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Click the blue word to pay attention to the content that we need to remember in our daily life.
Most of the content collections are organized by a certain structure.
These collections may be composed of time or space sequences (for example, traffic lights appear alternately according to time), or they may be irregular.
, but with a sequence structure (such as phone number 589635)
.
This ability to encode sequence information is critical for cognitive learning, language processing
.
As early as 1950, the problem of sequence structure was identified by Karl Lashley as one of the urgent problems that should be solved in behavioral and neuroscience.
it
.
The brain encodes sequence structure information in two ways: first, independent modes: these sequence structures have independent representations; second, dissociation modes: the representations of these sequence information can be dissociated through different ordinal levels or time sequences
.
On February 11, 2022, Wang Liping's research group from the Center for Excellence in Brain Science and Intelligent Technology of the Chinese Academy of Sciences revealed the spatial geometric representation of sequential working memory in the neuron population of the lateral prefrontal cortex of macaque monkeys
.
The delay space sequence reproduction task experiment consists of two factors: sequence information (rank sequence 1 to 3) and spatial information, which can satisfy the research of the above dissociation model.
Three targets were presented in sequence, and after 2.
5 seconds to 4 seconds apart, the macaques needed to scan to the corresponding positions in the correct order
.
Figure 1: Calcium imaging technology dynamically monitors neuronal activity in the PFC region.
Using two-photon in vivo calcium imaging technology, the researchers dynamically recorded the activity of neurons in the lateral prefrontal cortex (LPFC) of two macaque monkeys in the delayed spatial sequence reproduction task experiment.
They found that Conjunctive neurons that respond selectively to positional and sequence information in the right experiment: both accurately to specific spatial positions, and to their ordinal (1st, 2nd, or 3rd) information in the sequence
.
To further evaluate whether the neuronal activity in the high-dimensional space of the LPFC brain region can reflect the representation of sequential working memory, they used spatial location and ordinal grade as variables (6 spatial locations × 3 grades to form 18 variables) Linear regression models were performed.
To fit the calcium ion signal changes, a vector representation of the state of the neuron population is obtained
.
Figure 2: The highly credible state-space representation of the sequence level space can well reflect the geometric features between different level subspaces and each level subspace
.
Based on this mathematical theory, they found that there are three two-dimensional subspaces in the three-level space, and these subspaces exist in the space of neuron group states in a vector-orthogonal manner
.
In addition, each hierarchical space forms a shared ring structure that resembles the spatial location of the ring distribution presented to macaques in the delayed-space sequence reproduction task experiments
.
When the macaques failed to correct their saccade positions during training, the ring became smaller or even non-existent
.
Different cognitive functions such as coordinate transformation, position anchoring, and attention are performed through classical gain regulation mechanisms
.
From the overall level, the geometrical features of the spatial information of the above neuron groups conform to the characteristics of the gain adjustment model, but not from the individual neuron level
.
This suggests that the integration of sequence information and spatial location information is achieved from the level of the entire neural population
.
In general, this paper reveals the "dissociation" mechanism of the sequence information stored in the cerebral cortex through a mathematical model: the high-dimensional space of neuron groups is reduced to a two-dimensional space, and each level in the coding sequence has a different and near-orthogonal Subspace information
.
[References] 1.
Geometry of sequence working memory in macaque prefrontal cortex2.
The Neural Representation of Sequences: From Transition Probabilities to Algebraic Patterns and Linguistic Trees.
Neuron 88, 2–19 (2015).
The pictures in the text are from the reference
Most of the content collections are organized by a certain structure.
These collections may be composed of time or space sequences (for example, traffic lights appear alternately according to time), or they may be irregular.
, but with a sequence structure (such as phone number 589635)
.
This ability to encode sequence information is critical for cognitive learning, language processing
.
As early as 1950, the problem of sequence structure was identified by Karl Lashley as one of the urgent problems that should be solved in behavioral and neuroscience.
it
.
The brain encodes sequence structure information in two ways: first, independent modes: these sequence structures have independent representations; second, dissociation modes: the representations of these sequence information can be dissociated through different ordinal levels or time sequences
.
On February 11, 2022, Wang Liping's research group from the Center for Excellence in Brain Science and Intelligent Technology of the Chinese Academy of Sciences revealed the spatial geometric representation of sequential working memory in the neuron population of the lateral prefrontal cortex of macaque monkeys
.
The delay space sequence reproduction task experiment consists of two factors: sequence information (rank sequence 1 to 3) and spatial information, which can satisfy the research of the above dissociation model.
Three targets were presented in sequence, and after 2.
5 seconds to 4 seconds apart, the macaques needed to scan to the corresponding positions in the correct order
.
Figure 1: Calcium imaging technology dynamically monitors neuronal activity in the PFC region.
Using two-photon in vivo calcium imaging technology, the researchers dynamically recorded the activity of neurons in the lateral prefrontal cortex (LPFC) of two macaque monkeys in the delayed spatial sequence reproduction task experiment.
They found that Conjunctive neurons that respond selectively to positional and sequence information in the right experiment: both accurately to specific spatial positions, and to their ordinal (1st, 2nd, or 3rd) information in the sequence
.
To further evaluate whether the neuronal activity in the high-dimensional space of the LPFC brain region can reflect the representation of sequential working memory, they used spatial location and ordinal grade as variables (6 spatial locations × 3 grades to form 18 variables) Linear regression models were performed.
To fit the calcium ion signal changes, a vector representation of the state of the neuron population is obtained
.
Figure 2: The highly credible state-space representation of the sequence level space can well reflect the geometric features between different level subspaces and each level subspace
.
Based on this mathematical theory, they found that there are three two-dimensional subspaces in the three-level space, and these subspaces exist in the space of neuron group states in a vector-orthogonal manner
.
In addition, each hierarchical space forms a shared ring structure that resembles the spatial location of the ring distribution presented to macaques in the delayed-space sequence reproduction task experiments
.
When the macaques failed to correct their saccade positions during training, the ring became smaller or even non-existent
.
Different cognitive functions such as coordinate transformation, position anchoring, and attention are performed through classical gain regulation mechanisms
.
From the overall level, the geometrical features of the spatial information of the above neuron groups conform to the characteristics of the gain adjustment model, but not from the individual neuron level
.
This suggests that the integration of sequence information and spatial location information is achieved from the level of the entire neural population
.
In general, this paper reveals the "dissociation" mechanism of the sequence information stored in the cerebral cortex through a mathematical model: the high-dimensional space of neuron groups is reduced to a two-dimensional space, and each level in the coding sequence has a different and near-orthogonal Subspace information
.
[References] 1.
Geometry of sequence working memory in macaque prefrontal cortex2.
The Neural Representation of Sequences: From Transition Probabilities to Algebraic Patterns and Linguistic Trees.
Neuron 88, 2–19 (2015).
The pictures in the text are from the reference
