insight - Computational neuroscience - # Mesoscale Functional Connectivity in Mouse Visual Cortex

Discrete Functional Channels Preserve Visual Information Across Mouse Primary and Higher Visual Cortices

Q: How do the discrete functional channels in the V1-HVA network emerge during development and learning

The emergence of discrete functional channels in the V1-HVA network during development and learning is a complex process that involves both genetic predisposition and experience-dependent plasticity. Initially, during early development, genetic factors play a significant role in establishing the basic wiring patterns between neurons in the visual cortex. For example, the axonal projections from V1 to HVAs are known to match the spatiotemporal preferences of the target HVAs, indicating a genetic predisposition for specific connectivity patterns. As the animal interacts with the environment and experiences visual stimuli, synaptic connections between neurons are refined and strengthened through activity-dependent mechanisms. Neurons that fire together in response to similar visual stimuli tend to wire together, leading to the formation of discrete functional channels. This process, known as Hebbian plasticity, reinforces connections between neurons that are co-active, while weakening connections between neurons that are not co-active. Furthermore, experience-dependent plasticity, such as visual learning tasks or exposure to specific visual stimuli, can further shape the functional connectivity within the V1-HVA network. Neurons that are repeatedly activated in response to certain visual features or patterns will develop stronger connections, leading to the formation of more specialized and discrete functional channels. Overall, the emergence of discrete functional channels in the V1-HVA network is a dynamic process that involves a combination of genetic predisposition and experience-dependent plasticity, ultimately leading to the precise and specialized organization of visual information processing in the brain.

Q: What are the potential computational advantages of having discrete functional channels versus a more mixed representation of visual information

Having discrete functional channels in the V1-HVA network offers several computational advantages over a more mixed representation of visual information. Efficient Information Processing: By segregating visual information into discrete channels based on specific features such as spatial frequency, temporal frequency, and orientation, the brain can process and analyze different aspects of visual stimuli in parallel. This specialization allows for more efficient and rapid processing of visual information, leading to quicker and more accurate responses to the environment. Noise Reduction: Discrete functional channels help to reduce noise and interference between different types of visual information. By keeping channels separate, the brain can maintain the fidelity of each type of visual information without mixing or distortion, leading to clearer and more reliable processing of visual stimuli. Selective Attention: Having discrete channels allows the brain to selectively attend to specific features or aspects of visual stimuli. This selective attention mechanism enables the brain to focus on relevant information while filtering out irrelevant or distracting inputs, enhancing cognitive performance and decision-making. Adaptability and Plasticity: The presence of discrete functional channels provides a flexible framework for the brain to adapt to changing environmental conditions or learning tasks. The ability to dynamically adjust the strength and connectivity of specific channels allows for rapid learning and adaptation to new visual stimuli or tasks. Overall, the organization of discrete functional channels in the V1-HVA network optimizes information processing, reduces noise, enables selective attention, and enhances adaptability and plasticity, providing computational advantages for efficient visual processing.

Q: How do the principles of discrete functional connectivity observed in the visual cortex apply to other sensory modalities or higher-order cognitive functions

The principles of discrete functional connectivity observed in the visual cortex can be extended to other sensory modalities and higher-order cognitive functions, highlighting the generalizability of these organizational principles in the brain. Auditory System: Similar to the visual cortex, the auditory system may also exhibit discrete functional channels for processing different frequencies, intensities, and spatial locations of sound. Neurons specialized for specific auditory features could form distinct channels to optimize sound processing and discrimination. Somatosensory System: In the somatosensory cortex, discrete functional channels could be organized based on tactile sensations, such as pressure, texture, and temperature. Neurons with specific receptive fields and tuning properties could form segregated channels for processing different aspects of touch and proprioception. Higher-order Cognitive Functions: In higher-order cognitive functions, such as memory, attention, and decision-making, discrete functional channels could represent specialized neural circuits for processing specific types of information. For example, memory encoding and retrieval processes may involve distinct channels for different types of memories (e.g., episodic, semantic). Motor System: In the motor cortex, discrete functional channels could be organized based on movement parameters, such as direction, speed, and force. Neurons with specific motor properties could form segregated channels for controlling different aspects of movement and coordination. By applying the concept of discrete functional connectivity to other sensory modalities and cognitive functions, researchers can gain insights into the organizational principles of neural circuits across different brain regions and functions. This approach can help uncover common computational strategies used by the brain to process and integrate information from diverse sensory inputs and cognitive processes.

Core Concepts

Neurons in mouse primary visual cortex (V1) and higher visual areas (HVAs) form discrete functional channels that preserve visual information, rather than mixing channels, as revealed by large-scale two-photon calcium imaging and noise correlation analysis.

Abstract

The study used large-scale two-photon calcium imaging to measure noise correlations (NCs) among thousands of neurons across mouse V1 and multiple HVAs. The authors found that:

Neurons can be classified into around 60 distinct tuning classes based on their responses to drifting gratings. These tuning classes can be further grouped into 6 broader spatial frequency (SF) and temporal frequency (TF) preference groups.
NCs are higher between neurons within the same tuning class, both within and across cortical areas, indicating the presence of discrete functional channels that preserve visual information.
The biases in SF-TF representation across HVAs are better explained by the number of high-NC neuron pairs within each tuning group, rather than the strength of the NCs.
NCs to different stimuli (drifting gratings vs. naturalistic videos) are more stable than the corresponding signal correlations, suggesting the NC-based functional connectivity reflects a fundamental aspect of the circuit architecture.
Computational modeling suggests that recurrent connectivity is critical for stabilizing the NC-based functional networks across stimuli.

Overall, the results demonstrate that the V1-HVA network is organized into discrete functional channels that preserve specific aspects of visual information, rather than mixing channels, at both the micron and millimeter length scales.

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Stats

"Neurons in HVAs (LM, AL, PM and LI) had significantly larger receptive fields than V1 neurons."
"The overlap of population receptive fields confirmed that simultaneously imaged cortical areas (V1 and HVAs), each containing ∼102 neurons, responded to stimuli in the same region of the stimulus display system."
"The population mean NC is always larger than control values (the NC after trial shuffling)."
"With the experimental size of the population (>100 neuron pairs), the estimation precision of the population mean NC surpasses the 0.01 level."
"Signal correlation is the most pronounced factor that explains about 10% of the variance of within-area NCs, and about 5% of the variance of inter-area NCs."
"About 10-20% of neuron pairs within each SF-TF group exhibited high NCs, in contrast to 5% for inter SF-TF group connections."

Quotes

"Neurons in all six groups exhibited orientation and direction selectivity. The preferred directions of neurons were evenly distributed in V1 and HVAs, except high SF groups (Group 3 and 6) of AL, PM, and LI biased to cardinal directions."
"Neurons tuned to high SF and low TF (Group 3) exhibited lower OSI in all tested areas than all of the other groups."
"Neurons tuned to high TF and medium-high SF (Groups 5 and 6) exhibited lower direction selectivity than other groups."

Key Insights Distilled From

Visual information is broadcast among cortical areas in discrete channels

by Yu,Y., Stirm... at www.biorxiv.org 11-14-2018

https://www.biorxiv.org/content/10.1101/469114v4

Deeper Inquiries

How do the discrete functional channels in the V1-HVA network emerge during development and learning

The emergence of discrete functional channels in the V1-HVA network during development and learning is a complex process that involves both genetic predisposition and experience-dependent plasticity. Initially, during early development, genetic factors play a significant role in establishing the basic wiring patterns between neurons in the visual cortex. For example, the axonal projections from V1 to HVAs are known to match the spatiotemporal preferences of the target HVAs, indicating a genetic predisposition for specific connectivity patterns.
As the animal interacts with the environment and experiences visual stimuli, synaptic connections between neurons are refined and strengthened through activity-dependent mechanisms. Neurons that fire together in response to similar visual stimuli tend to wire together, leading to the formation of discrete functional channels. This process, known as Hebbian plasticity, reinforces connections between neurons that are co-active, while weakening connections between neurons that are not co-active.
Furthermore, experience-dependent plasticity, such as visual learning tasks or exposure to specific visual stimuli, can further shape the functional connectivity within the V1-HVA network. Neurons that are repeatedly activated in response to certain visual features or patterns will develop stronger connections, leading to the formation of more specialized and discrete functional channels.
Overall, the emergence of discrete functional channels in the V1-HVA network is a dynamic process that involves a combination of genetic predisposition and experience-dependent plasticity, ultimately leading to the precise and specialized organization of visual information processing in the brain.

What are the potential computational advantages of having discrete functional channels versus a more mixed representation of visual information

Having discrete functional channels in the V1-HVA network offers several computational advantages over a more mixed representation of visual information.

Efficient Information Processing: By segregating visual information into discrete channels based on specific features such as spatial frequency, temporal frequency, and orientation, the brain can process and analyze different aspects of visual stimuli in parallel. This specialization allows for more efficient and rapid processing of visual information, leading to quicker and more accurate responses to the environment.

Noise Reduction: Discrete functional channels help to reduce noise and interference between different types of visual information. By keeping channels separate, the brain can maintain the fidelity of each type of visual information without mixing or distortion, leading to clearer and more reliable processing of visual stimuli.

Selective Attention: Having discrete channels allows the brain to selectively attend to specific features or aspects of visual stimuli. This selective attention mechanism enables the brain to focus on relevant information while filtering out irrelevant or distracting inputs, enhancing cognitive performance and decision-making.

Adaptability and Plasticity: The presence of discrete functional channels provides a flexible framework for the brain to adapt to changing environmental conditions or learning tasks. The ability to dynamically adjust the strength and connectivity of specific channels allows for rapid learning and adaptation to new visual stimuli or tasks.

Overall, the organization of discrete functional channels in the V1-HVA network optimizes information processing, reduces noise, enables selective attention, and enhances adaptability and plasticity, providing computational advantages for efficient visual processing.

How do the principles of discrete functional connectivity observed in the visual cortex apply to other sensory modalities or higher-order cognitive functions

The principles of discrete functional connectivity observed in the visual cortex can be extended to other sensory modalities and higher-order cognitive functions, highlighting the generalizability of these organizational principles in the brain.

Auditory System: Similar to the visual cortex, the auditory system may also exhibit discrete functional channels for processing different frequencies, intensities, and spatial locations of sound. Neurons specialized for specific auditory features could form distinct channels to optimize sound processing and discrimination.

Somatosensory System: In the somatosensory cortex, discrete functional channels could be organized based on tactile sensations, such as pressure, texture, and temperature. Neurons with specific receptive fields and tuning properties could form segregated channels for processing different aspects of touch and proprioception.

Higher-order Cognitive Functions: In higher-order cognitive functions, such as memory, attention, and decision-making, discrete functional channels could represent specialized neural circuits for processing specific types of information. For example, memory encoding and retrieval processes may involve distinct channels for different types of memories (e.g., episodic, semantic).

Motor System: In the motor cortex, discrete functional channels could be organized based on movement parameters, such as direction, speed, and force. Neurons with specific motor properties could form segregated channels for controlling different aspects of movement and coordination.

By applying the concept of discrete functional connectivity to other sensory modalities and cognitive functions, researchers can gain insights into the organizational principles of neural circuits across different brain regions and functions. This approach can help uncover common computational strategies used by the brain to process and integrate information from diverse sensory inputs and cognitive processes.