the Center for Excellence in Brain Science and Intelligent Technology of the Chinese Academy of Sciences (Institute of Neuroscience), the Shanghai Center for Brain Science and Brain-like Research, and the Wang Liping Research Group of the Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences
.
Through behavioral analysis and modeling, the study found that when adults, children and macaques completed the same spatial sequence task, there were not only differences in the accuracy of information encoding, but also differences in the processing methods of relational structures
.
Only human subjects, regardless of age, spontaneously extract abstract spatial relationships between consecutive items and use internalized language to compress sequence lengths in working memory
.
This study directly quantitatively assesses the relative contributions of development and evolution to human sequence representation, which will help scientists further understand and explore the uniqueness of human cognitive abilities such as language processing
.
Most human behavior, from eye movements, walking, dancing, vocalization, to abstract cultural creations—languages such as reading (natural language) and mathematics (formal language), are organized in sequential forms
.
On the long evolutionary road, the reason why humans have been able to create all kinds of languages shows that compared with those species that parted ways with humans in the middle, people have some key unique features in the representation and processing of sequence information
.
A simple hypothesis is that sequences are processed in the same way in humans and other species at different developmental stages, with differences only in degree of processing power, for example, differences in the precision with which information is encoded due to differences in working memory capacity
.
Another hypothesis contains more possibilities: Humans and other species have not only quantitative differences in their ability to process sequence information, but also qualitative differences at some levels
.
Among them, "super-regularity at the level of formal grammar constitutes a grammatical barrier between humans and other species" was a traditional hypothesis in the field, and the research paper published by Wang Liping's research group in Current Biology in 2018, through "time-lapse sequence" Generative task" challenges this hypothesis and proposes a new hypothesis of language evolution: some unique structure-sensitive algorithms used by humans in the process of sequence processing are more likely to be unique and key to human beings
.
Specifically, previous evidence suggests that instead of encoding individual items in a sequence, humans tend to spontaneously detect certain relational structures between items, thereby compressing them into fewer "chunks" ( chunk) to reduce the sequence length
.
Currently, it is unclear whether this ability is unique to humans
.
To test these hypotheses, the research team tested the sequence processing ability of adults, children (6-7 years old) and non-human primates (rhesus monkeys) through the same spatial sequence generation task
.
Several computational modeling and electrophysiological studies have previously found that the information of each memory item in a sequence can be split into two independent properties of the item (such as spatial location information in this study) and temporal order information.
components, perform conjunctive coding, which may be the basis for the brain to encode and maintain complete sequence information
.
The researchers then built a joint coding model to quantitatively evaluate the first hypothesis
.
The model can not only reflect behavioral indicators such as primacy-recency effect, permutation error rate gradient curve, etc.
, but also its fitting parameters can well explain the performance differences between subjects: the encoding accuracy of spatial location and temporal order is A major factor in poor performance in children and macaques, while macaques, even after long-term training, still show strategic constraints in redistributing the encoding resources for sequence information
.
In order to test the second hypothesis, the researchers classified all 360 sequences of length 4 according to the unified "pattern" after rigid body transformation such as rotation and mirror image, and obtained 30 relational structures
.
Taking the Gestalt principles further, by compressing items that are adjacent in sequence and location into the same chunk, the 30 patterns can be subdivided into 8 "chunk patterns"
.
Statistical analysis of the correctness and response times of these relational structures revealed that human subjects, regardless of age, spontaneously compressed sequence information using a common block strategy across different patterns, whereas macaque monkeys did not have this common feature
.
The researchers also added the chunking strategy to the original joint coding model, which explained the differences in the performance of the subjects at the relational structure level, and proved that the chunking strategy can indeed capture more differences by comparing with the model adding other alternative strategies.
.
Taken together, this work provides new insights into the origin and developmental evolution of human sequence processing capabilities through cross-species comparative studies, which will help pinpoint the uniqueness of human cognitive capabilities, including understanding, learning, and generating sequence information.
ability, and even the most important language processing ability
.
Relevant research work has been funded by the Chinese Academy of Sciences, Shanghai and the National Natural Science Foundation of China
.
Figure 1.
Journal cover showing evolution (top white, from macaques to humans) and development (bottom white, infant to adult) applied to sequence learning (number string 1-3-4-6-7-8) factor
.
Unlike macaques, humans, regardless of age, spontaneously extract relationships between consecutive numbers and use a chunking strategy to compress sequences in working memory.
Figure 2.
Schematic representation of the time-lapse sequence generation task
.
The subjects were required to memorize the spatial location and temporal sequence information of the target points during the stimulus presentation stage, and after a delay, they reported the sequence of presentation stages in turn.
Figure 3 Schematic diagram of the joint coding model
.
The model is divided into two stages: in the encoding stage, each target point in the sequence is split into independent distributions corresponding to position and order information, and a joint distribution is formed, and the joint distribution of all target points is finally weighted and averaged to become Mixed distribution is used to describe the overall coding strength of sequence information; in the retrieval stage, the mixed distribution is discretized and normalized into retrieval probability, so that the probability of any sequence that may be reported can be calculated
.
Among them, λ and κ control the encoding accuracy of order and position information, respectively, and the weight {wi} controls the relative encoding strength of the joint distribution of each target point.
Figure 4 (A) 360 sequences of length 4 (B) 30 A link to the article on the chart: http://
.
The research was completed by the Center for Excellence in Brain Science and Intelligent Technology of the Chinese Academy of Sciences (Institute of Neuroscience), the Shanghai Center for Brain Science and Brain-like Research, and the Wang Liping Research Group of the Key Laboratory of Primate Neurobiology, Chinese Academy of Sciences
.
Through behavioral analysis and modeling, the study found that when adults, children and macaques completed the same spatial sequence task, there were not only differences in the accuracy of information encoding, but also differences in the processing methods of relational structures
.
Only human subjects, regardless of age, spontaneously extract abstract spatial relationships between consecutive items and use internalized language to compress sequence lengths in working memory
.
This study directly quantitatively assesses the relative contributions of development and evolution to human sequence representation, which will help scientists further understand and explore the uniqueness of human cognitive abilities such as language processing
.
Most human behavior, from eye movements, walking, dancing, vocalization, to abstract cultural creations—languages such as reading (natural language) and mathematics (formal language), are organized in sequential forms
.
On the long evolutionary road, the reason why humans have been able to create all kinds of languages shows that compared with those species that parted ways with humans in the middle, people have some key unique features in the representation and processing of sequence information
.
A simple hypothesis is that sequences are processed in the same way in humans and other species at different developmental stages, with differences only in degree of processing power, for example, differences in the precision with which information is encoded due to differences in working memory capacity
.
Another hypothesis contains more possibilities: Humans and other species have not only quantitative differences in their ability to process sequence information, but also qualitative differences at some levels
.
Among them, "super-regularity at the level of formal grammar constitutes a grammatical barrier between humans and other species" was a traditional hypothesis in the field, and the research paper published by Wang Liping's research group in Current Biology in 2018, through "time-lapse sequence" Generative task" challenges this hypothesis and proposes a new hypothesis of language evolution: some unique structure-sensitive algorithms used by humans in the process of sequence processing are more likely to be unique and key to human beings
.
Specifically, previous evidence suggests that instead of encoding individual items in a sequence, humans tend to spontaneously detect certain relational structures between items, thereby compressing them into fewer "chunks" ( chunk) to reduce the sequence length
.
Currently, it is unclear whether this ability is unique to humans
.
To test these hypotheses, the research team tested the sequence processing ability of adults, children (6-7 years old) and non-human primates (rhesus monkeys) through the same spatial sequence generation task
.
Several computational modeling and electrophysiological studies have previously found that the information of each memory item in a sequence can be split into two independent properties of the item (such as spatial location information in this study) and temporal order information.
components, perform conjunctive coding, which may be the basis for the brain to encode and maintain complete sequence information
.
The researchers then built a joint coding model to quantitatively evaluate the first hypothesis
.
The model can not only reflect behavioral indicators such as primacy-recency effect, permutation error rate gradient curve, etc.
, but also its fitting parameters can well explain the performance differences between subjects: the encoding accuracy of spatial location and temporal order is A major factor in poor performance in children and macaques, while macaques, even after long-term training, still show strategic constraints in redistributing the encoding resources for sequence information
.
In order to test the second hypothesis, the researchers classified all 360 sequences of length 4 according to the unified "pattern" after rigid body transformation such as rotation and mirror image, and obtained 30 relational structures
.
Taking the Gestalt principles further, by compressing items that are adjacent in sequence and location into the same chunk, the 30 patterns can be subdivided into 8 "chunk patterns"
.
Statistical analysis of the correctness and response times of these relational structures revealed that human subjects, regardless of age, spontaneously compressed sequence information using a common block strategy across different patterns, whereas macaque monkeys did not have this common feature
.
The researchers also added the chunking strategy to the original joint coding model, which explained the differences in the performance of the subjects at the relational structure level, and proved that the chunking strategy can indeed capture more differences by comparing with the model adding other alternative strategies.
.
Taken together, this work provides new insights into the origin and developmental evolution of human sequence processing capabilities through cross-species comparative studies, which will help pinpoint the uniqueness of human cognitive capabilities, including understanding, learning, and generating sequence information.
ability, and even the most important language processing ability
.
Relevant research work has been funded by the Chinese Academy of Sciences, Shanghai and the National Natural Science Foundation of China
.
Figure 1.
Journal cover showing evolution (top white, from macaques to humans) and development (bottom white, infant to adult) applied to sequence learning (number string 1-3-4-6-7-8) factor
.
Unlike macaques, humans, regardless of age, spontaneously extract relationships between consecutive numbers and use a chunking strategy to compress sequences in working memory.
Figure 2.
Schematic representation of the time-lapse sequence generation task
.
The subjects were required to memorize the spatial location and temporal sequence information of the target points during the stimulus presentation stage, and after a delay, they reported the sequence of presentation stages in turn.
Figure 3 Schematic diagram of the joint coding model
.
The model is divided into two stages: in the encoding stage, each target point in the sequence is split into independent distributions corresponding to position and order information, and a joint distribution is formed, and the joint distribution of all target points is finally weighted and averaged to become Mixed distribution is used to describe the overall coding strength of sequence information; in the retrieval stage, the mixed distribution is discretized and normalized into retrieval probability, so that the probability of any sequence that may be reported can be calculated
.
Among them, λ and κ control the encoding accuracy of order and position information, respectively, and the weight {wi} controls the relative encoding strength of the joint distribution of each target point.
Figure 4 (A) 360 sequences of length 4 (B) 30 A link to the article on the chart: http://
