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Advances in Cognitive Sciences 2023, 25(2): 87-105 |
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Khodaei F, Sadati S H, Lashgari R. Local field potential activity in response to a black square stimulus in the primary visual cortex. Advances in Cognitive Sciences 2023; 25 (2) :87-105
URL: http://icssjournal.ir/article-1-1542-en.html
URL: http://icssjournal.ir/article-1-1542-en.html
1- Ph.D. Student, Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
2- Associate Professor, Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
3- Assistant Professor, Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
2- Associate Professor, Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
3- Assistant Professor, Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
Abstract: (543 Views)
Introduction
The cerebral cortex of mammals comprises six layersbetween the soft gray matter and the white brain's white matter. The thickness of its subgroups also varies in different cortex regions. The histology and distribution of dendrites and axons also show significant variations in different cortex regions. Three main thalamic pathways feed the primary visual cortex (V1) and have a unique position in receiving and distributing sensory input compared to other areas of the visual cortex. It plays a role as the first center for visual information processing in the cerebral cortex. The information that enters the visual cortex from the outside world includes complex visual scenes that need to be analyzed and broken down. Neurons in the primary visual cortex transmit information about the surrounding environment and visual stimuli to higher brain regions with great precision and detail. The type of stimulus significantly affects the information present in the output signal.
Local field potentials (LFPs) are electrical potentials generated by local electric charges distributed in an extracellular conducting medium. A better understanding of LFPs can be useful in the interpretation of non-invasive human studies such as functional magnetic resonance imaging (fMRI), oxygen-dependent signals, electroencephalography (EEG), and event-related potential (ERP) signals. Local field potentials may vary in different cortical areas and layers. Recent studies suggest that LFPs in high-frequency ranges may originate from a limited cortical area, contrary to previous assumptions. These signals are measured from local neuronal populations recorded by an extracellular electrode. Cortical LFPs are believed to bepredominantly generated by subthreshold membrane potentials in layers 2.3, 5, and 6. Recording LFPs is easier than spike activity and can be used in neural prostheses.
In 2015, a study was conducted on the columnar organization of the visual cortex in the spatial phase (19). Kozai et al. investigated methods and parameters for quantifying multi-unit recordings and local field potentials (20). Martin-Vazquez et al. analyzed independent components extracted from local field potential activity recorded during motor movement with rewards in multiple depths of the motor cortex to investigate their role in motor learning (21). An accurate understanding of the properties of local field potential signal responses in different layers of the cortex is crucial for future use of these signals in neural prosthetics (22). Although local field potential studies have recently received attention (23-27), there has yet to be a systematic study on the response properties of local field potentials and their relationship with neighboring neuron properties (12). The main goal of neuroscience is to understand how populations of neurons are organized in different cortical areas and layers.
In this study, the primary visual cortex of macaques was investigated. Local field potential responses were simultaneously evaluated in all cortical layers using a 24-channel electrode. By presenting a half-degree black square stimulus and recording the response signal, the response range in different layers was investigated, and the extent of visual spread was calculated using only one electrode instead of multiple electrodes. In addition, the peak and trough time and amplitude were examined to investigate the entry and exit of information.
Methods
Data Acquisition
The experiment was conducted on macaque monkeys, and the data were recorded at the Alessandra Angelucci Laboratory at the University of Utah. The raw signals were continuously recorded at a sampling rate of 30 kHz using a 128-channel system. It is common to filter the local field potential signals to highlight the desired activity (28). The effect of a low-pass filter on a completely inactive neuron depends on the distance between the soma and the input site and the membrane time constant. This indicates that dendritic morphology plays an essential role in frequency filtering and that pyramidal cells with their long dendrites are particularly affected by low-pass filters (29). Digital filters such as Gaussian filters (30), low-pass filters, Butterworth filters (30-34), and zero-phase filters (30) are used in the analysis of local field potential signals. The raw recorded voltages were filtered (1-100 Hz, second-order Butterworth filter) and sampled up to 2 kHz to obtain local field potentials.
Receptive Field Mapping
The receptive field of neurons in each column of the primary visual cortex was manually identified to determine their approximate locations. Subsequently, black squares measuring 0.5° were presented within the visual field spanning 3*3°, precisely in the approximate location of the receptive field. This process identified the exact location of the receptive field for neurons within the cortical column.
Visual Stimulus
Black squares measuring 0.5° were presented within a field of view spanning 3*3°. A 24-channel linear electrode with a contact distance of 100 micrometers and a contact diameter of 20 micrometers, specifically the V-Probe type manufactured by Plexon, Texas, was employed to record local field potentials. Each stimulus within the network of these 36 blocks was presented for 500 milliseconds. The experiment was repeated between 5 to 15 times to ensure reliability and gather sufficient data.
Results
Local field potential signals hold great significance in neurophysiology research and are instrumental in diagnosing neurological disorders and abnormalities within the human body. In this section, this study presents the investigation findings into the response of these signals in macaque monkeys to a visual stimulus presented in a 36-square grid.
Initially, the current study assessed the layers using current source density analysis. Subsequently, this research analyzed the Minimum Response Field (mRF) behavior pattern in different layers, along with the neighboring areas, utilizing the response range derived from the local field potential signal. This study focuses on analyzing the propagation of the local field potential signal. By identifying the peaks and troughs within different layers, the researchers further explore the timing and intensity of information entry and exit.
Given the pivotal role of local field potential signals in comprehending brain information at the cognitive level, it is crucial to study their spatial accuracy and gain a deeper understanding of how these signals are processed.
Figure 1. Local field potential response to visual stimulus presented at the minimum receptive field
Figure 1 (A) shows the current source density of local field potential at the minimum receptive field in the layers. The color corresponding to the sink and source is shown in the figure legend. The x-axis shows time, and the y-axis shows the depth of the cortex. Figure 1 (B) indicates the local field potential response at the minimum receptive field to the presented stimulus. The upper, middle, and deep layers are indicated in the Figure 1. The blue dashed line indicates the stimulus presentation time (0 milliseconds), and the pink dashed line demonstrated 50 milliseconds after the stimulus presentation.
Response Range
Calculating the peak and trough times and values were extracted by calculating the first and second derivatives and the sign of the local potential field signal. As can be seen, this parameter evaluates the distance between the minimum and maximum values of the local potential field signal in the range under investigation (0-200 milliseconds).
The response pattern is uniform in the minimum receiver field and its surrounding cells in the layers, and in the minimum receiver field, it has the maximum value in terms of range compared to its surrounding cells. As can be seen, as we move from the upper layers towards the middle layers, the response range decreases and then increases again upon reaching deeper layers. Based on the results of the Kruskal-Wallis statistical test on the investigation of the response range across layers for the minimum receiver field and the P-value obtained from this test, indicatively, a statistically significant difference was found in the response range component among primary visual cortex layers.
Visual Spread
How far can a local field potential signal spread around the recording site? Visual spread can describe this concept for us. In this section, this study investigated the visual spread layer using black square stimuli. Undeniably, various factors affect the development of visual spread. The noteworthy approach was to use a vertical electrode and move the location of the stimulus instead of the electrode location. The obtained results showed that layer 4C has the least visual spread among the layers, and this value increases, movingtowards the superficial and deep layers.
Signals have notable peaks in the upper and middle layers, while notable troughs were observed in the deeper layers. The value of the signal at the peak or notable trough within the range of 0 to 200 milliseconds, was chosen to calculate the visual spread of the signal. Clearly, this selection is related to peaks in the deeper layers and troughs in the upper layers.
Nauhaus et al. used a Gaussian function to approximate the exponential shape of the signal's inflection point (29). Katzner et al. fitted a Gaussian function to determine the orientation selectivity of stimuli in V1 (26). Xing et al. developed a method for estimating the spread of the signal with its domain at the peak of deviation (27). The current study used the domain of the signal at the peak of deviation, estimated the visual spread of local field potential signals within 0-200 milliseconds, and plotted the visual spread for all stimuli presented in all 36 networks. In calculating the degree of visual spread, this study only used one electrode, unlike previous studies that required simultaneous use of multiple electrodes.
Peak and trough time and amplitude.
To accurately examine the flow of information in response to the provided stimuli, it is crucial to analyze the peaks and troughs formed in the local field potential, serving as indicators of information-containing locations. By calculating the first and second derivatives and analyzing the local field potential signal sign, this study could extract the timing and values of the peaks and troughs.
Observing the line associated with the first trough, representing the primary sink, revealed a decrease as we moved from the upper layers to the middle layers, followed by an increase in the fifth layer and a subsequent decrease in the sixth layer. The lowest value was observed in the sixth layer, indicating that information enters the sixth layer first, then the middle layers, and finally, the upper and fifth layers.
The behavior of the secondary sink, represented by the second trough highlighted in bold pink in the figure, differed from that of the first trough. The flow of secondary information first occurs towards the upper and deeper layers and then towards the middle layers. In terms of value, the first trough exhibited the smallest magnitude. The second trough had negative values, while the first peak had positive values.
Statistical analysis using the Kruskal-Wallis test was performed on the data. The resulting P-values indicate a statistically significant difference among the layers, both regarding the timing and range of occurrence for the peaks and troughs.
Conclusion
This study investigated the effect of a black square stimulus presented in the primary visual area of a monkey using a multi-contact electrode. By analyzing the local field potential signals, this research examined several important aspects of the visual cortex, such as response range, visual extension, and peak and trough characteristics in different layers. The analysis of the response range revealed significant variations across layers. The highest amplitude was observed in the minimum receptive field, while the surrounding areas exhibited a similar pattern with a lower amplitude. This characteristic can be utilized to determine the location of the receptive field by examining the local field potential signals. The observed changes in the response range across different layers underscore the specialized role of each layer in extracting specific visual information.
The current study examined the extent of visual spread in different layers with its dependence on the location of stimulus presentation in a grid of 36 squares. By fitting a Gaussian function to the significant peaks or troughs observed in these 36 squares, this study could quantify the width of the Gaussian curve, which represents the degree of visual spread. Layer 4C, known for its limited visual spread, plays a crucial role in early visual processing tasks such as motion detection and spatial perception. Conversely, layers that exhibit a broader visual spread are involved in processing more intricate visual attributes, such as color and shape, with greater precision. These aspects could be explored in future studies focusing on these specific topics.
The troughs in the local field potential signal represent information entry, while the peaks signify information exit. The changes in polarity of the local field potential serve as an indicator of neural activity. To analyze the input and output of information, extracting the components associated with polarity and examining them across the cortical layers is necessary. By observing differences in the timing and magnitude of peaks and troughs across these layers, this study can gain insights into the flow of information between them. These observations highlight the intricate interplay of excitatory and inhibitory processes, as well as feedback mechanisms within the visual cortex.
This study significantly advances our understanding of the organization and functioning of the visual cortex, shedding light on unique characteristics exhibited by different layers. These findings contribute to a broader comprehension of the mechanisms involved in visual information processing. Utilizing local field potential signals extends beyond this study, encompassing applications in the implantation of brain-computer interface chips, neural prostheses, and the analysis of other signals, including electroencephalography signals. Furthermore, these signals are becoming increasingly prevalent in research and clinical settings, enabling investigations into a wide array of cortical and subcortical disorders, such as paralysis, epilepsy, and cognitive impairments.
Ethical Considerations
Compliance with ethical guidelines
All experiments were conducted following approved protocols by the Institutional Animal Care and Use Committee at the University of Utah and the guidelines of the NIH. The monkey was initially anesthetized with ketamine (25 mg/kg, intramuscularly) and then maintained under anesthesia with isoflurane (2%) during the procedure. Vital signs were monitored throughout the surgery, including body temperature, electrocardiogram, oxygen saturation, and blood pressure.
Authors' contributions
Funding
The authors declare they have not received any financial support for conducting this research.
Acknowledgments
The authors would like to express their sincere gratitude to the Alessandra Angelucci Laboratory for their assistance in conducting and improving the quality of this research.
Conflicts of interest
The authors declare no conflict of interest.
The cerebral cortex of mammals comprises six layersbetween the soft gray matter and the white brain's white matter. The thickness of its subgroups also varies in different cortex regions. The histology and distribution of dendrites and axons also show significant variations in different cortex regions. Three main thalamic pathways feed the primary visual cortex (V1) and have a unique position in receiving and distributing sensory input compared to other areas of the visual cortex. It plays a role as the first center for visual information processing in the cerebral cortex. The information that enters the visual cortex from the outside world includes complex visual scenes that need to be analyzed and broken down. Neurons in the primary visual cortex transmit information about the surrounding environment and visual stimuli to higher brain regions with great precision and detail. The type of stimulus significantly affects the information present in the output signal.
Local field potentials (LFPs) are electrical potentials generated by local electric charges distributed in an extracellular conducting medium. A better understanding of LFPs can be useful in the interpretation of non-invasive human studies such as functional magnetic resonance imaging (fMRI), oxygen-dependent signals, electroencephalography (EEG), and event-related potential (ERP) signals. Local field potentials may vary in different cortical areas and layers. Recent studies suggest that LFPs in high-frequency ranges may originate from a limited cortical area, contrary to previous assumptions. These signals are measured from local neuronal populations recorded by an extracellular electrode. Cortical LFPs are believed to bepredominantly generated by subthreshold membrane potentials in layers 2.3, 5, and 6. Recording LFPs is easier than spike activity and can be used in neural prostheses.
In 2015, a study was conducted on the columnar organization of the visual cortex in the spatial phase (19). Kozai et al. investigated methods and parameters for quantifying multi-unit recordings and local field potentials (20). Martin-Vazquez et al. analyzed independent components extracted from local field potential activity recorded during motor movement with rewards in multiple depths of the motor cortex to investigate their role in motor learning (21). An accurate understanding of the properties of local field potential signal responses in different layers of the cortex is crucial for future use of these signals in neural prosthetics (22). Although local field potential studies have recently received attention (23-27), there has yet to be a systematic study on the response properties of local field potentials and their relationship with neighboring neuron properties (12). The main goal of neuroscience is to understand how populations of neurons are organized in different cortical areas and layers.
In this study, the primary visual cortex of macaques was investigated. Local field potential responses were simultaneously evaluated in all cortical layers using a 24-channel electrode. By presenting a half-degree black square stimulus and recording the response signal, the response range in different layers was investigated, and the extent of visual spread was calculated using only one electrode instead of multiple electrodes. In addition, the peak and trough time and amplitude were examined to investigate the entry and exit of information.
Methods
Data Acquisition
The experiment was conducted on macaque monkeys, and the data were recorded at the Alessandra Angelucci Laboratory at the University of Utah. The raw signals were continuously recorded at a sampling rate of 30 kHz using a 128-channel system. It is common to filter the local field potential signals to highlight the desired activity (28). The effect of a low-pass filter on a completely inactive neuron depends on the distance between the soma and the input site and the membrane time constant. This indicates that dendritic morphology plays an essential role in frequency filtering and that pyramidal cells with their long dendrites are particularly affected by low-pass filters (29). Digital filters such as Gaussian filters (30), low-pass filters, Butterworth filters (30-34), and zero-phase filters (30) are used in the analysis of local field potential signals. The raw recorded voltages were filtered (1-100 Hz, second-order Butterworth filter) and sampled up to 2 kHz to obtain local field potentials.
Receptive Field Mapping
The receptive field of neurons in each column of the primary visual cortex was manually identified to determine their approximate locations. Subsequently, black squares measuring 0.5° were presented within the visual field spanning 3*3°, precisely in the approximate location of the receptive field. This process identified the exact location of the receptive field for neurons within the cortical column.
Visual Stimulus
Black squares measuring 0.5° were presented within a field of view spanning 3*3°. A 24-channel linear electrode with a contact distance of 100 micrometers and a contact diameter of 20 micrometers, specifically the V-Probe type manufactured by Plexon, Texas, was employed to record local field potentials. Each stimulus within the network of these 36 blocks was presented for 500 milliseconds. The experiment was repeated between 5 to 15 times to ensure reliability and gather sufficient data.
Results
Local field potential signals hold great significance in neurophysiology research and are instrumental in diagnosing neurological disorders and abnormalities within the human body. In this section, this study presents the investigation findings into the response of these signals in macaque monkeys to a visual stimulus presented in a 36-square grid.
Initially, the current study assessed the layers using current source density analysis. Subsequently, this research analyzed the Minimum Response Field (mRF) behavior pattern in different layers, along with the neighboring areas, utilizing the response range derived from the local field potential signal. This study focuses on analyzing the propagation of the local field potential signal. By identifying the peaks and troughs within different layers, the researchers further explore the timing and intensity of information entry and exit.
Given the pivotal role of local field potential signals in comprehending brain information at the cognitive level, it is crucial to study their spatial accuracy and gain a deeper understanding of how these signals are processed.
Figure 1. Local field potential response to visual stimulus presented at the minimum receptive field
Figure 1 (A) shows the current source density of local field potential at the minimum receptive field in the layers. The color corresponding to the sink and source is shown in the figure legend. The x-axis shows time, and the y-axis shows the depth of the cortex. Figure 1 (B) indicates the local field potential response at the minimum receptive field to the presented stimulus. The upper, middle, and deep layers are indicated in the Figure 1. The blue dashed line indicates the stimulus presentation time (0 milliseconds), and the pink dashed line demonstrated 50 milliseconds after the stimulus presentation.
Response Range
Calculating the peak and trough times and values were extracted by calculating the first and second derivatives and the sign of the local potential field signal. As can be seen, this parameter evaluates the distance between the minimum and maximum values of the local potential field signal in the range under investigation (0-200 milliseconds).
The response pattern is uniform in the minimum receiver field and its surrounding cells in the layers, and in the minimum receiver field, it has the maximum value in terms of range compared to its surrounding cells. As can be seen, as we move from the upper layers towards the middle layers, the response range decreases and then increases again upon reaching deeper layers. Based on the results of the Kruskal-Wallis statistical test on the investigation of the response range across layers for the minimum receiver field and the P-value obtained from this test, indicatively, a statistically significant difference was found in the response range component among primary visual cortex layers.
Visual Spread
How far can a local field potential signal spread around the recording site? Visual spread can describe this concept for us. In this section, this study investigated the visual spread layer using black square stimuli. Undeniably, various factors affect the development of visual spread. The noteworthy approach was to use a vertical electrode and move the location of the stimulus instead of the electrode location. The obtained results showed that layer 4C has the least visual spread among the layers, and this value increases, movingtowards the superficial and deep layers.
Signals have notable peaks in the upper and middle layers, while notable troughs were observed in the deeper layers. The value of the signal at the peak or notable trough within the range of 0 to 200 milliseconds, was chosen to calculate the visual spread of the signal. Clearly, this selection is related to peaks in the deeper layers and troughs in the upper layers.
Nauhaus et al. used a Gaussian function to approximate the exponential shape of the signal's inflection point (29). Katzner et al. fitted a Gaussian function to determine the orientation selectivity of stimuli in V1 (26). Xing et al. developed a method for estimating the spread of the signal with its domain at the peak of deviation (27). The current study used the domain of the signal at the peak of deviation, estimated the visual spread of local field potential signals within 0-200 milliseconds, and plotted the visual spread for all stimuli presented in all 36 networks. In calculating the degree of visual spread, this study only used one electrode, unlike previous studies that required simultaneous use of multiple electrodes.
Peak and trough time and amplitude.
To accurately examine the flow of information in response to the provided stimuli, it is crucial to analyze the peaks and troughs formed in the local field potential, serving as indicators of information-containing locations. By calculating the first and second derivatives and analyzing the local field potential signal sign, this study could extract the timing and values of the peaks and troughs.
Observing the line associated with the first trough, representing the primary sink, revealed a decrease as we moved from the upper layers to the middle layers, followed by an increase in the fifth layer and a subsequent decrease in the sixth layer. The lowest value was observed in the sixth layer, indicating that information enters the sixth layer first, then the middle layers, and finally, the upper and fifth layers.
The behavior of the secondary sink, represented by the second trough highlighted in bold pink in the figure, differed from that of the first trough. The flow of secondary information first occurs towards the upper and deeper layers and then towards the middle layers. In terms of value, the first trough exhibited the smallest magnitude. The second trough had negative values, while the first peak had positive values.
Statistical analysis using the Kruskal-Wallis test was performed on the data. The resulting P-values indicate a statistically significant difference among the layers, both regarding the timing and range of occurrence for the peaks and troughs.
Conclusion
This study investigated the effect of a black square stimulus presented in the primary visual area of a monkey using a multi-contact electrode. By analyzing the local field potential signals, this research examined several important aspects of the visual cortex, such as response range, visual extension, and peak and trough characteristics in different layers. The analysis of the response range revealed significant variations across layers. The highest amplitude was observed in the minimum receptive field, while the surrounding areas exhibited a similar pattern with a lower amplitude. This characteristic can be utilized to determine the location of the receptive field by examining the local field potential signals. The observed changes in the response range across different layers underscore the specialized role of each layer in extracting specific visual information.
The current study examined the extent of visual spread in different layers with its dependence on the location of stimulus presentation in a grid of 36 squares. By fitting a Gaussian function to the significant peaks or troughs observed in these 36 squares, this study could quantify the width of the Gaussian curve, which represents the degree of visual spread. Layer 4C, known for its limited visual spread, plays a crucial role in early visual processing tasks such as motion detection and spatial perception. Conversely, layers that exhibit a broader visual spread are involved in processing more intricate visual attributes, such as color and shape, with greater precision. These aspects could be explored in future studies focusing on these specific topics.
The troughs in the local field potential signal represent information entry, while the peaks signify information exit. The changes in polarity of the local field potential serve as an indicator of neural activity. To analyze the input and output of information, extracting the components associated with polarity and examining them across the cortical layers is necessary. By observing differences in the timing and magnitude of peaks and troughs across these layers, this study can gain insights into the flow of information between them. These observations highlight the intricate interplay of excitatory and inhibitory processes, as well as feedback mechanisms within the visual cortex.
This study significantly advances our understanding of the organization and functioning of the visual cortex, shedding light on unique characteristics exhibited by different layers. These findings contribute to a broader comprehension of the mechanisms involved in visual information processing. Utilizing local field potential signals extends beyond this study, encompassing applications in the implantation of brain-computer interface chips, neural prostheses, and the analysis of other signals, including electroencephalography signals. Furthermore, these signals are becoming increasingly prevalent in research and clinical settings, enabling investigations into a wide array of cortical and subcortical disorders, such as paralysis, epilepsy, and cognitive impairments.
Ethical Considerations
Compliance with ethical guidelines
All experiments were conducted following approved protocols by the Institutional Animal Care and Use Committee at the University of Utah and the guidelines of the NIH. The monkey was initially anesthetized with ketamine (25 mg/kg, intramuscularly) and then maintained under anesthesia with isoflurane (2%) during the procedure. Vital signs were monitored throughout the surgery, including body temperature, electrocardiogram, oxygen saturation, and blood pressure.
Authors' contributions
- Fereshteh Khodaei: Valuable assistance in analyzing and interpreting data, preparing a draft of the article, or reviewing and revising it.
- S.H. Sadati: Valuable assistance in analyzing and interpreting data, preparing a draft of the article or reviewing and revising it, approval of the final version for publication, responsiveness to all aspects of the research – Supervisor.
- Reza Lashgari: Valuable assistance in analyzing and interpreting data, preparing a draft of the article or reviewing and revising it; approval of the final version for publication, responsiveness to all aspects of the research – Supervisor.
Funding
The authors declare they have not received any financial support for conducting this research.
Acknowledgments
The authors would like to express their sincere gratitude to the Alessandra Angelucci Laboratory for their assistance in conducting and improving the quality of this research.
Conflicts of interest
The authors declare no conflict of interest.
Keywords: Local field potential, Primary visual cortex, Multi-contact electrode, Visual spread, Monkey
Type of Study: Research |
Received: 2023/04/30 | Accepted: 2023/05/6 | Published: 2023/09/20
Received: 2023/04/30 | Accepted: 2023/05/6 | Published: 2023/09/20
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